This dataset provides climatological aggregation of aerosol remote sensing data over 22 years (2000-2021) in Kuopio, Finland. Level 3 climatological datasets are obtained as aggregated products from t…
This dataset provides climatological aggregation of aerosol remote sensing data over 22 years (2000-2021) in Kuopio, Finland. Level 3 climatological datasets are obtained as aggregated products from the ACTRIS/EARLINET fully quality controlled (QC) aerosol optical products (i.e. Level 2 products). In particular, this release considers only data fully compliant to the ACTRIS/EARLINET QC procedure v4.0 [https://earlinet.eu/wp-content/uploads/2025/03/EARLINET_QC_v4_0_20250225.pdf].
Two types of data are released: profile values and integrated quantities. For each type of data, four different temporal aggregations are provided: seasonal, annual, normal seasonal, normal monthly.
ACTRIS/EARLINET Level 3 2000-2021 climatological dataset over Bucharest, Romania
October, 2026 • Dataset
Nicolae, Doina, Belegante, Livio, Radu, Cristian, Pirloaga, Rarzvan, National Institute Of Research And Development For Optoelectronicset al.
This dataset provides climatological aggregation of aerosol remote sensing data over 22 years (2000-2021) in Bucharest, Romania. Level 3 climatological datasets are obtained as aggregated products fro…
This dataset provides climatological aggregation of aerosol remote sensing data over 22 years (2000-2021) in Bucharest, Romania. Level 3 climatological datasets are obtained as aggregated products from the ACTRIS/EARLINET fully quality controlled (QC) aerosol optical products (i.e. Level 2 products). In particular, this release considers only data fully compliant to the ACTRIS/EARLINET QC procedure v4.0 [https://earlinet.eu/wp-content/uploads/2025/03/EARLINET_QC_v4_0_20250225.pdf].
Two types of data are released: profile values and integrated quantities. For each type of data, four different temporal aggregations are provided: seasonal, annual, normal seasonal, normal monthly.
Reproducibility Code for "When Does a Pathway Score Preserve a Mediated Effect? Aggregation Geometry, Minimax Adequacy, and Gap Inference for High-Dimensional Mediation"
October, 2026 • Software
Hait, Subir
Version 1.0.2 of the R reproducibility code and frozen reference results accompanying the manuscript "When Does a Pathway Score Preserve a Mediated Effect? Aggregation Geometry, Minimax Adequacy, and …
Version 1.0.2 of the R reproducibility code and frozen reference results accompanying the manuscript "When Does a Pathway Score Preserve a Mediated Effect? Aggregation Geometry, Minimax Adequacy, and Gap Inference for High-Dimensional Mediation". The repository reproduces the analysis from the processed TCGA LUAD stage-1 object onward, including simulations, the empirical application, genome-wide audit, independent cross-screened audit, figure generation, and 48-check numerical verification. Raw and processed patient-level TCGA data are not redistributed.
ACTRIS/EARLINET Level 3 2000-2021 climatological dataset over Cabauw, Netherlands
October, 2026 • Dataset
Apituley, Arnoud, Wilson, Keith M., Alves Gouveia, Diego, Royal Netherlands Meteorological Institute, Mona, Luciaet al.
This dataset provides climatological aggregation of aerosol remote sensing data over 22 years (2000-2021) in Cabauw, Netherlands. Level 3 climatological datasets are obtained as aggregated products fr…
This dataset provides climatological aggregation of aerosol remote sensing data over 22 years (2000-2021) in Cabauw, Netherlands. Level 3 climatological datasets are obtained as aggregated products from the ACTRIS/EARLINET fully quality controlled (QC) aerosol optical products (i.e. Level 2 products). In particular, this release considers only data fully compliant to the ACTRIS/EARLINET QC procedure v4.0 [https://earlinet.eu/wp-content/uploads/2025/03/EARLINET_QC_v4_0_20250225.pdf].
Two types of data are released: profile values and integrated quantities. For each type of data, four different temporal aggregations are provided: seasonal, annual, normal seasonal, normal monthly.
This dataset provides climatological aggregation of aerosol remote sensing data over 22 years (2000-2021) in Naples, Italy. Level 3 climatological datasets are obtained as aggregated products from the…
This dataset provides climatological aggregation of aerosol remote sensing data over 22 years (2000-2021) in Naples, Italy. Level 3 climatological datasets are obtained as aggregated products from the ACTRIS/EARLINET fully quality controlled (QC) aerosol optical products (i.e. Level 2 products). In particular, this release considers only data fully compliant to the ACTRIS/EARLINET QC procedure v4.0 [https://earlinet.eu/wp-content/uploads/2025/03/EARLINET_QC_v4_0_20250225.pdf].
Two types of data are released: profile values and integrated quantities. For each type of data, four different temporal aggregations are provided: seasonal, annual, normal seasonal, normal monthly.
ACTRIS/EARLINET Level 3 2000-2021 climatological dataset over Granada, Spain
October, 2026 • Dataset
Alados-Arboledas, Lucas, Guerrero-Rascado, Juan Luis, Navas-Guzman, Francisco, Bravo-Aranda, Juan Antonio, Granados-Munoz, Maria Joseet al.
This dataset provides climatological aggregation of aerosol remote sensing data over 22 years (2000-2021) in Granada, Spain. Level 3 climatological datasets are obtained as aggregated products from th…
This dataset provides climatological aggregation of aerosol remote sensing data over 22 years (2000-2021) in Granada, Spain. Level 3 climatological datasets are obtained as aggregated products from the ACTRIS/EARLINET fully quality controlled (QC) aerosol optical products (i.e. Level 2 products). In particular, this release considers only data fully compliant to the ACTRIS/EARLINET QC procedure v4.0 [https://earlinet.eu/wp-content/uploads/2025/03/EARLINET_QC_v4_0_20250225.pdf].
Two types of data are released: profile values and integrated quantities. For each type of data, four different temporal aggregations are provided: seasonal, annual, normal seasonal, normal monthly.
ACTRIS/EARLINET Level 3 2000-2021 climatological dataset over Palaiseau, France
October, 2026 • Dataset
Pietras, Christophe, Haeffelin, Martial, Lapouge, Florian, Delville, Patricia, Centre National De La Recherche Scientifique-Institut Pierre Simon Laplaceet al.
This dataset provides climatological aggregation of aerosol remote sensing data over 22 years (2000-2021) in Palaiseau, France. Level 3 climatological datasets are obtained as aggregated products from…
This dataset provides climatological aggregation of aerosol remote sensing data over 22 years (2000-2021) in Palaiseau, France. Level 3 climatological datasets are obtained as aggregated products from the ACTRIS/EARLINET fully quality controlled (QC) aerosol optical products (i.e. Level 2 products). In particular, this release considers only data fully compliant to the ACTRIS/EARLINET QC procedure v4.0 [https://earlinet.eu/wp-content/uploads/2025/03/EARLINET_QC_v4_0_20250225.pdf].
Two types of data are released: profile values and integrated quantities. For each type of data, four different temporal aggregations are provided: seasonal, annual, normal seasonal, normal monthly.
A lightweight, vectorized toolkit for extracting structured information from URLs in R. Includes pipe-friendly functions for parsing, normalizing protocols, extracting domains, and constructing clean …
A lightweight, vectorized toolkit for extracting structured information from URLs in R. Includes pipe-friendly functions for parsing, normalizing protocols, extracting domains, and constructing clean URLs. Domain and public-suffix extraction is delegated to the pslr package, which implements the Public Suffix List from publicsuffix.org. Punycode and IDNA encoding is handled by the punycoder package.
Presentation for the Data Modelling Days 2023 (1 December 2023).
The video is available on Youtube: https://www.youtube.com/watch?v=rIzYTNYQfBQ
The content is mainly based on my paper Conflations…
Presentation for the Data Modelling Days 2023 (1 December 2023).
The video is available on Youtube: https://www.youtube.com/watch?v=rIzYTNYQfBQ
The content is mainly based on my paper Conflations and duplications in Wikidata items: causes, detection, solutions, and issues presented at the 4th Wikidata Workshop (17 November 2023) and on Wikidata:WikiProject Duplicates/VIAF members.
Originally published at: https://commons.wikimedia.org/wiki/File:DMD2023_-_Conflations_and_duplications.pdf
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