Find research datasets worth reusing

opencc-zeroSep 2020View details →

Is sexual conflict a driver of speciation? a case study with a tribe of brush-footed butterflies

Understanding the evolutionary mechanisms governing the uneven distribution of species richness across the tree of life is a great challenge in biology. Scientists have long argued that sexual conflict is a key driver of speciation. This hypothesis, however, has been highly debated in light of empirical evidence. Recent advances in the study of macroevolution make it possible to test this hypothesis with more data and increased accuracy. In the present study, we use phylogenomics combined with four different diversification rate analytical approaches to test whether sexual conflict is a driver of speciation in brush-footed butterflies of the tribe Acraeini. The presence of sphragis, an external mating plug found in most species among Acraeini, was used as a proxy for sexual conflict. Diversification analyses statistically reject the hypothesis that sexual conflict is associated with shifts in diversification rates in Acraeini. This result contrasts with earlier studies and suggests that the underlying mechanisms driving diversification are more complex than previously considered. In the case of butterflies, natural history traits acting in concert with abiotic factors possibly play a stronger role in triggering speciation than does sexual conflict.

opencc-zeroSep 2020View details →

Data from: Linking land use and the nutritional ecology of herbivores: a case study with the Senegalese locust

1) Access to high-quality food is a main driver of population dynamics. For herbivores protein and carbohydrates are key nutrients that are notoriously variable in plants and are affected by land use. However, few studies have linked foraging decisions and performance in the laboratory to the nutritional landscape available in the field. 2) Oedaleus senegalensis is a nonmodel locust, a grass-feeder, and the main pest of millet, a subsistence crop in the Sahel. In this study, we examined dietary preference and locust performance across a range of protein:carbohydrate ratios using the Geometric Framework methodology. We then applied a fitness landscape approach to visualize these results with the plant nutrient contents available across four land-use types: millet, groundnut, fallow, and grazed fields. Finally, we contrasted our results with locust distribution in the field. Several locust species (O. senegalensis included) exhibit density dependent color polymorphism thus we also reported individual coloration (brown or green). 3) We found that O. senegalensis preferred moderately carbohydrate-biased food 1:1.6 protein: carbohydrate ratio. All traits recorded (mass gain, development time, growth rate, molt success, and performance index) were best near that ratio and declined on either side presenting a "hump-shape". Fallow fields contained more plants, particularly grasses, that were both abundant and closer to the optimal protein:carbohydrate ratio recorded from the lab experiments. 4) When we surveyed O. senegalensis abundance and proportion, we found that they were more numerous in the fallow fields. Brown morph individuals, the ones associated with high density, were proportionally more abundant in fallow fields than green individuals. 5) Our study provides evidence that variation in nutritional landscapes—relative to an herbivore's optimal nutrient balance—is a key driver of herbivore population distribution and abundance, and can be used to predict bottom-up effects on herbivore species. protein:carbohydrate ratio recorded from the lab experiments.

opencc-by-4.0Oct 2020View details →

SmartUpLab- Co-Creation in sustainable mobility research - Systematic Reviews and Case Studies

The current dataset presents the results of systematic reviews and case studies about co-creation tools best practice for sustainable mobility, carried out in the context of the research project SmartUpLab (funded by EFRE).

opencc-by-4.0Oct 2020View details →

DAFNE Basemap for the Zambezi River Basin case study

Spatial dataset derived from many different open data repositories and cropped on the Zambezi River Basin boundary, used to create a base-map describing the components of Water-Energy-Food nexus in the case study. zambezi.gpkg: vector dataset including the following layers, together with the related map style for QGIS Desktop used in the DAFNE Geoportal basemap: <ul> <li>basin: Hydrological basin of the Zambezi river (case study boundary)</li> <li>subbasin: Basins of the main tributaries of the Zambezi River</li> <li>waterbodies: Natural lakes and reservoirs boundaries</li> <li>rivers: River network</li> <li>stations: Streamflow, Water level and Rainfall Gauging stations</li> <li>dams: Existing dams</li> <li>wetlands: Wetlands</li> <li>protected_areas: Protected areas</li> <li>aei_pct_cells: Area equipped for irrigation, expressed as percentage of total area.</li> <li>roads: Main roads network</li> <li>cities: Main cities in the riparian countries</li> <li>countries: Administrative borders of riparian countries</li> <li>markers: DAFNE model components location, with existing and planned dams and power plants, irrigation schemes, environmental target areas.</li> </ul> zambezi_raster.zip: raster dataset including the following layers: <ul> <li>DEM_1km: Digital Elevation Model</li> <li>Global Surface Water: <ul> <li>change: Occurrence Change Intensity map provides information on where surface water occurrence increased, decreased or remained the same between 1984-1999 and 2000-2015</li> <li>extent: Maximum Water Extent shows all the locations ever detected as water over period 1984-2015</li> <li>occurence: Occurrence shows where surface water occurred between 1984 and 2015 and provides information concerning overall water dynamics.</li> <li>recurrence: Recurrence provides information concerning the inter-annual behaviour of water surfaces and captures the frequency with which water returns from year to year.</li> <li>seasonality: Seasonality map provides information concerning the intra-annual behaviour of water surfaces for a single year (2015) and shows permanent and seasonal water and the number of months water was present.</li> <li>transitions: Transitions map provides information on the change in surface water seasonality between the first and last years (between 1984 and 2015) and captures changes between the three classes of not water, seasonal water and permanent water.</li> </ul> </li> </ul> Original data sources includes: <ul> <li><a href="http://www.fao.org/aquastat/en/">AQUASTAT</a>, the FAO global information system on water resources and agricultural water management;</li> <li> <a href="https://www.naturalearthdata.com/">Natural Earth, </a> a public domain map dataset available at different scales; </li> <li> <a href="https://www.protectedplanet.net/en">Protected Planet, </a> the most up to date and complete source of data on protected areas and other effective area-based conservation measures, maintained by UNEP-WCMC and IUCN; </li> <li> <a href="https://www.openstreetmap.org/">OpenStreetMap</a>, a collaborative project to create a free editable map of the world; </li> <li> <a href="http://zamwis.wris.info/">ZAMWIS</a>, a management information system for the Zambezi River Basin; </li> <li> NASA's Shuttle Radar Topography Mission (<a href="http://srtm.csi.cgiar.org/">SRTM</a>) Digital Elevation Database; </li> <li> <a href="https://global-surface-water.appspot.com/.">Global Water Surface</a>, a virtual time machine that maps the location and temporal distribution of water surfaces at the global scale. </li> </ul>

opencc-by-4.0Oct 2020View details →

DAFNE Basemap for the Omo-Turkana Basin case study

Spatial dataset derived from many different open data repositories and cropped on the Omo-Turkana Basin boundary, used to create a base-map describing the components of Water-Energy-Food nexus in the case study. omo-turkana.gpkg: vector dataset including the following layers, together with the related map style for QGIS Desktop used in the DAFNE Geoportal basemap: <ul> <li>basin: Hydrological basin of the Omo-Turkana river (case study boundary)</li> <li>subbasin: Basins of the main tributaries</li> <li>waterbodies: Natural lakes and reservoirs boundaries</li> <li>rivers: River network</li> <li>dams: Existing dams</li> <li>protected_areas: Protected areas</li> <li>aei_pct_cells: Area equipped for irrigation, expressed as percentage of total area.</li> <li>roads: Main roads network</li> <li>cities: Main cities in the riparian countries</li> <li>countries: Administrative borders of riparian countries</li> <li>markers: DAFNE model components location, with existing and planned dams and power plants, irrigation schemes, environmental target areas.</li> </ul> zambezi_raster.zip: raster dataset including the following layers: <ul> <li>srtm_90m: Digital Elevation Model</li> <li>Global Surface Water: <ul> <li>change: Occurrence Change Intensity map provides information on where surface water occurrence increased, decreased or remained the same between 1984-1999 and 2000-2015</li> <li>extent: Maximum Water Extent shows all the locations ever detected as water over period 1984-2015</li> <li>occurence: Occurrence shows where surface water occurred between 1984 and 2015 and provides information concerning overall water dynamics.</li> <li>recurrence: Recurrence provides information concerning the inter-annual behaviour of water surfaces and captures the frequency with which water returns from year to year.</li> <li>seasonality: Seasonality map provides information concerning the intra-annual behaviour of water surfaces for a single year (2015) and shows permanent and seasonal water and the number of months water was present.</li> <li>transitions: Transitions map provides information on the change in surface water seasonality between the first and last years (between 1984 and 2015) and captures changes between the three classes of not water, seasonal water and permanent water.</li> </ul> </li> </ul> Original data sources include: <ul> <li><a href="http://www.fao.org/aquastat/en/">AQUASTAT</a>, the FAO global information system on water resources and agricultural water management;</li> <li> <a href="https://www.naturalearthdata.com/">Natural Earth,</a> a public domain map dataset available at different scales; </li> <li> <a href="https://www.protectedplanet.net/en">Protected Planet, </a> the most up to date and complete source of data on protected areas and other effective area-based conservation measures, maintained by UNEP-WCMC and IUCN; </li> <li> <a href="https://www.openstreetmap.org/">OpenStreetMap</a>, a collaborative project to create a free editable map of the world; </li> <li> NASA's Shuttle Radar Topography Mission (<a href="http://srtm.csi.cgiar.org/">SRTM</a>) Digital Elevation Database; </li> <li> <a href="https://global-surface-water.appspot.com/.">Global Water Surface</a>, a virtual time machine that maps the location and temporal distribution of water surfaces at the global scale. </li> </ul>

5-day WRF case study for the Southern Alps of New Zealand (hourly output)

Full output file from the Weather and Research Forecasting (WRF) model for a 2 km resolution domain centered over the Southern Alps of New Zealand. Modelling period is 02-Feb-2011 00:00:00 UTC to 07-Feb-2011 00:00:00 UTC (5 days) with hourly output frequency. The data-set was generated in the framework of a case study to investigate the mesoscale influence of an atmospheric river on the mass balance of Brewster Glacier (Southern Alps) during a summertime melt event. For the related publication refer to <a href="https://doi.org/10.1029/2020JD034217">https://doi.org/10.1029/2020JD034217</a>.

Pretrained Spec2Vec model (case study for MS2Query)

The model was trained for 20 iterations on a subset of the "AllPositive" dataset, created from GNPS positive ionmode mass spectra (subset of 91320 spectra out of 95320 spectra after filtering). It is an example model to run the MS2query app: https://github.com/iomega/ms2query.

Three-systems for visual numerosity: A single case study

MOT TASK Each file refers to a session with a particular condition. It is spelt out in the file name the number of objects to track as well as the total amount of objects on the screen Within each file it is found a variable called “MatriceRisultati”. Which contains: <ol> <li>Number of targets to follow</li> <li>Number of correct answers</li> <li>Number of trials at the condition</li> <li>Percent correct responses (i.e. value_2 / value_3)</li> </ol>   NECKLACE – DISTANCE TASK Each file contains raw data for each session. All the data are store in a variable called RESP, which contains parameters for each trial. The crucial columns are <ol> <li>Inter dot distance in the reference (in pixels – typically 1 pixel =~0.03 cm)</li> <li>Interdot distance in the test (in pixels)</li> <li>Subject choice to the question “which contains closer dots”</li> </ol> For analysis one has to draw a psychometric curve (i.e. a cumulative gaussian) that fits the data of column 3, as a function of interdot distance (column 2). Varinat may include dividing column 2 by column 1 (so to have the ratio between test and reference) and run the psychometric curve on such normalized dimension   Further explanation of the other columns (seeds for generating the stimuli) can be obtained from the authors.   Numerosity discrimination <ul> <li>The relevant columns in the matrix ‘a’ contain the following information:</li> <li>1st: Numerosity</li> <li>2nd: Log10 Numerosity</li> <li>3rd: Response </li> </ul>   Further explanation of the other columns (seeds for generating the stimuli) can be obtained from the authors.   Numerosity estimation <ul> <li>The relevant columns in the matrix ‘ContengoRisultati’ contain the following information:</li> <li>1st: Numerosity</li> <li>2nd: Response</li> </ul>   Further explanation of the other columns (seeds for generating the stimuli) can be obtained from the authors.

Dataset for Repeated double cross validation applied to the PCA-LDA classification of SERS spectra: a case study with serum samples from hepatocellular carcinoma patients

This dataset contains all the spectra used in the paper  "Repeated double cross validation applied to the PCA-LDA classification of SERS spectra: a case study with serum samples from hepatocellular carcinoma patients", plus the R code to import the TXT (ASCII) files into a dataset, preprocess data, set-up and cross validate the PCA-LDA model and generate the figures shown in the paper. Data are available in 2 different formats:  - 1 compressed archive ("dataset.zip") containing all the 144 TXT files (1 file = 1 spectrum)  - 1 single CSV file (“dataset.csv”) with all the 144 spectra in the form of a table. The data are structured as follow, with each row being 1 spectrum, preceded by metadata: "acquisition_date", "substrate_batch", "class", "sample_code". The code for R is available as a single file "Rcode.R".

opencc-by-4.0Dec 2020View details →

Semantic Segmentation of Time Series Imagery Using Deep Convolutional Neural Networks: A Case Study of Sandbars in Grand Canyon

This dataset contains imagery used to train and test Deep Convolutional Neural Networks for the purpose of binary semantic segmentation of a time series of oblique imagery capturing sandbar monitoring sites in The Grand Canyon. In addition the scripts needed for removing image distortion, registering, rectifying, and labeling imagery is present.

FIG. 5 in Trophic position of some Late Devonian-Carboniferous (Mississippian) conodonts revealed on carbon organic matter isotope signatures: a case study of the East European basin

FIG. 5. — δ13Cdistribution along the facies profile plotted for dominating taxa (latest Famennian-middle Tournaisian; Kamenka River section org

FIG. 3 in Trophic position of some Late Devonian-Carboniferous (Mississippian) conodonts revealed on carbon organic matter isotope signatures: a case study of the East European basin

FIG. 3. — Distribution of δ13Cvalues among conodonts having different morphological types of P1 elements. Scale bar: 0.1 mm. org

FIG. 2 in Trophic position of some Late Devonian-Carboniferous (Mississippian) conodonts revealed on carbon organic matter isotope signatures: a case study of the East European basin

FIG. 2. — Lithology, biostratigraphy, and facies distribution of the Kamenka River section (Pechora Craton). Legend: 1, limestone; 2, clayey limestone; 3, clay; 4, cherty nodules; 5, flat lamination; 6, wavy lamination.

FIG. 1 in Trophic position of some Late Devonian-Carboniferous (Mississippian) conodonts revealed on carbon organic matter isotope signatures: a case study of the East European basin

FIG. 1. — Localization of the sites under consideration: A, Generalized map of Eastern Europe; rectangles mark the localities: 1, Pechora Craton; 2, Voronezh Anteclise (Kamenka Quarry and Russkiy Brod Quarry sections); 3, Ilmen Lake region (Chudovo section, Syas River section, Ilmen Lake borehole 8, Ilmen Lake section); 4, Chimbulat Quarry. B, Map of Pechora Craton; C, Scheme of outcrops' position in the Kozhva River basin.

opencc-by-4.0Dec 2016View details →

Fig. 3 in A case of intersex occurrence in Steindachneridion parahybae (Steindachner, 1877) (Siluriformes: Pimelodidae) under captivity condition: a cytogenetic and morphological study

Fig. 3. Micrographs of the ovotestes of Steindachneridion parahybae juveniles in captivity showing the different germ cell types. a) unrestricted spermatogonial testes with anastomosing tubular type, composed by numerous tubules (arrowhead); b) many spermatozoa inside the tubular lumen (arrowhead), separated by interstitial tissue (asterisk); c) gonads section showing perinucleolar oocyte (arrow) close to testicular tissue (arrowhead), containing spermatozoa inside the duct and many intratubular cists; d) ovotestes showing perinucleolar oocyte (arrow) close to spermatozoa inside the duct (arrowhead). Periodic-Acid-Schiff (PAS)/Weigert's Haematoxylin/Metanil Yellow staining. Scale bars: 74 µm (a); 19 µm (b, d); 37 µm (c).

opencc-by-4.0Dec 2016View details →

Fig. 4 in A case of intersex occurrence in Steindachneridion parahybae (Steindachner, 1877) (Siluriformes: Pimelodidae) under captivity condition: a cytogenetic and morphological study

Fig. 4. Karyotype in Giemsa in male (a), detail in (b), in female (c), detail in (d) and in intersex animal (e), detail in (f) of Steindachneridion parahybae from Unidade de Hidrobiologia e Aquicultura, Companhia Energética de São Paulo. See the text for more information about karyotype characteristics. Scale bars: 37 μm (a,c,e); 7,4 μm (b,d,f).

opencc-by-4.0Dec 2016View details →

Fig. 2 in A case of intersex occurrence in Steindachneridion parahybae (Steindachner, 1877) (Siluriformes: Pimelodidae) under captivity condition: a cytogenetic and morphological study

Fig. 2. Micrographs of the testes of Steindachneridion parahybae juveniles in captivity showing the different germ cell types. a) unrestricted spermatogonial testes with anastomosing tubular type, composed by numerous tubules (arrowhead), which contained the germinal compartment (GC, indicate with arrow) and separated by interstitial tissue; b) isolated spermatogonia cell (arrow) surrounded by Sertoli cells (arrowhead), separated by interstitial tissue (asterisk); c) many spermatocytes and spermatids within the cysts (arrowhead), separated by interstitial tissue (asterisk); d) cysts of spermatocytes (arrowhead), separated by interstitial tissue (asterisk); e) cysts of spermatids (arrowhead), separated by interstitial tissue (asterisk); f) many spermatozoa inside the tubular lumen (arrowhead). Periodic-Acid-Schiff (PAS)/Weigert's Haematoxylin/Metanil Yellow staining. Scale bars: 74µm (a); 37 µm (f); 19 µm (c,e); 14 µm (b); 7.4 µm (d).

opencc-zeroNov 2019View details →

Data from: A phylogenomic approach to clarifying the relationship of Mesodinium within the Ciliophora: a case study in the complexity of mixed-species transcriptome analyses

Recent high-throughput sequencing endeavors have yielded multi-gene/protein phylogenies that confidently resolve several inter- and intra-class relationships within the phylum Ciliophora. We leverage the massive sequencing efforts from the Marine Microbial Eukaryote Transcriptome Sequencing Project, other SRA submissions, and available genome data with our own sequencing efforts to determine the phylogenetic position of Mesodinium and to generate the most taxonomically-rich phylogenomic ciliate tree to date. Regardless of the data mining strategy, the multi-protein dataset, or the molecular models of evolution employed, we consistently recovered the same well-supported relationships among ciliate classes, confirming many of the higher-level relationships previously identified. Mesodinium always formed a monophyletic group with members of the Litostomatea, with mixotrophic species of Mesodinium – M. rubrum, M. major, and M. chamaeleon - being more closely related to each other than to the heterotrophic member, M. pulex. The well-supported position of Mesodinium as sister to other litostomes contrasts with previous molecular analyses including those from phylogenomic studies that exploited the same transcriptomic databases. These topological discrepancies illustrate the need for caution when mining mixed-species transcriptomes and indicate that identifying ciliate sequences among prey contamination - particularly for Mesodinium species where expression from stolen prey nuclei appears to dominate – requires thorough and iterative vetting with phylogenies that incorporate sequences from a large outgroup of prey.

opencc-zeroDec 2018View details →

Data from: Assessing the contributions of intraspecific and environmental sources of infection in urban wildlife: Salmonella enterica and white ibis as a case study

Conversion of natural habitats into urban landscapes can expose wildlife to novel pathogens and alter pathogen transmission pathways. Because transmission is difficult to quantify for many wildlife pathogens, mathematical models paired with field observations can help select among competing transmission pathways that might operate in urban landscapes. Here we develop a mathematical model for the enteric bacteria Salmonella enterica in urban-foraging white ibis (Eudocimus albus) in south Florida as a case study to determine (i) the relative importance of contact-based versus environmental transmission among ibis and (ii) whether transmission can be supported by ibis alone or requires external sources of infection. We use biannual field prevalence data to restrict model outputs generated from a Latin hypercube sample of parameter space and select among competing transmission scenarios. We find the most support for transmission from environmental uptake rather than between-host contact and that ibis–ibis transmission alone could maintain low infection prevalence. Our analysis provides the first parameter estimates for Salmonella shedding and uptake in a wild bird and provides a key starting point for predicting how ibis response to urbanization alters their exposure to a multi-host zoonotic enteric pathogen. More broadly, our study provides an analytical roadmap to assess transmission pathways of multi-host wildlife pathogens in the face of scarce infection data.