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1,610 results for “ratio”
Unsupervised Blink Detection Using Eye Aspect Ratio Values
<p>This datastore supports an open-source blink detection software which acts as both an implementation of methods proposed in the (unpublished) paper "Unsupervised Blink Detection Using Eye Aspect Ratio Values" and a validation of the results provided.</p> <p>The software can be accessed at the <strong>GitHub repository</strong>: <a href="https://github.com/mi3nts/tobiiBlinkDetection">https://github.com/mi3nts/tobiiBlinkDetection</a></p> <p>Although the study results can be displayed readily from the files provided at the GitHub, this datastore contains the required resources to apply the proposed blink detection algorithm to new data. Simply download this file and replace the resources folder of the cloned repository.</p>
Plantlet weight, including shoots and roots, and root/shoot ratio of Hylocereus polyrhizus 'Da Hong' grown on Murashige and Skoog (MS) medium supplemented with α-naphthaleneacetic acid (NAA) alone.
<p>Figure S2. Plantlet weight, including shoots and roots, and root/shoot ratio of <em>Hylocereus polyrhizus</em> ‘Da Hong’ grown on Murashige and Skoog (MS) medium supplemented with α-naphthaleneacetic acid (NAA) alone. Treatment: CS, control; TS01, 0.05 mg/L NAA; TS02, 0.10 mg/L NAA; TS03, 0.20 mg/L NAA. Mean ± SE (n = 3, 5 segments per replicate). Means followed by different letters near the column and circle are significantly different at <em>p </em>= 0.05 using Fisher’s protected LSD test.</p>
Aircraft profiles of stable isotope ratios in atmospheric total and condensed water from the NASA ORACLES mission.
<p>Aircraft in-situ measurements of water concentration and heavy water isotope ratios D/H and 18O/16O of cloud water and total water (water vapor plus condensed water) were collected during the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) project. Aircraft sampling took place in the southeast Atlantic marine boundary layer and lower troposphere (equator to 22 degrees south) over the months of Sept. 2016, Aug. 2017, and Oct. 2018. Isotope measurements were made using cavity ring-down spectroscopic analyzers integrated into the Water Isotope System for Precipitation and Entrainment Research (WISPER). The WISPER data are processed into mean latitude-altitude curtains and individual vertical profiles for each sampling period.</p> <p> </p> <p>The WISPER data accompanied a suite of other variables including standard meteorological quantities (wind, temperature, moisture), trace gas and aerosol concentrations, radar, and lidar remote sensing, which can be accessed through the DOIs listed further down. The ORACLES campaigns are described by Redemann et al., (2021). The water isotope measurements are further described in Henze et al., (2021). The absolute error with respect to the SMOW-SLAP scale is explained in detail by Henze et al., (2021).</p> <p> </p> <p>Total water concentration and isotope ratios were binned and averaged onto latitude-altitude grids using a kernel estimation approach, with weighting designed to estimate the mean during the approximate month-long duration of each sampling period. Standard deviations for each bin are also computed using kernel density estimation.</p> <p> </p> <p>Time intervals during aircraft vertical profiling are isolated and averaged onto 50-meter vertical levels. The files include water concentration and isotope ratios for both total water and cloud water in addition to temperature, pressure, latitude, and longitude.</p> <p> </p> <p>See included file README.txt for additional details.</p> <p> </p> <p>References</p> <p>---------------</p> <p>Henze, D., Noone, D., and Toohey, D.: Aircraft measurements of water vapor heavy isotope ratios in the marine boundary layer and lower troposphere during ORACLES, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2021-238, in review, 2021.</p> <p> </p> <p>Redemann, J., Wood, R., Zuidema, P., Doherty, S. J., Luna, B., LeBlanc, S. E., Diamond, M. S., Shinozuka, Y., Chang, I. Y., Ueyama, R., Pfister, L., Ryoo, J.-M., Dobracki, A. N., da Silva, A. M., Longo, K. M., Kacenelenbogen, M. S., Flynn, C. J., Pistone, K., Knox, N. M., Piketh, S. J., Haywood, J. M., Formenti, P., Mallet, M., Stier, P., Ackerman, A. S., Bauer, S. E., Fridlind, A. M., Carmichael, G. R., Saide, P. E., Ferrada, G. A., Howell, S. G., Freitag, S., Cairns, B., Holben, B. N., Knobelspiesse, K. D., Tanelli, S., L'Ecuyer, T. S., Dzambo, A. M., Sy, O. O., McFarquhar, G. M., Poellot, M. R., Gupta, S., O'Brien, J. R., Nenes, A., Kacarab, M., Wong, J. P. S., Small-Griswold, J. D., Thornhill, K. L., Noone, D., Podolske, J. R., Schmidt, K. S., Pilewskie, P., Chen, H., Cochrane, S. P., Sedlacek, A. J., Lang, T. J., Stith, E., Segal-Rozenhaimer, M., Ferrare, R. A., Burton, S. P., Hostetler, C. A., Diner, D. J., Seidel, F. C., Platnick, S. E., Myers, J. S., Meyer, K. G., Spangenberg, D. A., Maring, H., and Gao, L.: An overview of the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) project: aerosol–cloud–radiation interactions in the southeast Atlantic basin, Atmos. Chem. Phys., 21, 1507–1563, https://doi.org/10.5194/acp-21-1507-2021, 2021.</p> <p> </p> <p>The complete archive of ORACLES data are accessible via the digital object identifiers (DOIs) provided under ORACLES Science Team references as follows:</p> <p> </p> <p>ORACLES Science Team: Suite of Aerosol, Cloud, and Related Data Acquired Aboard P3 During ORACLES 2018, Version 3, NASA Ames Earth Science Project Office, https://doi.org/10.5067/Suborbital/ORACLES/P3/2018_V3, 2020a. </p> <p> </p> <p>ORACLES Science Team: Suite of Aerosol, Cloud, and Related Data Acquired Aboard P3 During ORACLES 2017, Version 3, NASA Ames Earth Science Project Office, https://doi.org/10.5067/Suborbital/ORACLES/P3/2017_V3, 2020b. </p> <p> </p> <p>ORACLES Science Team: Suite of Aerosol, Cloud, and Related Data Acquired Aboard P3 During ORACLES 2016, Version 3, NASA Ames Earth Science Project Office, https://doi.org/10.5067/Suborbital/ORACLES/P3/2016_V3, 2020c. </p> <p> </p> <p>ORACLES Science Team: Suite of Aerosol, Cloud, and Related Data Acquired Aboard ER2 During ORACLES 2016, Version 3, NASA Ames Earth Science Project Office, https://doi.org/10.5067/Suborbital/ORACLES/ER2/2016_V3, 2020d.</p>
Vasculature Segmentation Validation Dataset - Part II - Decreasing Contrast-To-Noise Ratio
<p>Dataset to allow exploration of data enhancement, segmentation, and validation for: https://www.biorxiv.org/content/10.1101/2020.07.21.213843v1 and associated future publications</p> <p><strong>Dataset description:</strong></p> <ul> <li><em><strong>LaserForNoise</strong></em>: Example data of the head vasculature of 4dpf of zebrafish. The data were consecutively acquired with 1.2%, 0.8%, and 0.4% laser power (LP), respectively. This allowed us to produce data with decreasing contrast-to-noise ratio, and thus study robustness over a range of signal distributions.</li> </ul> <p><em><strong>Data acquisition</strong></em>:<br> Experiments were performed according to the rules and guidelines of institutional and UK Home Office regulations under the Home Office Project Licence 70/8588 held by TC. Maintenance of adult zebrafish Tg(kdrl: HRAS-mCherry)s916 (Chi et al., 2008) was performed as described in standard husbandry protocols (Westerfield, 1993). Embryos, obtained from controlled mating, were kept in E3 medium buffer with methylene blue and staged as previously described (Kimmel et al., 1995).</p> <p>Embryos were embedded in 2% LMP-agarose with 0.01% Tricaine in E3 (MS-222, Sigma). Data were acquired using a Zeiss Z.1 light sheet microscope, Plan-Apochromat 20x/1.0 Corr nd=1.38 objective, dual-side illumination with online fusion, activated Pivot Scan, image acquisition chamber incubation at 28°C, with a scientific complementary metal-oxide-semiconductor (sCMOS) detection unit. Data properties can be summarised as: 16bit image depth, voxel dimensions in x, y and z of 1920 x 1920 x 400-600, respectively, giving a voxel size of 0.33 x 0.33 x 0.5 µm). </p> <p><strong>Contact</strong>: kugler.elisabeth[at]gmail.com</p> <p><strong>Useful code links</strong>: </p> <ul> <li>https://github.com/ElisabethKugler/ZFVascularQuantification</li> <li>https://github.com/ElisabethKugler/Matlab3D-ImageAnalysis</li> </ul>
ANI-1 dataset with added atomic volume ratios restricted to CHNO atoms for DNN-MBD
<p>ANI-1 dataset with added atomic volume ratios restricted to CHNO atoms for DNN-MBD</p>
Long-term resilience of primary sex ratios in a species with temperature dependent sex determination after decades of climate warming
<p><span>Species with environmental sex determination (ESD) have persisted through deep time, despite massive environmental perturbation in the geological record. Understanding how species with temperature-dependent sex determination (TSD), a type of ESD, persist through climate change is particularly timely given the current climate crisis, as highly biased sex ratios and extinction are predicted. Since 1982, we have studied primary sex ratios of a reptile with TSD (<em>Chelydra serpentina</em></span><span>). Primary sex ratios remained unchanged over time, despite warming in the environment. Resilience of the primary sex ratio occurred via a portfolio effect, realized through remarkable intra-annual variation in nest-level sex ratios, leading to a relatively consistent mean annual sex ratio. Intra-annual variation in nest-level sex ratios was related to variation in egg burial depth coupled with large clutch sizes, creating thermal gradients in the nest, and promoting mixed-sex clutches. Further, both locally and globally, sustained increases in nighttime air temperature contribute more to warming than increases in daily maximum temperature, but development rate was affected more strongly by maximum daily air temperature, conferring additional resilience to overall warming. Our study suggests that some TSD species may be resilient to warming and provides an example of how ESD may persist under environmental change.</span><span><br></span></p>
Expanding the Concept of Comprehensive Area Ratio Parameter to the South-Central States: Towards Simplifying the Structural Evaluation of Flexible Pavements at the Network Level
<p>The surface deflection bowl data collected through falling weight deflectometer (FWD) test is utilized by highway agencies in assessing the performance of the flexible pavement. However, a robust method to evaluate pavement sections utilizing FWD data from all the sensors is seldom developed. There is always a need for DOTs and highway agencies to have a simplified procedure, which can be directly implemented in agencies' databases. This study focuses on expanding and validating the concept of previously developed area ratio parameters towards the pavement section of South-Central States (Arkansas, Louisiana, New Mexico, Oklahoma, and Texas) in effectively analyzing the pavement performances. Simulation-based deflections are utilized to develop enhanced deflection-based parameters and to reduce the need for extensive FWD testing in the field. Ninety-seven pavement sections in these states are considered to implement and validate simplified procedures that will be readily available to various transportation agencies to evaluate their pavement conditions at the network level. Due to this purpose, a pavement ranking chart is proposed for the five South-Central states, which categorizes the pavement section into very good, good, fair, and poor pavement sections. Eventually, load-induced effects concerning developed parameters are effectively analyzed to predict the remaining service life of the flexible pavement structures. The developed methodologies will be helpful for DOTs and highway agencies to carry out the rehabilitation and maintenance work in time and estimate the budget required in these procedures.</p>
Environmental variation in sex ratios and sexual dimorphism in three wind-pollinated dioecious plant species
<p>Variation in plant sex ratios is often attributable to sex-specific mortality in heterogeneous environments that differentially limit male and female plant reproduction. Yet sexual dimorphism and plastic responses to environmental heterogeneity are common and may co-vary with variation in sex ratios. Here, we show that the sex ratio and the degree of sexual dimorphism for a number of plant traits varied along climatic and elevation gradients in three wind-pollinated dioecious species, <em>Rumex lunaria</em>, <em>Urtica dioica</em> and <em>Salix helvetica</em>. Some of the observed sex-specific responses to climatic variation are consistent with greater sensitivity of females to water scarcity, but most responses rather point to the greater sensitivity of males to ecological stress, consistent with larger male reproductive effort, as has been commonly reported for wind-pollinated plants. In contrast, we found no evidence for variation in either sex ratios or sexual dimorphism expected under sexual selection. Interestingly, sex ratios and sexual dimorphism varied both along distinct and the same ecological axes of variation, suggesting that the evolution of sexual dimorphism in the measured traits was not sufficient to prevent sex-specific mortality.</p>
Missing eddy feedback may explain weak signal to noise ratios in climate predictions
<p>Python scripts and data files required to reproduce all figures in the publication entitled "Missing eddy feedback may explain weak<br> signal to noise ratios in climate predictions". Please reference the publication if using this code or these data.</p>
Sperm limitation produces male biased family sex ratios
<p>Haplo-diploid sex determination in the parasitoid wasp, <em>Nasonia vitripennis</em> (Walker), allows females to adjust their brood sex ratios. Females influence whether ova are fertilized, producing diploid females, or remain unfertilized, producing haploid males. Females appear to adjust their brood sex ratios to minimize "local mate competition," <em>i.e.</em>, competition among sons for mates. Because mating occurs between siblings, females may optimize mating opportunities for their offspring by producing only enough sons to inseminate daughters when ovipositing alone and producing more sons when superparasitism is likely. Although widely accepted, this hypothesis makes no assumptions about gamete limitation in either sex. Because sperm is used to produce daughters, repeated oviposition could reduce sperm supplies, causing females to produce more sons. In contrast, if egg-limited females produce smaller broods, they might use fewer sperm, making sperm limitation less likely. To investigate whether repeated oviposition and female fertility influence gamete limitation within females, we created two treatments of six mated female wasps, which received a series of six hosts at intervals of 24 or 48 hrs. All females produced at least one mixed-sex brood (63 total broods; 3,696 offspring). As expected, if females became sperm limited, in both treatments, brood sex ratios became increasingly male-biased with increasing host number. The interhost interval did not affect brood size, total offspring number or sex ratio, indicating females did not become egg limited. Our results support earlier studies showing sperm depletion affects sex allocation in <em>N. vitripennis</em>¸ and could limit adaptive sex ratio manipulation in these parasitoid wasps.</p>
Dataset for: Mating competition and adult sex ratio in wild Trinidadian guppies
<p><span>Most experimental tests of mating systems theory have been conducted in the laboratory, using operational sex ratios (ratio of ready-to-mate male to ready-to-mate female) that are often not representative of natural conditions. Here, we first measured the range of adult sex ratio (proportion of adult males to adult females; ASR) in two populations of Trinidadian guppies (<em>Poecilia reticulata</em>) differing in ambient predation risk (high vs. low). We then explored, under semi-wild conditions, the effect of ASR (i.e. 0.17, 0.50, 0.83) on mating competition patterns in these populations. ASR in the wild was female-biased and did not significantly differ between the two populations. The range of ASR in our experiment was representative of natural ASRs. As expected, we observed an increase in intrasexual aggression rates in both sexes as the relative abundance of competitors increased. In support of the risky competition hypothesis, all measured behaviors had lower rates in a high vs. low predation-risk population, likely due to the costs of predation. In terms of mating tactics, a male-biased ASR did not lead males to favor forced mating over courtship,</span><span> </span><span>indicating that males did not compensate for the cost of competition by switching to a less costly alternative mating tactic</span><span>. </span><span>Overall, this study highlights the need for field experiments using natural ranges of ASRs to test the validity of mating systems theory in a more complex, ecologically relevant context.</span></p>
Type IIP Supernova Progenitors. III. Blue to Red Supergiant Ratio in Low-metallicity Models with Convective Overshoot (Dataset)
<p>MESA input and output files associated with the published journal article Wagle et al. (2020; doi:10.3847/1538-4357/ab8bd5). We used MESA version r-10398 and MESA SDK version 20180822 to run these models.</p> <p>The "MESA_inputs.tar.gz" file contains work directories for initial mass of 13 solar mass and several overshoot parameter (f) values as listed in Table 2 of the published article. The models can be run directly from each working directory ("f_*") by making (./mk) and then running MESA (./rn), after instantiating MESA SDK. The run-script ("rn") is modified to start a MESA run from the pre-main-sequence (preMS) stage through core-collapse (CC) stage, if the LOGS and photos directories are absent. Otherwise, it restarts MESA from the latest "photo" binary file saved in the photos directory (that is, it assumes that the previous run was interrupted and restarts the run. So, to start a fresh run delete the "LOGS" and "photos" directories.) Each working directory has "run_star_extras.f" file which is modified to save the compactness parameters, mu_4, M_4 as extra history columns, as well as, to implement additional temporal resolution constraints as explained in section 2.2 of the article. Any other combination of mass and f-value from Table 2 of the article can be run by changing initial_mass in "inlist_control" file, and overshoot values in "inlist_f*" file.</p> <p>Each "*M_z0.006_f_*.tar.xz" file has a "LOGS" directory that contains corresponding "history.data", "profile.data" at core-collapse (CC) stage and saved model ("*.mod") at CC stage for each mass and f-value combination from Table 2 of the paper. (Note: Please copy the tar.xz files for each mass in a separate folder before decompressing them, in order to avoid overwriting the folders with the same f-values.) The LOGS directory also contains a folder "png_plots" that has saved ".png" files generated by "inlist_pgstar". These files can be used to generate stellar evolution movies using the "images_to_movie.sh" script available in the MESA SDK.</p> <p> </p>
Environmental gradients predict the ratio of environmentally acquired carotenoids to self-synthesised pteridine pigments
<p>Carotenoids are important pigments producing integument coloration; however, their dietary availability may be limited in some environments. Many species produce red to yellow hues using a combination of carotenoids and self-synthesised pteridine pigments. A compelling but untested hypothesis is that pteridines replace carotenoids in environments where carotenoid availability is limited. Based on a phylogenetic comparative analysis of pigment concentrations in agamid lizards, we show that environmental gradients predict the ratio of carotenoids to pteridines; carotenoid concentrations are lower and pteridine concentrations higher in arid environments with low vegetation productivity. Both carotenoid and pteridine pigments were present in all species, but only pteridine concentrations explained colour variation among species and there were no correlations between carotenoid and pteridine pigments with similar hue. These results suggest that pteridine pigments replace carotenoids in carotenoid-limited environments, irrespective of skin hue, presumably because it is metabolically cheaper to synthesise pteridines than to acquire and sequester carotenoids when carotenoids are rare.</p>
Wolf pup sex ratios and covariates, Idaho, USA 2008-2018
<p>Wolf pup sex ratio data and associated covariates in Idaho USA (2008-2018).</p>
Data from: New perspectives on soil animal trophic ecology through the lens of C and N stable isotope ratios of oribatid mites
<p>Knowledge of the trophic ecology of soil animals is important for understanding their high alpha diversity as well as their functional role in soil food webs and systems. In the last 20 years, the analysis of natural variations in stable isotope ratios (<sup>15</sup>N/<sup>14</sup>N, <sup>13</sup>C/<sup>12</sup>C) has revolutionized our view on soil animal trophic ecology. Here, we review the state of the art of the trophic ecology of a highly abundant and diverse soil animal taxon, oribatid mites (Oribatida), investigated by stable isotope analyses. The review is based on 25 papers reporting stable isotope data of 292 oribatid mite taxa from 30 different sites. Four main findings emerged. (1) Oribatid mites cluster into six trophic groups, i.e. moss feeders, lichen feeders, primary decomposers, fungal feeders/secondary decomposers, predators/scavengers and marine algal feeders, plus one additional group, which incorporates CaCO<sub>3</sub> in their cuticle for defence but still belongs to the fungal feeders/secondary decomposers group. (2) Of the 292 species studied 43.7% were classified as fungal feeders/secondary decomposers, 27.0% as primary decomposers and 15.7% as predators/scavengers, only few species include CaCO<sub>3</sub> into their skeleton (6.1%), feed on lichens (4.9%), mosses (2.1%) or marine algae (0.7%). (3) In about one-third of the species studied the trophic niche was constant or varied little between sites or habitats, but in two-thirds of the species, their trophic niche varied between habitats, with some species even shifting trophic levels, indicating trophic plasticity. (4) When aggregated at higher taxonomic level oribatid mite species clustered in only three instead of six trophic groups. This indicates that species within the same high-level taxon often belong to different trophic groups, for example, because feeding habits evolved convergently. Therefore, to accurately reflect the trophic ecology of oribatid mites their stable isotope signatures need to be analysed at the species level. However, stable isotope analyses also have limitations, e.g. feeding on bacteria and fungi cannot be separated, and the same is true for feeding on ectomycorrhizal and arbuscular mycorrhizal fungi. Other methods such as fatty acid, amino acid and molecular gut content analyses as well as microbiome analyses may complement stable isotope studies and resolve oribatid mite trophic niche differentiation at a higher resolution. This will contribute to a better understanding of the local coexistence of large numbers of species in soil. Finally, we provide perspectives on how to integrate microarthropods into soil food webs using stable isotope and other methods allowing deeper insight into their<br>trophic structure.</p>
Data : Planktic-benthic foraminifera ratio (%P) as a tool for the reconstruction of paleobathymetry and geohazard: A case study from Taiwan
<p>Details of the core sites used in this study, gear used for recovery, sediment horizon analyzed, coordinates, water depth and foraminiferal data for the size fractions of >125 µm and >63 µm (only a subset of all the sites). Study sites are divided into East Taiwan that comprises the Southern Okinawa Trough (1), Nanao-Hoping-Hateruma Basins (2), and Taitung-Hualien (3). The area of West Taiwan is consisted of the Gaoping (4), Changchun sand Ridge (5), and Henghun Ridge (6) sectors. Gear for recovery are Box core (BC); Gravity core (GC) and Grab (G). Italic numbers in TOC column (in red) are average values, italic numbers in the Laboratory column show the laboratory where the TOC and C/N were analysed, namely Geosciences-NTU (1) , Institute of Oceanography-NTU (2) and National Sun-yat sen University (3). NaN= no available data. </p>
code and data for A new method applied for the determination of relative weight ratios under the TensorFlow platform when estimating coseismic slip distribution
<p>The zip file contains three folders:"Data for Illapel earthquake", "HVCE and ABIC method implement on matlab" and "GDED method implement on tensorflow". Take the simulation experiments 1.2 and actual Illapel earthquakes as examples. the code for GDED method are placed on "GDED method implement on tensorflow" folders, and the code for the ABIC method and the HVCE method are place on "HVCE and ABIC method implement on matlab" folders.</p> <p>In the file"HVCE and ABIC method implement on matlab", the meaning of each code are represent as following</p> <p><br> ABIC_SIM.m:the slip distribution inversion results with the relative weight ratios determined by ABIC method Of simulation experiments and Illapel earthquakes</p> <p><br> HVCE.m:the slip distribution inversion results with the relative weight ratios determined by HVCE method Of simulation experiments and Illapel earthquakes</p> <p><br> GDED.m:the slip distribution inversion results with the relative weight ratios determined by GDED method Of simulation experiments and Illapel earthquakes(the relative weight ratios are from the "GDED method implement on tensorflow")</p> <p>savedata.m: that code are used for save matrix or data for the GDED method implement on tensorflow</p> <p>In the file"GDED method implement on tensorflow", the meaning of each code are represent as following<br> joint_inver_tensor_ex_1.0(1.1).py: the code for determining the relative weight ratios by the GDED method with(without) plot figures, which implement on Tensorflow platform<br> <br> the InSAR data and GPS data of Illapel earthquakes are palce on the folder" Data for Illapel earthquake/GPS_ori.txt and InSAR_ori.txt"</p>
Lightcurves, Colour-Colour Ratio and CuSum plots for HD 179949 Chandra Observations - Acharya et al. (2022)
<p>Plots made for the paper "X-ray Activity on SPI Candidate HD 179949" Anshuman Acharya et al. (2022). This includes:<br> 1. All Light curves for the 7 passbands considered (4 physically motivated + 3 default Chandra passbands) + Broad band (0.5 - 7.0 keV) for the 5 datasets. The filename format is: "dataset ObsID"_"passband name"_lightcurve.pdf.<br> 2. Colour-colour ratios for the passbands (9 combinations) for the 5 datasets. The filename format is: "dataset ObsID"+ColourRatio_"soft passband name"+"hard passband name".pdf.<br> 3. Cumulative Sum of residuals plot for Model 1 (referred to as model 2m in the paper: chosen model for 6121, not chosen for 5427 and 6119) and Model 2 (referred to as model 2v in the paper: chosen model for 5427, 6119, 6121 and 6122). Note that Model 1 plots for ObsIDs 6120 and 6122 are not made as <span class="math-tex">\(\Delta\)</span>Cstat > 2 <span class="math-tex">\(\sigma\)</span> for them. The filename format is: Model1/Model2_"dataset ObsID"_residuals_for_CuSum.pdf.<br> 4. p-value calculated for the Cumulative Sums for all the above cases. The filename format is: Model1/Model2_"dataset ObsID"_p-value_for_CuSum.pdf.</p> <p>Dataset ObsIDs are: 5427, 6119, 6120, 6121 and 6122.<br> Passbands used:<br> Physically motivated: Oxy (0.5-0.7 keV), Fe (0.7-0.9 keV), Ne (0.9-1.2 keV), Mg (1.2-3.0 keV).<br> Default Chandra passbands: ultrasoft (0.2-0.5 keV), soft (0.5-1.2 keV), medium + hard (1.2-8.0 keV), broad (0.5-7.0 keV).</p>
Data for "Tetramine Aspect Ratio and Flexibility Determine Framework Symmetry for Zn8L6 Self-Assembled Structures"
<p>In the following subdirectories are the input and outputs of cage and face analysis for:</p> <p>Published DOI: <a href="https://onlinelibrary.wiley.com/doi/full/10.1002/anie.202217987">10.1002/anie.202217987 </a></p> <p>Code: <a href="https://github.com/andrewtarzia/sca_cage_assembler/tree/cubism-production">sca_cage_assembler</a></p> <p>Previously uploaded in 10.5281/zenodo.8432296 and <a href="https://github.com/andrewtarzia/citable_data" rel="noopener noreferrer">https://github.com/andrewtarzia/citable_data</a></p> <p>NOTES:</p> <ul> <li>the naming convention differs from manuscript:</li> </ul> <table> <tbody> <tr> <th>manuscript tetra-aniline</th> <th>computational label</th> <th>xtal-label</th> </tr> <tr> <td>A</td> <td>5</td> <td>370</td> </tr> <tr> <td>B</td> <td>16</td> <td>326</td> </tr> <tr> <td>C</td> <td>12</td> <td>235</td> </tr> <tr> <td>D</td> <td>3</td> <td>301</td> </tr> <tr> <td>E</td> <td>8</td> <td>257</td> </tr> <tr> <td>F</td> <td>2</td> <td>354</td> </tr> </tbody> </table> <ul> <li>computational labels are often preceded by `quad2_` or `cl1_quad2_`</li> <li>much of the analysis was not used in the manuscript but remains part of the accumulated data</li> </ul> <p> </p> <p>cage_library directory:</p> <ul> <li>_CS.json: information on all cages in the set of diastereomers - properties and whether they optimized successfully.</li> <li>_ligand_measures.json: information on the ligand associated with a set of cage diastereomers.</li> <li>_measures.json: represenets a cleaned up collation of all measures the diastereomers made from a given ligand</li> <li>C_NAME_optc.mol: optimized (at xTB level) structure of each cage.</li> <li>set_dft_run directory contains the input and output of the CP2K optimisations of one set of diastereomers</li> </ul> <p>complex_library directory:</p> <ul> <li>contains the optimised structures of both complexes</li> </ul> <p>ligand_library directory:</p> <ul> <li>contains `_opt.mol` input ligand structures for cage construction</li> <li>for cap, the input was provided manually in `manual/` directory</li> <li>in `face_analysis` directory: <ul> <li>contains manual_complex directory, with necessary input for face construction</li> <li>_long_properties.json files contains the measurements for the named face (in file name)</li> <li>_long_lopt.mol files contain the optimised structure of the named face, on which analysis was performed</li> <li>`long` corresponds to the longer restricted optimization discussed in the SI.</li> </ul> </li> </ul> <p>xray_structures directory:</p> <ul> <li>analysis directory: <ul> <li>contains input .pdb files for xray structure (as single molecules) used in analysis</li> <li>contains `all_xray_csv_data.csv`, which has all data needed on xray structures.</li> </ul> </li> </ul>
Measurements of lead concentrations and isotope ratios of moss and lichens from Portland, Oregon, U.S., and surrounding rural areas
<p>We conducted a high-resolution study of lead in an urban moss, <em>Orthotrichum lyellii,</em> to better understand lead distributions and sources in Portland, Oregon, United States. The goal of this study was to identify modern and persistent legacy urban lead sources. This included an investigation of the impact of relic lead-sheathed telecommunication cables on environmental lead levels. Here we present lead levels and isotopic compositions of (1) moss samples collected from Portland in 2013, (2) moss samples collected 10 years later in 2023 for proximity to lead-sheathed telecommunication cables, (3) archival moss and lichen samples, and (4) rural moss samples. The findings of this study and methods can be found in the linked primary article.</p>
ScienceDex guides
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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.