cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10638735
title: Data for the preprint of "Layer-by-layer unsupervised clustering of statistically relevant fluctuations in noisy time-series data of complex dynamical systems"

description: README: description of the files. 

This Zenodo repository contains all the data and original code necessary to reproduce the results of the paper https://doi.org/10.48550/arXiv.2402.07786. The code (continuously mantained and updated) is available open-source as a Python package at https://pypi.org/project/onion-clustering/ and on GitHub (https://github.com/matteobecchi/timeseries_analysis). 

The repository contains the folders "Fig1", "Fig2" etc, which contain the corresponding Datasets, together with the code to reproduce the figures. Additionally, the folder "FigS1 contains code and data for FigS1. 

The repository also contains the Supplementary Movies S1 to S4, in .mp4 format.
DOI: 10.5281/zenodo.10854843
title: Data from: Unexpected stability in faunal population abundances following an estuary-wide collapse of oysters

description: Data describing the number and lengths of fish and macroinvertebrates sampled from long-term fisheries independent sampling in Florida’s coastal waters. Original data were collected by the Florida Fish and Wildlife Conservation Commission (FWC) Fish and Wildlife Research Institute (FWRI).
description: Live oyster reefs are considered a critical recruitment habitat for estuarine faunal populations as localized in-situ or mesocosm studies have demonstrated many faunal species prefer live oyster habitat. It has therefore been assumed that the loss of live oyster habitat would precipitate faunal population declines, but this has been largely untested at large (estuary) scales. Here, we assessed how estuary-wide faunal populations were affected by a 95% loss of live oyster habitat following the 2012 oyster collapse of Apalachicola Bay, FL – which previously supported one of the largest oyster fisheries in the United States. We standardized long-term fisheries-independent monitoring seine and trawl data to create relative indices of resident, associated, and transient faunal species’ overall abundance and recruit abundance (restrictive to sizes between 15–35% of  ). We expected that both relative abundance indices would decrease following the oyster collapse, particularly among species that reside on or recruit to oyster reefs. However, analyses via a series of one-sided Bayesian t-tests did not indicate that faunal recruitment or overall abundance significantly declined in 2012 post-collapse. As the response of the faunal population could be lagged relative to the 2012 collapse, we also conducted change point analyses to search for lagged declines. Of the 24 relative abundance time series, only two had significant change points post-collapse, and only black sea bass overall relative abundance declined with an associated changepoint at the end of the time series. The surprising paucity of faunal decline following oyster loss may be due to the use of alternative habitat types, exceptionally lagged faunal responses, or, perhaps most compelling, a disconnect between preferred and required habitat. Our failure to detect faunal consequences following an oyster population collapse suggests that assumptions of habitat loss (or restoration) effects on estuarine fauna at ecosystem scales are not straightforward and the extrapolation of sub estuary-scale studies may result in poor predictions of future outcomes.
DOI: 10.5281/zenodo.7261921
title: MicroBooNE BNB Electron Neutrino Overlay Sample (No Wire Info)

description: MicroBooNE samples are provided for collaborative development in two different formats: HDF5, targeting the broadest audience, and artroot, targeting users that are familiar with the software infrastructure of Fermilab neutrino experiments and more in general of HEP experiments. The HDF5 files are stored on Zenodo, together with a list of artroot files accessible with xrootd. This sample includes simulated interactions of neutrinos from the Booster Neutrino Beam (BNB), overlaid on top of cosmic ray data. The sample is restricted to charged-current electron neutrino interactions within the argon active volume of the time projection chamber. The HDF5 files in this sample do not include the information at the wire waveform level ("NoWire" label), allowing for larger number of events to be included in the data set. More documentation, including detailed description of content, recipes, and example usage, at https://github.com/uboone/OpenSamples. Suggested text for acknowledgment is the following:<br> <em>We acknowledge the MicroBooNE Collaboration for making publicly available the data sets [data set DOIs] employed in this work. These data sets consist of simulated neutrino interactions from the Booster Neutrino Beamline overlaid on top of cosmic data collected with the MicroBooNE detector [2017 JINST 12 P02017].</em> In addition, we request that software products resulting from the usage of the datasets are also made publicly available.
description: This data set was prepared by the MicroBooNE collaboration using the resources of the Fermi National Accelerator Laboratory (Fermilab), a U.S. Department of Energy, Office of Science, HEP User Facility. Fermilab is managed by Fermi Research Alliance, LLC (FRA), acting under Contract No. DE-AC02-07CH11359. MicroBooNE is supported by the following: the U.S. Department of Energy, Office of Science, Offices of High Energy Physics and Nuclear Physics; the U.S. National Science Foundation; the Swiss National Science Foundation; the Science and Technology Facilities Council (STFC), part of the United Kingdom Research and Innovation; the Royal Society (United Kingdom); and the UK Research and Innovation (UKRI) Future Leaders Fellowship. Additional support for the laser calibration system and cosmic ray tagger was provided by the Albert Einstein Center for Fundamental Physics, Bern, Switzerland. We also acknowledge the contributions of technical and scientific staff to the design, construction, and operation of the MicroBooNE detector as well as the contributions of past collaborators to the development of MicroBooNE analyses, without whom this work would not have been possible. For the purpose of open access, the authors have applied a Creative Commons Attribution (CC BY) public copyright license to this submission.
DOI: 10.5281/zenodo.8370883
title: MicroBooNE BNB Inclusive Overlay Sample (No Wire Info)

description: MicroBooNE samples are provided for collaborative development in two different formats: HDF5, targeting the broadest audience, and artroot, targeting users that are familiar with the software infrastructure of Fermilab neutrino experiments and more in general of HEP experiments. The HDF5 files are stored on Zenodo, together with a list of artroot files accessible with xrootd. This sample includes simulated interactions of neutrinos from the Booster Neutrino Beam (BNB), overlaid on top of cosmic ray data. The sample is inclusive, i.e. it includes all types of neutrinos and interactions, with relative abundance matching our nominal flux and cross section models. Interactions are simulated in in the whole cryostat volume. The HDF5 files in this sample do not include the information at the wire waveform level ("NoWire" label), allowing for larger number of events to be included in the data set. More documentation, including detailed description of content, recipes, and example usage, at https://github.com/uboone/OpenSamples. Suggested text for acknowledgment is the following:<br> <em>We acknowledge the MicroBooNE Collaboration for making publicly available the data sets [data set DOIs] employed in this work. These data sets consist of simulated neutrino interactions from the Booster Neutrino Beamline overlaid on top of cosmic data collected with the MicroBooNE detector [2017 JINST 12 P02017].</em> In addition, we request that software products resulting from the usage of the datasets are also made publicly available.
description: This data set was prepared by the MicroBooNE collaboration using the resources of the Fermi National Accelerator Laboratory (Fermilab), a U.S. Department of Energy, Office of Science, HEP User Facility. Fermilab is managed by Fermi Research Alliance, LLC (FRA), acting under Contract No. DE-AC02-07CH11359. MicroBooNE is supported by the following: the U.S. Department of Energy, Office of Science, Offices of High Energy Physics and Nuclear Physics; the U.S. National Science Foundation; the Swiss National Science Foundation; the Science and Technology Facilities Council (STFC), part of the United Kingdom Research and Innovation; the Royal Society (United Kingdom); and the UK Research and Innovation (UKRI) Future Leaders Fellowship. Additional support for the laser calibration system and cosmic ray tagger was provided by the Albert Einstein Center for Fundamental Physics, Bern, Switzerland. We also acknowledge the contributions of technical and scientific staff to the design, construction, and operation of the MicroBooNE detector as well as the contributions of past collaborators to the development of MicroBooNE analyses, without whom this work would not have been possible. For the purpose of open access, the authors have applied a Creative Commons Attribution (CC BY) public copyright license to this submission.
DOI: 10.57780/sm1-857c3d7
title: SMOS L2 SM V700

description: SMOS L2 SM version 700
DOI: 10.6084/m9.figshare.21647759.v1
title: Oak Leaf Data

description: Oak leaf data set of "Temperature dependence of the dielectric function of dehydrated biological samples in the THz band" <br> The data is stored in a way that the columns represent the following information: <br> Column | information 1 | Frequency [THz] 2 - 6 | real part refractive index 7 - 11 | error real part refractive index 12 - 16 | imaginary part refractive index 17 - 21 | error imaginary part refractive index 22 - 26 | absorption coefficient [1/cm] 27 - 31 | error absorption coefficient [1/cm] 32 - 36 | real part dielectric function 37 - 41 | error real part dielectric function 42 - 46| imaginary part dielectric function 47 - 51| error imaginary part dielectric function <br> Subsequent columns show the information for different temperatures @ 20, 22.5, 27.5, 32.5, 36.5 °C. <br> So that for example: <br> n @ 20.0°C | n @ 22.5°C | n @ 27.5°C | n @ 32.5°C | n @ 36.5°C <br> The data sets represent processed data. <br>
DOI: 10.6084/m9.figshare.24975111
title: Data of "Global inland-water nitrogen cycling has accelerated in the Anthropocene"

description: Data of Wang et al. "Global inland-water nitrogen cycling has accelerated in the Anthropocene"
DOI: 10.6084/m9.figshare.25205219.v1
title: <b>Deciphering the Interplay of Age, Gender, Education, and Heart Rate in Dementia among the Elderly Population of Wakiso, Uganda</b>

description: <b>Introduction</b>: Dementia, a critical public health concern, involves a complex interplay of risk factors that are prominently influenced by age.<b>Aim</b>: Our study, conducted in Wakiso, Uganda, aimed to investigate the intricate interactions among age, sex, heart rate, and education in relation to dementia.<b>Methods</b>: Using a cross-sectional design from February to July 2023, we sampled 106 individuals aged 65 years and older, focusing on Alzheimer's disease and related dementia.<b>Results:</b> The findings revealed an age-related increase in the risk of Mild Cognitive Impairment (MCI) and dementia, with a 1.19- and 1.22-times escalation, respectively, for each year. Being male demonstrated a protective effect against MCI, and education was correlated with a 28% risk reduction in MCI. The unclear association between education and dementia prompted further research. An elevated heart rate was significantly associated with a higher risk of both MCI and dementia. Sex did not affect the risk of developing dementia.<b>Conclusion:</b> Our study offers nuanced insights into dementia risk factors, emphasizing age susceptibility, sex distinctions, educational protection, and the cardiovascular dimension. Further research is essential to elucidate the mechanisms of and interventions for healthy cognitive aging.
DOI: 10.6103/share.w8ca.900
title: Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 8. COVID-19 Survey 1
DOI: 10.15156/bio/sh0957464.10fu
title: SH0957464.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0957465.10fu
title: SH0957465.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.21227/9p2y-yq09
title: ISIC Melanoma Dataset

description: This robust dataset is extracted from the International Skin Imaging Collaboration (ISIC). Similar datasets are used for the annual ISIC Challenge, presenting an opportunity for the computer science community to produce algorithms that can outperform professional dermatology. The submitted dataset contains approximately 1,000 images of malignant melanomas, as well as approximately 1,000 images of benign melanomas. The general purpose of the dataset is to present an opportunity for cutting-edge image classification algorithms to find patterns between the respective groups of images, both for the advancement of deep learning solutions as well as to build potential life-saving applications in the field of medical imaging.
DOI: 10.15156/bio/sh0957466.10fu
title: SH0957466.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0957467.10fu
title: SH0957467.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0957468.10fu
title: SH0957468.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0957469.10fu
title: SH0957469.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0957470.10fu
title: SH0957470.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0957471.10fu
title: SH0957471.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0957472.10fu
title: SH0957472.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.