cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/mbmj2ymjmg.2
title: Data of mud and sand sediment transport by the 2011 Tohoku-oki tsunami at Sendai Plain, Japan

description: This dataset contains simulation data using Delft3D-FLOW. 

We put "erosion_sedimentation.mat" and "wd.mat" in the folder "Main results".  In the folder "Sensitivity test", we only put "erosion_sedimentation.mat"
erosion_sedimentation.mat; The distribution of sedimentation and erosion in domain 6 after the simulation.
wd.mat; The distribution of water depth with an interval of 5 min in domain 6.

We put our simulation data as follows.
Sensitivity test/Sand sediment transport; the simulation results in Table. 1.
Sensitivity test/Mud sediment transport; the simulation results in Table. 2.
Main results/Sand sediment transport; the simulation results in Table. 4.
Main results/Sand sediment transport; the simulation results in Table. 5.
DOI: 10.17632/f2gcgbkvgc.1
title: Data and Codes for "Central America's deindustrialization"

description: this zip file contains data and programs to replicate the figures and tables in the paper:
"Central America's Deindustrialization"

there are three main folders
01.data: contains the cleaned data used in the analysis. (for raw data and the programs to convert raw data to cleaned data please contact the author at rsinha.rs@gmail.com). the variable definitions for cleaned data located in .../02.clean/01.output/01.accounting and .../02.clean/01.output/02.model are provided in 01.def.var.xlsx.
02.tables: contains programs to replicate the tables (2-7) in the paper
03.figures: contains programs to replicate the figures in the paper and the appendix
DOI: 10.17632/dxzjr2z5yz.1
title: The Hippo pathway noncanonically drives autophagy and cell survival in response to energy stress (Seo. et al)

description: Raw data for the published study "The Hippo pathway noncanonically drives autophagy and cell survival in response to energy stress".
DOI: 10.17632/8yyfcm777k.1
title: Affect after team and individual exercise form

description: Research on 120 exercisers involved in team (60) and individual (60) exercises. We measured affect before and after an equal bout of exercise session. While apart exhaustion, positive affective states increased after individual exercise, they decreased after team exercises. These results indicate that the different attentional/mental processes during the exercise session determine the affect experienced after exercise. If one aims to feel better after exercise, individual forms of workout may be more beneficial than team exercises.
DOI: 10.17632/7fpvkxsh2d.1
title: PermEst4Statistics

description: The database presents the results of numerical estimation of absolute permeability and open porosity for four sandstone samples (sample7, sample25, sample31, sample78) and four carbonates (sampleAH, sample AL, sampleBH, sampleBL). The carbonates are considered at three different stages of CO_2 injection. To measure the permeability, each sample was divided into several subsamples. Each file contains the measurements of total porosity, open porosity, and permeability along each spatial direction for all subsamples. The structure of the files is 1 number of subsamples 4 bytes (N), porosity N*8 bytes, open porosity in X direction N*8bytes, open porosity in Y direction N*8bytes, open porosity in Z direction N*8bytes, permeability in X direction N*8bytes,  permeability in Y direction N*8bytes, permeability in Z direction N*8bytes. In addition, readData_Mendeley.m is provided, which reads the data.
DOI: 10.17632/9r67kdx4mv.1
title: Huang et al. Supplementary data

description: Supplementary material for the manuscript "Enhanced activation of mTORC1 signaling in eruptive xanthomas"  by Huang et al. 2023, JAAD International.
DOI: 10.17632/gxxjmw6gnc.1
title: Data of Agromorphological Traits of Butterfly Pea

description: This dataset contains data from 14 butterfly pea accessions (with 29 agromorphological traits observed). The traits were composed of 23 quantitative and 6 qualitative traits. Observation result showed some unique characteristics that is diverse in different origin.
DOI: 10.17632/yxc57jsm3p.1
title: JIE_export_replication

description: Replication files
DOI: 10.17632/5xnt9dn7nz.1
title: Data Set on selected soil properties of different land use system 

description: Land use changes under inadequate management techniques are the main causes of the loss of soil fertility and agricultural productivity. Hence, research on variability in soil characteristics across the land use type will have major impact on the planning of effective soil management for sustainable crop productivity. therefore this data studied selected soil properties namely pH, EC, OC, Avl. NPK, DTPA Zn, Cu, Mn, Fe, Soil MBC and microbial population. ). The data can be used to understand the changes in selected soil properties influenced by different land use system and to identify the integrated land management strategies that could aid in restoring soil fertility and so limit the soil deterioration.
DOI: 10.17632/yz6mvby9rn.1
title: Characterizing the 2020 summer floods in South China and effects on croplands. Chen et al.

description: The raw and analyzed data for "Characterizing the 2020 summer floods in South China and effects on croplands" published in iScience.
DOI: 10.17632/5pyf6bm36g.1
title: phbdataset

description: data collected from rural communities in Zimbabwe to evaluate preventive health behavior based on the health belief model.
DOI: 10.17632/s8xjt2jsxk.2
title: Research result data XCO2SAT+ P07 V01 2023-07-09

description: Scope:
Long-term time series of CO2 concentrations are required for studying e.g., the effects of rising CO2 concentrations on plants and ecosystems. Different methods for approximating column-averaged dry-air mole fractions of CO2 (XCO2) have been developed to substitute missing local CO2 measurements. 

This study presents a novel method (XCO2SAT+) for determining monthly XCO2 concentrations for selected sites, based entirely on observations from multiple satellites as well as statistical methods in the case of missing satellite data. The product currently covers a period of 16 years from 2003 to 2018. XCO2SAT+ results were validated against data of five European sites of the Total Carbon Column Observing Network (TCCON) and compared to two established XCO2 approximation methods. All three approximation methods were compared to CO2 measurements of German towers from the Integrated Carbon Observation System (ICOS). 

The mean absolute error (MAE) between the XCO2SAT+ method and TCCON site Karlsruhe, Germany ranges between 0.5 and 1.1 ppm (0.1 - 0.3%) for years 2014-2018. Mean differences between XCO2SAT+ and XCO2 approximation method CAMS-GCM shows a slightly better MAE of 0.1 – 0.3 ppm for CAMS-GCM at two German TCCON sites. Multi-year comparisons with ground-level ICOS measurements revealed a comparable seasonality of CO2 concentrations during the vegetation period, but underestimated high winter concentrations, a pattern also observed when comparing with CAMS-GCM. XCO2SAT+ is a suitable alternative and simple method for providing long-term time series of monthly averaged XCO2 concentrations for selected sites, expanding the methodological toolbox for in-situ CO2 research. The new method, which so far provides XCO2 concentrations, will thus serve as a first step towards providing further CO2 data sources, which could be used to further improve numerical models such as atmospheric models or crop growth models and to study CO2 impacts in agriculture and natural ecosystems.

Dataset:
The dataset includes research result data (XCO2 concentrations (ppm)) derived by the XCO2SAT+ method for years 2003 - 2018 and 5 TCCON sites in Europe and 5 ICOS sites in Germany.
DOI: 10.17632/s8xjt2jsxk.1
title: Research result data XCO2SAT+ P06 ALT8 2022-01-13

description: Scope:
In our Manuscript we describe a novel method (referred to as XCO2SAT+) for deriving time series of XCO2 concentrations for selected locations in Germany based on long-term observations from multiple satellites in combination with statistical methods. The product currently covers a period of 17 years and, with the approximation of XCO2 concentrations, represents a first step towards a further, alternative solution for studying CO2 effects for the above-mentioned research areas. Our intention is not to show regional maps of XCO2 concentrations, but for selected locations.

We validate the performance of the new XCO2SAT+ method with data from the Total Carbon Column Observing Network (TCCON, Wunch et al., 2011) and compare it with XCO2 concentrations derived via the SECM and CAMS-GCM methods. Finally, we compare the results of the SECM, CAMS-GCM and XCO2SAT+ methods using CO2 concentrations measured at various heights on towers of the Integrated Carbon Observation System (ICOS ERIC, 2021) in Germany.

Results:
The mean average error (MAE) between the XCO2SAT+ method and TCCON site Karlsruhe, Germany ranges between 0.9 and 1.2 ppm (0.2 - 0.3%) for years 2010-2019, except for 2012 and 2014. Mean differences between XCO2SAT+ and XCO2 approximation method CAMS-GCM shows a slightly better MAE of 0.2 – 0.3 ppm for CAMS-GCM at two German TCCON sites. Multi-year comparisons with ground-level ICOS measurements revealed a comparable seasonality of CO2 concentrations during the vegetation period, but underestimated high winter concentrations, a pattern also observed when comparing with CAMS-GCM. XCO2SAT+ is a suitable alternative and simple method for providing long-term time series of monthly averaged XCO2 concentrations for selected sites, expanding the methodological toolbox for in-situ CO2 research. The new method, which so far provides XCO2 concentrations, will thus serve as a first step towards providing further CO2 data sources, which could be used to further improve numerical models such as atmospheric models or crop growth models and to study CO2 impacts in agriculture and natural ecosystems.

Dataset:
The dataset includes research result data (XCO2 concentrations (ppm)) derived by the XCO2SAT+ method for years 2003 - 2019 and 7 locations in Germany (2 TCCON sites and 5 ICOS sites).
DOI: 10.17632/s8xjt2jsxk.3
title: Research result data XCO2SAT+ P07 V01 2023-07-11

description: Scope:
Long-term time series of CO2 concentrations are required for studying e.g., the effects of rising CO2 concentrations on plants and ecosystems. Different methods for approximating column-averaged dry-air mole fractions of CO2 (XCO2) have been developed to substitute missing local CO2 measurements. 

This study presents a novel method (XCO2SAT+) for determining monthly XCO2 concentrations for selected sites, based entirely on observations from multiple satellites as well as statistical methods in the case of missing satellite data. The product currently covers a period of 16 years from 2003 to 2018. XCO2SAT+ results were validated against data of five European sites of the Total Carbon Column Observing Network (TCCON) and compared to two established XCO2 approximation methods. All three approximation methods were compared to CO2 measurements of German towers from the Integrated Carbon Observation System (ICOS). 

The mean absolute error (MAE) between the XCO2SAT+ method and TCCON site Karlsruhe, Germany ranges between 0.5 and 1.1 ppm (0.1 - 0.3%) for years 2014-2018. Mean differences between XCO2SAT+ and XCO2 approximation method CAMS-GCM shows a slightly better MAE of 0.1 – 0.3 ppm for CAMS-GCM at two German TCCON sites. Multi-year comparisons with ground-level ICOS measurements revealed a comparable seasonality of CO2 concentrations during the vegetation period, but underestimated high winter concentrations, a pattern also observed when comparing with CAMS-GCM. XCO2SAT+ is a suitable alternative and simple method for providing long-term time series of monthly averaged XCO2 concentrations for selected sites, expanding the methodological toolbox for in-situ CO2 research. The new method, which so far provides XCO2 concentrations, will thus serve as a first step towards providing further CO2 data sources, which could be used to further improve numerical models such as atmospheric models or crop growth models and to study CO2 impacts in agriculture and natural ecosystems.

Dataset:
The dataset includes research result data (XCO2 concentrations (ppm)) derived by the XCO2SAT+ method for years 2003 - 2018 and 5 TCCON sites in Europe and 5 ICOS sites in Germany.
DOI: 10.17632/wpr3n7f4rf.1
title: Plant leaf images segmentation through multi-layer graph diffusion process.

description: We demonstrate the outcomes of our graph-based diffusion method that employs random walk with restart on a multi-layered graph using the publicly available Pl@ntleaves (H. Go¨eau, P. Bonnet, A. Joly, N. Boujemaa, D. Barth´el´emy, J.-F. Molino, P. Birnbaum, E. Mouysset, M. Picard, The clef 2011 plant images classification task, Vol. 1177, 2011.) dataset. This dataset consists of 233 high-resolution leaf images captured in their natural surroundings. The images present various challenges for segmentation, including shadows, varying lighting conditions, and overlapping leaves. Our algorithm focuses on leaf portions by spreading intensity scores from foreground templates to image boundaries. By applying a threshold to the saliency maps generated through the diffusion process, we obtain binary masks that separate the leaves from the backgrounds. Ground truth images are provided to visually assess the effectiveness of our algorithm's performance.
Folders description:
* JPEGimages: Leaf color images.
* masks: The ground truth binary masks that accurately delineat the leaf regions.
* foreground_template:  contains the bounding boxes that localize the leaves in blue and the foreground templates in red drawn on dataset images.
* saliency_maps:  contains saliency maps obtained by diffusing foreground queries within a multi-layer graph.
* segmentation_results : contains the segmentation results obtained after thresholding the saliency maps.
*MLG_Segmentation_results: a compressed folder containing the above folders.
DOI: 10.17632/3ymdm6gf72.1
title: Data_questionnaire_job performance

description: This is the data gathered through questionnaires distributed to over 400 respondents in the moroccan public sector
DOI: 10.5281/zenodo.8143426
title: macoma_nasuta_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8143425
title: macoma_nasuta_zanfona_1.fasta.gz

description: .
DOI: 10.17632/6x3jsjcc3r.1
title: Computational Study Instances of the Multi-visit Drone Pickup and Delivery Routing Problem Considering Time Windows

description: The set includes all instances used in the multi-visit drone pickup and delivery problem considering time windows:
1. Small instances 
2. Large instances
3. Instances for sensitivity analysis
4.Instances based on a real network
DOI: 10.17632/6x3jsjcc3r.2
title: Computational Study Instances of the Multi-visit Drone Pickup and Delivery Routing Problem Considering Time Windows

description: The set includes all instances used in the multi-visit drone pickup and delivery problem considering time windows:
1. Small instances 
2. Large instances
3. Instances for sensitivity analysis
4.Instances based on a real network
DOI: 10.17632/6x3jsjcc3r.3
title: Computational Study Instances of the Multi-visit Drone Pickup and Delivery Routing Problem Considering Time Windows

description: The set includes all instances used in the multi-visit drone pickup and delivery problem considering time windows:
1. Small instances 
2. Large instances
3. Instances for sensitivity analysis
4.Instances based on a real network
DOI: 10.17632/xtz43w2n6h.1
title: Citizen participation gaps and challenges in Dutch community heating initiatives: List of project content analyzed

description: This document outlines all the content analyzed in the paper: Citizen participation gaps and challenges in Dutch community heating initiatives. The aim of sharing the list of content is for researchers to understand the underlying data of the paper and to replicate the case study design
DOI: 10.17632/7gkjf92n9r.1
title: Interview Summaries: Citizen Participation Gaps and Challenges in Dutch Community Heating Initiatives

description: The anonymized summary of the semi-structured interviews conducted for the paper: Citizen participation gaps and challenges in Dutch community heating initiatives
DOI: 10.17632/8tph4gkfm8.1
title: Analysis of Sound Pressure Levels and Acoustic Intelligibility Indexes in Classrooms on Campus I of the Federal University of Paraíba (UFPB)

description: This project aims to elucidate the sound pressure levels (SPL) and the acoustic intelligibility characteristics of classrooms on Campus I of the Federal University of Paraíba (UFPB)(TALBOTSMITH, 1999, p. 1-12; 5-14; EVEREST, 2001, p. 39; 148-149; EARGLE, 2002, p. 97-98). The initiative is established as the second stage of the research project entitled: analysis of sound pressure levels on Campus I of UFPB, approved by the Department of Digital Media (DEMID/ CCHLA/ UFPB) in 2015 and implemented in 2016, which enabled the identification of sound pressure levels (SPL) in 08 (eight) locations on Campus I of the Institution, characterised by high levels of sound pressure in relation to the thresholds defined as safe by the World Health Organisation (WHO), in auditory and psychophysiological terms (SONODA, 2016a; 2016b; SONODA; PONTES, 2018). This second stage of the research has the purpose of elucidating, exclusively, the internal acoustic context of classrooms on Campus I of UFPB, focusing on analysis of SPL and characteristics of acoustic intelligibility of these environments, both on pedagogical-educational occasions (classes) and in acoustic-structural analyses without the presence of an audience (teachers and students). The methodology will include bibliographic-documentary, acoustic-structural analysis (SPL, intelligibility characteristics, noise sources, reflexion and refraction indices, etc.), in addition to statistical analysis for an adequate interpretation of the identified data. In terms of results, it is expected to elucidate both the contemporary picture corresponding to the acoustic-structural characteristics of classrooms on Campus I of the UFPB and the implications of these aspects in terms of damage to students and federal employees, whether in terms of damage to health of those involved or in terms of negative impacts on student educational productivity. In this sense, the present project establishes itself as an essential mechanism in the sense of pointing out coherent and feasible ways, in terms of institutional measures, for acoustic-structural adaptations in the aforementioned pedagogical environments, in order to enable an increase in the student's educational performance concomitantly to a reduction in the possibilities of health damage for students and federal employees.
Keywords: Sound pressure levels (SPL). Acoustic intelligibility. Classrooms. Campus I. Federal University of Paraíba (UFPB).
DOI: 10.17632/6k7bkfkwfb.1
title: Code Book for data in Citizen participation gaps and challenges in Dutch community heating initiatives

description: This code book ha s been created to facilitate the coding and analysis of interviews, surveys,
websites, reports, and other content collected for the research project titled "Citizen participation
gaps and challenges in Dutch community heating initiatives." The purpose of t his code book is to
provide a standardized framework for coding the collected data and to ensure consistency in the
analysis process.
DOI: 10.17632/t83kt3wnn8.1
title: Dog walking

description: Dog walking during covid 19
DOI: 10.17632/rhrggss272.1
title: MOCO-GCN

description: The datasets includes 107 metagenomic samples from Spanish and 76 samples from German based on fecal microbial species. Missing values in the German metadata were imputed using the missForest algorithm, a random forest-based method for missing data imputation. The imputation process involved the construction of 100 trees to accurately estimate and fill in the missing values. Of these, every metadata was able to be defined as a binary variable with a positive and negative class, for example, alcohol was considered positive for drinkers and negative for non-drinkers.
DOI: 10.17632/85sy7h4967.1
title: APPENDIX for: Going Viral On Advertising Youtube Video Detecting The Influences

description: APPENDIX A - Images used in the data collection
DOI: 10.17632/mwgvg882gb.1
title: Plant leaf images segmentation via graph diffusion process

description: We present the segmentation results obtained from our graph-based diffusion process using random walk with restart on a mono-layered graph using the public Pl@ntleaves (H. Go¨eau, P. Bonnet, A. Joly, N. Boujemaa, D. Barth´el´emy, J.-F. Molino, P. Birnbaum, E. Mouysset, M. Picard, The clef 2011 plant images classification task, Vol. 1177, 2011.) dataset. The dataset comprises 233 high-resolution leaf images captured in their natural environment. The images include various artefacts that pose challenges to the segmentation task, such as shadows, varying illumination, and the presence of overlapping leaves. Our algorithm emphasizes the leaf parts by diffusing intensity scores from foreground templates towards image boundaries. The resulting saliency maps are further refined through a fusion process with saliency maps generated by random forests. The refined saliency maps are then thresholded to extract the leaves from their backgrounds. Ground truth images are available to visually evaluate the effectiveness of our algorithm's performance.
Folders description:
* JPEGimages: Leaf color images.
* masks: The ground truth binary masks that accurately delineat the leaf regions.
* foreground_template:  contains the bounding boxes that localize the leaves in blue and the foreground templates in red drawn on dataset images.
* DF_sal: contains the saliency maps derived from the diffusion process within the graph.
* RF_sal: contains the saliency maps generated by random forests.
* final_sal: contains the final saliency maps obtained after the fusion process.
* PRE_segmentation:  contains the segmentation results obtained after thresholding the final saliency map and before refinement.
* final_segmentation: contains the final segmentation results obtained after refinement.
*SLG_Segmentation results: a compressed folder containing the above folders