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Publication Year: 2023

1,801 to 1,810 of 1,830 Results

N6_R1.fastq.gz Mar 16, 2023 - Comparison of MDA methods Archivo Gzip - 2,7 GB - MD5: 7597dff36c78f877dc61641638ce5759 DataDatos piMDA+D sample forward reads
N6_R2.fastq.gz Mar 16, 2023 - Comparison of MDA methods Archivo Gzip - 2,6 GB - MD5: 05779bfec918e8ee69e9b572d6f69023 DataDatos piMDA+D sample reverse reads
readme_en_piMDA.txt Mar 16, 2023 - Comparison of MDA methods Texto plano - 4,4 KB - MD5: 5610bb800d6c25e106aeea69bd96236d DocumentaciónDocumentation
xchem_public-1.0.0.zip Feb 25, 2023 - XChem_v1 Archivo ZIP - 49,5 MB - MD5: ddad8c755855badf5d2f125028396f73 CodeCódigo
Catalogue of residential buildings and classification according to seismic vulnerability in the city of Murcia (Spain). Feb 8, 2023 - Universidad Politécnica de Madrid Meyers-Angulo, Eduardo; Martínez-Cuevas, Sandra; Gaspar-Escribano, Jorge, 2023, "Catalogue of residential buildings and classification according to seismic vulnerability in the city of Murcia (Spain).", https://doi.org/10.21950/HLF2US, e-cienciaDatos, V1 The 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...
Buildings_01.csv Feb 8, 2023 - Catalogue of residential buildings and classification according to seismic vulnerability in the city of Murcia (Spain). Valores separados por comas - 747,6 KB - MD5: 7bedb73bf5ff11e75d0a1a796b6d3d36 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 Feb 8, 2023 - Catalogue of residential buildings and classification according to seismic vulnerability in the city of Murcia (Spain). Valores separados por comas - 8,5 KB - MD5: 7132add4f3f8d444cf5313f78f4b293c v_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.
readme-en.txt Feb 8, 2023 - Catalogue of residential buildings and classification according to seismic vulnerability in the city of Murcia (Spain). Texto plano - 9,8 KB - MD5: 5a95596542e3301c4e7295e917695625
RESPOND-HCWs - Mental health outcomes Jan 26, 2023 - Universidad Autónoma de Madrid Mediavilla, Roberto, 2023, "RESPOND-HCWs - Mental health outcomes", https://doi.org/10.21950/HN1HNO, e-cienciaDatos, V2 RESPOND is an EU funded research project running from 2020 to 2023. The project aims to identify which groups are most at risk for adverse mental health effects due to the COVID-19 pandemic, as well as to understand what determines that risk. In Spain, we conducted a randomised controlled trial among healthcare workers (HCWs) with psychological dis...
respond_hcws_outcomes_anonymised_codebook.txt Jan 26, 2023 - RESPOND-HCWs - Mental health outcomes Texto plano - 3,7 KB - MD5: 9dcc1bddf8f1f0f7a00d3e4de772f935 DocumentaciónDocumentation Codebook of the RESPOND-HCWs anonymised dataset

N6_R1.fastq.gz

Mar 16, 2023 - Comparison of MDA methods

Archivo Gzip - 2,7 GB -

DataDatos

piMDA+D sample forward reads

N6_R2.fastq.gz

Mar 16, 2023 - Comparison of MDA methods

Archivo Gzip - 2,6 GB -

DataDatos

piMDA+D sample reverse reads

readme_en_piMDA.txt

Mar 16, 2023 - Comparison of MDA methods

Texto plano - 4,4 KB -

DocumentaciónDocumentation

xchem_public-1.0.0.zip

Feb 25, 2023 - XChem_v1

Archivo ZIP - 49,5 MB -

CodeCódigo

Catalogue of residential buildings and classification according to seismic vulnerability in the city of Murcia (Spain).

Feb 8, 2023 - Universidad Politécnica de Madrid

Meyers-Angulo, Eduardo; Martínez-Cuevas, Sandra; Gaspar-Escribano, Jorge, 2023, "Catalogue of residential buildings and classification according to seismic vulnerability in the city of Murcia (Spain).", https://doi.org/10.21950/HLF2US, e-cienciaDatos, V1

The 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...

Buildings_01.csv

Feb 8, 2023 - Catalogue of residential buildings and classification according to seismic vulnerability in the city of Murcia (Spain).

Valores separados por comas - 747,6 KB -

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

Feb 8, 2023 - Catalogue of residential buildings and classification according to seismic vulnerability in the city of Murcia (Spain).

Valores separados por comas - 8,5 KB -

v_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.

readme-en.txt

Feb 8, 2023 - Catalogue of residential buildings and classification according to seismic vulnerability in the city of Murcia (Spain).

Texto plano - 9,8 KB -

RESPOND-HCWs - Mental health outcomes

Jan 26, 2023 - Universidad Autónoma de Madrid

Mediavilla, Roberto, 2023, "RESPOND-HCWs - Mental health outcomes", https://doi.org/10.21950/HN1HNO, e-cienciaDatos, V2

RESPOND is an EU funded research project running from 2020 to 2023. The project aims to identify which groups are most at risk for adverse mental health effects due to the COVID-19 pandemic, as well as to understand what determines that risk. In Spain, we conducted a randomised controlled trial among healthcare workers (HCWs) with psychological dis...

respond_hcws_outcomes_anonymised_codebook.txt

Jan 26, 2023 - RESPOND-HCWs - Mental health outcomes

Texto plano - 3,7 KB -

DocumentaciónDocumentation

Codebook of the RESPOND-HCWs anonymised dataset

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