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4,753 results for “shape”
Data from: Satellite-based Lagrangian model reveals how upwelling and oceanic circulation shape krill hotspots in the California Current System [updated]
<p><strong>Abstract</strong></p> <p>In the California Current System, wind-driven nutrient supply and primary production, computed from satellite data, provide a synoptic view of how phytoplankton production is coupled to upwelling. In contrast, linking upwelling to zooplankton populations is difficult due to relatively scarce observations and the inherent patchiness of zooplankton. While phytoplankton respond quickly to environmental forcing, zooplankton grow slower and tend to aggregate into mesoscale “hotspot” regions spatially decoupled from upwelling centers. To better understand mechanisms controlling the formation of zooplankton hotspots, we use a satellite-based Lagrangian method where variables from a plankton model, forced by wind-driven nutrient supply, are advected by near-surface currents following upwelling events. Modeled zooplankton distribution reproduces published accounts of euphausiid (krill) hotspots, including the location of major hotspots and their interannual variability. This satellite-based modeling tool is used to analyze the variability and drivers of krill hotspots in the California Current System, and to investigate how water masses of different origin and history converge to form predictable biological hotspots. The Lagrangian framework suggests that two conditions are necessary for a hotspot to form: a convergence of coastal water masses, and above average nutrient supply where these water masses originated from. The results highlight the role of upwelling, oceanic circulation, and plankton temporal dynamics in shaping krill mesoscale distribution, seasonal northward propagation, and interannual variability.</p> <p><strong>Data set description</strong></p> <p>This data set includes 2 files:</p> <ul> <li>a satellite-based 1993-2023 monthly retrospective of krill concentrations (Zbig) modeled using the growth-advection method in the California Current upwelling system. Inputs include the nitrate supply product described below and GlobCurrent 15 m oceanic currents. This dataset is updated monthly (using NRT data) at https://www.mbari.org/science/upper-ocean-systems/biological-oceanography/krill-hotspots-in-the-california-current/.</li> <li>a satellite-based 1993-2023 monthly retrospective of wind-driven nitrate supply estimated in a 150 km coastal band at 0.125° latitudinal resolution. Nitrate supply was calculated based primarily on CCMP v3.1 winds, AVISO geostrophic currents, and a climatology of in situ nitrate at 60m. This dataset is updated monthly (using NRT data) at https://www.mbari.org/science/upper-ocean-systems/biological-oceanography/nitrate-supply-estimates-in-upwelling-systems/.</li> </ul> <p>See details regarding data sources and calculations in <a href="https://doi.org/10.3389/fmars.2022.835813">Messié et al. (2022)</a>.</p> <p>[IMPORTANT NOTE:] There is an error in the Ekman pumping fields (trans_pump, Nsupply_pump, Nsupply_total) that will be corrected soon (those fields are not used in publications where only coastal transport was considered). Please contact me if you need Ekman pumping fields before this is fixed.</p>
Role of Personal Connections in Shaping Decisions About Private Forest Use in Central Massachusetts 2008
We begin with a simple premise: Social and ecological systems are interconnected in complex ways. Forests are, perhaps, one of the most intriguing examples of this interconnectedness--particularly those in private ownerships. Forested landscapes are essential in maintaining human systems through the provision of multiple ecosystem services that span public (e.g., clean water, nutrient cycling) and private (e.g., fiber, maple syrup, home sites) goods. However, the majority of forestland in the Eastern United States is a mosaic of small landholdings (less than 20 ha) where property management is largely uncoordinated. On such landscapes, decentralized, ownership-centric decision-making defines the mix of ecosystem services provided and the landscape patterns present now and in the future. While somewhat effective for less spatially sensitive ecosystem services (e.g., fiber production), this ownership-centric approach is ill suited to spatially sensitive ones (e.g., water quality) and may, in some cases, be detrimental to them (e.g., habitat fragmentation). Improving the ecological and landscape sensitivity of private forest conservation and management is a major challenge facing researchers, practitioners, and policymakers in sustaining forest ecosystems. Central to unraveling this challenge is a fundamental understanding of how landowners simultaneously fit within their social and bio-physical landscapes. Despite their importance to broader forest sustainability, our collectively understanding of forest landowners has been primarily concerned with individual landowners and/or individual properties. For example, most research surrounding private forest landowners centers on primarily agent-based theories of behavior or decision-making (e.g., rational actor, theory of planned behavior). This perspective is useful in predicting and effecting behavior at broad scales, but lacks the specificity needed to address local landscape concerns and/or opportunities. Other studies
Dataset of "Elucidation of factors shaping reactivity of 5'-deoxyadenosyl – a prominent organic radical in biology"
<p>This study investigates the factors modulating the reactivity of 5'-deoxyadenosyl (5'dAdo•) radical, a potent hydrogen atom abstractor, present in the active sites of radical SAM enzymes, but otherwise undergoing a rapid self-decay in aqueous solution. Here, we compare hydrogen atom abstraction (HAA) reactions between native substrates of radical SAM enzymes and 5'dAdo• in aqueous solution and in two enzymatic microenvironments and reveal that HAA efficiency of 5'dAdo• depends on (i) formation of 5'dAdo• in a pre-ordered complex with a substrate, which attenuates the unfavorable effect of substrate:5'dAdo• complex formation, (ii) hindering the conformational change associated with self-decay by performing the reaction in a tight cavity. The enzymatic cavity, however, does not have a strong effect on the HAA activity of 5'dAdo•. We performed an analysis of HAA performed by 5'dAdo• based on the three-component thermodynamic model incorporating the diagonal effect of the free energy of reaction, and the off-diagonal effect of asynchronicity and frustration. The study is based on the straightforward relationship between the off-diagonal thermodynamic effects and the electronic-structure descriptor – the redistribution of charge between the reactants during the reaction. It allows to access HAA-competent redox and acidobasic properties of 5'dAdo• that are otherwise unavailable due to its instability upon one-electron reduction and protonation. The results show that all reactions feature a favourable thermodynamic driving force and tunneling, the latter of which lowers systematically barriers by ~2 kcal mol-1. In addition, most of the reaction experience a favourable off-diagonal thermodynamic contribution. In HAA reactions, 5'dAdo• acts as a weak oxidant as well as a base, also 5'dAdo•-promoted HAA reactions proceed with quite low degree of asynchronicity of proton and electron transfer. Finally, the study elucidates the crucial and dual role of asynchronicity. It directly lowers the barrier as a part of the off-diagonal thermodynamic contribution, but also indirectly increases the non-thermodynamic part of the barrier by controlling the adiabatic coupling between proton and electron transfer. The latter signals that the reaction proceeds as a hydrogen atom transfer rather than a proton-coupled electron transfer.</p>
Natural frequency of oscillations of a solid surface (without holes) and perforated sieve with holes of complex geometry in the shape of five-petal epicycloid
<p>The experimental determination of the structural function of the frequency response consists in identifying the natural frequencies of oscillation of the test surfaces, for which the laboratory equipment was developed, and the following methodology was used. </p> <p>To determine the structural function of the frequency response, it is necessary to obtain two data channels: the input force and the corresponding response of the test object (test surface). In impact measurement, the input force is provided by a modal impact hammer, and the output response of the test object (test surface) is measured using an accelerometer.<br>The basic elements of the scheme are a special impact pulse type hammer PCB 084A17 for creating excitations (oscillations); cables for signals transmission; accelerometer sensor PCB 352V10 with highly sensitive piezoelectric elements for fixing oscillations; signal amplifier SIEMENS model SCADAS Mobile; computer with Simcenter Testlab 2019.1 software for processing and visualization test results.</p> <p>The study was conducted according to the following algorithms:<br>1. Test setup: boundary conditions; determination of test scheme and parameters; frequency range; determination of excitation source and force level.<br>2. Testing: installation and control of accelerometers; object excitation and frequency response measurement; check of measurement quality and coherence.<br>3. Post-test: modal curve fitting; validation of the modality against the assurance criterion and modal synthesis.<br>The research was carried out using the following algorithm. </p> <p>The perforated surface prototype was rigidly fixed to the prefabricated frame. With this type of fixation, the investigated surface at the periphery is fixed and unable to move.<br>The surface of the prototype was marked by overlaying a coordinate grid with the specified step.<br>This data of natural frequency of oscillations of a solid surface under various modes, which are obtained experimentally. The obtained oscillation frequencies are needed to determine the difference between the construction of a solid plate and a perforated surface with holes of complex geometry.</p>
Nucleation-Limited Kinetics of GaAs Nanostructures Grown by Selective Area Epitaxy: Implications for Shape Engineering in Optoelectronics Devices
<p>This dataset corresponds to the following manuscript: </p> <p>Zendrini, M., Dubrovskii, V., Rudra, A., Dede, D., Fontcuberta i Morral, A., Piazza, V. “Nucleation-Limited Kinetics of GaAs Nanostructures Grown by Selective Area Epitaxy: Implications for Shape Engineering in Optoelectronics Devices” <em>ACS Applied Nano Materials 7,16 (2024):</em> 19065–19074</p> <p>DOI: <a href="http://doi.org/10.1021/acsanm.4c02765">doi.org/10.1021/acsanm.4c02765</a></p> <p>The dataset contains raw SEM images in .tif format for all the arrays of nanowires and nanomembranes discussed in the paper. The dataset also contains the AFM scans in .xyz format for all the arrays of nanowires and nanomembranes. The data for the morphological analysis are extracted from the SEM images and the AFM scans and they are collected in two separate .txt files for NWs and NMs.</p>
Insights on global rangeland ecosystem services shaped by grazing and fertilization (2007-2021)
The Nutrient Network (NutNet) is a globally coordinated research initiative aimed at investigating the impacts of human-induced changes in nutrient availability and consumer presence on grassland ecosystems. In this study, we used data from 79 grassland sites participating in NutNet, which includes a factorial experiment involving herbivory exclusion and/or nutrient addition. Standardized methodologies were applied across all sites to facilitate direct comparisons of response variables. We used ecosystem variables to quantify three provisioning ecosystem services (forage quantity, forage chemical quality, and forage physical quality), three supporting services (forage stability, soil fertility, and soil stability), and eight regulating services (erosion control, control of soil acidification, regulation of water quantity and quality, carbon storage, resistance to plant invasion, pest control, and pollination). Additionally, we identified three plant biodiversity variables that are closely related to the provisioning of ecosystem services (alpha richness, beta diversity, and native diversity). Using this data, we quantified key ecosystem services provided by rangelands, assessed both short- and long-term impacts of grazing exclusion and fertilization on these services, and identified synergies and trade-offs between them.
Microplastic Abundance, Shape, and Color in Passerines Captured at Rushton Woods Preserve Bird Banding Station in Newtown Square, Pennsylvania, USA, April-September 2024
Fecal samples were collected from 5 species of passerine birds between April and September 2024 at the Rushton Woods Preserve Bird Banding Station. Samples were chemically digested and filtered for the purpose of extracting, quantifying, and describing microplastics.
MCR LTER: Coral Reef: Spatial portfolios in coral metapopulations are shaped by spatiotemporal asynchrony in environmental conditions; Data for Srednick et al., 2026 Ecology Letters
Using wavelet analyses of a 19-year coral community timeseries from Moorea, French Polynesia, we quantified timescale-specific population synchrony in four common coral genera and evaluated the predictors of spatial portfolio effects. We detected synchrony within genera associated with synchrony in degree heating days, diurnal temperature range (DTR), and macroalgal cover at different timescales. Synchrony in DTR and macroalgal cover was associated with lower synchrony of Pocillopora and Porites populations, respectively. Population (for three of four genera) and environmental synchrony were stronger within than among habitats across timescales, underscoring the role of habitat-specific conditions in driving spatial synchrony and spatial portfolios. These results describe how the spatial and temporal scales of heterogeneity in environmental and ecological conditions determine synchrony in coral population dynamics and support a spatial portfolio effect, which may buffer coral metapopulations from island-scale collapse. Data in support of analyses for: Spatial portfolios in coral metapopulations are shaped by spatiotemporal asynchrony in environmental conditions. Published in Ecology Letters 2026.
Diffraction images used to solve the structures published in the article "Contribution of Shape and Charge to the Inhibition of a Family GH99 endo-α-1,2-Mannanase"
<p>Raw diffraction images used for generating the structures published in the article "Contribution of Shape and Charge to the Inhibition of a Family GH99 endo-α-1,2-Mannanase" (available <a href="https://doi.org/10.1021/jacs.6b10075">here</a>). Full single-crystal datasets are published. The software used for the processing of each dataset is listed in their respective PDB entries.</p> <p> </p> <p>If you find this useful, please contact me at <a href="mailto:lukasz.sobala@hirszfeld.pl">lukasz.sobala@hirszfeld.pl</a>, I am just interested in how these data are used!</p>
Spherical harmonic models of the shape of Titan
<p>This archive contains spherical harmonic models of the shape of Saturn's moon Titan constructed from data collected by the Cassini mission. Two such models are here archived:</p> <ul> <li>Titan_shape_Mitri2014_unnorm.sh (Mitri et al. 2014)</li> <li>Titan_shape_Corlies2017_unnorm.sh (Corlies et al. 2017)</li> </ul> <p>Both models make use of unnormalized spherical harmonic functions that include the Condon-Shortley phase factor of (-1)^m. The model from Mitri et al. (2014) is developed to spherical harmonic degree 6, whereas the model of Corlies et al. (2017) is developed to degree 8. Note that most gravity models of Titan use spherical harmonic functions that exclude the Condon-Shortley phase factor.</p>
Spherical harmonic models of the shape of asteroid (1) Ceres [JPL SPC]
<p>This archive contains two spherical harmonic models of the shape of asteroid (1) Ceres, truncated at different maximum spherical harmonic degrees. The highest resolution model has a maximum spherical harmonic degree of 1023, which was generated from an ICQ shape model with Q=1024.</p> <p>The data used to generate these models are from a JPL stereo photoclinometric shape model based on Dawn framing camera images, as found in the file <code>CERES_SPC181019_1024.ICQ</code> on <a href="https://sbnarchive.psi.edu/pds3/dawn/fc/DWNCSPC_4_01/DATA/ICQ/">NASA's PDS website</a>. The vertices were first converted from Cartesian to spherical coordinates, from which a regular gridline registered netcdf file was created using the <a href="https://www.generic-mapping-tools.org/">generic-mapping-tools</a> function <code>surface</code> with a tension of 0.6 and with a grid spacing of 0.087890625 degrees. This file was then read into the <a href="https://shtools.github.io/SHTOOLS/index.html">pyshtools</a> software and expanded into spherical harmonics using the function <code>SHCoeffs.expand()</code>. The spherical harmonic functions were chosen to be "4pi" normalized and to exclude the Condon-Shortley phase factor of (-1)<sup>m</sup>. The units of the coefficients are meters.</p> <p>The two files in this archive are</p> <ul> <li>Ceres_JPL_SPC_shape_1023.sh.gz</li> <li>Ceres_JPL_SPC_shape_719.sh.gz</li> </ul> <p>The numbers 1023 and 719 in the filename refer to the maximum spherical harmonic degree of file, which corresponds to effective spatial resolutions of ~11.4 and 8 pixels per degree, respectively. The files are stored in the binary "bshc" format as described in the pyshtools documentation and are furthermore compressed using gzip. The lower resolution model was generated by truncating the spherical harmonic coefficients of the highest resolution model.</p>
Spherical harmonic models of the shape of Enceladus [JPL SPC]
<p>This archive contains two spherical harmonic models of the shape of Saturn's moon Enceladus, truncated at different maximum spherical harmonic degrees. The highest resolution model has a maximum spherical harmonic degree of 1023, which was generated from an ICQ shape model with Q=1024.</p> <p>The data used to generate these models are from a JPL stereo photoclinometric shape model based on images obtained by the Cassini mission, as found in the file <code>cas_enceladus_ssd_spc_1024icq_v1.bds</code> on <a href="https://naif.jpl.nasa.gov/pub/naif/pds/data/co-s_j_e_v-spice-6-v1.0/cosp_1000/data/dsk/">NASA's PDS website</a>. The vertices were first converted from Cartesian to spherical coordinates, from which a regular gridline registered netcdf file was created using the <a href="https://www.generic-mapping-tools.org/">generic-mapping-tools</a> function <code>surface</code> with a tension of 0.6 and with a grid spacing of 0.087890625 degrees. This file was then read into the <a href="https://shtools.github.io/SHTOOLS/index.html">pyshtools</a> software and expanded into spherical harmonics using the function <code>SHCoeffs.expand()</code>. The spherical harmonic functions were chosen to be "4pi" normalized and to exclude the Condon-Shortley phase factor of (-1)<sup>m</sup>. The units of the coefficients are meters.</p> <p>The two files in this archive are</p> <ul> <li>Enceladus_JPL_SPC_shape_1023.bshc.gz</li> <li>Enceladus_JPL_SPC_shape_719.bshc.gz</li> </ul> <p>The numbers 1023 and 719 in the filename refer to the maximum spherical harmonic degree of file, which corresponds to effective spatial resolutions of ~11.4 and 8 pixels per degree, respectively. The files are stored in the binary "bshc" format as described in the pyshtools documentation and are furthermore compressed using gzip. The lower resolution model was generated by truncating the spherical harmonic coefficients of the highest resolution model.</p>
Spherical harmonic models of the shape of the Moon (principal axis coordinate system) [LOLA]
<p>This archive contains four spherical harmonic models of the shape of the Moon in a principal axis coordinate system, truncated at different maximum spherical harmonic degrees. The highest resolution model has a maximum spherical harmonic degree of 5759, which was generated from a lunar shape model sampled at 64 pixels per degree.</p> <p>The data used to generate these models are from the LOLA instrument on the Lunar Reconaissance Orbiter, as found in the file <code>ldem_64_pa.img</code> on <a href="https://pds-geosciences.wustl.edu/lro/lro-l-lola-3-rdr-v1/lrolol_1xxx/data/lola_gdr/cylindrical/pa/">NASA's PDS website</a>. This image file was first converted to netcdf format using the <a href="https://www.generic-mapping-tools.org/">generic-mapping-tools</a> function <code>xyz2grd</code>, and the resulting gridline-registered netcdf file was read into the <a href="https://shtools.github.io/SHTOOLS/index.html">pyshtools</a> software and expanded into spherical harmonics using the function <code>SHCoeffs.expand()</code>. The spherical harmonic functions were chosen to be "4pi" normalized and to exclude the Condon-Shortley phase factor of (-1)<sup>m</sup>. The units of the coefficients are meters.</p> <p>The four files in this archive are</p> <ul> <li>Moon_LOLA_shape_pa_5759.bshc.gz</li> <li>Moon_LOLA_shape_pa_2879.bshc.gz</li> <li>Moon_LOLA_shape_pa_1439.bshc.gz</li> <li>Moon_LOLA_shape_pa_719.bshc.gz</li> </ul> <p>The numbers 5759, 2879, 1439, and 719 in the filename refer to the maximum spherical harmonic degree of file, which corresponds to effective spatial resolutions of 64, 32, 16, and 8 pixels per degree, respectively. The files are stored in the binary "bshc" format as described in the pyshtools documentation and are furthermore compressed using gzip. The lower resolution models were generated by truncating the spherical harmonic coefficients of the highest resolution model.</p> <p>This shape model uses the same coordinate system as most lunar gravity models. The principal axis coordinate system differs from the more common mean Earth/polar axis system by about 1 km at the equator. For a mean Earth/polar axis model, use <a href="../records/10796823">Spherical harmonic models of the shape of the Moon</a>.</p>
Spherical harmonic models of the shape of the Moon [LOLA]
<p>This archive contains four spherical harmonic models of the shape of the Moon truncated at different maximum spherical harmonic degrees. The highest resolution model has a maximum spherical harmonic degree of 5759, which was generated from a lunar shape model sampled at 64 pixels per degree in the DE421 mean Earth/polar axis coordinate frame.</p> <p>The data used to generate these models are from the LOLA instrument on the Lunar Reconaissance Orbiter, as found in the file <code>ldem_64_float.img</code> on <a href="https://pds-geosciences.wustl.edu/lro/lro-l-lola-3-rdr-v1/lrolol_1xxx/data/lola_gdr/cylindrical/float_img/">NASA's PDS website</a>. This image file was first converted to netcdf format using the <a href="https://www.generic-mapping-tools.org/">generic-mapping-tools</a> function <code>xyz2grd</code>, and the resulting pixel registed map was then converted to a gridline registration using the function <code>grdsample</code>. Following this, the resulting netcdf file was read into the <a href="https://shtools.github.io/SHTOOLS/index.html">pyshtools</a> software and expanded into spherical harmonics using the function <code>SHCoeffs.expand()</code>. The spherical harmonic functions were chosen to be "4pi" normalized and to exclude the Condon-Shortley phase factor of (-1)<sup>m</sup>. The units of the coefficients are meters.</p> <p>The four files in this archive are</p> <ul> <li>Moon_LOLA_shape_5759.bshc.gz</li> <li>Moon_LOLA_shape_2879.bshc.gz</li> <li>Moon_LOLA_shape_1439.bshc.gz</li> <li>Moon_LOLA_shape_719.bshc.gz</li> </ul> <p>The numbers 5759, 2879, 1439, and 719 in the filename refer to the maximum spherical harmonic degree of file, which corresponds to effective spatial resolutions of 64, 32, 16, and 8 pixels per degree, respectively. The files are stored in the binary "bshc" format as described in the pyshtools documentation and are furthermore compressed using gzip. The lower resolution models were generated by truncating the spherical harmonic coefficients of the highest resolution model.</p> <p>Note that this shape model should not be used in conjunction with most gravity models of the Moon. The gravity models use a principal axis coordinate system that differs from the mean Earth/polar axis frame by about 1 km at the equator. For a principal axis coordinate system model, use <a href="../doi/10.5281/zenodo.10796953">Spherical harmonic models of the shape of the Moon (principal axis coordinate system)</a>.</p>
Spherical harmonic models of the shape of asteroid (4) Vesta [DLR SPG]
<p>This archive contains four spherical harmonic models of the shape of asteroid 4 Vesta, truncated at different maximum spherical harmonic degrees. The highest resolution model has a maximum spherical harmonic degree of 5759, which was generated from a shape model sampled at 64 pixels per degree.</p> <p>The data used to generate these models are from a DLR stereo photogrammetric shape model based on Dawn high altitude mapping orbit framing camera images, as found in the file <code>VE_HAMO_G_00N_330E_EQU_DTM.IMG</code> on <a href="https://sbnarchive.psi.edu/pds3/dawn/fc/DWNVSPG_2/DATA/">NASA's PDS website</a>. This image file was first converted to netcdf format using the <a href="https://www.generic-mapping-tools.org/">generic-mapping-tools</a> function <code>xyz2grd</code>, and it was then converted to a gridline registration using the function <code>grdsample</code>. The grid was then shifted such that the frist column corresponded to 0 E longitude using the function <code>grdedit</code>, and the resulting netcdf file was read into the <a href="https://shtools.github.io/SHTOOLS/index.html">pyshtools</a> software and expanded into spherical harmonics using the function <code>SHCoeffs.expand()</code>. The spherical harmonic functions were chosen to be "4pi" normalized and to exclude the Condon-Shortley phase factor of (-1)<sup>m</sup>. The units of the coefficients are meters.</p> <p>The four files in this archive are</p> <ul> <li>Vesta_DLR_SPG_shape_5759.bshc.gz</li> <li>Vesta_DLR_SPG_shape_2879.bshc.gz</li> <li>Vesta_DLR_SPG_shape_1439.bshc.gz</li> <li>Vesta_DLR_SPG_shape_719.bshc.gz</li> </ul> <p>The numbers 5759, 2879, 1439, and 719 in the filename refer to the maximum spherical harmonic degree of file, which corresponds to effective spatial resolutions of 64, 32, 16, and 8 pixels per degree, respectively. The files are stored in the binary "bshc" format as described in the pyshtools documentation and are furthermore compressed using gzip. The lower resolution models were generated by truncating the spherical harmonic coefficients of the highest resolution model.</p>
Spherical harmonic models of the shape of asteroid (1) Ceres [DLR SPG]
<p>This archive contains four spherical harmonic models of the shape of asteroid (1) Ceres, truncated at different maximum spherical harmonic degrees. The highest resolution model has a maximum spherical harmonic degree of 5399, which was generated from a shape model sampled at 60 pixels per degree.</p> <p>The data used to generate these models are from a DLR stereo photogrammetric shape model based on Dawn high altitude mapping orbit framing camera images, as found in the file <a href="https://sbnarchive.psi.edu/pds3/dawn/fc/DWNCHSPG_2/DATA/"><code>CE_HAMO_G_00N_180E_EQU_DTM.IMG</code></a> on <a href="https://sbnarchive.psi.edu/pds3/dawn/fc/DWNCHSPG_2/DATA/">NASA's PDS website</a>. This image file was first converted to netcdf format using the <a href="https://www.generic-mapping-tools.org/">generic-mapping-tools</a> function <code>xyz2grd</code>, it was then converted to a gridline registration using the function <code>grdsample</code>, and the resulting netcdf file was read into the <a href="https://shtools.github.io/SHTOOLS/index.html">pyshtools</a> software and expanded into spherical harmonics using the function <code>SHCoeffs.expand()</code>. The spherical harmonic functions were chosen to be "4pi" normalized and to exclude the Condon-Shortley phase factor of (-1)<sup>m</sup>. The units of the coefficients are meters.</p> <p>The four files in this archive are</p> <ul> <li>Ceres_DLR_SPG_shape_5399.bshc.gz</li> <li>Ceres_DLR_SPG_shape_2879.bshc.gz</li> <li>Ceres_DLR_SPG_shape_1439.bshc.gz</li> <li>Ceres_DLR_SPG_shape_719.bshc.gz</li> </ul> <p>The numbers 5399, 2879, 1439, and 719 in the filename refer to the maximum spherical harmonic degree of file, which corresponds to effective spatial resolutions of 60, 32, 16, and 8 pixels per degree, respectively. The files are stored in the binary "bshc" format as described in the pyshtools documentation and are furthermore compressed using gzip. The lower resolution models were generated by truncating the spherical harmonic coefficients of the highest resolution model.</p>
Spherical harmonic models of the shape of Mars [MOLA]
<p>This archive contains four spherical harmonic models of the shape of Mars truncated at different maximum spherical harmonic degrees. The highest resolution model has a maximum spherical harmonic degree of 5759, which was generated from a Mars shape model sampled at 64 pixels per degree.</p> <p>The data used to generate these models are from the MOLA instrument on the Mars Global Surveyor spacecraft, as found in the files <code>MEGR00N000GB.IMG</code>, <code>MEGR00N180GB.IMG</code>, <code>MEGR90N000GB.IMG</code> and <code>MEGR90N180GM.IMG</code> on <a href="https://pds-geosciences.wustl.edu/mgs/mgs-m-mola-5-megdr-l3-v1/mgsl_300x/meg064/">NASA's PDS website</a>. These four image files were first converted to netcdf format using the <a href="https://www.generic-mapping-tools.org/">generic-mapping-tools</a> function <code>xyz2grd</code>, and then turned into a single file using the function <code>grdpaste</code>. The resulting pixel registed map was then converted to a gridline registration using the function <code>grdsample</code>. Following this, the resulting netcdf file was read into the <a href="https://shtools.github.io/SHTOOLS/index.html">pyshtools</a> software and expanded into spherical harmonics using the function <code>SHCoeffs.expand()</code>. The spherical harmonic functions were chosen to be "4pi" normalized and to exclude the Condon-Shortley phase factor of (-1)<sup>m</sup>. The units of the coefficients are meters.</p> <p>The four files in this archive are</p> <ul> <li>Mars_MOLA_shape_5759.bshc.gz</li> <li>Mars_MOLA_shape_2879.bshc.gz</li> <li>Mars_MOLA_shape_1439.bshc.gz</li> <li>Mars_MOLA_shape_719.bshc.gz</li> </ul> <p>The numbers 5759, 2879, 1439, and 719 in the filename refer to the maximum spherical harmonic degree of file, which corresponds to effective spatial resolutions of 64, 32, 16, and 8 pixels per degree, respectively. The files are stored in the binary "bshc" format as described in the pyshtools documentation and are furthermore compressed using gzip. The lower resolution models were generated by truncating the spherical harmonic coefficients of the highest resolution model.</p> <p>These models supercede <a href="../records/3870922">Spherical harmonic model of the shape of Mars: MarsTopo2600</a> and <a href="../records/6475460">Spherical harmonic model of the shape of Mars: MarsTopo719</a>.</p>
Inter-Chemical Correlation results for the study: HHEARx2018-2532 (Environmental Toxins in Early Life: Shaping Health and Disease in Childhood)
Title: Environmental Toxins in Early Life: Shaping Health and Disease in Childhood <br>Species: Homo sapiens <br>Number of samples: 1147 <br>Number of named analytes: 48 <br>Datasource url: https://hheardatacenter.mssm.edu/PublicFile/ViewPublicFile?projectid=69 <br>
Data to "Human shape perception spontaneously discovers the biological origin of novel, but natural, stimuli"
<p>This record contains analysis scripts (written in Matlab) as well as raw and processed data to reproduce the results shown in:</p> <p>Dehn, K.<strong>†</strong>, Maiello, G.<strong>†</strong>, Hartmann, F., Morgenstern, Y., Hawkins, S.J., Offner, T., Walter, J., Hassenklöver, T., Manzini, I., Fleming, R.W. (2024) Human shape perception spontaneously discovers the biological origin of novel, but natural, stimuli. bioRxiv, 2024-12. https://doi.org/10.1101/2024.12.21.629735 </p> <p><em><strong>†</strong>Co-first author</em></p>
Artisanal and farmer bread making practices differently shape fungal species community composition in French sourdoughs
<p>Datasets describing the fungal species diversity, microbial density and acidity of French sourdoughs, phenotypic variation of Kazachstania bulderi and Kazachstania humilis strains as well as the diversity of bread-making practices of 40 bakers and farmers-bakers.The data were collected, analyzed, and reported within the following publication :</p> <p>Elisa Michel, Estelle Masson, Sandrine Bubbendorf, Léocadie Lapicque, Thibault Nidelet, Diego Segond, Stéphane Guézenec, Thérèse Marlin, Hugo deVillers, Olivier Rué, Bernard Onno, Judith Legrand, Delphine Sicard and the participating bakers: <strong>Artisanal and farmer bread making practices differently shape fungal species community composition in French sourdoughs</strong>. PCI Evol. Biol.</p> <p> </p>
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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.