cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10361330
title: Dataset for a Norwegian medium and low voltage power distribution system with industrial loads

description: This dataset describes a Norwegian industrial medium voltage (MV) and low voltage (LV) distribution grid with load time series. The raw dataset was collected in collaboration with the Norwegian distribution grid company (DSO) Norgesnett as part of a pilot project in the Norwegian research centre FME CINELDI, and was anonymized and simplified into a secondary dataset.


The dataset consists of three parts:



	
Grid data: The grid data comprises two radials in the distribution grid, collected from the network information system of the DSO, including topology, electrical parameters and load points.
	
Load data: The load dataset comprises over three years of measurements of hourly load demand from 45 grid customers in the time period 2019-03-01 to 2022-03-16, collected from smart meters installed with the customers
	
Temperature data from nearby measuring station, Licence (CC BY 4.0), Source: Meteorologisk institutt (MET)



The data was anonymized and simplified. The dataset can be used for stochastic load modelling, analyzing the grid’s need for flexibility and power flow analyses for grid planning purposes.


 
description: This work is funded by CINELDI - Centre for Intelligent Electricity Distribution, an 8-year Research Centre under the FME-scheme (Centre for Environment-friendly Energy Research, 257626/E20). The authors gratefully acknowledge the financial support from the Research Council of Norway and the CINELDI partners.
DOI: 10.5281/zenodo.7123536
title: Dataset for a Norwegian medium and low voltage power distribution system with industrial loads

description: This dataset describes a Norwegian industrial medium voltage (MV) and low voltage (LV) distribution grid with load time series. The raw dataset was collected in collaboration with the Norwegian distribution grid company (DSO) Norgesnett as part of a pilot project in the Norwegian research centre FME CINELDI, and was anonymized and simplified into a secondary dataset.


The dataset consists of three parts:



	
Grid data: The grid data comprises two radials in the distribution grid, collected from the network information system of the DSO, including topology, electrical parameters and load points.
	
Load data: The load dataset comprises over three years of measurements of hourly load demand from 45 grid customers in the time period 2019-03-01 to 2022-03-16, collected from smart meters installed with the customers
	
Temperature data from nearby measuring station, Licence (CC BY 4.0), Source: Meteorologisk institutt (MET)



The data was anonymized and simplified. The dataset can be used for stochastic load modelling, analyzing the grid’s need for flexibility and power flow analyses for grid planning purposes.


 
description: This work is funded by CINELDI - Centre for Intelligent Electricity Distribution, an 8-year Research Centre under the FME-scheme (Centre for Environment-friendly Energy Research, 257626/E20). The authors gratefully acknowledge the financial support from the Research Council of Norway and the CINELDI partners.
DOI: 10.5281/zenodo.7763891
title: Dataset for a Norwegian medium and low voltage power distribution system with industrial loads

description: This dataset describes a Norwegian industrial medium voltage (MV) and low voltage (LV) distribution grid with load time series. The raw dataset was collected in collaboration with the Norwegian distribution grid company (DSO) Norgesnett as part of a pilot project in the Norwegian research centre FME CINELDI, and was anonymized and simplified into a secondary dataset. The dataset consists of three parts: Grid data: The grid data comprises two radials in the distribution grid, collected from the network information system of the DSO, including topology, electrical parameters and load points. Load data: The load dataset comprises over three years of measurements of hourly load demand from 45 grid customers in the time period 2019-03-01 to 2022-03-16, collected from smart meters installed with the customers Temperature data from nearby measuring station, Licence (CC BY 4.0), Source: Meteorologisk institutt (MET) The data was anonymized and simplified. The dataset can be used for stochastic load modelling, analyzing the grid’s need for flexibility and power flow analyses for grid planning purposes.
description: This work is funded by CINELDI - Centre for Intelligent Electricity Distribution, an 8-year Research Centre under the FME-scheme (Centre for Environment-friendly Energy Research, 257626/E20). The authors gratefully acknowledge the financial support from the Research Council of Norway and the CINELDI partners.
DOI: 10.5281/zenodo.10361273
title: Mozambique geographical coordinates

description: This table contains geographic coordinates (DD and DMS) of archaeological sites of Mozambique. Compiling all archaeological site coordinates of a country in a single table is a very ambitious challenging task. Different projects have been carried out in different parts of the country and a lot of data is still being processed. But here I present the archaeological sites known since the colonial period. Future works of this nature will be able to improve this content.
DOI: 10.5281/zenodo.10361272
title: Mozambique geographical coordinates

description: This table contains geographic coordinates (DD and DMS) of archaeological sites of Mozambique. Compiling all archaeological site coordinates of a country in a single table is a very ambitious challenging task. Different projects have been carried out in different parts of the country and a lot of data is still being processed. But here I present the archaeological sites known since the colonial period. Future works of this nature will be able to improve this content.
DOI: 10.6084/m9.figshare.24130356
title: <b>Prediction of the recurrence of differentiated thyroid carcinoma by post-operative neutrophil and platelet count</b>

description: Objective: The present study aimed to combine pre- and post-operative peripheral blood laboratory indicators with clinicopathological characteristics to predict differentiated thyroid carcinoma (DTC) recurrence. Study Design: Retrospective case-control analysis.Methods: From June 2013 to December 2020, 488 patients with DTC received treatment at The Second Affiliated Hospital of Guangxi University of Science and Technology. Pre- and post-operative inflammatory marker levels and clinicopathological features were obtained from the medical record system. Kaplan–Meier survival analysis and proportional hazards model were used to assess the DTC recurrence risk. The nomogram was developed to estimate the predictive power of the indicators by the C-index, area under the curve (AUC) and calibration curves. Results: 36 (7.38%) of 488 DTC patients suffered recurrence. Lymph node metastases (LNMs) (hazard ratio [HR]=12.07, 95%CI: 1.82–79.97, P=0.010), tumor diameter ≥2 cm (HR=3.78, 95%CI:1.55-9.25, P=0.004), post-operative neutrophil count (post-NEU)&gt;4.78 109/L (HR=0.29, 95%CI:0.11-0.73, P=0.008), and post-operative platelets count (post-PLT)&gt;316 109/L(HR=2.82, 95%CI:1.37-5.81, P=0.005) were independent risk factors for DTC recurrence. The median AUC values for predicting the recurrence of DTC at 2 years and 3 years were 0.86 (range: 0.75-0.97) and 0.84 (0.72-0.95), respectively. Patients with higher risk in nomogram had lower Recurrence-free survival (RFS) rate at both 2 years and 3 years (all P&lt;0.001). Conclusion: In the present study, DTC patients with LNMs, tumor diameter ≥2 cm, higher post-NEU level, and higher post-PLT level exhibited an increased risk of DTC recurrence. The prediction model incorporating these characteristics robust thereby offering valuable insights into the prognostication of DTC patients in practical healthcare applications.
DOI: 10.6084/m9.figshare.24130356.v2
title: <b>Prediction of the recurrence of differentiated thyroid carcinoma by post-operative neutrophil and platelet count</b>

description: Objective.The present study aimed to combine pre- and post-operative peripheral blood laboratory indicators with clinicopathological characteristics to predict differentiated thyroid carcinoma (DTC) recurrence. Study Design. Retrospective case-control analysis.Setting. The Second Affiliated Hospital of Guangxi University of Science and Technology.Methods. From June 2013 to December 2020, 488 patients with DTC were included. DTC recurrence was diagnosed by the experienced doctor. Pre- and post-operative inflammatory marker levels and clinicopathological features were obtained from the medical record system. Kaplan–Meier survival analysis and proportional hazards model were used to assess the DTC recurrence risk. The nomogram was developed to estimate the predictive power of the indicators by the C-index, area under the curve (AUC) and calibration curves. Results. 36 (7.38%) of 488 DTC patients suffered recurrence. Lymph node metastases (LNMs) (hazard ratio [HR]=12.07, 95%CI: 1.82–79.97, P=0.010), tumor diameter ≥2 cm (HR=3.78, 95%CI:1.55-9.25, P=0.004), post-operative neutrophil count (post-NEU)&gt;4.78 109/L (HR=0.29, 95%CI:0.11-0.73, P=0.008), and post-operative platelets count (post-PLT)&gt;316 109/L(HR=2.82, 95%CI:1.37-5.81, P=0.005) were independent risk factors for DTC recurrence. The median AUC values for predicting the recurrence of DTC at 2 years and 3 years were 0.86 (range: 0.75-0.97) and 0.84 (0.72-0.95), respectively. Patients with higher risk in nomogram had lower Recurrence-free survival (RFS) rate at both 2 years and 3 years (all P&lt;0.001). Conclusion. In the present study, DTC patients with LNMs, tumor diameter ≥2 cm, higher post-NEU level, and higher post-PLT level exhibited an increased risk of DTC recurrence. The prediction model incorporating these characteristics robust thereby offering valuable insights into the prognostication of DTC patients in practical healthcare applications.
DOI: 10.5281/zenodo.10077660
title: HORIZONT SPOT; dataset The impact of anti-COVID measures on accommodation performance (Open Research Europe)

description: Part of outputs of the project: HORIZONT SPOT; dataset for publication: The impact of anti-COVID measures on accommodation performance (in Open Research Europe); tool: original questionnaire and translated questionnaire into English.
DOI: 10.5281/zenodo.10246426
title: HORIZONT SPOT; dataset The impact of anti-COVID measures on accommodation performance (Open Research Europe)
title: survey_data_JMK_open_translated

description: Part of outputs of the project: HORIZONT SPOT; dataset for publication: The impact of anti-COVID measures on accommodation performance (in Open Research Europe); tool: original questionnaire and translated questionnaire into English.
DOI: 10.5281/zenodo.10361377
title: HORIZONT SPOT; dataset The impact of anti-COVID measures on accommodation performance (Open Research Europe)
title: survey_data

description: Part of outputs of the project: HORIZONT SPOT; dataset for publication: The impact of anti-COVID measures on accommodation performance (in Open Research Europe); tool: original questionnaire and translated questionnaire into English.
DOI: 10.5281/zenodo.8421228
title: HORIZONT SPOT; dataset The impact of anti-COVID measures on accommodation performance (Open Research Europe)
title: survey_data

description: Part of outputs of the project: HORIZONT SPOT; dataset for publication: The impact of anti-COVID measures on accommodation performance (in Open Research Europe); tool: original questionnaire and translated questionnaire into English.
DOI: 10.5281/zenodo.8421229
title: HORIZONT SPOT; dataset The impact of anti-COVID measures on accommodation performance (Open Research Europe)

description: Part of outputs of the project: HORIZONT SPOT; dataset for publication: The impact of anti-COVID measures on accommodation performance (in Open Research Europe); tool: original questionnaire and translated questionnaire into English.
DOI: 10.5281/zenodo.10137730
title: Deep learning to extract the meteorological by-catch of wildlife cameras: Supporting data, models and code

description: This repository contains the data, models and code to train and deploy deep learning models related to the paper "Deep learning to extract the meteorological by-catch of wildlife cameras" published in the journal Global Change Biology (https://doi.org/10.1111/gcb.17078).
DOI: 10.5281/zenodo.10137731
title: Deep learning to extract the meteorological by-catch of wildlife cameras: Supporting data, models and code

description: This repository contains the data, models and code to train and deploy deep learning models related to the paper "Deep learning to extract the meteorological by-catch of wildlife cameras" published in the journal Global Change Biology (https://doi.org/10.1111/gcb.17078).
DOI: 10.5281/zenodo.10361237
title: Data on mitochondrial respiratory function in skeletal muscle of adult male mice in response to 3-weeks heat stress
DOI: 10.5281/zenodo.10361238
title: Data on mitochondrial respiratory function in skeletal muscle of adult male mice in response to 3-weeks heat stress
DOI: 10.48677/cced2282-cfc5-42eb-9acb-b1c799522fcd
title: Serie ALS DSM Höhenraster 1m Stichtag 15.09.2019

description: Das Digitale Oberflächenmodell (DOM, engl.: DSM) beschreibt die Erdoberfläche samt allen darauf befindlichen Objekten in Form von Punktmengen, die in einem regelmäßigen Gitter angeordnet und in Lage und Höhe georeferenziert sind. Im Unterschied zum digitalen Geländemodell (DGM) wird somit die Vegetations- und Bebauungsoberfläche dargestellt.

Durch insgesamt 55 Kacheln wird das Gebiet Österreich abgedeckt.

Stichtag = Erstellungsdatum:
Die Daten sind zu diesem Tag der aktuellste Datenbestand des BEV.
Dies ist nicht ident mit dem Aufnahme- bzw. Vermessungsdatum.
Die Aktualität finden Sie unter "Downloads, Ansichten und Links" in der Aktualitätsübersicht.
DOI: 10.6084/m9.figshare.24257806
title: Modeling the Ocean-Sea ice-Lower Trophic Levels in the Ross Sea Ecosystem

description: Modeling the Ocean-Sea ice-Lower Trophic Levels in the Ross Sea Ecosystem
DOI: 10.6084/m9.figshare.24257806.v2
title: Modeling the Ocean-Sea ice-Lower Trophic Levels in the Ross Sea Ecosystem

description: Modeling the Ocean-Sea ice-Lower Trophic Levels in the Ross Sea Ecosystem
DOI: 10.6084/m9.figshare.24257806.v1
title: Development and evaluation of a regional high-resolution coupled ocean - sea ice - ecosystem model for the Ross Sea, Antarctic

description: Development and evaluation of a regional high-resolution coupled ocean - sea ice - ecosystem model for the Ross Sea, Antarctic
DOI: 10.48677/9a4e3e4f-2cd5-4f73-af51-384beb9331d0
title: Serie ALS DTM Höhenraster 1m Stichtag 15.09.2019

description: Das ALS DTM-Höhenraster gehört zur Produktgruppe "Digitales Geländehöhenmodell" (DGM). Das digitale Geländehöhenmodell (DGM) beschreibt die Erdoberfläche (natürlicher Boden, ohne Bewuchs) in Form von Punktmengen, die in einem regelmäßigen Gitter von 1m angeordnet und in Lage und Höhe in den europäischen Referenzsystemen georeferenziert sind. Das ALS DTM Höhenraster wurde mit Airborne Laserscanning Technologien aufgenommen. Das ALS DTM Höhenraster ist ein Kooperationsprodukt der österreichischen behördlichen Geodatenprovider des Bundes und der Länder.

Durch insgesamt 55 Kacheln wird das Gebiet Österreich abgedeckt.

Stichtag = Erstellungsdatum:
Die Daten sind zu diesem Tag der aktuellste Datenbestand des BEV.
Dies ist nicht ident mit dem Aufnahme- bzw. Vermessungsdatum.
Die Aktualität finden Sie unter "Downloads, Ansichten und Links" in der Aktualitätsübersicht.
DOI: 10.48677/cacf8665-e58c-46df-b6b0-8ea162ee62a6
title: Serie ALS DSM Höhenraster 1m Stichtag 15.09.2021

description: Das Digitale Oberflächenmodell (DOM, engl.: DSM) beschreibt die Erdoberfläche samt allen darauf befindlichen Objekten in Form von Punktmengen, die in einem regelmäßigen Gitter angeordnet und in Lage und Höhe georeferenziert sind. Im Unterschied zum digitalen Geländemodell (DGM) wird somit die Vegetations- und Bebauungsoberfläche dargestellt.

Durch insgesamt 55 Kacheln wird das Gebiet Österreich abgedeckt.

Stichtag = Erstellungsdatum:
Die Daten sind zu diesem Tag der aktuellste Datenbestand des BEV.
Dies ist nicht ident mit dem Aufnahme- bzw. Vermessungsdatum.
Die Aktualität finden Sie unter "Downloads, Ansichten und Links" in der Aktualitätsübersicht.
DOI: 10.48677/63fd20c5-cd34-4d00-829f-a1fd380f6b4b
title: Serie ALS DTM Höhenraster 1m Stichtag 15.09.2021

description: Das ALS DTM-Höhenraster gehört zur Produktgruppe "Digitales Geländehöhenmodell" (DGM). Das digitale Geländehöhenmodell (DGM) beschreibt die Erdoberfläche (natürlicher Boden, ohne Bewuchs) in Form von Punktmengen, die in einem regelmäßigen Gitter von 1m angeordnet und in Lage und Höhe in den europäischen Referenzsystemen georeferenziert sind. Das ALS DTM Höhenraster wurde mit Airborne Laserscanning Technologien aufgenommen. Das ALS DTM Höhenraster ist ein Kooperationsprodukt der österreichischen behördlichen Geodatenprovider des Bundes und der Länder.

Durch insgesamt 55 Kacheln wird das Gebiet Österreich abgedeckt.

Stichtag = Erstellungsdatum:
Die Daten sind zu diesem Tag der aktuellste Datenbestand des BEV.
Dies ist nicht ident mit dem Aufnahme- bzw. Vermessungsdatum.
Die Aktualität finden Sie unter "Downloads, Ansichten und Links" in der Aktualitätsübersicht.
DOI: 10.48677/3c5d8b81-3ee1-4f2c-8f0a-b97375b52b7b
title: Serie ALS DSM Höhenraster 1m Stichtag 15.09.2022

description: Das Digitale Oberflächenmodell (DOM, engl.: DSM) beschreibt die Erdoberfläche samt allen darauf befindlichen Objekten in Form von Punktmengen, die in einem regelmäßigen Gitter angeordnet und in Lage und Höhe georeferenziert sind. Im Unterschied zum digitalen Geländemodell (DGM) wird somit die Vegetations- und Bebauungsoberfläche dargestellt.

Durch insgesamt 55 Kacheln wird das Gebiet Österreich abgedeckt.

Stichtag = Erstellungsdatum:
Die Daten sind zu diesem Tag der aktuellste Datenbestand des BEV.
Dies ist nicht ident mit dem Aufnahme- bzw. Vermessungsdatum.
Die Aktualität finden Sie unter "Downloads, Ansichten und Links" in der Aktualitätsübersicht.
DOI: 10.48677/eae5f98d-d605-4783-8292-8b913d163cac
title: Serie ALS DTM Höhenraster 1m Stichtag 15.09.2022

description: Das ALS DTM-Höhenraster gehört zur Produktgruppe "Digitales Geländehöhenmodell" (DGM). Das digitale Geländehöhenmodell (DGM) beschreibt die Erdoberfläche (natürlicher Boden, ohne Bewuchs) in Form von Punktmengen, die in einem regelmäßigen Gitter von 1m angeordnet und in Lage und Höhe in den europäischen Referenzsystemen georeferenziert sind. Das ALS DTM Höhenraster wurde mit Airborne Laserscanning Technologien aufgenommen. Das ALS DTM Höhenraster ist ein Kooperationsprodukt der österreichischen behördlichen Geodatenprovider des Bundes und der Länder.

Durch insgesamt 55 Kacheln wird das Gebiet Österreich abgedeckt.

Stichtag = Erstellungsdatum:
Die Daten sind zu diesem Tag der aktuellste Datenbestand des BEV.
Dies ist nicht ident mit dem Aufnahme- bzw. Vermessungsdatum.
Die Aktualität finden Sie unter "Downloads, Ansichten und Links" in der Aktualitätsübersicht.
DOI: 10.6084/m9.figshare.24792828
title: transition1x splits

description: .db versions of the train/test/val splits as described by https://gitlab.com/matschreiner/Transition1x.For Fall 2023 CS224W Final Project
DOI: 10.6084/m9.figshare.19614657
title: Transition1x

description: <b>Transition1x - a dataset for building generalizable reactive machine learning potentials</b>https://www.nature.com/articles/s41597-022-01870-w<br>This dataset is constructed by running NEB on 10.000 reactions with H, C, N and O using the wb97x functional and 6-31G(d) basis set. This resulted in DFT calculations for 9.6 million molecular configurations on and around minimal energy paths on the potential energy surface. The data is intended for training ML models to work in transition state regions of chemical space.<br>Dataloaders and example scripts are availble in https://gitlab.com/matschreiner/T1x<br>The authors acknowledge support from the Novo Nordisk Foundation (SURE, NNF19OC0057822) and the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 957189 (BIG-MAP) and No. 957213 (BATTERY2030PLUS). Ole Winther also receives support from Novo Nordisk Foundation through the Center for Basic Machine Learning Research in Life Science (NNF20OC0062606) and the Pioneer Centre for AI, DNRF grant number P1
DOI: 10.18112/openneuro.ds004873.v1.0.1
title: Two distinct modes of hemodynamic responses in the human brain
DOI: 10.6084/m9.figshare.24793236
title: Supplementary Material for: Current guidelines on fat intake in pregnant and lactating women, infants, children and adolescents: a scoping review

description: Introduction: Dietary fat intake in pregnancy, lactation and childhood determines child growth, neurodevelopment and long-term health. 
Methods: We performed a scoping review of dietary guidelines on fat intake for pregnant and lactating women, infants, children and adolescents. We systematically searched several databases and websites for relevant documents published in English from 2015-2019.
Results: We included 14 documents. Of those eight targeted pregnant and/or lactating women, mainly recommending daily intake of approx.250 mg/d of eicosapentaenoic (EPA) and docosahexaenoic acid (DHA), while one advised supplementing 800 mg/d DHA and 100 mg/d EPA in women of low omega-3 fatty acids status. The number of guidelines for infants was low (n=3). Recommended intakes of total fat were 30-40% and 20-35% of total energy intake (TEI) for infants and children, respectively. Intakes of saturated fatty acids (SFA) &lt;10% of TEI and avoidance of trans-fatty acids (TFA) were recommended across childhood. The methodology applied to develop guidelines and to grade the strength of recommendations was heterogeneous. 
Conclusion: Quantitative recommendations on fat intake during pregnancy focused mainly on PUFA intake, and those targeting infants were limited. Consistent recommendations were provided for total fat, SFA and TFA intake in childhood, however strength of recommendation was mostly not reported.
DOI: 10.6084/m9.figshare.24793236.v1
title: Supplementary Material for: Current guidelines on fat intake in pregnant and lactating women, infants, children and adolescents: a scoping review

description: Introduction: Dietary fat intake in pregnancy, lactation and childhood determines child growth, neurodevelopment and long-term health. 
Methods: We performed a scoping review of dietary guidelines on fat intake for pregnant and lactating women, infants, children and adolescents. We systematically searched several databases and websites for relevant documents published in English from 2015-2019.
Results: We included 14 documents. Of those eight targeted pregnant and/or lactating women, mainly recommending daily intake of approx.250 mg/d of eicosapentaenoic (EPA) and docosahexaenoic acid (DHA), while one advised supplementing 800 mg/d DHA and 100 mg/d EPA in women of low omega-3 fatty acids status. The number of guidelines for infants was low (n=3). Recommended intakes of total fat were 30-40% and 20-35% of total energy intake (TEI) for infants and children, respectively. Intakes of saturated fatty acids (SFA) &lt;10% of TEI and avoidance of trans-fatty acids (TFA) were recommended across childhood. The methodology applied to develop guidelines and to grade the strength of recommendations was heterogeneous. 
Conclusion: Quantitative recommendations on fat intake during pregnancy focused mainly on PUFA intake, and those targeting infants were limited. Consistent recommendations were provided for total fat, SFA and TFA intake in childhood, however strength of recommendation was mostly not reported.
DOI: 10.5281/zenodo.10354933
title: Genus Erica Interactive Identification Key V.1.00
DOI: 10.5281/zenodo.10354934
title: Genus Erica Interactive Identification Key V.1.00