cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7913084
title: Data and code for "Turning tables: food availability shapes dynamic aggressive behaviour among asynchronously hatching siblings in red kites Milvus milvus"

description: Abstract


Aggression represents the backbone of dominance acquisition in several animal societies, where the decision to interact is dictated by its relative cost. Among siblings, such costs are weighted in the light of inclusive fitness, but how this translates to aggression patterns in response to changing external and internal conditions remains unclear. Using a null-model-based approach, we investigate how day-to-day changes in food provisioning affect aggression networks and food allocation in growing red kite (Milvus milvus) nestlings, whose dominance rank is largely dictated by age. We show that older siblings, irrespective of age, change from targeting only close-aged peers (close-competitor pattern) when food provisioning is low, to uniformly attacking all other peers (downward heuristic pattern) as food conditions improve. While food allocation was generally skewed towards the older siblings, the youngest sibling in the nest increased its probability of accessing food as more was provisioned and as downward heuristic patterns became more prominent, suggesting that different aggression patterns allow for catch-up growth after periods of low food. Our results indicate that dynamic aggression patterns within the nest modulate environmental effects on juvenile development by influencing the process of dominance acquisition and potentially impacting the fledging body condition, with far-reaching fitness consequences.
DOI: 10.5281/zenodo.7913085
title: Data and code for "Turning tables: food availability shapes dynamic aggressive behaviour among asynchronously hatching siblings in red kites Milvus milvus"

description: Abstract


Aggression represents the backbone of dominance acquisition in several animal societies, where the decision to interact is dictated by its relative cost. Among siblings, such costs are weighted in the light of inclusive fitness, but how this translates to aggression patterns in response to changing external and internal conditions remains unclear. Using a null-model-based approach, we investigate how day-to-day changes in food provisioning affect aggression networks and food allocation in growing red kite (Milvus milvus) nestlings, whose dominance rank is largely dictated by age. We show that older siblings, irrespective of age, change from targeting only close-aged peers (close-competitor pattern) when food provisioning is low, to uniformly attacking all other peers (downward heuristic pattern) as food conditions improve. While food allocation was generally skewed towards the older siblings, the youngest sibling in the nest increased its probability of accessing food as more was provisioned and as downward heuristic patterns became more prominent, suggesting that different aggression patterns allow for catch-up growth after periods of low food. Our results indicate that dynamic aggression patterns within the nest modulate environmental effects on juvenile development by influencing the process of dominance acquisition and potentially impacting the fledging body condition, with far-reaching fitness consequences.
DOI: 10.15468/dl.e49n84
title: Occurrence Download

description: A dataset containing 219 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Scutarcopagia scobinata",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence)",
 {
 "not" : {
 "OccurrenceStatus" : [
 "is one of (Absent)"
 ]
 }
 }
 ]
}

 The dataset includes 219 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011045-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30148630.v1
title: Supplementary Material from "Enhanced Nitrogen Removal in Aqueous Solution by HNO<sub>3</sub> and NaOH Comodified Activated Carbon Fibers: Adsorption Performance and Mechanisms".docx

description: Nitrogen serves as an important driver of eutrophication in water bodies, with its excessive inputs posing considerable threats to aquatic ecosystems and human health. In order to remove nitrogen pollutants efficiently, activated carbon fibers (ACFs) were comodified with HNO<sub>3</sub> and NaOH to improve their adsorption performance in aqueous solution. Batch experiments on surface characteristics and adsorption effects on ammonia nitrogen (NH<sub>3</sub>-N) and total nitrogen (TN) were conducted to assess the adsorption performance and related mechanisms of modified ACFs (MACFs). The surface roughness of the MACFs was increased, and –OH, C=O and C=C double bonds, and Na<sup>+</sup> were loaded on their surfaces. Among the nine MACFs, ACF50-0.4, which was modified with 50% HNO<sub>3 </sub>and 0.4% NaOH, achieved the highest adsorption capacity and removal rate of the nitrogen pollutants. Its adsorption effect could be maximized and a high removal rate could be achieved at the dose of 1.0 g/L; initial NH<sub>3</sub>-N and TN concentrations of 15 and 25 mg/L, respectively; pH of 7; and temperature of 25 °C. Moreover, the nitrogen adsorption mode was multilayer heterogeneous surface adsorption, which was spontaneous, endothermic, and dominated by chemisorption. The main adsorption mechanisms of MACFs included surface adsorption, electrostatic attraction, ligand and ion exchange.
DOI: 10.5281/zenodo.17143704
title: Intensivkapazitäten und COVID-19-Intensivbettenbelegung in Deutschland

description: Der Datensatz "Intensivkapazitäten und COVID-19-Intensivbettenbelegung in Deutschland" des Robert Koch-Instituts dokumentiert die tägliche intensivmedizinische Versorgungslage seit der COVID-19-Pandemie. Basierend auf Meldungen aller intensivbettenführenden Krankenhäuser in Deutschland erfasst das DIVI-Intensivregister Echtzeitdaten zu belegten und freien Intensivbetten. Die Erhebung differenziert nach Altersgruppen, Regionen und Versorgungsstufen. COVID-19-Fälle auf Intensivstationen werden gesondert ausgewiesen. Die Daten stehen aggregiert auf Bundes-, Landes- und Kreisebene zur Verfügung. Damit bildet der Datensatz eine Grundlage für die Überwachung von Kapazitäten, die Koordination von Behandlungskapazitäten und politische Entscheidungsprozesse während der Pandemie und darüber hinaus.
DOI: 10.11583/dtu.28152410
title: Data for Pollok et al. "Magnetic microscopy for operando imaging of battery dynamics"

description: <b>Fig3b_LCO.csv</b> contains data for Fig. 3b. <i>Molar magnetic susceptibility of Li</i><i>x</i><i>CoO</i><i>2 </i><i>[m3/mol] at 300 K</i><i> </i><i>as a function of the</i><i> state-of-</i><i>charge, which is</i><i> obtained by electrochemically cycling a liquid-state battery </i><i>with a Li</i><i>x</i><i>CoO</i><i>2 at the positive electrode</i><i>.</i><b>Fig3c_elements.csv</b> contains data for Fig. 3c. <i>Molar </i><i>m</i><i>agnetic susceptibility of various elements of relevance to batteries at 300 K </i><i>[m3/mol] (</i><i>SI unit) </i><i>as a function of the</i><i> atomic number [Z].</i><br><i>Data from </i><i>Weast, R.C., CRC handbook of chemistry and physics (</i><i>1986)</i><i>.</i><b>Fig4b_paramagnetic.csv</b> contains data for Fig. 4b. <i>S</i><i>imulated magnetic signal strengths </i><i>for the paramagnetic </i><i>lithium metal and Li</i><i>x</i><i>CoO</i><i>2 </i><i>[T] as a function of the external magnetic field (B</i><sub><em>ext</em></sub><i>) </i><i>[T].</i><b>Fig4b_oersted.csv</b> contains data for Fig. 4b. <i>S</i><i>imulated magnetic signal strengths </i><i>for the Ørsted magnetic field</i><i> [T] as a function of the</i><i> nominal current density (J</i><sub><em>nominal</em></sub><i>) [mA/cm2].</i><b>FigS1_galvanostatic_charging.csv</b> contains data for Fig. S1. <i>Galvanostatic charging curve of Li-ion battery cell, at C/10-rate for complete </i><i>delithiation after 10 hours.</i><b>FigS2_VSM_LixCoO2.csv</b> contains data for Fig. S2. <i>Measured m</i><i>agnetic moment of Li</i><i>x</i><i>CoO</i><i>2</i><i> </i><i>samples with varying lithium content x at room </i><i>temperature [emu/g] </i><i>as a function of</i><i> the magnetic field [G].</i><b>FigS3_NMC532.csv</b> contains data for Fig. S3. <i>Molar mag</i><i>netic susceptibility of NMC532 [m3/mol] </i><i>as a function of the</i><i> state-</i><i>of-charge, associated with different lithium content within the crystal structure.</i><br><i>Data from </i>https://doi.org/10.1038/s41467-018-04192-x<i>.</i><b>FigS4_LFP.csv </b>contains data for Fig. S4. <i>Molar mag</i><i>netic susceptibility</i><i> of LFP </i><i>[m3/mol]</i><i> </i><i>as a function of the</i><i> state-of-</i><i>charge, which in </i><i>LFP is a two-phase mixture of </i><i>LiFePO</i><i>4</i><i> </i><i>and FePO</i><i>4</i><i>.</i><br><i>Data from </i>https://doi.org/10.1109/TIM.2015.2437634<i>.</i><b>README.txt</b> is the README for this dataset.
DOI: 10.11583/dtu.28152410.v1
title: Data for Pollok et al. "Magnetic microscopy for operando imaging of battery dynamics"

description: <b>Fig3b_LCO.csv</b> contains data for Fig. 3b. <i>Molar magnetic susceptibility of Li</i><i>x</i><i>CoO</i><i>2 </i><i>[m3/mol] at 300 K</i><i> </i><i>as a function of the</i><i> state-of-</i><i>charge, which is</i><i> obtained by electrochemically cycling a liquid-state battery </i><i>with a Li</i><i>x</i><i>CoO</i><i>2 at the positive electrode</i><i>.</i><b>Fig3c_elements.csv</b> contains data for Fig. 3c. <i>Molar </i><i>m</i><i>agnetic susceptibility of various elements of relevance to batteries at 300 K </i><i>[m3/mol] (</i><i>SI unit) </i><i>as a function of the</i><i> atomic number [Z].</i><br><i>Data from </i><i>Weast, R.C., CRC handbook of chemistry and physics (</i><i>1986)</i><i>.</i><b>Fig4b_paramagnetic.csv</b> contains data for Fig. 4b. <i>S</i><i>imulated magnetic signal strengths </i><i>for the paramagnetic </i><i>lithium metal and Li</i><i>x</i><i>CoO</i><i>2 </i><i>[T] as a function of the external magnetic field (B</i><sub><em>ext</em></sub><i>) </i><i>[T].</i><b>Fig4b_oersted.csv</b> contains data for Fig. 4b. <i>S</i><i>imulated magnetic signal strengths </i><i>for the Ørsted magnetic field</i><i> [T] as a function of the</i><i> nominal current density (J</i><sub><em>nominal</em></sub><i>) [mA/cm2].</i><b>FigS1_galvanostatic_charging.csv</b> contains data for Fig. S1. <i>Galvanostatic charging curve of Li-ion battery cell, at C/10-rate for complete </i><i>delithiation after 10 hours.</i><b>FigS2_VSM_LixCoO2.csv</b> contains data for Fig. S2. <i>Measured m</i><i>agnetic moment of Li</i><i>x</i><i>CoO</i><i>2</i><i> </i><i>samples with varying lithium content x at room </i><i>temperature [emu/g] </i><i>as a function of</i><i> the magnetic field [G].</i><b>FigS3_NMC532.csv</b> contains data for Fig. S3. <i>Molar mag</i><i>netic susceptibility of NMC532 [m3/mol] </i><i>as a function of the</i><i> state-</i><i>of-charge, associated with different lithium content within the crystal structure.</i><br><i>Data from </i>https://doi.org/10.1038/s41467-018-04192-x<i>.</i><b>FigS4_LFP.csv </b>contains data for Fig. S4. <i>Molar mag</i><i>netic susceptibility</i><i> of LFP </i><i>[m3/mol]</i><i> </i><i>as a function of the</i><i> state-of-</i><i>charge, which in </i><i>LFP is a two-phase mixture of </i><i>LiFePO</i><i>4</i><i> </i><i>and FePO</i><i>4</i><i>.</i><br><i>Data from </i>https://doi.org/10.1109/TIM.2015.2437634<i>.</i><b>README.txt</b> is the README for this dataset.
DOI: 10.6084/m9.figshare.30148714
title: Bacterial MAGs from Corals

description: Bacterial Metagenome Assembled Genomes (bMAGs) from stony coral metagenomes. Bins from MaxBin2 v2.2.7 (Wu et al., 2015), MetaBat2 v2.15 (Kang et al., 2019), and CONCOCT v1.1.0 (Alneberg et al., 2014) were consolidated and improved with the metaWRAP v1.2.1 (Uritskiy et al., 2018). Bins were then quality filtered to ≥50% completion and ≤10% contamination with CheckM2 v1.0.2 (Chklovski et al., 2023). This dataset has been dereplicated using fastANI (--similarity-threshold 0.95).
DOI: 10.6084/m9.figshare.30148714.v1
title: Bacterial MAGs from Corals

description: Bacterial Metagenome Assembled Genomes (bMAGs) from stony coral metagenomes. Bins from MaxBin2 v2.2.7 (Wu et al., 2015), MetaBat2 v2.15 (Kang et al., 2019), and CONCOCT v1.1.0 (Alneberg et al., 2014) were consolidated and improved with the metaWRAP v1.2.1 (Uritskiy et al., 2018). Bins were then quality filtered to ≥50% completion and ≤10% contamination with CheckM2 v1.0.2 (Chklovski et al., 2023). This dataset has been dereplicated using fastANI (--similarity-threshold 0.95).
DOI: 10.15468/dl.y6ndh3
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Etheostoma pallididorsum)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 23 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011048-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17143420
title: YOLOv8 grapevine leaf blade and vein pixel segmentation mask

description: This repository contains a fully reproducible pipeline for grapevine leaf instance segmentation using YOLOv8. The code is designed to be a lightweight and easily distributable solution for researchers, viticulturists, and ampelographers to prepare their own data, train a state-of-the-art model, and perform inference.

Key Components:





0_prepare_yolo_dataset.py: A preprocessing script that takes raw image and annotation data and converts it into the necessary YOLOv8 format, including creating segmentation masks and labels for training. It handles multiple directory structures and automatically splits the data into training, validation, and testing sets.




1_train_yolo.py: This script trains a YOLOv8n-seg model on the prepared dataset. It utilizes a lightweight architecture to achieve high performance with minimal computational resources, making it suitable for a wide range of hardware.


2_inference.py: A final script to perform inference on new images, saving the predictions in an organized folder structure for easy visualization and analysis.


How to Reproduce the Analysis

To reproduce the analysis and train a custom model, place your raw image and annotation data in the ./data/ folder and then run the scripts in numerical order. Please note: all data is provided to reproduce buliding and running inference using the model. However, you can add your own data as a new folder to ./data/ and then update the 0_prepare_yolo_dataset.py script to accomodate the new data.
DOI: 10.5281/zenodo.17143419
title: YOLOv8 grapevine leaf blade and vein pixel segmentation mask

description: This repository contains a fully reproducible pipeline for grapevine leaf instance segmentation using YOLOv8. The code is designed to be a lightweight and easily distributable solution for researchers, viticulturists, and ampelographers to prepare their own data, train a state-of-the-art model, and perform inference.

Key Components:





0_prepare_yolo_dataset.py: A preprocessing script that takes raw image and annotation data and converts it into the necessary YOLOv8 format, including creating segmentation masks and labels for training. It handles multiple directory structures and automatically splits the data into training, validation, and testing sets.




1_train_yolo.py: This script trains a YOLOv8n-seg model on the prepared dataset. It utilizes a lightweight architecture to achieve high performance with minimal computational resources, making it suitable for a wide range of hardware.


2_inference.py: A final script to perform inference on new images, saving the predictions in an organized folder structure for easy visualization and analysis.


How to Reproduce the Analysis

To reproduce the analysis and train a custom model, place your raw image and annotation data in the ./data/ folder and then run the scripts in numerical order. Please note: all data is provided to reproduce buliding and running inference using the model. However, you can add your own data as a new folder to ./data/ and then update the 0_prepare_yolo_dataset.py script to accomodate the new data.
DOI: 10.5281/zenodo.16918640
title: Onset of Coherent Phonon Motion in Peierls-Distorted Antimony by Attosecond Transient Absorption

description: Attosecond extreme-ultraviolet (XUV) transient absorption spectroscopy measurements on the Peierls-distorted phase of the semimetal antimony (Sb) are presented.After excitation by an ultrashort, broad band near-infrared (NIR) pulse, the distortion is (partly) lifted causing the well-known coherent phonon motion of the lattice. While the overall observed dynamics generally follow a displacive excitation model, a delayed onset of the pump-induced carrier dynamics due to hot-carrier thermalization is observed, as well as a large spectral phase dependence in the coherent phonon oscillation. This is attributed to significantly different carrier relaxation timescales for carrier energies above and near the Fermi level of the semimetal and corroborated by a simple theoretical model that considers the carrier relaxation timescales in the displacive phonon model to explain the observed dynamics. Our results provide direct experimental evidence about the role of carrier-relaxation in the origin of displacive coherent phonon motion.
DOI: 10.5281/zenodo.16918641
title: Onset of Coherent Phonon Motion in Peierls-Distorted Antimony by Attosecond Transient Absorption

description: Attosecond extreme-ultraviolet (XUV) transient absorption spectroscopy measurements on the Peierls-distorted phase of the semimetal antimony (Sb) are presented.After excitation by an ultrashort, broad band near-infrared (NIR) pulse, the distortion is (partly) lifted causing the well-known coherent phonon motion of the lattice. While the overall observed dynamics generally follow a displacive excitation model, a delayed onset of the pump-induced carrier dynamics due to hot-carrier thermalization is observed, as well as a large spectral phase dependence in the coherent phonon oscillation. This is attributed to significantly different carrier relaxation timescales for carrier energies above and near the Fermi level of the semimetal and corroborated by a simple theoretical model that considers the carrier relaxation timescales in the displacive phonon model to explain the observed dynamics. Our results provide direct experimental evidence about the role of carrier-relaxation in the origin of displacive coherent phonon motion.
DOI: 10.15468/dl.mh9hn7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Senegona senegambiensis",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence)",
 {
 "not" : {
 "OccurrenceStatus" : [
 "is one of (Absent)"
 ]
 }
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011047-250914085247600/datasets/export for details.
DOI: 10.15468/dl.4j7dfs
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Erysimum pulchellum",
 "Country is Austria",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011049-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30148789
title: Supplementary Tables

description: Table S1_IBE vs NBE mRNA DE analysis, targets of DE miRNA analysis, Overlap of up mRNA and targets of down miRNA, Overlap of down mRNA and target of up miRNA.
DOI: 10.6084/m9.figshare.30148789.v1
title: Supplementary Tables

description: Table S1_IBE vs NBE mRNA DE analysis, targets of DE miRNA analysis, Overlap of up mRNA and targets of down miRNA, Overlap of down mRNA and target of up miRNA.
DOI: 10.6084/m9.figshare.28255364
title: Raw sequence reads as Supplementary Data to the manuscript <b>Metabarcoding and microtomography </b><b>reveal new insights into the dietary niche of near-extinct amphibians</b>

description: Raw sequence reads as Supplementary Data to the manuscript <b>Metabarcoding and microtomography </b><b>reveal new insights into the dietary niche of near-extinct amphibians</b>. Reads constitute unmerged MiSeq (Illumina) paired-end reads from COI metabarcoding of faecal samples.
DOI: 10.6084/m9.figshare.28255364.v1
title: Raw sequence reads as Supplementary Data to the manuscript <b>Metabarcoding </b><b>reveals insights into the dietary niche of near-extinct amphibians</b>

description: Raw sequence reads as Supplementary Data to the manuscript <b>Metabarcoding </b><b>reveals insights into the dietary niche of near-extinct amphibians</b>. Reads constitute unmerged MiSeq (Illumina) paired-end reads from COI metabarcoding of faecal samples.
DOI: 10.6084/m9.figshare.28255364.v2
title: Raw sequence reads as Supplementary Data to the manuscript <b>Metabarcoding and microtomography </b><b>reveal new insights into the dietary niche of near-extinct amphibians</b>

description: Raw sequence reads as Supplementary Data to the manuscript <b>Metabarcoding and microtomography </b><b>reveal new insights into the dietary niche of near-extinct amphibians</b>. Reads constitute unmerged MiSeq (Illumina) paired-end reads from COI metabarcoding of faecal samples.
DOI: 10.15468/dl.a2atnh
title: Occurrence Download

description: A dataset containing 234 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tellina radiata",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence)",
 {
 "not" : {
 "OccurrenceStatus" : [
 "is one of (Absent)"
 ]
 }
 }
 ]
}

 The dataset includes 234 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011051-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ujaz73
title: Occurrence Download

description: A dataset containing 22 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hirschfeldia incana",
 "Country is Austria",
 "HasCoordinate is true"
 ]
}

 The dataset includes 22 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011052-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.