cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4121/87cb9614-be70-40c5-b0f3-760d87f44ab1.v2
title: Acquiring Semantic Knowledge for User Model Updates via Human-Agent Alignment Dialogues: Transcriptions

description: The data is the transcriptions for the focus groups underlying the paper "Acquiring Semantic Knowledge for User Model Updates via Human-Agent Alignment Dialogues: An exploratory focus group study" by Pei-Yu Chen, Myrthe Tielman, Dirk Heylen, Catholijn Jonker, and Birna van Riemsdijk. The goal of this paper is to explore what potential users like or dislike about certain aspects of the dialogues and identify dimensions that are important for designing good alignment dialogues.<br><strong>Study</strong>We performed an exploratory focus group user study, in which we showed participants six scenarios with different variants of how we envision such alignment dialogues might look like. The scenarios and dialogues are in textual form. After they finished reading, we asked them to discuss and compare the dialogues, and then we moved on to the next scenario and discussion. The process continued until all six scenarios were discussed. For the structure of the discussion, we prepared the following questions to guide the participants:Which version of the dialogue do you prefer, or which part of which dialogue do you prefer? Why?Is there a certain part of the dialogue that you particularly like/not like? Why? How would you want to do it instead?Which dialogue is more ‘intelligent’, as in has more capability in providing support?Do you feel one dialogue is more supportive than the other?After which dialogue do you think the agent would be more ‘on the same page’ as you?<br><strong>Data & analysis</strong>We transcribed the focus group sessions and analyzed the transcriptions using inductive thematic analysis with the addition of triangulation with literature.
DOI: 10.5281/zenodo.10551237
title: List of business and system roles of Northern Cluster in OneNet project

description: The list of roles includes in CSV format the names and definitions of business roles and system roles referred to in the use cases of OneNet Northern cluster. The Harmonised Electricity Market Role Model (HEMRM) defines many of the roles used. However, if not existing in HEMRM, use cases provide their own definitions, sometimes relying on the ones proposed by BRIDGE Initiative.

The context of usage of the roles in business use cases and system use cases can be found here: https://onenet-project.eu/wp-content/uploads/2023/10/D7.2_OneNet_v1.0.pdf, https://onenet-project.eu/wp-content/uploads/2023/05/OneNet_D7.3_v1.0-1.pdf,https://onenet-project.eu/wp-content/uploads/2022/12/OneNet_D7.4_v.1.0.pdf

 The explanation of HEMRM can be found here: https://mwgstorage1.blob.core.windows.net/public/Ebix/Harmonised_Role_Model_2023-01.pdf

 The explanation of additions to HEMRM as proposed by BRIDGE Initiative: https://energy.ec.europa.eu/system/files/2021-06/bridge_wg_regulation_eu_bridge_hemrm_report_2020-2021_0.pdf
DOI: 10.5281/zenodo.10551238
title: List of business and system roles of Northern Cluster in OneNet project

description: The list of roles includes in CSV format the names and definitions of business roles and system roles referred to in the use cases of OneNet Northern cluster. The Harmonised Electricity Market Role Model (HEMRM) defines many of the roles used. However, if not existing in HEMRM, use cases provide their own definitions, sometimes relying on the ones proposed by BRIDGE Initiative.

The context of usage of the roles in business use cases and system use cases can be found here: https://onenet-project.eu/wp-content/uploads/2023/10/D7.2_OneNet_v1.0.pdf, https://onenet-project.eu/wp-content/uploads/2023/05/OneNet_D7.3_v1.0-1.pdf,https://onenet-project.eu/wp-content/uploads/2022/12/OneNet_D7.4_v.1.0.pdf

 The explanation of HEMRM can be found here: https://mwgstorage1.blob.core.windows.net/public/Ebix/Harmonised_Role_Model_2023-01.pdf

 The explanation of additions to HEMRM as proposed by BRIDGE Initiative: https://energy.ec.europa.eu/system/files/2021-06/bridge_wg_regulation_eu_bridge_hemrm_report_2020-2021_0.pdf
DOI: 10.6084/m9.figshare.25047041
title: Declining potential nectar production of the herb layer in temperate forests under global change - Derived data from forestREplot database

description: Dataset derived from the forestREplot database on potential nectar production of the forest herb layer.<br>NP = Nectar production<br>OS = Overstory cover<br>SCA = Shade-casting ability<br>LQ = Litter quality<br>MAP10 = Mean annual precipitation<br>MAT10 = Mean annual temperature<br>N_cum = Cumulative nitrogen deposition
DOI: 10.5522/04/24932499
title: SAR-RARP50 test set

description: Test dataset released as a part of the EndoVis 2022 SAR-RARP50 challenge<br><br>Details on the dataset format are included in the provided README file<br><br>To learn more about the dataset construction and the EndoVis 2022 SAR-RARP50 challenge, please read the challenge's Arxiv paper.
DOI: 10.5522/04/24932499.v1
title: SAR-RARP50 test set

description: Test dataset released as a part of the EndoVis 2022 SAR-RARP50 challenge<br><br>Details on the dataset format are included in the provided README file<br><br>To learn more about the dataset construction and the EndoVis 2022 SAR-RARP50 challenge, please read the challenge's Arxiv paper.
DOI: 10.6084/m9.figshare.25047020
title: vcf_data

description: To examine population genomic variation and the demographic history of <i>Thrips palmi</i>, we conducted whole-genome resequencing for 249 individuals from 17 geographical populations sampled across its natural distribution of China and Japan, as well as a heat-stress selected population and its control population in the laboratory.
DOI: 10.5522/04/24932529
title: SAR-RARP50 train set

description: Training dataset released as a part of the EndoVis 2022 SAR-RARP50 challenge<br><br>Details on the dataset format are included in the provided README file<br><br>To learn more about the dataset construction and the EndoVis 2022 SAR-RARP50 challenge, please read the challenge's Arxiv paper.
DOI: 10.5522/04/24932529.v1
title: SAR-RARP50 train set

description: Training dataset released as a part of the EndoVis 2022 SAR-RARP50 challenge<br><br>Details on the dataset format are included in the provided README file<br><br>To learn more about the dataset construction and the EndoVis 2022 SAR-RARP50 challenge, please read the challenge's Arxiv paper.
DOI: 10.21227/ez1b-8c02
title: Smart Home Intrusion Detection Dataset

description: Micorocntroller based IoT Devices of smart homes has limited access to network performance parameters. To access the network parameters, we utilized lwIP library and socket library for accessing real time network features. In this work, the network parameters (connection activity and statistical activity) accessed on smart thermostats are as follows: Timestamp, Source IP, Source Port, Destination IP, Destination Port, proto, service, duration, source bytes, destination bytes, source packets, source IP bytes, destination packets, destination IP bytes. Apart from network parameters, smart thermostat is measuring temperature, humidity and control signal for air conditioner (i.e., ON/OFF) sent from webpage. We have collected dataset of normal, MITM and DoS attack on smart thermostat. This dataset is collected from ESP32 based smart thermostat.In future, dataset for other devices of smart homes will be included in this dataset.
DOI: 10.17864/1947.000525
title: Data from perennial flower margins reduce orchard fruit damage by rosy apple aphid, Dysaphis plantaginea (Homoptera: Aphididae).

description: Data were collected from ten conventional commercial apple orchards in Kent, UK. They include the number of Rosy aphid infested shoots, the number of apples, and the number of Rosy aphid damaged fruits on 45 trees per orchard which were systematically searched (2021 and 2022). They also include the number of bait aphids remaining on sentinel bait cards in the same orchards on a subset of those trees (2021). This also includes the abundance of natural enemies and other taxa of interest found during the surveys. These data are all in tabular form (excel files).
DOI: 10.17031/65ae3f18ab6af
title: 1961 Marine Biological Association of the UK (MBA) European Continental Slope RV Sarsia Cruise No. G June
title: 1961 MBA European Continental Slope RV Sarsia Cruise No. G June

description: Records from the RV Sarsia Cruise No. G in June 1960 to the European Continental Slope. Samples were collected by dredge of unspecified type and identified by MBA staff. Records supplied by Dr. Eve Southward and collated by DASSH as part of the 'Dredging the Depths' project.
DOI: 10.5281/zenodo.7096349
title: The Tsez Annotated Corpus Project

description: Cite the source of the dataset as:




Abdulaev, A.K. & I. K. Abdullaev. 2010. Cezyas folklor/Dido (Tsez) folklore/Didojskij (cezskij) fol´klor. Leipzig–Makhachkala: "Lotos".
DOI: 10.5281/zenodo.7096350
title: The Tsez Annotated Corpus Project

description: Cite the source of the dataset as: Abdulaev, A.K. & I. K. Abdullaev. 2010. Cezyas folklor/Dido (Tsez) folklore/Didojskij (cezskij) fol´klor. Leipzig–Makhachkala: "Lotos".
DOI: 10.6084/m9.figshare.25047200
title: Supplementary Material for: Angiopoietin as A Novel Prognostic Marker in Kidney Disease

description: Renal injury is among the leading causes of morbidity and mortality, however, there are no reliable indicators for determining the likelihood of developing CKD, CKD progression or AKI events. Vascular growth factors called angiopoietins have a role in endothelial function, vascular remodeling, tissue stabilization and inflammation, and have been implicated as prognostic and predictive markers in AKI. Although the exact mechanism of the relationship between kidney injury and angiopoietins is unknown, this review demonstrates that AKI patients have higher angiopoietin-2 levels and that higher angiopoietin-1 to angiopoietin-2 ratio may potentially be linked with a reduced risk of the chronic kidney disease progression. This review therefore emphasizes the importance of angiopoietin-2 and proposes that it could be an important predictor of AKI in clinical settings. There is a need for further large scale randomized clinical trials in order to have a better understanding of the significance of angiopoietin-2 and for the determination of its potential clinical implications.
DOI: 10.5281/zenodo.10555859
title: The Tsez Annotated Corpus Project

description: Cite the source of the dataset as:




Abdulaev, A.K. & I. K. Abdullaev. 2010. Cezyas folklor/Dido (Tsez) folklore/Didojskij (cezskij) fol´klor. Leipzig–Makhachkala: "Lotos".
DOI: 10.6084/m9.figshare.25047200.v1
title: Supplementary Material for: Angiopoietin as A Novel Prognostic Marker in Kidney Disease

description: Renal injury is among the leading causes of morbidity and mortality, however, there are no reliable indicators for determining the likelihood of developing CKD, CKD progression or AKI events. Vascular growth factors called angiopoietins have a role in endothelial function, vascular remodeling, tissue stabilization and inflammation, and have been implicated as prognostic and predictive markers in AKI. Although the exact mechanism of the relationship between kidney injury and angiopoietins is unknown, this review demonstrates that AKI patients have higher angiopoietin-2 levels and that higher angiopoietin-1 to angiopoietin-2 ratio may potentially be linked with a reduced risk of the chronic kidney disease progression. This review therefore emphasizes the importance of angiopoietin-2 and proposes that it could be an important predictor of AKI in clinical settings. There is a need for further large scale randomized clinical trials in order to have a better understanding of the significance of angiopoietin-2 and for the determination of its potential clinical implications.
DOI: 10.6084/m9.figshare.25047209
title: Supplementary Material for: Angiopoietin as A Novel Prognostic Marker in Kidney Disease

description: Renal injury is among the leading causes of morbidity and mortality, however, there are no reliable indicators for determining the likelihood of developing CKD, CKD progression or AKI events. Vascular growth factors called angiopoietins have a role in endothelial function, vascular remodeling, tissue stabilization and inflammation, and have been implicated as prognostic and predictive markers in AKI. Although the exact mechanism of the relationship between kidney injury and angiopoietins is unknown, this review demonstrates that AKI patients have higher angiopoietin-2 levels and that higher angiopoietin-1 to angiopoietin-2 ratio may potentially be linked with a reduced risk of the chronic kidney disease progression. This review therefore emphasizes the importance of angiopoietin-2 and proposes that it could be an important predictor of AKI in clinical settings. There is a need for further large scale randomized clinical trials in order to have a better understanding of the significance of angiopoietin-2 and for the determination of its potential clinical implications.
DOI: 10.6084/m9.figshare.25047209.v1
title: Supplementary Material for: Angiopoietin as A Novel Prognostic Marker in Kidney Disease

description: Renal injury is among the leading causes of morbidity and mortality, however, there are no reliable indicators for determining the likelihood of developing CKD, CKD progression or AKI events. Vascular growth factors called angiopoietins have a role in endothelial function, vascular remodeling, tissue stabilization and inflammation, and have been implicated as prognostic and predictive markers in AKI. Although the exact mechanism of the relationship between kidney injury and angiopoietins is unknown, this review demonstrates that AKI patients have higher angiopoietin-2 levels and that higher angiopoietin-1 to angiopoietin-2 ratio may potentially be linked with a reduced risk of the chronic kidney disease progression. This review therefore emphasizes the importance of angiopoietin-2 and proposes that it could be an important predictor of AKI in clinical settings. There is a need for further large scale randomized clinical trials in order to have a better understanding of the significance of angiopoietin-2 and for the determination of its potential clinical implications.
DOI: 10.5281/zenodo.10555763
title: Supplementary files / Ensemble modelling employing models with different complexity levels

description: Dear members of the scientific community,

This folder contains all data and scripts adopted to prepare the manuscript entitled "Ensemble modeling employing models with different complexity levels to reconstruct the mid-Holocene surface temperature". This paper was submitted to the "Geoscientific Model Development (GMD)" journal in January 2024. 

Please note that these data must not be reused in other articles while the current manuscript is under review in the GMD journal. 

Sincerely,

Emerson D. Oliveira
DOI: 10.5281/zenodo.10555764
title: Supplementary files / Ensemble modelling employing models with different complexity levels

description: Dear members of the scientific community,

This folder contains all data and scripts adopted to prepare the manuscript entitled "Ensemble modeling employing models with different complexity levels to reconstruct the mid-Holocene surface temperature". This paper was submitted to the "Geoscientific Model Development (GMD)" journal in January 2024. 

Please note that these data must not be reused in other articles while the current manuscript is under review in the GMD journal. 

Sincerely,

Emerson D. Oliveira
DOI: 10.5519/qd.pikduv0k
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (61 records)
DOI: 10.21227/va5z-dm34
title: 3-D B-field Modelling Method of Magnetic Viscosity Effect in Time-Domain Electromagnetic Surveys

description: A direct three-dimensional (3-D) modeling of B-field in TDEM is proposed in the paper. We first introduce the forward modeling method of static magnetic field for the calculation of initial value of B-field. Then, we achieve the iterative calculation of B-field of magnetic media during the transient electromagnetic (TEM) stage by substituting the Cole–Cole susceptibility model into the B-field diffusion equation of double-curl induced magnetization intensity. The validity of this method is verified using several analytical solutions. A 3-D multi-magnetic anomaly model is established, and the characteristics of B-field responses are observed in three dimensions. This method can realize the 3-D modeling of the B-field of the MV effect in TDEM, which is helpful to accurately understand the characteristics of the B-field attenuation curves and can provide a basis for the direct inversion interpretation of B-field data.
DOI: 10.23728/b2share.d79b822743184facb08aafb8c0b40d4d
title: Gesäuse-Johnsbachtal - Austria, Groundwater

description: Groundwater data of the Etzbach spring in the Gesäuse-Johnsbachtal site
DOI: 10.5281/zenodo.10301912
title: A large and diverse brain organoid dataset of 1,400 cross-laboratory images of 64 trackable brain organoids from four different clones

description: This dataset is presented in the paper A large and diverse brain organoid dataset of 1,400 cross-laboratory images of 64 trackable brain organoids from four different clones

 

This dataset encompasses two sources of data:



A comma-separated values ('CSV') file. This file serves as a key to our dataset with one image per row. Each image is represented by its image identifier ('img_id') with the format [org_id]_[clone]_d[imaging_day]_[imaging_lab]. For each image, the CSV file also specifies the organoid size for convenience. Alternatively, the organoid size can be calculated using the ground truth organoid segmentation (org_segGT). 

For each row of the CSV file, we provide the image and org_segGT. For Lab A, the images are in JPEG format. For lab B, the images are in TIF format. Org_segGT is a manually created binary 2D NumPy array with the same size as the image (1024 x 768 for lab A, 1388 x 1040 for lab B). A value of 1 in org_segGT at position (x, y) means that the same position (x, y) in the corresponding image is covered by the organoid. The image file and the org_segGT file have the following format: [img_id].[jpg|tif] and [img_id].npy. For day 12, organoids were imaged before and after embedding from 96-well plates in 12-well plates, allowing the investigation of well-specific optical properties.


For segmentation and growth monitoring using this dataset, please see https://github.com/deiluca/robust_monitoring_organoid_growth.
DOI: 10.5281/zenodo.7836863
title: A large and diverse brain organoid dataset of 1,400 cross-laboratory images of 64 trackable brain organoids from four different clones

description: This dataset is presented in the paper A large and diverse brain organoid dataset of 1,400 cross-laboratory images of 64 trackable brain organoids from four different clones

 

This dataset encompasses two sources of data:



A comma-separated values ('CSV') file. This file serves as a key to our dataset with one image per row. Each image is represented by its image identifier ('img_id') with the format [org_id]_[clone]_d[imaging_day]_[imaging_lab]. For each image, the CSV file also specifies the organoid size for convenience. Alternatively, the organoid size can be calculated using the ground truth organoid segmentation (org_segGT). 

For each row of the CSV file, we provide the image and org_segGT. For Lab A, the images are in JPEG format. For lab B, the images are in TIF format. Org_segGT is a manually created binary 2D NumPy array with the same size as the image (1024 x 768 for lab A, 1388 x 1040 for lab B). A value of 1 in org_segGT at position (x, y) means that the same position (x, y) in the corresponding image is covered by the organoid. The image file and the org_segGT file have the following format: [img_id].[jpg|tif] and [img_id].npy. For day 12, organoids were imaged before and after embedding from 96-well plates in 12-well plates, allowing the investigation of well-specific optical properties.


For segmentation and growth monitoring using this dataset, please see https://github.com/deiluca/robust_monitoring_organoid_growth.
DOI: 10.5281/zenodo.7836864
title: A large brain organoid dataset reveals extensive improvement potential of state-of-the-art analysis pipelines

description: This dataset is presented in the paper <em>A large brain organoid dataset reveals extensive improvement potential of state-of-the-art analysis pipelines.</em> This dataset encompasses two sources of data: A comma-separated values (‘CSV’) file. This file serves as a key to our dataset with one image per row. Each image is represented by its image identifier (‘img_id’) with the format [img_nr]_d[imaging_day]_[clone]. For each image, the CSV also specifies the organoid size for convenience. Alternatively, the organoid size can be calculated using the ground truth organoid segmentation (org_seg<sub>GT</sub>). For each row of the CSV, we provide the image (.jpg file) and org_seg<sub>GT</sub> (.npy file). org_seg<sub>GT</sub> is a manually created binary 2D NumPy array with the same size as the image (1024 x 768). A value of 1 in org_seg<sub>GT</sub> at position (x, y) means that the same position (x, y) in the corresponding image is covered by the organoid. The image file and the org_seg<sub>GT</sub> file have the following format: [img_id].jpg and [img_id]_org-mask.npy. For segmentation and growth monitoring using this dataset, please see https://github.com/deiluca/robust_monitoring_organoid_growth.
DOI: 10.5281/zenodo.10518279
title: Comparative efficacy of non-pharmacological interventions for adults with obstructive sleep apnea: a systematic review and network meta-analysis

description: Datasets for all analyses performed.
DOI: 10.5281/zenodo.10555892
title: Comparative efficacy of non-pharmacological interventions for adults with obstructive sleep apnea: a systematic review and network meta-analysis

description: -Datasets for all analyses performed.-Appendix 4. List of studies identified from the literature search, with their inclusion/exclusion status, and exclusion reasons.
DOI: 10.23728/b2share.856fc9b03032436ab0288a0cefcbb0af
title: Gesäuse-Johnsbachtal - Austria, Forest Disturbances

description: Forest disturbance data of the Gesäuse-Johnsbachtal site
DOI: 10.23728/b2share.619936ec706d447f9dd10c791dae6abf
title: Gesäuse-Johnsbachtal - Austria, Soil type classification

description: Soil type classification of the Gesäuse-Johnsbachtal site.
DOI: 10.34740/kaggle/dsv/7463567
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.23728/b2share.afa453709a5f4094beab222be64c6504
title: Gesäuse-Johnsbachtal - Austria, Ground vegetation

description: Ground vegetation of the Gesäuse-Johsnbachtal site.
DOI: 10.23728/b2share.3571a1551df44152853c97a42a172d2e
title: Gesäuse-Johnsbachtal - Austria, Nomenclature of territorial units for statistics

description: Nomenclature of territorial units for statistics of the Gesäuse-Johnsbachtal site
DOI: 10.34740/kaggle/ds/4344096
title: 🍔 Sri Lanka McDonald's FB Reviews Data
DOI: 10.23728/b2share.e69bed0dbfcd40bfa53650f99730620f
title: Gesäuse-Johnsbachtal - Austria, Reference documentation

description: Reference documentation of the Gesäuse-Johnsbachtal site