cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/zphwvpjxkv.1
title: Inverse and Forward Kinematic Analysis of a 6-DOF Foldable Mechanism with a Circular Rail (FoldRail Mechanism). Julia Files

description: This dataset contains Julia files that solve inverse and forward kinematic problems of a 6-DOF 3-RRRS foldable parallel mechanism with a circular rail (FoldRail mechanism), which was presented in paper https://doi.org/10.1016/j.mechmachtheory.2023.105425. The corresponding paper describing the applied algorithms is going to be published in the Mechanism and Machine Theory journal. Please check the list of works at https://orcid.org/0000-0002-3928-5440.

The dataset includes the following files:
1. File "main.jl" is the main file that proceeds with the inverse and forward kinematic analysis of the mechanism step by step.
2. File "geometry.jl" is used to define geometrical parameters of the mechanism.
3. File "trajectories.jl" includes functions that define trajectory of the output link and path time scaling, which are used as the input motion for the inverse kinematics.
4. File "kinematics.jl" includes functions that solve inverse and forward kinematic problems and some auxiliary functions.
5. File "plots.jl" includes functions that visualize the results of the kinematic analysis.
6. Optional files "Project.toml" and "Manifest.toml" contain information about the used packages.
DOI: 10.17632/fy5mnzt4gz.1
title: How CEO foreign experience affects corporate environmental violations: the role of enhanced environmental ethics and general competency

description: Using data from heavy-polluting firms listed in China, we examine the relationship between CEO foreign experience and corporate environmental violation. Our data are based on heavy-polluting firms listed on Chinese exchanges, the main body of environmental polluters and environmental violations in China. Environmental violation data are manually collected from the PKULaw database, an online legal database maintained by the Peking University Legal Information Center. We hand-collect the CEO's foreign experience data from the firms’ annual reports. Other data are all from the CSMAR database and the CNRDS Platform database, two leading financial data providers in China. After setting global paths as per the root setting instructions, proceed to run the code.do file following the sequence provided in the project directory. This process will guide the execution through each phase of the analysis.
DOI: 10.17632/fr95xpvjt7.1
title: High surface area and interconnected nanoporosity of clay-rich astromaterials: N2 BET and TG-DSC-MSEGA data

description: Whereas the bulk porosity of clay-rich meteorites is well established, the magnitude of their surface area and nano-scale porosity is poorly known. Here we apply the N2 BET gas adsorption method to measure the scale-distribution and net surface area of porosity in a range of clay-rich carbonaceous chondrite (CC) meteorites: Tarda (C2-ung), Ivuna (CI1), Orgueil (CI1), Aguas Zarcas (CM2), and Murchison (CM2). For comparison, N2 BET data was also acquired from the anhydrous CC Allende (CV3). Tarda (C2-ung) has high surface area, up to 82 m2/g, dominated by an interconnected network of ~3-nm-sized pores. In comparison, Ivuna and Orgueil (CI1) and Aguas Zarcas and Murchison (CM2) have bimodal nanopore-size distributions with a lower density of ~3-nm pores and broader size distributions around 40 nm, and corresponding lower surface areas ~14-19 m2/g. A summary of the data is shown in Table 1 (file 2Table1 N2BET data CC meteorites.docx). 

Two data sets are included that accompany the paper entitled "High surface area and interconnected nanoporosity of clay-rich astromaterials": the raw N2 BET data files including the derivation of the pore size and pore-size distribution; and the TG, DSC, and MSEGA data for the unweathered and artificially weathered Tarda meteorite.

Prior to the N2 BET measurements, it is necessary to remove these physisorbed species through outgassing. The N2 BET measurements were acquired after several outgassing pretreatment - the pretreatment is listed after the meteorite name: Tarda-100 refers to the sample outgassed at 100 °C under flowing N2 for 24 hr; after prolonged storage under a dry N2 atmosphere (-NH); after being held under a vacuum for 24 hr at room temperature (-VRT); and, after heating in the presence of flowing dry nitrogen at 250 °C for 24 hr (-250) (Table 1). The N2 BET measurements are made by exposing the degassed sample to N2 at a series of controlled pressures while maintaining the sample at a constant cryogenic temperature of -195.8 °C, which corresponds to the boiling point of N2. The volume of adsorbed or desorbed gas is measured over a relative equilibrium adsorption pressure (p/p0) from near 0 to 1, where p is the absolute equilibrium pressure and p0 the saturation pressure of the gas.

The Tarda N2 BET data shows the ease with which atmospheric moisture can adsorb onto its high surface area. This magnitude of the adsorption under laboratory conditions is measured by TG-DSC-MSEGA. 

Further information on the data acquisition and the samples is provided in the attached file 1Materials and Methods - N2BET, TG, DSC, MSEGA.doc
DOI: 10.17632/nxk9r22wd6.1
title: GNSS Dataset (with Interference and Spoofing) Part III

description: GNSS Dataset (with Interference and Spoofing) consists of three parts: 
Part I (Raw data of 2023 12 to 20, Sept, 2023, clean data), 
Part II (Raw data of 2023 21 to 30, Sept, 2023, clean data) and 
Part III (Processed data 12 to 30, Sept, 2023; data collected with spoofing and jamming on 21 Dec, 2023; Scripts and Material) .

The data were recorded by a GNSS receiver installed on the 5th floor of the Science Hall of Yunnan University. HackRF One emits spoofing signals and the commercial jammer emits suppression jamming to attack the receiver on 21 Dec, 2023. The provided datasets are interesting for the GNSS monitoring, GNSS security, anti-jamming and anti-spoofing mechanisms based scientific communities.

These data provide the most comprehensive information available on the spatial and temporal patterns of GNSS satellites, observation and receiver parameters, referring to five constellations (GPS, Campass, Galileo, GLONASS and QZSS) and eight signal bands (L1C/A, L2C, E1, E5b, B1, B2, L1, L2). The dataset provides observations of the receiver three scenarios: normal state, affected by commercial jammers, and spoofed by SDR HackRF One. These observations include more details such as carrier-to-noise density ratio (C/N0), signal spectrum, Doppler shift, pseudorange, carrier phase, satellite health indicator, real-time position data and dilution of precision (DOP), etc. These data can be used to analyze navigation satellite operation rules, satellite covering time above the receiver, satellite overhead time prediction and GNSS monitoring system construction, provides a large amount of fine-grained data that can be used as an example to study safeguards at civil aviation airports, monitoring for harmful radio interference.
DOI: 10.17632/nxk9r22wd6.2
title: GNSS Dataset (with Interference and Spoofing) Part III

description: GNSS Dataset (with Interference and Spoofing) consists of three parts: 
Part I (Raw data of 2023 12 to 20, Sept, 2023, clean data), 
Part II (Raw data of 2023 21 to 30, Sept, 2023, clean data) and 
Part III (Processed data 12 to 30, Sept, 2023; data collected with spoofing and jamming on 21 Dec, 2023; Scripts and Material) .

The data were recorded by a GNSS receiver installed on the 5th floor of the Science Hall of Yunnan University. HackRF One emits spoofing signals and the commercial jammer emits suppression jamming to attack the receiver on 21 Dec, 2023. The provided datasets are interesting for the GNSS monitoring, GNSS security, anti-jamming and anti-spoofing mechanisms based scientific communities.

These data provide the most comprehensive information available on the spatial and temporal patterns of GNSS satellites, observation and receiver parameters, referring to five constellations (GPS, Campass, Galileo, GLONASS and QZSS) and eight signal bands (L1C/A, L2C, E1, E5b, B1, B2, L1, L2). The dataset provides observations of the receiver three scenarios: normal state, affected by commercial jammers, and spoofed by SDR HackRF One. These observations include more details such as carrier-to-noise density ratio (C/N0), signal spectrum, Doppler shift, pseudorange, carrier phase, satellite health indicator, real-time position data and dilution of precision (DOP), etc. These data can be used to analyze navigation satellite operation rules, satellite covering time above the receiver, satellite overhead time prediction and GNSS monitoring system construction, provides a large amount of fine-grained data that can be used as an example to study safeguards at civil aviation airports, monitoring for harmful radio interference.
DOI: 10.17632/nxk9r22wd6.3
title: GNSS Dataset (with Interference and Spoofing) Part III

description: GNSS Dataset (with Interference and Spoofing) consists of three parts: 
Part I (Raw data of 2023 12 to 20, Sept, 2023, clean data), 
Part II (Raw data of 2023 21 to 30, Sept, 2023, clean data) and 
Part III (Processed data 12 to 30, Sept, 2023; data collected with spoofing and jamming on 21 Dec, 2023; Scripts and Material) .

The data were recorded by a GNSS receiver installed on the 5th floor of the Science Hall of Yunnan University. HackRF One emits spoofing signals and the commercial jammer emits suppression jamming to attack the receiver on 21 Dec, 2023. The provided datasets are interesting for the GNSS monitoring, GNSS security, anti-jamming and anti-spoofing mechanisms based scientific communities.

These data provide the most comprehensive information available on the spatial and temporal patterns of GNSS satellites, observation and receiver parameters, referring to five constellations (GPS, Campass, Galileo, GLONASS and QZSS) and eight signal bands (L1C/A, L2C, E1, E5b, B1, B2, L1, L2). The dataset provides observations of the receiver three scenarios: normal state, affected by commercial jammers, and spoofed by SDR HackRF One. These observations include more details such as carrier-to-noise density ratio (C/N0), signal spectrum, Doppler shift, pseudorange, carrier phase, satellite health indicator, real-time position data and dilution of precision (DOP), etc. These data can be used to analyze navigation satellite operation rules, satellite covering time above the receiver, satellite overhead time prediction and GNSS monitoring system construction, provides a large amount of fine-grained data that can be used as an example to study safeguards at civil aviation airports, monitoring for harmful radio interference.
DOI: 10.17632/wc9ykt8d9b.2
title: Supplementary Material

description: Abstract
Investigations into the role of vitamin D in the immune response of cattle are limited. The objectives of this study were to investigate the association between circulating vitD concentration, TB vaccination and Mycobacterium bovis (M. bovis) infection outcomes in dairy calves. The study design incorporated two phases: vaccination (week 0-52) and an experimental infection phase (week 52-65). Blood samples were taken throughout weeks 0-65. Twenty-four cattle less than 8 weeks old were housed throughout the study and fed a bodyweight-based allowance. Vaccinated calves (n=12) received a subcutaneous injection of a live-attenuated TB strain at week 0, whereas non-vaccinated ones (n=10) were injected with saline. Both groups were infected with 7,600 CFU of M. bovis (strain 2122/97) 52 weeks post-vaccination. All calves were euthanized in week 66 and their lymph nodes and lungs were assessed for pathology. Serum 25-hydroxyvitamin D (25D) concentrations were measured at intervals using a commercial ELISA with custom bovine standards. A mixed-effects logistic regression model revealed significantly higher 25D concentrations in the vaccinates post-infection (week 65) compared to the non-vaccinates. Linear regression analysis between 25D concentration and the level of M. bovis-driven pathology revealed a negative linear relationship i.e. higher concentrations were associated with lower pathology scores, irrespective of vaccination status. No correlation was detected between interferon-γ cytokine production and vitD concentration. Overall, the results support a significant role for vitamin D in the development of effective immunity of cattle against M. bovis. Gaining insight into this interaction between BCG vaccination, M. bovis infection and vitamin D could potentially guide the optimization of vaccination protocols and TB control strategies going forward.
DOI: 10.17632/xtw9gvhbfp.1
title: Preventive Efficacy of Silver Diamine Fluoride and MI Varnish on Molars Affected by Molar Incisor Hypomineralization in Children: A Randomized Controlled Trial

description: The aim of this study was to compare the effectiveness of silver diamine fluoride (SDF) and MI varnish in preventing the development and progression of caries and post-eruptive enamel breakdown in children's molars affected by MIH. 100 children with 200 molars affected with mih were enrolled in this study. This study was a randomized controlled clinical trial, double-blinded with a split-mouth design.
Datasets include Ethical approval, Study protocol with statistical analysis plan, participant data entry-level, and Teeth data entry-level.
DOI: 10.17632/6yx6my74ys.1
title: Preventive Efficacy of Silver Diamine Fluoride and MI Varnish on Molars Affected by Molar Incisor Hypomineralization in Children: A Randomized Controlled Trial (CONSORT flow diagram and CONSORT checklist)

description: CONSORT Checklist and CONSORT flow diagram
DOI: 10.17632/fckxt4z422.1
title: The nature of space-weathered rims on Chang’e-5 lunar soil grains

description: The data of "The nature of space-weathered rims on Chang’e-5 lunar soil grains"
DOI: 10.17632/fckxt4z422.2
title: Nature of space-weathered rims on Chang’e-5 lunar soil grains

description: The data of "Nature of space-weathered rims on Chang’e-5 lunar soil grains"
DOI: 10.17632/44pbrbsnkh.3
title: Indonesian Sign Language System (SIBI) Dataset

description: The SIBI Dataset is a collection of Indonesian Sign Language System (SIBI) video signs based on the SIBI online dictionary issued by the Ministry of Education and Culture of the Republic of Indonesia. The dataset includes numbers, alphabets, affixes, and sentences. The SIBI sentences were created in collaboration with Special School Teachers, consisting of 40 sentences commonly used during lessons. Expressions including neutral, happy, sad, angry, afraid, disgusted, and surprised are stored in different folders. Ten of the 40 sentences were used for each expression. Recordings were carried out with 20 signers, consisting of 10 teachers and 10 students. The total video dataset consists of 820 number videos, 520 alphabet videos, 360 affix videos, and 1400 sentence videos.

Considering ethical issues, we cannot share the entire video dataset in this repository. We provide sample videos from the SIBI dataset, performed by the data owners with faces blurred. You can find the SIBI dataset metadata information in the attached Metadata file. We are happy to share the SIBI dataset with you after you understand and sign the attached Data Use Agreement (DUA) and return it to the data owner’s email.
DOI: 10.17632/xtw9gvhbfp.2
title: Preventive Efficacy of Silver Diamine Fluoride and MI Varnish on Molars Affected by Molar Incisor Hypomineralization in Children: A Randomized Controlled Trial

description: The aim of this study was to compare the effectiveness of silver diamine fluoride (SDF) and MI varnish in preventing the development and progression of caries and post-eruptive enamel breakdown in children's molars affected by MIH. 100 children with 200 molars affected with mih were enrolled in this study. This study was a randomized controlled clinical trial, double-blinded with a split-mouth design.
Datasets include Ethical approval, Study protocol with statistical analysis plan, participant data entry-level, and Teeth data entry-level.
DOI: 10.17632/pj4z9x666x.1
title: A nature-inspired HIF stabilizer derived from a highland-adaptation insertion of plateau pika Epas1 protein

description: Original data in paper A nature-inspired HIF stabilizer derived from a highland-adaptation insertion of plateau pika Epas1 protein.
DOI: 10.17632/43c9pvrksc.1
title: Raw Data from Physicochemical and Toxicological Analyses and Average Temperatures of the Organic Compost from the Composting and Social Technology Work.

description: Experiment Duration: The experiment lasted 90 days, allowing for the observation of changes over time in the composting process.
Collection Points: Samples were collected at two critical time points: at the initial time (Day 1) to establish a baseline, and at the final time (Day 90) to assess the outcomes of the composting process.
Collection Location: To ensure a representative sample of the composting reactors, samples were taken from three distinct points within each reactor.
Sample Processing: After collection, the samples were homogenized to ensure that subsequent analyses reflected a uniform distribution of components throughout the composted material.
Storage: The homogenized samples were stored under refrigerated conditions until the start of laboratory analyses, preserving the relevant chemical and biological characteristics.
Temperature Measurement:
Frequency: The temperature of the reactors was monitored daily throughout the entire experimental period.
DOI: 10.17632/3fgnmwyjgj.1
title: Dataset of the article: 'Functional Properties of Brewer’s Spent Grain Protein Isolate: The Missing Piece in the Plant Protein Portfolio'

description: Dataset relating to the article 'Functional Properties of Brewer’s Spent Grain Protein Isolate: The Missing Piece in the Plant Protein Portfolio'
DOI: 10.15468/dl.4y2axm
title: Occurrence Download

description: A dataset containing 50 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is The Coleoptera collection (EC) of the Muséum national d'Histoire naturelle (MNHN - Paris)",
 "Geometry POLYGON((-90.59849 -0.87718,-90.17271 -0.84564,-90.10568 -0.37649,-90.54724 -0.48688,-90.59849 -0.87718))"
 ]
}

 The dataset includes 50 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004236-250117142028555/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/kdwybn8gxy.1
title: LINF_210012300

description: metallo-beta-lactamase family-like protein; Leishmania infantum (strain JPCM5)
DOI: 10.15468/dl.jcwfq9
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dolichophis andreanus (Werner, 1917)"
 ]
}

 The dataset includes 8 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004237-250117142028555/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/44zpkbrpxb.1
title: Credal Dog-4

description: Most datasets used for classification use hard labels. Credal Dog-4 was labeled uncertainly and imprecisely by contributors during crowdsourcing campaigns. Resulting in richer labels, modeled with the theory of belief funtions, which generalizes several reasoning frameworks with uncertainty. These datasets can be used with classical models using hard labels but also with probabilistic, fuzzy or even evidential models.

Dataset:
4 classes, 400 observations, 47 features (or raw pictures)

When using the dataset please cite :
A. Hoarau, C. Thierry, A. Martin, J.-C. Dubois, Y. Le Gall, "Datasets with rich labels for machine learning", in: FUZZ-IEEE, 2023.

Credal Dog-4 dataset
├── data
│ ├── classes.csv: Classes of the dataset
│ ├── X.csv: Features of the dataset
│ ├── X_512.csv: Learge 512 features vector of the dataset
│ ├── X_pictures.csv: Raw features (Pictures themselves)
│ ├── y.csv: Rich labels
│ └── y_true.csv: True labels
└── extra
 ├── y_hard.csv: Hard labels given during a new campaign
 ├── DATA_imperfect.csv: Imperfect answers given during the campaign
 ├── ITERATION_imperfect.csv: Imperfect 2nd step answers given during the campaign
 ├── EVENT_imperfect.csv: Contributors events
 ├── ID_imperfect.csv: Contributors IDs
 └── DATA_perfect.csv: Precise answers given during a new campaign
DOI: 10.17632/v8k6c5s9cy.1
title: Credal Bird-2

description: Most datasets used for classification use hard labels. Credal Bird-2 was labeled uncertainly and imprecisely by contributors during crowdsourcing campaigns. Resulting in richer labels, modeled with the theory of belief funtions, which generalizes several reasoning frameworks with uncertainty. These datasets can be used with classical models using hard labels but also with probabilistic, fuzzy or even evidential models.

Dataset:
10 classes, 200 observations, 30 features (or raw pictures)

When using the dataset please cite:
A. Hoarau, C. Thierry, A. Martin, J.-C. Dubois, Y. Le Gall, "Datasets with rich labels for machine learning", in: FUZZ-IEEE, 2023.

Credal Bird-2 dataset
├── data
│ ├── classes.csv: Classes of the dataset
│ ├── X.csv: Features of the dataset
│ ├── X_512.csv: Learge 512 features vector of the dataset
│ ├── X_pictures.csv: Raw features (Pictures themselves)
│ ├── y.csv: Rich labels
│ └── y_true.csv: True labels
└── extra
 ├── y_hard.csv: Hard labels given during a new campaign
 ├── DATA_imperfect.csv: Imperfect answers given during the campaign
 ├── ITERATION_imperfect.csv: Imperfect 2nd step answers given during the campaign
 ├── EVENT_imperfect.csv: Contributors events
 ├── ID_imperfect.csv: Contributors IDs
 └── DATA_perfect.csv: Precise answers given during a new campaign
DOI: 10.17632/9sz5vm8g7h.1
title: Credal Bird-10

description: Most datasets used for classification use hard labels. Credal Bird-10 was labeled uncertainly and imprecisely by contributors during crowdsourcing campaigns. Resulting in richer labels, modeled with the theory of belief funtions, which generalizes several reasoning frameworks with uncertainty. These datasets can be used with classical models using hard labels but also with probabilistic, fuzzy or even evidential models.

Dataset:
10 classes, 200 observations, 30 features (or raw pictures)

When using the dataset please cite :
A. Hoarau, C. Thierry, A. Martin, J.-C. Dubois, Y. Le Gall, "Datasets with rich labels for machine learning", in: FUZZ-IEEE, 2023.

Credal Bird-10 dataset
├── data
│ ├── classes.csv: Classes of the dataset
│ ├── X.csv: Features of the dataset
│ ├── X_512.csv: Learge 512 features vector of the dataset
│ ├── X_pictures.csv: Raw features (Pictures themselves)
│ ├── y.csv: Rich labels
│ └── y_true.csv: True labels
└── extra
 ├── y_hard.csv: Hard labels given during a new campaign
 ├── DATA_imperfect.csv: Imperfect answers given during the campaign
 ├── ITERATION_imperfect.csv: Imperfect 2nd step answers given during the campaign
 ├── EVENT_imperfect.csv: Contributors events
 ├── ID_imperfect.csv: Contributors IDs
 └── DATA_perfect.csv: Precise answers given during a new campaign
DOI: 10.17632/3n449bdt4j.1
title: Wang 2024 Cell Rep Data

description: Calcium imaging data for whisker sensory coding. For Wang & Feldman, Cell Rep. 2024. Contains data from Control and Cntnap2-/- mice. See Readme file for description. See Wang & Feldman Cell Rep 2024 for description of the experimental design. Analysis code for this data is available at: https://github.com/dfeldman189/Wang2024Data
DOI: 10.5284/1125813
title: Images and Text from a Photographic Building Record Survey (Level 1) at Airey-type Homes, 60 Worrall Road, Sheffield, South Yorkshire, October 2023

description: This collection consists of images and text from a building record survey by York Archaeology at 60 Worrall Road, Sheffield, South Yorkshire, in October 2023.This was done in advance of the re-cladding of the property to improve its visual appearance and thermal performance.