cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/b8h39fbd5w.1
title: Knowledge, attitudes and practices on antibiotics and antibiotic resistance among university students in the health sector

description: Antimicrobial resistance is the phenomenon by which a microorganism ceases to be affected by an antimicrobial to which it was previously exposed. microorganism is no longer affected by an antimicrobial to which it was previously sensitive. was sensitive to. Antimicrobial resistance is a public health problem, due to the multiple complications it may complications it can lead to. Generally, health care trainees have a much higher health care students are generally much more knowledgeable about the use of antibiotics than the general community. the general community, but not enough to prevent further increases in antibiotic resistance. further increase in resistance. Studies have been conducted to investigate this problem among among future health care workers have been conducted and found inadequate knowledge. inadequate knowledge, therefore, a good education in their training will have a positive impact on resistance. will have a positive impact on antibiotic resistance during professional practice. professional practice. Objective: To evaluate knowledge, attitudes and practices on antibiotics, antibiotic use and antibiotic resistance. and antibiotic resistance in medical and nursing students of a higher education institution in Barranquilla, Colombia. an institution of higher education in Barranquilla (Colombia). Key words: Antibiotics, Antimicrobial resistance, Knowledge, Attitudes, Practices Methods: A descriptive, cross-sectional, observational, survey-type, descriptive, cross-sectional, observational study was sample of 530 students distributed in 315 medical students and 215 nursing students of the and 215 nursing students of the institution of higher education under study, during the second semester of 2022. the institution of higher education under study, during the second semester of 2022. It demographic variables and variables related to knowledge, attitudes and practices about antibiotics, antibiotic use and antibiotic resistance were studied. A previously designed and validated questionnaire was applied, which had four sections. The first section corresponded to demographic information of the study subjects. The second section included seven true-false questions that measured the level of knowledge related to antibiotics.
DOI: 10.25574/45170
title: Chandra X-ray Observatory ObsId 45170
DOI: 10.5281/zenodo.15374433
title: Hectometric-scale modelling of the mixed layer in an urban region evaluated with a dense LiDAR-ceilometer network: Part II

description: In support of article submitted to Weather and Climate Dynamics: Hectometric-scale modelling of the mixed layer in an urban region evaluated with a dense LiDAR-ceilometer network

Descriptions of all files for Parts I & II are contained in readme.txt (Part I)

Part I - Observations data, materials relating to MMLH algorithm, scripts used to generate all figures: https://zenodo.org/uploads/15365634

Part II - model input and output data that were used for figures: https://zenodo.org/uploads/15374434
DOI: 10.5281/zenodo.15374434
title: Hectometric-scale modelling of the mixed layer in an urban region evaluated with a dense LiDAR-ceilometer network: Part II

description: In support of article submitted to Weather and Climate Dynamics: Hectometric-scale modelling of the mixed layer in an urban region evaluated with a dense LiDAR-ceilometer network

Descriptions of all files for Parts I & II are contained in readme.txt (Part I)

Part I - Observations data, materials relating to MMLH algorithm, scripts used to generate all figures: https://zenodo.org/uploads/15365634

Part II - model input and output data that were used for figures: https://zenodo.org/uploads/15374434
DOI: 10.15468/dl.rjedcz
title: Occurrence Download

description: A dataset containing 96 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((-74.985 -8.223913, -75.055989 -8.229473, -75.125236 -8.246015, -75.191042 -8.273134000000001, -75.251789 -8.310162999999999, -75.305986 -8.356194, -75.352299 -8.410095999999999, -75.38958599999999 -8.470545, -75.416927 -8.536054999999999, -75.433645 -8.605016000000001, -75.439322 -8.67573, -75.433813 -8.746456, -75.41724600000001 -8.815454000000001, -75.39002600000001 -8.881023000000001, -75.35281500000001 -8.941546000000001, -75.306529 -8.99553, -75.252306 -9.041643000000001, -75.191481 -9.078747, -75.125556 -9.105924, -75.056157 -9.122503999999999, -74.985 -9.128076, -74.913843 -9.122503999999999, -74.844444 -9.105924, -74.778519 -9.078747, -74.71769399999999 -9.041643000000001, -74.663471 -8.99553, -74.61718500000001 -8.941546000000001, -74.57997400000001 -8.881023000000001, -74.55275399999999 -8.815454000000001, -74.536187 -8.746456, -74.53067799999999 -8.67573, -74.536355 -8.605016000000001, -74.553073 -8.536054999999999, -74.580414 -8.470545, -74.617701 -8.410095999999999, -74.66401399999999 -8.356194, -74.718211 -8.310162999999999, -74.778958 -8.273134000000001, -74.844764 -8.246015, -74.914011 -8.229473, -74.985 -8.223913))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 96 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028459-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ektps6
title: Occurrence Download

description: A dataset containing 243 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Opisthopora"
 ]
}

 The dataset includes 243 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028455-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xvkz63
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is University of Texas, Biodiversity Center, Entomology Collection (UTIC)",
 "Geometry POLYGON((-97.17588 30.08275,-97.15701 30.08275,-97.15701 30.10232,-97.17588 30.10232,-97.17588 30.08275))",
 "TaxonKey is Pogonomyrmex barbatus",
 "Year 2017-2025"
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028458-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/ssvn96xrd3
title: Direccionadores de futuro en el turismo de naturaleza

description: Objetivo: Identificar los direccionadores de futuro en el turismo de naturaleza para proporcionar una ruta que oriente la gestión de los distintos actores sociales del sector turístico en el departamento del Quindío (Colombia). Método: La investigación fue cualitativa, de tipo correlacional, se recolectó la información primaria mediante talleres y tres técnicas de prospectiva estratégica como: Factores de cambio, Análisis estructural y Ejes de Schwartz, que permitieron la convergencia de 40 actores estratégicos (Universidad, Empresa, Estado y Sociedad). Resultados: Se encontró que los direccionadores de futuro son la gestión público-privada y el desarrollo turístico, los cuales se deben fortalecer mediante procesos de construcción colectiva de futuro. Dentro de la literatura se encontró que hay estudios en el contexto nacional e internacional que evidencian una limitada gestión de autoridades turísticas y la necesidad de promover políticas que articulen el sector privado con las comunidades. Por otra parte, hay investigaciones enfocadas en el desarrollo económico local para la preservación del patrimonio natural y cultural. Conclusiones: El turismo de naturaleza en el Quindío tiene un enorme potencial en la medida en que se logre la convergencia entre los actores, cuya influencia y gobernabilidad les va a permita impulsar iniciativas con criterios de sostenibilidad.
DOI: 10.5281/zenodo.15365633
title: Hectometric-scale modelling of the mixed layer in an urban region evaluated with a dense LiDAR-ceilometer network: Part I

description: In support of article submitted to Weather and Climate Dynamics: Hectometric-scale modelling of the mixed layer in an urban region evaluated with a dense LiDAR-ceilometer network

Descriptions of all files for Parts I & II are contained in readme.txt (Part I)

Part I - Observations data, materials relating to MMLH algorithm, scripts used to generate all figures: https://zenodo.org/uploads/15365634

Part II - model input and output data that were used for figures: https://zenodo.org/uploads/15374434
DOI: 10.5281/zenodo.15365634
title: Hectometric-scale modelling of the mixed layer in an urban region evaluated with a dense LiDAR-ceilometer network: Part I

description: In support of article submitted to Weather and Climate Dynamics: Hectometric-scale modelling of the mixed layer in an urban region evaluated with a dense LiDAR-ceilometer network

Descriptions of all files for Parts I & II are contained in readme.txt (Part I)

Part I - Observations data, materials relating to MMLH algorithm, scripts used to generate all figures: https://zenodo.org/uploads/15365634

Part II - model input and output data that were used for figures: https://zenodo.org/uploads/15374434
DOI: 10.17026/ar/5xeogs
title: PAN-00104829 - coin/coin-related, Constantinus I en zonen (306-361), naar, nummus

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00104829&lt;/p&gt;
description: Modified: 2025-05-06T09:55:54+02:00
DOI: 10.17632/ssvn96xrd3.1
title: Direccionadores de futuro en el turismo de naturaleza

description: Objetivo: Identificar los direccionadores de futuro en el turismo de naturaleza para proporcionar una ruta que oriente la gestión de los distintos actores sociales del sector turístico en el departamento del Quindío (Colombia). Método: La investigación fue cualitativa, de tipo correlacional, se recolectó la información primaria mediante talleres y tres técnicas de prospectiva estratégica como: Factores de cambio, Análisis estructural y Ejes de Schwartz, que permitieron la convergencia de 40 actores estratégicos (Universidad, Empresa, Estado y Sociedad). Resultados: Se encontró que los direccionadores de futuro son la gestión público-privada y el desarrollo turístico, los cuales se deben fortalecer mediante procesos de construcción colectiva de futuro. Dentro de la literatura se encontró que hay estudios en el contexto nacional e internacional que evidencian una limitada gestión de autoridades turísticas y la necesidad de promover políticas que articulen el sector privado con las comunidades. Por otra parte, hay investigaciones enfocadas en el desarrollo económico local para la preservación del patrimonio natural y cultural. Conclusiones: El turismo de naturaleza en el Quindío tiene un enorme potencial en la medida en que se logre la convergencia entre los actores, cuya influencia y gobernabilidad les va a permita impulsar iniciativas con criterios de sostenibilidad.
DOI: 10.15468/dl.echkqq
title: Occurrence Download

description: A dataset containing 705303 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Populus tremula"
 ]
}

 The dataset includes 705303 records from 2681 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028394-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e201945
title: Data and Code for: "Tailoring Mentorship: Evidence on Diverse Needs and Application Patterns for High School Students"

description: This paper employs unique survey data from final year high school students in 57 Spanish schools to document patterns of declared interest in participation in a one-to-one mentoring program that matches them with university-educated individuals, actual provision of the required documentation for participation in the program, and preferences towards the characteristics of a potential mentor. We find that immigrants and individuals facing financial constraints are particularly likely to initially express an interest in the program, but are not more likely to eventually provide all required documents for participation. We also document that certain minorities (e.g., females and financially-constrained individuals) value particularly being matched with a mentor that shares these characteristics.
DOI: 10.3886/e201945v1
title: Data and Code for: "Tailoring Mentorship: Evidence on Diverse Needs and Application Patterns for High School Students"

description: This paper employs unique survey data from final year high school students in 57 Spanish schools to document patterns of declared interest in participation in a one-to-one mentoring program that matches them with university-educated individuals, actual provision of the required documentation for participation in the program, and preferences towards the characteristics of a potential mentor. We find that immigrants and individuals facing financial constraints are particularly likely to initially express an interest in the program, but are not more likely to eventually provide all required documents for participation. We also document that certain minorities (e.g., females and financially-constrained individuals) value particularly being matched with a mentor that shares these characteristics.
DOI: 10.15468/dl.fxf3yu
title: Occurrence Download

description: A dataset containing 391933 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Ireland, United Kingdom of Great Britain and Northern Ireland, Portugal, Spain, France, Germany, Belgium, Netherlands, Italy, Greece, Denmark, Norway, Sweden, Finland, Svalbard and Jan Mayen, Estonia, Latvia, Lithuania, Türkiye, Russian Federation, Belarus, Ukraine, Moldova, Republic of, Switzerland, Austria, Poland, Czechia, Hungary, Slovakia, Croatia, Romania, Bulgaria, Kazakhstan, Armenia, North Macedonia, Albania, Serbia, Montenegro, Kosovo, Bosnia and Herzegovina, Slovenia, Cyprus)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Scorzoneroides autumnalis (L.) Moench"
 ]
}

 The dataset includes 391933 records from 804 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021531-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.20731680
title: Active Control of Fuel Position in Opposed-Flow Strand Burner Experiments

description: This paper describes a new active method of controlling the position of the burning surface of a solid fuel strand in an opposed-flow burner experiment. This method is designed to avoid biases to the combustion process introduced by retaining wires and to avoid experimental delays caused by wire failures. Regression rates are presented for hydroxyl-terminated polybutadiene fuel strands burning in various oxidizer streams. The active control method uses a control loop composed of a diode laser, a photodiode, and a stepper motor. For comparison, tests were also performed using the commonly used passive control method of spring-loading the fuel against a retaining wire. This active control method can only be used at high values of oxidizer mass flux; at low mass flux, soot accumulation obstructs the laser beam. In passive control tests, the retaining wire conducts heat from the flame into the fuel and increases regression rate. The presence of the wire also modifies the extinction limits of the flame. A model was developed for regression rate as a function of oxidizer mass flux, oxidizer composition, and retaining wire diameter. This model can be used to correct future regression rate data for the bias introduced by retaining wires.
DOI: 10.15468/dl.w4u4sd
title: Occurrence Download

description: A dataset containing 601 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China",
 "TaxonKey is Toona sinensis (A.Juss.) M.Roem."
 ]
}

 The dataset includes 601 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021532-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10254684
title: The Automotive Visual Inspection Dataset (AutoVI): A Genuine Industrial Production Dataset for Unsupervised Anomaly Detection (v.0)

description: See the official website: https://autovi.utc.fr

Modern industrial production lines must be set up with robust defect inspection modules that are able to withstand high product variability. This means that in a context of industrial production, new defects that are not yet known may appear, and must therefore be identified.

On industrial production lines, the typology of potential defects is vast (texture, part failure, logical defects, etc.). Inspection systems must therefore be able to detect non-listed defects, i.e. not-yet-observed defects upon the development of the inspection system. To solve this problem, research and development of unsupervised AI algorithms on real-world data is required.

Renault Group and the Université de technologie de Compiègne (Roberval and Heudiasyc Laboratories) have jointly developed the Automotive Visual Inspection Dataset (AutoVI), the purpose of which is to be used as a scientific benchmark to compare and develop advanced unsupervised anomaly detection algorithms under real production conditions. The images were acquired on Renault Group's automotive production lines, in a genuine industrial production line environment, with variations in brightness and lighting on constantly moving components. This dataset is representative of actual data acquisition conditions on automotive production lines.

The dataset contains 3950 images, split into 1530 training images and 2420 testing images.

DisclaimerAll defects shown were intentionally created on Renault Group's production lines for the purpose of producing this dataset. The images were examined and labeled by Renault Group experts, and all defects were corrected after shooting.

LicenseCopyright © 2023-2024 Renault Group

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. To view a copy of the license, visit https://creativecommons.org/licenses/by-nc-sa/4.0/.

For using the data in a way that falls under the commercial use clause of the license, please contact us.

AttributionPlease use the following for citing the dataset in scientific work:

Carvalho, P., Lafou, M., Durupt, A., Leblanc, A., & Grandvalet, Y. (2023). The Automotive Visual Inspection Dataset (AutoVI): A Genuine Industrial Production Dataset for Unsupervised Anomaly Detection (v.0) [Dataset]. https://doi.org/10.5281/zenodo.10254684

ContactIf you have any questions or remarks about this dataset, please contact us at philippe.carvalho@utc.fr, meriem.lafou@renault.com, alexandre.durupt@utc.fr, antoine.leblanc@renault.com, yves.grandvalet@utc.fr.

Changelog



v0.1.1



Added ground truth segmentation maps

Fixed categorization of some images

Added new defect categories

Removed tube_fastening and kitting_cart

Removed duplicates in pipe_clip
DOI: 10.5281/zenodo.8099580
title: The Automotive Visual Inspection Dataset (AutoVI): A Genuine Industrial Production Dataset for Unsupervised Anomaly Detection (v.0)

description:  

 

NOTE: This version is deprecated, please use v1.0.0 instead!

 

 

Modern industrial production lines must be set up with robust defect inspection modules that are able to withstand high product variability. This means that in a context of industrial production, new defects that are not yet known may appear, and must therefore be identified.

On industrial production lines, the typology of potential defects is vast (texture, part failure, logical defects, etc.). Inspection systems must therefore be able to detect non-listed defects, i.e. not-yet-observed defects upon the development of the inspection system. To solve this problem, research and development of unsupervised AI algorithms on real-world data is required.

Renault Group and the Université de technologie de Compiègne (Roberval and Heudiasyc Laboratories) have jointly developed the Automotive Visual Inspection Dataset (AutoVI), the purpose of which is to be used as a scientific benchmark to compare and develop advanced unsupervised anomaly detection algorithms under real production conditions. The images were acquired on Renault Group's automotive production lines, in a genuine industrial production line environment, with variations in brightness and lighting on constantly moving components. This dataset is representative of actual data acquisition conditions on automotive production lines.

The dataset contains 6530 images, split into 2462 training images and 4068 testing images.

DisclaimerAll defects shown were intentionally created on Renault Group's production lines for the purpose of producing this dataset. The images were examined and labeled by Renault Group experts, and all defects were corrected after shooting.

LicenseCopyright © 2023 Renault Group

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. To view a copy of the license, visit https://creativecommons.org/licenses/by-nc-sa/4.0/.

For using the data in a way that falls under the commercial use clause of the license, please contact us.

AttributionPlease use the following for citing the dataset in scientific work:Carvalho, P., Durupt, A., Lafou, M., Grandvalet, Y., & Leblanc, A. (2023). The Automotive Visual Inspection Dataset (AutoVI): A Genuine Industrial Production Dataset for Unsupervised Anomaly Detection (v.0) [Dataset]. https://doi.org/10.5281/zenodo.8099580

ContactIf you have any questions or remarks about this dataset, please contact us at philippe.carvalho@utc.fr, alexandre.durupt@utc.fr, meriem.lafou@renault.com, yves.grandvalet@utc.fr, antoine.leblanc@renault.com.
DOI: 10.60797/irj.2024.143.29.1
title: Биохимические показатели в исследуемых группах

description: Международный научно-исследовательский журнал, Выпуск 5 (143) 2024
DOI: 10.3886/e201984
title: Data and Code for: "(Empirical) Bayes Approaches to Parallel Trends"

description: This is replication data and code for the paper "(Empirical) Bayes Approaches to Parallel Trends" by Soonwoo Kwon and Jonathan Roth, published in AEA P&P.
DOI: 10.3886/e201984v1
title: Data and Code for: "(Empirical) Bayes Approaches to Parallel Trends"

description: This is replication data and code for the paper "(Empirical) Bayes Approaches to Parallel Trends" by Soonwoo Kwon and Jonathan Roth, published in AEA P&P.
DOI: 10.60797/irj.2024.143.103.2
title: Экспериментальная группа крыс, которым перорально вводили по 100 мг испытуемого образца Монадасила за 30 мин до эксперимента (1 день)

description: Международный научно-исследовательский журнал, Выпуск 5 (143) 2024
DOI: 10.15468/dl.btfq5g
title: Occurrence Download

description: A dataset containing 4464 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is Spain",
 "TaxonKey is Cetacea",
 "Year 1985-2024"
 ]
}

 The dataset includes 4464 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021538-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.