cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20058959
title: Persuasive Strategies and Their Implementations in Mobile Interventions for Physical Activity: A Systematic Review

description: Unhealthy lifestyle behaviors such as spending too many hours sitting and inadequate physical activity (PA) can contribute to different chronic diseases. Research has revealed the capabilities of digital technology interventions such as persuasive technologies (PTs) for providing health support and encouraging healthy behavior changes to assist people in preventing chronic diseases and having healthier lifestyles. Thus, the use of mobile technology to deliver PT interventions has dramatically increased, especially for promoting PA and reducing sedentary behavior (SB) by employing various persuasive strategies (PSs). This paper provides a systematic review of 16 years of research from 2006 to 2021. The review aims to (1) explore the various ways each strategy is implemented on mobile-based PTs for PA and SB, (2) evaluate the effectiveness of different ways of implementing the PSs on mobile-based PT interventions for PA and SB, (3) provide a comparison of the different ways of implementing each PS, (4) show the weaknesses and strengths of the interventions based on the strategies and implementations, (5) highlight the limitations and pitfalls of the existing research, and (6) give recommendations and directions for future research.
DOI: 10.6084/m9.figshare.20058959.v1
title: Persuasive Strategies and Their Implementations in Mobile Interventions for Physical Activity: A Systematic Review

description: Unhealthy lifestyle behaviors such as spending too many hours sitting and inadequate physical activity (PA) can contribute to different chronic diseases. Research has revealed the capabilities of digital technology interventions such as persuasive technologies (PTs) for providing health support and encouraging healthy behavior changes to assist people in preventing chronic diseases and having healthier lifestyles. Thus, the use of mobile technology to deliver PT interventions has dramatically increased, especially for promoting PA and reducing sedentary behavior (SB) by employing various persuasive strategies (PSs). This paper provides a systematic review of 16 years of research from 2006 to 2021. The review aims to (1) explore the various ways each strategy is implemented on mobile-based PTs for PA and SB, (2) evaluate the effectiveness of different ways of implementing the PSs on mobile-based PT interventions for PA and SB, (3) provide a comparison of the different ways of implementing each PS, (4) show the weaknesses and strengths of the interventions based on the strategies and implementations, (5) highlight the limitations and pitfalls of the existing research, and (6) give recommendations and directions for future research.
DOI: 10.17632/647jsm4m36.1
title: Estrategia de apropiación social del conocimiento en la isquemia cardiaca

description: Estos son las evidencias de los talleres desarrollados con pacientes en grupos focales con preguntas semiestructuras para la creación de la estrategia de Apropiación Social de la Ciencia, la Tecnología y la Innovación (ASCTeI) que aquí se presenta, busca contribuir al fortalecimiento del cuidado de la salud cardiovascular en las personas con enfermedad isquémica cardiaca, mediante el enfoque de la comunicación social, a través de la herramienta tipo MHealth (página web/app), soportado en el creciente auge en el uso de tecnologías de la información y comunicación (TIC) para la atención en salud, en co-creación con los diferentes actores y articulando la evidencia científica frente a la temática.
DOI: 10.17632/sjvbr6pw4n.1
title: Data-Making Meaning in Multimodal Texts

description: This data contains the Comprehension Scores of Two Levels of Struggling Readers to two different multimodal texts (Comic and YouTube). This data also contains Lexical Richness measures of struggling readers of select Government schools in India.
DOI: 10.17632/984bcsp4yt.1
title: 维生素A儿科数据

description: 记录了基础数据，维生素浓度，膳食数据
DOI: 10.6084/m9.figshare.19860472
title: Data from: The hydrochorous dispersal of plant propagules in a giant river reservoir: implications for restoration of riparian vegetation

description: <strong>Effects of environmental variables</strong> The effects of environmental variables on the downstream dispersal distance of propagule mimics. Abbreviations: D90 (the distances when 90% of retrieved propagule mimics were retained), WaterLevel (water level variation), Sinuosity (channel sinuosity), NetWind_Down (cumulative net wind speed towards downstream direction), Width (channel width), FlowVelocity (flow velocity). <strong>Filename</strong>: Table 2.CSV <br> <strong>Dispersal distance of propagule mimics</strong> The dispersal distance of propagule mimics in three regulated tributaries. The positive and negative values in the column ‘Dispersal distance (km)’ indicate the downstream and upstream distance from the release points, respectively. <strong>Filename</strong>: Figure 3.xlsx <br> <strong>Water level variation</strong> The water level variation of the Three Gorges Reservoir (TGR) during the release period of propagule mimics. The positive and negative values in the column ‘Relative water level (m)’ indicate the water level of the TGR raised and declined, respectively. <strong>Filename</strong>: Figure 4_Left.xlsx <br> <strong>Retrieved propagule mimics stranded on shorelines</strong> The percentage of retrieved propagule mimics stranded on shorelines of three regulated rivers under raising and declining water levels. <strong>Filename</strong>: Figure 4_Right.xlsx <br> <strong>Retained patterns of the retrieved propagule mimics</strong> Percentage of the retrieved propagule mimics staying in the water and stranded on shorelines. <strong>Filename</strong>: Figure 5_Left.xlsx <br> <strong>Propagule mimics stranded on different slope gradients</strong> Percentage of propagule mimics stranded on riparian zones with different slope gradients. Seven instead of nine release events are shown because the other two release events had no propagule mimics stranding on shorelines. <strong>Filename</strong>: Figure 5_Right.xlsx <br> <strong>The floating ability of propagule mimics with different painting patterns</strong> <strong>Filename</strong>: Figure_S1.xlsx <br> <strong>Projected wind speed</strong> Projected wind speed towards downstream (positive values) and upstream directions (negative values). <strong>Filename</strong>: Figure_S3.xlsx
DOI: 10.6084/m9.figshare.23522433
title: Data from Adaptive phenotypic plasticity induces individual variability along a cognitive trade-off

description: Datasets supporting the study.
DOI: 10.6084/m9.figshare.23522433.v1
title: Data from Adaptive phenotypic plasticity induces individual variability along a cognitive trade-off

description: Datasets supporting the study.
DOI: 10.48758/ufz.12622
title: Eddy covariance rawdata from grassland site 'Am Grossen Bruch' (DE-GsB) in Central Germany for May 2015 (201505)

description: eddy covariance raw data (20Hz) from Am Grossen Bruch (Grosses Bruch) in 2.3m height, acquisition of CSAT3, LI7500 and LI7700 with eddymeas, converted from slt- and dia-files to ascii-format (u, v, w, T_Sonic, CO2, H2O, p_75, CH4, P_77, T_77, SA_DIAG, GA75_DIAG, GA77_DIAG_a, GA77_DIA_b), no time column, individual file names are indicating the starting time of the data acquisition period (according to RFlux-requirements)

sonic alignment: 280 deg
IRGA: LI75H-1600

Am Grossen Bruch DoY 121-151 (May 2015)

file: DE-GsB_201505_eddy-raw_csv.zip
DOI: 10.5258/soton/d2283
title: Dataset for the PhD thesis of Alexander Black entitled 'Characterisation and application of weakly coordinating solvents for the electrodeposition of semiconductors'

description: Dataset contains values underpinning graphs and microscope images from figures in the thesis. This includes cyclic voltammograms at macro and microdisc electrodes investigating the effect of variables, plots resulting from further quantitative analysis of voltammograms, SEM images of electrodeposited materials, XRD patterns of electrodeposited materials and Raman spectra of electrodeposited materials The data is composed of various experimental information collected throughout the above thesis, including electrochemical data such as voltammograms, or chronoamperograms, as well as data from physical characterisation methods such as scanning electron microscopy (SEM) images or X-ray diffraction patterns. All graphical data is included in a single .opju file which each figure corresponding to a single book, SEM images are organised into folders corresponding to each results Chapter in the thesis.
DOI: 10.5281/zenodo.7956942
title: Lung nodule CT false positive reduction

description: This data set is part of the public development data for the 2023 Automated Universal Classification Challenge (AUC23). The data set concerns the classification of lung nodules on screening thoracic computed tomography (CT) scans and was derived from the 2016 Lung Nodule Analysis (LUNA) challenge. The data set was previously introduced and described by Setio et al. (2017) and no images or patient information were added. Only the "false positive reduction" track was considered, where a provided set of nodule candidates should be classified. Data was restructured in compliance with the AUC23 challenge format. The data set was collected from the largest publicly available reference database for lung nodules: The Lung Image Database Consortium image collection. Images are 3D tensors: 0: 3D axial screening CT scan (cropped to candidate nodule's region of interest) Classification labels: 0: Is a nodule 1: Is not a nodule Folder structure: imagesTr (root folder with all patients and studies)<br> ├── LUNA16_0000_0000.mha (axial CT imaging for nodule 0000)<br> ├── LUNA16_0000_0002.mha (axial CT imaging for nodule 0002)<br> ├── ...<br> Please cite the following article if you are using the 2016 Lung Nodule Analysis (LUNA) challenge false positive reduction track data set: <pre><code>Setio AAA, Traverso A, de Bel T, Berens MSN, Bogaard CVD, Cerello P, Chen H, Dou Q, Fantacci ME, Geurts B, Gugten RV, Heng PA, Jansen B, de Kaste MMJ, Kotov V, Lin JY, Manders JTMC, Sóñora-Mengana A, García-Naranjo JC, Papavasileiou E, Prokop M, Saletta M, Schaefer-Prokop CM, Scholten ET, Scholten L, Snoeren MM, Torres EL, Vandemeulebroucke J, Walasek N, Zuidhof GCA, Ginneken BV, Jacobs C. Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge. Med Image Anal. 2017 Dec;42:1-13. doi: 10.1016/j.media.2017.06.015. Epub 2017 Jul 13. PMID: 28732268.</code></pre>
description: {"references": ["Setio AAA, Traverso A, de Bel T, Berens MSN, Bogaard CVD, Cerello P, Chen H, Dou Q, Fantacci ME, Geurts B, Gugten RV, Heng PA, Jansen B, de Kaste MMJ, Kotov V, Lin JY, Manders JTMC, S\u00f3\u00f1ora-Mengana A, Garc\u00eda-Naranjo JC, Papavasileiou E, Prokop M, Saletta M, Schaefer-Prokop CM, Scholten ET, Scholten L, Snoeren MM, Torres EL, Vandemeulebroucke J, Walasek N, Zuidhof GCA, Ginneken BV, Jacobs C. Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge. Med Image Anal. 2017 Dec;42:1-13. doi: 10.1016/j.media.2017.06.015. Epub 2017 Jul 13. PMID: 28732268."]}
DOI: 10.5281/zenodo.7956943
title: Lung nodule CT false positive reduction

description: This data set is part of the public development data for the 2023 Automated Universal Classification Challenge (AUC23). The data set concerns the classification of lung nodules on screening thoracic computed tomography (CT) scans and was derived from the 2016 Lung Nodule Analysis (LUNA) challenge. The data set was previously introduced and described by Setio et al. (2017) and no images or patient information were added. Only the "false positive reduction" track was considered, where a provided set of nodule candidates should be classified. Data was restructured in compliance with the AUC23 challenge format. The data set was collected from the largest publicly available reference database for lung nodules: The Lung Image Database Consortium image collection. Images are 3D tensors: 0: 3D axial screening CT scan (cropped to candidate nodule's region of interest) Classification labels: 0: Is a nodule 1: Is not a nodule Folder structure: imagesTr (root folder with all patients and studies)<br> ├── LUNA16_0000_0000.mha (axial CT imaging for nodule 0000)<br> ├── LUNA16_0000_0002.mha (axial CT imaging for nodule 0002)<br> ├── ...<br> Please cite the following article if you are using the 2016 Lung Nodule Analysis (LUNA) challenge false positive reduction track data set: <pre><code>Setio AAA, Traverso A, de Bel T, Berens MSN, Bogaard CVD, Cerello P, Chen H, Dou Q, Fantacci ME, Geurts B, Gugten RV, Heng PA, Jansen B, de Kaste MMJ, Kotov V, Lin JY, Manders JTMC, Sóñora-Mengana A, García-Naranjo JC, Papavasileiou E, Prokop M, Saletta M, Schaefer-Prokop CM, Scholten ET, Scholten L, Snoeren MM, Torres EL, Vandemeulebroucke J, Walasek N, Zuidhof GCA, Ginneken BV, Jacobs C. Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge. Med Image Anal. 2017 Dec;42:1-13. doi: 10.1016/j.media.2017.06.015. Epub 2017 Jul 13. PMID: 28732268.</code></pre>
description: {"references": ["Setio AAA, Traverso A, de Bel T, Berens MSN, Bogaard CVD, Cerello P, Chen H, Dou Q, Fantacci ME, Geurts B, Gugten RV, Heng PA, Jansen B, de Kaste MMJ, Kotov V, Lin JY, Manders JTMC, S\u00f3\u00f1ora-Mengana A, Garc\u00eda-Naranjo JC, Papavasileiou E, Prokop M, Saletta M, Schaefer-Prokop CM, Scholten ET, Scholten L, Snoeren MM, Torres EL, Vandemeulebroucke J, Walasek N, Zuidhof GCA, Ginneken BV, Jacobs C. Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge. Med Image Anal. 2017 Dec;42:1-13. doi: 10.1016/j.media.2017.06.015. Epub 2017 Jul 13. PMID: 28732268."]}
DOI: 10.5281/zenodo.8042115
title: Lung nodule CT false positive reduction

description: This data set is part of the public development data for the 2023 Automated Universal Classification Challenge (AUC23). The data set concerns the classification of lung nodules on screening thoracic computed tomography (CT) scans and was derived from the 2016 Lung Nodule Analysis (LUNA) challenge. The data set was previously introduced and described by Setio et al. (2017) and no images or patient information were added. Only the "false positive reduction" track was considered, where a provided set of nodule candidates should be classified. Data was restructured in compliance with the AUC23 challenge format. The data set was collected from the largest publicly available reference database for lung nodules: The Lung Image Database Consortium image collection. Images are 3D tensors: 0: 3D axial screening CT scan (cropped to candidate nodule's region of interest) Classification labels: 0: Is a nodule 1: Is not a nodule Folder structure: imagesTr (root folder with all patients and studies)<br> ├── LUNA16_0000_0000.mha (axial CT imaging for nodule 0000)<br> ├── LUNA16_0000_0002.mha (axial CT imaging for nodule 0002)<br> ├── ...<br> Please cite the following article if you are using the 2016 Lung Nodule Analysis (LUNA) challenge false positive reduction track data set: <pre><code>Setio AAA, Traverso A, de Bel T, Berens MSN, Bogaard CVD, Cerello P, Chen H, Dou Q, Fantacci ME, Geurts B, Gugten RV, Heng PA, Jansen B, de Kaste MMJ, Kotov V, Lin JY, Manders JTMC, Sóñora-Mengana A, García-Naranjo JC, Papavasileiou E, Prokop M, Saletta M, Schaefer-Prokop CM, Scholten ET, Scholten L, Snoeren MM, Torres EL, Vandemeulebroucke J, Walasek N, Zuidhof GCA, Ginneken BV, Jacobs C. Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge. Med Image Anal. 2017 Dec;42:1-13. doi: 10.1016/j.media.2017.06.015. Epub 2017 Jul 13. PMID: 28732268.</code></pre>
description: {"references": ["Setio AAA, Traverso A, de Bel T, Berens MSN, Bogaard CVD, Cerello P, Chen H, Dou Q, Fantacci ME, Geurts B, Gugten RV, Heng PA, Jansen B, de Kaste MMJ, Kotov V, Lin JY, Manders JTMC, S\u00f3\u00f1ora-Mengana A, Garc\u00eda-Naranjo JC, Papavasileiou E, Prokop M, Saletta M, Schaefer-Prokop CM, Scholten ET, Scholten L, Snoeren MM, Torres EL, Vandemeulebroucke J, Walasek N, Zuidhof GCA, Ginneken BV, Jacobs C. Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge. Med Image Anal. 2017 Dec;42:1-13. doi: 10.1016/j.media.2017.06.015. Epub 2017 Jul 13. PMID: 28732268."]}
DOI: 10.18112/openneuro.ds004606.v1.0.3
title: A Polish Electroencephalography, Alzheimer’s Risk-genes, Lifestyle and Neuroimaging (PEARL-Neuro) Database
DOI: 10.5281/zenodo.7885835
title: Data for "Minimizing non-radiative decay in molecular aggregates through control of excitonic coupling"

description: Data for "Minimizing non-radiative decay in molecular aggregates through control of excitonic coupling". "Adding 'FIG.5c-20230615.npz' to match the revised manuscript" - Updated 2023.06.15
DOI: 10.5281/zenodo.7885836
title: Data for "Minimizing non-radiative decay in molecular aggregates through control of excitonic coupling"

description: Data for "Minimizing non-radiative decay in molecular aggregates through control of excitonic coupling"
DOI: 10.5281/zenodo.8019771
title: Data for "Minimizing non-radiative decay in molecular aggregates through control of excitonic coupling"

description: Data for "Minimizing non-radiative decay in molecular aggregates through control of excitonic coupling". Upadated 2023-06-09
DOI: 10.5281/zenodo.8042117
title: Data for "Minimizing non-radiative decay in molecular aggregates through control of excitonic coupling"

description: Data for "Minimizing non-radiative decay in molecular aggregates through control of excitonic coupling". "Adding 'FIG.5c-20230615.npz' to match the revised manuscript" - Updated 2023.06.15
DOI: 10.25345/c55717z47
title: MassIVE MSV000092169 - MYC as a Key Regulator of Protein Synthesis: Characterization of Downstream Targets in Multiple Myeloma
title: Multiple myeloma (MM) is a malignant plasma cell disorder and frequently characterized by the 16 dysregulation of the MYC oncogene, which is associated with poor prognosis and disease progression. While MYC's involvement in transcriptional regulation is well-established, the functional role of MYC target proteins and the impact on post-transcriptional processes in MM cells remain poorly understood. This study employed Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC) coupled with mass spectrometry analysis to investigate the effects of MYC depletion on the proteome of MM cells. The results revealed that MYC primarily regulates translational processes. Specifically, the three RNA-binding proteins (RBPs) 4EBP1, hnRNPC, and LARP1, were prominently down-regulated upon MYC depletion in MM cells. Notably, high expression levels of these proteins were correlated with poor survival and disease progression in MM patients. These findings highlight the critical role of MYC in the regulation of translation and identify 4EBP1, hnRNPC, and LARP1 as MYC target proteins. Targeting these proteins may offer new therapeutic strategies and prognostic markers for MM, potentially improving patient outcomes. This study provides valuable insights into the post-transcriptional regulatory mechanisms mediated by MYC and opens avenues for further research in understanding and treating this devastating disease.
DOI: 10.5281/zenodo.8034245
title: RMLStreamer with Reference Conditions in the KGCW Challenge 2023

description: This repository contains all necessary data to reproduce the participation of RMLStreamer with reference conditions in the KGCW 2023 Challenge, as well as the reported results. For more information we refer to the related paper: <em>E. de Vleeschauwer, G.Haesendonck, D. Van Assche. B. De Meester, RMLStreamer with Reference Conditions in the<br> KGCW Challenge 2023, in: Proceedings of the 4rd International Workshop on Knowledge Graph Construction (KGCW 2023) co-located with 20th Extended Semantic Web Conference (ESWC 2023), 2023</em>
DOI: 10.5281/zenodo.8034244
title: RMLStreamer with Reference Conditions in the KGCW Challenge 2023

description: This repository contains all necessary data to reproduce the participation of RMLStreamer with reference conditions in the KGCW 2023 Challenge, as well as the reported results. For more information we refer to the related paper: <em>E. de Vleeschauwer, G.Haesendonck, D. Van Assche. B. De Meester, RMLStreamer with Reference Conditions in the<br> KGCW Challenge 2023, in: Proceedings of the 4rd International Workshop on Knowledge Graph Construction (KGCW 2023) co-located with 20th Extended Semantic Web Conference (ESWC 2023), 2023</em>
DOI: 10.1285/i6226376600
title: Scavi e Ricerche a Shahr-i Sokhta = Excavations and Researches at Shahr-i Sokhta
DOI: 10.6084/m9.figshare.23522355
title: Supplementary file 1

description: Raw files (fasta)
DOI: 10.6084/m9.figshare.23522355.v1
title: Supplementary file 1

description: Raw files (fasta)
DOI: 10.1285/i6226376600p1
title: Frontespizio e pagine iniziali
DOI: 10.1285/i6226376600p5
title: Indice
DOI: 10.1285/i6226376600p9
title: Prefazione
DOI: 10.1285/i6226376600p13
title: Il Progetto Archeologico Multidisciplinare Internazionale a Shahr-i Sokhta (= MAIPS)
DOI: 10.1285/i6226376600p19
title: Rapporto preliminare sugli scavi 2017 in Area 33 a Shahr-i Sokhta
DOI: 10.1285/i6226376600p75
title: Gli oggetti dell'Area 33 a Shahr-i Sokhta
DOI: 10.5281/zenodo.8033453
title: Parameterization of beam—beam-induced optical distortions of van der Meer scans at the LHC

description: These two data sets provide the coefficients of the parameterisation of the (L/L<sub>0</sub>)<sub>Opt</sub> luminosity-bias factor as a function of the normalized nominal separation, for horizontal and vertical vdM scans, respectively. The data sets are part of a paper with title "Impact of Beam-Beam Effects on Absolute Luminosity Calibrations at the CERN Large Hadron Collider" and are referred thereby as Table 10 and Table 11.
DOI: 10.5281/zenodo.8033452
title: Parameterization of beam—beam-induced optical distortions of van der Meer scans at the LHC

description: These two data sets provide the coefficients of the parameterisation of the (L/L<sub>0</sub>)<sub>Opt</sub> luminosity-bias factor as a function of the normalized nominal separation, for horizontal and vertical vdM scans, respectively. The data sets are part of a paper with title "Impact of Beam-Beam Effects on Absolute Luminosity Calibrations at the CERN Large Hadron Collider" and are referred thereby as Table 10 and Table 11.
DOI: 10.1285/i6226376600p115
title: La ceramica dell'Area 33 a Shahr-i Sokhta
DOI: 10.1285/i6226376600p137
title: Considerazioni insediamentali sull'abitato e demografiche sulla necropoli di Shahr-i Sokhta
DOI: 10.1285/i6226376600p159
title: Nota su tre potenziali pesi da bilancia rinvenuti nel Building 33 di Shahr-i Sokhta
DOI: 10.1285/i6226376600p165
title: Studio preliminare del vasellame in alabastro dal Building 33 a Shahr-i Sokhta: tipologia e analisi petrografiche
DOI: 10.25345/c51g0j49d
title: MassIVE MSV000092170 - DNA AP-MS on E. coli cells grown in presence of different amino acids
title: AP-MS to identify transcription factors binding to specific DNA regions used as bait. Cells were grown in M9 medium supplemented with specific amino acids. See associated publication for details.
DOI: 10.1285/i6226376600p195
title: Ricerche topografiche a Shahr-i Sokhta: rapporto preliminare
DOI: 10.1285/i6226376600p209
title: Risultati preliminari dello studio dei resti animali provenienti dal sito di Shahr-i Sokhta, Iran: nuove ricerche
DOI: 10.1285/i6226376600p221
title: Gli strumenti in materia dura di origine animale provenienti da Shahr-i Sokhta: analisi preliminare
DOI: 10.1285/i6226376600p245
title: Under the Surface. The Geomagnetic Survey at Shahr-i Sokhta in 2017