Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
2,107
datasets available to search
ShareScore release 0.9.0
Dataset results
2,107 results for “Spectrum”
Data for: Size spectrum model reveals importance of considering species interactions in a freshwater fisheries management context
<p>Inland fisheries have significant cultural and economic value around the globe, providing dietary protein, income, and recreation. Consequently, methods for monitoring and managing these important fisheries are continually being refined. In marine systems, multi-species size spectrum models have been increasingly used to explore management scenarios of important fish stocks within an ecosystem-based fisheries management framework; however, these models have not been applied in freshwater systems. In this study, we developed a multi-species size spectrum model for the fish community of Lake Nipissing, a large, productive lake in Ontario, Canada. To the best of our knowledge, this is the first fully calibrated multi-species size spectrum model for an inland fishery. Using this model, we explored the impacts of different management scenarios on fish community dynamics while taking species interactions into account. Specifically, we examined how changes in fishing mortality affect: (1) species biomass; (2) community size structure; and (3) stock recovery times. We found that community dynamics following changes in fishing mortality were driven by complex interactions among species, including competition and predation. The greatest changes in biomass and community size structure were observed following changes in fishing mortality to top predators, with community size structure most strongly influenced by changes in mortality to the largest species in the community. Counter to predictions based on generation time, the smallest species in our model exhibited the longest time to recovery due to strong competition and predation. Our results demonstrate the importance of taking an ecosystem-based approach and considering species interactions in the management of inland fisheries and highlight the potential of size spectrum model use in freshwater systems.</p>
Spectrum of Open Methods
<p>In order for Open Methods to mitigate resource barriers to linguistics research, the Open Methods themselves must not act as or require <em>substantial</em> resource barriers to access and use. We emphasize "substantial" here because there is no such thing as an absence of resource barriers; just because an Open Method is freely <em>available</em> online doesn't make it <em>accessible</em> to everyone. To evaluate this aspect of Open Methods, we build on similar widely-used tools in the Open Access space to create a "Spectrum of Open Methods".</p> <p>This tool is not meant to gatekeep open methods; a method that's imperfect but published is always more open than a method that never gets published because it's not perfect yet. Rather, the Spectrum of Open Methods is intended to inspire creators to make adjustments to their resources to make them as open as possible. To illustrate, a Case Study is included where Dan Villarreal has deployed the Spectrum of Open Methods to one of his projects and identified avenues for future development and improvement.</p> <p>We developed this tool while working on a chapter titled "Open Methods: Decolonizing (or not) research methods in linguistics" for the forthcoming volume <em>Decolonizing Linguistics </em>edited by Anne Charity Hudley, Christine Mallinson, and Mary Bucholtz and published by Oxford University Press. We welcome iterations of this Spectrum of Open Methods with edits, adaptations to other fields, or discipline-specific adjustments.</p>
Phenotypic plasticity and the leaf economics spectrum: plasticity is positively associated with specific leaf area
<p>Phenotypic plasticity is a key mechanism by which plants respond to changing or heterogeneous conditions. Efforts to predict phenotypic plasticity across plant species have mainly focused on environmental variability or abiotic conditions, i.e., site characteristics. However, the considerable variation in phenotypic plasticity within sites calls for alternative approaches. Different functional groups are thought to differ in their plasticity levels. Further, traits such as leaf specific area (SLA), leaf area (LA) and maximum photosynthetic rate (Amax) reflect central aspects of plant strategies. Lower values of SLA, LA and Amax are indicative of a resource-conservative strategy, which is thought to be associated with lower phenotypic plasticity. We used meta-analytical data to test whether plant functional group (herbs, woody deciduous and woody evergreens) and SLA, LA and Amax are associated with phenotypic plasticity in four trait types: biomass allocation, plant size, leaf morphology and physiology. We obtained data from 168 plant species and accounted for phylogenetic relationships in all analyses. We found a positive relationship between SLA and phenotypic plasticity in biomass allocation, leaf morphology and physiology, with differences across functional groups. In contrast, there was no evidence of greater plasticity in plant size in species with higher SLA; rather the opposite was true for woody evergreens. Amax and LA showed similar, but less consistent associations with phenotypic plasticity. Our results show the potential of building predictive frameworks for phenotypic plasticity based on easily measured plant functional characteristics. Results also provide insights into plant strategies and suggest the existence of potential compromises: resource-conservative, low-SLA species tend to be more stress-tolerant but may be less able to cope with variable conditions due to their generally lower phenotypic plasticity. Further studies are needed to explore the mechanisms and the potential implications of this association.</p>
Intraspecific variation and economics spectrum of Phragmites australis in lakeshore wetland of (semi-) arid regions
<p><em>Phragmites australis</em>, as a widely distributed species, has a high degree of intraspecific variation in functional traits and is able to respond to external climatic and environmental changes and adjust its adaptation strategies on time. The plant economic spectrum can reflect the adaptation strategies of resource acquisition and storage of plants in different climatic regions, and provide a scientific basis for understanding the ecological differentiation of plants in different habitats and their adaptation mechanisms. In this study, the morphological traits, nutrient contents and stoichiometric ratios of <em>P. australis</em> in lakes and lakeshore wetlands of semi-arid and arid climatic regions from east to west in Inner Mongolia Plateau were investigated to reveal the variability of plant functional traits at different regional scales and the influencing factors, and to reveal the ecological adaptation strategies of <em>P. australis</em> in different regions through plant economic spectrum. The results showed that soil moisture gradient, geographic location and regional scale effected the intraspecific variation of functional traits of <em>P. australis</em>. At the local scale, soil moisture gradients had opposite effects on the response to functional traits of <em>P. australis</em> in the arid and semi-arid regions. At the regional scale, climatic factors dominated the variation of reed functional traits across the latitudinal gradient, while the correlation with soil properties was not significant (<em>P</em> > 0.05). Plant economic spectrum theory is also applicable to the functional traits of various organs and whole plants of <em>P. australis</em> populations at different regional scales, and the acquisition and assimilation of resources is conservative in arid regions, while in semi-arid regions it is an acquisition strategy. This study provides a new understanding of the ecological niche differentiation and drivers of plant populations and ecological adaptation strategies of species at the regional scale, and provides a theoretical basis for the restoration and reconstruction of degraded wetland ecosystems.</p>
Direct prediction for carbapenemase-producing and colistin-resistant Klebsiella pneumoniae isolates from routine MALDI-TOF mass spectrum using machine learning
<p>The emergence of carbapenem-nonsusceptible K. pneumoniae (CnSKP) leads a serious threat to patient survival and colistin resistance makes the treatment of CnSKP more difficultly. To make treatment strategy properly and quickly, we aimed to develop a rapid prediction method for CnSKP and colistin-resistant K. pneumoniae (ColRKP) based on the spectra of routine matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI–TOF MS). The machine learning (ML) model for differentiating CnSKP and carbapenem-susceptible K. pneumoniae (CSKP) showed accuracy of 0.8869 and AUC of 0.9551; the model for ColRKP and colistin-intermediate K. pneumoniae (ColIKP) showed accuracy of 0.8361 and the AUC of 0.8447.</p>
Trait coordination in boreal mosses reveals a bryophyte economics spectrum
<p>1. The study of plant trait spectra and their association with trade-offs in resource use strategy has greatly advanced our understanding of vascular plant function, yet trait spectra remain poorly studied in bryophytes, particularly outside of the Sphagnum genus. Here, we measured 25 traits related to carbon, nutrient, and water conservation in 60 moss canopies (each dominated by one of 15 moss species) across diverse boreal forest habitats, and used bi-variate correlations and multi-variate analyses to assess trait coordination and trait spectra.</p> <p>2. We found substantial trait coordination along a main principal components axis driven by trade-offs in carbon, nutrient, and water conservation strategies. Along this trait spectrum, traits varied from resource-acquisitive at one end (e.g., high maximum photosynthetic capacity, high tissue nitrogen content, low water holding capacity) to resource-conservative at the other end, in line with resource economics theory.</p> <p>3. Traits related to carbon turnover (photosynthesis and respiration rates, litter decomposability) were positively related to nitrogen content and to desiccation rates, in line with global trait spectra in vascular plants. However, architectural traits of the moss shoots and of the moss canopy were generally unrelated to the main axis of trait variation and formed a secondary axis of trait variation, contrary to what is observed for vascular plants.</p> <p>4. Resource-conservative trait spectra dominated in moss canopies from open and wet habitats (i.e., mires), indicating that high irradiance and possibly high moisture fluctuation induce a resource-conservative trait strategy in mosses.</p> <p>5. Synthesis. Our work suggests that trait relationships that are well established for vascular plants can be extended for bryophytes as well. Bryophyte trait spectra can be powerful tools to improve our understanding of ecosystem processes in moss-dominated ecosystems, such as boreal or arctic environments, where bryophyte communities exert strong control on nutrient and carbon cycling.</p>
Data files for "Curvature in the very-high energy gamma-ray spectrum of M87"
<h1>Summary</h1> <p>In this repository, we provide some auxiliary material in connection to our paper “Curvature in the very-high energy gamma-ray spectrum of M87" accepted for publication in the Astronomy and Astrophysics (A&A) Journal and available on Arxiv through the ID <a href="https://arxiv.org/abs/2402.13330" target="_blank" rel="noopener">arXiv:2402.13330</a>. For the full list of authors, please refer to the paper.</p> <p>In the publication, we study the very-high energy gamma-ray spectrum of a stacked high emission state of M87 using H.E.S.S. observations. We detect a curvature in the spectrum that is not related to the EBL absorption. In addition to that, we show that the gamma-gamma absorption by star light from the galaxy is weak to explain the measured curvature and that it is unlikely that different high states with similar spectral distribution could be able to explain the same curvature.</p> <h1>Data and example code</h1> <h2>ECSV tables</h2> <p>The ecsv tables provide the means to reproduce the figures found in the paper. They can be opened with `astropy.QTable` as demonstrated below.</p> <pre><code>from astropy.table import QTable table = QTable.read('Fig1_lightcurve_table.ecsv') print(table)</code></pre> <p>The following example shows how to reproduce Fig. A2 from the paper (the modules imported are needed in the loaded enviroment):</p> <pre><code>from astropy.table import QTable from scipy.stats import gmean %matplotlib inline import matplotlib.pyplot as plt import numpy as np import seaborn as sns from ebltable.ebl_from_model import EBL cmap = sns.color_palette("colorblind", as_cmap=True) colors = sns.color_palette("colorblind", 6) ebl = {} for m in ["finke2022", "kneiske", "dominguez-upper"]: ebl[m] = EBL.readmodel(m) lmu = np.logspace(-1,3.,100) z = 0.0042 nuInu = {} for m, e in ebl.items(): nuInu[m] = e.ebl_array(z,lmu) nuInu table = QTable.read('FigA2_EBL_ULs.ecsv') wavelengths = table["Wavelength"].value wavelengths = wavelengths counter = 0 for m in ["finke2022", "kneiske", "dominguez-upper"]: plt.loglog(lmu,nuInu[m], lw = 2.,label=f"{m} UL", color=colors[counter] ) ULs = table[f"{m} UL"][(wavelengths>12.4)*(wavelengths<40)].value plt.loglog(wavelengths[(wavelengths>12.4)*(wavelengths<40)],ULs, lw = 2., label = f"UL (this work)", ls='dashed', color=colors[counter]) plt.arrow(gmean(wavelengths[(wavelengths>12.4)*(wavelengths<40)]), np.median(ULs), 0, -0.2*np.median(ULs), head_width=5 ,head_length=0.1*np.median(ULs), alpha=0.5, color=colors[counter]) counter+=1 plt.gca().set_xlabel('Wavelength ($\mu$m)',size = 'x-large') plt.gca().set_ylabel(r'$\nu I_\nu (\mathrm{nW}\,\mathrm{sr}^{-1}\mathrm{m}^{-2})$',size = 'x-large') plt.legend(loc = 'lower center', ncol = 2) plt.tight_layout() plt.show()</code></pre> <h2>Text files</h2> <p>The text files provide the gammapy fit results for the various analyses in the main text of the paper. For a complete definition of the models, we refer the reader to the paper. The name of the file is given by <em>fit_stacked_M87_<strong>MODEL</strong>_flux_90perc_<strong>ENERGYRANGE</strong>_90perc.txt</em>, where <strong>MODEL</strong> is the spectral model fitted (e.g., <em>PLxEBLfinke2022</em> or <em>PLxEBLfinke2022-free</em> in case the EBL intensity alpha_norm is a free parameter) and <strong>ENERGYRANGE</strong> is the energy range of the reduced dataset (e.g., <em>0.3_31.6TeV</em>).</p> <p> </p>
Data from: Signature of altered retinal microstructures and electrophysiology in schizophrenia spectrum disorders is associated with disease severity and polygenic risk
<p>This dataset contains supporting data for the publication: </p> <p>Boudriot, E.<em> et al.</em> Signature of altered retinal microstructures and electrophysiology in schizophrenia spectrum disorders is associated with disease severity and polygenic risk. <em>Biological Psychiatry</em><span> </span><a href="https://doi.org/10.1016/j.biopsych.2024.04.014">https://doi.org/10.1016/j.biopsych.2024.04.014</a></p> <p> </p> <p>Files:</p> <ul> <li><em>clinical.csv </em>contains data from clinical assessment and polygenic risk scores for schizophrenia</li> <li><em>ophthalmic_examination.csv </em>contains data on spherical equivalent, intraocular pressure and visual acuity</li> <li><em>oct.csv </em>contains segmentation output from Iowa Reference Algorithms</li> <li><em>erg.csv </em>contains pre-processed ERG data for the four ERG conditions</li> <li><em>mri.csv </em>contains ICV-corrected MRI volumes</li> </ul>
Supplementary Material for "The Anion Photoelectron Spectrum and Diabatization of Tetrazolyl"
<p>This is the supplementary material for "The Anion Photoelectron Spectrum and Diabatization of Tetrazolyl."</p> <p>The file "README - table of contents.pdf" lays out what information and data is present in each file.</p>
JWST MIRI MRS spectrum of IC 348
<p>This spectrum was extracted from the IFU cube (which was downloaded via the MAST platform, from the GTO program ID 1236 (PI Michael Ressler) ) using a circular aperture of radius 1.15”, centered on coordinates (3:43:56.980,+32:03:03.98).</p> <p>First column correcponds to wavelength in microns, the second column to flux in MJy/sr.</p> <p>All JWST MIRI MRS channels are included in one single spectrum.</p> <p> </p>
Relative importance of intensity and spectrum of artificial light at night in disrupting behavior of a nocturnal rodent
<p>The influence of light spectral properties on circadian rhythms is of substantial interest to laboratory-based investigation of the circadian system and to field-based understanding of the effects of artificial light at night. The tradeoffs between intensity and spectrum regarding masking behaviors are largely unknown, even for well-studied organisms. We used a custom LED illumination system to document the response of wild type house mice (Mus musculus) to 1-hr nocturnal exposure of all combinations of four intensity levels (0.01, 0.5, 5, and 50 lx) and three correlated color temperatures (CCT; 1750, 1950, and 3000 K). Higher intensities of light (50 lx) suppressed cage activity substantially, and consistently more for the higher CCT light (91% for 3000 K; 53% for 1750 K). At the lower intensities (0.01 lx), mean activity was increased, with the greatest increases for the lowest CCT (12.3% increase at 1750 K; 3% increase at 3000 K). Multiple linear regression confirmed the influence of both CCT (p&lt;0.001) and intensity (p&lt;0.001) on changes in activity (r2=0.66, F9,171=3.33; p<0.001) with the scaled effect size of intensity 3.6 times greater than CCT. Activity suppression was significantly lower for male than female mice (p&lt;0.0001). Assessment of light-evoked cFos expression in the suprachiasmatic nucleus at 50 lx showed no significant difference between high and low CCT exposure. The significant differences by spectral composition illustrate a need to account for light spectrum in circadian studies of behavior and confirm that spectral controls can mitigate some, but certainly not all, of the effects of light pollution on species in the wild.</p>
"Adaptive Radial Projection on Fourier Magnitude Spectrum for Document Image Skew Estimation"
<p>We build DISE2021 datasets from 95 images from DISEC2013 dataset [12], 70 images from RDCL dataset [22], and 324 images from RVL-CDIP dataset [14]. The composed datasets contains various types of documents, multiple languages, and typography features. Firstly, all the images are ensured and verified to be in a straight position. Secondly, we use the generating algorithm as in [12] to generate skew images in the range −15 to +15 skew degree. The dataset is split into two development/test sets by a ratio of 0.7/0.3 that results in 3399 development images and 1491 testing images. When generating the skew dataset in the range from −44.9 to 44.9 skew degree, we double the augmented image that results in 6980 development images and 2800 testing images. </p> <p>Note: This datasets are built upon three other datasets: DISEC 2013, RVL-CDIP, RDCL 2017. So I urge you to respect their LICENSE.</p>
Inverse Design of Metamaterials with Manufacturing-Aware Spectrum-to-Shape Diffusion Models
<p>The dataset includes detailed information on the MIM tri-layer metamaterial structures designed and used for training the DiffMeta framework. Specifically, it contains 60000 data:</p> <p>Structural Data: Detailed geometric patterns and composition parameters of the designed MIM tri-layer metamaterial structures.</p> <p>Spectral Data: Spectral measurements on MIM tri-layer metamaterial structures, including emissivity, reflectivity and transmittance spectra across a range of wavelengths.<br><br>The dataset is meticulously organized to facilitate the replication of our study and support further research in the field of metamaterial design. </p>
Unified Clumpy AGN Torus Model and X-ray spectrum
<p>In Buchner et al. (in prep) we develop a geometry for the X-ray obscurer of AGN. Its cloud population is consistent with existing CLUMPY (Nenkova+02) infrared models. However, we find that a inner torus ring component is required to fit local Compton-thick AGN.</p> <p>More information at <a href="https://github.com/JohannesBuchner/xars/blob/master/doc/uxclumpy.rst">https://github.com/JohannesBuchner/xars/blob/master/doc/uxclumpy.rst</a></p> <p>Our model has two geometry parameter:<br> 1) The opening of the torus, or the vertical extent of the clouds (sigma)<br> 2) The covering of the inner Compton-thick wall.<br> Further parameters are:<br> 3) Photon index and energy cut-off of the corona<br> 4) Column density in the line of sight (up to 10^26)<br> 5) Viewing angle.</p> <p>We release XSPEC table spectra here.</p>
Animated plots of the spectrum and polarisation of Cassiopeia A based on a 24 hour observation with LOFAR Station IE613 (LBA)
<p>This collection of animated plots over time of the variation in channel flux for the linear polarisation channels XX, XY and YY and Stokes Parameters U, V, I and Q against frequency for Cassiopeia A as observed at LOFAR station SE607 between 2018-04-06 and 2018-04-07 using the LBA</p>
Animated plots of the spectrum and polarisation of Cassiopeia A based on a 24 hour observation with LOFAR Station IE613 (LBA)
<p>This collection of animated plots over time of the variation in channel flux for the linear polarisation channels XX, XY and YY and Stokes Parameters U, V, I and Q against frequency for Cassiopeia A as observed at LOFAR station IE613 between 2018-04-06 and 2018-04-07 using the LBA</p>
5G-Xcast Open Spectrum data 5/6
<p>This dataset is part 5/6 of the open spectrum measurement data from Horizon 2020 -funded 5G-PPP project 5G-Xcast.</p> <p>The whole dataset includes a continuous 8-day period of spectrum data from January 20<sup>th</sup> to January 27<sup>th</sup><strong><sup> </sup></strong>from four years, 2015 to 2018.</p> <p>The data and the measurement system is described in the Open Spectrum data.pdf file.</p>
5G-Xcast Open Spectrum data 6/6
<p>This dataset is part 6/6 of the open spectrum measurement data from Horizon 2020 -funded 5G-PPP project 5G-Xcast.</p> <p>The whole dataset includes a continuous 8-day period of spectrum data from January 20<sup>th</sup> to January 27<sup>th</sup><strong><sup> </sup></strong>from four years, 2015 to 2018.</p> <p>The data and the measurement system is described in the Open Spectrum data.pdf file.</p>
5G-Xcast Open Spectrum data 4/6
<p>This dataset is part 4/6 of the open spectrum measurement data from Horizon 2020 -funded 5G-PPP project 5G-Xcast.</p> <p>The whole dataset includes a continuous 8-day period of spectrum data from January 20<sup>th</sup> to January 27<sup>th</sup><strong><sup> </sup></strong>from four years, 2015 to 2018.</p> <p>The data and the measurement system is described in the Open Spectrum data.pdf file.</p>
5G-Xcast Open Spectrum data 2/6
<p>This dataset is part 2/6 of the open spectrum measurement data from Horizon 2020 -funded 5G-PPP project 5G-Xcast.</p> <p>The whole dataset includes a continuous 8-day period of spectrum data from January 20<sup>th</sup> to January 27<sup>th</sup><strong><sup> </sup></strong>from four years, 2015 to 2018.</p> <p>The data and the measurement system is described in the Open Spectrum data.pdf file.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.