cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.30626726
title: Enrichment of Charge Carrier Mobility, Quantum Efficiency and Lifetime Behavior of Emissive Polymer for Hybrid Photodetector Utilization

description: This research aims to enhance the optoelectronic characteristics of the MEH-PPV (Poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene]) emissive layer by introducing zinc oxide (ZnO-30nm) nanoparticles, to achieve specific properties. The MEH-PPV hybrid composite films were fabricated using spin coating followed by hot plate thermal annealing with varying ZnO nanoparticle concentrations of 1–7 wt%, with a 2 wt% span. The fabricated device with the structure of indium tin oxide/Poly(3,4-ethylenedioxythiophene) polystyrene sulfonate/MEH-PPV with ZnO (0–7 wt%)/aluminum top electrode was comprehensively characterized, including PL performance, absorption behavior, charge carrier mobility, quantum efficiency, lifetime, and transient current-voltage performances. The optimal results were achieved with a 3 wt% ZnO composition, showing better charge movement with carrier mobility of 7.94 × 10<sup>−5</sup> cm<sup>2</sup>/V·s and quantum efficiency of 36.5%. This optimized composition showed enhanced PL emission with 70% improvement, with the operational lifetime of 146 h. The absorption spectrum was also increased by 1.32 a.u. relative to pure MEH-PPV, and the photocurrent decay response was reduced to 0.86 µs and the photovoltage decay response to 1.23 µs. Thus, the paper confirmed that adding ZnO helped overcome the intrinsic limitations of MEH-PPV with a 3 wt% ZnO composite, a promising option for use in high-performing hybrid photodetectors.
DOI: 10.6084/m9.figshare.30626726.v1
title: Enrichment of Charge Carrier Mobility, Quantum Efficiency and Lifetime Behavior of Emissive Polymer for Hybrid Photodetector Utilization

description: This research aims to enhance the optoelectronic characteristics of the MEH-PPV (Poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene]) emissive layer by introducing zinc oxide (ZnO-30nm) nanoparticles, to achieve specific properties. The MEH-PPV hybrid composite films were fabricated using spin coating followed by hot plate thermal annealing with varying ZnO nanoparticle concentrations of 1–7 wt%, with a 2 wt% span. The fabricated device with the structure of indium tin oxide/Poly(3,4-ethylenedioxythiophene) polystyrene sulfonate/MEH-PPV with ZnO (0–7 wt%)/aluminum top electrode was comprehensively characterized, including PL performance, absorption behavior, charge carrier mobility, quantum efficiency, lifetime, and transient current-voltage performances. The optimal results were achieved with a 3 wt% ZnO composition, showing better charge movement with carrier mobility of 7.94 × 10<sup>−5</sup> cm<sup>2</sup>/V·s and quantum efficiency of 36.5%. This optimized composition showed enhanced PL emission with 70% improvement, with the operational lifetime of 146 h. The absorption spectrum was also increased by 1.32 a.u. relative to pure MEH-PPV, and the photocurrent decay response was reduced to 0.86 µs and the photovoltage decay response to 1.23 µs. Thus, the paper confirmed that adding ZnO helped overcome the intrinsic limitations of MEH-PPV with a 3 wt% ZnO composite, a promising option for use in high-performing hybrid photodetectors.
DOI: 10.15468/dl.kc9hpc
title: Occurrence Download

description: A dataset containing 27 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-108.1188 23.69913, -107.9688 23.69913, -107.9688 23.84913, -108.1188 23.84913, -108.1188 23.69913))"
 ]
}

 The dataset includes 27 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034785-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.57kqu3
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hypselecara temporalis",
 "HasCoordinate is true",
 "Geometry POLYGON((-78 12, -73 12, -73 0, -78 0, -78 12))"
 ]
}

 The dataset includes 6 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034786-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j737y7
title: Occurrence Download

description: A dataset containing 31 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-107.9688 23.69913, -107.8188 23.69913, -107.8188 23.84913, -107.9688 23.84913, -107.9688 23.69913))"
 ]
}

 The dataset includes 31 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034787-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17614268
title: Underwater images collected by a Kite surf in Le-Morne, Mauritius - 2018-07-22

description: This dataset was collected by a Kite surf in Le-Morne, Mauritius - 2018-07-22. 

            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: 

                No GPS.
            
                    
                

                
            

            
 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.17614328
title: Underwater images collected by a Kite surf in Le-Morne, Mauritius - 2018-07-22

description: This dataset was collected by a Kite surf in Le-Morne, Mauritius - 2018-07-22. 

            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: 

                No GPS.
            
                    
                

                
            

            
 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.8vy48w
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hypsophrys nicaraguensis",
 "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/0034788-251025141854904/datasets/export for details.
DOI: 10.15468/dl.95nmgp
title: Occurrence Download

description: A dataset containing 66928 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aves",
 "Geometry POLYGON((77 32, 79 32, 79 33, 77 33, 77 32))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 66928 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034723-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xcrasp
title: Occurrence Download

description: A dataset containing 7073937 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "OccurrenceStatus is Present",
 "TaxonKey is Mammalia"
 ]
}

 The dataset includes 7073937 records from 1199 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034771-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.75x5sv
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Senna siamea",
 "Country is Rwanda",
 "HasCoordinate is true"
 ]
}

 The dataset includes 25 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024879-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tm674y
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Senna siamea",
 "Country is Niue",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024878-250811113504898/datasets/export for details.
DOI: 10.15468/dl.ae8zzc
title: Occurrence Download

description: A dataset containing 266 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cleome violacea",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 266 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002175-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14677932
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.5281/zenodo.18431801
title: D6.2 - Monitoring framework and evaluation methods & LRGs vulnerability assessment and adaptation measures baseline data

description: Ex-ante baseline datasets and analysis of three demonstrators of the FairFuture project (Thessaloniki, Zagreb and Hamburg), detailing key data points reported to the CDP-ICLEI Track.

The deliverable is currently awaiting approval by the European Commission.
DOI: 10.5281/zenodo.18431802
title: D6.2 - Monitoring framework and evaluation methods & LRGs vulnerability assessment and adaptation measures baseline data

description: Ex-ante baseline datasets and analysis of three demonstrators of the FairFuture project (Thessaloniki, Zagreb and Hamburg), detailing key data points reported to the CDP-ICLEI Track.

The deliverable is currently awaiting approval by the European Commission.
DOI: 10.5281/zenodo.17716583
title: 3D qMRI Phantom Measurements Using QALAS and Reference T₁/T₂ Mapping Protocols for Intraoperative Application Validation
DOI: 10.17043/brussee-2026-methane-1
title: Methane stable isotope endmember database and inner Laptev Sea geochemical data
DOI: 10.5281/zenodo.17716582
title: 3D qMRI Phantom Measurements Using QALAS and Reference T₁/T₂ Mapping Protocols for Intraoperative Application Validation
DOI: 10.15468/dl.zq2psb
title: Occurrence Download

description: A dataset containing 107295 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Polistes dominula"
 ]
}

 The dataset includes 107295 records from 433 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002153-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18432681
title: CRN: C. elegans Touch Circuit Simulation Artifacts

description: This dataset contains reproducible artifacts for Coherent Resonant Netting (CRN)simulations performed on a C. elegans touch-withdrawal subcircuit derived fromthe Varshney et al. connectome.

The circuit includes mechanosensory neurons (ALM, AVM, PLM), command interneurons(AVA, AVB, AVD, PVC), and motor neuron classes (VA, VB, DA, DB). Edge weightscorrespond to synaptic connection counts reported in the original connectome.

Raw trajectory-level outputs are not stored; simulations generate aggregatedmetrics directly for reproducibility and efficiency. This dataset is a companionto the CRN manuscript and software repository.
DOI: 10.15468/dl.a8vt3v
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "Geometry POLYGON((-102.74094 25.02597,-93.26227 25.02597,-93.26227 36.15667,-102.74094 36.15667,-102.74094 25.02597))",
 "HasCoordinate is true",
 "TaxonKey is Cisthene subjecta"
 ]
}

 The dataset includes 9 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002176-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18432680
title: CRN: C. elegans Touch Circuit Simulation Artifacts

description: This dataset contains reproducible artifacts for Coherent Resonant Netting (CRN)simulations performed on a C. elegans touch-withdrawal subcircuit derived fromthe Varshney et al. connectome.

The circuit includes mechanosensory neurons (ALM, AVM, PLM), command interneurons(AVA, AVB, AVD, PVC), and motor neuron classes (VA, VB, DA, DB). Edge weightscorrespond to synaptic connection counts reported in the original connectome.

Raw trajectory-level outputs are not stored; simulations generate aggregatedmetrics directly for reproducibility and efficiency. This dataset is a companionto the CRN manuscript and software repository.
DOI: 10.5281/zenodo.18432737
title: HARBIY MUHITDA RAHBARLIK USLUBLARI VA INTIZOMIY XULQ-ATVORNING PSIXOLOGIK OMILLARI

description: Ushbu maqolada harbiy tashkilotlarda rahbarlik uslublarining shaxsiy tarkib intizomiy xulq-atvoriga psixologik ta’siri tahlil qilinadi. Tadqiqot doirasida rahbarlikning avtoritar, demokratik va moslashuvchan shakllari harbiy xizmatchilarning motivatsiyasi, mas’uliyat hissi va bo‘ysunish darajasi bilan bog‘liq holda o‘rganildi. Natijalar rahbarlikning psixologik jihatdan asoslangan yondashuvi intizomning barqarorligini ta’minlashda muhim ahamiyatga ega ekanini ko‘rsatdi.
DOI: 10.5281/zenodo.18432738
title: HARBIY MUHITDA RAHBARLIK USLUBLARI VA INTIZOMIY XULQ-ATVORNING PSIXOLOGIK OMILLARI

description: Ushbu maqolada harbiy tashkilotlarda rahbarlik uslublarining shaxsiy tarkib intizomiy xulq-atvoriga psixologik ta’siri tahlil qilinadi. Tadqiqot doirasida rahbarlikning avtoritar, demokratik va moslashuvchan shakllari harbiy xizmatchilarning motivatsiyasi, mas’uliyat hissi va bo‘ysunish darajasi bilan bog‘liq holda o‘rganildi. Natijalar rahbarlikning psixologik jihatdan asoslangan yondashuvi intizomning barqarorligini ta’minlashda muhim ahamiyatga ega ekanini ko‘rsatdi.
DOI: 10.15468/dl.vwb8md
title: Occurrence Download

description: A dataset containing 25228 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Observation, Human Observation)",
 "Country is Canada",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Fratercula arctica"
 ]
}

 The dataset includes 25228 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002177-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18432168
title: Dataset for the Broad-scale Dune Vulnerability Index (BDVI) along the Gharb coast, NW Morocco
DOI: 10.5281/zenodo.18432169
title: Dataset for the Broad-scale Dune Vulnerability Index (BDVI) along the Gharb coast, NW Morocco
DOI: 10.5281/zenodo.18432637
title: H2-SCR at high water concentrations with in-situ generated NH3-SCR for efficient removal of NOx from H2 engines
DOI: 10.5281/zenodo.18432636
title: H2-SCR at high water concentrations with in-situ generated NH3-SCR for efficient removal of NOx from H2 engines
DOI: 10.5281/zenodo.18432734
title: LINF_320016200

description: Vps29-like protein; Leishmania infantum (strain JPCM5)
DOI: 10.5281/zenodo.18432733
title: LINF_320016200

description: Vps29-like protein; Leishmania infantum (strain JPCM5)
DOI: 10.5281/zenodo.18432740
title: IMPROVEMENT OF OBJECT DETECTION AND CLASSIFICATION ALGORITHMS IN COMPUTER VISION SYSTEMS

description: This article analyzes the issues of improving object detection and classification algorithms in computer vision systems. As a result of the rapid development of modern artificial intelligence technologies, especially deep learning methods, the possibilities of accurately separating objects from image and video streams are expanding. The article considers the principles of operation of existing convolutional neural networks (CNN), region-based detection models, as well as their advantages and limitations. New approaches aimed at increasing accuracy, improving computing speed, and reducing resource consumption are also described. Data set expansion, image preprocessing, transfer learning, and the use of ensemble models are shown as important factors for improving efficiency. The practical significance of such improved algorithms in areas such as real-time surveillance systems, medical image analysis, industrial control, and autonomous transportation is highlighted. The research results show that the reliability of detection and classification processes is significantly increased by using optimized model architectures and adaptive training strategies.
DOI: 10.5281/zenodo.18432741
title: IMPROVEMENT OF OBJECT DETECTION AND CLASSIFICATION ALGORITHMS IN COMPUTER VISION SYSTEMS

description: This article analyzes the issues of improving object detection and classification algorithms in computer vision systems. As a result of the rapid development of modern artificial intelligence technologies, especially deep learning methods, the possibilities of accurately separating objects from image and video streams are expanding. The article considers the principles of operation of existing convolutional neural networks (CNN), region-based detection models, as well as their advantages and limitations. New approaches aimed at increasing accuracy, improving computing speed, and reducing resource consumption are also described. Data set expansion, image preprocessing, transfer learning, and the use of ensemble models are shown as important factors for improving efficiency. The practical significance of such improved algorithms in areas such as real-time surveillance systems, medical image analysis, industrial control, and autonomous transportation is highlighted. The research results show that the reliability of detection and classification processes is significantly increased by using optimized model architectures and adaptive training strategies.
DOI: 10.15468/dl.j9g9gv
title: Occurrence Download

description: A dataset containing 690 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-106.50484 22.3775,-89.25688 22.3775,-89.25688 38.55962,-106.50484 38.55962,-106.50484 22.3775))",
 "HasCoordinate is true",
 "TaxonKey is Cisthene packardii"
 ]
}

 The dataset includes 690 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002178-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.