cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/ttswxmffm7
title: 2D and 3D ground penetrating radar data from the Late Jurassic Hanifa Fm outcrop - Wadi Birk, Central Saudi Arabia: Shallow marine carbonate platform sediments equivalent to Arabian subsurface reservoirs

description: 2D and 3D ground penetrating radar (GPR) data were recorded in March 2019 from the Late Jurassic (Oxfordian – Early Kimmeridgian) Hanifa Fm outcrop – Wadi Birk, Central Saudi Arabia. The primary objective of these data is to complement outcrop data with behind-the-outcrop geophysical images for a three-dimensional outcrop facies interpretation. All GPR surveys conducted in this dataset are constant offset reflection surveys where the separation between transceiver and receiver antennas is constant at 1 m. We utilized PulseEKKO© Smart Cart Acquisition System to record the data. The transceiver and receiver antennas were mounted on a draggable cart, allowing both of them to be moved along a profile line or a 3D grid. The 2D dataset was acquired using 50 MHz and 100 MHz antennas, while the 3D dataset utilized 50 MHz antennas only. We provided the 2D raw data in PulseEKKO© format with trace coordinates in .dst format that can be opened in the standard ASCII editor software. Please check the README.txt for the table format of the .dst files. The 3D data is already embedded with trace coordinates. A pdf file summarizing the study area, processing steps, and an example of the processed line is provided.
DOI: 10.17632/43hgpkr9rj
title: Comparison of TTDS of Sebaceous Carcinoma between racial groups within stage and insurance

description: Supplementary Table 1 for manuscript "Factors associated with time to treatment for definitive surgery for Sebaceous Carcinoma"
DOI: 10.17632/n9pjyhxkht
title: Research and Teaching on Robust Design in early Design Phases

description: Research and Teaching on Robust Design in early Design Phases (this is an extended version)
DOI: 10.6084/m9.figshare.5127298.v1
title: Supplementary Material for: Retrospective Analysis of 255 Papillary Thyroid Carcinomas ≤2 cm: Clinicohistological Features and Prognostic Factors

description: <b><i>Background:</i></b> Papillary thyroid carcinoma (PTC) is the most common thyroid cancer. The widespread use of neck ultrasound (US) and US-guided fine-needle aspiration cytology is triggering an overdiagnosis of PTC. <b><i>Objective: </i></b>To evaluate clinical behavior and outcomes of patients with PTCs ≤2 cm, seeking for possible prognostic factors. <b><i>Methods:</i></b> Clinical records of cases with histological diagnosis of PTC ≤2 cm followed at the Endocrine Department of Instituto Português de Oncologia, Lisbon between 2002 and 2006 were analyzed retrospectively. <b><i>Results:</i></b> We identified 255 PTCs, 111 were microcarcinomas. Most patients underwent near-total thyroidectomy, with lymph node dissections in 55 cases (21.6%). Radioiodine therapy was administered in 184 patients. At the last evaluation, 38 (14.9%) had evidence of disease. Two deaths were attributed to PTC. Median (±SD) follow-up was 74 (±23) months. Multivariate analysis identified vascular invasion, lymph node and systemic metastases significantly associated with recurrence/persistence of disease. In addition, lymph node involvement was significantly associated with extrathyroidal extension and angioinvasion. Median (±SD) disease-free survival (DFS) was estimated as 106 (±3) months and the 5-year DFS rate was 87.5%. Univariate Cox analysis identified some relevant parameters for DFS, but multivariate regression only identified lymph node and systemic metastases as significant independent factors. The median DFS estimated for lymph node and systemic metastases was 75 and 0 months, respectively. <b><i>Conclusions:</i></b> In the setting of small PTCs, vascular invasion, extrathyroidal extension and lymph node and/or systemic metastases may confer worse prognosis, perhaps justifying more aggressive therapeutic and follow-up approaches in such cases.
DOI: 10.17632/mcgzznfbyw
title: Data for: Manufacturing assembly layouts definition and its impact on work breaks and workers
DOI: 10.17632/yjdmrmrj8d
title: OptQC v1.3: An (updated) optimized parallel quantum compiler

description: Abstract We present a revised version of the OptQC program of Loke et al. (2014) [1]. We have removed the simulated annealing process in favour of a descending random walk. We have also introduced a new method for iteratively generating permutation matrices during the random walk process, providing a reduced total cost for implementing the quantum circuit. Lastly, we have also added a synchronization mechanism between threads, giving quicker convergence to more optimal solutions. New version program s... Title of program: OptQC v1.3 Catalogue Id: AEUA_v1_3 Nature of problem It aims to minimise the number of quantum gates required to implement a given unitary operation. Versions of this program held in the CPC repository in Mendeley Data AEUA_v1_0; <i>OptQC</i>; 10.1016/j.cpc.2014.07.022 AEUA_v1_3; OptQC v1.3; 10.1016/j.cpc.2016.05.028 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)
DOI: 10.6084/m9.figshare.7514219.v1
title: Breast density pattern characterization by histogram features and texture descriptors

description: Abstract Introduction Breast cancer is the first leading cause of death for women in Brazil as well as in most countries in the world. Due to the relation between the breast density and the risk of breast cancer, in medical practice, the breast density classification is merely visual and dependent on professional experience, making this task very subjective. The purpose of this paper is to investigate image features based on histograms and Haralick texture descriptors so as to separate mammographic images into categories of breast density using an Artificial Neural Network. Methods We used 307 mammographic images from the INbreast digital database, extracting histogram features and texture descriptors of all mammograms and selecting them with the K-means technique. Then, these groups of selected features were used as inputs of an Artificial Neural Network to classify the images automatically into the four categories reported by radiologists. Results An average accuracy of 92.9% was obtained in a few tests using only some of the Haralick texture descriptors. Also, the accuracy rate increased to 98.95% when texture descriptors were mixed with some features based on a histogram. Conclusion Texture descriptors have proven to be better than gray levels features at differentiating the breast densities in mammographic images. From this paper, it was possible to automate the feature selection and the classification with acceptable error rates since the extraction of the features is suitable to the characteristics of the images involving the problem.
DOI: 10.17632/gfvmk3ty67
title: Renewable Energy Installation Capacity Taiwan

description: Renewable Energy Installation Capacity Taiwan is the dataset for RE capacity across Taiwan Cities and Districts
DOI: 10.17632/rt55j2tcy3
title: Raw data for electricity, gas, kerosene, firewood and charcoal prices for six geopolitical zones in Nigeria

description: Raw data for annual electricity, gas, kerosene, firewood, and charcoal prices for six geopolitical zones in Nigeria is presented. Related Research Article: Emodi, N. V., Haruna, E. U., Abdu, N., Morataya, S. D. A., Dioha, M. O., & Abraham-Dukuma, M. C. (2022). Urban and rural household energy transition in Sub-Saharan Africa: Does spatial heterogeneity reveal the direction of the transition?. Energy Policy, 168, 113118.
DOI: 10.6084/m9.figshare.14432729.v3
title: Fig. 5g

description: MICAgen mice were injected s.c. with MCA. Around 100 days later, mice bearing fibrosarcomas were randomized in 4 groups. Two groups were treated once with 2 mg/kg of MICAB1 PDB2G-ADCs or IC-PDB2Gand two groups were treated once a week for three weeks with 10 mg/kg of mIgG2a-MICAB1 or mIgG2a-IC.
DOI: 10.17632/8j997skdj8
title: Trained Machine Learning Models of '' Improving performance in colorectal cancer histology decomposition using deep and ensemble machine learning''

description: This repository encompasses fully trained deep and ensemble learning models from https://www.sciencedirect.com/science/article/pii/S240584402413592X. These models are available in h5 file format. To load these models effectively, users must have TensorFlow/Keras and Scikit-Learn installed, and be running Python version 3.7 or higher.
DOI: 10.17632/p6rj6cjn4x
title: Mujeres con hijos hemofílicos: conocimientos y prácticas de cuidado

description: Transcripción de las entrevistas: Mujeres con hijos hemofílicos: conocimientos y prácticas de cuidado
DOI: 10.17632/vxbtmh66jz
title: Data for: Remote sensing, GIS, and Fieldwork Studies to Assess and Valorize Groundwater Resources in the Springs Area of Oum-Er-Rabiaa (Moroccan Middle Atlas).

description: Geochemical analysis of groundwater samples in the springs area of Oum-Errabia-Morocco
DOI: 10.17605/osf.io/zm64g
title: Open Data Project on Global Endogenous Climate Adaptation (DatAdapt)

description: Code and data delivering a global dataset supporting the refinement, calibration, and validation of a quantitative model of endogenous climate adaptation.

1) Climate adaptation is an endogenous process that unfolds over time. 
2) Adaptation decisions are considered as investment choices made to mitigate potential future losses from uncertain climate risks. 
3) To effectively model adaptation, we focus on three primary variables: H) natural Hazards, X) the eXposure of human systems, and M) the stock of infrastructure for hazard Mitigation. 
4) These primary variables lead to two additional derived variables: P) the Protected human assets and activities, and D) the potential Damage. 
5) All these variables pose challenges in terms of observation and measurement, with M being particularly challenging due to its largely unobservable and non measurable nature.
DOI: 10.15468/dl.ggfavh
title: Occurrence Download

description: A dataset containing 15883 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "OccurrenceStatus is Present",
 "TaxonKey is Acoraceae"
 ]
}

 The dataset includes 15883 records from 422 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009111-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/6vk4f3ph4b
title: The abundance of persistent free radicals in biochar determines the degradation efficiency of plasticizer DBP in soils through regulating the ROS yielding
DOI: 10.21233/wy6j-4b15
title: FCKP 3 pollen surface sample dataset

description: Raw data for the FCKP 3 pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.17632/3v5jm2vkgy
title: Data for: blood and feather carbon and nitrogen stable isotopes for the Saffron Finch

description: We measured δ13C and δ15N in blood over a year, and in different feathers from yellow females, yellow males and dull individuals of a Saffron Finch (Sicalis flaveola) population in a private farm in the Central Brazilian savannas. We sampled 195 individuals in seven field samplings between January 2017 and March 2018. The mean blood δ13C values were similar among yellow females, yellow males and dull individuals, indicating that this population of Saffron Finch predominantly accesses similar resources throughout the year, with a predominant C4 signal. Although Saffron Finch is considered a granivorous species, the mean δ15N values found indicate that both adults and juveniles also incorporate in their tissues animal protein.
DOI: 10.17632/fv7sy2fhnz
title: Data for: Rare Disaster Risk and Exchange Rates: An Empirical Investigation of South Korean Exchange Rates under Tension between the Two Koreas

description: Data Explanation 1. rare_disaster_data1.txt monthly data for the number of news articles 1st column: time 2nd column: The number of news articles covering North Korea’s military provocations 3rd column: The number of news articles covering North Korea’s nuclear bomb tests 4th column: The number of news articles covering North Korea’s missile tests 5th column: The nominal exchange rate between South Korea and the US 6th column: CPI for South Korea 7th column: CPI for the US 2. rare_disaster_data2_5m_2.txt - rare_disaster_data2_5m_6.txt 5 minute high-frequency data for the exchange rate 2nd – 6th nuclear tests in North Korea 1st column: date 2nd column: time 3rd column: The nominal exchange rate between South Korea and the US 3. rare_disaster_data3_daily_1.txt daily data for the exchange rate 1st nuclear test in North Korea 1st column: date 2nd column: The nominal exchange rate between South Korea and the US
DOI: 10.17632/g8wrxkbzpg
title: WRF-Chem sensitivity to biogenic emission inventories in a tropical region. Global online model (MEGAN) vs local offline model (BIGA)

description: This dataset presents two NetCDF files with three-dimensional and four-dimensional gridded values of meteorological and air quality variables obtained through simulation using the WRF-Chem version 3.7 model. The files present the results of two air quality simulations performed for a region in the tropical Andes, each one using a different biogenic emission inventory. In addition, the dataset contains the information needed to replicate the elaboration of the local emission inventory using the BIGA, and the gridded anthropogenic and biogenic emission inventories employed for simulation.
DOI: 10.17632/6h6c3b57mj
title: Can growth mindset interventions improve academic achievement?

description: Encouraging the idea of a growth mindset in which students believe that they can improve their ability, as opposed to a fixed mindset, has been suggested as an effective and relatively cheap approach to improving student attainment at school. This paper offers a comprehensive review of the evidence from growth mindset interventions. After a rigorous search, screening, and evaluation, the inclusion criteria led to 24 studies. All were randomised control trials (RCTs) focused on growth mindset of intelligence interventions for school-age children, and included output measures for academic performance assessment. Their findings reveal that the strongest studies, characterised by larger sample sizes, minimal missing data, and high data quality, exhibit null or very small effect sizes, ranging from Cohen's d = -0.008 to +0.054. Additionally, certain findings raise concerns about a potential conflict-of-interest bias, suggesting that some negative or null results may remain unpublished. The review identifies three evaluations with a high degree of trustworthiness and with no conflict of interest. Among these, two studies indicate no discernible impact, while one shows a small impact. Given these findings, it is not advisable for schools, school districts, or governments to allocate significant time or resources to the implementation of growth mindset interventions, as the anticipated outcomes are likely to be either null or very modest. However, if there is an opportunity to implement such interventions at a minimal or negligible cost, or as part of another objective, it might be reasonable to proceed with them, considering the potential for a small positive impact.
DOI: 10.17632/9c6y62nv9z
title: Sponges and coral microbiome 1/3

description: This repository contain data generated by Illumina MiSeq of different invertabrates. It is divided in 3 different data sets (see sample_data file for indentification of Sponge Samples )
DOI: 10.17632/kb9sgg7x2p
title: AutoNaVIT : Vision-Based Path and Obstacle Segmentation Dataset for Autonomous Driving - CSV Compatible

description: AutoNaVIT is a carefully designed dataset intended to advance research in autonomous navigation, semantic scene understanding, and deep learning-based object segmentation. This release includes only the annotation labels in CSV format, corresponding to high-resolution frames extracted from a driving sequence recorded at Vellore Institute of Technology – Chennai Campus (VIT-C). The corresponding images will be provided in Version 2 of the dataset.

The dataset comprises manually annotated bounding boxes for three key classes that are critical for path planning and perception in autonomous vehicle systems:

Kerb – 1,377 instances

Obstacle – 258 instances

Path – 532 instances

All annotations were generated using Roboflow, with precise, human-verified labeling for consistent, high-quality data—essential for training robust models that generalize well to real-world urban and semi-urban driving scenarios.

Data Capture Specifications
The video footage used for annotation was recorded using a Sony IMX890 camera sensor under stable daylight conditions, with the following details:

Sensor Size: 1/1.56", 50 MP

Lens: 6P optical configuration

Aperture: ƒ/1.8

Focal Length: 24mm equivalent

Pixel Size: 1.0 µm

Features: Optical Image Stabilization (OIS), PDAF autofocus

Video Duration: 4 minutes 11 seconds

Frame Rate: 2 FPS

Total Annotated Frames: 504

Format Compatibility and Model Support
AutoNaVIT’s annotations are made available in standard CSV format, enabling direct compatibility with the following three models:

Multiclass

TensorFlow CSV

RetinaNet

Since CSV is a highly adaptable format, the annotations can be easily modified or reformatted to suit other deep learning models or pipelines that support CSV-based label structures.

Benchmark Results
To validate the dataset's effectiveness, a segmentation model using YOLOv8 was trained with the full dataset (images + annotations). The resulting performance metrics were:

Mean Average Precision (mAP): 96.5%

Precision: 92.2%

Recall: 94.4%

These metrics confirm the dataset’s value in developing perception systems for autonomous vehicles, particularly for object detection and path segmentation tasks.

Disclaimer and Attribution Requirement
By accessing or using this dataset, users agree to the following terms under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0):

The dataset is available for non-commercial academic and research purposes only.

Proper attribution must be included as:
“Dataset courtesy of Vellore Institute of Technology – Chennai Campus.”
This citation must appear in all forms of publication, presentation, or dissemination using this dataset.

Redistribution, commercial usage, public hosting, or modification of the dataset is not permitted without explicit written consent from VIT-C.

Use of the dataset indicates acceptance of these conditions. All rights not explicitly granted are reserved by VIT-C.
DOI: 10.6084/m9.figshare.11702076.v1
title: Patient 3

description: Premature Ventricular Contraction patient #1Part 1 contains the raw ultrasound RF dataPart 2 contains the B-mode, multi-2D and 3D-rendered EWI activation timings
DOI: 10.15468/dl.7prrp9
title: Occurrence Download

description: A dataset containing 374660 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Arachnida",
 "Year is 2014"
 ]
}

 The dataset includes 374660 records from 822 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009104-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/ehqbql
title: Standard baseline result for working mothers in Ibadan SHEVACCS

description: shevacccs
DOI: 10.7910/dvn/nike3d
title: Project participant database- Year 5

description: It captures general demographic information of SSA farmers. This database provides the list of participant farmers by township and implementing partners in Year 5, including the type of gender, age, household member, pond acre and number of own land acres.
description: Type: Dataset; Sub-type(s): Other (Project participant data)
DOI: 10.7910/dvn/eglszc
title: Replication Data for: 'Overinference from Weak Signals and Underinference from Strong Signals'

description: The data and programs replicate tables and figures from "Overinference from Weak Signals and Underinference from Strong Signals," by Augenblick, Lazarus, and Thaler. Please see the README file for additional details.
DOI: 10.7910/dvn/elzsbf
title: A90_3553.jpg

description: Link to OCHRE database: &lt;a href = 'http://pi.lib.uchicago.edu/1001/org/ochre/197de953-ed14-4d6f-2b81-4536f86c5024'&gt;http://pi.lib.uchicago.edu/1001/org/ochre/197de953-ed14-4d6f-2b81-4536f86c5024
DOI: 10.7910/dvn/nkafge
title: Promise Program Eligible Academic Programs

description: Data include information on more than 13,000 academic programs across 9 states with program-based promise programs in the 2023 academic year. These states include Arkansas, Indiana, Kansas, Kentucky, Minnesota, Missouri, South Carolina, Virginia, and West Virginia. Data were collected across a variety of sources, such as state government, policy-specific, and college-specific websites. Data include 2- and 6-digit CIP code classifications, the name of the program (e.g. Advanced Manufacturing Technology), the college where the program is offered, and the degree type (e.g. certificate, associate, or bachelor’s degree). 6-digit CIP codes have a high degree of missingness, and 2-digit CIP codes are imputed based on academic program name when missing.
DOI: 10.7910/dvn/nl8vwv
title: X3D_model

description: Title: Zang tumb tuuum

Author: Marinetti, F. T. (1876-1944)

Date: 1914

Dimensions: 225 page portfolio

Details: Original printed orange wrappers; in cloth case. Inscribed by the author on front fly-leaf.

Link to catalog record

This model was created with Agisoft Metashape from 144 images captured by Harvard Library Imaging Services, Widener Library using a Nikon D810 and Zeiss 100mm lens at f/16, 1/60sec.
DOI: 10.7910/dvn/nmdj36
title: Replication Data for: Examining American Attitudes toward vaccination during the COVID-19 Pandemic from the Perspective of Negative and Positive Right

description: Data to accompany publication of:
Koong, AJ, McDermott, R, & Kaplan, RM (2023). Examining American Attitudes toward vaccination during the COVID-19 Pandemic from the Perspective of Negative and Positive Right. Politics and the Life Sciences.
DOI: 10.7910/dvn/ehcbdo
title: Replication Data for: Explaining state participation in ten universal WMD treaties: A survival analysis of ratification decisions

description: Replication Data for Karlas, Jan (2023): Explaining state participation in ten universal WMD treaties: A survival analysis of ratification decisions.
DOI: 10.7910/dvn/egw86k
title: Humans versus Chatbots: Scaling-Up Behavioral Interventions to Reduce Teacher Shortages

description: This is the replication package for "Humans versus Chatbots: Scaling-up Behavioral Interventions to Reduce Teacher Shortages," accepted in 2024 by the Journal of Political Economy Microeconomics.
DOI: 10.7910/dvn/niwbvy
title: 2008 locations of ship-track pixels

description: Granule names, latitudes and longitudes of ship-track pixels in year 2008, date and time of each ship-track pixels can be derived from granule name. ind_i and in_j are the indices of ship-track pixels in the Aqua granule hdf file. Please ignore ship-track pixels over land if any.
DOI: 10.7910/dvn/nkxvep
title: A99_12568A.jpg

description: Link to OCHRE database: &lt;a href = 'http://pi.lib.uchicago.edu/1001/org/ochre/054ea6a0-4959-dcc3-e518-9eedbbf04da3'&gt;http://pi.lib.uchicago.edu/1001/org/ochre/054ea6a0-4959-dcc3-e518-9eedbbf04da3