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FIGURE 7 in Otolith shape analysis supports three cryptic species in the Stellifer punctatissimus complex (Acanthuriformes: Sciaenidae)

FIGURE 7 | A. Principal Component Analysis (PCA) of sulcus acusticus's shape variation using Procrustes residual of geometric morphometric method. Shape variation in each principal component (PC1 in the horizontal and PC2 in the vertical) in the upper left corner. B. Pairwise shape comparisons; GM = Stellifer gomezi, MN = S. menezesi, PC = S. punctatissimus.

FIGURE 4 in Otolith shape analysis supports three cryptic species in the Stellifer punctatissimus complex (Acanthuriformes: Sciaenidae)

FIGURE 4 | A. Scatterplot of otolith weight using a LOESS curve fitting. B. Scatterplot of rectangularity index. GM = Stellifer gomezi, MN = S. menezesi, PC = S. punctatissimus.

FIGURE 3 in Otolith shape analysis supports three cryptic species in the Stellifer punctatissimus complex (Acanthuriformes: Sciaenidae)

FIGURE 3 | Otoliths of Stellifer punctatissimus complex. A. S. gomezi. B. S. menezesi. C. S. punctatissimus. Left: inner face; Middle: inset of the ostium; Right: dorsal profile. Arrow indicates spout-like groove; asterisk indicates projection on the outer face. Scale bars = 1 mm.

FIGURE 2 in Otolith shape analysis supports three cryptic species in the Stellifer punctatissimus complex (Acanthuriformes: Sciaenidae)

FIGURE 2 | Illustration of representative sagitta otolith with key anatomical features, based on an average shape specimen. Filled dots = landmarks, empty circles = semilandmarks; A = anterior, M = medial, D = dorsal (asterisk: sulcus acusticus = ostium + cauda).

FIGURE 1 in Otolith shape analysis supports three cryptic species in the Stellifer punctatissimus complex (Acanthuriformes: Sciaenidae)

FIGURE 1 | Map of the study area highlighting the sampling sites in the Bahia State, Brazil. B. Representative specimens of the species studied. Stellifer gomezi (top); S. menezesi (middle); S. punctatissimus (bottom). Scale bars = 10 mm.

FIGURE 6 in Otolith shape analysis supports three cryptic species in the Stellifer punctatissimus complex (Acanthuriformes: Sciaenidae)

FIGURE 6 | Linear Discriminant Analysis (LDA) of contour shape according to elliptical Fourier descriptors (EFDs). GM = Stellifer gomezi, MN = S. menezesi, PC = S. punctatissimus.

Research data supporting "Mechanical properties of semi-regular lattices"

Research data supporting "Mechanical properties of semi-regular lattices" published in Materials & Design in 2022.  This dataset includes: <ul> <li>Processed data plotted in Figure 11 (Fig11.xlsx).</li> <li>Processed data plotted in Figure 19 (Fig19.xlsx).</li> <li>Finite element models used to compute the elastic and shear moduli of each semi-regular lattice.  These can be opened with the commercial software Abaqus CAE version 2023 (periodic_boundary_model.cae).</li> </ul>

Efficiency and heat transport processes of low-temperature aquifer thermal energy storage systems: new insights from global sensitivity analyses - Supporting Dataset

This dataset contains the files used to substantiate the outcomes of the publication "Efficiency and heat transport processes of low-temperature aquifer thermal energy storage systems: new insights from global sensitivity analyses".  It includes the output of 250 random model realizations of an aquifer thermal energy storage system in a thick productive aquifer (Case 1). It also includes the output of 500 random model realizations of an aquifer thermal energy storage system in a shallow alluvial aquifer (Case 2 part 1 and part 2). If there is interest in generating new output, the datset also includes the model input files for both cases. (Scripts to process the output data or to generate new output data can be found in the corresponding GitHub repository: https://github.com/lukatas/ATES_SensitivityAnalyses.git )

Research data supporting "The fracture toughness of demi-regular lattices"

Research data supporting "The fracture toughness of demi-regular lattices" published in Scripta Materialia in 2023.  This dataset includes: <ul> <li>Processed data plotted in Figures 2 and 4 (Figs.xlsx).</li> <li>Python scripts used to generate the finite element models (*.py files).  These have to be used with the commercial software Abaqus CAE.</li> </ul>

Research data supporting "Fracture toughness of semi-regular lattices"

Research data supporting "Fracture toughness of semi-regular lattices" published in International Journal of Solids and Structures in 2023.  This dataset includes: <ul> <li>Processed data plotted in Figures 4, 5, 6, 10, and A2 (*.xlsx files).</li> <li>Raw data plotted in Figure 8 (Fig 8.xlsx).</li> <li>CAD files for all test specimens (*.STL files).</li> <li>Python scripts used to generate the finite element models (*.py files).  These have to be used with the commercial software Abaqus CAE.</li> </ul>

Datasets, trained models and supporting results for machine learning tensorial properties of atomic systems via XPaiNN model.

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CESM2.2-8P4Z data supporting Yu et al. (2024): Simulating ecosystem dynamics and marine biogeochemical cycles with multiple plankton functional types

This dataset contains the model output from CESM2.2-8P4Z, used in Yu et al. (2024) and submitted to the Journal of Advances in Modeling Earth Systems (JAMES). These are the last 20-year averaged output files from 310 years of the model simulations, which are analyzed in Yu et al., (2024). CESM2.2-8P4Z contains twelve plankton groups, including eight types of phytoplankton: 1) picophytoplankton groups: Prochlorococcus, Synechococcus, picoeukaryotes and diazotrophs; 2) nanophytoplankton groups: Phaeocystis, coccolithophores and a generic other nanophytoplankton; 3) micro-sized phytoplankton: diatoms; and four types of zooplankton: small microzooplankton (5-20 um, such as ciliates, nanoflagellates), large microzooplankton (20-200 um, such as copepod nauplii, small dinoflagellates etc.), mesozooplankton (200-2000 um, such as smaller copepod, large dinoflagellates) and macrozooplankton (>2000 um, such as larger copepod, krill). The MARBL-8P4Z model improves seasonal simulation of the spring bloom compared with more simplified MARBL configurations, benefiting from dampened diatom blooms at higher latitudes due to a combination of bottom-up and top-down drivers.

Data From: Clinical evaluation of patterned dried plasma spot cards to support quantification of HIV viral load and reflexive genotyping

This is the data set from all figures and tables from the manuscript "Clinical evaluation of patterned dried plasma spot cards to support quantification of HIV viral load and reflexive genotyping", which is posted to the ChemRxiv preprint server (10.26434/chemrxiv-2024-5bqm7) and currently in consideration for peer-reviewed publication elsewhere.

openmit-licenseJun 2023View details →

Supporting data and code for: Demographic and genetic impacts of powdery mildew in a young oak cohort

This is a new release following the submission of the related PCI recommended manuscript to the Annals of Forest Science journal. It contains the necessary scripts to produce most of the analyses and figures of the manuscript. Apart from minor modifications following the recommendation in 'PCI Forest and Wood Sciences', the main change is the addition of an extra dataset "Data_S2.txt" to the additional datasets. This dataset was previously included as a table in the 'supplementary material' file.

opencc-by-4.0Mar 2024View details →

Supporting Images to "A new species of velvet worm of the genus Oroperipatus (Onychophora: Peripatidae) from western Amazonia"

Raw photographs, without brightness and contrast adjustments, corresponding to those shown in Figure 3 of "A new species of velvet worm of the genus Oroperipatus (Onychophora: Peripatidae) from western Amazonia". Photographs published in Figure 3 were obtained by stacking using CombineZP 1.0 software, and then adjusted for brightness and contrast to highlight taxonomically important structures with Adobe Photoshop CC 2020 software (Adobe Systems, USA). Fig. 3. Tegument and legs morphology of Oroperipatus tiputini sp. nov. A. Dorsal integument. B. Ventral detail of right leg V showing five spinous pads and nephridial tubercule (np) indented at third spinous pad. C. Genital pad and pregenital legs of right side showing crural tubercules pointed by white arrows. Scales bars: 1 mm (A), 0.2 mm (B), 0.4 mm (C).

Modelled temperature, mortality impact, and external benefits of cool roofs and rooftop photovoltaics in London - supporting data

Supporting data for "Modelled temperature, mortality impact, and external benefits of cool roofs and rooftop photovoltaics in London" Included are outputs from the Weather Research and Forecast (WRF) model. All simulations cover London, United Kingdom over summer 2018. Scenarios include a "baseline" which represents the real urban climate of the region, and scenarios which model 100% coverage of rooftops with either high albedo materials or solar panels. Data are provided in netCDF format. <ul> <li>The baseline simulation which models the current urban climate of the region WRF_Urb_BouLac_T2-V10-U10_20180525-20180831.nc</li> <li>The 100% rooftop-solar simulation WRF_Urb_BouLac_PV_T2-V10-U10-PSFC-RAINNC-TH2-Q2_20180525-20180831.nc</li> <li>The 100% high-albedo roof simulation WRF_Urb_BouLac_ClRf_T2-V10-U10-PSFC-RAINNC-TH2-Q2_20180525-20180831.nc</li> <li>The non-urban scenario is in WRF_NoUrb_BouLac_T2-V10-U10-PSFC-RAINNC-TH2-Q2_20180525-20180831.nc</li> <li>The power production estimates solarpv_prod_2018.nc</li> <li>wrf_popweighting-main.zip contains the analysis code. It is provided as-is with no guarantee of usability.</li> </ul> T2 means air temperature at 2m height. V10 and U10 are windspeeds at 10m height. PSFC is surface level pressure. TH2 is potential temperature. Q2 is specific humidity at 2m height. More description of the simulations is given in the citing article.

opencc-by-4.0Jun 2024View details →

Complex Lava Tube Networks Developed Within the 1792-93 Lava Flow Field on Mount Etna (Italy): Insights for hazard assessment Supporting Informations: Maps and sections of the lava tubes

<div> <div> <div> This supporting information for the above paper submitted to Frontiers in Earth Science - Volcanology, comprises Table 1, as well as the maps and sections of the 8 lava tubes analyzed in this paper, that are located within the 1792-93 lava flow field at Etna volcano. The methods used for the new surveys of the lava tubes are also explained. </div> </div> </div>

opencc-by-4.0Sep 2022View details →

Supporting Data for: The V30 Benchmark Set for Anharmonic Vibrational Frequencies of Molecular Dimers

Intermolecular vibrations are extremely challenging to describe but are the most crucial part for determining entropy and hence free energies, and enable for instance the distinction between different crystal-packing arrangements of the same molecule via THz spectroscopy. Herein, we introduce a benchmark data set - V30 - containing 30 small molecular dimers with intermolecular interactions ranging from exclusively van-der-Waals dispersion to systems with hydrogen bonds. All calculations are performed with the gold standard of Quantum Chemistry CCSD(T). We discuss vibrational frequencies obtained via different models starting with the harmonic approximation over independent Morse oscillators up to second-order vibrational perturbation theory (VPT2), which allows a proper anharmonic treatment including coupling of vibrational modes. However, large amplitude motions present in many low-frequency intermolecular modes are problematic for VPT2. In analogy to the often used treatment for internal rotations, we replace such problematic modes by a simple one-dimensional hindered rotor model. We compare selected dimers with available experimental data or high-level calculations of potential energy surfaces and show that VPT2 in combination with hindered rotors can yield a very good description of fundamental frequencies for the discussed subset of dimers involving small and semi-rigid molecules. This supporting dataset includes the calculated force constants, harmonic frequencies, Morse frequencies, VPT2 frequencies, and the optimized structures for the V30 dataset. See the included README.md file for more details. The related preprint can be found at <a href="https://doi.org/10.48550/arXiv.2209.04392">https://doi.org/10.48550/arXiv.2209.04392</a>.

opencc-by-4.0Sep 2024View details →

Supporting Datasets for 'The longest documented distance traveled by a West Indian manatee'

This dataset contains multiple sources of geospatial and environmental data used for the analysis of Tico's journey. This is a West-Indian manatee that was rescued, rehabilitated and tracked after release. Tico traveled approximately 4,017 km over 62 days through deep oceanic waters. Correlating Tico's trajectory and velocity with surface currents revealed the influence of the North Brazil Current (NBC) and its vortices on his trajectory. The data integrates satellite remote sensing, ocean reanalysis, . The dataset include: <ol> <li> Geographic locations of Tico (Delemetry Data) </li> <li> General Bathymetric Chart of the Oceans (GEBCO) </li> <li> NEMO - Global Ocean Physics Analysis and Forecast data: Surface current data from the NEMO model provided by CMEMS (GLORYS reanalysis). </li> <li> HYCOM Global Ocean Forecasting System (GOFS) 3.1 Analysis: </li> <li> OSCAR - Ocean Surface Current Analyses Real-time </li> <li> Soil Moisture Active Passive (SMAP) </li> <li> Integrated Multi-satellite Retrievals for Global Precipitation Measurements (IMERG) </li> </ol> Disclaimer: This dataset is a compilation of various data sources, each of which may be subject to its own specific licensing terms and conditions. Users of this dataset are strongly advised to review the license associated with each individual sub-dataset before using, modifying, or redistributing the data. While we have provided the dataset under a Creative Commons Attribution 4.0 International (CC BY 4.0) license, certain sub-datasets may have additional restrictions or requirements, such as attribution, non-commercial use, or limitations on derivative works. It is the responsibility of the user to ensure compliance with all applicable licenses. Please refer to the original data sources and their respective licenses for detailed information.