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Federico-Tena World Population Historical Database : Cape Verde (Portuguese Africa)
No full textProject developed by Giovanni Federico (New York University Abu Dhabi) and Antonio Tena Junguito (Universidad Carlos III de Madrid). Dataset: Cape Verde (Portuguese Africa
Cu PAS data
No full textThis part of the project consists of the characterization of a Cu-Y alloy through Positron Annihilation Spectroscopy (PLS and CDB).
Origin software files containing raw and processed data and graphical representations
Servando Rodríguez. (San Jorge de Alor). Familia
No full textLas familias tenían muchos hijos. Si una mujer tenía muchos hijos y su hermana no podía concebir, alguno de sus descendientes se criaba con esta, como si fuesen hijos suyos. Ahora ha descendido mucho el número de nacimientos. También afectó mucho a Olivenza la emigración, porque mucha gente se quedó allí.As famílias tinham muitos filhos. Se uma mulher tinha muitas crianças e a sua irmã não podia conceber, alguns dos seus descendentes criavam-se com ela, como se fossem os seus próprios filhos. Agora o número de nascimentos diminuiu muito. A emigração também afectou muito Olivenza, porque muitas pessoas ficaram lá.Families had numerous children. If a woman had many babies and her sister could not conceive, some of her offspring were raised with her, as if they were her own children. Now the number of births has decreased greatly. Emigration also affected Olivenza a lot, because many people stayed there
Federico-Tena World Population Historical Database : Norway
No full textProject developed by Giovanni Federico (New York University Abu Dhabi) and Antonio Tena Junguito (Universidad Carlos III de Madrid). Dataset: Norwa
Supplementary material for the paper "The Predominance of Relational Nature and Physical Capacity in Spontaneous Dimensions of Animal Species"
No full textWhereas a variety of attributes has been empirically associated to the social perception of animals, the identification of the underlying fundamental dimensions has been infrequent. Rooted in the stereotype content conceptualization and using multidimensional scaling, we explore the dimensions in which people organize animal targets based on how humans relate to them. Asking about the similarity in which humans relate to animals, participants rated thirty-four salient animals (from a pilot study; N = 76) using Likert scales in Study 1 (N = 108) and grouping similar animals in Study 2 (N = 112). A 3-dimension scaling solution fitted adequately the data (S-Stress
Data from pilot and three studies. Pilot Study: List of salient animal species through an open-ended question (N = 76 Spanish college participants).
Study 1: Similarity measures (7 point Likert-type scale, 1 is completely different, 7 completely similar) between 34 animal species based on how people relate to them (N = 108 Spanish college participants).
Study 2: Similarity measures (card sorting task, 0 if the species do not appear together, 1 if they do appear together) between 34 animal species based on how people relate to them (N = 112 college participants).
Study 3: Ratings (7 point Likert-type scale) of the 34 animal species in 11 relevant attributes (N = 176 Spanish college participants).
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Federico-Tena World Population Historical Database : Italy
No full textProject developed by Giovanni Federico (New York University Abu Dhabi) and Antonio Tena Junguito (Universidad Carlos III de Madrid). Dataset: Ital
Design and Optimisation of Sustainable Sample Treatments Based on Ultrasound-Assisted Extraction and Strong Cation-Exchange Purification with Functionalised SBA-15 for Opium Alkaloids in Ground Poppy Seeds
No full textThis database includes the results of the optimisation of the analytical methodology, firstly the design of experiments
carried out to optimise the extraction step, specifically with ultrasound-assisted extraction, and then the purification step by
solid phase extraction. Then all the results obtained from the validation of the analytical methodology and finally the concentrations
of opium alkaloids found in samples of ground poppy seeds using the proposed analytical methodology are shown
XChem_v1
No full textThis dataset contains the first release of XChem code as registered at the Madrid Registry of Intelectual property (reg. num. 16/2022/2643).
It includes the source code, installation instructions, manuals, tutorials and example
Federico-Tena World Population Historical Database : Qatar (Ottoman Empire)
No full textProject developed by Giovanni Federico (New York University Abu Dhabi) and Antonio Tena Junguito (Universidad Carlos III de Madrid). Dataset: Qatar (Ottoman Empire
Catalogue of residential buildings and classification according to seismic vulnerability in the city of Murcia (Spain).
No full textThe residential building catalogue and seismic vulnerability classification is a supplementary dataset associated with the paper entitled “Classifying Buildings According to Seismic Vulnerability Using Cluster-ANN Techniques. Applied to the City of Murcia, Spain
The goal is to identify building patterns in construction typologies (CTs), related to both structural and non-structural elements that make up a building, called Building Typologies (BTs). The analysis identifies urban modifiers associated with different CTs, and using machine learning techniques, different building configurations are obtained, which are defined as Building Cluster Typologies (BCT).
The results of the BCT identification include the definition of BCT attributes, their representativeness in the study area, the spatial distribution and seismic vulnerability. 11 BCTs associated with 5 CTs are identified, as well as the distribution of seismic vulnerability ranges at the census section scale in the city of Murcia.
In conclusion, the identification of BCTs allows for exposure assessments that take into account the particular characteristics of buildings, grouped according to specific configurations, and facilitates future seismic vulnerability evaluations.
4. Description of the dataset
The dataset is the final data from the research titled: “Classifying Buildings According to Seismic Vulnerability Using Cluster-ANN Techniques. Applied to the City of Murcia, Spain.”
The database is the result of the identification of the different CTs and BCTs in the city of Murcia. The data is organized into 7631 records of residential buildings, which have urban modifier attributes associated with each CT. The combination of CTs and urban modifiers define the different BCTs. In total, for each building record (rows), a CT, the year of construction, ten urban modifiers, and the BCT identification result are associated (in columns).
In addition, the distribution of the Seismic Vulnerability Index (Iv) of the buildings at the census blocks scale is provided. The Iv is expressed in intervals. Minimum, maximum, and average values are provided.
1. Methodology
The methodology for obtaining the present database contains several steps:
1. Extraction of building data from the Spanish Cadastre (https://www.sedecatastro.gob.es/) and configuration of an initial database.
2. Identification of construction typologies (CT) using a typology membership probability matrix for Murcia (RISMUR, 2014).
3. Error detection and correction with remote field work.
4. Assignation of urban modifiers of the buildings in the study area (Martinez-Cuevas and Gaspar-Escribano 2016; Martinez-Cuevas et al., 2017) with remote field work in combination with different GIS processes (Lantada et. al. 2010). The coding of new attributes (urban modifiers) was done according to the GEM taxonomy (https://taxonomy.openquake.org/).
5. Application of a Two-Step Cluster analysis identify clusters. The resulting clusters (CTs with the corresponding urban modifiers) are called Building Cluster Typologies (BCT). The BCT field was assigned to every record of the database.
6. Assignation of vulnerability index (Iv) value to each building (Benedetti and Petrini, 1984; Angeletti et al., 1988; Milutinovic and Tredafiloski, 2003; Lagomarsino and Giovinazzi 2006) and calculation of the average Iv value for the census block level.
FILES
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The dataset consists of two files in csv format.
-Buildings_01.csv: database with 7631 building records. Each record consists of an ID, centroid coordinates in ETRS_1989_UTM_Zone_30N and thirteen attributes.
-Iv_CB_02.csv: database with 158 records corresponding to the census blocks of the study area. Each record consists of an ID, centroid coordinates in ETRS_1989_UTM_Zone_30N, census block code and three attributes.
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