We aim at exposing Brazilian students to discussions on the state-of-the-art concepts of immunology and their application to the understanding of chronic diseases, either infectious or noncommunicable diseases, and in the implementation of prophylactic and therapeutic interventions. The course is divided into 4 one-week courses, that could be attended independently and will be delivered simultaneously to Paris and New York, via videoconference. All students and the responsible for the course will meet and attend to the course (so it is a presential course) which will be transmitted online simultaneously to S_o Paulo, Paris and New York. The responsible for the course will mediate discussions with the students at the end of every videoconference session. The discussion will serve as evaluation of active participation of the students by the responsible for the course. This course is an initiative from USP International Office and is part of an active strategy to foster international collaborations between USP and the Sorbonne University (Universit_ Pierre et Marie Curie). This is a pilot project; the course may be repeated in the future, depending on the results achieved. Medical School (FM) São Paulo, Pinheiros campus Human Immunodeficiency Virus, Flu viruses, Dengue, Malaria, Tuberculosis, Chagas disease, Ebola, Chikungunya, Shigella; vaccination to Streptococcal pneumonias and development of vaccines for rheumatic fever Roger Chammas 20 MCM5920 2 Participation in seminars http://www.fm.usp.br/en/portal/

We aim at exposing Brazilian students to discussions on the state-of-the- art concepts of immunology and their application to the understanding of chronic diseases, either infectious or noncommunicable diseases, and in the implementation of prophylactic and therapeutic interventions. The course is divided into 4 one-week courses, that could be attended independently and will be delivered simultaneously to Paris and New York, via videoconference. All students and the responsible for the course will meet and attend to the course (so it is a presential course) which will be transmitted online simultaneously to S_o Paulo, Paris and New York. The responsible for the course will mediate discussions with the students at the end of every videoconference session. The discussion will serve as evaluation of active participation of the students by the responsible for the course. This course is an initiative from USP International Office and is part of an active strategy to foster international collaborations between USP and the Sorbonne University (Universit_ Pierre et Marie Curie. This is a pilot project; the course may be repeated in the future, depending on the results achieved. Medical School (FM) São Paulo, Pinheiros campus Inflammatory bowel disease, psoriais, rheumatoid arthritis, diabetes, atherosclerosis, allergic diseases na ashma, rheumatic fever. Roger Chammas 20 MCM5921 2 http://www.fm.usp.br/en/portal/

Stochastic processes are natural models for phenomena occurring in time and for spatial systems. Modeling natural phenomena using stochastic processes requires the knowledge of specific inferential and statistical model selection tools. Moreover, stochastic processes have also been used as computational tools in statistical inference, as exemplified by Monte-Carlo Markov chain algorithms for sampling probability distributions. To present basic notions of statistical inference for some important classes of stochastic processes. Institute of Mathematics ans Statistics (IME) São Paulo main campus 1) Statistical inference for Markov chains. Maximum likelihood estimation. Estimation of the order of the chain. 2) Statistical inference for stochastic chains with memory of variable length. The algorithm Context. 3) Context tree selection using the Bayesian Information Criterion (BIC). The algorithm_CTW. 4) Statistical inference for hidden Markov models. 5) Gibbs states. Interaction graph selection and maximum likelihood estimation for the_Ising_model. 6) Simulations using Monte-Carlo Markov chains (MCMC)._Glauber_dynamics, Gibbs sampler, Metropolis algorithm. 7) Perfect simulation algorithms. Jefferson Antonio Galves, Florencia Graciela Leonardi 40 MAE5741 8 Students will be evaluated through projects, seminars, exercise lists and write tests, https://www.ime.usp.br/en

The general treatment of Probability Theory requires its formulation in abstract spaces, in the framework introduced by Kolmogorov. Introduce the basics of Probability Theory into abstract spaces, including the necessary elements of Measure Theory, in the framework formulated by Kolmogorov. Institute of Mathematics ans Statistics (IME) São Paulo main campus 1. Probability Spaces: (a) Lebesgue-Stieltjes Measure, Carath_dory Extension Theorem; (b) Measures of Probability, Random Variables; (c) Integration, Expectation, Convergence Theorems; (d) Product measures, Fubini’s theorem; (e) Independence; (f) Kolmogorov Extension Theorem; (g) Radon-Nikodym Theorem, Conditional Expectation. 2. Laws of Large Numbers: (a) Convergence in Probability and Almost Sure Convergence; (b) Weak Law of Large Numbers; (c) Borel-Cantelli lemmas; (d) Strong Law of Large Numbers. 3. Central Limit Theorem: (a) Convergence in Distribution; (b) Characteristic Functions; (c) TLC for Random Variables I.I.D; (d) TLC for Triangular Arrangements. Vladimir Belitsky, Miguel Natalio Abadi, Anatoli Iambartsev 50 MAE5811 8 Exam and exercises, with the possibility of collecting an article at the end of the course. https://www.ime.usp.br/en

The formal study of the asymptotic properties of estimators and test statistics is fundamental to understand and propose modern statistical methods. To discuss formally asymptotic theory of statistical methods. Institute of Mathematics ans Statistics (IME) São Paulo main campus 1. Order of magnitudes and Taylor series. 2. Weak and strong convergence laws of the estimators. Univariate and multivariate cases. Slutsky’s Theorem. 3. Central limit Theorems _ Univariate, Multivariate and Martingales. Cram_r-Wold’s Theorem. Hajek-Sidak’ s Theorem and applications to regression models. Delta method and variance stabilizing transformations. 4. Asymptotic expansions. 5. Applications. Antonio Carlos Pedroso de Lima, Alexandre Galv_o Patriota 50 MAE5835 8 Exams, Worksheets and Seminars https://www.ime.usp.br/en

The correct application of selection approaches for superior genotypes is directly dependent of the chromosome behavior during the process of cell division – mitosis and meiosis. Moreover, cytogenetics is the connection between the molecular level (genomics and epigenetics) and phenotypic level (from individual to biosystems). Cytogenetics by itself is the phenotypic expression of the genome organization and its epigenetic indexing. The evolutionary machinary acts directly in the genome organization promoting changes in the structure, behavior and the number of genes, with direct consequences to phenotype and thus, to germplasm manipulation. The cytogenetic knowledge is an important and indispensable tool for General Biology, with direct applications to Plant Breeding, Biotechnology and Biodiversity conservation, exploration and prospection. Basic concepts of Cytogenetics applied to plant breeding are presented and their implications to genomics, epigenomics, evolution, systematic, biotechnology and ecology, covering: 1) Introduction to Cytogentics; 2) Introduction to genome organization, chromatin epigenetics and chromosome structure (DNA sequences and chromosomal proteins – histone and non-histone proteins); 3) mitotic behaviour and biotechnology applications; 4) meiotic behavior and applications to plant breeding; 5) Cytological and molecular principles of genetic mapping; 6)Structural and numerical chromosomal alterations, mechanism of origin and consequences; 7) Importance of the chromosomal alterations to evolution and gene mapping into the chromosomes; 8) Recombination mechanisms, meiotic behavior and genetic mapping in polyploid species (cytogenetic principles); 9) variant chromosomal systems from parthenogenesis and apomixis Luiz de Queiroz College of Agriculture (ESALQ) Piracicaba campus – Introduction to Cytogenetics. General overview of chromosomes behavior during cell cycles – mitosis and meiosis, chromatin strcuture and molecular organization of the chromosomes. Introduction to epigenetic indexing mechanism. – Meiotic behavior. Meiosis and recombination, linkage and crossing-over. Genetic and Cytological Maps. Genetic mapping approaches in plant and animals. Meiotic instabilities and their consequences to fertility. – Alterations in chromosome structure – deficiencies/deletions, duplications, inversions and translocations. Origin, phenotypic effects, meiotic behavior and its genetic consequences. Segmental Genome Duplication (SGD) – Alterations in chromosome numbers – aneuploidy, autopolyploidy and allopolyploidy. Origin and genetic consequences. Importance in the evolution and for breeding. Aneuploidy applied to genetic mapping. – Whole Genome Duplication (WGD) and types of poliploidy. Artificial polyploids. Gene expression and silencing in polyploids. Gene expression and epigentic alterations as consequences of genome duplication. – Diversity in reproductive systems, parthenogenesis and apomixis. Cytogenetics, Evolution and Biotechnology. Study of cases covering the main subjects. Practicals: chromosome analysis in plant and animals. Chiasma and meiotic instability analysis in maize. Chromosomal alterations in plants. Physical mapping of ribosomal genes by Fluorescent Molecular in situ Hybridization. Immunodetection of chromosomal proteins and DNA methylation. Introduction to bioinformatic applied to cytogenetics. Mateus Mondin 70 LGN5703 8 Seminar presentations and bibliographic review. Theoretical exams. Analysis of practical exercises. http://pt.esalq.usp.br/

The aim of this course is to provide the students’ knowledge and training in genetics and breeding of allogamous (cross-fertilized) crop species, including annual, semi-perennial, and perennial crop species. Thus, this course is directed to the students that intend to develop both basic, as the study of the genetic structure of populations and statistical-genetic designs, and applied research, as the study of the selection methods for the development and improvement of cultivars. It is the only course in this post-graduate program that addresses the subjects related to the breeding and genetics of allogamous crop species. Therefore, for this program, this course could be deemed of paramount importance for those students that intend to carry out research in genetics and/or plant breeding programs of allogamous crops in public or private institutions. Luiz de Queiroz College of Agriculture (ESALQ) Piracicaba campus Genetic structure of allogamous species. Population effective size. Conservation of the accesses of germplasm banks. Covariance of relatives at intra- and interpopulation levels. Components of the genetic variance for populations at any level of inbreeding. Heterosis and inbreeding depression. Selection of parents for the development of reference populations. Responses to selection at intra- and interpopulation methods. Effects of the genetic drift and the inbreeding depression in response to selection. Changes in the heterosis and the inbreeding depression through selection. Theoretical responses to intra- and interpopulation recurrent selection. Comparison of the selection methods for perennial, semi-perennial, annual crop species, and asexual reproduction plant species. Recurrent selection, early selection, selection index, and observations repeated in temporal times. Responses to selection under abiotic stressed environments. Correlated responses to selection under any level of inbreeding. Molecular markers and plant breeding: backcross assisted selection; development of heterotic groups; hybrid prediction; genome-wide selection. Roberto Fritsche Neto 23 LGN5825 8 02 Written tests, participation during classes and weekly exercises in R. http://pt.esalq.usp.br/

Genome sequencing of domestic animals and advances in quantitative genetics have enable new approaches in animal breeding. This course will talk about recent advances in the area of quantitative genetics and genomics and the aplications in beef cattle breeding. The course will have the contribution of especialists in different areas. Provide the principles of quantitative genetics aplied to genome selection and genomics, so the students can understand a contribute to the development of this new area. Luiz de Queiroz College of Agriculture (ESALQ) Piracicaba campus The U.S. Beef Industry: Structure and Current Genetic Selection Programs; Priors in the Bayesian Alphabet; Developing Genomic Predictions: Training and Evaluation; Additive genomic relationship matrix and GBLUP; Haplotype-based models: BayesIM; Interpreting “genomic correlations” and pleiotropy; Tour of Genomics Center; Population structure in admixed populations; Reproducing kernel Hilbert spaces regression; GO enrichment analysis; MeSH enrichment analysis; GO / MeSH enrichment analysis in Bioconductor Luiz Lehmann Coutinho, Gerson Barreto Mour_o 75 LZT5869 4 University of Sao Paulo,Universidade de Campinas and Universidade Estadual Paulista Student participation and Exam. http://pt.esalq.usp.br/

The joint development of areas such as discrete mathematics, probability, operational research and computer theory is continuous and relevant. The solution of theoretical and applied problems in these areas can be given in terms of a probabilistic modeling that arises from physics as well as the analysis of engineering systems or areas such as economics, biology, engineering, neuroscience. The tools used in such modeling include Markov chains, martingales, stochastic optimization, coupling and combinatorics. Introduce and apply probability topics such as Markov chains, coupling and Poisson approaches through concrete examples such as those from the stochastic models for information theory, engineering, combinatorics, biology, neuroscience and other areas of application of Probability and Stochastic Processes. Institute of Mathematics ans Statistics (IME) São Paulo main campus 1. Discrete Probability Models; 2. Markov chains; 3. Recurrence and ergodicity; 4. Coupling and limiting behavior; 5. Martingales; 6. Renewal processes; 7. Contemporary Topics: Variable Range, Poisson Approximations, Reliability Theory, and Queue Theory Fabio Prates Machado, Luiz Renato Goncalves Fontes, Miguel Natalio Abadi 50 MAE5703 8 The evaluation will consist of the score’s average of tests and lists of exercises. https://www.ime.usp.br/en

Exploratory data analysis and computational techiques are fundamental to understand modern modern statistical methods. Introduce modern techniques of data analysis with concomitant using of computer. Using statistical packages. Institute of Mathematics ans Statistics (IME) São Paulo main campus 1. Exploratory data analysis (univariate and multivariate): position measurements, dispersion, asymmetry, robust measures, bivariate measures, association between variables, outliers identification, processing variables, graphics. 2. Linear Regression Models, Regression Tough and Smoothing Methods. 3. Stochastic Simulation: inversion methods, rejection, composition and resampling methods. 4. Numerical Optimization: Newton-Raphson, scoring, quasi-Newton. 5. EM Algorithm. 6. “Bootstrap” and “Jacknife”. 7. Monte Carlo methods and Gaussian quadratures Denise Aparecida Botter, Eduardo Jordao Neves, Anatoli Iambartsev 40 MAE5704 8 Tests, Lists of exercises and seminars https://www.ime.usp.br/en

The concept of natural resources remains vague and loose. Thus, there is a tenuous limit between what is still natural resource and what is already transformed by mankind to some extent. I the same way, a mere classification of renewable and exhaustible resources is insufficient to promote a satisfactory comprehension about this subject. Hence, before analysing natural resources themselves, it is necessary to undertake a conceptual revision that strengthens the accuracy of definitions towards their empirical correspondent objects – Mature the conceptual background about natural resources under a geographical perspective through which social and natural dimensions merge. – Comprehend the complex relationship between natural resources and human development. – Develop analysis skills by building links between conceptual background and Brazil´s natural resources. Faculty of Philosophy, Languages and Human Sciences (FFLCH) São Paulo main campus 1 – The concept of natural resource and its derivations Introduction 1.1 Some complementary issues 1.2 Renewable x exhaustible resources: a false antagonism 1.3 Renewable or Inexhaustible? 1.4 Difference between renewable and naturally recyclable resources: the case of water 1.5 Difference between renewable and reproductive resource Conclusions Activities 2 – The richness of resources in Brazil: natural premises Introduction 2.1 Geographical positioning and climate features 2.2 Tectonic: the architecture of territory and water concentration 2.3 Macro-structures: cratons, sedimentary basins and orogenic belts 2.4 Macro-sculptures: highlands, plains and depressions 2.5 Biodiversity: the result of combination of the landscape components Conclusions Activities 3 – Natural resources and territorial organisation Introduction 3.1 Global scale 3.2 Continental scale: Latin America 3.3 National scale: Egypt 3.4 Regional scale: Amazon 3.5 Local scale: coastal areas 3.6 Other examples 3.7 Territorial configuration beyond natural resources 3.8 The influence of natural conditions over the urbanisation of S_o Paulo State Activities 4 – Energy: an essential knowledge Introduction 4.1 Brief historic of use 4.2 Useful concepts: energy, force, work 4.3 Types of energy and possibilities of conversions 4.4 Potency and efficiency 4.5 Energy losses and rational use Conclusions Our vital virtual energy Activities EMPIRICAL LESSONS 5 _ Non-renewable minerals for energy generation Introduction 5.1 Hydrocarbons – Petrol – Natural gas – Shale gas – Coal 5.2 Uranium Activities 6 – Minerais (non-renewables, renewables and inexhaustibles) for other uses Introduction 6.1 Impacts and restoration 6.2 Raw material for construction – Aggregates, Stones, Sands, Clays, Chalk – Aggregates from rejects (non-naturals) 6.3 Other minerals (non-metallics) – Evaporites: salt and gypsum – Barite 6.4 Soils – Conservation of soils 6.5 Agrochemicals and natural resources 6.6 Ferrous metallic minerals – Iron ore – Other ferrous metallic minerals 6.7 Non-ferrous metallic minerals – Aluminium ore – Copper ore – Other non-ferrous metallic minerals Activities 7 – Renewable and reproductive natural resources: biomass Introduction 7.1 Biomass for food production – Agriculture – Livestock – Aquaculture and mariculture 7.2 Biomass for energy production – Modern biomass – Traditional and other biomasses 7.3 Biomass for other uses – Silviculture – Timber from deforestation – Other biomasses 7.4 Biomass related to environment preservation – Protected areas – Sustainable ways to produce biomass – The milestone of biodiversity and bio-piracy Conclusions Activities 8 – Water resources: a special chapter Introduction 8.1 Definition and essential information – Atmospheric waters – Superficial, fresh and liquid waters – Underground fresh water 8.2 Water uses – Non-energy uses – Energy uses 8.3 Desalination of ocean water 8.4 The Brazilian paradox 8.5 San Peter: wanted alive or dead 8.6 S_o Francisco river transposition 8.7 Perspectives Activities 9 – Natural resources for non-traditional or alternative energy production Introduction 9.1 Sun energy – Transformation of Sun energy into thermo-energy – Transformation of Sun energy into electrical energy 9.2 Wind energy 9.3 Geothermal energy – Transformation of geothermal energy into electricity – Geothermal energy in Brazil 9.4 Alternative hydraulic energy – Tidal energy – Wave energy – Water flow energy 9.5 Hydrogen (H2) Conclusion Activities Luis Antonio Bittar Venturi 42 FLG5144 8 Fieldworks may have alterations due to logistic issues All demanded activities during the course will be assessed. The final mark will be composed by the average marks of: exercises (E), seminars (S), fieldwork repo https://www.google.com.br/url?sa=t&rct=j&q=&esrc=s&source=web&cd=10&ved=0ahUKEwi3paLQ9tzYAhXBE5AKHdAvBDkQFghfMAk&url=http%3A%2F%2Fwww.ru.nl%2Fpublish%2Fpages%2F798477%2Fstudent_guide_fflch.pdf&usg=AOvVaw1Cv-BPFTbngDpr4qVjQBud

The course offers an introduction to programming logic and computational tools for the social sciences graduate students. The course focus on procedures to (1) gather (2) organize and (3) present social data. The course aims to develop programming skills for handling data with academic purposes. Notice that this is not a methods, data analysis or computational social science course. The course is divided in two parts. In the first part we focus on preparing the computational enviroment, getting used with the tools and developing programming literacy in R, Git, SQL, Markdown, and other languages required in class. In the second part we apply the skills acquired in the first part to handle big datasets, webscrapping and third party APIs, digital files management for textual analysis, graphs, maps and other topics of interest. This course aims to fill a gap _common among social science students- providing the training in data management and computational skills Faculty of Philosophy, Languages and Human Sciences (FFLCH) São Paulo main campus 1 – Basics of R Programming 2 – Data structures and data management in R 3 – Tables and graphs in R 4 _ R + SQL basics 5 – Git basics 6 – Markdown basics 7 – LaTex basics 8 – Webscraping 9 – Text, corpus and natural language processing 10 – Maps and GIS 11 – Networks and graphs Glauco Peres da Silva, Leonardo Sangali Barone 40 FLS6397 8 Weekly activities (50%) and a final project (50%). https://www.google.com.br/url?sa=t&rct=j&q=&esrc=s&source=web&cd=10&ved=0ahUKEwi3paLQ9tzYAhXBE5AKHdAvBDkQFghfMAk&url=http%3A%2F%2Fwww.ru.nl%2Fpublish%2Fpages%2F798477%2Fstudent_guide_fflch.pdf&usg=AOvVaw1Cv-BPFTbngDpr4qVjQBud