cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2fkx64
title: CCDC 2251536: Experimental Crystal Structure Determination

description: Related Article: Kasumi Hayashi, Qiuming Liang, Franka Philippi, Datong Song|2024|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.13909301
title: BAXSHICHILIK SAN'ATINING O'RTA OSIYODA MUSIQA MADANIYATI RIVOJIDAGI O'RNI VA AHAMIYATI
DOI: 10.5281/zenodo.13909302
title: BAXSHICHILIK SAN'ATINING O'RTA OSIYODA MUSIQA MADANIYATI RIVOJIDAGI O'RNI VA AHAMIYATI
DOI: 10.5281/zenodo.13780495
title: Ruinon Landslide, Northern Italy - Evolution and Environmental Factors Through a Virtual Reality Environment - UNITY Dataset

description: This project is part of the thesis titled "Exploring Landslide Evolution and Environmental Factors Through a Virtual Reality Environment", submitted for the MSc. of Geoinformatics Engineering degree at Politecnico di Milano. The development was carried out by Huzaifa Mohammed Khair Khider Abdulaziz and Mohamed Ridaeldin Mukhtar Mohamed during the Academic Year 2023-2024; supervised by Prof. Maria Antonia Brovelli and co-supervised by Dr. Vasil Yordanov.

Video examples of the environment:

Ruinon landslide, Italy - Surrounding area and environmental influencing factors in a VR Environment

Ruinon landslide, Italy - Landslide evolution over time in the VR Environment.

How to use:

To run the project using the Meta Oculus Quest 2, follow these detailed steps:

 1. Setting Up Oculus Quest 2 for PC VR

 A. Install Oculus Software on PC:   1. Download and install the Oculus PC app (Oculus Link) from the official Meta website.   2. Open the Oculus app after installation and sign in to your Oculus account.

 B. Connecting Oculus Quest 2 to PC:   1. Use a USB-C Cable: Connect the Oculus Quest 2 to your PC using a compatible USB-C cable (Oculus Link cable or any high-quality USB-C cable).   2. Enable Oculus Link:      - Once connected, put on your Oculus Quest 2 headset.      - In the headset, you’ll see a prompt asking if you want to enable Oculus Link.      - Select Enable to connect the headset to the PC.    C. Wireless Option (Air Link):   1. Enable Air Link (Optional):If you prefer wireless connectivity, ensure both the PC and Oculus are connected to the same high-speed Wi-Fi network.   2. In the Oculus PC app, go to Settings > Beta and toggle on Air Link.   3. In your headset, go to Settings > Experimental Features and enable Air Link. Pair the headset with the PC following the on-screen instructions.

 2. Running the VR Project (VR_Terrain_Visualization.exe):      1. After the Oculus Quest 2 is connected to the PC (either via Oculus Link or Air Link), open Windows Explorer and navigate to the folder containing the project file: VR_Terrain_Visualization.exe.   2. Double-click the VR_Terrain_Visualization.exe file to launch the virtual reality environment.   3. Once the application is running, your Oculus Quest 2 headset will automatically display the project, immersing you in the virtual landslide visualization.    3. Interacting with the VR Environment:      - Oculus Quest 2 controllers will allow you to move around, explore the terrain, and interact with different elements of the virtual environment.   - Ensure the controllers are working correctly with Unity’s VR features as per the setup.
DOI: 10.5281/zenodo.13780494
title: Ruinon Landslide, Northern Italy - Evolution and Environmental Factors Through a Virtual Reality Environment - UNITY Dataset

description: This project is part of the thesis titled "Exploring Landslide Evolution and Environmental Factors Through a Virtual Reality Environment", submitted for the MSc. of Geoinformatics Engineering degree at Politecnico di Milano. The development was carried out by Huzaifa Mohammed Khair Khider Abdulaziz and Mohamed Ridaeldin Mukhtar Mohamed during the Academic Year 2023-2024; supervised by Prof. Maria Antonia Brovelli and co-supervised by Dr. Vasil Yordanov.

Video examples of the environment:

Ruinon landslide, Italy - Surrounding area and environmental influencing factors in a VR Environment

Ruinon landslide, Italy - Landslide evolution over time in the VR Environment.

How to use:

To run the project using the Meta Oculus Quest 2, follow these detailed steps:

 1. Setting Up Oculus Quest 2 for PC VR

 A. Install Oculus Software on PC:   1. Download and install the Oculus PC app (Oculus Link) from the official Meta website.   2. Open the Oculus app after installation and sign in to your Oculus account.

 B. Connecting Oculus Quest 2 to PC:   1. Use a USB-C Cable: Connect the Oculus Quest 2 to your PC using a compatible USB-C cable (Oculus Link cable or any high-quality USB-C cable).   2. Enable Oculus Link:      - Once connected, put on your Oculus Quest 2 headset.      - In the headset, you’ll see a prompt asking if you want to enable Oculus Link.      - Select Enable to connect the headset to the PC.    C. Wireless Option (Air Link):   1. Enable Air Link (Optional):If you prefer wireless connectivity, ensure both the PC and Oculus are connected to the same high-speed Wi-Fi network.   2. In the Oculus PC app, go to Settings > Beta and toggle on Air Link.   3. In your headset, go to Settings > Experimental Features and enable Air Link. Pair the headset with the PC following the on-screen instructions.

 2. Running the VR Project (VR_Terrain_Visualization.exe):      1. After the Oculus Quest 2 is connected to the PC (either via Oculus Link or Air Link), open Windows Explorer and navigate to the folder containing the project file: VR_Terrain_Visualization.exe.   2. Double-click the VR_Terrain_Visualization.exe file to launch the virtual reality environment.   3. Once the application is running, your Oculus Quest 2 headset will automatically display the project, immersing you in the virtual landslide visualization.    3. Interacting with the VR Environment:      - Oculus Quest 2 controllers will allow you to move around, explore the terrain, and interact with different elements of the virtual environment.   - Ensure the controllers are working correctly with Unity’s VR features as per the setup.
DOI: 10.5281/zenodo.13898319
title: FactCheckBureau: Build Your Own Fact-Check Analysis Pipeline

description: FactCheckBureau: An end-to-end solution that enables researchers to easily and interactively design and evaluate FC retrieval pipelines.



Fact-checkers are overwhelmed by the volume of claims they need to pay attention to fight misinformation. Even once debunked, a claim may still be spread by people unaware that it is false, or it may be recycled as a source of inspiration by malicious users. Hence, the importance of fact-check (FC) retrieval as a research problem: given a claim and a database of previous checks, find the checks relevant to the claim. Existing solutions addressing this problem rely on the strategy of retrieve and re-rank relevant documents. We have built FactCheckBureau, an end-to-end solution that enables researchers to easily and interactively design and evaluate FC retrieval pipelines. We also present a corpus 1 we have built, which can be used in further research to test fact-check retrieval tools.Paper:  https://zenodo.org/records/13868429Repository: https://gitlab.inria.fr/cedar/factcheckbureau
DOI: 10.5281/zenodo.13898318
title: FactCheckBureau: Build Your Own Fact-Check Analysis Pipeline

description: FactCheckBureau: An end-to-end solution that enables researchers to easily and interactively design and evaluate FC retrieval pipelines.



Fact-checkers are overwhelmed by the volume of claims they need to pay attention to fight misinformation. Even once debunked, a claim may still be spread by people unaware that it is false, or it may be recycled as a source of inspiration by malicious users. Hence, the importance of fact-check (FC) retrieval as a research problem: given a claim and a database of previous checks, find the checks relevant to the claim. Existing solutions addressing this problem rely on the strategy of retrieve and re-rank relevant documents. We have built FactCheckBureau, an end-to-end solution that enables researchers to easily and interactively design and evaluate FC retrieval pipelines. We also present a corpus 1 we have built, which can be used in further research to test fact-check retrieval tools.Paper:  https://zenodo.org/records/13868429Repository: https://gitlab.inria.fr/cedar/factcheckbureau
DOI: 10.18739/a2cz32678
title: Lab experiments of synthetic ice mélange, 2022-2024

description: ### Access 

Dataset and extensive metadata can be accessed and downloaded via: [https://arcticdata.io/data/10.18739/A2CZ32678/](https://arcticdata.io/data/10.18739/A2CZ32678/) 

### Overview 

A limited understanding of how glacier-ocean interactions lead to iceberg calving and melting at the ice-ocean boundary contributes to uncertainty in predictions of sea level rise. Dense packs of icebergs and sea ice, known as ice mélange, occur in many fjords in Greenland and Antarctica. Observations suggest that ice mélange may directly affect iceberg calving by pressing against the glacier front and indirectly affect glacier melting by controlling where and when icebergs melt which can impact ocean circulation and ocean heat transport towards glaciers. However, the interactions between ice mélange, ocean circulation, and iceberg calving have not been systematically investigated due to the difficulty of conducting field work in Greenland fjords. In order to investigate the dynamics of ice mélange (and other floating granular materials) and to inform development of ice mélange models, we conducted a series of laboratory experiments using synthetic icebergs (plastic blocks) that were pushed down a tank by a synthetic glacier. This data set consists of force measurements on the glacier terminus and time-lapse photographs of the experiments that were used for visualizing motion.
DOI: 10.15468/dl.n3azvm
title: Occurrence Download

description: A dataset containing 2240 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mannia fragrans (Balb.) Frye & L.Clark"
 ]
}

 The dataset includes 2240 records from 129 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004756-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13332143
title: QC and WGS around the breakpoints of deletions in the compound heterozygous PRKN-deficient PD iPSC line FINi006-A (FI.CS.PRKNDex2/Dex5-7.@40)

description: BAM files from WGS on the regions of deletions in both PRKN gene alleles of the iPSC line (clone 18) derived using Sendai virus from PRKN 09/090 patient's fibroblasts
DOI: 10.5281/zenodo.13332144
title: QC and WGS around the breakpoints of deletions in the compound heterozygous PRKN-deficient PD iPSC line FINi006-A (FI.CS.PRKNDex2/Dex5-7.@40)

description: BAM files from WGS on the regions of deletions in both PRKN gene alleles of the iPSC line (clone 18) derived using Sendai virus from PRKN 09/090 patient's fibroblasts
DOI: 10.15468/dl.8psr2j
title: Occurrence Download

description: A dataset containing 152277 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "DatasetKey is Pl@ntNet automatically identified occurrences"
 ]
}

 The dataset includes 152277 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004722-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13907870
title: The dataset of article "Early Detection of Cognitive Impairment in End-Stage Renal Disease Patients Undergoing Hemodialysis: Insights from Resting-State Functional Connectivity Analysis"

description: This is a file as dataset of the article "Early Detection of Cognitive Impairment in End-Stage Renal Disease Patients Undergoing Hemodialysis: Insights from Resting-State Functional Connectivity Analysis".

It includes fMRI brain imaging data of subjects included in the case group (ESRD group) and healthy control group (HC group).
DOI: 10.5281/zenodo.13907871
title: The dataset of article "Early Detection of Cognitive Impairment in End-Stage Renal Disease Patients Undergoing Hemodialysis: Insights from Resting-State Functional Connectivity Analysis"

description: This is a file as dataset of the article "Early Detection of Cognitive Impairment in End-Stage Renal Disease Patients Undergoing Hemodialysis: Insights from Resting-State Functional Connectivity Analysis".

It includes fMRI brain imaging data of subjects included in the case group (ESRD group) and healthy control group (HC group).
DOI: 10.5281/zenodo.13899480
title: 【outputs_best_number_tokens_to_tpm_large_scales】/best_number_tokens_log_part_12, only two 8B LLMs, 12 (tpm) + 12 (span_vectors) = 24 files

description: Part 12

only two 8B LLMs,  

only valid results (both MP p value and CI),

all permutation controls,

all seeds,

all linguistic spans,

all 5 tasks, 

12 (tpm) + 12 (span_vectors) = 24 files
DOI: 10.5281/zenodo.13899479
title: 【outputs_best_number_tokens_to_tpm_large_scales】/best_number_tokens_log_part_12 (1), only two 8B LLMs, 30 (tpms) = 30 files

description: Part 12 (1)

only two 8B LLMs,  

only valid results (both MP p value and CI),

all permutation controls,

all seeds,

all linguistic spans,

all 5 tasks, 

30 (tpms) = 30 files
DOI: 10.5281/zenodo.13907677
title: 【outputs_best_number_tokens_to_tpm_large_scales】/best_number_tokens_log_part_12 (1), only two 8B LLMs, 30 (tpms) = 30 files

description: Part 12 (1)

only two 8B LLMs,  

only valid results (both MP p value and CI),

all permutation controls,

all seeds,

all linguistic spans,

all 5 tasks, 

30 (tpms) = 30 files
DOI: 10.5281/zenodo.13909274
title: QCA-2024-SCC-KH00340 R&D data

description: Project Code: QCA-2024-SCC-KH00340.This project is classified as CONFIDENTIAL. All information, data, and results associated with this project are strictly restricted to authorized personnel only. Any dissemination, distribution, or copying of the project details is strictly prohibited without prior approval from the project lead and the university's Office of Research Compliance.
DOI: 10.5281/zenodo.13909275
title: QCA-2024-SCC-KH00340 R&D data

description: Project Code: QCA-2024-SCC-KH00340.This project is classified as CONFIDENTIAL. All information, data, and results associated with this project are strictly restricted to authorized personnel only. Any dissemination, distribution, or copying of the project details is strictly prohibited without prior approval from the project lead and the university's Office of Research Compliance.
DOI: 10.5281/zenodo.13908452
title: Exploring the potential of Near Infrared Hyperspectral Imaging and chemometrics to discriminate soil seed bank of two timber species central African : Erythrophleum suaveolens (Guill. & Perr.) Brenan, and Erythrophleum ivorense A. Chev.

description: The data of this study are accessible by sending a request to the corresponding author at the email address: douhch382@gmail.com. https://doi.org/10.5281/zenodo.13908452
DOI: 10.5281/zenodo.13908451
title: Exploring the potential of Near Infrared Hyperspectral Imaging and chemometrics to discriminate soil seed bank of two timber species central African : Erythrophleum suaveolens (Guill. & Perr.) Brenan, and Erythrophleum ivorense A. Chev.

description: The data of this study are accessible by sending a request to the corresponding author at the email address: douhch382@gmail.com. https://doi.org/10.5281/zenodo.13908452
DOI: 10.5281/zenodo.13909382
title: Incremental Covering Array Generation
DOI: 10.5281/zenodo.13909383
title: Incremental Covering Array Generation
DOI: 10.5281/zenodo.13909370
title: QCA-2024-SCC-ER44038 R&D data

description: Project Code: QCA-2024-SCC-ER44038.This project is classified as CONFIDENTIAL. All information, data, and results associated with this project are strictly restricted to authorized personnel only. Any dissemination, distribution, or copying of the project details is strictly prohibited without prior approval from the project lead and the university's Office of Research Compliance.
DOI: 10.5281/zenodo.13909371
title: QCA-2024-SCC-ER44038 R&D data

description: Project Code: QCA-2024-SCC-ER44038.This project is classified as CONFIDENTIAL. All information, data, and results associated with this project are strictly restricted to authorized personnel only. Any dissemination, distribution, or copying of the project details is strictly prohibited without prior approval from the project lead and the university's Office of Research Compliance.
DOI: 10.5281/zenodo.13909316
title: Supplementary Material for Comparison between Electroporation at Different Voltage Levels and Microinjection to Generate Porcine Embryos with Multiple Xenoantigen Knock-outs

description: Data upload for my dissertation about gene editing
DOI: 10.5281/zenodo.13909317
title: Supplementary Material for Comparison between Electroporation at Different Voltage Levels and Microinjection to Generate Porcine Embryos with Multiple Xenoantigen Knock-outs

description: Data upload for my dissertation about gene editing
DOI: 10.5281/zenodo.13898049
title: Dataset: Hybrid Polarizing Solids with Extended Pore Diameters for Dissolution Dynamic Nuclear Polarization

description: This dataset contains raw NMR, EPR, and relaxometry data, N2 adsorption-desorption isotherms for best HYPSOs, and all of the codes, used for data processing and figures in the article.
DOI: 10.5281/zenodo.13898050
title: Dataset: Hybrid Polarizing Solids with Extended Pore Diameters for Dissolution Dynamic Nuclear Polarization

description: This dataset contains raw NMR, EPR, and relaxometry data, N2 adsorption-desorption isotherms for best HYPSOs, and all of the codes, used for data processing and figures in the article.
DOI: 10.15468/dl.95f62p
title: Occurrence Download

description: A dataset containing 877 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is North America",
 "CoordinateUncertaintyInMeters 0.0-1000.0",
 "Geometry POLYGON((-123.88136 28.65099,-57.81281 28.8816,-57.69751 49.1749,-123.88136 49.1749,-123.88136 28.65099))",
 "TaxonKey is Elymus repens (L.) Gould"
 ]
}

 The dataset includes 877 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004759-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13909406
title: QCA-2024-SCC-TU26043 R&D data

description: Project Code: QCA-2024-SCC-TU26043.This project is classified as CONFIDENTIAL. All information, data, and results associated with this project are strictly restricted to authorized personnel only. Any dissemination, distribution, or copying of the project details is strictly prohibited without prior approval from the project lead and the university's Office of Research Compliance.
DOI: 10.5281/zenodo.13909407
title: QCA-2024-SCC-TU26043 R&D data

description: Project Code: QCA-2024-SCC-TU26043.This project is classified as CONFIDENTIAL. All information, data, and results associated with this project are strictly restricted to authorized personnel only. Any dissemination, distribution, or copying of the project details is strictly prohibited without prior approval from the project lead and the university's Office of Research Compliance.
DOI: 10.15468/dl.5y2b73
title: Occurrence Download

description: A dataset containing 4729 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "CoordinateUncertaintyInMeters 0.0-10000.0",
 "Geometry POLYGON((-132.22509 24.8974,-61.77418 24.8974,-61.77418 51.62016,-132.22509 51.62016,-132.22509 24.8974))",
 "TaxonKey is Bromus tectorum L."
 ]
}

 The dataset includes 4729 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004760-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rwrbvt
title: Occurrence Download

description: A dataset containing 1714213 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Pl@ntNet observations"
 ]
}

 The dataset includes 1714213 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004732-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qkfc95
title: Occurrence Download

description: A dataset containing 41 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is MEX",
 "IucnRedListCategory is one of (EX, EW, CR, EN, VU, NT, LC, DD, NE)",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Verbesina elgalloana B.L.Turner, Verbesina crassipes B.L.Rob. & Greenm.)"
 ]
}

 The dataset includes 41 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004762-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/79c61ac1899448e29cf06a6d049b2491
title: Oligotrend, a global database of multi-decadal timeseries of chlorophyll-a and nutrient concentrations in inland and transitional waters, 1986-2023

description: The Oligotrend database is a collection of multi-decadal chlorophyll-a and nutrient timeseries in inland and transitional waters. The objective of this Data Package was to explore how inland and transitional aquatic ecosystems respond to oligotrophication trends.
 Overall, the Oligotrend L1 database is made of 4.3 million valid observations originating from 1,894 stations. There are 238, 687 and 969 stations located in estuaries, lakes and rivers, respectively. The top 3 largest sources of data are the French national water quality monitoring (775 stations), the global database of lake datasets from Naderian et al. 2024 (378 stations), and the Chesapeake Bay Program (199 stations).
 The data was harmonized through a reproducible data processing pathway. In this Data Package, quality-checked level 1 data is provided, together with data sources, geographical coordinates of the stations, and the output of a trend analysis of all timeseries.
DOI: 10.6084/m9.figshare.27196422
title: scirep_data.xlsx

description: scirep data
DOI: 10.6084/m9.figshare.27196422.v1
title: scirep_data.xlsx

description: scirep data
DOI: 10.15468/dl.ukp7ab
title: Occurrence Download

description: A dataset containing 6278697 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is one of (Larus argentatus Pontoppidan, 1763)",
 "BasisOfRecord is one of (Human Observation, Observation, Occurrence evidence)",
 "Year is greater than or equal to 1901",
 "Year is less than or equal to 2019",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 6278697 records from 1172 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004750-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3d4znh
title: Occurrence Download

description: A dataset containing 74 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hyporhamphus Gill, 1859",
 "Country is India"
 ]
}

 The dataset includes 74 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042591-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.