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HPCf Moodle Update
by HPCf Moodle Admin - Friday, 28 March 2014, 2:22 PM
 

As you may have noticed, the HPCf Moodle has undergone a major update.  If you experience any issues, please feel free to direct them to help (at) hpcf.upr.edu.

 

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Theoretical and practical foundation in the area of cellular and molecular neurobiology, including genetics, as well as electrophysiological principles of neural cells, synaptic transmission, and neurodevelopment culminating in aging and neurodegenerative disorders.

This course will introduce students to the field of Molecular and Cellular Cognition (MCC). MCC is a
relatively young field with the goal of deriving explanations of cognitive processes that
integrate molecular, cellular, and behavioral mechanisms and to find
treatments for cognitive disorders. MCC studies focus on molecular
(ie. receptor, kinase activation), intra-cellular (i.e. dendritic
processes), and inter-cellular processes (i.e. synaptic plasticity;
network representations such as place fields) that modulate animal models of
cognitive function.

Estudio de los principios y conceptos básicos que operan en los organismos vivos y sus unidades constituyentes.
Introduction to system and network administration. Hands on experience in system and network administration and security issues.
History of computation. Problem solving by algorithmic development. Computer organization. Input/output units. Memory and central processing unit. Variables and data types. Program development techniques. Logic. Preconditioning and post-conditioning. Logical expressions. Conditional and iterative instructions. Procedures and functions. Structure data types such as arrays, strings, and files. Data type definition. Recursion. Program verification and testing. Social context and ethical principles of computing.
Introduction to compiling, a simple one pass compiler; lexical analysis, symbol tables, parsing; syntax directed translation, introduction to type checking, intermediate code generation, introduction to code generation and code optimization.
Introduction to organization and design of digital computers. The
configuration of logic gates to form flip-flops, shift registers,
memories and arithmetic registers. The internal representation of
data. Input-output devices.
Development of algorithms and their implementation in a structured high level language. Programming techniques applied to the solution of engineering and mathematical problems.

Este curso es una introducción a los aspectos físicos y ambientales de la producción de energía. consideraremos tópicos relacionados con los conceptos físicos aplicados en las diferentes tecnologías utilizdas para la producción de energía, sus ventajas y desventajas, así como medidas para l optimización del uso de enrgía. Nuestra consideración de estos tópicos también se caracterizará por el énfasis en la pertinencia de los mismos a la situación de Puerto Rico.


Curso introductorio de laboratorio de Física, destinado a estudiantes de programas de estudios técnicos. La clase de tres horas consta de una hora de discusión y dos horas de práctica de laboratorio. Los temas tratados en los laboratorios siguen la secuencia general de temas cubiertos en el curso de teoría.


Curso introductorio de laboratorio de Física, destinado a estudiantes de programas de estudios técnicos. La clase de tres horas consta de una hora de discusión y dos horas de práctica de laboratorio. Los temas tratados en los laboratorios siguen la secuencia general de temas cubiertos en el curso de teoría.


Curso introductorio de laboratorio de Física, destinado a estudiantes de programas de estudios técnicos. La clase de tres horas consta de una hora de discusión y dos horas de práctica de laboratorio. Los temas tratados en los laboratorios siguen la secuencia general de temas cubiertos en el curso de teoría.

Introduction to Bioinformatics

Topics covered will include biological sequences, programming in python, UNIX, sequence alignments, sequence phylogeny, sequence database searches, gene prediction, and whole genome analysis, including transcriptome and microarray analysis, gene clustering and application of statistics to gene profiling data.

We will emphasize the fundamental theory behind the analysis, and also present practical problems and their solutions. The course will use open-source bioinformatics tools, and show how to construct such tools using biopython, a set of libraries for bioinformatics in the python programming language.

The course is designed for graduate and advanced undergraduate students in biology. A basic knowlege of molecular biology is assumed. Students from other disciplines are invited to participate, but will have to make up the background

This one credit course is meant to give students exposure to different topics of relevance to Environmental Sciences. Students will learn about the research currently being conducted at the University of Puerto Rico and abroad through a series of graduate students and faculty seminars. The seminar will also provide an opportunity for students to learn skills essential for becoming successful student researchers.  Students will be able to identify and obtain research opportunities that are appropriate to their professional goals. This seminar will also allow students to develop an awareness of the diversity of research opportunities available to them in the environmental sciences. Skills that students will acquire will include among others finding the right research advisor, critical analysis of research manuscripts and how to navigate the whole research process.

This one credit course is meant to give students exposure to different topics of relevance to Environmental Sciences. Students will learn about the research currently being conducted at the University of Puerto Rico and abroad through a series of graduate students and faculty seminars. The seminar will also provide an opportunity for students to learn skills essential for becoming successful student researchers.  Students will be able to identify and obtain research opportunities that are appropriate to their professional goals. This seminar will also allow students to develop an awareness of the diversity of research opportunities available to them in the environmental sciences. Skills that students will acquire will include among others finding the right research advisor, critical analysis of research manuscripts and how to navigate the whole research process.

Our quality of life is mainly being driven by the way we exploit and consume energy; which somehow differentiate us from pre-industrial societies. Unfortunately, energy, the largest industry in the world, also turned out to be the biggest polluter on the planet. Therefore it is vital for us to think critically about energy issues, if we want to maintain our lifestyle and not jeopardizing future generations. With that in mind, this multidisciplinary course is designed to provide participants with an overview of energy technologies, fuels and environmental impacts. Topics will be interdisciplinary and will include an introduction to quantitative concepts in energy, including the differences among fuels and energy technologies. This course will use real-world examples while providing insights into technological trends aiming at securing our energy future. The course will feature prominent guest speakers and lectures focusing on current energy related events. In addition to in-class lectures, information will be shared via outside reading assignments, laboratories projects and a research paper focusing on a specific energy topic.

The purpose of this course is to provide the basic scientific knowledge and understanding of how our world works from an environmental perspective. Toward this end, we will touch on topics as broad as general issues on the environment, basic principles of ecology and ecosystem function, water resources and pollution, hazardous chemicals, air pollution and climate change, biodiversity, energy resources, and sustainability. The limited scope of this course will allow us to only cover basic techniques in the analysis of water, air, and soil quality using a hands-on approach. The discussion of processes and topics, as well as techniques studied will include: chlorine, alkalinity, hardness, nutrients, suspended solids, dissolved solids, sedimentable solids, biochemical oxygen demand, biological oxygen demand, dissolved oxygen, total organic carbon, fecal coliforms, turbidity, oils and fats, and long-term monitoring.

Biogas Lab Group Meeting

The purpose of this course is to provide the basic scientific knowledge and understanding of how our world works from an environmental perspective. Toward this end, we will touch on topics as broad as general issues on the environment, basic principles of ecology and ecosystem function, water resources and pollution, hazardous chemicals, air pollution and climate change, biodiversity, energy resources, and sustainability. The limited scope of this course will allow us to only cover basic techniques in the analysis of water, air, and soil quality using a hands-on approach. The discussion of processes and topics, as well as techniques studied will include: chlorine, alkalinity, hardness, nutrients, suspended solids, dissolved solids, sedimentable solids, biochemical oxygen demand, biological oxygen demand, dissolved oxygen, total organic carbon, fecal coliforms, turbidity, oils and fats, and long-term monitoring.

Se estudia de forma “hands-on” como hacer las técnicas básicas de un análisis de calidad de agua, aire, y tierra. En grupos de 3-4 estudiantes hacen un informe de evaluación ambiental comparando dos sitios en Puerto Rico usando las técnicas que aprendieron durante la clase. La discusión de procesos y tópicos y las técnicas estudiadas incluye: cloro residual, alcalinidad, dureza, nutrientes, sólidos suspendidos, sólidos disueltos, sólidos sedimentables, demanda bioquímica de oxígeno, demanda química de oxígeno, oxígeno disuelto, carbón orgánico total, coliformes fecales, turbidez, aceites y grasas, y monitoreo.

Revised TECNICAS course to be offered in January 2012

This is the shared web site for all new Haitian students in the graduate programs of UPR

Bienvenue

Gary Gervais, gary.gervais@uprrp.edu, 787-764-0000 x (1)7344#

Here we will place all of the documents related to the July orientation program for new graduate students. Please watch for changes in the calendar and new announcements
This is a multidisciplinary course for introducing the students to the basic concepts of Bayesian statistics, and how they can be applied for data analysis using modern computational tools (R and WinBUGS). The focus will be on applications, especially to problems in Life Sciences.
Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can now be generated to address extremely complex biological questions. Correspondingly, advances in the statistical methods necessary to analyze such data are following closely behind the advances in data generation methods. The statistical methods required by bioinformatics present many new and difficult problems for the research community.
Poblaciones y muestras. Distribuciones chi-cuadrada, t, F. Estimación. Intervalos de confianza. Pruebas de hipótesis simples y compuestas. Teoría de decisiones. Modelos lineales. Métodos no paramétricos. Estadística de series cronológicas.
MATE 6611 Modelos Lineales I. Tres Créditos. Prerequisito: MATE 5002.
Modelos estadísticos lineales con énfasis en los fundamentos matemáticos. Aplicación del álgebra lineal especialmente en la consideración de los temas principales: regresión y análisis de varianza.
Espacios muestrales, axiomas y teoremas elementales de la probabilidad. Combinatoria. Teorema de Bayes. Variables aleatorias. Distribuciones de probabilidad. Esperanza matemática. Media y varianza de una variable aleatoria. Funciones generatrices de momentos. La desigualdad de Chebyshev y la ley de los números grandes. El teorema del límite central. Trayectorias aleatorias y cadenas de Markov.
Curso introductorio de Cálculo Diferencial para estudiantes de administración de Empresas. Estudio de los conceptos de límite y continuidad, la derivada de una función y las reglas de diferenciación de funciones de una variable independiente. Énfasis en las aplicaciones de interés continuo, análisis marginal, optimización de funciones y trazado de curvas. Introducción al Cálculo Integral.
Introducción a la estadística para la Administración de Empresas uno es un curso en el que se discute estadística descriptiva conceptos básicos de probabilidad, variables aleatorias, discretas y continuas y sus distribuciones de probabilidad. Distribuciones de probabilidad y sus propiedades. La distribuciones de probabilidad tales como Binomial, Poisson y Normal. También se discutirá distribuciones de muestreo y topicos especiales de diseño de experimentos aplicados al mercado. La utilización de programas estadísticos computadorizados para implementar las técnicas estadísticas estudiadas es fundamental en el curso. Para esto usaremos EXCEL y R.
Introducción a la inferencia estadística. Estimación y pruebas de hipótesis para una y dos muestras. Introducción al control estadístico de calidad. Análisis de varianza de un factor y pruebas de comparación multiple. Análisis de tablas de contingencia. Regresión lineal simple y múltiple. Aplicaciones de series de tiemplo. Utilización de programas estadísticos computadorizados para implementar las técnicas de la estadísticas estudiadas.
Espacios muestrales, axiomas y teoremas elementales de la probabilidad, análisis combinatorio, independencia y probabilidad condicional. Teorema de Bayes. Variables aleatorias, distribuciones de probabilidad, esperanza matemática, media y varianza. Funciones generatrices de momentos. La desigualdad de Chebyshev, la ley de los números grandes, el teorema del límite central.
Teoría de inferencia estadística. Estimadores y métodos de estimación. Pruebas de hipótesis. Regresión lineal. Se hará hincapié en el rigor matemático y en el desarrollo formal del tema, así como en los aspectos computacionales utilizando el lenguaje R

Análisis Exploratorio de Datos. Teoría de Probabilidad. Variables aleatorias. Distribuciones
muestrales discretas y continuas. Estimación. Pruebas de hipótesis. Correlación y
regresión. El uso de la computadora en la simulación de experimentos aleatorios. Estadística computacional.

This is a multidisciplinary course in which students will be introduced to the most common methods in Experimental Design and Statistical Data analysis and their application in Biology, Environmental Sciences and other areas. Students will use computer tools in order to enhance their understanding and mastering of the studied techniques.

Este es un curso multidisciplinario en el cual se introducirá a los estudiantes a métodos de mayor uso en las áreas de Diseño Experimental y Análisis Estadístico de Datos y sus aplicaciones en disciplinas en Biología, Ciencias Ambientales y otras áreas. Los estudiantes usarán análisis computarizados para aumentar su comprensión y dominio de las técnicas adquiridas durante el curso