Pay Inequality in Cuba: the Special Period and After

This paper analyzes the evolution of pay inequality in Cuba from the early 1990s through 2004, during what was known as the “Special Period in Times of Peace” and after. We measure pay inequality across sectors and regions, using the between-groups component of Theil’s T statistic, and we map the changing components of that statistic in order to provide a compact summary of structural change in Cuba. This method helps us to observe the transition of the Cuban economy from one based fundamentally on sugar to one based largely on services, especially tourism, but also others with greater growth potential, such as information technology, pharmaceuticals, and biotechnology. Regionally, we observe that a main dividing line between winners and losers is the presence of tourist attractions: the recent increase of regional pay inequality is associated primarily with changing incomes in the city of Havana and the province of Matanzas.

Programación de computadores orientada al análisis y la visualización de datos, como formación básica de estudiantes de ingeniería

En la actualidad, estamos en una época donde la información ha sido explorada muy poco y en donde la big-data y el análisis de datos, se tornan como proceso de alta demanda por parte de diferentes campos del saber profesional. Para esto, la lectura y manipulación de estos datos, se tornan en procesos complejos y de muchos recursos si no se tiene conocimiento de alguna herramienta que permita ejercer esta habilidad. Es así que se pretende la creación de esta guía orientada al análisis y visualización de datos para estudiantes de ingenierías, buscando como finalidad transmitir un conocimiento fundamental al lector, sobre el lenguaje de programación R, donde con este, podamos generar cálculos estadísticos, crear gráficos y una mejor y cómoda lectura de múltiples datos, ofreciendo así un nuevo enfoque hacia el ámbito estadístico y obteniendo un mejor razonamiento para brindar soluciones a diferentes problemas de la vida cotidiana.At present, we are in a time where the information has been explored very little, where big data and data analysis become high demand processes by different fields of professional knowledge. For this, the reading and manipulation of this data become complex and resource intensive proccesses if there's no knowledge of any tool that allows to exercise this ability. It's in this way we pretend the creation of this guide oriented to the analysis and visualization of data for engineering students that is intended to transmit a fundamental knowledge to the reader, about the R programming language, where with this we can generate statistical calculations, create graphs and a better and comfortable reading of multiple data, offering a new approach to the statistical field and obtaining a better reasoning to provide solutions to different problems of everyday life.PregradoIngeniero(a) de Sistemas y ComputaciónContenido Agradecimientos................................................................................................................. 6 Resumen.............................................................................................................................. 7 Palabras Claves: .............................................................................................................. 7 Abstract............................................................................................................................... 8 Keywords: ....................................................................................................................... 8 Capítulo I: Formulación Del Problema............................................................................. 13 1.1 Introducción. ........................................................................................................... 13 1.2 Descripción del Problema. ...................................................................................... 13 1.3 Justificación............................................................................................................. 14 1.4 Objetivos. ................................................................................................................ 14 1.4.1 Objetivo General............................................................................................... 14 1.4.2 Objetivos Específicos. ...................................................................................... 14 1.5 Alcance del proyecto............................................................................................... 14 Capitulo II: Marco Teórico. .............................................................................................. 16 2.1 Introducción. ........................................................................................................... 16 2.1.1 ¿Qué es R? ........................................................................................................ 16 2.1.2 ¿Cómo Instalar R? ............................................................................................ 18 2.1.3 Como Se Ve R. ................................................................................................. 19 2.2 Conceptos Básicos................................................................................................... 20 2.2.1 R Como Calculadora. ....................................................................................... 20 2.2.2 Ayuda en R. ...................................................................................................... 23 2.2.3 Paquetes (Packages) en R. ................................................................................ 24 2.2.3.1 Instalar Paquetes. ...................................................................................... 25 2.2.3.2 Cargar Paquete.......................................................................................... 27 2.2.3.3 Comprobar Paquetes Instalados................................................................ 28 Capitulo III: Marco Metodológico.................................................................................... 30 3.1 Tipo de Datos y Objetos.......................................................................................... 30 3.1.1 Tipo de Datos.................................................................................................... 30 3.1.2 Objetos.............................................................................................................. 30 3.1.2.1 Variable..................................................................................................... 31 3.1.2.2 Vector........................................................................................................ 32 3.1.2.2.1 ¿Cómo Extraer Datos de un Vector? ................................................. 34 3.1.2.3 Matriz........................................................................................................ 36 3.1.2.3.1 ¿Cómo Extraer Datos de una Matriz?................................................ 37 3.1.2.4 Arreglo. ..................................................................................................... 39 3.1.2.4.1 ¿Cómo Extraer Datos de un Arreglo?................................................ 40 3.1.2.5 Marco de Datos. ........................................................................................ 42 3.1.2.5.1 ¿Cómo Extraer Datos de un Marco de Datos?................................... 43 3.1.2.5.2 ¿Cómo extraer Subconjuntos de Datos de un Marco de Datos?........ 44 3.1.2.6 Listas......................................................................................................... 45 3.1.2.6.1 ¿Cómo Extraer Datos de un Marco de Datos?................................... 46 3.2 Estructura de Control. ............................................................................................. 48 3.2.1 If, Else............................................................................................................... 48 3.2.2 Bucles. .............................................................................................................. 51 3.2.2.1 Bucle For................................................................................................... 51 3.2.2.2 Bucle While. ............................................................................................. 54 3.2.2.3 Bucle Repeat. ............................................................................................ 55 3.3 Importación y Exportación de Datos....................................................................... 56 3.3.1 Almacenamiento de Datos................................................................................ 56 3.3.1.1 Guardar Datos en Excel. ........................................................................... 57 3.3.1.2 Guardar Datos en Bloc de Notas............................................................... 58 3.3.2 Importación de Datos........................................................................................ 59 3.3.2.1 Leer Base de Datos Desde Excel. ............................................................. 60 3.3.2.2 Leer Base de Datos Desde Bloc de Notas con Espacios Simples............. 61 3.3.2.3 Leer Base de Datos Desde Bloc de Notas con Tabulación....................... 62 3.3.3 Exportar Datos.................................................................................................. 62 3.4 Graficas en R........................................................................................................... 68 3.4.1 Introducción a los gráficos en R....................................................................... 68 3.4.2 Tipos de Gráficos.............................................................................................. 70 3.4.2.1 Histograma................................................................................................ 70 3.4.2.2 Grafica de Barras ...................................................................................... 72 3.4.2.3 Diagrama de Dispersión............................................................................ 75 3.4.2.4 Diagrama Circular..................................................................................... 77 3.4.3 Exportar Gráficos ............................................................................................. 80 3.4.3.1 ¿Por qué exportar los gráficos?................................................................. 81 3.4.3.2 ¿Cómo exportar mi grafica?...................................................................... 82 Capitulo IV: Test de Conocimiento .................................................................................. 84 4.1 Ejercicio 1 ............................................................................................................... 84 4.2 Ejercicio 2 ............................................................................................................... 84 4.3 Ejercicio 3 ............................................................................................................... 86 4.4 Ejercicio 4 ............................................................................................................... 86 Conclusiones..................................................................................................................... 88 Bibliografía ....................................................................................................................... 8

Iberá Wetlands: diversity hotspot, valid ecoregion or transitional area? Perspective from a faunistic jumping spiders revision (Araneae: Salticidae)

In the present work, the fauna of jumping spiders or Salticidae of the Iberá Wetlands was investigated. Patterns of species richness, composition and endemism in hygrophilous woodlands and savannah parklands in ten locations covering the Iberá Wetlands were analyzed. Samples were obtained using four methods: garden vacuum, pit-fall trap, beating and litter extraction. 75 species were collected, representing one third of the known Argentine salticids. Six species are recorded for the first time for Argentina. The community structure of the investigated locations suggests that the high diversity of jumping spiders is the result of the mixing of species of adjacent ecoregions such as Humid Chaco, Atlantic forest and Espinal. The transitional character of Iberá Wetlands, in combination with no endemism in nominally identified taxa, questions the ecoregion validity of Iberá for jumping spiders. The importance of taxonomy and the use of mature spiders in ecological studies is discussed.Fil: Rubio, Gonzalo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Universidad Nacional de Misiones. Instituto de Biología Subtropical; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Misiones; ArgentinaFil: Nadal, María Florencia. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas, Naturales y Agrimensura. Laboratorio de Biología de los Artrópodos; ArgentinaFil: Munevar Lozano, Ana Katerinne. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Universidad Nacional de Misiones. Instituto de Biología Subtropical; ArgentinaFil: Avalos, Gilberto. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas, Naturales y Agrimensura. Laboratorio de Biología de los Artrópodos; ArgentinaFil: Perger, Robert. .Colección Boliviana de Fauna; Bolivi

Dildos, arneses y otros artículos sexuales: tecnología de asistencia sexual en la diversidad funcional

The participation and full exercise of sexuality in people with functional diversity turns out to be a little-addressed and denied aspect, facing barriers and limitations in their sexuality, which could be eliminated with the use of technology. This document corresponds to a mixed research of an exploratory nature, describes the technology to promote sexuality in people with functional diversity, available in erotic shops of the locality of Chapinero, Bogota, Colombia. Its methodology was developed virtually, it included consultation of eight online catalogues, online surveying and in-depth virtual interviews, involving ten people with functional diversity and two erotic store owners. The analysis included statistical techniques of frequency interpretation and qualitative categorization techniques through participants' experiences with sexual products. Nine sexual products used by the participants were evidence, with the lubricants being the most widely used. The Catalogue of Sexual Technology for Functional Diversity describes eleven groups of sexual products and was co-built with research participants.La participación y el ejercicio pleno de la sexualidad en las personas con diversidad funcional resulta ser un aspecto poco abordado y negado, enfrentando barreras y limitaciones en su sexualidad, que podrían ser eliminadas con el uso de tecnología. Este documento corresponde a una investigación mixta de carácter exploratorio, describe la tecnología para favorecer la sexualidad en las personas con diversidad funcional disponible en las tiendas eróticas de la localidad de Chapinero en Bogotá, Colombia. Fue desarrollada de forma virtual; incluyó la consulta de ocho catálogos en línea, el diligenciamiento de encuestas en línea y entrevistas virtuales a profundidad, en las que participaron diez personas con diversidad funcional y dos propietarios de tiendas eróticas. El análisis incluyó técnicas estadísticas de interpretación por frecuencias y técnicas cualitativas de categorización a partir de las experiencias de los participantes con productos sexuales. Se evidenciaron nueve productos sexuales usados por los participantes, siendo el lubricante el de mayor uso. El Catálogo de tecnología sexual para la diversidad funcional describe once grupos de productos sexuales y fue co-construido con los participantes de la investigación.Tesis de pregrado del programa de Terapia Ocupacional y fue postulada como uno de los mejores trabajos de grado del año 2020. Esta monografía dispone de un producto final titulado "Catálogo de tecnología sexual para personas con diversidad funcional" y conforma un anexo de este trabajo, disponible en dos versiones la primera es accesible en formato Word y la segunda con diseño y diagramación en formato PDF.Pregrad

Differential cross section and recoil polarization measurements for the gamma p to K+ Lambda reaction using CLAS at Jefferson Lab

We present measurements of the differential cross section and Lambda recoil polarization for the gamma p to K+ Lambda reaction made using the CLAS detector at Jefferson Lab. These measurements cover the center-of-mass energy range from 1.62 to 2.84 GeV and a wide range of center-of-mass K+ production angles. Independent analyses were performed using the K+ p pi- and K+ p (missing pi -) final-state topologies; results from these analyses were found to exhibit good agreement. These differential cross section measurements show excellent agreement with previous CLAS and LEPS results and offer increased precision and a 300 MeV increase in energy coverage. The recoil polarization data agree well with previous results and offer a large increase in precision and a 500 MeV extension in energy range. The increased center-of-mass energy range that these data represent will allow for independent study of non-resonant K+ Lambda photoproduction mechanisms at all production angles.Comment: 22 pages, 16 figure

A comparison of forward and backward pp pair knockout in 3He(e,e'pp)n

Measuring nucleon-nucleon Short Range Correlations (SRC) has been a goal of the nuclear physics community for many years. They are an important part of the nuclear wavefunction, accounting for almost all of the high-momentum strength. They are closely related to the EMC effect. While their overall probability has been measured, measuring their momentum distributions is more difficult. In order to determine the best configuration for studying SRC momentum distributions, we measured the $^3$He$(e,e'pp)n$ reaction, looking at events with high momentum protons ($p_p > 0.35$ GeV/c) and a low momentum neutron ($p_n< 0.2$ GeV/c). We examined two angular configurations: either both protons emitted forward or one proton emitted forward and one backward (with respect to the momentum transfer, $\vec q$). The measured relative momentum distribution of the events with one forward and one backward proton was much closer to the calculated initial-state $pp$ relative momentum distribution, indicating that this is the preferred configuration for measuring SRC.Comment: 8 pages, 9 figures, submitted to Phys Rev C. Version 2 incorporates minor corrections in response to referee comment

Tensor Correlations Measured in 3He(e,e'pp)n

We have measured the 3He(e,e'pp)n reaction at an incident energy of 4.7 GeV over a wide kinematic range. We identified spectator correlated pp and pn nucleon pairs using kinematic cuts and measured their relative and total momentum distributions. This is the first measurement of the ratio of pp to pn pairs as a function of pair total momentum, $p_{tot}$. For pair relative momenta between 0.3 and 0.5 GeV/c, the ratio is very small at low $p_{tot}$ and rises to approximately 0.5 at large $p_{tot}$. This shows the dominance of tensor over central correlations at this relative momentum.Comment: 4 pages, 4 figures, submitted to PR

Measurement of the nuclear multiplicity ratio for Ks0K^0_s hadronization at CLAS

The influence of cold nuclear matter on lepto-production of hadrons in semi-inclusive deep inelastic scattering is measured using the CLAS detector in Hall B at Jefferson Lab and a 5.014 GeV electron beam. We report the $K_s^0$ multiplicity ratios for targets of C, Fe, and Pb relative to deuterium as a function of the fractional virtual photon energy $z$ transferred to the $K_s^0$ and the transverse momentum squared $p_{T}^2$ of the $K_s^0$. We find that the multiplicity ratios for $K^0_s$ are reduced in the nuclear medium at high $z$ and low $p_{T}^2$, with a trend for the $K^0_s$ transverse momentum to be broadened in the nucleus for large $p_{T}^2$.Comment: Submitted to Phys. Lett.

Differential cross sections and spin density matrix elements for the reaction gamma p -> p omega

High-statistics differential cross sections and spin density matrix elements for the reaction gamma p -> p omega have been measured using the CLAS at Jefferson Lab for center-of-mass (CM) energies from threshold up to 2.84 GeV. Results are reported in 112 10-MeV wide CM energy bins, each subdivided into cos(theta_CM) bins of width 0.1. These are the most precise and extensive omega photoproduction measurements to date. A number of prominent structures are clearly present in the data. Many of these have not previously been observed due to limited statistics in earlier measurements

Coherent Photoproduction of pi^+ from 3^He

We have measured the differential cross section for the $\gamma$$^3$He$\rightarrow \pi^+ t$ reaction. This reaction was studied using the CEBAF Large Acceptance Spectrometer (CLAS) at Jefferson Lab. Real photons produced with the Hall-B bremsstrahlung tagging system in the energy range from 0.50 to 1.55 GeV were incident on a cryogenic liquid $^3$He target. The differential cross sections for the $\gamma$$^3$He$\rightarrow \pi^+ t$ reaction were measured as a function of photon-beam energy and pion-scattering angle. Theoretical predictions to date cannot explain the large cross sections except at backward angles, showing that additional components must be added to the model.Comment: 11 pages, 16 figure