cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8411167
title: Dataset minat beli konsumen ITS melalui endorsment media sosial

description: Dataset minat beli mahasiswa ITS terhadap endorsment celebrity di sosial media
DOI: 10.5281/zenodo.7657481
title: Replication Package - Illicit Content Recognition with Few-shot Learning

description: Replication package and dataset for the paper: When the Few Outweigh the Many: Illicit Content Recognition with Few-shot Learning
DOI: 10.5281/zenodo.7657482
title: Replication Package - Illicit Content Recognition with Few-shot Learning

description: Replication package and dataset for the paper: When the Few Outweigh the Many: Illicit Content Recognition with Few-shot Learning
DOI: 10.5281/zenodo.8411254
title: Ideal Solutions for the Evaluation of A User-driven Hybrid Neuro-symbolic Approach for Knowledge Graph Creation from Relational Data

description: Those two files represent one ideal solution of RML rules for the provided ontology and database by the study conductors. Note: in those two Turtle files joins are not necessary since templates could have been defined, too. This would lead to the same result.
DOI: 10.5281/zenodo.8411253
title: Ideal Solutions for the Evaluation of A User-driven Hybrid Neuro-symbolic Approach for Knowledge Graph Creation from Relational Data

description: Those two files represent one ideal solution of RML rules for the provided ontology and database by the study conductors. Note: in those two Turtle files joins are not necessary since templates could have been defined, too. This would lead to the same result.
DOI: 10.25345/c51v5bq6s
title: MassIVE MSV000093049 - Systematic perturbations of SETD2, NSD1, NSD2, NSD3 and ASH1L reveals their distinct contributions to H3K36 methylation
title: Methylation of histone 3 lysine 36 (H3K36me) has emerged as an essential epigenetic component for the faithful regulation of gene expression. Despite its demonstrated importance in development, disease, and cancer, the molecular agents responsible for the deposition of H3K36me are not yet well understood. Here, we use a mouse mesenchymal stem cell model to comprehensively perturb the components of the H3K36me deposition machinery and infer the activities of the five most prominent players: SETD2, NSD1, NSD2, NSD3, and ASH1L. We find that H3K36me2 is the most abundant of the three methylation states and that it is predominantly deposited at intergenic regions by NSD1, and in part by NSD2. In contrast, H3K36me1/3 are most abundant within exons and have a positive correlation with gene expression. We further demonstrate that while SETD2 is responsible for depositing most H3K36me3, it also deposits a modest amount of H3K36me2 within transcribed genes. Additionally, loss of SETD2 results in an increase of exonic H3K36me1, suggesting that other H3K36 methyltransferases may prime gene bodies with lower methylation states ahead of transcription. Through a reductive approach, we uncover the genome-wide distribution patterns of NSD3- and ASH1L-catalyzed H3K36me2. While NSD1/2 establish broad intergenic H3K36me2 domains, NSD3 deposits broad H3K36me2 peaks centered on active promoter and enhancer regions. Meanwhile, the activity of ASH1L is focused primarily on the promoters of developmentally relevant genes, and our analyses implicate PBX2 as a potential recruitment factor for ASH1L to these regions. Overall, our study provides new insights into the regulation of H3K36me by the H3K36 methyltransferase family and helps to consolidate the wealth of previous observations in the context of a structured analysis.
DOI: 10.5281/zenodo.8411234
title: Dataset related to article "Deep learning and atlas-based models to streamline the segmentation workflow of Total Marrow and Lymphoid Irradiation"

description: This record contains raw data related to article “Deep learning and atlas-based models to streamline the segmentation workflow of Total Marrow and Lymphoid Irradiation" Abstract: <strong>Purpose: </strong>To improve the workflow of Total Marrow and Lymphoid Irradiation (TMLI) by enhancing the delineation of organs-at-risk (OARs) and clinical target volume (CTV) using deep learning (DL) and atlas-based (AB) segmentation models. <strong>Materials and Methods:</strong> Ninety-five TMLI plans optimized in our institute were analyzed. Two commercial DL software were tested for segmenting 18 OARs. An AB model for lymph node CTV (CTV_LN) delineation was built using 20 TMLI patients. The AB model was evaluated on 20 independent patients and a semi-automatic approach was tested by correcting the automatic contours. The generated OARs and CTV_LN contours were compared to manual contours in terms of topological agreement, dose statistics, and time workload. A clinical decision tree was developed to define a specific contouring strategy for each OAR. <strong>Results: </strong>The two DL models achieved a median Dice Similarity Coefficient (DSC) of 0.84 [0.73;0.92] and 0.84 [0.77;0.93] across the OARs. The absolute median dose (Dmedian) difference between manual and the two DL models was 2% [1%;5%] and 1% [0.2%;1%]. The AB model achieved a median DSC of 0.70 [0.66;0.74] for CTV_LN delineation, increasing to 0.94 [0.94;0.95] after manual revision, with minimal Dmedian differences. Since September 2022, our institution has implemented DL and AB models for all TMLI patients, reducing from 5 to 2 hours the time required to complete the entire segmentation process. <strong>Conclusion: </strong>DL models can streamline the TMLI contouring process of OARs. Manual revision is still necessary for lymph node delineation using AB models. <strong>Statements & Declarations</strong> <strong>Funding:</strong> This work was funded by the Italian Ministry of Health, grant AuToMI (GR-2019-12370739). <strong>Competing Interests:</strong> The authors have no conflict of interests to disclose. <strong>Author Contributions:</strong> All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by D.D., N.L., L.C., R.C.B., D.L., and P.M. The first draft of the manuscript was written by D.D. and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. <strong>Ethics approval:</strong> The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Ethics Committee of IRCCS Humanitas Research Hospital (ID 2928, 26 January 2021). ClinicalTrials.gov identifier: NCT04976205. <strong>Consent to participate: </strong>Informed consent was obtained from all individual participants included in the study.
DOI: 10.5281/zenodo.8411233
title: Dataset related to article "Deep learning and atlas-based models to streamline the segmentation workflow of Total Marrow and Lymphoid Irradiation"

description: This record contains raw data related to article “Deep learning and atlas-based models to streamline the segmentation workflow of Total Marrow and Lymphoid Irradiation" Abstract: <strong>Purpose: </strong>To improve the workflow of Total Marrow and Lymphoid Irradiation (TMLI) by enhancing the delineation of organs-at-risk (OARs) and clinical target volume (CTV) using deep learning (DL) and atlas-based (AB) segmentation models. <strong>Materials and Methods:</strong> Ninety-five TMLI plans optimized in our institute were analyzed. Two commercial DL software were tested for segmenting 18 OARs. An AB model for lymph node CTV (CTV_LN) delineation was built using 20 TMLI patients. The AB model was evaluated on 20 independent patients and a semi-automatic approach was tested by correcting the automatic contours. The generated OARs and CTV_LN contours were compared to manual contours in terms of topological agreement, dose statistics, and time workload. A clinical decision tree was developed to define a specific contouring strategy for each OAR. <strong>Results: </strong>The two DL models achieved a median Dice Similarity Coefficient (DSC) of 0.84 [0.73;0.92] and 0.84 [0.77;0.93] across the OARs. The absolute median dose (Dmedian) difference between manual and the two DL models was 2% [1%;5%] and 1% [0.2%;1%]. The AB model achieved a median DSC of 0.70 [0.66;0.74] for CTV_LN delineation, increasing to 0.94 [0.94;0.95] after manual revision, with minimal Dmedian differences. Since September 2022, our institution has implemented DL and AB models for all TMLI patients, reducing from 5 to 2 hours the time required to complete the entire segmentation process. <strong>Conclusion: </strong>DL models can streamline the TMLI contouring process of OARs. Manual revision is still necessary for lymph node delineation using AB models. <strong>Statements & Declarations</strong> <strong>Funding:</strong> This work was funded by the Italian Ministry of Health, grant AuToMI (GR-2019-12370739). <strong>Competing Interests:</strong> The authors have no conflict of interests to disclose. <strong>Author Contributions:</strong> All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by D.D., N.L., L.C., R.C.B., D.L., and P.M. The first draft of the manuscript was written by D.D. and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. <strong>Ethics approval:</strong> The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Ethics Committee of IRCCS Humanitas Research Hospital (ID 2928, 26 January 2021). ClinicalTrials.gov identifier: NCT04976205. <strong>Consent to participate: </strong>Informed consent was obtained from all individual participants included in the study.
DOI: 10.5517/ccdc.csd.cc2cqbq5
title: CCDC 2196217: Experimental Crystal Structure Determination

description: Related Article: Bolesław Picur, Iwona Bryndal, Tadeusz Lis|2023|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.cc2cqbr6
title: CCDC 2196218: Experimental Crystal Structure Determination

description: Related Article: Tadeusz Lis|2023|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.cc2cwl0w
title: CCDC 2201248: Experimental Crystal Structure Determination

description: Related Article: Li Lu|2023|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.cc2czwv3
title: CCDC 2204436: Experimental Crystal Structure Determination

description: Related Article: Zhifang Guo, Jun Wang, Glen B. Deacon, Peter Courtney Junk|2023|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.cc2dg5wy
title: CCDC 2218170: Experimental Crystal Structure Determination

description: Related Article: Longyu Li|2023|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.cc2g7pcs
title: CCDC 2271505: Experimental Crystal Structure Determination

description: Related Article: Xiao-Bo Ding, Alexander Wung, Daniel P. Furkert, Margaret A. Brimble|2023|Org.Biomol.Chem.|21|6008|doi:10.1039/D3OB00998J
description: Related Article: Xiao-Bo Ding, Alexander Wung, Daniel P. Furkert, Margaret A. Brimble*|2023|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.cc2g7qyd
title: CCDC 2271554: Experimental Crystal Structure Determination

description: Related Article: Philipp Meyer, Amitabh Banerji, Eric Sperlich|2023|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.cc2g7t2m
title: CCDC 2271620: Experimental Crystal Structure Determination

description: Related Article: Madavi S. Prasad and Murugesan Sivaprakash|2023|CSD Communication|||
description: Related Article: Madavi S. Prasad, Murugesan Sivaprakash, A. Palanichamy|2022|Org.Biomol.Chem.|20|6329|doi:10.1039/D2OB01085B
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.cc2g7t4p
title: CCDC 2271622: Experimental Crystal Structure Determination

description: Related Article: Mauricio Saraiva, Pascal Retailleau, Robert H. Dodd|2023|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.cc2g7tfz
title: CCDC 2271631: Experimental Crystal Structure Determination

description: Related Article: Mauricio Saraiva, Pascal Retailleau, Robert H. Dodd|2023|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.cc2g7ttc
title: CCDC 2271643: Experimental Crystal Structure Determination

description: Related Article: Mauricio Saraiva, Pascal Retailleau, Robert H. Dodd|2023|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.cc2h5sk1
title: CCDC 2299473: Experimental Crystal Structure Determination

description: Related Article: Yu Ting Huang|2023|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: 10.6084/m9.figshare.24251236
title: PFCinLSUT_LiceaJKhanOASinghTModleskyCM_EJN_2023

description: Data from EJN paper titled "Prefrontal cortex hemodynamic activity during a test of lower extremity functional muscle strength in children with cerebral palsy: a functional near-infrared spectroscopy study".<br><br>
DOI: 10.5519/qd.4d7irxpb
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (2567 records)
DOI: 10.6084/m9.figshare.23546517
title: Data and Analysis Code: Non-Consummatory Behavior Signals Predict Aversion-Resistant Alcohol Drinking in Head-Fixed Mice

description: This file contains behavioral data and analysis code for a study examining aversion-resistant drinking in head-fixed mice.<br>Abstract:A key facet of alcohol use disorder is continuing to drink alcohol despite negative consequences (so called "aversion-resistant drinking"). In this study, we sought to assess the degree to which head-fixed mice exhibit aversion-resistant drinking and to leverage behavioral analysis techniques available in head-fixture to relate non-consummatory behaviors to aversion-resistant drinking. We assessed aversion-resistant drinking in head-fixed female and male C57BL/6J mice. We adulterated 20% (v/v) alcohol with varying concentrations of the bitter tastant quinine to measure the degree to which mice would continue to drink despite this aversive stimulus. We recorded high-resolution video of the mice during head-fixed drinking, tracked body parts with machine vision tools, and analyzed body movements in relation to consumption. Female and male head-fixed mice exhibited heterogenous levels of aversion-resistant drinking. Additionally, non-consummatory behaviors, such as paw movement and snout movement, were related to the intensity of aversion-resistant drinking. These studies demonstrate that head-fixed mice exhibit aversion-resistant drinking and that non-consummatory behaviors can be used to assess perceived aversiveness in this paradigm. Furthermore, these studies lay the groundwork for future experiments that will utilize advanced electrophysiological techniques to record from large populations of neurons during aversion-resistant drinking to understand the neurocomputational processes that drive this clinically relevant behavior
DOI: 10.6084/m9.figshare.23546517.v2
title: Data and Analysis Code: Non-Consummatory Behavior Signals Predict Aversion-Resistant Alcohol Drinking in Head-Fixed Mice

description: This file contains behavioral data and analysis code for a study examining aversion-resistant drinking in head-fixed mice. <br> Abstract: A key facet of alcohol use disorder is continuing to drink alcohol despite negative consequences (so called "aversion-resistant drinking"). In this study, we sought to assess the degree to which head-fixed mice exhibit aversion-resistant drinking and to leverage behavioral analysis techniques available in head-fixture to relate non-consummatory behaviors to aversion-resistant drinking. We assessed aversion-resistant drinking in head-fixed female and male C57BL/6J mice. We adulterated 20% (v/v) alcohol with varying concentrations of the bitter tastant quinine to measure the degree to which animals would continue to drink despite this aversive stimulus. We recorded high-resolution video of the mice during head-fixed drinking, tracked body parts with machine vision tools, and analyzed body movements in relation to consumption. Female and male head-fixed mice exhibited heterogenous levels of aversion-resistant drinking. Additionally, non-consummatory behaviors, such as paw movement and snout movement, were related to the intensity of aversion-resistant drinking. These studies demonstrate that head-fixed mice exhibit aversion-resistant drinking and that non-consummatory behaviors can be used to assess perceived aversiveness in this paradigm. Furthermore, these studies lay the groundwork for future experiments that will utilize advanced electrophysiological techniques to record from large populations of neurons during aversion-resistant drinking to understand the neurocomputational processes that drive this clinically relevant behavior
DOI: 10.18120/4fy9-fe84
title: ICMS evoked activity in motor cortex
DOI: 10.5066/p9sh5ynv
title: Kaguya Terrain Camera Uncontrolled Image Data
DOI: 10.6084/m9.figshare.24251233
title: IOP vs Fitness - Data- Final.sav

description: This is a large database of anonymized patients from a research article in Ophthalmology
DOI: 10.5519/qd.2dg9myoq
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1119 records)
DOI: 10.21223/quzwed/jd0mm9
title: 01_Field_TMIN200412_LAVICT_LTVR.txt

description: :unav
DOI: 10.21223/quzwed/i5dc3i
title: 04_Datadictionary.txt

description: :unav
DOI: 10.21223/quzwed/txb3m6
title: 03_Material_list.txt

description: :unav
DOI: 10.21223/quzwed/ldj2vf
title: 02_Field_TVIT200412_LAVICT_LTVR.txt

description: :unav
DOI: 10.21223/quzwed/8h59eq
title: TVIT200412_LAVICT_LTVR.xls

description: :unav
DOI: 10.21223/quzwed/l81r2d
title: TMIN200412_LAVICT_LTVR.xls

description: :unav
DOI: 10.21223/quzwed
title: Dataset for: Assessment of Micronutrient Concentrations in Potato Clones from the LTVR Population in Huancayo - Junin, 2004

description: An analysis of micronutrient concentrations, encompassing minerals and vitamin C, was carried out on 47 potatoes from the LTVR Population in Huancayo, Junin, in 2004, using a completely randomized design (CRD) with two replications.
DOI: 10.5281/zenodo.8408943
title: CMS High Granularity Calorimeter Trigger Cell Simulated Dataset (Part 2)

description: See https://doi.org/10.5281/zenodo.8338607 for a full description of this dataset.
DOI: 10.5281/zenodo.8408942
title: CMS High Granularity Calorimeter Trigger Cell Simulated Dataset (Part 2)

description: See https://doi.org/10.5281/zenodo.8338607 for a full description of this dataset.
DOI: 10.57745/jq95ez
title: BDD Rapsodyn 2016.17-DataServe2021.xlsx

description: Le fichier comprend les données de l'expérimentation CANOPY-A Grignon 2016-2017 obtenues par l'UMR AGRONOMIE (onglet BDD) et un descriptif des variables mesurée et du dispositif expérimental (onglet Glossaire) The file includes the data of the CANOPY-A Grignon 2016-2017 experiment obtained by the UMR AGRONOMIE (BDD tab) and a description of the measured variables and the experimental setup (Glossary tab)
DOI: 10.57745/ez3wdb
title: BDD Rapsodyn 2013.2014-DataServe2021.xlsx

description: Le fichier comprend les données de l'expérimentation CANOPY-A Grignon 2013-2014 obrtenues par AGRONOMIE (onglet BDD) et un descriptif des variables mesurée et du dispositif expérimental (onglet Glossaire)
DOI: 10.5281/zenodo.8091821
title: Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems"

description: Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems"