cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.9jnp63
title: Occurrence Download

description: A dataset containing 445265 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tyto alba"
 ]
}

 The dataset includes 445265 records from 2255 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006451-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/mvpzzbyfhs
title: Glucose uptake measurements in PIK3CA-mutant ovarian cancer cell lines

description: This dataset contains glucose uptake measurements (via 2-NBDG assay) in PIK3CA-mutant ovarian cancer cell lines (OVCAR-3 and A2780) . Data files include: 
- Original datas 
- Ethical review materials
DOI: 10.17632/mvpzzbyfhs.1
title: Glucose uptake measurements in PIK3CA-mutant ovarian cancer cell lines

description: This dataset contains glucose uptake measurements (via 2-NBDG assay) in PIK3CA-mutant ovarian cancer cell lines (OVCAR-3 and A2780) . Data files include: 
- Original datas 
- Ethical review materials
DOI: 10.17632/x7h34tkwcp.1
title: Editable Oil Seed Dataset

description: Editable Oil Seed Dataset :-
The Oil seed classification plays a critical role in the agricultural and industrial sectors, aiding in quality control, sorting, and automation of processing systems. With the rise of machine learning and deep learning technologies, there is a growing need for high-quality, labeled datasets that can support the development and testing of classification models. This paper introduces the Editable Oil Seed Dataset, a carefully curated collection of 10,111 images across six widely cultivated oil seed types: Black Sesame, Groundnut, Mustard, Soybean, Sunflower, and White Sesame.
Captured using a high-resolution mobile imaging system with burst-shot capabilities, each image has undergone preprocessing steps such as resizing, normalization, and labeling to ensure suitability for machine learning applications. The dataset provides a solid foundation for tasks involving computer vision in agriculture, such as real-time seed sorting, quality assessment, and educational demonstrations of classification algorithms.

Representing six categories:-
1. Black Sesame Seeds - 1850
2. Groundnuts - 3000
3. Mustard Seeds - 1500
4. Soybean Seeds - 1531
5. Sunflower Seeds -1569
6. White Sesame Seeds - 661
Total Images= 10,111

 Device Specifications:-
- Primary Camera: 
 Device Model: Xiaomi Redmi 10C - 50 MP sensor, f/1.8 aperture, 26mm (wide), PDAF 
- Secondary Camera: 
Device Model: Xiaomi Redmi Note 7S - 48 MP sensor, f/1.8 aperture, 1/2.0" sensor size, 0.8µm pixel size, PDAF 
- Features: Dual - LED flash, HDR 
- Modes Used: Burst Shot Mode (capturing 20+ frames for optimal image selection)

This dataset is intended to bridge the gap between theoretical research and real-world application, making it a valuable resource for developers, researchers, and educators aiming to implement or explore seed classification using artificial intelligence techniques. Its versatility supports diverse use cases from research and development to practical deployment in smart agricultural systems.
DOI: 10.17632/x7h34tkwcp.2
title: Edible Oil Seed Dataset

description: Edible Oil Seed Dataset :-
The Oil seed classification plays a critical role in the agricultural and industrial sectors, aiding in quality control, sorting, and automation of processing systems. With the rise of machine learning and deep learning technologies, there is a growing need for high-quality, labeled datasets that can support the development and testing of classification models. This paper introduces the Edible Oil Seed Dataset, a carefully curated collection of 10,111 images across six widely cultivated oil seed types: Black Sesame, Groundnut, Mustard, Soybean, Sunflower, and White Sesame.
Captured using a high-resolution mobile imaging system with burst-shot capabilities, each image has undergone preprocessing steps such as resizing, normalization, and labeling to ensure suitability for machine learning applications. The dataset provides a solid foundation for tasks involving computer vision in agriculture, such as real-time seed sorting, quality assessment, and educational demonstrations of classification algorithms.

Representing six categories:-
1. Black Sesame Seeds - 1850
2. Groundnuts - 3000
3. Mustard Seeds - 1500
4. Soybean Seeds - 1531
5. Sunflower Seeds -1569
6. White Sesame Seeds - 661
Total Images= 10,111

 Device Specifications:-
- Primary Camera: 
 Device Model: Xiaomi Redmi 10C - 50 MP sensor, f/1.8 aperture, 26mm (wide), PDAF 
- Secondary Camera: 
Device Model: Xiaomi Redmi Note 7S - 48 MP sensor, f/1.8 aperture, 1/2.0" sensor size, 0.8µm pixel size, PDAF 
- Features: Dual - LED flash, HDR 
- Modes Used: Burst Shot Mode (capturing 20+ frames for optimal image selection)

This dataset is intended to bridge the gap between theoretical research and real-world application, making it a valuable resource for developers, researchers, and educators aiming to implement or explore seed classification using artificial intelligence techniques. Its versatility supports diverse use cases from research and development to practical deployment in smart agricultural systems.
DOI: 10.15468/dl.3h3e6t
title: Occurrence Download

description: A dataset containing 80571 species occurrences available in GBIF matching the query:
{
 "PublishingOrg" : [
 "is 5299c15f-07ad-4ef6-8d6a-b3acbb90ce93"
 ]
}

 The dataset includes 80571 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004093-250426092105405/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.28511978
title: Circulatory system-based optimization algorithm with dynamic penalty function for optimum design of large-scale water distribution networks

description: Water distribution networks (WDNs) are a crucial component of urban infrastructure, and their optimization plays a vital role in minimizing construction costs. However, existing heuristic algorithms for WDN optimization often rely on specific parameters, limiting their performance and hindering their applicability to diverse network configurations, particularly in large-scale systems. To address this challenge, a novel method called circulatory system-based optimization (CSBO) is proposed, which minimizes the need for algorithm-specific parameters and achieves optimal designs across WDNs of various scale. The impact of a dynamic penalty function tailored to pressure constraints on the optimal design is also investigated. This study encompasses the optimization of the Goyang and combined gravity networks and the large-scale Balerma irrigation and Kang and Lansey networks under identical conditions. The results of the standard and dynamic CSBO approaches prove that the proposed algorithms have a superior performance, particularly in convergence rate and stability, compared to previous methods.
DOI: 10.6084/m9.figshare.28511978.v1
title: Circulatory system-based optimization algorithm with dynamic penalty function for optimum design of large-scale water distribution networks

description: Water distribution networks (WDNs) are a crucial component of urban infrastructure, and their optimization plays a vital role in minimizing construction costs. However, existing heuristic algorithms for WDN optimization often rely on specific parameters, limiting their performance and hindering their applicability to diverse network configurations, particularly in large-scale systems. To address this challenge, a novel method called circulatory system-based optimization (CSBO) is proposed, which minimizes the need for algorithm-specific parameters and achieves optimal designs across WDNs of various scale. The impact of a dynamic penalty function tailored to pressure constraints on the optimal design is also investigated. This study encompasses the optimization of the Goyang and combined gravity networks and the large-scale Balerma irrigation and Kang and Lansey networks under identical conditions. The results of the standard and dynamic CSBO approaches prove that the proposed algorithms have a superior performance, particularly in convergence rate and stability, compared to previous methods.
DOI: 10.17608/k6.auckland.28079666
title: List of articles for a systematic review on student explanations in tertiary mathematics and statistics education (2014-2024)

description: List of peer-reviewed articles included in the systematic literature review on student-generated explanation in tertiary mathematics and statistics education
DOI: 10.15468/dl.jnux6q
title: Occurrence Download

description: A dataset containing 326 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Petrocodon Hance"
 ]
}

 The dataset includes 326 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004088-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/s95t7x5mmw.1
title: Face naming study

description: Describing an unfamiliar face can impede its later recognition. This phenomenon, known as the verbal overshadowing effect, is one of the most problematic issues affecting eyewitness testimony. This study examined whether generating a name for a target face could mitigate VOE and enhance lineup identification accuracy. Participants were assigned to one of four face naming conditions: (a) immediately after viewing the target person, (b) just before describing the target face, (c) prior to the identification task, or (d) no face naming (control). Results showed that participants who generated a name immediately before describing the face showed significantly higher identification accuracy than those in other naming conditions or the control group. Face naming appears to strengthen familiarity, making facial representation more robust against the disruptive effects of verbalization. These findings introduce the “face name generating effect” as a promising cognitive intervention for preserving the eyewitness memory integrity.
DOI: 10.17632/s95t7x5mmw.2
title: Face naming study

description: Describing an unfamiliar face can impede its later recognition. This phenomenon, known as the verbal overshadowing effect, is one of the most problematic issues affecting eyewitness testimony. This study examined whether generating a name for a target face could mitigate VOE and enhance lineup identification accuracy. Participants were assigned to one of four face naming conditions: (a) immediately after viewing the target person, (b) just before describing the target face, (c) prior to the identification task, or (d) no face naming (control). Results showed that participants who generated a name immediately before describing the face showed significantly higher identification accuracy than those in other naming conditions or the control group. Face naming appears to strengthen familiarity, making facial representation more robust against the disruptive effects of verbalization. These findings introduce the “face name generating effect” as a promising cognitive intervention for preserving the eyewitness memory integrity.
DOI: 10.17632/s95t7x5mmw.3
title: Epilogue on Verbal Overshadowing Effect: How Face-Naming an Unfamiliar Face Can Bypass the Deleterious Effect of Verbal Description?

description: Describing an unfamiliar face can impede its later recognition. This phenomenon, known as the verbal overshadowing effect, is one of the most problematic issues affecting eyewitness testimony. This study examined whether generating a name for a target face could mitigate VOE and enhance lineup identification accuracy. Participants were assigned to one of four face naming conditions: (a) immediately after viewing the target person, (b) just before describing the target face, (c) prior to the identification task, or (d) no face naming (control). Results showed that participants who generated a name immediately before describing the face showed significantly higher identification accuracy than those in other naming conditions or the control group. Face naming appears to strengthen familiarity, making facial representation more robust against the disruptive effects of verbalization. These findings introduce the “face name generating effect” as a promising cognitive intervention for preserving the eyewitness memory integrity.
DOI: 10.60629/23ky-g603
title: Climate activists on climate assemblies

description: <p><span style="color:rgb( 0 , 0 , 0 )">Despite the many participatory mechanisms available in climate governance, activists in Poland, including representatives of social movements, non-governmental organizations and local action groups have chosen to focus on citizens&#39; assemblies. This strategic choice raises important empirical and theoretical questions. </span><em style="color:rgb( 0 , 0 , 0 )">How do climate activists in Poland perceive citizens&#39; assemblies, and why do they advocate for this deliberative mechanism? How do they assess the role, democratic potential, and outcomes of citizens’ assemblies? What role do citizens&#39; assemblies play in the actions of climate activists and members of social movements?</em><span style="color:rgb( 0 , 0 , 0 )"> These are the central puzzles guiding our analysis.</span></p>
description: <p>Qualitative research, Indepth Interviews</p>
DOI: 10.15468/dl.xjd7s3
title: Occurrence Download

description: A dataset containing 236 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dactylorhiza hatagirea (D.Don) Soó"
 ]
}

 The dataset includes 236 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0105113-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25654/ifbq-bq22:kermit:3/2017
title: KERMIT 3, Schuljahr 2016/17

description: Unter dem Motto „Kompetenzen ermitteln“ – KERMIT – führen alle Hamburger Grundschulen, Stadtteilschulen und Gymnasien seit dem Schuljahr 2012/13 standardisierte Tests durch.
Mit KERMIT wird festgestellt, inwieweit die schulischen Leistungen der Schülerinnen und Schüler den Anforderungen der nationalen Bildungsstandards und der Hamburger Bildungspläne entsprechen. Die Testergebnisse informieren die Lehrkräfte über fachbezogene Stärken und Schwächen ihrer Lerngruppen.
KERMIT 3 hat im Schuljahr 2016/17 in den folgenden Domänen stattgefunden: Deutsch-Leseverstehen, Deutsch-Rechtschreibung, Mathematik.
description: Educational measurements and tests
description: lehrkraftadministrierte Kompetenzmessung
description: Schülerinnen und Schüler der dritten Jahrgangsstufe des Schuljahres 2016/17 in Hamburg
description: Vollerhebung
DOI: 10.15468/dl.8c2zbv
title: Occurrence Download

description: A dataset containing 1051 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Grus nigricollis Prjevalsky, 1876"
 ]
}

 The dataset includes 1051 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0201219-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ocgwzw
title: Occurrence Download

description: A dataset containing 448 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Schefflera distractiflora (Harms) Frodin"
 ]
}

 The dataset includes 448 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031993-180131172636756/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/z2gu44
title: Données Biodiversité Raffinerie de Donges

description: Biodiversity monitoring observations at the industrial site
DOI: 10.15468/dl.w966ws
title: Occurrence Download

description: A dataset containing 4758 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Emberiza sulphurata Temminck & Schlegel, 1848"
 ]
}

 The dataset includes 4758 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009435-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a52s3x
title: Occurrence Download

description: A dataset containing 626 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Anastatica L."
 ]
}

 The dataset includes 626 records from 62 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0207919-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j6y88s
title: Occurrence Download

description: A dataset containing 2610 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dendrortyx macroura (Jardine & Selby, 1828)"
 ]
}

 The dataset includes 2610 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010157-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x9rbmu
title: Occurrence Download

description: A dataset containing 278 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carex tristachya var. pocilliformis (Boott) Kük.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 278 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0077448-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25654/ifbq-bq22:ueko:primar/2017
title: ÜKO Primarstufe, Schuljahr 2016/17

description: Doppelte Ressource zu DOI: https://doi.org/10.25654/IfBQ-BQ21:UEKO:Primar/2017
double resource to DOI: https://doi.org/10.25654/IfBQ-BQ21:UEKO:Primar/2017
DOI: 10.15468/dl.8ckslx
title: Occurrence Download

description: A dataset containing 759 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Fitzroya cupressoides (Molina) I.M.Johnst."
 ]
}

 The dataset includes 759 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000894-190320150433242/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ze8op2
title: Occurrence Download

description: A dataset containing 33 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Schefflera gleasonii (Britton & P.Wilson) Alain"
 ]
}

 The dataset includes 33 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032028-180131172636756/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25654/ifbq-bq21:ueko:primar/2017
title: ÜKO Primarstufe, Schuljahr 2016/17

description: Das ÜKO-Instrumentarium dient zur Erfassung überfachlicher Kompetenzen von Schülerinnen und Schülern in den Jahrgangsstufen 1 bis 10. Für die Primarstufe stehen Bögen zur Fremdeinschätzung durch Lehrkräfte zur Verfügung. Für die Sekundarstufe gibt es neben Fremdeinschätzungsbögen auch Selbsteinschätzungsbögen für Schülerinnen und Schüler.
Die ÜKO-Bögen sind abgestimmt auf die Hamburger Bildungspläne und die Hamburger Bildungsempfehlungen für Kitas.
Hamburger Schulen können die bereit gestellten Instrumente nutzen und die Ergebnisse über eine Online-Eingabemaske erfassen und die Kompetenzprofile ihrer Schülerinnen und Schüler visualisieren.
description: Self-administered questionnaire: Paper
description: ÜKO (Überfachliche Kompetenzen): Self-administered questionnaire (Papier und Bleistift)
description: Schülerinnen und Schüler der zweiten und dritten Jahrgangsstufe des Schuljahres 2016/17 in Hamburg
description: Anfallende Stichprobe aus Hamburger Schulen, die das ÜKO-Instrumentarium nutzen
DOI: 10.25654/ifbq-bq21:ueko:primar/2018
title: ÜKO Primarstufe, Schuljahr 2017/18

description: Das ÜKO-Instrumentarium dient zur Erfassung überfachlicher Kompetenzen von Schülerinnen und Schülern in den Jahrgangsstufen 1 bis 10. Für die Primarstufe stehen Bögen zur Fremdeinschätzung durch Lehrkräfte zur Verfügung. Für die Sekundarstufe gibt es neben Fremdeinschätzungsbögen auch Selbsteinschätzungsbögen für Schülerinnen und Schüler.
Die ÜKO-Bögen sind abgestimmt auf die Hamburger Bildungspläne und die Hamburger Bildungsempfehlungen für Kitas.
Hamburger Schulen können die bereit gestellten Instrumente nutzen und die Ergebnisse über eine Online-Eingabemaske erfassen und die Kompetenzprofile ihrer Schülerinnen und Schüler visualisieren.
description: Self-administered questionnaire: Paper
description: ÜKO (Überfachliche Kompetenzen): Self-administered questionnaire (Papier und Bleistift)
description: Schülerinnen und Schüler der zweiten und dritten Jahrgangsstufe des Schuljahres 2017/18 in Hamburg
description: Anfallende Stichprobe aus Hamburger Schulen, die das ÜKO-Instrumentarium nutzen
DOI: 10.25654/ifbq-bq21:ueko:primar/2019
title: ÜKO Primarstufe, Schuljahr 2018/19

description: Das ÜKO-Instrumentarium dient zur Erfassung überfachlicher Kompetenzen von Schülerinnen und Schülern in den Jahrgangsstufen 1 bis 10. Für die Primarstufe stehen Bögen zur Fremdeinschätzung durch Lehrkräfte zur Verfügung. Für die Sekundarstufe gibt es neben Fremdeinschätzungsbögen auch Selbsteinschätzungsbögen für Schülerinnen und Schüler.
Die ÜKO-Bögen sind abgestimmt auf die Hamburger Bildungspläne und die Hamburger Bildungsempfehlungen für Kitas.
Hamburger Schulen können die bereit gestellten Instrumente nutzen und die Ergebnisse über eine Online-Eingabemaske erfassen und die Kompetenzprofile ihrer Schülerinnen und Schüler visualisieren.
description: Self-administered questionnaire: Paper
description: ÜKO (Überfachliche Kompetenzen): Self-administered questionnaire (Papier und Bleistift)
description: Schülerinnen und Schüler der zweiten und dritten Jahrgangsstufe des Schuljahres 2018/19 in Hamburg
description: Anfallende Stichprobe aus Hamburger Schulen, die das ÜKO-Instrumentarium nutzen
DOI: 10.25654/ifbq-bq21:ueko:sekundar/2017
title: ÜKO Sekundarstufe, Schuljahr 2017/18

description: Das ÜKO-Instrumentarium dient zur Erfassung überfachlicher Kompetenzen von Schülerinnen und Schülern in den Jahrgangsstufen 1 bis 10. Für die Primarstufe stehen Bögen zur Fremdeinschätzung durch Lehrkräfte zur Verfügung. Für die Sekundarstufe gibt es neben Fremdeinschätzungsbögen auch Selbsteinschätzungsbögen für Schülerinnen und Schüler.
Die ÜKO-Bögen sind abgestimmt auf die Hamburger Bildungspläne und die Hamburger Bildungsempfehlungen für Kitas.
Hamburger Schulen können die bereit gestellten Instrumente nutzen und die Ergebnisse über eine Online-Eingabemaske erfassen und die Kompetenzprofile ihrer Schülerinnen und Schüler visualisieren.
description: Self-administered questionnaire: Paper
description: ÜKO (Überfachliche Kompetenzen): Self-administered questionnaire (Papier und Bleistift)
description: Schülerinnen und Schüler der fünften, siebten und zehnten Jahrgangsstufe des Schuljahres 2017/18 in Hamburg
description: Anfallende Stichprobe aus Hamburger Schulen, die das ÜKO-Instrumentarium nutzen