cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/43ndspvpsx.1
title: Agent-based modeling and reinforcement learning for equitable waste transitions in Costa Rica: A national policy stress-test

description: CONTENT

ABMMACHINENEW.py – Agent-based model of household waste and recycling with optional PAYT policy. Outputs province-level and national waste, recycling, CO₂ and biogas indicators (model_summary.csv, agent_final_states.csv).

ECONOMICNEWWASTE.py – Uses ABM and RL outputs (agent_final_states.csv, agent_states_RL.csv) to compute annualized flows, total cost, cost per ton of waste and per kg CO₂, and discounted cost metrics. Outputs economic_comparison_results.csv and cost_breakdown.csv.

WASTESENSIVILITYNEW.py – ±20% one-way sensitivity analysis on key cost parameters for ABM and RL strategies. Outputs sensitivity_analysis_results.csv for tornado plots and robustness checks.

RLFIGURENEW.py – Builds a 2×2 figure with RL results by province (CO₂ avoided, recycling share, landfill mass) and cumulative recycling rate over time using agent_states_RL.csv and model_vars_RL.csv.

FUGREALLPROVINCES.py – Creates heatmaps of household accessibility to existing and potential facilities by province and distance band using ACCESS_FINAL_OUTPUT.csv.

Shapefiles (inputLayers.*, FindCentroidsOutput.*) – GIS layers used to derive accessibility metrics. Provided for transparency; not required to run the Python scripts, which work from CSVs.
DOI: 10.15468/dl.tzj87q
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Protobothrops dabieshanensis)",
 "Country is one of (China, India, Indonesia, Pakistan, Bangladesh, Japan, Philippines, Viet Nam, Türkiye, Iran (Islamic Republic of), Thailand, Myanmar, Korea, Republic of, Korea (Democratic People’s Republic of), Iraq, Afghanistan, Saudi Arabia, Uzbekistan, Malaysia, Yemen, Nepal, Sri Lanka, Kazakhstan, Syrian Arab Republic, Cambodia, Jordan, Azerbaijan, United Arab Emirates, Tajikistan, Israel, Lao People’s Democratic Republic, Lebanon, Kyrgyzstan, Turkmenistan, Singapore, Oman, Palestine, State of, Kuwait, Georgia, Mongolia, Armenia, Qatar, Bahrain, Timor-Leste, Cyprus, Bhutan, Maldives, Brunei Darussalam)",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2025",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007351-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/9j2hbgt9sf
title: Algorithmic Platform Management and Risk-Taking Behavior among Chinese Food Delivery Riders

description: 1. Research Overview
This dataset explores how algorithmic platform management shapes food delivery riders’ risk-taking behavior (e.g., traffic violations). Based on Cognitive Appraisal (CAT) and Persistent Cognition Theories (PCT), we proposed a dual-path model: algorithmic management influences behavior via an "online" path (Perceived Algorithmic Control during work) and an "offline" path (post-work Work Rumination), with Self-Control Resource Depletion (risk factor) and Learning Agility (protective factor) as boundary conditions.
2. Key Findings
Data supports the dual-path model, revealing a double-edged sword effect:
Algorithmic management increases risk-taking via Perceived Algorithmic Control and Emotional Rumination, but reduces it via Problem-Solving Contemplation.
Riders’ risk-taking is "silent compliance," driven by both active reward pursuit and passive penalty avoidance.
Self-Control Resource Depletion amplifies Perceived Algorithmic Control’s negative impact; Learning Agility mitigates the effects of Perceived Algorithmic Control and Emotional Rumination.
3. Data Interpretation
Algorithmic management’s influence extends beyond work hours via offline cognition. Behavioral outcomes are co-determined by algorithmic pressure, individual cognitive resources, and adaptive capabilities. Enhancing rider safety requires algorithm optimization (e.g., flexible time buffers) and programs to boost Learning Agility.
4. Data Collection
Source: Two-wave matched questionnaire survey of food delivery riders (Meituan, Ele.me, etc.) in Changsha, China.
Timeframe: T1 (Apr-May 2024), T2 (3 weeks post-T1).
Sample: 320 valid matched responses (full-time/part-time riders).
Design: Multi-wave offline collection (via station managers, field visits) to reduce common method bias.
5. Data Usage
Variables: Constructs (APM, PAC, ER, PSC, RTB, etc.) measured with adapted 6-point Likert scales.
Application: Ideal for gig economy, algorithmic management, occupational safety, and work psychology research (verification, secondary analysis, methodological reference).
DOI: 10.17632/9j2hbgt9sf.1
title: Algorithmic Platform Management and Risk-Taking Behavior among Chinese Food Delivery Riders

description: 1. Research Overview
This dataset explores how algorithmic platform management shapes food delivery riders’ risk-taking behavior (e.g., traffic violations). Based on Cognitive Appraisal (CAT) and Persistent Cognition Theories (PCT), we proposed a dual-path model: algorithmic management influences behavior via an "online" path (Perceived Algorithmic Control during work) and an "offline" path (post-work Work Rumination), with Self-Control Resource Depletion (risk factor) and Learning Agility (protective factor) as boundary conditions.
2. Key Findings
Data supports the dual-path model, revealing a double-edged sword effect:
Algorithmic management increases risk-taking via Perceived Algorithmic Control and Emotional Rumination, but reduces it via Problem-Solving Contemplation.
Riders’ risk-taking is "silent compliance," driven by both active reward pursuit and passive penalty avoidance.
Self-Control Resource Depletion amplifies Perceived Algorithmic Control’s negative impact; Learning Agility mitigates the effects of Perceived Algorithmic Control and Emotional Rumination.
3. Data Interpretation
Algorithmic management’s influence extends beyond work hours via offline cognition. Behavioral outcomes are co-determined by algorithmic pressure, individual cognitive resources, and adaptive capabilities. Enhancing rider safety requires algorithm optimization (e.g., flexible time buffers) and programs to boost Learning Agility.
4. Data Collection
Source: Two-wave matched questionnaire survey of food delivery riders (Meituan, Ele.me, etc.) in Changsha, China.
Timeframe: T1 (Apr-May 2024), T2 (3 weeks post-T1).
Sample: 320 valid matched responses (full-time/part-time riders).
Design: Multi-wave offline collection (via station managers, field visits) to reduce common method bias.
5. Data Usage
Variables: Constructs (APM, PAC, ER, PSC, RTB, etc.) measured with adapted 6-point Likert scales.
Application: Ideal for gig economy, algorithmic management, occupational safety, and work psychology research (verification, secondary analysis, methodological reference).
DOI: 10.15468/dl.h36kwc
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Labisia pumila",
 "Year 1950-2025"
 ]
}

 The dataset includes 14 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007353-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17701688
title: Large SEM-BSE images of hydrated belite of ages from 1 day up to 1 year

description: This dataset contains 8-Bit SEM-BSE images of commercially available dicalcium silicate (C2S; belite; Vustah, Czech Republic). The belite was mixed with a water/binder ratio of 0.5. The paste was the cast in small sealed containers, which were submersed with water. The specimens were stored at 22 ± 2°C.

After the desired hydration times (1, 7, 14, 28, 84, 365 days) the hydration was stopped by immersing the prisms in isopropanol and drying them at 60°C for 12 hours. The dried prisms were then embedded in low viscosity epoxy resin and mechanically polished using diamond paste with a grain size down to 0.25 µm. Finally, the specimens were coatet with a thin layer of carbon to avoid charging.

The images were acquired at 12 kV using a CBS (concentric backscatter) detector within a Thermo Fisher Scientific Helios G4 UX.

All images have a resolution of 36864 x 36864 px at 42.1550 nm/px (1.554 x 1.554 mm² = 2.41 mm²)

Table 1: Basic information like resolution, size and phase composition of the images.




file
age
pores
hydrates
clinker


 
in days
area-%
area-%
area-%


Layer-C2S 1d (stitched).tif
1
46.2
15.4
38.4


Layer-C2S 7d (stitched).tif
7
43.2
27.0
30.1


Layer-C2S 7d (2) (stitched).tif
7
46.3
23.9
29.8


C2S 14d.tif
14
31.4
43.5
25.2


C2S 28d.tif
28
15.9
62.6
21.5


C2S 84d.tif
84
19.3
65.6
15.2


C2S 365d.tif
365
23.8
64.4
12.0




*not processed

The proportions of pores, hydrates and unhydrated clinker shown in table 1 are the result of manual thresholding of denoised versions of these images and may therefore differ to own measurements.

The scaling is backed into the file and can be read using ImageJ/Fiji.

The unstitched files are provded as 7z archives. The sub-images were arranged in a 10 x 10 grid. The pixel scaling of these files is the same as in the larger files. The overlap is ~10%. The filename indicates the position of the Tile. For example, "Tile_005-008-000000_0-000.s0001_e00.tif" is in the fifth row and the eigth column. The indices are counted from 1 to 10.

Internal note

These files are included in the following MAPS datasets:



2023_05_24 C32-C2S 14-84 d

2023_06_08 C2S-C3S 28d-1year

2023_07_18 C3S 7d, C2S 1d, 7d, 3C3S-1C2S 7d
DOI: 10.5281/zenodo.8119085
title: Large SEM-BSE images of hydrated belite of ages from 1 day up to 1 year

description: This dataset contains 8-Bit SEM-BSE images of commercially available dicalcium silicate (C2S; belite; Vustah, Czech Republic). The belite was mixed with a water/binder ratio of 0.5. The paste was the cast in small sealed containers, which were submersed with water. The specimens were stored at 22 ± 2°C.

After the desired hydration times (1, 7, 14, 28, 84, 365 days) the hydration was stopped by immersing the prisms in isopropanol and drying them at 60°C for 12 hours. The dried prisms were then embedded in low viscosity epoxy resin and mechanically polished using diamond paste with a grain size down to 0.25 µm. Finally, the specimens were coatet with a thin layer of carbon to avoid charging.

The images were acquired at 12 kV using a CBS (concentric backscatter) detector within a Thermo Fisher Scientific Helios G4 UX.

All images have a resolution of 36864 x 36864 px at 42.1550 nm/px (1.554 x 1.554 mm² = 2.41 mm²)

Table 1: Basic information like resolution, size and phase composition of the images.




file
age
pores
hydrates
clinker


 
in days
area-%
area-%
area-%


Layer-C2S 1d (stitched).tif
1
46.2
15.4
38.4


Layer-C2S 7d (stitched).tif
7
43.2
27.0
30.1


Layer-C2S 7d (2) (stitched).tif
7
46.3
23.9
29.8


C2S 14d.tif
14
31.4
43.5
25.2


C2S 28d.tif
28
15.9
62.6
21.5


C2S 84d.tif
84
19.3
65.6
15.2


C2S 365d.tif
365
23.8
64.4
12.0




*not processed

The proportions of pores, hydrates and unhydrated clinker shown in table 1 are the result of manual thresholding of denoised versions of these images and may therefore differ to own measurements.

The scaling is backed into the file and can be read using ImageJ/Fiji.

The unstitched files are provded as 7z archives. The sub-images were arranged in a 10 x 10 grid. The pixel scaling of these files is the same as in the larger files. The overlap is ~10%. The filename indicates the position of the Tile. For example, "Tile_005-008-000000_0-000.s0001_e00.tif" is in the fifth row and the eigth column. The indices are counted from 1 to 10.

Internal note

These files are included in the following MAPS datasets:



2023_05_24 C32-C2S 14-84 d

2023_06_08 C2S-C3S 28d-1year

2023_07_18 C3S 7d, C2S 1d, 7d, 3C3S-1C2S 7d
DOI: 10.17632/njx9nfp8th
title: Prognostic Value of Pretreatment Neutrophil-to-Lymphocyte Ratio Independent of Comorbidity Burden in Melanoma

description: Supplementary Tables
Mendeley Supplementary Table 1. Clinicopathologic characteristics of the 288 enrolled patients (ALM versus NACM)
Mendeley Supplementary Table 2. Cox univariate and multivariate analyses for disease-free survival (279 patients)
Mendeley Supplementary Table 3. Cox univariate and multivariate analyses for distant-metastasis-free survival (279 patients)
Mendeley Supplementary Table 4. Clinicopathologic characteristics of the patients who received sentinel lymph node biopsy (225 patients)
Mendeley Supplementary Table 5. Cox univariate and multivariate analyses for disease-free survival of negative SLN patients (171 patients)
Mendeley Supplementary Table 6. Cox univariate and multivariate analyses for distant-metastasis-free survival of negative SLN patients (171 patients)

Supplementary Figures
Mendeley Supplementary Figure 1. Receiver operating characteristic curves.
Mendeley Supplementary Figure 2. Kaplan-Meier survival analysis for negative sentinel lymph node patients (171 patients).
DOI: 10.17632/njx9nfp8th.1
title: Prognostic Value of Pretreatment Neutrophil-to-Lymphocyte Ratio Independent of Comorbidity Burden in Melanoma

description: Supplementary Tables
Mendeley Supplementary Table 1. Clinicopathologic characteristics of the 288 enrolled patients (ALM versus NACM)
Mendeley Supplementary Table 2. Cox univariate and multivariate analyses for disease-free survival (279 patients)
Mendeley Supplementary Table 3. Cox univariate and multivariate analyses for distant-metastasis-free survival (279 patients)
Mendeley Supplementary Table 4. Clinicopathologic characteristics of the patients who received sentinel lymph node biopsy (225 patients)
Mendeley Supplementary Table 5. Cox univariate and multivariate analyses for disease-free survival of negative SLN patients (171 patients)
Mendeley Supplementary Table 6. Cox univariate and multivariate analyses for distant-metastasis-free survival of negative SLN patients (171 patients)

Supplementary Figures
Mendeley Supplementary Figure 1. Receiver operating characteristic curves.
Mendeley Supplementary Figure 2. Kaplan-Meier survival analysis for negative sentinel lymph node patients (171 patients).
DOI: 10.17632/hbbsxmx78z
title: Isometric wall squat reduce ambulatory blood pressure similary to aerobic exercise in enderely with controlled hypertension: A randomized controlled trial

description: SBP and DBP data.
DOI: 10.17632/hbbsxmx78z.1
title: Isometric wall squat reduce ambulatory blood pressure similary to aerobic exercise in enderely with controlled hypertension: A randomized controlled trial

description: SBP and DBP data.
DOI: 10.34740/kaggle/dsv/13862175
title: Trending Youtube Video Statistics (113 Countries)
DOI: 10.24403/jp.1512702
title: Inhaltsverzeichnis 06/2025
DOI: 10.17632/29zv3z9c9m
title: CHEMJOURNAL-D-25-01422R1-WB gel

description: Original western blot images datasets that are composed of standardized data types and reported in Cell Press papers be deposited in a data-type-specific, Cell Press-recommended repository before a paper is accepted for publication.
DOI: 10.17632/29zv3z9c9m.1
title: CHEMJOURNAL-D-25-01422R1-WB gel

description: Original western blot images datasets that are composed of standardized data types and reported in Cell Press papers be deposited in a data-type-specific, Cell Press-recommended repository before a paper is accepted for publication.
DOI: 10.17632/t87gc8t3f4
title: C(N)-(A)-S-H gel modification

description: This database is a specialized resource dedicated to the study of C(N)-(A)-S-H gel gel modification, with the objective of enhancing the degree of polymerization of the gel and improving the overall material performance.
DOI: 10.17632/t87gc8t3f4.1
title: C(N)-(A)-S-H gel modification

description: This database is a specialized resource dedicated to the study of C(N)-(A)-S-H gel gel modification, with the objective of enhancing the degree of polymerization of the gel and improving the overall material performance.
DOI: 10.17632/s9g65ht6hm.2
title: Psychochemical Pretreatment on Lesser-Known Shrub Biomass for Bio-Pellet Production

description: The dataset generated from this study consists of characteristics of four physicochemical treated lesser-known shrub species (Lagerstroemia speciosa, Gliricidia falcatum, Melastoma avenis, and Melastoma sundaicus) subjected to different extraction treatments. Each species was treated using four types of solvents: distilled water, ethanol, hexane, and a combination of ethanol and hexane, under two temperature conditions: room temperature (25°C) and elevated temperature (50°C). The primary parameters measured include moisture content, weight loss, yield, volatile matter, and gross calorific value, which are critical indicators of biomass quality for biopellet production.
DOI: 10.17632/shj94nrczy
title: Behavior Analysis Dataset for Social Engineering Attacks

description: This data includes spam e-mail and phishing detection dataset for cybersecurity research projects
DOI: 10.17632/shj94nrczy.3
title: Behavior Analysis Dataset for Social Engineering Attacks

description: This data includes spam e-mail and phishing detection dataset for cybersecurity research projects
DOI: 10.15468/dl.gk3azz
title: Occurrence Download

description: A dataset containing 9223 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Sweden",
 "TaxonKey is Saccharina latissima"
 ]
}

 The dataset includes 9223 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007352-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/4ytrtgd9bd.1
title: Carbon nanoparticles promote Amazonian seedlings development: leaves biomass and potential productivity increased in forestry species

description: Data collected at the National Institute of Amazonian Research Campus III in Manaus, Brazil. Study experimentations in greenhouse from March 2023 to June 2023. The carbon nanoparticle (CNP) was applied in the substract, once a week for four weeks. Gas exchange measures were taken in the application month. Growth period was carried for other 60 days, and final analyses were performed in June.
DOI: 10.17632/y87nyj8hth
title: A Dataset of Textual Functional Requirements for Fried Chicken Processing and Sales Systems and Academic Information Systems

description: This dataset is compiled to provide structured functional requirements documentation for two system domains that are widely used in Indonesia: processing–sales of geprek chicken, and academic information systems. In the midst of a high requirement for clear documentation of requirements, the availability of public datasets containing functional requirements textually is still very limited. Therefore, this dataset presents 54 lines of data, each containing a complete functional requirement, complete with application attributes, modules, actors, title requirements, text requirements in English, and Indonesian translations. This bilingual presentation makes it easy to use for learning software engineering, SRS creation, and NLP research, such as requirement classification and entity extraction.
Some of the data contains the Geprek Resto Management System, which describes general business processes in the culinary industry, including ordering, food processing, cashier-kitchen synchronization, stock management, transaction recording, and financial statement preparation. Requirements are written based on real-world flows, such as the cashier entering an order, the system sending tickets to the kitchen, the chef updating the order status, raw materials automatically being reduced, and notifications of low stock. The dataset also includes specific conditions, such as order cancellations or out-of-stock, providing a realistic context for developing a small to medium business system.
The other section outlines the functional requirements of the Academic Information System, which encompass core educational processes, including Study Plan Card, lecture schedule management, attendance tracking, assessment, and academic validation. Actors such as students, lecturers, and academic staff are represented through requirements that describe multi-level interactions, for example, validation of course prerequisites, the process of filling in grades, to recording attendance based on lecture sessions. The requirement patterns in this domain exhibit typical educational complexities, such as tiered data structures, time-based rules, and repetitive evaluation mechanisms.
With a consistent table structure and coverage of two different domains, this dataset is a rich resource for requirements engineering research, document analysis automation, and the development and education of restaurant systems. It is hoped that this dataset will encourage digital innovation in culinary SMEs and educational institutions, and also serve as a reference for improving the quality of software requirements documentation.
DOI: 10.17632/y87nyj8hth.1
title: A Dataset of Textual Functional Requirements for Fried Chicken Processing and Sales Systems and Academic Information Systems

description: This dataset is compiled to provide structured functional requirements documentation for two system domains that are widely used in Indonesia: processing–sales of geprek chicken, and academic information systems. In the midst of a high requirement for clear documentation of requirements, the availability of public datasets containing functional requirements textually is still very limited. Therefore, this dataset presents 54 lines of data, each containing a complete functional requirement, complete with application attributes, modules, actors, title requirements, text requirements in English, and Indonesian translations. This bilingual presentation makes it easy to use for learning software engineering, SRS creation, and NLP research, such as requirement classification and entity extraction.
Some of the data contains the Geprek Resto Management System, which describes general business processes in the culinary industry, including ordering, food processing, cashier-kitchen synchronization, stock management, transaction recording, and financial statement preparation. Requirements are written based on real-world flows, such as the cashier entering an order, the system sending tickets to the kitchen, the chef updating the order status, raw materials automatically being reduced, and notifications of low stock. The dataset also includes specific conditions, such as order cancellations or out-of-stock, providing a realistic context for developing a small to medium business system.
The other section outlines the functional requirements of the Academic Information System, which encompass core educational processes, including Study Plan Card, lecture schedule management, attendance tracking, assessment, and academic validation. Actors such as students, lecturers, and academic staff are represented through requirements that describe multi-level interactions, for example, validation of course prerequisites, the process of filling in grades, to recording attendance based on lecture sessions. The requirement patterns in this domain exhibit typical educational complexities, such as tiered data structures, time-based rules, and repetitive evaluation mechanisms.
With a consistent table structure and coverage of two different domains, this dataset is a rich resource for requirements engineering research, document analysis automation, and the development and education of restaurant systems. It is hoped that this dataset will encourage digital innovation in culinary SMEs and educational institutions, and also serve as a reference for improving the quality of software requirements documentation.