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4,240 results for “Peru”
Survey data on climate policy in three countries (Peru, Ghana, Philippines) within the project "Sustainable Middle Classes in Middle Income Countries: Transforming Carbon Consumption Patterns (SMMICC)"
<p>The unprecedented growth of the new middle classes in middle income developing countries implies a strong growth in both consumption and carbon emissions. The research project Sustainable Middle Classes in Middle Income Countries (SMMICC) investigates the drivers of carbon consumption choices of the new middle classes and policy options to decrease their carbon footprints, including the implementation of carbon taxes</p> <p>The research of the authors generated quantitative data on the acceptability of carbon taxes in three countries (Peru, Ghana, Philippines).</p> <p> </p> <p><strong>The data is provided in the following formats:</strong></p> <p>- 2024-07-26_malerba_10.5281/zenodo.12662722_ghana.csv<br>- 2024-07-26_malerba_10.5281/zenodo.12662722_peru.csv<br>- 2024-07-26_malerba_10.5281/zenodo.12662722_philippines.csv</p> <p>- 2024-07-26_malerba_10.5281/zenodo.12662722_ghana.dta<br>- 2024-07-26_malerba_10.5281/zenodo.12662722_peru.dta<br>- 2024-07-26_malerba_10.5281/zenodo.12662722_philippines.dta</p> <p>Additionally, the codebooks on variables of questionnaire and political parties in each country are attached in a csv format.</p>
Peru Energy Data (Part I)
<p>The data illustrate the evolution of the Peruvian Energy System from 2005 to 2022. This information has been compiled by consulting the National Energy Balances for each respective year. It is important to note that data for primary energy, transformation, and secondary energy for the years 2010 and 2011 is either missing or incomplete. Additionally, final consumption by source includes data dating back to 1985.</p>
Dataset containing binominal lexemes in Harakmbut (isolate, Peru), for "The derivational use of classifiers in Western Amazonia" and "When the alienability contrast fails to surface in adnominal possession: Bound nouns in Harakmbut"
<p>This is the dataset used, amongst others, in the paper: Van linden, An. Forthcoming. When the alienability contrast fails to surface in adnominal possession: Bound nouns in Harakmbut. Special Issue “Re-assessing the explanatory potential of alienability contrasts”, guest-edited by Françoise Rose & An Van linden. <em>Linguistics – An Interdisciplinary Journal of the Language Sciences</em>. [<a href="https://doi.org/10.1515/ling-2022-0039">https://doi.org/10.1515/ling-2022-0039</a>]</p> <p>For more details, see the ReadMe file.</p>
Cambridge butterfly collection - Loreto, Peru 2018
<p>Cambridge Butterfly Collection. Loreto, Peru Part 1</p> <p>EN: This upload contains photographs taken by Eva van der Heijden at the Butterfly Genetics Group at the University of Cambridge, from a butterfly wing collection from Loreto, Peru, in collaboration with Green Gold Forestry. Individual sample names can be found in the information sheet. Further Information on individual samples from the Butterfly Genetics Group Collection can be found on the public database Earthcape (<a href="https://heliconius.ecdb.io/">click here for the database</a>, and <a href="https://heliconius.zoo.cam.ac.uk/databases/earthcape-specimen-database/">here for FAQ</a>). Please contact Chris Jiggins (c.jiggins[at]zoo.cam.ac.uk) or Gabriela Montejo-Kovacevich (gmontejokovacevich[at]gmail.com) for further information.</p> <p> </p> <p>ES: Este repositorio contiene fotografías tomadas por Eva van der Heijden en el Butterfly Genetics Group de la Universidad de Cambridge, de mariposas de Loreto (Peru), en colaboración con la compañía Green Gold Forestry. Puede encontrar información sobre muestras individuales de Butterfly Genetics Group Collection en la base de datos pública Earthcape (<a href="https://heliconius.ecdb.io/">haga clic aquí para la base de datos</a>, y <a href="https://heliconius.zoo.cam.ac.uk/databases/earthcape-specimen-database/">aquí para preguntas frecuentes</a>) Por favor, póngase en contacto con Chris Jiggins (c.jiggins [arroba] zoo.cam.ac.uk) o Gabriela Montejo-Kovacevich (gmontejokovacevich[at]gmail.com) con sus preguntas o peticiones.</p>
Survey data on financial literacy, financial inclusion, informal financial business practices, and intentions towards formalization of female small vendors in Lima, Peru
<p><span>This dataset encapsulates a comprehensive survey aimed at understanding informal business practices and financial literacy among small business vendors in Peru. The dataset comprises three key components: the survey questionnaire, raw survey data, and a detailed codebook. Researchers interested in the dynamics of financial practices in emerging markets may find this dataset particularly valuable, as it allows for the exploration of factors influencing financial decisions in small enterprises, with potential modifications suggested for adapting the survey to different national or cultural contexts. This dataset not only contributes to empirical research in financial behavior but also supports gender-specific studies by allowing the variable 'sex' to be adapted to 'gender' with multiple response options. </span></p> <p><span>The data and supplementary material is divided in tree files:</span></p> <p><span>The survey, presented in "Survey IFE.docx," includes questions across various domains such as informal business practices, financial literacy, financial inclusion, intentions towards financial formalization, and the formality of business ventures, along with demographic variables like age, sex, business age, and number of employees. </span></p> <p><span>The raw data, stored in "Dataset.csv," records responses from 118 participants, mapped against 31 indicators. </span></p> <p><span>The "Codebook.doc" provides exhaustive details about the survey variables, coding of responses, and the methodology employed, facilitating the replication of the study and application of the dataset in varied research contexts.</span></p>
CLDF dataset derived from Ugarte et al.'s "NorthPeruLex - A Lexical Dataset of Small Language Families and Isolates from Northern Peru (forthcoming).
<p>Cite the source of the dataset as:</p> <blockquote> <p>Ugarte, Carlos and Blum, Frederic and Ingunza, Adriano and Gonzales, Rosa and Peña, Jaime. Forthcoming. NorthPeruLex - A Lexical Dataset of Small Language Families and Isolates from Northern Peru.</p> </blockquote>
Data for Publication "Sensitivity of precipitation in the highlands and lowlands of Peru to physics parameterization options in WRFV3.8.1"
<p>The data are made available as part of the paper "Sensitivity of precipitation in the highlands and lowlands of Peru to physics parameterization options in WRFV3.8.1", submitted to Geoscientific Model Development. This data set incorporates selected postprocessed files needed to reproduce the results presented in the paper. </p> <p>The files including the monthly means of precipitation for domain 2 (5 km) are named following the same structure:</p> <p> RR-D02-EXPERIMENTNAME-25km3Doms-YYYY_monthly.nc</p> <p>These are the options available in each case:</p> <ul> <li>EXPERIMENTNAME: Europe, SouthAmerica, Kenya, Micro13 or NoCumulus. These are the names included in Table 1 <br> from the paper.</li> <li>YYYY: 2008 or 2012. This is only applicable to precipitation.</li> </ul> <p>The field means for the northeastern slopes follow this structure:</p> <p> VARIABLE-D02-ERA5-Peru-25-Present-EXPERIMENTNAME-2008.EastLow.fldmean.nc</p> <ul> <li>VARIABLE: CLOUDFRA, PW, RH2, RR, SMOIS or T2. This abbreviations represent the following variable from the model<br> respectively: cloud fraction, precipitable water, relative humidity at 2 meters, total precipitation, soil moisture<br> and temperature at 2 meters.</li> <li>EXPERIMENTNAME: Europe, SouthAmerica, Kenya, Micro13 or NoCumulus. These are the names included in Table 1<br> from the paper.</li> </ul> <p>These files contained hourly values so to obtain the monthly means or sums the user must perform the following command:</p> <p> cdo monmean/monsum in.nc out.nc</p> <p>Two .txt files including the information about the stations considered for the validation of the WRF experiments for year 2008 or 2012 are also included. The data is separated with white spaces, and the structure of the columns is the following one:</p> <p> STATION LATITUDE LONGITUDE ELEVATION COUNTRY PROVIDER REGION</p> <p>Finally, two .zip files are provided. Scripts.zip includes all the scripts used to read, process and plot the data from the model, and Namelist_files.zip includes all the namelist files used to run the WRF simulations.</p> <p> </p>
El Niño Enhances Snowline Rise and Ice Loss on the Quelccaya Ice Cap, Peru
<p>El Niño Enhances Snowline Rise on the Quelccaya Ice Cap, Peru (in-review)</p> <p>Kara A. Lamantia, Laura J. Larocca, Lonnie G. Thompson, Bryan Mark</p> <p>Exported results from automated snow cover area detection on the Quelccaya Ice Cap (QIC). Further calculated results are detailed in the supplementary documentation in the draft manuscript. See READ ME.txt file for details</p> <p>Sample Code available for Landsat 8 imagery here at the following URL: https://code.<br>earthengine.google.com/cfcbd0780ff3f09b0698035cd6dd678a</p>
Images of "Iglu" shelter at Caraz in Peru
<p>Seven images (no. 1-7) of "Iglu" shelter and fragments, located at Jirón Los Alisos with Avenida 9 de Octubre in<span> </span>Caraz, 02167 Peru. The data set includes a list of the photographies with descriptions. The photographies show the remaining parts of the humanitarian shelter "Iglu", a joint relief operation of Bayer AG with the German Red Cross Societies in the aftermath of the Peruvian earthquake of 31st May 1970.</p>
Frequency and Rank of Family Names in Peru
<p>Count of family names (surnames, last names) in Peru, from an approximately 7% sample of the adult population.</p> <p>In Peru, many people are registered as supporters of political parties, and their names are published by the <a href="https://aplicaciones007.jne.gob.pe/srop_publico/Consulta/PadronAfiliado">Registro de Organizaciones Políticas</a>. The lists include a DNI (national identity number) for each person to avoid duplicates. The 1,572,002 people on these lists (excluding the regional movements) represent around 7% of the adult population of Peru.</p> <p>Their maternal and paternal family names have been sorted and counted. Nearly all of the names have entries for both paternal and maternal names.</p> <p>These 3,142,561 family names represent 85,395 different names, most of which are infrequent. The file has been limited to names that occur ten or more times in the sample, which is 12,139 unique names (3,021,655 names, more than 96% of the total).</p> <p>Each row in the file contains the rank, a percentage of that name in the entire set of 3,142,561 names, a count of the times the name occurs in the sample, and the name. </p> <p>There are some names (around 800) in this file that contain a space. In most cases, these are names like "GARCIA DE RUIZ", where RUIZ is the name of the woman's husband. There are also cases where the name is like "DE LA CRUZ", which is a complete family name. No attempt has been made to remove the part of names which refer to the husband's name, this could be considered for a later version. </p> <p> </p>
Frequency and Rank of First Names in Peru
<p>Count of popularity of adult first names (forenames, given names) in Peru, from an approximately 7% sample of the adult population.</p> <p>In Peru, many people are registered as supporters of political parties, and their names are published by the <a href="https://aplicaciones007.jne.gob.pe/srop_publico/Consulta/PadronAfiliado">Registro de Organizaciones Políticas</a>. The lists include a DNI (national identity number) for each person to avoid duplicates. The 1,572,002 people on these lists (excluding the regional movements) represent around 7% of the adult population of Peru.</p> <p>The first and middle names have been sorted and counted (there are an average of 1.6 first names for each person).</p> <p>These 2,538,011 first (and middle) names represent 76,720 different names, most of which are infrequent. The file has been limited to names that occur ten or more times in the sample, which is 7,250 unique names (2,417,750 names, more than 95% of the total).</p> <p>Each row in the file contains the rank, a percentage of that name in the entire set of 2,538,011 names, a count of the times the name occurs in the sample, and the name. </p> <p> </p> <p> </p> <p> </p>
National Checklists 2017: Peru Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>A list of species from Peru collected using effechecka and geonames polygons
National Checklists 2019: Peru Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>A list of species from Peru collected using effechecka and geonames polygons
Information of the centroids and geographical limits of the regions, departments, provinces and districts of Peru
<p>Datasets with information of the centroids and geographical limits of the regions, departments, provinces and districts of Peru.</p> <p>Data processed from National Statistical System (INEI) publications.</p> <p>2025.</p>
Time-of-failure prediction of the Achoma landslide, Peru, from high frequency Planetscope satellites
<p><strong>Introduction</strong></p> <p>This repository contains the data used for the study of the slope instability of Achoma, Peru, described in Lacroix et al. (submitted). Specifically, the repository contains a time series of horizontal ground displacements, obtained from high frequency PlanetScope satellite between 2017 and 2020. It also contains two Digital Elevation Models, one from before the Achoma failure obtained with Pléaides stero images, and the other from just after the Achoma failure obtained with drone imagery.</p> <p>The data and methods used for the elaboration of this data repository are described in detail in Lacroix et al. (submitted). In this repository we also provide a short summary and overview of the data and methods used.</p> <p><strong>Data</strong></p> <p>A total of 79 PlanetScope scenes were used to produce the time series of horizontal horizontal ground displacements maps. Table 1 provides an overview of these data.</p> <p>Table1: Data used for the creation of this repository</p> <table> <tbody> <tr> <td> <p>Application</p> </td> <td> <p>Platforms</p> </td> <td> <p>Acquisition dates</p> </td> </tr> <tr> <td> <p>Pre-failure DEM</p> </td> <td> <p>Pléiades</p> <p> </p> </td> <td> <p>2017/05/13</p> </td> </tr> <tr> <td> <p>Post-failure DEM</p> </td> <td> <p>Drone</p> </td> <td> <p>2020/06/19</p> </td> </tr> <tr> <td> <p>Horizontal ground displacement</p> </td> <td> <p>PlanetScope</p> </td> <td> <p>79 scenes from 2017/11/27 to 2020/06/17</p> </td> </tr> </tbody> </table> <p><br> </p> <p><strong>Methods</strong></p> <p>The horizontal ground displacement maps, both along the NS and the EW directions (file names NSxxxxxxxx.tif and Ewxxxxxxxx.tif, where xxxxxxxx is the date in the format yyyymmdd) were created using the offset tracking methodology described in Bontemps et al. (2018), consisting of: (1) correlation of all the pairs of images using Mic-Mac (Rupnik et al., 2017), (2) masking the low correlation coefficient values (CC<0.7), (3) mosaicking correction, similar to stripe corrections (Bontemps et al., 2018), that we obtained by subtracting the median value of the stacked profile in the along-stripe direction, taking into account only stable areas, (4) least square inversion of the redundant system per pixel, weighted by the time separation between pairs (Bontemps et al., 2018), (5) correction of illumination effects (Lacroix et al., 2019), based on the 2 years of data between November 2017 and December 2019.</p> <p>The pre-failure DEM was computed from Ames Stereo Pipeline (Shean et al. 2016) and the methodology developed in (Lacroix, 2016) applied to the Pléiades stereo images (file name DEM_20170513_shifted_vertical2.tif ).</p> <p>The post-failure DEM was processed using the Structure from Motion-Multi View Stereo (SfM-MVS) methodology with the Agisoft Metashape Professional 1.5.5 software applied on 1824 pictures taken from the drone (file name Achoma_DEM_2020.06.20_UTM19S_50cm.tif ).<br> </p> <p><strong>Acknowledgements</strong></p> <p>P.L. acknowledge the support from the French Space Agency (CNES) through the TOSCA, PNTS, and ISIS programs.</p> <p><strong>Dataset attribution</strong></p> <p>This dataset is licensed under a Creative Commons CC BY 4.0 International License.</p> <p><strong>Dataset Citation</strong></p> <p>Lacroix, P., Huanca, J., Angel, L., Taipe, E.: Data Repository: Time-of-failure prediction of the Achoma landslide, Peru, from high frequency Planetscope satellites. Dataset distributed on Zenodo: 10.5281/zenodo.7866962</p>
Psychometric Properties of the Maslach Burnout Inventory in Healthcare Professionals, Ancash Region, Peru
<p><strong>Background:</strong> Burnout syndrome (BS) among healthcare professionals in Peru demands immediate attention. Consequently, there is a need for a validated and standardized instrument to measure and address it effectively. This study aimed to determine the psychometric properties of the Maslach Burnout Inventory (MBI) among healthcare professionals in the Ancash region of Peru.</p> <p><strong>Methods:</strong> Using an instrumental design, this study included 303 subjects of both sexes (77.56% women), ranging in age from 22 to 68 years (M = 44.46, SD = 12.25), selected via purposive non-probability sampling. Appropriate content validity, internal structure validity, and item internal consistency were achieved through confirmatory factor analysis, and discriminant validity for the three dimensions was obtained. Evidence of convergent validity was found for the Emotional Exhaustion (EE) and Personal Accomplishment (PA) dimensions, with reliability values (ω > .75).</p> <p><strong>Results:</strong> The EE and PA dimensions exhibited acceptable levels of reliability (ω and α > .80). However, the Depersonalization (DP) dimension demonstrated significantly lower reliability (α < .60 and ω < .50).</p> <p><strong>Conclusions:</strong> A correlated three-factor model was confirmed, with most items presenting satisfactory factor loadings and inter-item correlations. Nonetheless, convergent validity was not confirmed for the DP dimension.</p> <p><strong>Keywords: </strong>Burnout; Psychometrics; Validity; Reliability; Healthcare Professionals.</p>
Leaf traits plus growth and dieback data for cloud forest epiphytes in a cloud exclusion treatment at Wayqecha Biological Station, Peru
Morphological traits [specific leaf area, stomatal length and density, leaf thickness, cuticle thickness and hydrenchymal layer thickness] and physiological traits [stomatal conductance, minimum leaf conductance and foliar water uptake capacity] along with pressure volume curves were measured at the Wayqecha Biological Station, Peru. Vascular epiphytes were sampled from a control plot and fog reduction treatment plot constructed from two 30 m tall aluminum towers, 40 m apart with panels of polyethylene mesh strung between the towers. Measurements of leaf morphological traits were taken in June-July 2022 in the control and treatment plots to assess plasticity to fog reductionin the fifth year of the experiment. Samples of branches and leaves for each individual approximately 1-2 meters off the ground were collected in the plot, close enough to the curtain to maximize any effects of fog interception. Growth and dieback data were also collected species of vascular and non-vascular epiphytes attached to wooden transplant boards in the control and treatment plot in 2017. Rates of growth and dieback were recorded for vascular epiphytes from 2017-2019 and for non-vascular epiphytes from 2018-2019. The 2017 data collection took place in November while data for 2018 and 2019 were collected in June.
Flooded forest plot sampling in Peru
In order to better understand how flooding and gap formation affect Amazonian rainforests, I set up plots both in three major forest types that differed by flooding duration (referred to here as dry, wet, very wet) and in their respective gaps. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Fig. 1 in Pseudotelegeusis meloi sp. nov., the first Telegeusinae from Peru (Coleoptera: Omethidae, Telegeusinae)
Fig. 1. Pseudotelegeusis meloi sp. nov., paratype from Mazuko DZUP 458.569. A. Habitus, dorsal view; B. Habitus, lateral view. C. Antenna, lateral view. D. Head, dorsal view. E. Pronotum, dorsal view. F. Left elytron, dorsal view.
FIG. 50 in Mystacodon selenensis, the earliest known toothed mysticete (Cetacea, Mammalia) from the late Eocene of Peru: anatomy, phylogeny, and feeding adaptations
FIG. 50. — Lateral view of the right pelvic bones of some extant mysticetes. A, Balaenoptera musculus; B, Balaenoptera musculus; C, Megaptera novaeangliae; D, E, Balaena mysticetus. The iliac, pubic and ischial portions are, respectively, in blue, yellow and green. Modified from Struthers (1893).
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