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FIGURE 18 in A review of the taxonomy and osteology of the Rhombophryne serratopalpebrosa species group (Anura: Microhylidae) from Madagascar, with comments on the value of volume rendering of micro-CT data to taxonomists
FIGURE 18. The pelvic girdle of the R. serratopalpebrosa species group in lateral and dorsal view. Darker colour indicates cartilage. Abbreviations: il.cr = iliac crest, il.sh = iliac shaft, il.dp = dorsal prominence of ilium, il.og = oblique groove of ilium.
FIGURE 10 in A review of the taxonomy and osteology of the Rhombophryne serratopalpebrosa species group (Anura: Microhylidae) from Madagascar, with comments on the value of volume rendering of micro-CT data to taxonomists
FIGURE 10. Osteology of Rhombophryne regalis sp. nov. (MRSN A4602). Full skeleton in (a) dorsal, (b) ventral, and (c) lateral view; skull in (d) dorsal, (e) ventral, and (f) lateral view. Abbreviations as in Fig. 7.
FIGURE 3. Bayesian consensus tree for Neoplecostomus species obtained from 5 million generations. Numbers after branches are posterior probabilities. Values below 0.95 in Neoplecostomus canastra, a new catfish (Teleostei: Siluriformes) species from upper Rio Paraná basin
FIGURE 3. Bayesian consensus tree for Neoplecostomus species obtained from 5 million generations. Numbers after branches are posterior probabilities. Values below 0.95 are not shown. Results from different methods of species delimitation are shown with bars colored at right side of the phylogeny. Pink bars represent morphospecies, yellow bars GMYC model and blue bars 2% genetic distance between clusters. The upper-left graphic is the Lineage-through-time plot representing the threshold time at -0.007195772 (yellow line).
Ocean Meridional Heat Transport Values
<p>This dataset includes data for Figures 2, 4, 6, 10 and 12 of the "Observation-based Estimate of Global and Basin Ocean Meridional Heat Transport Time Series" paper. This paper is published through the Journal of Climate (2019) and by authors, Kevin E. Trenberth, Yongxin Zhang, John T. Fasullo and Lijing Cheng. The data files associated with this dataset provides tabular values and are for general use.</p>
Valorization of plastic wastes into value-add biochar production through co-pyrolysis with biomass residues
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Clinical data of patients and values of antibodies in the IgM, IgA and IgG classess against Mycoplasma pneumoniae
<p><span>Data on <em>Mycoplasma pneumoniae</em> infections during last years are very limited. In this manuscript, we presented the assessment of the seroprevalence of antibodies against <em>Mycoplasma pneumoniae</em> in the numerous group of patients, as well as clinical aspects of the differential diagnostics of respiratory tract infections.</span></p>
Correlation between estimated pulse wave velocity values from two equations in healthy and under cardiovascular risk populations
<p><strong>Introduction </strong><strong>: </strong>Equations can calculate pulse wave velocity (ePWV) from blood pressure values (BP) and age. The ePWV predicts cardiovascular events beyond carotid-femoral PWV. We aimed to evaluate the correlation between four different equations to calculate ePWV.</p> <p><strong>Methods: </strong>The ePWV was estimated utilizing mean BP (MBP) from office BP (MBP<sub>OBP</sub>) or 24-hour ambulatory BP (MBP<sub>24-hBP</sub>). We separated the whole sample into two groups: individuals with risk factors and healthy individuals. The e-PWV was calculated as follows: </p> <p>We calculated the concordance correlation coefficient (Pc) between e1-PWV<sub>OBP</sub> vs e2-PWV<sub>OBP</sub>, e1-PWV<sub>24-hBP</sub> vs e2-PWV<sub>24-hBP</sub>, and mean values of e1-PWV<sub>OBP</sub>, e2-PWV<sub>OBP</sub>, e1-PWV<sub>24-hBP, </sub>and e2-PWV<sub>24-hBP </sub>. The multilevel regression model determined how much the ePWVs are influenced by age and MBP values.</p> <p><strong>Results:</strong> We analyzed data from 1541 individuals; 1374 ones with risk factors and 167 healthy ones. The values are presented for the entire sample, for risk-factor patients and for healthy individuals, respectively. The correlation between e1-PWV<sub>OBP</sub> with e2-PWV<sub>OBP</sub> and e1-PWV<sub>24-hBP </sub>with e2-PWV<sub>24-hBP</sub> was almost perfect. The Pc for e1-PWV<sub>OBP</sub> vs e2-PWV<sub>OBP</sub> was 0.996 (0.995-0.996), 0.996 (0.995-0.996), and 0.994 (0.992-0.995); furthermore, it was 0.994 (0.993-0.995), 0.994 (0.994-0.995), 0.987 (0.983-0.990) to the e1-PWV<sub>24-hBP </sub>vs e2-PWV<sub>24-hBP</sub>. There were no significant differences between mean values (m/s) for e1-PWV<sub>OBP</sub> vs e2-PWV<sub>OBP</sub> 8.98±1.9 vs 8.97±1.8; p=0.88, 9.14±1.8 vs 9.13±1.8; p=0.88, and 7.57±1.3 vs 7.65±1.3; p=0.5; mean values are also similar for e1-PWV<sub>24-hBP </sub>vs e2-PWV<sub>24-hBP</sub>, 8.36±1.7 vs 8.46±1.6; p=0.09, 8.50±1.7 vs 8.58±1.7; p=0.21 and 7.26±1.3 vs 7.39±1.2; p=0.34. The multiple linear regression showed that age, MBP, and age² predicted more than 99.5% of all four e-PWV.</p> <p><strong>Conclusion: </strong>Our data presents a nearly perfect correlation between the values of two equations to calculate the estimated PWV, whether utilizing office or ambulatory blood pressure.</p>
Numerical data: time dependence of spin-spin expectation value in "Nonmonotonic buildup of spin-singlet correlations in a double quantum dot" Phys. Rev. B 108, 144307 (2023).
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Average values of S(B) and their corresponding 90% confidence intervals
<p>The animation displays the average values of S(B) for B < 10^6 along with their corresponding 90% confidence intervals, <br>for elliptic curves with ranks 0 or 1 in the conductor range [N,N+10\sqrt(n)]. The cross indicates the location of the local maximum, <br>while circles represent predictions for the first three local maxima at 0.08N, 0.65N, and 1.7N.</p>
Dataset and Software code _ Localized and global representation of prior value, sensory evidence, and choice in male mouse cerebral cortex
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Dataset for Can we predict kick force based solely on spatial-temporal variables? Applying long short-term memory model for predicting force values of turning and side kick of taekwon-do athletes
<p>This data set is created for a purpose of publication "<span>Can we predict kick force based solely on spatial-temporal variables? Applying long short-term memory model for predicting force values of turning and side kick of taekwon-do athletes". It contains of dataset of kicks and lstm models for predictions a force of kicks upon IMU data. Detailed description of file names are in readme file. Folders are divided into specific kicks - turning or side kick in sport or traditional versions.</span></p>
Assessing Multiple Values of Nature in National Biodiversity Strategies and Action Plans: Coded Data
<p>We coded eleven National Biodiversity Strategies and Action Plans (NBSAPs) for the human values for nature (instrumental, instrinsic, and relational) expressed in the NBSAPs. The 11 country NBSAPs coded were: Angola, Australia, Bhutan, Czech Republic, Egypt, Germany, Guyana, Malaysia, Russia, Saint Vincent and the Grenadines, and Turkey. Each sentence, <span>defined as an orthographic unit beginning with a capital letter and ending with a full stop, was provided a value code (instrumental, intrinsic, relational, unspecified, ‘not value orientation statement', or uncertain) depending on the value orientation of the statement. Coding criteria for each code is given below: </span></p> <p><span><span> </span></span></p> <table> <tbody> <tr> <td> <p><strong><span>Code</span></strong></p> </td> <td> <p><strong><span>Description</span></strong></p> </td> </tr> <tr> <td> <p><span>Instrumental</span></p> </td> <td> <p><span><span>●<span> </span></span></span><span>Nature is described as valuable or useful for humans ends</span></p> <p><span><span>●<span> </span></span></span><span>Mentions of provisioning services, regulating services, economic benefits, natural capital, stocks and harvests, use of nature (tourism/recreation was tagged as instrumental unless an explicit relational aspect mentioned)</span></p> </td> </tr> <tr> <td> <p><span>Intrinsic</span></p> </td> <td> <p><span><span>●<span> </span></span></span><span>Nature is described as valuable regardless of humans</span></p> <p><span><span>●<span> </span></span></span><span>Nature is valuable for natural (nonhuman) ends (e.g., forests must be preserved as habitats for animals)</span></p> <p><span><span>●<span> </span></span></span><span>Nature as having a right to exist undisturbed by humans</span></p> </td> </tr> <tr> <td> <p><span>Relational</span></p> </td> <td> <p><span><span>●<span> </span></span></span><span>Meaningful relationships with nature </span></p> <p><span><span>●<span> </span></span></span><span>Links between nature and culture, identity, traditions, traditional knowledge, fairness, environmental justice and rights, sharing, future generations, heritage, responsibilities, human beings as a part of nature, and quality of life</span></p> <p><span><span>●<span> </span></span></span><span>References to personified nature (e.g. “Mother Earth”)</span></p> </td> </tr> <tr> <td> <p><span>Unspecified</span></p> </td> <td> <p><span><span>●<span> </span></span></span><span>Value or importance of nature is implied, but no direct link to instrumental, intrinsic, or relational values (e.g., “our coastal and marine areas house important ecosystems”; “we have safeguarded all our key ecosystems, species and genetic diversity”)</span></p> </td> </tr> <tr> <td> <p><span>Not value orientation statement</span></p> </td> <td> <p><span><span>●<span> </span></span></span><span>Sentence does not imply value, or value statement does not link to nature. Purely biophysical language that is only descriptive (e.g., “There are an estimated 15,000 species of plants in the country”).</span></p> </td> </tr> </tbody> </table> <p> </p> <p>For a detailed overview of the methods, please refer the paper published in People and Nature.</p>
Suppl. Table 2: P-values of statistical tests comparing morphometric parameters characterising Saccharina embryos and their cells.
<p>Samuel Boscq Thesis Chapter 2 Supplementary data</p>
Hourly and daily values of meteorological elements from 40 meteorological stations located in Arizona (USA)
<p>The collection includes three text files (Arizona_meteo_hourly_01.txt; Arizona_meteo_hourly_02.txt; Arizona_meteo_daily.txt) with hourly and daily values of measurements from 40 meteorological stations located in Arizona (USA). The data was collected from September to November 2024 by Sylwester Wereski as a part of MINIATURA 5 "The occurrence of strong heat stress in hot and arid climate condition" (2021/05/X/ST10/00587), the research internship project at Arizona State University financed by the National Science Center in Poland. The source of data is website https://cales.arizona.edu/azmet/az-data.htm managed by AZMET (The Arizona Meteorological Network). The collection also includes a Readme.txt file, which contains a description of the location of the meteorological stations and the period of measurements conducted, as well as a description of meteorological variables.</p>
Calculation of R2 regression values after square root transformation of the data in intact condition of Haemaphysalis darjeeling
<p>Table: Calculation of R2 regression values after square root transformation of the data in intact condition of <em>Haemaphysalis darjeeling</em></p>
The value of increased spatial resolution of pesticide usage data for assessing risk to endangered species: Data, notebooks, and results
<p>Decision makers often cite data quality as a limitation in environmental management. Value of information approaches evaluates the benefit of new data collection for management outcomes. Pesticide exposure risk assessment for endangered species is one context where data limitations may affect decisions and a value of information type approach could be useful for identifying optimal data <span><span><span><span><span><span><span><span><span><span><span><span><span><span><span>quality and resolution. Under the U.S. Federal Insecticide, Fungicide and Rodenticide Act, the U.S. Environmental Protection Agency (EPA) is responsible for registering pesticides before they can be sold and regularly reviewing pesticides. Section 7 of the Endangered Species Act requires that the EPA consider potential impacts of pesticides to listed endangered species and critical habitats in this process, and for the Services—U.S. Fish and Wildlife Service and National Marine Fisheries Service—to complete a formal Section 7 consultation if the EPA deems it necessary. The current process is time‐intensive, lacks transparency and confidence among stakeholders, and leaves hundreds of unreviewed pesticides on the market. Increasing the resolution of pesticide usage data could address these concerns by improving estimated overlaps between species ranges and pesticide usage. Thus, we evaluated the relative importance of different resolutions of pesticide usage data for assessing expected carbaryl exposure to endangered plant species endemic to California. We found that spatially explicit, township resolution usage data (~36</span></span></span></span></span></span></span></span></span></span></span></span></span></span></span> <span><span><span><span><span><span><span><span><span><span><span><span><span><span><span>mile</span></span></span></span></span></span></span></span></span></span></span></span></span></span></span><sup>2</sup><span><span><span><span><span><span><span><span><span><span><span><span><span><span><span>) excluded 33% of terrestrial plants (55/168) and 51% their critical habitats (27/53) from requiring a Section 7 consultation, while coarser resolution data excluded none. In contrast, the EPA's biological evaluation for carbaryl only excludes 4% of terrestrial plants (nationally) from requiring formal Section 7 consultation. This suggests high‐resolution data could increase pesticide review efficiency and decrease the amount of time pesticides remain on the market without a formal evaluation.</span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></p>
Validation of the predictive accuracy of health-state utility values based on the Lloyd model for metastatic or recurrent breast cancer in Japan
<p>Although there is a lack of data on health-state utility values (HSUVs) for calculating quality-adjusted life years in Japan, Cost-utility analysis has been introduced by the Japanese government to inform decision-making in the medical field since 2016. This study aimed to determine whether the Lloyd model which was a predictive model of HSUVs for metastatic breast cancer (MBC) patients in the United Kingdom can accurately predict actual HSUVs for Japanese patients with MBC. The prospective observational study, followed by the validation study of the clinical predictive model.<b> </b>Forty-four Japanese patients with MBC were studied at 336 survey points. This study consisted of two phases. In the first phase, we constructed a database of clinical data prospectively and HSUVs for Japanese patients with MBC to evaluate the predictive accuracy of HSUVs calculated using the Lloyd model. In the second phase, Bland-Altman analysis was used to determine how accurately predicted HSUVs (based on the Lloyd model) correlated with actual HSUVs obtained using the EuroQol 5-Dimension 5-Level questionnaire, a preference-based measure of HSUVs in patients with MBC. In the Bland-Altman analysis, the mean difference between HSUVs estimated by the Lloyd model and actual HSUVs, or systematic error, was -0.106. The precision was 0.165. The 95% limits of agreement ranged from -0.436 to 0.225. The t value was 4.6972, which was greater than the t value with 2 degrees of freedom at the 5% significance level (p=0.425). There were acceptable degrees of fixed and proportional errors associated with the prediction of HSUVs based on the Lloyd model for Japanese patients with MBC. We recommend that sensitivity analysis be performed when conducting cost-effectiveness analyses with HSUVs calculated using the Lloyd model.</p>
FIGURE. The Bayesian tree of the Adaintum pedatum complex based on chloroplast markers and corresponding rhizome type. Support values (Bayesian inference posterior probability (BIPP) (upper) ≥ 0.5, and maximum likelihood bootstrap support (MLBS) (nether) ≥ 50%) are shown above the main branches, the thickened branches indicate MLBS=100 and BIPP=1. Yellow bar means erect rhizome; blue bar means creeping rhizome; gray bar means decumbent or short-creeping rhizome. in Adiantum japonicum, a new species of the Adiantum pedatum complex (Pteridaceae) from Japan
FIGURE. The Bayesian tree of the Adaintum pedatum complex based on chloroplast markers and corresponding rhizome type. Support values (Bayesian inference posterior probability (BIPP) (upper) ≥ 0.5, and maximum likelihood bootstrap support (MLBS) (nether) ≥ 50%) are shown above the main branches, the thickened branches indicate MLBS=100 and BIPP=1. Yellow bar means erect rhizome; blue bar means creeping rhizome; gray bar means decumbent or short-creeping rhizome.
FIGURE Phylogenetic relationships of the Coelastrella genus inferred from the 18S-ITS1-5.8S-ITS2 region. The Neighbor-Joining (NJ), Maximum Likelihood (ML) bootstrap values and Bayesian posterior probabilities (PP) are presented at the nodes (NJ/ML/PP). Only values above 75 are shown. Strains provided in this study are indicated in bold font. Authentic strains marked with asterisks. The scale bar represents the number of substitutions per site. The GenBank accession numbers of Coelastrella can be found in the Table 3. in Morphological and phylogenetic relations of members of the genus Coelastrella (Scenedesmaceae, Chlorophyta) from the Ural and Khentii Mountains (Russia, Mongolia)
FIGURE Phylogenetic relationships of the Coelastrella genus inferred from the 18S-ITS1-5.8S-ITS2 region. The Neighbor-Joining (NJ), Maximum Likelihood (ML) bootstrap values and Bayesian posterior probabilities (PP) are presented at the nodes (NJ/ML/PP). Only values above 75 are shown. Strains provided in this study are indicated in bold font. Authentic strains marked with asterisks. The scale bar represents the number of substitutions per site. The GenBank accession numbers of Coelastrella can be found in the Table 3.
Figure 3. A–F in Anatomy and phylogenetic value of the mandibular and coronoid canals and their associated foramina in proboscideans (Mammalia)
Figure 3. A–F, horizontal computed tomography (CT) slices of a mandible of Elephas maximus (TMM M-6445) showing the position and path of the mandibular canal and its associated foramina. G, diagrammatic representation of the mandible in left lateral view, illustrating the position of the CT slices depicted in A–F. The course of the mandibular canal is outlined. Abbreviations: a.m2, second molar alveolus; a.m.c., anterior mental canal; a.m.f., anterior mental foramen; co.f., coronoid foramen; co.p., coronoid process; l.m.c., lateral mental canal; m1, first lower molar; ma.c., mandibular canal; ma.f., mandibular foramen; p.m.f., posterior mental foramen.
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.