cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5502440
title: Dataset: Longitudinal personal thermal comfort preference datain the wild

description: Thermal comfort affects the well-being, productivity, and overall satisfaction of building occupants. However, due to economical and practical limitations, the number of longitudinal studies that have been conducted is limited, and only a few of these studies have shared their data publicly. Longitudinal datasets collected indoors are a valuable resource to better understand how people perceive their environment. Moreover, they provide a more realistic scenario to those conducted in thermal chambers. Our objective was to share publicly a longitudinal dataset comprising data collected over a 4-week long experiment. A total of 17 participants completed thermal preferences surveys which accounted for a total of approximately 1400 unique responses across indoor and outdoor 17 spaces. For the whole duration of the study, we monitored environmental variables (e.g., temperature and relative humidity) throughout 3 buildings. Participants completed comfort surveys from the screen of their smartwatches using an open-source application named Cozie. Their indoor location was continuously monitored using a custom-designed smartphone application.<br> Location data were used to time and spatially align environmental measurements to thermal preference responses provided by the participants. Background information of participants, such as physical characteristics and personality traits (satisfaction with life scale, highly sensitive person scale, the Big Five personality traits), was collected using an on-boarding survey administered at the beginning of the experiment. You can find the features descriptions, raw data processing, and raw files in our project repository: https://github.com/buds-lab/longitudinal-personal-thermal-comfort
DOI: 10.5281/zenodo.5573728
title: Exploring the interaction of a curcumin azobioisostere with Abeta42 dimers using replica exchange molecular dynamics simulations

description: Structural data and parameters relative to the evaluation of the interaction of an anti aggregating azobioisostere compound with the full-length Aβ42 peptide by replica-exchange molecular dynamics (REMD) simulations. Two different force fields (Amber and CHARMM) were used to simulate the azobioisostere-Abeta42 (AZ-Ab42) complex in a monomeric and dimeric assembly. A brief description of the shared output data is reported below: <strong>1. Amber and CHARMM-adapted parameters for the simulated azobioisostere (AZ) compound.</strong> <strong>2. Modified version of the CHARMM36m FF - (CHARMM36mW)</strong> <strong>3. Starting (equilibrated) structures (first 5 T-replicas) for REMD on each of the following three systems (PDB): </strong> Amber: AZ-Ab42 (monomeric ensemble): <strong>Repl.0 </strong>(315.0 K), <strong>Repl.1</strong> (316.7 K), <strong>Repl.2</strong> (318.4 K), <strong>Repl.3</strong> (320.1 K), <strong>Repl.4</strong> (321.8 K) Amber: AZ-Ab42 (dimeric ensemble): <strong>Repl.0</strong> (315.0 K), <strong>Repl.1</strong> (316.0 K), <strong>Repl.2</strong> (317.0 K), <strong>Repl.3</strong> (318.0 K), <strong>Repl.4</strong> (319.1 K) CHARMM: AZ-Ab42 (dimeric ensemble): <strong>Repl.0</strong> (315.0 K), <strong>Repl.1</strong> (316.0 K), <strong>Repl.2</strong> (317.0 K), <strong>Repl.3 </strong>(318.0 K), <strong>Repl.4</strong> (319.1 K) <strong>4. Most populated clusters for the three simulated systems (PDB):</strong> Amber AZ-Ab42 (monomeric ensemble): <strong>7</strong> clusters (<strong>Cl.0</strong>: 12.4%, <strong>Cl.1</strong>: 10.1%, <strong>Cl.2</strong>: 9.8%, <strong>Cl.3</strong>: 5.4%, <strong>Cl.4</strong>: 3.7%,<strong> Cl.5</strong>: 3.6%, <strong>Cl.6</strong>: 2.0%) Amber AZ-Ab42 (dimeric ensemble): <strong>5</strong> clusters (<strong>Cl.0</strong>: 7.1%, <strong>Cl.1</strong>: 4.3%, <strong>Cl.2</strong>: 3.5%,<strong> Cl.3</strong>: 3.2%, <strong>Cl.4</strong>: 2.4%) CHARMM: AZ-Ab42 (dimeric ensemble): <strong>3</strong> clusters (<strong>Cl.0</strong>: 4.7%, <strong>Cl.1</strong>: 4.6%, <strong>Cl.2</strong>: 2.5%)
DOI: 10.5281/zenodo.5573727
title: Exploring the interaction of a curcumin azobioisostere with Abeta42 dimers using replica exchange molecular dynamics simulations

description: Structural data and parameters relative to the evaluation of the interaction of an anti aggregating azobioisostere compound with the full-length Aβ42 peptide by replica-exchange molecular dynamics (REMD) simulations. Two different force fields (Amber and CHARMM) were used to simulate the azobioisostere-Abeta42 (AZ-Ab42) complex in a monomeric and dimeric assembly. A brief description of the shared output data is reported below: <strong>1. Amber and CHARMM-adapted parameters for the simulated azobioisostere (AZ) compound.</strong> <strong>2. Modified version of the CHARMM36m FF - (CHARMM36mW)</strong> <strong>3. Starting (equilibrated) structures (first 5 T-replicas) for REMD on each of the following three systems (PDB): </strong> Amber: AZ-Ab42 (monomeric ensemble): <strong>Repl.0 </strong>(315.0 K), <strong>Repl.1</strong> (316.7 K), <strong>Repl.2</strong> (318.4 K), <strong>Repl.3</strong> (320.1 K), <strong>Repl.4</strong> (321.8 K) Amber: AZ-Ab42 (dimeric ensemble): <strong>Repl.0</strong> (315.0 K), <strong>Repl.1</strong> (316.0 K), <strong>Repl.2</strong> (317.0 K), <strong>Repl.3</strong> (318.0 K), <strong>Repl.4</strong> (319.1 K) CHARMM: AZ-Ab42 (dimeric ensemble): <strong>Repl.0</strong> (315.0 K), <strong>Repl.1</strong> (316.0 K), <strong>Repl.2</strong> (317.0 K), <strong>Repl.3 </strong>(318.0 K), <strong>Repl.4</strong> (319.1 K) <strong>4. Most populated clusters for the three simulated systems (PDB):</strong> Amber AZ-Ab42 (monomeric ensemble): <strong>7</strong> clusters (<strong>Cl.0</strong>: 12.4%, <strong>Cl.1</strong>: 10.1%, <strong>Cl.2</strong>: 9.8%, <strong>Cl.3</strong>: 5.4%, <strong>Cl.4</strong>: 3.7%,<strong> Cl.5</strong>: 3.6%, <strong>Cl.6</strong>: 2.0%) Amber AZ-Ab42 (dimeric ensemble): <strong>5</strong> clusters (<strong>Cl.0</strong>: 7.1%, <strong>Cl.1</strong>: 4.3%, <strong>Cl.2</strong>: 3.5%,<strong> Cl.3</strong>: 3.2%, <strong>Cl.4</strong>: 2.4%) CHARMM: AZ-Ab42 (dimeric ensemble): <strong>3</strong> clusters (<strong>Cl.0</strong>: 4.7%, <strong>Cl.1</strong>: 4.6%, <strong>Cl.2</strong>: 2.5%)
DOI: 10.6084/m9.figshare.16822054
title: Raw data for: "Identifying optimal cycles in quantum thermal machines with reinforcement-learning"

description: Raw data used to produce figures and results presented in the paper "Identifying optimal cycles in quantum thermal machines with reinforcement-learning" by P. A. Erdman and F. Noé.
DOI: 10.6084/m9.figshare.16811494
title: The role of Intra-clutch variation of magpie clutches in foreign egg rejection depends on the egg trait considered- Dataset

description: This data set provides all the variables used to analyze the role of intra-clutch variation in the main host defense mechanism against brood parasitism, the rejection of foreign eggs. We measured egg color in three different parts of the egg, egg volume and the fractal dimension of spottines of eggshell<br>All the details could be find in the file entitled "Dataset_intra-clutch variation in traits_MMM".
DOI: 10.6084/m9.figshare.16811494.v1
title: The role of Intra-clutch variation of magpie clutches in foreign egg rejection depends on the egg trait considered- Dataset

description: This data set provides all the variables used to analyze the role of intra-clutch variation in the main host defense mechanism against brood parasitism, the rejection of foreign eggs. We measured egg color in three different parts of the egg, egg volume and the fractal dimension of spottines of eggshell<br>All the details could be find in the file entitled "Dataset_intra-clutch variation in traits_MMM".
DOI: 10.18112/openneuro.ds003844.v1.0.0
title: RESPect
DOI: 10.18112/openneuro.ds003844.v1.0.1
title: RESPect
DOI: 10.5281/zenodo.5573809
title: Microtus oregoni SPAdes preassembly

description: .
DOI: 10.5281/zenodo.5573808
title: Microtus oregoni SPAdes preassembly

description: .
DOI: 10.34740/kaggle/dsv/2711798
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.5573846
title: Questões do Exame Nacional do Ensino Médio (ENEM)

description: Corpus estruturado do comando das questões do Exame Nacional do Ensino Médio (ENEM) do ano de 2016, 2017, 2018 e 2019.
DOI: 10.5281/zenodo.4667738
title: Questões do Exame Nacional do Ensino Médio (ENEM)

description: Corpus estruturado do comando das questões do Exame Nacional do Ensino Médio (ENEM) do ano de 2016, 2017, 2018 e 2019.
DOI: 10.5281/zenodo.1235445
title: Georges Laplace's archaeological offprints collection

description: Table of the offrint collection held by the prehistoric archaeologist Georges Laplace (1918–2004) at the <em>Centre de palethnographie stratigraphique</em> in Arudy, France. This index has been generated from the Georges Laplace archives in the <em>Musée national de Préhistoire</em> (Les Eyzies-de-Tayac, France) and the offprint collection of the TRACES laboratory (Toulouse, France). Each line corresponds to one offprint, which is described by 16 values (columns): <strong>ART_lang</strong>: language of the offprint. <strong>ART_title</strong>: title of the offprint. <strong>ART_year</strong>: publication year of the offprint. <strong>ART_journal</strong>: journal title in which the offprint was published. <strong>ART_fullref</strong>: unstructured reference of the journal title, issue, and pages of the offprint. <strong>aut1</strong>: first author of the offprint. <strong>aut2</strong> <strong>aut3</strong> <strong>aut4</strong> <strong>aut5</strong> <strong>aut6</strong> <strong>aut7</strong> <strong>aut8</strong> <strong>aut9</strong> <strong>aut10</strong> <strong>source</strong>: whether the line comes from the TRACES laboratory collection or the MNP collection.
DOI: 10.34740/kaggle/dsv/2711809
title: 2021 World Population (updated daily)
DOI: 10.6084/m9.figshare.14724447
title: Modeling_the_influence_of motor_skills_on_literacy_in_third_grade.xlsx

description: This data file was used for a study investigating the relationship between motor skills and literacy.The results are presented in the manuscript: "Modeling the influence of motor skills on literacy in third grade: Contributions of executive functions and handwriting"
DOI: 10.6084/m9.figshare.14724447.v2
title: Modeling_the_influence_of motor_skills_on_literacy_in_third_grade.xlsx

description: This data file was used for a study investigating the relationship between motor skills and literacy.The results are presented in the manuscript: "Modeling the influence of motor skills on literacy in third grade: Contributions of executive functions and handwriting"
DOI: 10.6084/m9.figshare.14724447.v1
title: Modeling_the_influence_of motor_skills_on_literacy_in_third_grade.xlsx

description: This data file was used for a study investigating the relationship between motor skills and literacy.The results are presented in the manuscript: "Modeling the influence of motor skills on literacy in third grade: Contributions of executive functions and handwriting"
DOI: 10.6084/m9.figshare.16817749
title: raw data of laying performance.xlsx

description: the raw data of laying performance is a part of project "the effect of natural vitamin E on laying hens"
DOI: 10.6084/m9.figshare.16817749.v2
title: raw data of laying performance.xlsx

description: the raw data of laying performance is a part of project "the effect of natural vitamin E on laying hens"
DOI: 10.6084/m9.figshare.16817749.v1
title: raw data of laying performance.xlsx

description: the raw data of laying performance is a part of project "the effect of natural vitamin E on laying hens"
DOI: 10.18112/openneuro.ds003834.v1.0.0
title: Shared neural codes for visual and semantic information about familiar faces in a common representational space
DOI: 10.34740/kaggle/dsv/2711927
title: COVID Vaccination in World (updated daily)
DOI: 10.5281/zenodo.5573837
title: Properties of initial and broken (PC4) WPI/lactose model powders

description: Supplementary Table. Properties of initial and broken (PC4) agglomerated WPI/lactose model powders.
description: This research was funded by the Teagasc, Agriculture and Food Development Authority of Ireland under project 0153.
DOI: 10.5281/zenodo.5573836
title: Properties of initial and broken (PC4) WPI/lactose model powders

description: Supplementary Table. Properties of initial and broken (PC4) agglomerated WPI/lactose model powders.
description: This research was funded by the Teagasc, Agriculture and Food Development Authority of Ireland under project 0153.
DOI: 10.5281/zenodo.5573886
title: Dataset associated to paper: Nanoscaffold effects on the performance of air-cathodes for microbial fuel cells: Sustainable Fe/N-carbon electrocatalysts for the oxygen reduction reaction under neutral pH conditions

description: This file contains the dataset associated to the published research article "Nanoscaffold effects on air-cathode performance in microbial fuel cells: Fe/N-carbon electrocatalysts for the oxygen reduction reaction under neutral pH conditions". The dataset contains X-ray powder diffraction, Inductively Coupled Plasma Emission Spectroscopy, elemental analysis, measurements of the specific surface area, transmission electron microscopies, x-ray photoelectron microscopy, electrochemistry and microbial fuel cells power outputs data from their relative instruments. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreements No. 799175 (HiBriCarbon) and No. 748968 (EDGE-FREEMAB). The results of this publication reflect only the authors' view and the Commission is not responsible for any use that may be made of the information it contains. This publication has also emanated from research conducted with the financial support of Science Foundation Ireland under Grant No. 13/CDA/2213 and 19/FFP/6761. SI kindly acknowledges support by the Department of Social Justice State Government of Maharashtra, India.
description: This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreements No. 799175 (HiBriCarbon) and No. 748968 (EDGE-FREEMAB).This publication has also emanated from research conducted with the financial support of Science Foundation Ireland under Grant No. 13/CDA/2213 and 19/FFP/6761. SI kindly acknowledges support by the Department of Social Justice State Government of Maharashtra, India.
DOI: 10.5281/zenodo.5573885
title: Dataset associated to paper: Nanoscaffold effects on the performance of air-cathodes for microbial fuel cells: Sustainable Fe/N-carbon electrocatalysts for the oxygen reduction reaction under neutral pH conditions

description: This file contains the dataset associated to the published research article "Nanoscaffold effects on air-cathode performance in microbial fuel cells: Fe/N-carbon electrocatalysts for the oxygen reduction reaction under neutral pH conditions". The dataset contains X-ray powder diffraction, Inductively Coupled Plasma Emission Spectroscopy, elemental analysis, measurements of the specific surface area, transmission electron microscopies, x-ray photoelectron microscopy, electrochemistry and microbial fuel cells power outputs data from their relative instruments. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreements No. 799175 (HiBriCarbon) and No. 748968 (EDGE-FREEMAB). The results of this publication reflect only the authors' view and the Commission is not responsible for any use that may be made of the information it contains. This publication has also emanated from research conducted with the financial support of Science Foundation Ireland under Grant No. 13/CDA/2213 and 19/FFP/6761. SI kindly acknowledges support by the Department of Social Justice State Government of Maharashtra, India.
description: This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreements No. 799175 (HiBriCarbon) and No. 748968 (EDGE-FREEMAB).This publication has also emanated from research conducted with the financial support of Science Foundation Ireland under Grant No. 13/CDA/2213 and 19/FFP/6761. SI kindly acknowledges support by the Department of Social Justice State Government of Maharashtra, India.
DOI: 10.5281/zenodo.5573875
title: Insights on the dynamics of vegetated alternate bars by means of flume experiments

description: The dataset consists of the measurements carried out in a mobile-bed laboratory flume to study the alterations induced by adding added artificial vegetation on the morphodynamics of hybrid bars.<br> The data are divided according to the initial setup of the flume and the density of vegetation deployed in the second phase. Each zip file contains the Digital Elevation Models (DEMs) of the bed topography, data regarding sediment transport and flow discharge, and elaborations of the surface flow field.
DOI: 10.18112/openneuro.ds003838.v1.0.0
title: EEG, pupillometry, ECG and photoplethysmography, and behavioral data in the digit span task
DOI: 10.6084/m9.figshare.16822213
title: Data Repository for 'Dayside Low Energy Electron Precipitation Driven by Hiss Waves in the Presence of Ionospheric Photoelectrons'

description: This is the dataset for 'Dayside Low Energy Electron Precipitation Driven by Hiss Waves in the Presence of Ionospheric Photoelectrons'. The paper is submitted to Journal of Geophysical Research: Space Physics. <br>As was demonstrated by many observations, hiss waves are often to observed in the dayside plasmasphere and plumes. Previous studies of hiss waves have been focused on the scattering of energetic electrons of 10–1,000 keV energies and only recently this focus was shifted to the energies below several keV down to the energies of tens of eV. These studies, however, did not include electrons of ionospheric origin photo- and secondary electrons. The major focus of our paper is dayside low energy electron precipitation driven by hiss waves in the presence of ionospheric photo- and secondary electrons. It is found that photoelectrons play an important role in hiss waves driven low energy electron precipitation phenomena. They are serving as the seed population that is required to study the low energy (below 1 keV) electrons using different kinetic approaches that are considered in this study.
DOI: 10.6084/m9.figshare.16822213.v1
title: Data Repository for 'Dayside Low Energy Electron Precipitation Driven by Hiss Waves in the Presence of Ionospheric Photoelectrons'

description: This is the dataset for 'Dayside Low Energy Electron Precipitation Driven by Hiss Waves in the Presence of Ionospheric Photoelectrons'. The paper is submitted to Journal of Geophysical Research: Space Physics. <br>As was demonstrated by many observations, hiss waves are often to observed in the dayside plasmasphere and plumes. Previous studies of hiss waves have been focused on the scattering of energetic electrons of 10–1,000 keV energies and only recently this focus was shifted to the energies below several keV down to the energies of tens of eV. These studies, however, did not include electrons of ionospheric origin photo- and secondary electrons. The major focus of our paper is dayside low energy electron precipitation driven by hiss waves in the presence of ionospheric photo- and secondary electrons. It is found that photoelectrons play an important role in hiss waves driven low energy electron precipitation phenomena. They are serving as the seed population that is required to study the low energy (below 1 keV) electrons using different kinetic approaches that are considered in this study.
DOI: 10.6084/m9.figshare.16822228
title: PONE-D-21-17805R1 minimal data set

description: Minimal data set for PONE-D-21-17805R1, manuscript titled <b>Diagnosis of <i>Streptococcus pneumoniae</i> Infection Using Circulating Antibody Secreting Cells </b><b></b>
DOI: 10.6084/m9.figshare.16822228.v1
title: PONE-D-21-17805R1 minimal data set

description: Minimal data set for PONE-D-21-17805R1, manuscript titled <b>Diagnosis of <i>Streptococcus pneumoniae</i> Infection Using Circulating Antibody Secreting Cells </b><b></b>
DOI: 10.5281/zenodo.5573887
title: spn

description: Experiments with WARC data from the Internet Archive's Save Page Now service.
DOI: 10.5281/zenodo.5552272
title: DeepDIVA automatic synthesizer programmer project

description: DeepDIVA is a data science project in which we aim to create a deep-learning syntheziser programmer using the vst plugin DIVA. We are creating a tool that addresses the challenge of programming sound synthesizers. This requires a thorough technical understanding as software synthesizers often have many parameters. To tackle this, we built a deep learning model for automatic synthesizer programming that takes a target sound as input, predicts the parameter settings for the synthesizer that cause it to emit as close a sound as possible, and generate a template that you can load in your DIVA synthesizer. In future work, we aim to improve the sound matching performance of our deep neural network architecture. At this point in time the sound matching performance of our best performing architecture is too limited for an application that users can integrate into their workflow, at least not for a synthesizer as complex as the Diva. We generated and saved datasets for training and validating deep learning models. Here we share the dataset (extracted features and patch targets) we created on which our currently best performing model is trained. For this dataset, 11 parameters of the DIVA synthesizers were allowed to vary during data generation.
DOI: 10.5281/zenodo.5552271
title: DeepDIVA automatic synthesizer programmer project

description: DeepDIVA is a data science project in which we aim to create a deep-learning syntheziser programmer using the vst plugin DIVA. We are creating a tool that addresses the challenge of programming sound synthesizers. This requires a thorough technical understanding as software synthesizers often have many parameters. To tackle this, we built a deep learning model for automatic synthesizer programming that takes a target sound as input, predicts the parameter settings for the synthesizer that cause it to emit as close a sound as possible, and generate a template that you can load in your DIVA synthesizer. In future work, we aim to improve the sound matching performance of our deep neural network architecture. At this point in time the sound matching performance of our best performing architecture is too limited for an application that users can integrate into their workflow, at least not for a synthesizer as complex as the Diva. We generated and saved datasets for training and validating deep learning models. Here we share the dataset (extracted features and patch targets) we created on which our currently best performing model is trained. For this dataset, 11 parameters of the DIVA synthesizers were allowed to vary during data generation.
DOI: 10.5517/ccng61b
title: CCDC 609461: Experimental Crystal Structure Determination

description: Related Article: F.R.Fronczek, Y.Marcos, A.W.Maverick|2006|CSD Communication|||
DOI: 10.6084/m9.figshare.10260983
title: Hydrogen mapping, laws and table.pdf

description: Item Removed.
DOI: 10.6084/m9.figshare.10260983.v2
title: Hydrogen mapping, laws and table.pdf

description: Item Removed.
DOI: 10.6084/m9.figshare.10260983.v1
title: Hydrogen mapping, laws and table.pdf

description: This is the theoretical demonstration of hydrogen enhancement and the laws governing this enhancement process. Only the first stage of the map and the table forms part of this article.
DOI: 10.18112/openneuro.ds003838.v1.0.1
title: EEG, pupillometry, ECG and photoplethysmography, and behavioral data in the digit span task