cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7391073
title: Competences and Needs of Students and Support Received / Competencias y Necesidades de los Alumnos y Apoyos que Reciben // STUDENT-INFORM_Data_IC_T6-Pre

description: Information provided by the teacher on the competencies, needs and individual supports of the students in his/her classroom. The teacher estimates the competence in 5 areas (Social, Mathematics, Spanish Language, Valencian Language and Physical Education), the presence of educational needs (motor, intellectual, hearing, vision, hearing and language, learning, behavioral, developmental, and high abilities), and the type of support received and with what periodicity (therapeutic pedagogy, compensatory education, hearing and language and educational reinforcement). The information was collected through interviews with tutor teachers from public schools in Castellón (Spain) in the fall of the school year 2015-16 and compiled in this Descriptive Data, Competencies and Educational Needs of the Student Report (STUDENT-INFORM) (García Bacete et al., 2014). The dataset also includes information on the worries that some students generate in the teacher in different areas (relational, behavioral, and academic) and the specific reasons why these students worry the teacher, compiled in the Class Group and Teacher Report (CLASSROOM-INFORM) (García Bacete et al., 2014). To learn more about our research and access to other datasets of this or other measures, follow the link GREI Longitudinal Project. Información proporcionada por el profesor sobre las competencias, necesidades y apoyos individuales de los alumnos de su aula. El profesor estima la competencia en 5 áreas (Social, Matemáticas, Lengua Española, Lengua Valenciana y Educación Física), la presencia de necesidades educativas (motrices, intelectuales, auditivas, visuales, de lenguaje, de aprendizaje, de conducta, de desarrollo y de altas capacidades), y el tipo de apoyo recibido y con qué periodicidad (pedagogía terapéutica, educación compensatoria, audición y lenguaje y refuerzo educativo). La información se recogió a través de entrevistas a profesores tutores de colegios públicos de Castellón (España) en el otoño del curso escolar 2015-16 y se recopiló en este Informe de Datos Descriptivos, Competencias y Necesidades Educativas del Alumno (STUDENT-INFORM) (García Bacete et al., 2014). El fichero de datos también incluye información sobre las preocupaciones que algunos alumnos generan en el profesor en diferentes ámbitos (relacional, conductual y académico) y los motivos concretos por los que estos alumnos preocupan al profesor, recopilados en el Informe del grupo de clase y del profesor (CLASSROOM-INFORM) (García Bacete et al., 2014). Para saber más sobre nuestra investigación y acceder a otros ficheros de datos de esta medida o de otras, siga el enlace Proyecto Longitudinal GREI.
DOI: 10.6084/m9.figshare.24632184.v1
title: Data for figures

description: <br>Data related to the paper "Quantum simulation of Pauli channels and dynamical maps: algorithm and implementation"<br><br>
DOI: 10.25345/c5b27q26f
title: MassIVE MSV000093484 - Procesamiento y analisis de datos metabolimicos curso
title: Procesamiento y analisis de datos metabolimicos curso, con datos para GNPS.
DOI: 10.25345/c5xw48668
title: MassIVE MSV000093482 - Procesamiento y analisis de datos metabolomicos curso
title: Estos datos se usan en el curso de analisis de datos
DOI: 10.25345/c52j68f9d
title: MassIVE MSV000093483 - PROCESAMIENTO DE DATOS METABOLOMICOS CURSO UNIANDES
title: PROCESAMIENTO DE DATOS DE METABOLOMICA OBTENIDOS EN MODO DE TIEMPO DE VUELO
DOI: 10.25345/c5697082p
title: MassIVE MSV000093481 - massivetitulogenerosodeprueba24112023
title: estos cursos se usan en el curso de analisis de datos
DOI: 10.25345/c5t43jd3x
title: MassIVE MSV000093485 - Procesamiento curso procesamiento analisis de datos
title: Estos datos se usan en el curso de analisis de datos
DOI: 10.25345/c5pc2tm08
title: MassIVE MSV000093486 - Procesamiento_uniandes_curso_2023
title: Estos datos se usan en el curso de analisis de datos
DOI: 10.25345/c5jm23s5d
title: MassIVE MSV000093488 - Procesamiento y analisis de datos metabolomicos curso
title: Estos datos se usan en el curso de analisis de datos del curso de metabolica 2023-02 en muestras de plasma
DOI: 10.25345/c5dv1d006
title: MassIVE MSV000093487 - Procesamiento-analisis-de-datos-curso-EdCo
title: Estos datos son un set de ejemplo para el curso de PROCESAMIENTO Y ANALISIS DE DATOS METABOLOMICOS POR ESPECTROMETRIA DE MASAS de la Universidad de Los Andes.
DOI: 10.25345/c5930p56r
title: MassIVE MSV000093489 - procesamiento de metabolomico curso
title: Datos prueba de curso para aprender limpieza de datos en procesamiento de Metabolomica
DOI: 10.25345/c5599zc41
title: MassIVE MSV000093490 - Curso Prueba - Humanos - Este nombre tiene que ser mas largo
title: Estos datos fueron adquiridos en el equipo de Cala, estamos practicando GNPS - Muestra de plasma MABNDJKABSDAJSDBASKJDBASJOBDALSDBAKSDSAKJ
DOI: 10.25345/c51n7xz0r
title: MassIVE MSV000093491 - Procesamiento y analisis de datos metabolomicos cusrso
title: Estos datos se obtuvieron en el curso de analisis de datos metabolomicos dicto en la univerisda de los andes, en el cual se llevo el analisis en polaridad positiva o fase normal
DOI: 10.5281/zenodo.10204232
title: User Feedback Dataset from the Top 15 Downloaded Mobile Applications

description: This dataset comprises user feedback data collected from 15 globally acclaimed mobile applications, spanning diverse categories. The included applications are among the most downloaded worldwide, providing a rich and varied source for analysis. The dataset is particularly suitable for Natural Language Processing (NLP) applications, such as text classification and topic modeling.
List of Included Applications:

TikTok
Instagram
Facebook
WhatsApp
Telegram
Zoom
Snapchat
Facebook Messenger
Capcut
Spotify
YouTube
HBO Max
Cash App
Subway Surfers
Roblox
Data Columns and Descriptions:
Data Columns and Descriptions:

review_id: Unique identifiers for each user feedback/application review.
content: User-generated feedback/review in text format.
score: Rating or star given by the user.
TU_count: Number of likes/thumbs up (TU) received for the review.
app_id: Unique identifier for each application.
app_name: Name of the application.
RC_ver: Version of the app when the review was created (RC).
Terms of Use:
This dataset is open access for scientific research and non-commercial purposes. Users are required to acknowledge the authors' work and, in the case of scientific publication, cite the most appropriate reference:
M. H. Asnawi, A. A. Pravitasari, T. Herawan, and T. Hendrawati, "The Combination of Contextualized Topic Model and MPNet for User Feedback Topic Modeling," in IEEE Access, vol. 11, pp. 130272-130286, 2023, doi: 10.1109/ACCESS.2023.3332644.

Researchers and analysts are encouraged to explore this dataset for insights into user sentiments, preferences, and trends across these top mobile applications. If you have any questions or need further information, feel free to contact the dataset authors.
description: This project was sponsored by Universitas Padjadjaran and supported by the Research Center for Artificial Intelligence and Big Data (AIDA) Universitas Padjadjaran
DOI: 10.5281/zenodo.10204231
title: User Feedback Dataset from the Top 15 Downloaded Mobile Applications

description: This dataset comprises user feedback data collected from 15 globally acclaimed mobile applications, spanning diverse categories. The included applications are among the most downloaded worldwide, providing a rich and varied source for analysis. The dataset is particularly suitable for Natural Language Processing (NLP) applications, such as text classification and topic modeling.
List of Included Applications:

TikTok
Instagram
Facebook
WhatsApp
Telegram
Zoom
Snapchat
Facebook Messenger
Capcut
Spotify
YouTube
HBO Max
Cash App
Subway Surfers
Roblox
Data Columns and Descriptions:
Data Columns and Descriptions:

review_id: Unique identifiers for each user feedback/application review.
content: User-generated feedback/review in text format.
score: Rating or star given by the user.
TU_count: Number of likes/thumbs up (TU) received for the review.
app_id: Unique identifier for each application.
app_name: Name of the application.
RC_ver: Version of the app when the review was created (RC).
Terms of Use:
This dataset is open access for scientific research and non-commercial purposes. Users are required to acknowledge the authors' work and, in the case of scientific publication, cite the most appropriate reference:
M. H. Asnawi, A. A. Pravitasari, T. Herawan, and T. Hendrawati, "The Combination of Contextualized Topic Model and MPNet for User Feedback Topic Modeling," in IEEE Access, vol. 11, pp. 130272-130286, 2023, doi: 10.1109/ACCESS.2023.3332644.

Researchers and analysts are encouraged to explore this dataset for insights into user sentiments, preferences, and trends across these top mobile applications. If you have any questions or need further information, feel free to contact the dataset authors.
description: This project was sponsored by Universitas Padjadjaran and supported by the Research Center for Artificial Intelligence and Big Data (AIDA) Universitas Padjadjaran
DOI: 10.5281/zenodo.10204325
title: Changing in adaptive cellular repertoire after different SARS-CoV-2 VOCs infection in a cohort of vaccinated Healthcare workers

description: Despite currently approved vaccines are highly effective in protecting against hospitalization and severe Covid-19 infections, however, their effectiveness in counteracting symptoms presentation and breakthrough infections appears to decrease over time. How pre-existing immunity responds to new variants with mutated antigens is a crucial information to elucidate the functional interplay between antibodies, B and T cell responses during infection with new SARS-CoV-2 variants. In this study, we monitored the dynamics and persistence of the immune response versus different SARS-CoV-2 variants of concern emerged during the pandemic period (2021-2022), in a cohort of vaccinated health care workers, who experienced breakthrough infection in the Pre-Delta, Delta and Omicron waves. Our results suggest a direct dependence between VOCs and different humoral and B and T cells balance in the post-infection period, despite the administration of a different number of vaccine doses and the elapsed time since the last vaccination.
DOI: 10.5281/zenodo.10204324
title: Changing in adaptive cellular repertoire after different SARS-CoV-2 VOCs infection in a cohort of vaccinated Healthcare workers

description: Despite currently approved vaccines are highly effective in protecting against hospitalization and severe Covid-19 infections, however, their effectiveness in counteracting symptoms presentation and breakthrough infections appears to decrease over time. How pre-existing immunity responds to new variants with mutated antigens is a crucial information to elucidate the functional interplay between antibodies, B and T cell responses during infection with new SARS-CoV-2 variants. In this study, we monitored the dynamics and persistence of the immune response versus different SARS-CoV-2 variants of concern emerged during the pandemic period (2021-2022), in a cohort of vaccinated health care workers, who experienced breakthrough infection in the Pre-Delta, Delta and Omicron waves. Our results suggest a direct dependence between VOCs and different humoral and B and T cells balance in the post-infection period, despite the administration of a different number of vaccine doses and the elapsed time since the last vaccination.
DOI: 10.5281/zenodo.10156438
title: NoCORA - Northern Cameroon Observed Rainfall Archive

description: Description: The NoCORA dataset represents a significant effort to compile and clean a comprehensive set of rainfall data for Northern Cameroon (North and Extreme North regions). This dataset is instrumental for researchers, meteorologists, and policymakers working in climate research, agricultural planning, and water resource management in the region. It integrates data from diverse sources, including Sodecoton rain funnels, the archive of Robert Morel (IRD), Centrale de Lagdo, the GHCN daily service, and the TAHMO network, covering more than 1 million observations across 418 rainfall stations on a temporal range going from 1927 to 2022.
The construction of NoCORA involved meticulous processes, including manual assembly of data, extensive data cleaning, and standardization of station names and coordinates, making it a hopefully robust and reliable resource for understanding climatic dynamics in Northern Cameroon.
Data Sources: The dataset comprises eight primary rainfall data sources and a comprehensive coordinates dataset. The rainfall data sources include extensive historical and contemporary measurements, while the coordinates dataset was developed using reference data and an inference strategy for variant station names or missing coordinates.
Dataset Preparation Methods: The preparation involved manual compilation, integration of machine-readable files, data cleaning with OpenRefine, and finalization using Python/Jupyter Notebook. This process should ensured the accuracy and consistency of the dataset.
Discussion: NoCORA, with its extensive data compilation, presents an invaluable resource for climate-related studies in Northern Cameroon. However, users must navigate its complexities, including missing data interpretations, potential biases, and data inconsistencies. The dataset's comprehensive nature and historical span require careful handling and validation in research applications.
Access to Dataset: The NoCORA dataset, while a comprehensive resource for climatological and meteorological research in Northern Cameroon, is subject to specific access conditions due to its compilation from various partner sources. The original data sources vary in their openness and accessibility, and not all partners have confirmed the open-access status of their data. As such, to ensure compliance with these varying conditions, access to the NoCORA dataset is granted on a request basis. Interested researchers and users are encouraged to contact us for permission to access the dataset. This process allows us to uphold the data sharing agreements with our partners while facilitating research and analysis within the scientific community.
Authors Contributions:

Data treatment: Victor Hugo Nenwala, Carmel Foulna Tcheobe, Jérémy Lavarenne.
Documentation: Jérémy Lavarenne.
Funding: This project was funded by the DESIRA INNOVACC project.
DOI: 10.5281/zenodo.10180179
title: NoCORA - Northern Cameroon Observed Rainfall Archive

description: Description: The NoCORA dataset represents a significant effort to compile and clean a comprehensive set of daily rainfall data for Northern Cameroon (North and Extreme North regions). This dataset, overing more than 1 million observations across 418 rainfall stations on a temporal range going from 1927 to 2022, is instrumental for researchers, meteorologists, and policymakers working in climate research, agricultural planning, and water resource management in the region. It integrates data from diverse sources, including Sodecoton rain funnels, the archive of Robert Morel (IRD), Centrale de Lagdo, the GHCN daily service, and the TAHMO network.
The construction of NoCORA involved meticulous processes, including manual assembly of data, extensive data cleaning, and standardization of station names and coordinates, making it a hopefully robust and reliable resource for understanding climatic dynamics in Northern Cameroon.
Data Sources: The dataset comprises eight primary rainfall data sources and a comprehensive coordinates dataset. The rainfall data sources include extensive historical and contemporary measurements, while the coordinates dataset was developed using reference data and an inference strategy for variant station names or missing coordinates.
Dataset Preparation Methods: The preparation involved manual compilation, integration of machine-readable files, data cleaning with OpenRefine, and finalization using Python/Jupyter Notebook. This process should ensured the accuracy and consistency of the dataset.
Discussion: NoCORA, with its extensive data compilation, presents an invaluable resource for climate-related studies in Northern Cameroon. However, users must navigate its complexities, including missing data interpretations, potential biases, and data inconsistencies. The dataset's comprehensive nature and historical span require careful handling and validation in research applications.
Access to Dataset: The NoCORA dataset, while a comprehensive resource for climatological and meteorological research in Northern Cameroon, is subject to specific access conditions due to its compilation from various partner sources. The original data sources vary in their openness and accessibility, and not all partners have confirmed the open-access status of their data. As such, to ensure compliance with these varying conditions, access to the NoCORA dataset is granted on a request basis. Interested researchers and users are encouraged to contact us for permission to access the dataset. This process allows us to uphold the data sharing agreements with our partners while facilitating research and analysis within the scientific community.
Authors Contributions:

Data treatment: Victor Hugo Nenwala, Carmel Foulna Tcheobe, Jérémy Lavarenne.
Documentation: Jérémy Lavarenne.
Funding: This project was funded by the DESIRA INNOVACC project.
Changelog: 

v1.0.1 : dataset specification file has been updated with complementary information regarding station locations
v1.0.0 : initial submission
DOI: 10.6084/m9.figshare.24632205
title: Database sunflower yield gaps

description: In preparation
DOI: 10.5281/zenodo.10108694
title: Data for "Double Superionicity in Icy Compounds at Planetary Interior Conditions"

description: Data for "Double Superionicity in Icy Compounds at Planetary Interior Conditions" by authors Kyla de Villa, Felipe Gonzalez-Cataldo, and Burkhard Militzer (DOI: 10.1038/s41467-023-42958-0).  
To keep the data volume reasonable, only the files from the first checkpoint of DFT-MD and ML-MD simulations are provided. Further simulation data are available from the corresponding author upon reasonable request.
DOI: 10.5281/zenodo.10108693
title: Data for "Double Superionicity in Icy Compounds at Planetary Interior Conditions"

description: Data for "Double Superionicity in Icy Compounds at Planetary Interior Conditions" by authors Kyla de Villa, Felipe Gonzalez-Cataldo, and Burkhard Militzer (DOI: 10.1038/s41467-023-42958-0).  
To keep the data volume reasonable, only the files from the first checkpoint of DFT-MD and ML-MD simulations are provided. Further simulation data are available from the corresponding author upon reasonable request.
DOI: 10.3886/e195143v1-143288
title: Neural Diversity and Decisions

description: The present study measured nine physiologic factors and collected 16 types of psychological data while participants made decisions in standard tasks from experimental economics measuring risk aversion, intertemporal patience, altruism, cooperation, generosity, trust and trustworthiness. Robust predictors were defined as those that were statistically significant in both forward and backward stepwise regressions using all the collected independent variables. The analysis showed that multiple measures of physiologic stress decrease cooperative behaviors while testosterone consistently increased antisocial behaviors. Further, cognitive abilities robustly increased patience but decreased cooperation while those more satisfied with their lives were more trustworthy. Participants scoring high on the personality trait of Imagination were shown to be less altruistic and generous, while those high on Neuroticism were more prosocial.
DOI: 10.25625/vs4qk9/1xksua
title: MILINDA_v1_March2019.tab

description: :unav
DOI: 10.25625/vs4qk9/jirgix
title: MILINDA-v1-March2019.xls

description: :unav
DOI: 10.25625/vs4qk9
title: Replication Data for: MILINDA: A new dataset on United Nations-led and non-united Nations-led peace operations

description: The MILINDA dataset encompasses all military and non-military peace operations between 1947 and 2016 explicitly designated as peace operations. Peace operations are the expeditionary use of uniformed personnel with or without a UN mandate, but with an explicit mandate to assist in the prevention of armed conflict by supporting a peace process. It includes not only UN missions but also a substantial number of missions conducted by ad hoc coalitions of states or individual state not included in the UN or SIPRI’s database. The MILINDA dataset contains 293 observations altogether. The unit of analysis is the mission. If a mission changes its category—for example, from an Observer to a Peacekeeping operation—we coded this as a new observation. MILINDA codes four types of interventions, denoting the distribution of responsibilities among the various actors, which we defined in line with the international legal literature: Peace Enforcement, Peacekeeping, Observer, and Other.
DOI: 10.17630/d328524e-e958-4d72-bca6-82edf18cddbf
title: Computational NMR Investigation of Mixed-Metal (Al,Sc)-MIL-53 and its Phase Transitions (dataset)
DOI: 10.25934/pr00005473.1
title: Available IPD datapackage for study 'Topiramate Clinical Trial in Primary Generalized Tonic-Clonic Seizures'

description: The purpose of this study is to evaluate the effectiveness and safety of topiramate as an add-on therapy in epilepsy patients with uncontrolled primary generalized tonic-clonic seizures, who are taking 1 or 2 standard antiepileptic drugs.
DOI: 10.17630/7af95004-b469-44eb-9448-3aa20ddf2131
title: Counting Processes For Spatial Capture-Recapture (thesis data)

description: Data and code underpinning the main chapters of this thesis.
DOI: 10.25934/pr00005470.0
title: Available IPD datapackage for study 'Topiramate Clinical Trial in Primary Generalized Tonic-Clonic Seizures'

description: The purpose of this study is to evaluate the efficacy and safety of topiramate as an add-on therapy in epilepsy patients with uncontrolled primary generalized tonic-clonic seizures, who are taking 1 or 2 standard antiepileptic drugs.
DOI: 10.6084/m9.figshare.24632181.v1
title: An open database on inequality and polarization in length of life (1950-2021)

description: This database includes a comprehensive set of estimates on lifespan inequality and polarization for 258 countries and areas for the period 1950–2021. These extensive series on the distribution of lifespans provide access to crucial information for researchers, policy-makers, and the general public, thus representing a fundamental step towards a better understanding of health differences within and between nations.
DOI: 10.5281/zenodo.10204051
title: Fluorinated derivatives of sulfolane, cyclopentanone and gamma-butyrolactone

description: The dataset contains the output of DFT calculations for the compounds studied in the article "Theoretical study on fluorinated derivatives of sulfolane, cyclopentanone, and gamma-butyrolactone". The files are named according to the compound codes in the publication.
[B3LYP]: results of gas-phase optimization and vibrational frequency analysis at B3LYP/6-311+G** level for neutral species (output of Gaussian 16 software).
[M06-2X]: results of gas-phase optimization and vibrational frequency analysis at M062X/6-311+G** level for neutral, oxidized and reduced species (output of Gaussian 16 software).
[BP-TZVP-COSMO_geom]: geometries of neutral and protonated species optimized at BP86/def-TZVP level of theory in ideal conductor (COSMO model), as *.xyz files
[BP-TZVPD-COSMO_cosmo-files]: results of single-point calculations at BP86/def2-TZVPD level with Fine cavity parameter in ideal conductor (COSMO model), for geometries presented in 'BP-TZVP-COSMO_geom' (see above), as *.cosmo files.