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FIGURE 2 in Redescription of Pinnixa haematosticta Sakai, 1934, its transfer to Indopinnixa Manning & Morton, 1987, and a reappraisal of Indopinnixa kumejima Naruse & Maenosono, 2012 (Decapoda: Brachyura: Pinnotheridae)
FIGURE 2. Indopinnixa haematosticta (Sakai, 1934) n. comb., male (3.6×8.3 mm), CBM-ZC 15291, habitus, in preservative. A, dorsal view; B, ventral view. Photo taken by T. Komai.
FIGURE 5 in Redescription of Pinnixa haematosticta Sakai, 1934, its transfer to Indopinnixa Manning & Morton, 1987, and a reappraisal of Indopinnixa kumejima Naruse & Maenosono, 2012 (Decapoda: Brachyura: Pinnotheridae)
FIGURE 5. Indopinnixa haematosticta (Sakai, 1934) n. comb., male (3.6×8.3 mm), CBM-ZC 15291. A, entire thoracic sternum, ventral view (setae omitted; gonopods omitted); B, anterior thoracic sternites, ventral view (perpendicular to horizontal plane; gonopods dissected); C, right edge of sterno-pleonal cavity of thoracic sternites 5 and 6, ventrolateral view; D, right thoracic sternites 7 and 8 and pleomeres 1 and 2, posterior view; E, pleon and telson, ventral (external) view; F, pleomeres 3–6, dorsal (internal) view; G, right gonopod 1, ventral view; H, same, distal part, dorsal view; I, right gonopod 2.
FIGURE 4 in Redescription of Pinnixa haematosticta Sakai, 1934, its transfer to Indopinnixa Manning & Morton, 1987, and a reappraisal of Indopinnixa kumejima Naruse & Maenosono, 2012 (Decapoda: Brachyura: Pinnotheridae)
FIGURE 4. Indopinnixa haematosticta (Sakai, 1934) n. comb. A, B, D, F–I, male (3.6×8.3 mm), CBM-ZC 15291; C, E, male (2.5×5.5 mm), CBM-ZC 15297. A, right chela, outer view; B, right pereopod 2, lower view; C, same, carpus and propodus, lower view; D, right pereopod 3, lower view; E, same, carpus and propodus, lower view; F, right pereopod 4, upper view; G, same, lower view; H, right pereopod 5, upper view; I, same, lower view. Setae omitted.
FIGURE 13 in Redescription of Pinnixa haematosticta Sakai, 1934, its transfer to Indopinnixa Manning & Morton, 1987, and a reappraisal of Indopinnixa kumejima Naruse & Maenosono, 2012 (Decapoda: Brachyura: Pinnotheridae)
FIGURE 13. Indopinnixa kumejima Naruse & Maenosono, 2012, female (3.3×7.0 mm), CBM-ZC 16591, habitus, in preservative. A, dorsal view; B, ventral view. Photo taken by T. Komai.
FIGURE 12 in Redescription of Pinnixa haematosticta Sakai, 1934, its transfer to Indopinnixa Manning & Morton, 1987, and a reappraisal of Indopinnixa kumejima Naruse & Maenosono, 2012 (Decapoda: Brachyura: Pinnotheridae)
FIGURE 12. Indopinnixa kumejima Naruse & Maenosono, 2012, male (3.4×8.2 mm), CBM-ZC 16590. A, left chela, outer view (setae omitted); B, left pereopod 2, lower view (setae omitted); C, left pereopod 3, lower view (setae omitted); D, left pereopod 4, upper view; E, same, lower view (setae omitted); F, left pereopod 5, upper view; G, same, lower view (setae omitted).
FIGURE 9 in Redescription of Pinnixa haematosticta Sakai, 1934, its transfer to Indopinnixa Manning & Morton, 1987, and a reappraisal of Indopinnixa kumejima Naruse & Maenosono, 2012 (Decapoda: Brachyura: Pinnotheridae)
FIGURE 9. Indopinnixa kumejima Naruse & Maenosono, 2012, male (3.8×8.5 mm), RUMF-ZC-7325, habitus, in preservative. A, dorsal view; B, ventral view (pleon removed). Photo taken by T. Komai.
FIGURE 16 in Redescription of Pinnixa haematosticta Sakai, 1934, its transfer to Indopinnixa Manning & Morton, 1987, and a reappraisal of Indopinnixa kumejima Naruse & Maenosono, 2012 (Decapoda: Brachyura: Pinnotheridae)
FIGURE 16. Maximum-likelihood (ML) tree from partial sequences of mitochondrial 16S rRNA gene (520–534 bp) of three specimens of Indopinnixa haematosticta (Sakai, 1934) n. comb. and seven specimens of I. kumejima Naruse & Maenosono, 2012 based on the Tamura 3-parameter + G model (highest log likelihood: -1053.93). Indopinnixa moosai Rahayu & Ng, 2010 and Glassella costaricana (Wicksten, 1982) (Pinnotheridae) were used as outgroup taxa. Numbers at nodes are bootstrap values (ML/NJ) and only values>60 are shown.
FIGURE 1 in Redescription of Pinnixa haematosticta Sakai, 1934, its transfer to Indopinnixa Manning & Morton, 1987, and a reappraisal of Indopinnixa kumejima Naruse & Maenosono, 2012 (Decapoda: Brachyura: Pinnotheridae)
FIGURE 1. Schematic illustration of ambulatory pereopod, showing terminology for the orientation of surfaces and margins of articles (A) and measurements of the merus, carpus and propodus (B).
FIGURE 7 in Redescription of Pinnixa haematosticta Sakai, 1934, its transfer to Indopinnixa Manning & Morton, 1987, and a reappraisal of Indopinnixa kumejima Naruse & Maenosono, 2012 (Decapoda: Brachyura: Pinnotheridae)
FIGURE 7. Indopinnixa haematosticta (Sakai, 1934) n. comb. A–H, holotype, female (2.9×6.9 mm), KPM-NH107899; I, female (4.1×8.5 mm), CBM-ZC 15291. A, carapace, eyes and left antennule, dorsal view (setae omitted); B, left chela, outer view; C, right pereopod 2, lower view; D, right pereopod 3, lower view; E, right pereopod 4, upper view (setae partially removed); F, same, lower view; G, left pereopod 5, upper view; H, pleon, outer view (setae omitted); I, right thoracic sternites 3–6, ventral view.
FIGURE 15 in Redescription of Pinnixa haematosticta Sakai, 1934, its transfer to Indopinnixa Manning & Morton, 1987, and a reappraisal of Indopinnixa kumejima Naruse & Maenosono, 2012 (Decapoda: Brachyura: Pinnotheridae)
FIGURE 15. Indopinnixa kumejima Naruse & Maenosono, 2012, habitus in dorsal view, showing living colouration. A, female (4.0×9.4 mm), RUMF-ZC-7322, photo taken by T. Naruse; B, male (3.0×6.6 mm), CBM-ZC 16592, photo taken by H. Yokooka.
FIGURE 8 in Redescription of Pinnixa haematosticta Sakai, 1934, its transfer to Indopinnixa Manning & Morton, 1987, and a reappraisal of Indopinnixa kumejima Naruse & Maenosono, 2012 (Decapoda: Brachyura: Pinnotheridae)
FIGURE 8. Indopinnixa haematosticta (Sakai, 1934) n. comb., androgynous specimen (2.7×5.6 mm), CBM-ZC 15292, habitus, showing living colouration. A, dorsal view; B, ventral view. Photo taken by Shoichi Kimura.
Non-local eddy-mean Kinetic Energy transfers
<p>Animation of eddy-mean Kinetic Energy transfers during the decorrelation phase of 120-day long, 20-member ensemble simulations of the Western Mediterranean basin. The three terms are associated with the kinetic energy equation of the ensemble mean flow (left), that of the turbulent flow (center) and that of the ensemble mean of the full flow (right). The latter is associated with non-local eddy-mean KE transfers.</p>
Machine learning models predict calculation outcomes with the transferability necessary for computational catalysis
<p>data files, including ML models of dynamic classifiers, trajectories of electronic structure and geometric features, optimized geometries, and final csv files.</p>
Machine Learning Potentials for Metal-Organic Frameworks with Thermodynamic Transferability: training data
<p>This dataset contains potential energies, forces, and virial stress for a large set of reference configurations for UiO-66(Zr) and MIL-53(Al), computed at the PBE-D3 level using CP2K 7.1. The basis set contained both TZVP Gaussian basis functions as well as plane waves (cutoff energy 800 Ry for UiO-66(Zr) and 900 Ry for MIL-53(Al)). The sampling of the Brillouin zone was restricted to the gamma point.</p>
Partial-envelope stripping and nuclear-timescale mass transfer from evolved supergiants at low metallicity
<p>Model data and input files (inlists) used to compute MESA binary models to paper<br> "Partial-envelope stripping and nuclear-timescale mass transfer from evolved supergiants at low metallicity"<br> (<a href="https://ui.adsabs.harvard.edu/abs/2021arXiv211110271K/abstract">ADS link</a>)<br> MESA version r11554.<br> <br> The data consists of stellar tracks of the primary (donor) star. Provided are MESA history.data files and the final MESA model of the primary (terminated at core-He depletion).<br> <br> The data for solar metallicity models is also available on request.<br> </p>
FIGURE 2 in The new tribe Fourraeeae (Brassicaceae) and two Moroccan Arabis species transferred to the new genus Hurkaea
FIGURE 2. Photographs of mitotic chromosomes preparations from (a) H. conringioides and (b) H. josiae indicating 2n = 2x = 14 chromosome for both taxa.
Data from: Conjugative plasmid transfer is limited by prophages but can be overcome by high conjugation rates
<p><span><span><span><span>Antibiotic resistance spread via plasmids is a serious threat to successfully fight infections and makes understanding plasmid transfer in nature crucial to prevent the rise of antibiotic resistance. Studies addressing the dynamics of plasmid conjugation have yet neglected one omnipresent factor: prophages (viruses integrated into bacterial genomes), whose activation can kill host and surrounding bacterial cells. To investigate the impact of prophages on conjugation, we combined experiments and mathematical modelling. Using <em>E. coli</em>, prophage lambda and the multidrug-resistant plasmid RP4 we find that prophages can substantially limit the spread of conjugative plasmids. This inhibitory effect was strongly dependent on environmental conditions and bacterial genetic background. Our empirically parameterized model reproduced experimental dynamics of cells acquiring either the prophage or the plasmid well but failed to predict the number of cells acquiring both elements. This suggests more complex interactions between conjugative plasmids and prophages in sequential infections. Varying phage and plasmid infection parameters over empirically realistic ranges revealed that plasmids can overcome the negative impact of prophages through high conjugation rates. Overall, the presence of prophages introduces an additional death rate for plasmid carriers, the magnitude of which is determined in non-trivial ways by the environment, the phage and the plasmid.</span></span></span></span></p>
An Algebraic Architecture Model to Select PUSH/PULL Data Transfer
<p>The supplementary material for ASE 2022 Submission #21.</p> <p> </p> <p><strong>Detailed Proofs</strong></p> <p>The detailed proofs of Theorems 1, 2, 3 and other lemmas are contained in the following .PDF file.</p> <table> <tbody> <tr> <td>File Name </td> <td>Description</td> </tr> <tr> <td>ASE2022_proofs.pdf</td> <td>The detailed proofs of the correstness</td> </tr> </tbody> </table> <p> </p> <p><strong>Graph-based Refactoring Tool</strong></p> <p>The following .jar file is the current implementation of the graph-based tool for push/pull refactoring. </p> <table> <tbody> <tr> <td>File Name </td> <td>Description </td> </tr> <tr> <td>GraphBasedRefactor.jar</td> <td>graph-based refactoring tool</td> </tr> </tbody> </table> <p>It can work with Java 13 or later. The tool can be used in the following steps:</p> <ol> </ol> <ol> <li>Launch the tool from the command prompt.<br> <code>java -jar GraphBasedRefactor.jar</code></li> <li>Open a model file. (File -> Open)</li> <li>Select one data transfer method for each edge. (A pop-up menu is displayed by double clicking each edge.)</li> <li>Generate a plain Java prototype or JAX-RS prototype. (Generate -> Generate Plain Java Prototype, or Generate -> Generate JAX-RS Prototype)</li> </ol> <p> </p> <p><strong>Model Files</strong></p> <p>As case studies, we designed the architectures of the WOS (Weather Observation System), POS (Point Of Sales) system, twitter-like web service and jumping game. Their model files are compressed in the following .zip file.</p> <table> <tbody> <tr> <td>File Name </td> <td>Description </td> </tr> <tr> <td>models.zip</td> <td>Compressed model files</td> </tr> </tbody> </table> <p> </p> <p><strong>Generated Prototypes</strong></p> <p>We generated the prototypes from the above model files. The source files are compressed in the following .zip files.</p> <table> <tbody> <tr> <td>File Name </td> <td>Description</td> </tr> <tr> <td>prototypes.zip</td> <td>Compressed prototypes</td> </tr> </tbody> </table> <p> </p> <p><strong>Performance Evaluations</strong></p> <p>We measured the computation time of each API call on the JAX-RS prototypes of WOS, JAX-RS prototypes of twitter-like web service, and Java prototypes and the completed implementations of POS. The results are summarized in the following Excel file.</p> <table> <tbody> <tr> <td>File Name </td> <td>Description </td> </tr> <tr> <td>evaluations.xlsx</td> <td>Performance evaluations of API calls</td> </tr> </tbody> </table> <p> </p> <p><strong>Completed Implementations</strong></p> <p>We had completed the implementaions of the jumping game and POS system in Java. The source files and the executable .jar files are compressed in the following .zip files.</p> <table> <tbody> <tr> <td>File Name </td> <td>Description </td> </tr> <tr> <td>JumpingGame.zip</td> <td>A completed push-first implementation and the executable .jar file of the jumping game in Java</td> </tr> <tr> <td>PosSystem.zip</td> <td>A completed push-first implementation and the executable .jar file of the POS system in Java</td> </tr> </tbody> </table> <p>The .jar files can work with Java 13 or later. They can be launched by typing the following commands on the command prompt.</p> <p><code>java -jar JumpingGame.jar</code></p> <p><code>java -jar PosSystem.jar</code></p>
Transfer efficiency of carbon, nutrients, and PUFAs in planktonic food webs under different environmental conditions
<p>We investigated the transfer of essential substances (carbon, nutrients, and polyunsaturated fatty acids) through plankton communities in 30 Polish lakes with different trophic status in the middle of summer. The results of our study revealed that different essential substances were transferred from phytoplankton to zooplankton with varying efficiencies. The average TTE of C, N, P, and the sum of ω-3 PUFA were 6.55%, 9.82%, 15.82%, 20.90%, respectively. Our results also show a large mismatch between the elemental and biochemical compositions of zooplankton and their food during the peak of the summer stagnation, which may further promote the accumulation of essential substances. There were also large differences in TTEs between trophic conditions, with the highest efficiencies in oligotrophic lakes and the lowest in dystrophic and eutrophic lakes. Therefore, our study indicates that disturbances like eutrophication and dystrophication similarly decrease the TTE of essential substances between phytoplankton and zooplankton in freshwater food webs.</p>
Data for the journal article: 'Ecology of testate amoebae along an environmental gradient from bogs to calcareous fens in East-Central Europe: development of transfer functions for palaeoenvironmental reconstructions'
<p><strong>DATA DESCRIPTION</strong>: This repository provides training sets and R scripts for the development of three transfer function models that allow reconstructions of Holocene hydrochemical or hydrological (hydroclimatic) conditions from testate amoeba assemblages preserved in mires of East-Central Europe. Specifically, the repository contains (<em>i</em>) <strong>the full dataset and an R script for the development of the final MLRC model</strong> for inferring past water-mineral richness (expressed as pH) in various types of mires; (<em>ii</em>) <strong>the minerotrophic subset and an R script for the development of the final WAPLS com1 model</strong> for the reconstructions of past water-mineral richness (expressed as pH) in calcareous and rich fens; and (<em>iii</em>) <strong>the ombrotrophic subset and an R script for the development of the final PLS com2 model</strong> for inferring past depth to water table (DWT) in bogs and poor fens. Additionally, the repository includes <strong>the original versions of the full, minerotrophic and ombrotrophic training sets</strong> (i.e., the versions before removing outlier samples and rare taxa due to transfer function optimisation), and <strong>the compiled dataset</strong>, from which the three above-mentioned training sets were generated. For details, see <a href="https://doi.org/10.1016/j.palaeo.2022.111145">Šímová et al. (2022)</a>.</p> <p><strong>ARTICLE ABSTRACT</strong>: Testate amoebae play an important role in biomonitoring and the understanding of peatland (palaeo)ecology. However, their application has been mainly limited to <em>Sphagnum</em>-dominated peatlands, especially ombrotrophic bogs. To facilitate wider use of these microorganisms, we explored their ecology along a gradient from mineral-poor acidic bogs to mineral-rich calcareous fens with tufa formation using a new calibration dataset of over 250 samples from East-Central Europe. Specifically, we examined environmental controls on testate amoebae along the complete gradient and separately in the minerotrophic (pH >5.5) and ombrotrophic (pH <5) parts. Based on these findings, we developed and statistically evaluated transfer function models for the dominant factors controlling the community composition of these protists. Multivariate statistical analysis showed that groundwater pH was the main driver of species composition in the full and minerotrophic datasets. In contrast, testate amoeba communities in the ombrotrophic dataset were primarily structured by depth to water table (DWT). Under leave-one-out cross-validation (LOO), the best-performing model for DWT gave a prediction error (RMSEP) of 5.43 cm. The most robust models for groundwater mineral richness yielded RMSEP<sub>LOO</sub> of 0.45 and 0.27 pH units, for the full and the minerotrophic dataset respectively. This is the first study to present a complete set of testate amoeba-based transfer functions that allow reconstructions of Holocene hydrochemical and hydrological (hydroclimatic) variability in different mire types within one region. The new models open up the possibility for testate amoebae to become a valuable tool in palaeoecological research, although further work is needed to fully assess their performance and usefulness in practice.</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.