cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.16495219
title: Quantitative results corresponding to the work "Evaluating the effectiveness of nasoalveolar molding in the management of children with unilateral cleft lip and palate: a cohort study"

description: This database corresponds to the measurements obtained from patients with unilateral cleft lip and palate (UCLP) subjected or not to nasoalveolar molding treatment. Details are explained in the manuscript "Evaluating the effectiveness of nasoalveolar molding in the management of children with unilateral cleft lip and palate: a cohort study", whose abstract is shown here:

Background: Children affected by unilateral cleft lip and palate (UCLP) represent a therapeutic challenge requiring the development of novel therapies, such as the implant of a bioengineered tissue -BIOCLEFT- or the use of nasoalveolar molding (NAM). The objective of this work was to evaluate the effects of NAM on the surgical and aesthetic outcomes of children with UCLP. Methods: 36 children with UCLP treated at a Craniofacial Malformations Management Unit were evaluated, including 23 patients treated with presurgical NAM followed by palate surgical correction (NAM group), and 13 patients treated surgically without previous NAM (non-NAM group). Measurements were obtained from each patient immediately before palate surgery, including four linear measurements: nasal ala projection length (NAPL), nasal dome height (NDH), superoinferior alar groove position (S-I AGP), and nasal dome position (M-L NDP), and two angular measurements: columellar deviation (CD) and nasal bridge deviation (NBD). Results: When NAM was used, a significant improvement of the basilar view linear measures of the patient’s nose was found, including the NAPL and NDH, and the frontal view linear measurement M-L NDP, but not S-I AGP. Significant improvements were also observed in the angular measurements of nasal symmetry CD and NBD. All these variables, except the S-I AGP significantly correlated with the treatment group, and two variables -NAPL and CD- significantly contributed to generate a predictive model developed using binary logistic regression. Conclusions: These findings support the use of NAM to efficiently improve the nasal symmetry and the presurgical outcomes of patients with UCLP.
DOI: 10.25919/95gr-1x56
title: Parkes observations for project P1183 semester 2025OCTS_07

description: After nearly three years of monitoring, comprising with the Parkes telescope and the FAST telescopes, FRB 20220529 is proven to be an extremely interesting repeater. It exhibits one of the longest activity durations and a potential ~200-day RM period. Due to frequent observations scheduled with both Parkes and FAST, an abrupt rotation measure (RM) flare has been observed in this source. This is the first detection of such an ``RM flare'' in a fast radio burst (FRB), suggesting that the source is in an environment with occasionally erupting coronal mass ejection. This presents a unique opportunity to study the eruption environment of FRBs and investigate the relation between burst activity and other burst parameters. If confirmed, the periodicity and the ``RM flare'' of FRB 20220529 would corroborate each other and become a ``smoking gun'' of the binary origin of FRB. In previous analysis, both Parkes and FAST observations have proven essential. While FAST's higher sensitivity has enabled the capture of many bursts, Parkes' wideband receiver has provided a good burst detection rate even during low-rate phases. Notably, during the RM flare, two high signal-to-noise ratio bursts from Parkes have been crucial in understanding the RM variations. To further investigate FRB 20220529, we have scheduled regular FAST observations every fortnight, monitoring the source for 20 minutes each time. Therefore, we also propose to monitor FRB 20220529 using the Parkes UWL receiver, ensuring high-time resolution and employing full-polarization observations.
DOI: 10.15468/dl.s35wbr
title: Occurrence Download

description: A dataset containing 3620 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Callosciurus finlaysonii"
 ]
}

 The dataset includes 3620 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035238-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17616036
title: Underwater images collected by  Scuba diving in Ifaty, Madagascar - 2022-10-30

description: This dataset was collected by  Scuba diving in Ifaty, Madagascar - 2022-10-30. 

            Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation.
            These images can be annotated and shared to train IA models which can in turn predict the objects on the images.
            We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps.

            This dataset is part of larger collection referencing numerous underwater and aerial images Seatizen Altas. 
            Methods, tools and scientific objectives are also described in a dedicated data paper.

            
                
                                       
                
                
 GPS information: 

                GPX file from Garmin watch.
            
                    
                

                
            

            
 Generic folder structure 
            
            YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number 
            ├── DCIM :  folder to store videos and photos depending on the media collected. 
            ├── GPS :  folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. 
            │   ├── BASE :  files coming from rtk station or any static positioning instrument. 
            │   └── DEVICE : files coming from the device. 
            ├── METADATA : folder with general information files about the session. 
            ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. 
            │   ├── BATHY :  output folder for bathymetry raw data extracted from mission logs. 
            │   ├── FRAMES :  output folder for georeferenced frames extracted from DCIM videos. 
            │   ├── IA :  destination folder for image recognition predictions. 
            │   └── PHOTOGRAMMETRY :  destination folder for reconstructed models in photogrammetry. 
            └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot,  mission plan etc.).       
            

            
 Software 
            All the raw data was processed using our worflow. All predictions were generated by our inference pipeline. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!
DOI: 10.5281/zenodo.17616066
title: Underwater images collected by  Scuba diving in Ifaty, Madagascar - 2022-10-30

description: This dataset was collected by  Scuba diving in Ifaty, Madagascar - 2022-10-30. 

            Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation.
            These images can be annotated and shared to train IA models which can in turn predict the objects on the images.
            We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps.

            This dataset is part of larger collection referencing numerous underwater and aerial images Seatizen Altas. 
            Methods, tools and scientific objectives are also described in a dedicated data paper.

            
                
                                       
                
                
 GPS information: 

                GPX file from Garmin watch.
            
                    
                

                
            

            
 Generic folder structure 
            
            YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number 
            ├── DCIM :  folder to store videos and photos depending on the media collected. 
            ├── GPS :  folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. 
            │   ├── BASE :  files coming from rtk station or any static positioning instrument. 
            │   └── DEVICE : files coming from the device. 
            ├── METADATA : folder with general information files about the session. 
            ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. 
            │   ├── BATHY :  output folder for bathymetry raw data extracted from mission logs. 
            │   ├── FRAMES :  output folder for georeferenced frames extracted from DCIM videos. 
            │   ├── IA :  destination folder for image recognition predictions. 
            │   └── PHOTOGRAMMETRY :  destination folder for reconstructed models in photogrammetry. 
            └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot,  mission plan etc.).       
            

            
 Software 
            All the raw data was processed using our worflow. All predictions were generated by our inference pipeline. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!
DOI: 10.15468/dl.cvs2pf
title: Occurrence Download

description: A dataset containing 7062 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Axis axis"
 ]
}

 The dataset includes 7062 records from 90 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035237-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2z7cs4
title: Occurrence Download

description: A dataset containing 38 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-109.4688 24.59913, -109.3188 24.59913, -109.3188 24.74913, -109.4688 24.74913, -109.4688 24.59913))"
 ]
}

 The dataset includes 38 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035239-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7fhbs9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Moxostoma lachneri",
 "HasCoordinate is true",
 "Geometry POLYGON((-78 12, -73 12, -73 0, -78 0, -78 12))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035240-251025141854904/datasets/export for details.
DOI: 10.15468/dl.ds46yv
title: Occurrence Download

description: A dataset containing 4738 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Spain, Portugal)",
 "DatasetKey is one of (CSIC-Real Jardín Botánico-Anthos. Sistema de Información de las Plantas de España, FloraCAT: Banco de datos de los cormófitos de Cataluña, Banco de Datos de la Biodiversidad de la Comunitat Valenciana, CSIC-Real Jardín Botánico-Colección de Plantas Vasculares (MA), Sistema de Información de la vegetación Ibérica y Macaronésica, Colección de plantas vasculares del herbario de la Universitat de València (VAL), MGC Herbarium of University of Malaga (Spain): MGC-Cormof dataset, Flora vascular de Mallorca, Illes Balears, Base de datos de plantas vasculares del País Vasco: ARAN-EH)",
 "TaxonKey is Asplenium trichomanes quadrivalens"
 ]
}

 The dataset includes 4738 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035241-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6te4qz
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-109.3188 24.59913, -109.1688 24.59913, -109.1688 24.74913, -109.3188 24.74913, -109.3188 24.59913))"
 ]
}

 The dataset includes 3 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035242-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ezdba7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Moxostoma macrolepidotum",
 "HasCoordinate is true",
 "Geometry POLYGON((-78 12, -73 12, -73 0, -78 0, -78 12))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035243-251025141854904/datasets/export for details.
DOI: 10.5281/zenodo.17615867
title: 当代中国政治文献译入译出的对等观差异——基于语料库的多维分析-附录

description: 本附录为论文”当代中国政治文献译入/译出的对等观差异:基于语料库的多维分析“的支撑材料,详细列出了研究所依据的71项语言特征的操作化定义、功能描述、示例及出处。
DOI: 10.5281/zenodo.17615868
title: 当代中国政治文献译入译出的对等观差异——基于语料库的多维分析-附录

description: 本附录为论文”当代中国政治文献译入/译出的对等观差异:基于语料库的多维分析“的支撑材料,详细列出了研究所依据的71项语言特征的操作化定义、功能描述、示例及出处。
DOI: 10.15468/dl.d5thtg
title: Occurrence Download

description: A dataset containing 56709 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Urtica dioica",
 "Year 2024-2024"
 ]
}

 The dataset includes 56709 records from 89 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035216-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sahhhj
title: Occurrence Download

description: A dataset containing 52 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-109.1688 24.59913, -109.0188 24.59913, -109.0188 24.74913, -109.1688 24.74913, -109.1688 24.59913))"
 ]
}

 The dataset includes 52 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035246-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ysph7c
title: Occurrence Download

description: A dataset containing 7008 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Portugal, Spain)",
 "DatasetKey is one of (Banco de Datos de la Biodiversidad de la Comunitat Valenciana, CSIC-Real Jardín Botánico-Anthos. Sistema de Información de las Plantas de España, EDP Foz-Tua: Vascular Flora – Ecological and Complentary Measures Monitoring Programs – Contruction Phase I [2012-2014], EDP Foz-Tua: Vascular Flora and Habitats – Ecological and Complementary Measures Monitoring Programs – Construction Phase II [2015-2016] and Flooding Phase [2016-2017], Localización de táxones botánicos de interés para la identificación de hábitats de la REDIAM (Secretaría General de Medio Ambiente, Agua y Cambio Climático), EDP Baixo Sabor: Construction and Reservoir Filling Phases – Vascular Flora and Habitats: species from prioritary conservation habitats - [2010-2014], FloraCAT: Banco de datos de los cormófitos de Cataluña, Colección de plantas vasculares del herbario de la Universitat de València (VAL), DIBA-Parc Natural del Montseny, Herbario de la Universidad de Sevilla)",
 "TaxonKey is Ceterach officinarum"
 ]
}

 The dataset includes 7008 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035247-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7dnupf
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Moxostoma pisolabrum",
 "HasCoordinate is true",
 "Geometry POLYGON((-78 12, -73 12, -73 0, -78 0, -78 12))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035248-251025141854904/datasets/export for details.
DOI: 10.34740/kaggle/dsv/13741362
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.e3zdym
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-109.0188 24.59913, -108.8688 24.59913, -108.8688 24.74913, -109.0188 24.74913, -109.0188 24.59913))"
 ]
}

 The dataset includes 18 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035250-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bjf387
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Moxostoma rupiscartes",
 "HasCoordinate is true",
 "Geometry POLYGON((-78 12, -73 12, -73 0, -78 0, -78 12))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035251-251025141854904/datasets/export for details.
DOI: 10.6084/m9.figshare.30626234
title: Global Daily Surface Soil Moisture Data from 2015-2020 generated by Multi-Collocation Fusion and Spatiotemporal Deep Learning

description: We used multiple collocation analysis and least-squares linear weighted averaging to combine soil moisture estimates from SMAP, AMSR2, ASCAT, and SMOS microwave missions and GLDAS, MERRA2, and ERA5-Land model simulations. We then used a ConvLSTM model to fill in the spatiotemporal gaps in the fused soil moisture data, ultimately obtaining a seamless daily global surface soil moisture dataset spanning from March 31, 2015 to December 31, 2020. Due to limited computational resources, we trained the data by continent, dividing each continent into 1~4 tiles. Therefore, the final results are presented as tile-based compressed packages for each continent. The files named "MCA" and "ConvLSTM" contain our codes.
DOI: 10.6084/m9.figshare.30626234.v1
title: Global Daily Surface Soil Moisture Data from 2015-2020 generated by Multi-Collocation Fusion and Spatiotemporal Deep Learning

description: We used multiple collocation analysis and least-squares linear weighted averaging to combine soil moisture estimates from SMAP, AMSR2, ASCAT, and SMOS microwave missions and GLDAS, MERRA2, and ERA5-Land model simulations. We then used a ConvLSTM model to fill in the spatiotemporal gaps in the fused soil moisture data, ultimately obtaining a seamless daily global surface soil moisture dataset spanning from March 31, 2015 to December 31, 2020. Due to limited computational resources, we trained the data by continent, dividing each continent into 1~4 tiles. Therefore, the final results are presented as tile-based compressed packages for each continent. The files named "MCA" and "ConvLSTM" contain our codes.
DOI: 10.6084/m9.figshare.30626234.v2
title: Global Daily Surface Soil Moisture Data from 2015-2020 generated by Multi-Collocation Fusion and Spatiotemporal Deep Learning

description: We used multiple collocation analysis and least-squares linear weighted averaging to combine soil moisture estimates from SMAP, AMSR2, ASCAT, and SMOS microwave missions and GLDAS, MERRA2, and ERA5-Land model simulations. We then used a ConvLSTM model to fill in the spatiotemporal gaps in the fused soil moisture data, ultimately obtaining a seamless daily global surface soil moisture dataset spanning from March 31, 2015 to December 31, 2020. Due to limited computational resources, we trained the data by continent, dividing each continent into 1~4 tiles. Therefore, the final results are presented as tile-based compressed packages for each continent. The files named "MCA" and "ConvLSTM" contain our codes.
DOI: 10.34740/kaggle/dsv/13741349
title: Trending Youtube Video Statistics (113 Countries)
DOI: 10.15468/dl.nyqssj
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-108.8688 24.59913, -108.7188 24.59913, -108.7188 24.74913, -108.8688 24.74913, -108.8688 24.59913))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035252-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8r32df
title: Occurrence Download

description: A dataset containing 1549 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pterygoplichthys pardalis"
 ]
}

 The dataset includes 1549 records from 68 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035253-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rubych
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mugil cephalus",
 "HasCoordinate is true",
 "Geometry POLYGON((-78 12, -73 12, -73 0, -78 0, -78 12))"
 ]
}

 The dataset includes 18 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035254-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17616136
title: Test_dbs
DOI: 10.5281/zenodo.17616137
title: Test_dbs
DOI: 10.15468/dl.zfpaaa
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-108.7188 24.59913, -108.5688 24.59913, -108.5688 24.74913, -108.7188 24.74913, -108.7188 24.59913))"
 ]
}

 The dataset includes 23 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035256-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aakbdn
title: Occurrence Download

description: A dataset containing 10943 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mugil curema",
 "HasCoordinate is true",
 "Geometry POLYGON((-78 12, -73 12, -73 0, -78 0, -78 12))"
 ]
}

 The dataset includes 10943 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035257-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.