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1 to 9 of 9 Results

Replication Data for: https://arxiv.org/abs/2210.07833v2 May 16, 2023 Singh, Juhi; Zeier, Robert; Calarco, Tommaso; Motzoi, Felix, 2023, "Replication Data for: https://arxiv.org/abs/2210.07833v2", https://doi.org/10.26165/JUELICH-DATA/FJO68W, Jülich DATA, V1 The files contains all the data used for generating all figures in the manuscript. All the folders the named according to the figure numbers.
Replication Data for: On Noise-Sensitive Automatic Tuning of Gate-Defined Sensor Dots Feb 23, 2023 Hader, Fabian; Vogelbruch, Jan; Humpohl, Simon; Hangleiter, Tobias; Eguzo, Chimezie; Heinen, Stefan; Meyer, Stefanie; van Waasen, Stefan, 2023, "Replication Data for: On Noise-Sensitive Automatic Tuning of Gate-Defined Sensor Dots", https://doi.org/10.26165/JUELICH-DATA/QIIBZV, Jülich DATA, V1 Sensor dot measurement data (Matlab format) and format description used in the evaluation of IEEE TQE paper: On Noise-Sensitive Automatic Tuning of Gate-Defined Sensor Dots, 2023
Data used in: Spanning Fermi arcs in a two-dimensional magnet Sep 7, 2022 Chen, Ying-Jiun; Jan-Philipp Hanke; Markus Hoffmann; Gustav Bihlmayer; Yuriy Mokrousov; Stefan Blügel; Claus M. Schneider; Christian Tusche, 2022, "Data used in: Spanning Fermi arcs in a two-dimensional magnet", https://doi.org/10.26165/JUELICH-DATA/CXWKMJ, Jülich DATA, V1 We provide here the raw data used to produce the figures in the publication Y.J. Chen et al. XXXXXXX, XX, XXXX, DOI: XXXXXXXX. All metadata necessary to analyze the data are contained in the files.
Data set of the manuscript 'Opposite signs in local and nonlocal soil moisture-precipitation couplings across Europe' Aug 29, 2022 Tesch, Tobias; Kollet, Stefan; Garcke, Jochen; Katragkou, Eleni; Kartsios, Stergios, 2022, "Data set of the manuscript 'Opposite signs in local and nonlocal soil moisture-precipitation couplings across Europe'", https://doi.org/10.26165/JUELICH-DATA/YO3JCM, Jülich DATA, V1 This is a data set of the manuscript 'Opposite signs in local and nonlocal soil moisture-precipitation couplings across Europe', submitted to Geophysical Research Letters. It contains data from a convection-permitting (CP) simulation across central Europe. The simulation was perf...
Advancing AI-based pan-European groundwater monitoring Mar 28, 2022 Ma, Yueling; Montzka, Carsten; Naz, Bibi; Kollet, Stefan, 2021, "Advancing AI-based pan-European groundwater monitoring", https://doi.org/10.26165/JUELICH-DATA/ZBLDIR, Jülich DATA, V2 This study proposes an AI-based methodology combining Long Short-Term Memory (LSTM) networks and transfer learning (TL) to estimate water table depth anomalies (wtd_a) at the European scale in the absence of consistent water table depth (wtd) observational data sets, which is nam...
Dataset for the Arabidopsis npq study using active and passive fluorescence and reflectance Mar 23, 2022 Acebron, Kelvin, 2022, "Dataset for the Arabidopsis npq study using active and passive fluorescence and reflectance", https://doi.org/10.26165/JUELICH-DATA/LCUQZC, Jülich DATA, V1 This dataset contains all the main and supplementary data collected from diurnal measurements of Arabidopsis npq mutants in the summer of 2017 and winter of 2018. The dataset is composed of reflectance measurements, passive fluorescence signal (SIF) and active fluorescence signal...
Specim IQ Camera: Dataset for Arabidopsis Case Study Mar 22, 2022 Acebron, Kelvin, 2022, "Specim IQ Camera: Dataset for Arabidopsis Case Study", https://doi.org/10.26165/JUELICH-DATA/OM1JKZ, Jülich DATA, V1 Hyperspectral imaging is a technique used in plant phenotyping which can detect differences in plant traits. Information about the morphology and physiology of plants can be derived by calculating spectral ratios (Vegetation Indices) from hyperspectral datacube. Here we publish t...
An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis Dec 13, 2021 Ma, Yueling; Montzka, Carsten; Bayat, Bagher; Kollet, Stefan, 2021, "An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis", https://doi.org/10.26165/JUELICH-DATA/AMQ6NI, Jülich DATA, V1 This study introduced a number of hydrometeorological variables in addition to precipitation anomaly (pr_a) in the construction of Long Short-Term Memory (LSTM) networks to arrive at improved water table depth anomaly (wtd_a) at individual pixels over Europe in various experiment...
Using Long Short-Term Memory networks to connect water table depth anomalies to precipitation anomalies over Europe May 31, 2021 Ma, Yueling; Montzka, Carsten; Bayat, Bagher; Kollet, Stefan, 2021, "Using Long Short-Term Memory networks to connect water table depth anomalies to precipitation anomalies over Europe", https://doi.org/10.26165/JUELICH-DATA/WPRA1F, Jülich DATA, V1 This study utilized spatiotemporally continuous precipitation anomaly (pr_a) and water table depth anomaly (wtd_a) from integrated hydrologic simulation results (i.e., the TSMP-G2A data set) over Europe in combination with Long Short-Term Memory (LSTM) networks to capture the tim...

Replication Data for: https://arxiv.org/abs/2210.07833v2

May 16, 2023

Singh, Juhi; Zeier, Robert; Calarco, Tommaso; Motzoi, Felix, 2023, "Replication Data for: https://arxiv.org/abs/2210.07833v2", https://doi.org/10.26165/JUELICH-DATA/FJO68W, Jülich DATA, V1

The files contains all the data used for generating all figures in the manuscript. All the folders the named according to the figure numbers.

Replication Data for: On Noise-Sensitive Automatic Tuning of Gate-Defined Sensor Dots

Feb 23, 2023

Hader, Fabian; Vogelbruch, Jan; Humpohl, Simon; Hangleiter, Tobias; Eguzo, Chimezie; Heinen, Stefan; Meyer, Stefanie; van Waasen, Stefan, 2023, "Replication Data for: On Noise-Sensitive Automatic Tuning of Gate-Defined Sensor Dots", https://doi.org/10.26165/JUELICH-DATA/QIIBZV, Jülich DATA, V1

Sensor dot measurement data (Matlab format) and format description used in the evaluation of IEEE TQE paper: On Noise-Sensitive Automatic Tuning of Gate-Defined Sensor Dots, 2023

Data used in: Spanning Fermi arcs in a two-dimensional magnet

Sep 7, 2022

Chen, Ying-Jiun; Jan-Philipp Hanke; Markus Hoffmann; Gustav Bihlmayer; Yuriy Mokrousov; Stefan Blügel; Claus M. Schneider; Christian Tusche, 2022, "Data used in: Spanning Fermi arcs in a two-dimensional magnet", https://doi.org/10.26165/JUELICH-DATA/CXWKMJ, Jülich DATA, V1

We provide here the raw data used to produce the figures in the publication Y.J. Chen et al. XXXXXXX, XX, XXXX, DOI: XXXXXXXX. All metadata necessary to analyze the data are contained in the files.

Data set of the manuscript 'Opposite signs in local and nonlocal soil moisture-precipitation couplings across Europe'

Aug 29, 2022

Tesch, Tobias; Kollet, Stefan; Garcke, Jochen; Katragkou, Eleni; Kartsios, Stergios, 2022, "Data set of the manuscript 'Opposite signs in local and nonlocal soil moisture-precipitation couplings across Europe'", https://doi.org/10.26165/JUELICH-DATA/YO3JCM, Jülich DATA, V1

This is a data set of the manuscript 'Opposite signs in local and nonlocal soil moisture-precipitation couplings across Europe', submitted to Geophysical Research Letters. It contains data from a convection-permitting (CP) simulation across central Europe. The simulation was perf...

Advancing AI-based pan-European groundwater monitoring

Mar 28, 2022

Ma, Yueling; Montzka, Carsten; Naz, Bibi; Kollet, Stefan, 2021, "Advancing AI-based pan-European groundwater monitoring", https://doi.org/10.26165/JUELICH-DATA/ZBLDIR, Jülich DATA, V2

This study proposes an AI-based methodology combining Long Short-Term Memory (LSTM) networks and transfer learning (TL) to estimate water table depth anomalies (wtd_a) at the European scale in the absence of consistent water table depth (wtd) observational data sets, which is nam...

Dataset for the Arabidopsis npq study using active and passive fluorescence and reflectance

Mar 23, 2022

Acebron, Kelvin, 2022, "Dataset for the Arabidopsis npq study using active and passive fluorescence and reflectance", https://doi.org/10.26165/JUELICH-DATA/LCUQZC, Jülich DATA, V1

This dataset contains all the main and supplementary data collected from diurnal measurements of Arabidopsis npq mutants in the summer of 2017 and winter of 2018. The dataset is composed of reflectance measurements, passive fluorescence signal (SIF) and active fluorescence signal...

Specim IQ Camera: Dataset for Arabidopsis Case Study

Mar 22, 2022

Acebron, Kelvin, 2022, "Specim IQ Camera: Dataset for Arabidopsis Case Study", https://doi.org/10.26165/JUELICH-DATA/OM1JKZ, Jülich DATA, V1

Hyperspectral imaging is a technique used in plant phenotyping which can detect differences in plant traits. Information about the morphology and physiology of plants can be derived by calculating spectral ratios (Vegetation Indices) from hyperspectral datacube. Here we publish t...

An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis

Dec 13, 2021

Ma, Yueling; Montzka, Carsten; Bayat, Bagher; Kollet, Stefan, 2021, "An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis", https://doi.org/10.26165/JUELICH-DATA/AMQ6NI, Jülich DATA, V1

This study introduced a number of hydrometeorological variables in addition to precipitation anomaly (pr_a) in the construction of Long Short-Term Memory (LSTM) networks to arrive at improved water table depth anomaly (wtd_a) at individual pixels over Europe in various experiment...

Using Long Short-Term Memory networks to connect water table depth anomalies to precipitation anomalies over Europe

May 31, 2021

Ma, Yueling; Montzka, Carsten; Bayat, Bagher; Kollet, Stefan, 2021, "Using Long Short-Term Memory networks to connect water table depth anomalies to precipitation anomalies over Europe", https://doi.org/10.26165/JUELICH-DATA/WPRA1F, Jülich DATA, V1

This study utilized spatiotemporally continuous precipitation anomaly (pr_a) and water table depth anomaly (wtd_a) from integrated hydrologic simulation results (i.e., the TSMP-G2A data set) over Europe in combination with Long Short-Term Memory (LSTM) networks to capture the tim...

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