Find research datasets worth reusing

Fig. 4 in Host biology, ecology and the environment influence microbial biomass and diversity in 101 marine fish species

Fig. 4 | Associations between fishmass and collection location as measuredby and d distance from shore with gill microbial biomass. e Comparison of fish mass distancefrom shorewith fishgill microbialbiomassand alphadiversity. Subset and f distancefromshorewithalpha diversitymetrics (Chao1).g Comparison of fish of fish from EPO and Atlantic (n = 54) collected from ocean (excludes bay and mass and h distance from shore with alpha diversity metric: Faith's PD. estuary samples) and from the neritic zone (<200 m depth). a Correlation matrix c–h (Confidenceintervalsof 95% aredisplayedasdotted lines). habita- between sample metadata where values are rho and significance indicated by t_act_collection refers to the metadata column name from where this habitat clas- *p <0.05, **p <0.01, ***p <0.001, ****p <0.0001 (Spearmancorrelation). sification can be found…, SZsurf zone, RIT rocky intertidal, RST rocky subtidal, IS b Comparison of gill microbial biomass (log cells per gram) across habitat types inner shelf, KBRF kelp bed rocky reef, MDRF mid depth rocky reef, CP coastal from which the fish were collected. Distribution is in median and interquartile pelagic, P pelagic. Mass_g_log = log 10 (mass of the fish in grams), dis- range. Statistical differences determined using non-parametric testing tance_from_shore_m_log = log 10 (distance from nearest point on shore in meters Kruskal–Wallistest with 0.05 FDRBenjamini–Hochberg. c Comparison of fish mass from where the fish was caught).

PAsCAL WP6 Pilot 5 Experience of Vulnerable Travellers in Connected Transport Environments

These three datasets were collected within the context of the PAsCAL research project between May and November 2021. Each survey included a different user group and all activities were conducted in different places: <ol> <li>Apertum Testing: 165 individual testers used the Apertum (https://apertum.world/) mobile application for step-free public transport information. These participants consisted of elderly persons (65+ years old), paraplegic users and persons with temporary mobility constraints (like injuries or persons who use baby strollers or heavy luggage). The testing took place in 3 different locations and followed 3 different scenarios to ensure that the routing or departure point of the user does not influence their acceptance of the CAV solution;</li> <li>UI-UX Testing: The same application was tested by 20 additional persons (half of them digital natives and half of them digital nomads) in Madrid, Spain. For the UI-UX testing, a few standard tasks were defined and the participants were able to familiarise themselves with the application for 30 minutes before the testing started. The WAMMI methodology was applied, consisting of a survey that is to the point.</li> <li>Focus Discussion Groups: The FDGs took place across 4 cities in Italy (Rome, Bologna, Milan and Naples) and included a diverse range of 51 blind and partially sighted persons. The participants attended a short briefing about autonomous and connected mobility and shared their experiences, opinions and attitudes freely before completing a survey to report on their freedom of travel, their needs and attitudes towards CAVs.</li> </ol> In order to analyse the answers given to the questions, it is recommended to consult also the "PAsCAL WP6 Pilots Surveys" dataset, which contains all questions and possible answers.

Fig. 2 in Host biology, ecology and the environment influence microbial biomass and diversity in 101 marine fish species

Fig. 2 | Limit of detection, sample exclusion, and microbial biomassestimation for FMP101 dataset. a Application of KatharoSeq formula to calculate limit of detection of microbiota platesusing the Bacillus/Paracoccus mock community (1150 reads at 90%). b Limit of detection based on cell counts of Bacillus/ Paracoccus mock community (~16 cells into extraction at 90%). c Model fit of the log(sequencing read counts) of positive extraction controls vs. the log cell counts of those positive extraction controls (empirically determined using plate counts. The linear regression of the line is indicative of the quality of method to estimate microbial biomass from sequencing read counts. Con- fidenceintervalsof 95% aredisplayedas dottedlines. Thismethodissimilar to a qPCR curvewherethe log (Ct) would beequivalent to the log(read counts).This equation is then used to estimate the number of "microbial density" of the existing samples which is then further normalized by the volume of the DNA extraction,biomass of materialgoinginto theextraction and finallynormalized to at estimated microbial cells per gram of tissue. d Community analysis comparison and validation of compositionality of controls of twosets of mock community controls (section 1 = Bacillus/Paracoccus mock community; section 2 = zymo mock community). Putative contaminant g__Geobacillus identified (presentin 93% of negatives and higherrelative abundance ascompared to positives and samples). e Number of samples successful across the four body sites collected from the broad fish microbiota dataset. QC quality control, g__ refers to a genus of bacteria, HM mock homemade mock or human made mixture of bacteria to use as a control whereas zymo mock = mock microbial community created by a company "Zymo".

Fig. 1 in Host biology, ecology and the environment influence microbial biomass and diversity in 101 marine fish species

Fig. 1 | Samplingdesignof 116 speciesof marine fish. a Using ArcGIS todepictthe general area from which fish were sampled: black dots indicate the locations of the 101 unique species of marine fish sampled from the California Current Ecosystem in the Eastern Pacific Ocean primarily in the waters of San Diego CA. Red circles depict the locations of an additional 17 species of fish (15 unique species with 2 species duplicates) collected from the Western Atlantic primarily in the waters of New York. When multiple species of fish were caught in the same location, a single circle is used to indicate the location. b Fish were sampled across a gradient of depth and distances from shore. c Biometric measurements taken for nearly all fish include total length, fork length, mass, gape, and GI length. Various ratios from these lengths were also calculated. Microbiota samples from the gill were primarily whole tissue specimens from the entire left second gill arch or a section of the top middle and bottom of the entire filament. Skin mucus samples were taken by scraping using a razor blade. Midgut digesta material was collected from directly posterior of the stomach or if stomach was absent, the beginning of the GI tract. Hindgut digesta samples were taken from near the anus. Image from phylopic. MG midgut, HG hindgut, GI gastrointestinal tract, m meters.

opencc-zeroNov 2022View details →

Data from: How long does a brachiopod shell last on a seafloor? Modern mid-bathyal environments as taphonomic analogues of continental shelves prior to the Mesozoic Marine Revolution

Carbonate skeletal remains are altered and disintegrate at yearly to decadal scales in present-day shallow-marine environments with intense bioerosion and dissolution. Present-day brachiopod death assemblages are invariably characterized by poor preservation on continental shelves, and abundant articulated shells of brachiopods with well-preserved brachidia are thus not expected to be preserved if not rapidly buried. However, such preservation is paradoxically observed in shallow-water Paleozoic and Mesozoic brachiopod assemblages. Here, we show that a bathyal death assemblage time-averaged to several millennia (Adriatic Sea) consists of sediment-filled articulated shells of Gryphus vitreus with complete brachidia. Postmortem age distributions indicate that disintegration half-lives exceed several centuries (~500-1,700 years). The high frequency of articulated but centuries-old shells (>50%) and the fitting of taphonomic models to postmortem ages indicate that disarticulation half-life is unusually long (~200 years). Rapid sediment filling of shells (1) inhibited disarticulation, loop fragmentation and colonization by coelobites and (2) induced precipitation of ferromanganese oxides at redox fronts within shells. Sediment-filled articulated shells, however, still resided at the sediment-water interface as indicated by encrusters and sponges that infested them after death. Sediment-filled shells disintegrated through bioerosion and wear when residence time in the taphonomically active zone exceeded ~2,000 years. We suggest that the articulation paradox is driven by the Mesozoic Marine Revolution (MMR) that escalated predation, bioturbation and organic matter recycling, all intensifying shell disintegration. A scenario with slow disarticulation in bathyal environments can be an analogue of conditions leading to preservation of articulated shells in shallow-water assemblages prior to the MMR.

Fig. 2 in Larval Development And Habitat Usage Of Stream-Breeding Fire Salamanders In An Urban Environment

Fig. 2. Changes in the number of salamander larvae and rainfall. The bold black continuous line shows the mean number of salamander larvae detected during the surveys in the three 10 day intervals of months in Hűvös-ér stream, 2011–2014. The bar graph shows the mean amount (and SD) of precipitation (mm) during the three 10-day intervals of months

Fig. 3 in Larval Development And Habitat Usage Of Stream-Breeding Fire Salamanders In An Urban Environment

Fig. 3. Mean density of salamander larvae (number of larvae/m2) detected in the 16 segments during surveys every 10 days in "Hűvös-ér" stream, 2011–2014 (2011: thin line, 2012:

Fig. 5 in Larval Development And Habitat Usage Of Stream-Breeding Fire Salamanders In An Urban Environment

Fig. 5. Mean number of salamander larvae detected per a year in the "releasing" 2–6 upper segments (continuous bold line), in the "strong collector" middle segments: 7–9 (dashed line) and the "weak collector" lower segments: 10–13 (dotted line) during surveys every 10 days in "Hűvös-ér" stream between 2011–2014. Data from segment 1 have not been plotted because larvae were present at only one time point

opencc-by-3.0-usJul 2022View details →

Yield Prediction Through Integration of Genetic, Environment, and Management Data Through Deep Learning: Cleaned Data

The included files and script are to allow for reconstruction of the data directory and cleaned data used in "Yield Prediction Through Integration of Genetic, Environment, and Management Data Through Deep Learning" ( https://doi.org/10.1101/2022.07.29.502051 ). Code used is available at 10.5281/zenodo.7401113 . <table> <tbody> <tr> <th>Filename</th> <th>Description</th> </tr> <tr> <td>interim.tar.gz</td> <td>Contains site grouping dictonary</td> </tr> <tr> <td>processed.tar.gz</td> <td>Processed data</td> </tr> <tr> <td>raw.tar.gz</td> <td>Input data</td> </tr> <tr> <td>SetupInstructions.sh</td> <td>Bash script to prepare folders and unzipped data expected by code in 10.5281/zenodo.7401113</td> </tr> <tr> <td>SetupInstructions.txt</td> <td>Instructions for unzipping the data</td> </tr> <tr> <td>Train_Test_Split_Reference_Phenotypes.csv</td> <td>Reference spreadsheet to allow for easily exploring training and test set groupings</td> </tr> </tbody> </table> <ul> </ul> This work was supported through funding from the USDA Agricultural Research Service, ARS project number 5070-21000-041-000-D. Raw data provided by the [Genomes to Field Initiative](https://www.genomes2fields.org/) and the [Daymet database](https://daymet.ornl.gov/).

Magnetic field reversal in the turbulent environment around a repeating fast radio burst

All the bursts of FRB 20190520B detected from the Green Bank Telescope (GBT) that was used in the Anna-Thomas et al (2022) paper. This dataset contains both L-Band (1.4 GHz) and C-Band (6 GHz) bursts. The data is in pulse archive format, which can be read using the software suite PSRCHIVE or the package PyPulse. The L-band bursts are not calibrated. The C-Band bursts which has an extension .calib is calibrated for both flux and polarization and those which has an extension .calibP is only calibrated for polarization.

opencc-zeroDec 2022View details →

Convergent adaptation of true crabs (Decapoda: Brachyura) to a gradient of terrestrial environments

For much of terrestrial biodiversity, the evolutionary pathways of adaptation from marine ancestors are poorly understood, and have usually been viewed as a binary trait. True crabs, the decapod crustacean infraorder Brachyura, comprise over 7,600 species representing a striking diversity of morphology and ecology, including repeated adaptation to non-marine habitats. Here, we reconstruct the evolutionary history of Brachyura using new and published sequences of 10 genes for 344 tips spanning 88 of 109 families. Using 36 newly vetted fossil calibrations, we infer that brachyurans most likely diverged in the Triassic, with family-level splits in the late Cretaceous and early Paleogene. By contrast, the root age is underestimated with automated sampling of 328 fossil occurrences explicitly incorporated into the tree prior, suggesting such models are a poor fit under heterogeneous fossil preservation. We apply recently defined trait-by-environment associations to classify a gradient of transitions from marine to terrestrial lifestyles. We estimate that crabs left the marine environment at least seven and up to 17 times convergently, and returned to the sea from non-marine environments at least twice. Although the most highly terrestrial- and many freshwater-adapted crabs are concentrated in Thoracotremata, Bayesian threshold models of ancestral state reconstruction fail to identify shifts to higher terrestrial grades due to the degree of underlying change required. Lineages throughout our tree inhabit intertidal and marginal marine environments, corroborating the inference that the early stages of terrestrial adaptation have a lower threshold to evolve. Our framework and extensive new fossil and natural history datasets will enable future comparisons of non-marine adaptation at the morphological and molecular level. Crabs provide an important window into the early processes of adaptation to novel environments, and different degrees of evolutionary constraint that might help predict these pathways. --

Fig. 1 in Larval Development And Habitat Usage Of Stream-Breeding Fire Salamanders In An Urban Environment

Fig. 1. Segments of "Hűvös-ér" stream, where Salamandra salamandra larvae were surveyed. (Numbers indicate individual stream segments, bold meandering line = main branch of the stream, thin branch- ing line = tributaries of the stream, straight lines = segment boundaries, four-pointed stars at segment boundaries and in the stream bed = water steps, double line = main road between Budapest and Solymár, P = "Paprikás"-stream)

opencc-by-4.0Dec 2022View details →

Multi-location trials and population-based genotyping reveal high diversity and adaptation to breeding environments in a large collection of red clover

This dataset accompanies the article with the same title made available on bioRxiv <a href="https://doi.org/10.1101/2022.12.19.520744">https://doi.org/10.1101/2022.12.19.520744</a>

opencc-zeroJan 2023View details →

Cloacal microbiomes of sympatric and allopatric Sceloporus lizards vary with environment and host relatedness

Animals and their microbiomes exert reciprocal influence; the host's environment, physiology, and phylogeny can impact the composition of the microbiome, while the microbes present can affect host behavior, health, and fitness. While some microbiomes are highly malleable, specialized microbiomes that provide important functions can be more robust to environmental perturbations. Recent evidence suggests Sceloporus virgatus has one such specialized microbiome, which functions to protect eggs from fungal pathogens during incubation. Here, we examine the cloacal microbiome of three different Sceloporus species (spiny lizards; Family Phrynosomatidae) – Sceloporus virgatus, Sceloporus jarrovii, and Sceloporus occidentalis. We compare two species with different reproductive modes (oviparous vs. viviparous) living in sympatry: S. virgatus and S. jarrovii. We compare sister species living in similar habitats (riparian oak-pine woodlands) but different latitudes: S. virgatus and S. occidentalis. And, we compare three populations of one species (S. occidentalis) living in different habitat types: beach, low-elevation forest, and the riparian woodland. We found differences in beta diversity metrics between all three comparisons, although those differences were more extreme between animals in different environments, even though those populations were more closely related. Similarly, alpha diversity varied among the S. occidentalis populations and between S. occidentalis and S. virgatus, but not between sympatric S. virgatus and S. jarrovii. Despite these differences, all three species and all three populations of S. occcidentalis had the same dominant taxon, Enterobacteriaceae. The majority of the variation between groups was in low abundance taxa and at the ASV level, and responded to habitat differences, geographic distance, and host relatedness. Understanding wild microbiomes and factors that influence their composition is important to understanding the ecology and evolution of the host animals.

Supplementary Material - Marine animal forests in turbid environments are overlooked seascapes in urban areas

Figures S1, S2, and S3 of the manuscript "Marine animal forests in turbid environments are overlooked seascapes in urban areas" accepted in the open-access journal Ocean and Coastal Research (Soares et al. 2023)

Dataset: Modelling surface color discrimination under different lighting environments using image chromatic statistics and convolutional neural networks

Associated publication [1] Samuel Ponting*, Takuma Morimoto*, Hannah E. Smithson, “Modelling surface color discrimination under different lighting environments using image chromatic statistics and convolutional neural networks”, *equal contribution, bioRxiv, <a href="https://www.google.com/url?q=https%3A%2F%2Fdoi.org%2F10.1101%2F2022.11.02.514864&sa=D&sntz=1&usg=AOvVaw3KwSo7KmqPzBR1UMc1MHmk">https://doi.org/10.1101/2022.11.02.514864</a> [2] Takuma Morimoto, and Hannah E. Smithson, “Discrimination of spectral reflectance under complex environmental illumination,” Journal of the Optical Society of America A, 35, 4, B244-B255 (2018) https://doi.org/10.1364/JOSAA.35.00B244   Datasets contain 2 folders and 1 mat file.   (Folder 1) Stimuli (Folder 2) Psychophysics_data (Mat file) stimulusMagnitudeToMacLeodBoynton.mat   Details are described below.   ---------------------------------------------------------------------------------------------------------------------------------------- (Folder 1) Stimuli   Overview of datasets This Image dataset includes 57,600 images (2 gloss levels * 3 environments * 100 stimulus magnitudes * 8 hue directions * 12 camera angles from 0 to 330 degree in 30 degree step) in .mat format.   The half of images were used in psychophysical experiment (camera angles: 0, 60, 120, 180, 240, 300 degrees). Other half images were used for testing chromatic statistics models and CNN-based models [1] (camera angles: 30, 90, 150, 210, 270, 330 degrees).   Each image file Filename denotes a condition name and the camera angle as formatted in a following way.   stim_”environment” _”glossiness”_”hueAngle”_”magnitude”_”cameraAngle”.mat e.g. “stim_en1_glossy_hue45_n45_cameraAngle90.mat”   Stimulus magnitude 100 is a maximum saturation, and 1 corresponds to equal energy white (which was used as a distractor object).   Each image file contains two valuables : MacLeodBoynton, XYZ   Each variable contains an image of 128*128*3 pixels (height*width*channel).   MacLeod-Boynton: MacLeod-Boynton chromaticity image (1st channel: L/(L+M), 2nd channel: S/(L+M), and 3rd channel L+M) XYZ: XYZ coordinates calculated based on 2-degree CIE 1931 xyz color matching function (1st channel: X, 2nd channel: Y, and 3rd channel Z)   Luminance and L+M are both relative (normalised by the maximum luminance across all 57,600 images).   ---------------------------------------------------------------------------------------------------------------------------------------- (Folder 2) Psychophysics_data Filename denotes the condition and observers formatted in a following way.   data_”environment” _”specularities”_”sessionNumber”_”obsever”.mat e.g. data_en2_matte_session4_JH.mat or .csv   Each file includes following variables:   (Variable 1) threshold Thresholds are stored in MacLeod-Boynton (MB) chromaticity coordinates for all 8 hue directions (from 0 to 315 degree in 45 degree step).   MacLeod-Boynton chromaticity coordinates were calculated in a following way. These scalings are in accordance with description in CVRL main site (Chromaticity coordinates tab ).   First of all, L, M, and S cone signals were calculated based on Stockman & Sharpe cone fundamentals (energy in linear scale available at at http://www.cvrl.org). Each sensitivity curve was normalised to have 1.0 at the peak.   Then, MB coordinates were calculated using equation (1-3).   L/(L+M) = Lw*L/(Lw*L+Mw*M) - (1) S/(L+M) = Sw*S/(Lw*L+Mw*M) - (2) L+M = Lw*L+Mw*M - (3)   where Lw = 0.689903; Mw = 0.348322;Sw = 1.93540.   L, M and S denote L-cone, M-cone, S-cone excitations, respectively.   Under this calculation, equal energy white becomes L/(L+M) = 0.7078 and S/(L+M) = 1.   (Variable 2) staircase   Since we ran 8 interleaved staircase (for 8 hue angles), information about 8 staircases are stored in this single variable. (staircase(1) corresponds to 0 degree, and staircase(8) corresponds to 315 degree)   There are 5 fields: (i) groundtruth, (ii) response, (iii) correct, (iv) magnitude, (v) cameraAngle   For each trial, the location of objects was defined in a following way. | 1 3 | | 2 4 |   And each field stores following information for all trials in the staircase.   (i) groundtruth Location of the target object   (ii) response Location that the participant chose   (iii) correct If the response was correct (1) or incorrect (0)   (iv) magnitude Stimulus magnitude of target object in each trial from 1 to 100 (1 for equal energy white and 100 for maximum saturation).   (v) Camera angle Camera angles assigned for four objects in each trial. This data and (i) groundtruth allow reconstruct of the exact image for each trial.   ---------------------------------------------------------------------------------------------------------------------------------------- (Mat file) stimulusMagnitudeToMacLeodBoynton.mat This file stores a variable ‘stimulusMagnitudeToMacLeodBoynton’ (8*100*2) which describes correspondence map between stimulus magnitude and MacLeod-Boynton chromaticity.   1st channel: hue direction from 0 degree to 315 degree, 45 degree step 2nd channel: magnitude from 1 to 100 3rd channel: MacLeod-Boynton coordinate, 1 being L/(L+M) and 2 being S/(L+M)

opencc-zeroJan 2023View details →

Data for: Positive impact of postfire environment on bumble bees not explained by habitat variables in a remote forested ecosystem

Bumble bees are important pollinators in temperate forested regions where fire is a driving force for habitat change, and thus understanding how these insects respond to fire is critical. Previous work has shown bees are often positively affected by the post-fire environment, with burned sites supporting greater bee abundance and diversity, and increased floral resources. The extent to which fire impacts variation in bumble bee site occupancy is not well understood, especially in higher latitude regions with dense, primarily coniferous forests. Occupancy models are powerful tools for biodiversity analyses, as they separately estimate occupancy probability (likelihood that a species is present at a particular location) and detection probability (likelihood of observing a species when it is present). Using these models, we tested whether bumble bee site occupancy is higher in burned locations as a result of the increase in canopy openness, floral species richness, and floral abundance. We quantified the impact of fire, and associated habitat changes, on bumble bee species' occupancy in an area with high wildfire frequency in British Columbia, Canada. The burn status of a site was the only significant predictor for determining bumble bee occurrence (with burned sites having higher occupancy); floral resource availability and canopy openness only impacted detection probability (roughly, sample bias). These findings highlight the importance of controlling for the influence of habitat on species detection in pollinator studies and suggest that fire in this system changes the habitat for bumble bees in positive ways that extend beyond our measurements of differences in floral resources and canopy cover.

Dataset of Public Objects in Uncontrolled Environment for Navigation Aiding

Computer vision is a new approach to navigation aiding that assist visually impaired people to travel independently. A deep learning-based solution implemented on a portable device that uses a monocular camera to capture public objects could be a low-cost and handy navigation aid. By recognizing public objects in the street and estimating the distance between the users, visually impaired people are able to avoid obstacles in the outdoor environment and walk safely. This dataset is created for navigation aiding and contains 3 classes of objects which commonly exist on the pavement in the city. It is verified that the dataset is of high quality for object detection and distance estimation, and is ultimately utilized for navigation aid solution.

Data package for Poromechanical analysis of oil well cements in CO2-rich environments

Data package for the results obtained in Poromechanical analysis of oil well cements in CO2-rich environments. Juan Cruz Barría, Mohammadreza Bagheri, Diego Manzanal, Seyed M. Shariatipour, Jean-Michel Pereira, Poromechanical analysis of oil well cements in CO2-rich environments, International Journal of Greenhouse Gas Control, Volume 119, 2022, 103734, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2022.103734.