81 Works

DataCite Metadata Schema Documentation for the Publication and Citation of Research Data and Other Research Outputs v4.4

1 Introduction 1.1 The DataCite Consortium 1.2 DataCite Community Participation 1.3 The Metadata Schema 1.4 Version 4.4 Update 2 DataCite Metadata Properties 2.1 Overview 2.2 Citation 2.3 DataCite Properties 3 XML Example 4 XML Schema 5 Other DataCite Services Appendices Appendix 1: Controlled List Definitions Appendix 2: Earlier Version Update Notes Appendix 3: Standard values for unknown information Appendix 4: Version 4.1 Changes in support of software citation Appendix 5: FORCE11 Software Citation Principles Mapping

Grasslands of temperate Europe in a changing world – Editorial to the 16th EDGG Special Feature in Tuexenia

Steffen Boch, Thomas Becker, Balázs Deák, Jürgen Dengler & Valentin H. Klaus
Mitglieder der Eurasian Dry Grassland Group (EDGG) und deren Vorgängerorganisationen geben seit 16 Jahren Grasland-Sonderausgaben (Special Features) in Tuexenia heraus. Das diesjährige Special Feature mit dem Titel Grasländer des gemäßigten Europas in einer sich verändernden Welt umfasst sieben Artikel, die verschiedene Aspekte der Graslandforschung beleuchten und dabei unterschiedliche Organismengruppen einbeziehen: LLUMIQUINGA et al. untersuchten Langzeiteffekte von Einsaat, Mahd und Kohlenstoffzusatz (Reduktion der Nährstoffverfügbarkeit durch Verschiebung des C/N-Verhältnis) auf den Renaturierungserfolg von pannonischem Sandgrasland auf ehemaligen...

Additional file 4 of Novel trends of genome evolution in highly complex tropical sponge microbiomes

Joseph B. Kelly, David E. Carlson, Jun Siong Low & Robert W. Thacker
Additional file 4: Fig. S4. CSGs plotted annotated on bacterial phylogeny comprising sponge-derived (Ircinia and non-Ircinia) and Tara Oceans MAGs, following tree construction and plotting scheme as outlined for Fig. 3.

Subduction Dynamics and Rheology Control on Forearc and Backarc Subsidence: Numerical Models and Observations from the Mediterranean

Attila Balazs , Claudio Faccenna , Taras Gerya , Kosuke Ueda & Francesca Funiciello
The dynamics of subduction zones is linked to the rise and demise of forearc and backarc sedimentary basins in the overriding plate. Subsidence and uplift rates of these distinct basins are controlled by variations in plate convergence and subduction velocities and determined by the rheological and thermal structure of the lithosphere. In this study we conducted a series of high-resolution 2D numerical models of oceanic subduction and subsequent continental collision. The numerical code 2DELVIS involves...

Additional file 4 of MP4: a machine learning based classification tool for prediction and functional annotation of pathogenic proteins from metagenomic and genomic datasets

Ankit Gupta, Aditya S. Malwe, Gopal N. Srivastava, Parikshit Thoudam, Keshav Hibare & Vineet K. Sharma
Additional file 4. Table S3: Performances of random forest-based models at top features and different mtry values.

Gaze-Based Interaction with Maps and Panoramas

Laura Schalbetter, Tiffany C. K. Kwok, Peter Kiefer & Martin Raubal

DataCite to Dublin Core Mapping v4.4.

On the occasion of the release of v4.4 of the DataCite Metadata Schema its Metadata Working Group has updated the mapping to Dublin Core. This replaces the mapping in the Appendix of the DataCite-MetadataKernel v2.1. The mapping can be used to convert records described following version 4.4 of the DataCite Metadata Schema into records that comply with the Dublin Core Metadata Initiative Schema.

Additional file 2 of H3K18 lactylation marks tissue-specific active enhancers

Eva Galle, Chee-Wai Wong, Adhideb Ghosh, Thibaut Desgeorges, Kate Melrose, Laura C. Hinte, Daniel Castellano-Castillo, Magdalena Engl, Joao Agostinho de Sousa, Francisco Javier Ruiz-Ojeda, Katrien De Bock, Jonatan R. Ruiz & Ferdinand von Meyenn
Additional file 2: Uncropped western blot images. Cropped images used in Fig. 1A and Fig S1B.

Additional file 7 of H3K18 lactylation marks tissue-specific active enhancers

Eva Galle, Chee-Wai Wong, Adhideb Ghosh, Thibaut Desgeorges, Kate Melrose, Laura C. Hinte, Daniel Castellano-Castillo, Magdalena Engl, Joao Agostinho de Sousa, Francisco Javier Ruiz-Ojeda, Katrien De Bock, Jonatan R. Ruiz & Ferdinand von Meyenn
Additional file 7. Review history.

Additional file 1 of Novel trends of genome evolution in highly complex tropical sponge microbiomes

Joseph B. Kelly, David E. Carlson, Jun Siong Low & Robert W. Thacker
Additional file 1: Fig. S1. Phylogenetic depiction of MAG distributions across Caribbean Ircinia species and redundancy in primary metabolic modes. The heatmap immediately to the right of the tree indicates the ln-transformed relative abundances of each MAG by host specimen. Species abbreviations accompanying specimen labels at the bottom of the heatmap are as follows: ICam (I. campana), IcfR (I. cf. reteplana), IRad (I. radix), ILae (I. laeviconulosa), IBoc (I. bocatorensis B), ILow (I. lowi), IVan...

Additional file 2 of Novel trends of genome evolution in highly complex tropical sponge microbiomes

Joseph B. Kelly, David E. Carlson, Jun Siong Low & Robert W. Thacker
Additional file 2: Fig. S2. Plots depicting prevalence of MAGs associated with Caribbean Ircinia by source and region, inferred using the relative abundance matrix produced by CoverM. A. Bar chart depicting the percent of MAGs that are found across multiple host species. B. Bar chart depicting the regional specificity of MAGs. C. PCA of taxonomic community compositions of each host species’ microbiome.

Designing and Evaluating Coherent Policies and Measures for the SDGs. An Input Paper for the GSDR 2023

IASS Brochure; November 2021

When cows meet robots - Agricultural Sciences at ETH Zurich

Graf Sophie, Gilgen Anna & Flatt Sandra

Integration of socio-technological transition constraints into energy demand and systems models. Deliverable 2.5. Sustainable Energy Transitions Laboratory (SENTINEL) project

Diana Süsser, Bryn Pickering, Souran Chatterjee, Gabriel Oreggioni, Vassilis Stavrakas & Johan Lilliestam
The decarbonisation of the European energy system is a large-scale transformation, which demands not only for a techno-economic feasibility analysis, but also for an assessment of the social and political feasibility and environmental impacts. However, most energy models are not able to fully represent the social and political developments and dynamics of the energy transition, such as preferences, acceptance and behavioural changes of citizens and decision-makers. To address this shortcoming, we developed QTDIAN (Quantification of...

Sex difference in lipid levels in first-diagnosed drug-naïve depression patients: A case-control and 12-weeks follow-up study

Rui Yang, Lu Wang, Song Cao, Ming Chen, Chu-Jun Wu, Floyd Silva, Man-Jun Shen, Jin-Dong Chen, Mi-Mi Tang & Bi-Lian Liu
Patients with depression have a high prevalence of developing dyslipidemia. In this study, we aim to investigate the difference of serum lipids, including total cholesterol (TCH), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG), between the depressed patients and healthy controls. Sex differences in lipids and their psychological correlations were also included. The study included 56 healthy controls (males/females = 26/30) and 110 first-diagnosed drug-naïve outpatients (males/females = 35/75). A total of...

Additional file 1 of Deep learning-based behavioral profiling of rodent stroke recovery

Rebecca Z. Weber, Geertje Mulders, Julia Kaiser, Christian Tackenberg & Ruslan Rust
Additional file 1: Fig. S1. Walking profile of mice following DeepLabCut tracking. Fig. S2. Tracking of body parts in injured mice and mice with different genotypes. Fig. S3. Kinematic changes in spontaneous walk after stroke. Fig. S4. Angular variability between body center and front and hind paws. Fig. S5. Subgroup analysis for random forest classification and principal component analysis. Fig. S6. Principal component analysis and random forest classification of uninjured control mice. Fig. S7. Correlation...

Mapping Dominant Boreal Tree Species Groups by Combining Area-Based and Individual Tree Crown LiDAR Metrics with Sentinel-2 Data

Martin Queinnec, Nicholas C. Coops, Joanne C. White, Verena C. Griess, Naomi B. Schwartz & Grant McCartney
Airborne light detection and ranging (LiDAR) data are increasingly used to inform sustainable forest management practices. Information about species composition is needed for a range of applications; however, commonly used area-based summaries of LiDAR data are limited to accurately differentiate tree species. The objective of this study was to map dominant species groups across a large (>580,000 ha) boreal forest by combining area-based and individual tree metrics derived from single photon LiDAR data with multispectral...

Additional file 2 of The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

Hiba Mohammed Taha, Reza Aalizadeh, Nikiforos Alygizakis, Jean-Philippe Antignac, Hans Peter H. Arp, Richard Bade, Nancy Baker, Lidia Belova, Lubertus Bijlsma, Evan E. Bolton, Werner Brack, Alberto Celma, Wen-Ling Chen, Tiejun Cheng, Parviel Chirsir, Ľuboš Čirka, Lisa A. D’Agostino, Yannick Djoumbou Feunang, Valeria Dulio, Stellan Fischer, Pablo Gago-Ferrero, Aikaterini Galani, Birgit Geueke, Natalia Głowacka, Juliane Glüge … & Emma L. Schymanski
Additional file 2: Overview of the NORMAN-SLE website (DOCX format) as of 30 May 2022 [82].

Additional file 2 of The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

Hiba Mohammed Taha, Reza Aalizadeh, Nikiforos Alygizakis, Jean-Philippe Antignac, Hans Peter H. Arp, Richard Bade, Nancy Baker, Lidia Belova, Lubertus Bijlsma, Evan E. Bolton, Werner Brack, Alberto Celma, Wen-Ling Chen, Tiejun Cheng, Parviel Chirsir, Ľuboš Čirka, Lisa A. D’Agostino, Yannick Djoumbou Feunang, Valeria Dulio, Stellan Fischer, Pablo Gago-Ferrero, Aikaterini Galani, Birgit Geueke, Natalia Głowacka, Juliane Glüge … & Emma L. Schymanski
Additional file 2: Overview of the NORMAN-SLE website (DOCX format) as of 30 May 2022 [82].

Additional file 1 of Combined, sequential dye analysis and radiocarbon dating of single ancient textile yarns from a Nazca tunic

Gregory D. Smith, Victor J. Chen, Amanda Holden, Negar Haghipour & Laura Hendriks
Additional file 1: Table S1. Table of LC–DAD–MS data of dyes. Figure S2. Library of UV–vis, FSMS, and MS/MS spectra for dye compounds identified in this study sorted by retention time. Figure S3. Chromatogram of red fiber extract, Sample 3A. Figure S4. Chromatogram of black fiber, Sample 5, extracted with oxalic acid/water/DMSO. Figure S5. Chromatogram of brown fiber extract, Sample 4A. Table S6. Table of 14C dating data. Figure S7. Calibration plot of 14C dating...

Additional file 3 of Infant behavioral state and stool microbiome in infants receiving Lactocaseibacillus rhamnosus GG in formula: randomized controlled trial

Robert J. Shulman, Maciej Chichlowski, Fabiola Gutierrez Orozco, Cheryl L. Harris, Jennifer L. Wampler, Nicholas A. Bokulich & Carol Lynn Berseth
Additional file 3: Supplemental Figure 2. Random Forest classification (with 10-fold cross-validation) correctly predicts study feeding group 80% (±17.95%) on average. Panel A shows a receiver operating curve, indicating that both groups could be predicted with a high degree of accuracy vs. random chance. Panel B shows the relative importance scores for the top five most predictive sequence variants. The predictive potential was powered by a very small number of sequence variants; the top two...

Additional file 1 of MP4: a machine learning based classification tool for prediction and functional annotation of pathogenic proteins from metagenomic and genomic datasets

Ankit Gupta, Aditya S. Malwe, Gopal N. Srivastava, Parikshit Thoudam, Keshav Hibare & Vineet K. Sharma
Additional file 1. Table S1: The complete list of variables with the mean decrease in accuracy values.

Additional file 2 of MP4: a machine learning based classification tool for prediction and functional annotation of pathogenic proteins from metagenomic and genomic datasets

Ankit Gupta, Aditya S. Malwe, Gopal N. Srivastava, Parikshit Thoudam, Keshav Hibare & Vineet K. Sharma
Additional file 2. Table S2: The different parameters used for the optimisation of the SVM based classifier.

Additional file 7 of MP4: a machine learning based classification tool for prediction and functional annotation of pathogenic proteins from metagenomic and genomic datasets

Ankit Gupta, Aditya S. Malwe, Gopal N. Srivastava, Parikshit Thoudam, Keshav Hibare & Vineet K. Sharma
Additional file 7. List of important features obtained by VarImp function in SVM.

Registration Year

  • 2022
    63
  • 2021
    11
  • 2020
    2
  • 2019
    5

Resource Types

  • Text
    81

Affiliations

  • ETH Zurich
    73
  • Indian Institute of Science Education and Research, Bhopal
    11
  • Uppsala University
    11
  • Smithsonian Tropical Research Institute
    8
  • Università della Svizzera Italiana
    8
  • University of Granada
    7
  • Spanish National Research Council
    6
  • Helmholtz Zentrum München
    5
  • Baylor College of Medicine
    5
  • Yale University
    5