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2,239 results for “MicroED”
Data for: Assets in Periphery, Agents in the Core: Mapping the Micro Structures of International Tax Planning
<p>Data for: Assets in Periphery, Agents in the Core: Mapping the Micro Structures of International Tax Planning</p> <p>See paper at: https://osf.io/preprints/socarxiv/hyc4p</p> <p>In the last two decades, tax avoidance has risen to the top of the agenda of policy makers and international organizations. The majority of political action and academic research has focused on the macro-level of states, pointing towards the responsibility of ‘tax havens’ or ‘offshore financial centers’. Research on the micro-level has demonstrated the importance of non-state actors who facilitate tax planning, but tax advisors have never been studied systematically with global data. In this paper, we connect the micro and macro levels. We map tax advisors geographically using a novel empirical approach based on LinkedIn. We show that tax advisors generally locate in large cities in the EU and OECD, rather than in places targeted as ‘tax havens’. We further consider what determines the locations of tax advisors. Using multiple regression analysis, we find that locations of tax advisors does not correlate with the location of corporate profits, financial secrecy, or economic activity. Rather, it correlates with the managerial and financial activity. Our results underscore the core-periphery structure in offshore finance. Effective regulation of tax avoidance should focus on tax advisors, not only on the destination of money flows, since the active facilitation does not occur in those places.</p>
Dataset of micro-phytoplankton biodiversity in the Eastern Channel area from 1987 to 2019.
<p>Micro-phytoplankton communities are widely influenced by the environment and seasonal cycling. The French-English Channel is a system between the East Atlantic and the North Sea with contrasted coastal areas along the French coast. In a context of changing environment, it is crucial to understand the causes and consequences of environmental variability on marine compartments whose phytoplankton represent the first link.</p> <p>Thanks to various monitoring programs such as REPHY (REPHY – French Observation And Monitoring Program For Phytoplankton And Hydrology In Coastal Waters, 2021) and RHLN (Regional Observation and Monitoring programs for Phytoplankton and Hydrology in the eastern English Channel), datasets of micro-phytoplankton diversity are available since the late 80s at a national scale.</p> <p>Here, we present a subset of these datasets on micro-phytoplankton community. It gathers diversity and abundance from 1987 to 2019. Compared to the main dataset, a taxonomical review was done to ensure a correct spatial and temporal homogenization of the taxonomical denomination (description below). We also focus on 6 monitored stations along the French Channel coast; Antifer ponton pétrolier, Cabourg, Géfosse, Donville, At so and St Cast – Les Hébihens (gathering of two times series geographically close). A graphical visual of the sampling history (for the FLORTOT standard protocol) is available in the uploaded image below.</p> <p>The dataset comes from a national-wide standard protocol of water sampling (Neaud-Masson, 2016). All records are stored in the Quadrige² platform, the reference information system for coastal waters in France. A compilation of the various results obtained at the French national scale was done on the last 30 years of monitoring (Belin and Soudant, 2018). The sampling is done at water surface (0-1 meter) around the high tide period (+/- 2 hours), it is fixed through lugol acid on arrivals at the lab and analysed through reversed microscopy by experts trained through a similar 2 years learning process. The taxa are identified to the lowest taxonomic level possible and names are updated according to the WORMs’ denomination base. Since 2015, evaluations (International Phytoplankton Intercomparison - IPI) are being implemented at the European scale, coordinated by the Marine Institute of Galway, to reduce identification deviations and biases between laboratories.</p> <p>The columns are described as following:</p> <ul> <li><strong>#1 : Taxa_Name</strong></li> </ul> <p>Due to the extent of the initial dataset, both in space and time, a work of homogenization in the taxa’s denomination was applied. Therefore, associated with this dataset, we made available a table that summarizes changes applied in the nominations. It displays all the taxa initially present in the REPHY database (first column), the change in denomination applied if needed as they are not at the same resolution between stations’ laboratories, or because two species are now grouped into a common denomination. There is an “X” if the taxa is not relevant, rare, or not a phytoplankton or protist of interest and therefore it means the taxa was deleted and is not in the given dataset (second column) and potential comments or justifications (third column). It has been build and reviewed several times by the phytoplankton experts from the three Ifremer laboratories covering the stations (Dinard, Port en Bessin and Boulogne sur Mer).</p> <ul> <li><strong>#2 to 5 : Date, Day, Month, Year</strong></li> </ul> <p>Temporal description of the samples. Details of the sampling history are given in the image below.</p> <ul> <li><strong>#6 : Season</strong></li> </ul> <p>Defined as Spring = March to May; Summer = June to August; Autumn = September to November; Winter = December (Y) to February (Y+1)</p> <ul> <li><strong>#7 and 8 : Julian_days and week number</strong></li> <li><strong>#9 and 10 : Station_FullName and Station_Code</strong></li> </ul> <p><strong></strong>In the REPHY monitoring program, stations are both describe by full name locations and codes. The same level of detail was kept available in this version, with : Antifer ponton pétrolier (010-P-001), Cabourg (010-P-109), Géfosse (014-P-023), Donville (018-P-054), At so (006-P-001) and St Cast – Les Hébihens (022-P-002)</p> <ul> <li><strong>#11: Parameter</strong></li> </ul> <p>FLORTOT (standard samples, all micro-phytoplanktonic species are identified). FLORPAR (partially identified samples in area identified as under any sanitary risk). FLORIND (additional samples taken for toxic species monitoring, or for species reaching 100 000 cells per liter or producing toxins are identified).</p> <ul> <li><strong>#12 : Results </strong></li> </ul> <p>Abundance (in cells.L<sup>-1</sup>), whose level of detection (lowest value) through the microscopy approach is at 100 cells per liter.</p> <ul> <li><strong>#13 : Class.worms2019</strong></li> </ul> <p>The taxa’s class according to the World Register of Marine Species 2019 (https://www.marinespecies.org/)</p> <ul> <li><strong>#14 : Rank</strong></li> </ul> <p>Taxa's taxonomical rank : Species, Genus, Family, e-species (aka: group of similar species), e-genus (aka : group of similar genus), Class, subclass, Order, Phylum, Other.</p> <p> </p>
Drivers of spatial and temporal micro- and mesozooplankton dynamics in an estuary under strong anthropogenic influences (The Eastern Scheldt, Netherlands)
<p>Supplement to: Horn, H.G., van Rijswijk, P., Soetaert, K., van Oevelen, D. (2023): Drivers of spatial and temporal micro- and mesozooplankton dynamics in an estuary under strong anthropogenic influences (The Eastern Scheldt, Netherlands). J Sea Res. <a href="https://doi.org/10.1016/j.seares.2023.102357">https://doi.org/10.1016/j.seares.2023.102357</a></p> <p>This data set contains mesozooplankton and microzooplankton abundances, temperature, salinity, O2, DOC, Chl.a, SPM, and nutrient concentrations from eight stations in the Eastern Scheldt sampled in 2018. Phytoplankton growth and microzooplankton grazing rates from dilution experiments are also provided.</p>
Dataset for "Infiltration and resuspension of dilute particle suspensions in micro cavity flow "
<p>This dataset contains the numerical simulation data describing the migration behaviour of particles. Detailed study on the infiltration and resuspension of particle in a cavity flow is presented in a journal paper entitled "Infiltration and resuspension of dilute particle suspensions in micro cavity flow ". We provide all the essential data in a single excel file with the description below:</p> <p> </p> <p>Dataset 1- Particle trajectory for different releasing positions. The parameters are <em>Re</em>=56.9, <em>h</em>=32, <em>l</em>=80. The particle densities are <em>ρ<sub>p</sub></em>=1.3 in plot (Fig. 7a) and <em>ρ<sub>p</sub></em>=2.0 in plot (Fig. 7b). (Data of Fig. 7)</p> <p>Dataset 2 - Particle trajectory for different periodic domain lengths. The parameters are <em>ρ<sub>p</sub></em>=1.3, <em>Re</em>=56.9, <em>h</em>=32 and <em>l</em>=80. (Data of Fig. 8)</p> <p>Dataset 3 - The time evolution of (Fig. 9a) the vertical position <em>z</em>, (Fig. 9b) the horizontal velocity <em>u<sub>x</sub></em>, and (Fig. 9c) the vertical velocity <em>u<sub>z</sub></em> of a single particle with the same Renolds number <em>Re</em>=56.9 and cavity size of <em>h</em>=32 and <em>l</em>=80, but different particle densities. (Data of Fig. 9)</p> <p>Dataset 4 - The trajectories of a single particle over the cavity with: (Fig. 10a) different particle densities but the same Renolds number <em>Re</em>=85.3 and cavity size of <em>h</em>=16 and <em>l</em>=80; (Fig. 10b) different Reynolds numbers but the same particle density <em>ρ<sub>p</sub></em>=1.3 and cavity size of <em>h</em>=32 and <em>l</em>=80; (Fig. 10c) different cavity sizes but the same Renolds number<em> Re</em>=56.9 and particle density <em>ρ<sub>p</sub></em>=1.3. The dashed lines represent the boundary of the cavity. (Data of Fig. 10)</p> <p>Dataset 5 - Typical particle trajectories in the cavity. The dashed lines represent the boundary of the trap. (Data of Fig. 12)</p> <p>Dataset 6 - The variation of trap efficiency with particle density for (Fig. 13a) different cavity sizes with the same <em>Re</em>=56.9, and (Fig. 13b) different Reynolds numbers with the same cavity size <em>h</em>=32, <em>l</em>=80, respectively. (Data of Fig. 13)</p> <p>Dataset 7 - The critical entering distance as a function of the scaling parameter <em>T<sub>h</sub></em>. The fitting line is performed with an exponential function with the same form as Eq. (19). (Data of Fig.14)</p> <p>Dataset 8 - The variation of the trap efficiency with the trap number. (Data of Fig.15)</p> <p> </p>
Short- And Long-Term Micro & Nano Particles Exposure to Estuarine Model Species at Variable Salinities
Micro (< 5mm) & Nano (1-1000 nm) plastic (MNP) particles are ubiquitous in the environment and have been shown to have a variety of effects on aquatic organisms. The effects of MNP exposure can vary depending on the type of MNP, the concentration of MNP, the duration of exposure, and the salinity of the water. This study used 5 plastic types including polyester (PE), polypropylene (PP), polylactic acid (PLA), polyethylene terephthalate (PETE) and tire particles (TP) in two forms, solid plastic particles and microfibers. To assess potential impacts on exposed organisms, early life stages of the estuarine indicator species Inland Silverside (Menidia beryllina) and mysid shrimp (Americamysis bahia) were exposed to three concentrations at micro- and nano-size fractions, and separately to leachate, across a 5-25 PSU salinity gradient. This exposure study was performed in longer term (21 days for Inland Silverside and 28 days for mysid shrimp) and shorter term (4 days for Inland Silverside and 7 days for mysid shrimp). Following MNP exposures of 7d (A. bahia) and 96 h (M. beryllina), behavioral assays were performed post-exposure from each treatment using a Danio Vision Observation Chamber (Noldus, Wageningen, the Netherlands) for the dark: light cycle as described previously (Siddiqui et al., 2022; Siddiqui et al., 2023; Mundy et al., 2021; Segarra et al., 2021). These behavior studies provide important information for risk assessments and policy making that can establish knowledge for MNPs risk.
Data and analysis code from: Micro-scale geography of synchrony in a serpentine plant community
This package includes data and code to reproduce analyses of micro-scale geography of synchrony in the plant community at Jasper Ridge Biological Preserve. Plant cover and soil depth data come from long-term experimental plots established by Richard Hobbs. Plant cover is aggregated into 36 1m2 plots across three treatments (control, gopher exclosure, rabbit exclosure) from 1983 to 2015; included herein are data on the 6 most abundant species (Plantago erecta, Bromus hordeaceous, Lasthenia californica, Microseris douglasii, Vulpia microstachys, and Calycadenia multiglandulosa), total plant cover across all species, and records of gopher disturbance in the plots. The data package also includes time series of monthly precipitation and growing season Palmer’s Drought Severity Index for the same time period. An R Markdown file is included that reproduces all analyses described in the manuscript and reproduces all data figures. Data to support: Walter, Hallett et al. in review “Micro-scale geography of synchrony in a serpentine plant community
A micro-environmental dataset exploring shrub-open climate contrasts in Cuyama Valley, California, USA,
A total of 62 Hobo micro-station data logger weather stations were deployed in Cuyama Valley, California drylands on public lands. Each station had 4 channels with two EC5 soil moisture smart sensors and two 12-Bit temperature smart sensors. The sensor arrays were deployed for two years or a total of 24 months. Key ecological variables included microsite, location, vegetation type, and extent of vegetation at each microsite. Temperature sensors were deployed 15 cm above the soil surface under the shrub canopy of Ephedra californica (sheltered from direct sunlight) or at adjacent, open paired-microsites within 1.5m of a focal shrub.Temperatures listed are in degrees Celsius. Soil moisture sensors were inserted into the soil near each temperature probe. The x,y,z columns are the width, perpendicular measure, and height in m respectively of each shrub at those microsites.
Major and trace bulk sample and micro-XRF geochemistry, carbon and oxygen stable isotope compositions of magmatic and sedimentary rocks from Hovedøya Island, Oslo fjord, Norway.
<p>This data set reports on the methodologies and results of geochemical analysis carried out on samples of magmatic rock, calcite and sedimentary rocks of Hovedoya Island, Oslo fjord, Norway, in the framework of the publication by Poppe et al. (2020; <em>Geochemistry, Geophysics, Geosystems</em>; <a href="https://doi.org/10.1029/2019GC008685">https://doi.org/10.1029/2019GC008685</a>). The major and trace element bulk sample geochemical analysis was carried at the Laboratoire G-Time, Université Libre de Bruxelles, Brussels (V. Debaille), the micro-XRF mapping and line scanning, was carried out at the laboratory of the Analytical and Environmental Geo-Chemistry (AMGC) group at the Vrije Universiteit Brussel (VUB), Brussels (N.J. de Winter, S. Poppe) and the stable isotope composition analysis was carried out as well at the AMGC laboratory (S. Poppe, S. Goderis), supervised by P. Claeys and M. Kervyn, in collaboration with P. Boulvias. Data sheets are provided in .csv or .xlsx format and compressed folders containing .TIF images of µXRF elemental maps are attached. This data set also contains the complete data sets obtained for the construction of calibration curves for µXRF line scan analysis of rock samples of magmatic composition at the AMGC laboratory at VUB.</p>
Supplementary Materials for "Simultaneous single-shot radiographic imaging using a laser-driven x-ray and proton micro-source"
<p>Simulation Data Repository, please read the contained README file in the contained simulation/ directory.</p> <p>This directory contains a copy of the used PIConGPU source code, version 0.5.0-dev-60ad9eb85 and analysis scripts.</p> <p>The PIConGPU source code is archived including its complete git history (git version 2.17.1) in source/picongpu.tar.gz with the input parameter template inside in share/picongpu/examples/Wneedle .</p> <p>Generally, PIConGPU source code is available via <a href="https://doi.org/10.5281/zenodo.591746">https://doi.org/10.5281/zenodo.591746</a> with its public git repository being maintained on <a href="https://github.com/ComputationalRadiationPhysics/picongpu">https://github.com/ComputationalRadiationPhysics/picongpu</a> .</p> <p>The two simulations’ exact input is modified accordingly in the directory input/ inside: 2D_a0-45_Z-10_ppc-20_002_light.tar.gz (p-polarized; along X) 2D_a0-45_Z-10_ppc-20_003_light.tar.gz (s-polarized; along Z).</p> <p>“Heavy” simulation data (checkpoints in simOutput/checkpoints/, full-resolution field and particle output in simOutput/bp/ ) has been stripped from this archive and are archived on NERSC’s HPSS tape archive.</p> <p>Analysis scripts are provided as Jupyter notebooks (DensityPlot_polX.ipynb and DensityPlot_polZ.ipynb) and depend on the following software:</p> <p>- adios 1.13.1 python bindings with enabled c-blosc transformations<br> - numpy 1.17.1<br> - matplotlib 3.1.1<br> - PIConGPU post-processing helper modules located in each simulation root directory under “input/lib/python/”<br> <br> The detailed conda environment can be found in the README.</p>
BreXLiMe: A Semantically Enriched Dataset With News Articles, Micro-Posts, and TV Shows Related to the Brexit
<p>We provide a <strong>large data set of media content metadata</strong> from various media sources (including online news sites, social media, and live-TV) in three languages (<strong>English, German, and Spanish</strong>). Overall, the data set contains rich metadata for about <strong>240 thousand news articles, 12 million micro-posts, and 900 TV shows</strong>. All media content information has been semantically enriched with annotations of both entities and categories from DBpedia.</p> <p>The data can be used as a valuable data basis for applications and studies of various disciplines (e.g., social studies, political science, and humanities) on the case of Brexit, particularly on the <strong>media landscape before the Brexit referendum held on June 23, 2016</strong>.</p> <p>We provide the data set in the RDF serialization format Turtle (.ttl) as well as in XML.</p> <p>If you use our data set, please <strong>cite</strong> it as follows:</p> <pre><code>Lei Zhang, Maribel Acosta, Michael Färber, Steffen Thoma and Achim Rettinger. "BreXearch: Exploring Brexit Data Using Cross-Lingual and Cross-Media Semantic Search". In: Proceedings of the ISWC 2017 Posters & Demonstrations Track within the 16th International Semantic Web Conference (ISWC 2017). Vienna, Austria, 2017.</code></pre> <p> </p>
Figure 98 in The symphytognathoid spiders of the Gaoligongshan, Yunnan, China (Araneae: Araneoidea): Systematics and diversity of micro-orbweavers
Figure 98. Distribution map, inset map shows study area. White: Simaoa maku sp. n.; blue: Simaoa bianjing sp. n.; red: Gaoligonga changya sp. n.; yellow: Gaoligonga zhusun sp. n.; orange: Crassignatha pianma sp. n.; purple: Crassignatha yinzhi sp. n.
Figure 96 in The symphytognathoid spiders of the Gaoligongshan, Yunnan, China (Araneae: Araneoidea): Systematics and diversity of micro-orbweavers
Figure 96. Distribution map, inset map shows study area. Black: Wendilgarda muji sp. n.; yellow: Mysmena changouzi sp. n.; blue: Mysmena bizi sp. n.; red: Mosu huogou sp. n.; purple: Crassignatha quanqu sp. n.; white: Crassignatha gudu sp. n.
Figure 95 in The symphytognathoid spiders of the Gaoligongshan, Yunnan, China (Araneae: Araneoidea): Systematics and diversity of micro-orbweavers
Figure 95. Distribution map, inset map shows study area. Blue: Baalzebub nemesis sp. n.; red: Theridiosoma shuangbi sp. n.; purple: Mysmena jinlong sp. n.; yellow: Crassignatha longtou sp. n.
Figure 97 in The symphytognathoid spiders of the Gaoligongshan, Yunnan, China (Araneae: Araneoidea): Systematics and diversity of micro-orbweavers
Figure 97. Distribution map, inset map shows study area. Yellow: Mysmena goudao sp. n.; red: Mysmena haban sp. n.; purple: Simaoa yaojia sp. n.; white: Simaoa kavanaugh sp. n.
Figure 89. A, B in The symphytognathoid spiders of the Gaoligongshan, Yunnan, China (Araneae: Araneoidea): Systematics and diversity of micro-orbweavers
Figure 89. A, B, Crassignatha ertou sp. n. from Zaotang He; C, D, Crassignatha gudu sp. n. from Zaotang He; E, F, Crassignatha longtou sp. n. from Yamu He. A, C, E, epigynum, ventral view; B, D, F, cleared vulva, dorsal view. CD: copulatory duct; S: spermatheca.
Figure 85 in The symphytognathoid spiders of the Gaoligongshan, Yunnan, China (Araneae: Araneoidea): Systematics and diversity of micro-orbweavers
Figure 85. Crassignatha quanqu sp. n. from Bang Bie village, SEM of spinnerets. A-E, female; F, male. A, spinnerets; B, ALS; C, PMS; D, F, PLS; E, base of ALS showing lack of colulus. AC: aciniform gland spigot; AG: aggregate gland spigot; ALS: anterior lateral spinneret; CY: cylindrical gland spigot; FL: flagelliform gland spigot; MAP: major ampullate gland spigot; mAP: minor ampullate gland spigot; n: nubbin; PI: piriform gland spigot; PLS: posterior lateral spinneret; PMS: posterior median spinneret; t: tartipore.
Figure 84 in The symphytognathoid spiders of the Gaoligongshan, Yunnan, China (Araneae: Araneoidea): Systematics and diversity of micro-orbweavers
Figure 84. Crassignatha quanqu sp. n. from Bang Bie village, male palp. A, prolateral; B, retrolateral. CB: cymbium; CT: cymbial tooth; E: embolus; EM: embolic membrane; MA: median apophysis; T: tegulum.
Figure 92 in The symphytognathoid spiders of the Gaoligongshan, Yunnan, China (Araneae: Araneoidea): Systematics and diversity of micro-orbweavers
Figure 92. Crassignatha longtou sp. n. from Yamu He, SEM of female spinnerets. A, spinnerets; B, ALS; C, PMS; D, PLS. AC: aciniform gland spigot; AG: aggregate gland spigot; ALS: anterior lateral spinneret; CY: cylindrical gland spigot; FL: flagelliform gland spigot; MAP: major ampullate gland spigot; mAP: minor ampullate gland spigot; n: nubbin; PI: piriform gland spigot; PLS: posterior lateral spinneret; PMS: posterior median spinneret; t: tartipore.
Figure 87 in The symphytognathoid spiders of the Gaoligongshan, Yunnan, China (Araneae: Araneoidea): Systematics and diversity of micro-orbweavers
Figure 87. Crassignatha yamu sp. n. from Yamu He, male palp. A, prolateral; B, retrolateral. CB: cymbium; CT: cymbial tooth; E: embolus; EM: embolic membrane; MA: median apophysis; T: tegulum.
Figure 94 in The symphytognathoid spiders of the Gaoligongshan, Yunnan, China (Araneae: Araneoidea): Systematics and diversity of micro-orbweavers
Figure 94. Distribution map, inset map shows study area. Blue: Epeirotypus dalong sp. n.; purple: Ogulnius barbandrewsi sp. n.; yellow: Theridiosoma diwang sp. n.; red: Zoma dibaiyin sp. n.; black: Coddingtonia euryopoides sp. n.; white: Mysmena shibali sp. n.; orange: Crassignatha yamu sp. n.
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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.