cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2hz92w
title: CCDC 2323018: Experimental Crystal Structure Determination

description: Related Article: Suma Dilipkumar|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: 10.5517/ccdc.csd.cc2hz93x
title: CCDC 2323019: Experimental Crystal Structure Determination

description: Related Article: Suma Dilipkumar|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.10090407
title: V2C: Venμs Vessel Classification

description: This dataset comprises raw multispectral imagery acquired from the VENµS (Vegetation and Environment monitoring on a New Micro Satellite)  satellite, featuring a single sensor, the VSSC (VENµS SuperSpectral Camera), which captures high-resolution, multispectral optical images of the Earth's surface. VENµS is an innovative Earth observation mission, resulting from a collaborative effort between France and Israel. The mission serves dual purposes: it conducts both scientific and technological exploration. On the scientific front, VENµS focuses on capturing detailed imagery of the Earth's surface to bolster our comprehension and simulation of terrestrial, vegetative, and ecological dynamics. It aims to propel advancements in various environmental applications, including assessments of water balance, agricultural productivity, and carbon exchange processes
 

Purpose: This dataset is specifically curated for the development and validation of deep learning models aimed at classifying maritime vessels directly onboard satellites from raw multispectral data. By providing a range of spectral information (12 Bands), the dataset is instrumental in distinguishing between different types of vessels, such as cargo ships and tankers, based on their spectral signatures.
 

Data Characteristics:

- Data Type: Raw multispectral imagery. The VENµS satellite's VSSC instrument has 12 spectral bands with central wavelengths ranging from 420 nm to 910 nm. These bands have bandwidths ranging from 16-20 nm. The selection of these bands is strategic for characterizing vegetation status and for estimating atmospheric constituents like aerosol optical depth and water vapor content for accurate atmospheric corrections. The sensor's capabilities are optimized for a variety of applications, including vegetation monitoring and studies of coastal areas and inland waters.
- Annotations: The dataset for detection is annotated in the COCO (Common Objects in Context) format, supplemented with AIS (Automatic Identification System) data to provide accurate vessel identification and classification. In this dataset the annotations are just categories.
- Categories: Annotated categories include various vessel types, for example, Cargo, Tanker, Fishing, Passenger, and others, as discernible from the AIS data.
 

Use Case: The primary use case of this dataset is to facilitate research and development in the field of vessel classification using cutting-edge AI techniques in remote sensing. The dataset is poised to contribute to the enhancement of maritime surveillance, traffic monitoring, and environmental studies related to maritime activities.
 
Note: For further details on the sensor's technical specifications and configuration, refer to the detailed documentation available in [10.1109/IGARSS.2010.5652087]
DOI: 10.5281/zenodo.10090408
title: V2C: Venμs Vessel Classification

description: This dataset comprises raw multispectral imagery acquired from the VENµS (Vegetation and Environment monitoring on a New Micro Satellite)  satellite, featuring a single sensor, the VSSC (VENµS SuperSpectral Camera), which captures high-resolution, multispectral optical images of the Earth's surface. VENµS is an innovative Earth observation mission, resulting from a collaborative effort between France and Israel. The mission serves dual purposes: it conducts both scientific and technological exploration. On the scientific front, VENµS focuses on capturing detailed imagery of the Earth's surface to bolster our comprehension and simulation of terrestrial, vegetative, and ecological dynamics. It aims to propel advancements in various environmental applications, including assessments of water balance, agricultural productivity, and carbon exchange processes
 

Purpose: This dataset is specifically curated for the development and validation of deep learning models aimed at classifying maritime vessels directly onboard satellites from raw multispectral data. By providing a range of spectral information (12 Bands), the dataset is instrumental in distinguishing between different types of vessels, such as cargo ships and tankers, based on their spectral signatures.
 

Data Characteristics:

- Data Type: Raw multispectral imagery. The VENµS satellite's VSSC instrument has 12 spectral bands with central wavelengths ranging from 420 nm to 910 nm. These bands have bandwidths ranging from 16-20 nm. The selection of these bands is strategic for characterizing vegetation status and for estimating atmospheric constituents like aerosol optical depth and water vapor content for accurate atmospheric corrections. The sensor's capabilities are optimized for a variety of applications, including vegetation monitoring and studies of coastal areas and inland waters.
- Annotations: The dataset for detection is annotated in the COCO (Common Objects in Context) format, supplemented with AIS (Automatic Identification System) data to provide accurate vessel identification and classification. In this dataset the annotations are just categories.
- Categories: Annotated categories include various vessel types, for example, Cargo, Tanker, Fishing, Passenger, and others, as discernible from the AIS data.
 

Use Case: The primary use case of this dataset is to facilitate research and development in the field of vessel classification using cutting-edge AI techniques in remote sensing. The dataset is poised to contribute to the enhancement of maritime surveillance, traffic monitoring, and environmental studies related to maritime activities.
 
Note: For further details on the sensor's technical specifications and configuration, refer to the detailed documentation available in [10.1109/IGARSS.2010.5652087]
DOI: 10.5519/qd.pic3didg
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (5374691 records)
DOI: 10.25345/c5zg6gj46
title: MassIVE MSV000093747 - DYRK1B blockade promotes tumoricidal macrophage activity in pancreatic cancer
title: Highly malignant pancreatic ductal adenocarcinoma (PDAC) is characterized by an abundant immunosuppressive and fibrotic tumor microenvironment (TME). Future therapeutic attempts therefore demand targeting of both compartments in order to be effective. We show here that Dual Specificity and Tyrosine Phosphorylation-regulated Kinase 1B (DYRK1B) represents a compartment-agnostic anti-cancer target in PDAC. DYRK1B is mainly expressed by pancreatic epithelial cancer cells and modulates the influx and activity of TME-associated macrophages through effects on the cancer cells themselves as well as affecting the tumor secretome. Mechanistically, genetic ablation or pharmacological inhibition of DYRK1B strongly attracts tumoricidal macrophages and in addition downregulates the phagocytosis checkpoint and "don't eat me"-signal CD24 on cancer cells, resulting in enhanced tumor cell phagocytosis. Consequently, tumor cells lacking DYRK1B hardly expand in transplantation experiments despite doing so rapidly in culture. Furthermore, combining a small-molecule DYRK1B-directed therapy with mTOR inhibition and conventional chemotherapy stalls the growth of established tumors and results in significant extension of life span in a highly aggressive autochthonous model of PDAC. In light of DYRK inhibitors currently entering clinical phase testing, our data thus provide a novel and clinically translatable approach targeting the cancer cell compartment and its microenvironment, both.
DOI: 10.21227/fnfp-yv12
title: Flow shop scheduling under ToU tariffs

description: Time-of-use (ToU) tariffs flexibly offer cheaper electricity prices to industrial and residential users during off-peak periods, encouraging them to shift their peak electricity demands in valley periods. Flow Shop Scheduling (FSS) model is one of the most prevalent models in manufacturing. To explore the significant role of ToU tariffs in manufacturing, this study addresses a novel bi-objective FSS problem under ToU tariffs.
DOI: 10.6084/m9.figshare.24303109
title: Chromosome-scale genome assembly of <i>Lepus oiostolus</i> (<i>Lepus</i>, Leporidae) (<i>天兔座</i>，Leporidae）

description: <i>Lepus oiostolus</i> (<i>L. oiostolus</i>) is a species endemic to the Qinghai-Tibet Plateau. However, the absence of a reference genome limits genetic studies. Here, we report a high-quality <i>L. oiostolus</i> genome assembly, with scaffolds anchored to 24 chromosomes and a total assembled length of 2.80 Gb (contig N50 = 64.25 Mb). We found that transposable elements account for 49.84% of the genome, a total of 22,295 predicted protein-coding genes. Long interspersed nuclear elements (LINEs) constitute a high proportion of the genome. This study will provide a valuable genomic resource for future research on the evolution of the Leporidae.
DOI: 10.5281/zenodo.7915934
title: Temporal Seismic Velocity Changes Associated with the Mw 6.1, May 2008 Ölfus Doublet, South Iceland: a Joint Interpretation from dv/v and GPS. Cubuk-Sabuncu-etal-Dataset

description: The dataset for the article "Temporal Seismic Velocity Changes Associated with the Mw 6.1, May 2008 Ölfus Doublet, South Iceland: a Joint Interpretation from dv/v and GPS" by Cubuk-Sabuncu et al. is provided.
DOI: 10.6084/m9.figshare.23943060
title: Dataset_Graph

description: The "Dataset_Graph.zip" file contains the graph models of the trees in the dataset. These graph models are saved in the "pickle" format, which is a binary format used for 
serializing Python objects. The graph models capture the structural information and relationships of the cylinders in each tree, representing the hierarchical organization of the branches.
DOI: 10.6084/m9.figshare.23943060.v1
title: Dataset_Graph

description: The "Dataset_Graph.zip" file contains the graph models of the trees in the dataset. These graph models are saved in the "pickle" format, which is a binary format used for 
serializing Python objects. The graph models capture the structural information and relationships of the cylinders in each tree, representing the hierarchical organization of the branches.
DOI: 10.6084/m9.figshare.23943063
title: Dataset_transformation_matrix

description: The scanning projects were registered within their project coordinate system, which can be converted to geocentric coordinate system and geographic coordinate system using the provided 
transformation matrix for each project and a Python script in GitHub repository (https://github.com/hadi-yazdi/TreeML-Data).
DOI: 10.6084/m9.figshare.23943063.v1
title: Dataset_transformation_matrix

description: The scanning projects were registered within their project coordinate system, which can be converted to geocentric coordinate system and geographic coordinate system using the provided 
transformation matrix for each project and a Python script in GitHub repository (https://github.com/hadi-yazdi/TreeML-Data).
DOI: 10.6084/m9.figshare.23943066
title: Projects_map

description: The projects map file is provided in .kml format, allowing users to view the locations of the 40 projects on Earth browsers such as Google Earth. This file serves as a guide for 
locating each project based on their respective project names.
DOI: 10.6084/m9.figshare.23943066.v1
title: Projects_map

description: The projects map file is provided in .kml format, allowing users to view the locations of the 40 projects on Earth browsers such as Google Earth. This file serves as a guide for 
locating each project based on their respective project names.
DOI: 10.6084/m9.figshare.23943072
title: TreeML_Data_QSM

description: we have included a separate dataset CSV file named "TreeML_Dataset_QSM," which presents the structural measurements of the entire tree dataset obtained through the TreeQSM model.
DOI: 10.6084/m9.figshare.23943069
title: TreeML_Data

description: The main CSV tree dataset, named TreeML_Dataset, contains the structural measurements of 3,755 trees, along with their corresponding botanical names.
DOI: 10.6084/m9.figshare.23943078
title: Readme

description: Readme file for describing the dataset
DOI: 10.6084/m9.figshare.23943069.v1
title: TreeML_Data

description: The main CSV tree dataset, named TreeML_Dataset, contains the structural measurements of 3,755 trees, along with their corresponding botanical names.
DOI: 10.6084/m9.figshare.23943072.v1
title: TreeML_Data_QSM

description: we have included a separate dataset CSV file named "TreeML_Dataset_QSM," which presents the structural measurements of the entire tree dataset obtained through the TreeQSM model.
DOI: 10.6084/m9.figshare.23943078.v1
title: Readme

description: Readme file for describing the dataset
DOI: 10.6084/m9.figshare.23943195
title: Dataset_QSM

description: The "Dataset_QSM.zip" file includes three directories: "opt," "optcsv," and "trans," which correspond to each project in the dataset. The "opt" directory contains the main 
Quantitative Structure Model (QSM) files in ".mat" format. These files store the structural information of the tree cylinders, including their geometry and other relevant attributes. 
In the "optcsv" directory, you can find the extracted features from the QSM files in a more accessible format, specifically as ".csv" files. These files contain 
the selected features of the cylinders, making it easier to work with and analyze the QSM data. Lastly, the "trans" directory holds the transformation information files. 
These files provide the necessary details for converting the location coordinates of the cylinders to the project's coordinate system.
DOI: 10.6084/m9.figshare.23947230
title: Dataset_pointcloud

description: In the "Dataset_pointcloud.zip," you will find two files related to the point clouds in the dataset: "Dataset_building_other.zip" and "Dataset_tree.zip." The "Dataset_building_other.zip" 
file contains separate text files for each project, specifically for the "Buildings" and "Other" point clouds. On the other hand, the "Dataset_tree.zip" file includes all the point cloud 
files for the trees in each project. These files are in TXT format and consist of four main numbers representing each point in the point clouds. The first three numbers represent the location 
coordinates of the point. These coordinates typically correspond to the X, Y, and Z coordinates in a 3D space, indicating the position of the point within the project. The fourth number in each 
line represents the intensity value of the point.
DOI: 10.6084/m9.figshare.23943195.v1
title: Dataset_QSM

description: The "Dataset_QSM.zip" file includes three directories: "opt," "optcsv," and "trans," which correspond to each project in the dataset. The "opt" directory contains the main 
Quantitative Structure Model (QSM) files in ".mat" format. These files store the structural information of the tree cylinders, including their geometry and other relevant attributes. 
In the "optcsv" directory, you can find the extracted features from the QSM files in a more accessible format, specifically as ".csv" files. These files contain 
the selected features of the cylinders, making it easier to work with and analyze the QSM data. Lastly, the "trans" directory holds the transformation information files. 
These files provide the necessary details for converting the location coordinates of the cylinders to the project's coordinate system.
DOI: 10.6084/m9.figshare.23947230.v1
title: Dataset_pointcloud

description: In the "Dataset_pointcloud.zip," you will find two files related to the point clouds in the dataset: "Dataset_building_other.zip" and "Dataset_tree.zip." The "Dataset_building_other.zip" 
file contains separate text files for each project, specifically for the "Buildings" and "Other" point clouds. On the other hand, the "Dataset_tree.zip" file includes all the point cloud 
files for the trees in each project. These files are in TXT format and consist of four main numbers representing each point in the point clouds. The first three numbers represent the location 
coordinates of the point. These coordinates typically correspond to the X, Y, and Z coordinates in a 3D space, indicating the position of the point within the project. The fourth number in each 
line represents the intensity value of the point.
DOI: 10.14473/csda/wualtl/dge8py
title: seznam_divaku_ukazka.pdf

description: Seznam diváků - ukázka.
DOI: 10.14473/csda/wualtl/lqo2wh
title: Kralovny_letak_obsazeni_large_print.docx

description: Obsazení představení Královny vod.
DOI: 10.14473/csda/wualtl/1u7ds1
title: Odkazy_Vocaleyes.docx

description: Odkazy na materiály VocalEyes.
DOI: 10.14473/csda/wualtl/m95yyb
title: The-Southbury-Child-The-Bridge-Theatre-2022-Introdu.pdf

description: :unav
DOI: 10.14473/csda/wualtl/42iekd
title: Large-Print-Cast-List-The-Southbury-Child-Bridge-Theatre-July-2022.pdf

description: :unav
DOI: 10.14473/csda/wualtl/6n85gj
title: Kralovny_vod.docx

description: Informace o představení.
DOI: 10.14473/csda/wualtl/ahn6vo
title: Letak_obsazeni_Bp.pdf

description: Leták představení s obsazením v Braillově písmu.
DOI: 10.14473/csda/wualtl
title: Uzpůsobování divadelního představení nevidomým divákům

description: Výzkum byl prováděn v rámci diplomové práce Uzpůsobování divadelního představení nevidomým divákům psané na Katedře divadelních a filmových studií Filozofické fakulty Univerzity Palackého v Olomouci. Diplomová práce se zaměřuje především na to, jestli je možné úspěšně aplikovat britský způsob uzpůsobování divadelních představení do České republiky. V repozitáři najdeme příklad dokumentů a souborů vytvářených během uzpůsobování představení ve Velké Británii, jejich české varianty vytvořené v rámci uzpůsobování inscenace Královny Moravského divadla Olomouc, nahrávky rozhovorů s nevidomými diváky reflektující kvalitu uzpůsobeného představení Královny a jeden díl zvukového magazínu Naše šance reflektující uzpůsobené představení a obsahující audio nahrávky z touch tour a z představení s audio popisem.
DOI: 10.34740/kaggle/dsv/7323504
title: 2021 World Population (updated daily)
DOI: 10.11583/dtu.22555672.v1
title: Data for "Structural trends in antibody-antigen binding interfaces: a computational analysis of 1833 experimentally determined 3D structures"

description: Raw data from the paper "Structural trends in antibody-antigen binding interfaces: a computational analysis of 1833 experimentally determined 3D structures". The files contain the raw contact points extracted using the Python script as described in the paper. The data also contains a reference file with the atoms in the pdb files not considering if they are contact points or not.
DOI: 10.11583/dtu.22555672
title: Data for "Structural trends in antibody-antigen binding interfaces: a computational analysis of 1833 experimentally determined 3D structures"

description: Raw data from the paper "Structural trends in antibody-antigen binding interfaces: a computational analysis of 1833 experimentally determined 3D structures". The files contain the raw contact points extracted using the Python script as described in the paper. The data also contains a reference file with the atoms in the pdb files not considering if they are contact points or not.
DOI: 10.34740/kaggle/dsv/7323521
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.10450866
title: Google questionnaire English - Association of the Magnitude of anti-SARS-CoV-2 Vaccine Side Effects with Sex, Allergy History, Chronic Diseases, Medications Intake and SARS-CoV-2 Infection
DOI: 10.5281/zenodo.10450867
title: Google questionnaire English - Association of the Magnitude of anti-SARS-CoV-2 Vaccine Side Effects with Sex, Allergy History, Chronic Diseases, Medications Intake and SARS-CoV-2 Infection
DOI: 10.5281/zenodo.10450880
title: Google questionnaire Arabic - Association of the Magnitude of anti-SARS-CoV-2 Vaccine Side Effects with Sex, Allergy History, Chronic Diseases, Medications Intake and SARS-CoV-2 Infection
DOI: 10.5281/zenodo.10450881
title: Google questionnaire Arabic - Association of the Magnitude of anti-SARS-CoV-2 Vaccine Side Effects with Sex, Allergy History, Chronic Diseases, Medications Intake and SARS-CoV-2 Infection
DOI: 10.5281/zenodo.10450886
title: YUZ JAG' SOXASI JAROHATLARI VA JAG' SUYAKLARI SINISHI.
DOI: 10.5281/zenodo.10450887
title: YUZ JAG' SOXASI JAROHATLARI VA JAG' SUYAKLARI SINISHI.
DOI: 10.5281/zenodo.10450901
title: DIDAKTIK ASARLARNI O'RGANISH USULLARI   (IBROHIM ADHAM QISSASI MISOLIDA)
DOI: 10.5281/zenodo.10450902
title: DIDAKTIK ASARLARNI O'RGANISH USULLARI   (IBROHIM ADHAM QISSASI MISOLIDA)
DOI: 10.5281/zenodo.10450915
title: O`QUVCHILARNI   SAN'ATNING  TURLI  ОQIM  VA YO`NALISHLARI  BILAN   TANISHTIRISH
DOI: 10.5281/zenodo.10450916
title: O`QUVCHILARNI   SAN'ATNING  TURLI  ОQIM  VA YO`NALISHLARI  BILAN   TANISHTIRISH
DOI: 10.5519/qd.73wehyj4
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (184 records)
DOI: 10.5281/zenodo.10450929
title: THE ROLE AND IMPORTANCE OF CONTINUOUS PEDAGOGICAL PRACTICE IN THE FORMATION OF PROFESSIONAL COMPETENCE OF FUTURE TEACHERS.
DOI: 10.5281/zenodo.10450930
title: THE ROLE AND IMPORTANCE OF CONTINUOUS PEDAGOGICAL PRACTICE IN THE FORMATION OF PROFESSIONAL COMPETENCE OF FUTURE TEACHERS.
DOI: 10.5281/zenodo.10450940
title: IMPLEMENTATION OF INTERDISCIPLINARY RELATIONSHIP IN TEACHING OF READING AND SCIENCES IN PRIMARY GRADES.
DOI: 10.5281/zenodo.10450941
title: IMPLEMENTATION OF INTERDISCIPLINARY RELATIONSHIP IN TEACHING OF READING AND SCIENCES IN PRIMARY GRADES.
DOI: 10.5281/zenodo.10450951
title: THE REFLECTION OF TERMS IN THE ARTISTIC TEXT IS A SPECIFIC FEATURE
DOI: 10.5281/zenodo.10450952
title: THE REFLECTION OF TERMS IN THE ARTISTIC TEXT IS A SPECIFIC FEATURE
DOI: 10.5281/zenodo.10450968
title: CONTENT OF THE WORD AND ITS SIGNIFICANCE
DOI: 10.5281/zenodo.10450969
title: CONTENT OF THE WORD AND ITS SIGNIFICANCE
DOI: 10.5281/zenodo.10450981
title: MYTHOLOGICAL THINKING AND CREATIVE ART WORLD
DOI: 10.5281/zenodo.10450982
title: MYTHOLOGICAL THINKING AND CREATIVE ART WORLD
DOI: 10.5281/zenodo.10450993
title: THE STUDY OF DERIVATIONAL PROPERTIES OF TERMS
DOI: 10.5281/zenodo.10450994
title: THE STUDY OF DERIVATIONAL PROPERTIES OF TERMS
DOI: 10.6084/m9.figshare.15190011
title: Processing L2 Russian verbal morphology: The effect of language immersion on priming patterns

description: These datasets include reaction times from a masked priming study. The goal of the study is to study processing of Russian verbal morphology in L1 and L2 participants. There were 80 participants in total, 57 second language learners and 23 Russian native speakers. <br>
DOI: 10.6084/m9.figshare.15190011.v6
title: Processing L2 Russian verbal morphology: The effect of language immersion on priming patterns

description: These datasets include reaction times from a masked priming study. The goal of the study is to study processing of Russian verbal morphology in L1 and L2 participants. There were 80 participants in total, 57 second language learners and 23 Russian native speakers. <br>