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66 results for “strontium”
TEM Data on Strontium-deficient SrxCoO2–CoO2 nanotubes
<p>Raw data ((scanning) transmission electron microscopy images, diffraction patterns and EDX/EELS spectra) obtained for work on Strontium-deficient SrxCoO2–CoO2 nanotubes as a high ampacity and high conductivity material published in Materials Horizons</p>
Cryogenic hyperabrupt strontium titanate varactors for sensitive reflectometry of quantum dots
<p>Supplementary Data for:</p> <p>"Cryogenic hyperabrupt strontium titanate varactors for sensitive reflectometry of quantum dots"</p> <p>Rafael S. Eggli, Simon Svab,Taras Patlatiuk, Dominique Trüssel, Miguel J. Carballido, Pierre Chevalier Kwon, Simon Geyer, Ang Li,<br> Erik P. A. M. Bakkers, Andreas V. Kuhlmann, and Dominik M. Zumbühl</p>
Interpolated data on bioavailable strontium in the southern Trans-Urals, 2020-2022 version 3.1 (current)
<p><strong>Description</strong></p> <p><strong>The Interpolated Strontium Values dataset Ver. 3.1 </strong>presents the interpolated data of strontium isotopes for the southern Trans-Urals, based on the data gathered in 2020-2022. The current dataset consists of five sets of files for five various interpolations: based on grass, mollusks, soil, and water samples, as well as the average of three (excluding the mollusk dataset). Each of the five sets consists of a CSV file and a KML file where the interpolated values are presented to use with a GIS software (ordinary kriging, 5000 m x 5000 m grid). In addition, two GeoTIFF files are provided for each set for a visual reference. </p> <p><a href="../records/10253264/files/Averaged%205000%20m%20interpolated%20points.kml?download=1">Average 5000 m interpolated points.kml</a> / <a href="../records/10253264/files/Averaged%205000%20m%20interpolation.csv?download=1">csv</a>: these files contain averaged values of all three sample types.</p> <p><a href="../records/10253264/files/Grass%205000%20m%20interpolated%20points.kml?download=1">Grass 5000 m interpolated points.kml</a> / <a href="../records/10253264/files/Grass%205000%20m%20interpolation.csv?download=1">csv</a>: these files contain data interpolated from the grass sample dataset.</p> <p><a href="../records/10253264/files/Mollusks%205000%20m%20interpolation%20raster.tif?download=1">Mollusks 5000 m interpolated points.kml</a> / <a href="../records/10253264/files/Mollusks%205000%20m%20interpolation.csv?download=1">csv</a>: these files contain data interpolated from the mollusk sample dataset.</p> <p><a href="../records/10253264/files/Soil%205000%20m%20interpolated%20points.kml?download=1">Soil 5000 m interpolated points.kml </a>/ <a href="../records/10253264/files/Soil%205000%20m%20interpolation.csv?download=1">csv</a>: these files contain data interpolated from the soil sample dataset.</p> <p><a href="../records/10253264/files/Water%205000%20m%20interpolated%20points.kml?download=1">Water 5000 m interpolated points.km</a>l / <a href="../records/10253264/files/Water%205000%20m%20interpolation.csv?download=1">csv</a>: these files contain data interpolated from the water sample dataset.</p> <p>The current version is also supplemented with GeoTiff raster files where the same interpolated values are color-coded. These files can be added to Google Earth or any GIS software together with KML files for better interpretation and comparison.</p> <p><a href="../records/10253264/files/Averaged%205000%20m%20interpolation%20raster.tif?download=1">Averaged 5000 m interpolation raster.tif</a>: this file contains a raster representing the averaged values of all three sample types.</p> <p><a href="../records/10253264/files/Grass%205000%20m%20interpolation%20raster.tif?download=1">Grass 5000 m interpolation raster.tif</a>: this file contains a raster representing the data interpolated from the grass sample dataset.</p> <p><a href="../records/10253264/files/Mollusks%205000%20m%20interpolation%20raster.tif?download=1">Mollusks 5000 m interpolation raster.tif</a>: this file contains a raster representing the data interpolated from the mollusk sample dataset.</p> <p><a href="../records/10253264/files/Soil%205000%20m%20interpolation%20raster.tif?download=1">Soil 5000 m interpolation raster.tif</a>: this file contains a raster representing the data interpolated from the soil sample dataset.</p> <p><a href="../records/10253264/files/Water%205000%20m%20interpolation%20raster.tif?download=1">Water 5000 m interpolation raster.tif</a>: this file contains a raster representing the data interpolated from the water sample dataset</p> <p>In addition, the cross-validation rasters created during the interpolation process are also provided. They can be used as a visual reference of the interpolation reliability. The grey areas on the raster represent the areas where expected values do not differ from interpolated values for more than 0.001. The red areas represent the areas where the error exceeded 0.001 and, thus, the interpolation is not reliable. </p> <p> </p> <p><strong>How to use it?</strong></p> <p>The data provided can be used to access interpolated background values of bioavailable strontium in the area of interest. Note that a single value is not a good enough predictor and should never be used as a proxy. Always calculate a mean of 4-6 (or more) nearby values to achieve the best guess possible. Never calculate averages from a single dataset, always rely on cross-validation by comparing data from all five datasets. Check the cross-validation rasters to make sure that the interpolation is reliable for the area of interest. </p> <p> </p> <p><strong>References</strong></p> <p>The interpolated datasets are based upon the actual measured values published as follows:</p> <p>Epimakhov, Andrey; Kisileva, Daria; Chechushkov, Igor; Ankushev, Maksim; Ankusheva, Polina (2022): Strontium isotope ratios (87Sr/86Sr) analysis from various sources the southern Trans-Urals. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.950380</p> <p> </p> <p><strong>Description of the original dataset of measured strontium isotopic values</strong></p> <p>The present dataset contains measurements of bioavailable strontium isotopes (87Sr/86Sr) gathered in the southern Trans-Urals. There are four sample types, such as wormwood (n = 103), leached soil (n = 103), water (n = 101), and freshwater mollusks (n = 80), collected to measure bioavailable strontium isotopes. The analysis of Sr isotopic composition was carried out in the cleanrooms (6 and 7 ISO classes) of the Geoanalitik shared research facilities of the Institute of Geology and Geochemistry, the Ural Branch of the Russian Academy of Sciences (Ekaterinburg). Mollusk shell samples preliminarily cleaned with acetic acid, as well as vegetation samples rinsed with deionized water and ashed, were dissolved by open digestion in concentrated HNO 3 with the addition of H 2 O 2 on a hotplate at 150°C. Water samples were acidified with concentrated nitric acid and filtered. To obtain aqueous leachates, pre-ground soil samples weighing 1 g were taken into polypropylene containers, 10 ml of ultrapure water was added and shaken in for 1 hour, after which they were filtered through membrane cellulose acetate filters with a pore diameter of 0.2 μm. In all samples, the strontium content was determined by ICP-MS (NexION 300S). Then the sample volume corresponding to the Sr content of 600 ng was evaporated on a hotplate at 120°C, and the precipitate was dissolved in 7M HNO 3. Sample solutions were centrifuged at 6000 rpm, and strontium was chromatographically isolated using SR resin (Triskem). The strontium isotopic composition was measured on a Neptune Plus multicollector mass spectrometer with inductively coupled plasma (MC-ICP-MS). To correct mass bias, a combination of bracketing and internal normalization according to the exponential law 88 Sr/ 86 Sr = 8.375209 was used. The results were additionally bracketed using the NIST SRM 987 strontium carbonate reference material using an average deviation from the reference value of 0.710245 for every two samples bracketed between NIST SRM 987 measurements. The long-term reproducibility of the strontium isotopic analysis was evaluated using repeated measurements of NIST SRM 987 during 2020-2022 and yielded 87 Sr/ 86 Sr = 0.71025, 2SD = 0.00012 (104 measurements in two replicates). The within-laboratory standard uncertainty (2σ) obtained for SRM-987 was ± 0.003 %. </p>
Figs 1A–H. Achradina pulchra. A–B in Achradina pulchra, a Unique Dinoflagellate (Amphilothales, Dinophyceae) with a Radiolarian-like Endoskeleton of Celestite (Strontium Sulfate)
Figs 1A–H. Achradina pulchra. A–B – Light micrographs of the isolated cells of Achradina pulchra for PCR analysis from the SW Atlantic (São Sebastião Channel). C–D – Other cells from the same sample. Note that the skeleton is internal. E–G – Scanning electron micrographs of the skeleton from the NE Atlantic (Seine and Sedlo Seamounts). H – X-ray energy dispersive spectroscopy (EDS) spectrum of the endoskeleton. Scale bars: 5 µm.
Interpolated data on bioavailable strontium in the southern Trans-Urals, 2020-2023, version 1.2. (current)
<p><strong>The Interpolated Strontium Values dataset Ver. 1.2 </strong>presents the interpolated data of strontium isotopes for the southern Trans-Urals, based on the data gathered in 2020-2023. The current dataset consists of five sets of files for two interpolations: based on grass, mollusks, soil, and water samples, as well as the average of three (excluding the mollusk dataset). Each of the five sets consists of a CSV file and a KML file where the interpolated values are presented to use with a GIS software (ordinary kriging, 5000 m x 5000 m grid). In addition, GeoTIFF and JPEG files are provided for each set for a visual reference. </p> <p>Version 1.2 fixes bugs in GeoTIFF files. They can now be accessed in Google Earth (choose "Scale" if prompted that an imported image is too large). </p> <p><strong>How to use it?</strong></p> <p>The data provided can be used to access interpolated background values of bioavailable strontium in the area of interest. Note that a single value is not a good enough predictor and should never be used as a proxy. Always calculate a mean of 4-6 (or more) nearby values to achieve the best guess possible. Never calculate averages from a single dataset, always rely on cross-validation by comparing data from all five datasets. Check the cross-validation rasters to make sure that the interpolation is reliable for the area of interest. </p> <p> </p> <p><strong>References</strong></p> <p>The interpolated datasets are based upon the actual measured values, partially (2020-2022) published as follows:</p> <p>Epimakhov, Andrey; Kisileva, Daria; Chechushkov, Igor; Ankushev, Maksim; Ankusheva, Polina (2022): Strontium isotope ratios (87Sr/86Sr) analysis from various sources the southern Trans-Urals. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.950380</p> <p>Kiseleva, D., Ankusheva, P., Maksim, A., Chechushkov, I., & Epimakhov, A. (2024). Strontium isotopes (87Sr/86Sr) data from southern Trans-Urals, 2023 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14257258</p> <p> </p> <p><strong>Description of the original dataset of measured strontium isotopic values</strong></p> <p>The present dataset contains measurements of bioavailable strontium isotopes (87Sr/86Sr) gathered in the southern Trans-Urals. There are two sample types, such as leached soil (n = 56) and water (n = 56), collected to measure bioavailable strontium isotopes. The analysis of Sr isotopic composition was carried out in the cleanrooms (6 and 7 ISO classes) of the Geoanalitik shared research facilities of the Institute of Geology and Geochemistry, the Ural Branch of the Russian Academy of Sciences (Ekaterinburg). Mollusk shell samples preliminarily cleaned with acetic acid, as well as vegetation samples rinsed with deionized water and ashed, were dissolved by open digestion in concentrated HNO 3 with the addition of H 2 O 2 on a hotplate at 150°C. Water samples were acidified with concentrated nitric acid and filtered. To obtain aqueous leachates, pre-ground soil samples weighing 1 g were taken into polypropylene containers, 10 ml of ultrapure water was added and shaken in for 1 hour, after which they were filtered through membrane cellulose acetate filters with a pore diameter of 0.2 μm. In all samples, the strontium content was determined by ICP-MS (NexION 300S). Then the sample volume corresponding to the Sr content of 600 ng was evaporated on a hotplate at 120°C, and the precipitate was dissolved in 7M HNO 3. Sample solutions were centrifuged at 6000 rpm, and strontium was chromatographically isolated using SR resin (Triskem). The strontium isotopic composition was measured on a Neptune Plus multicollector mass spectrometer with inductively coupled plasma (MC-ICP-MS). To correct mass bias, a combination of bracketing and internal normalization according to the exponential law 88 Sr/ 86 Sr = 8.375209 was used. The results were additionally bracketed using the NIST SRM 987 strontium carbonate reference material using an average deviation from the reference value of 0.710245 for every two samples bracketed between NIST SRM 987 measurements. The long-term reproducibility of the strontium isotopic analysis was evaluated using repeated measurements of NIST SRM 987 during 2020-2022 and yielded 87 Sr/ 86 Sr = 0.71025, 2SD = 0.00012 (104 measurements in two replicates). The within-laboratory standard uncertainty (2σ) obtained for SRM-987 was ± 0.003 %. </p>
Effect of low-temperature compression on crystal structure and superconductivity in strontium metal
<p>The superconducting and structural properties of elemental strontium metal were studies as a function of pressure to 60 GPa, while maintaining cryogenic conditions during the pressure application.</p> <p>This data set includes raw and analyzed electrical resistivity and xray diffraction data.</p>
Fig. 2 in Achradina pulchra, a Unique Dinoflagellate (Amphilothales, Dinophyceae) with a Radiolarian-like Endoskeleton of Celestite (Strontium Sulfate)
Fig. 2. Bayesian phylogenetic tree of dinoflagellate SSU rDNA sequences, based on 1,610 aligned positions. Names in bold represent sequences obtained in this study. The clades containing sequences of the symbionts of acantharians and polycystine radiolarians are highlighted in shaded boxes. Numbers at nodes are bootstrap values (values <50 are omitted). The scale bar represents the number of substitutions for a unit branch length.
Fig. 4 in Use of otolith strontium:calcium and zinc:calcium ratios as an indicator of the habitat of Percophis brasiliensis Quoy & Gaimard, 1825 in the southwestern Atlantic Ocean
Fig. 4. Discriminant analysis of the otolith Sr:Ca and Zn:Ca ratios for Percophis brasiliensis. Plot of the first two discriminant functions for each age group (a-d). An association was observed between data for ER and SMG, which were separated from data for AUCFZ. Triangles: ArgentineUruguayan Common Fishing Zone (AUCFZ), stars: San Matías Gulf (SMG) and black circles: El Rincón (ER).
Fig. 2 in Use of otolith strontium:calcium and zinc:calcium ratios as an indicator of the habitat of Percophis brasiliensis Quoy & Gaimard, 1825 in the southwestern Atlantic Ocean
Fig. 2. Variation of Sr:Ca (a) and Zn:Ca (b) ratios of Percophis brasiliensis separated by age for the three sampling sites. Different letters indicate statistical significant differences among age groups (years) for each sampling site (p<0.05).
Fig. 3 in Use of otolith strontium:calcium and zinc:calcium ratios as an indicator of the habitat of Percophis brasiliensis Quoy & Gaimard, 1825 in the southwestern Atlantic Ocean
Fig. 3. Relationship between otolith Sr:Ca and Zn:Ca ratios (mmol mol-1) for Percophis brasiliensis from three areas. Data for ER and SMG tended to cluster, while data for AUCFZ tended to disperse. Separation of data of AUCFZ and ER-SMG is observed. Triangles: Argentine-Uruguayan Common Fishing Zone (AUCFZ), stars: San Matías Gulf (SMG) and black circles: El Rincón (ER).
Data from: Evaluating tooth strontium and barium as indicators of weaning age in Pacific walruses
<p>A dataset of calcium-normalized <sup>88</sup>Sr and <sup>137</sup>Ba concentrations from laser ablation transects across the cementum layer of 107 (female: n = 84, male: n = 23) Pacific walrus (Odobenus rosmarus divergens) teeth. Dataset includes spreadsheets containing elapsed time of laser ablation transect in seconds (ElapsedTime_s; laser transect speed = 5μm/s), calcium-normalized strontium concentrations (Sr_ppm_m88; values below limit of detection replaced with 1/2*limit of detection, see methods), and calcium-normalized barium concentrations (Ba_ppm_m137; values below limit of detection replaced with 0.5*limit of detection). Photos (in .tif format) of tooth cementum used to estimate the positions of cementum growth layer groups are included for each animal. For teeth where more than one laser ablation scar is visible in the photo, an arrow is included to indicate the laser ablation scar that corresponds with the included trace element data. Finally, a Word document containing metadata (Catalog Number/ID, Sex, Median Age Est., Coll. Year, Est. Birth Year), weaning age estimates produced by both a visual and mathematical method (Sr Vis. Est., Sr Math. Est., Ba Vis. Est., Ba Math. Est.), and a descriptive grouping of the patterns of accumulation of Sr and Ba (Sr Pat., Ba Pat.) are included. See methods and accompanying paper in Methods in Ecology and Evolution for more details.</p>
New application of strontium isotopes reveals evidence of limited migratory behaviour in Late Cretaceous hadrosaurs
<p>Dinosaur migration patterns are very difficult to determine, often relying solely on the geographic distribution of fossils. Unfortunately, it is generally not possible to determine if a fossil taxon's geographic distribution is the result of migration or simply a wide distribution. Whereas some attempts have been made to use isotopic systems to determine migratory patterns in dinosaurs, these methods have yet to achieve wider usage in the study of dinosaur ecology.</p> <p>Here we have used strontium isotope ratios from fossil enamel to reconstruct the movements of an individual hadrosaur from Dinosaur Provincial Park in Alberta, Canada. Results from this study are consistent with a range or migratory pattern between Dinosaur Provincial Park and a contemporaneous locality in the South Saskatchewan River area, Alberta Canada. This represents a minimum distance of approximately 80 km, which is consistent with migrations seen in modern elephants. These results suggest the continent-wide distribution of some hadrosaur species in the Late Cretaceous of North America is not the result of extremely long-range migratory behaviours.</p>
Analysis of the occurrence of the fall armyworm (Spodoptera frugiperda) in the winter season on the southwestern islands of Japan using the insect's strontium radiogenic isotope ratio (87Sr/86Sr)
<p><em>Spodoptera frugiperda</em>, an invasive pest insect that targets maize and other crops, first arrived in Japan in the summer of 2019. This species occurs year-round in East Asian subtropical regions such as southern mainland China and the island of Taiwan, where the mean air temperature in the coldest month is above 10°C. Adults are similarly found throughout the year on the southwestern islands of Japan. Trap monitoring there showed continuous or intermittent <em>S. frugiperda</em> catches in the 3 winter seasons since 2019. However, it was difficult to distinguish between immigrants arriving from these neighboring areas and local individuals occurring on each Japanese island. In this study, the possible natal origin of captured insects on 5 small islands (Yonagunijima, Taramajima, Okinawajima, Amamioshima, and Tanegashima) was determined by investigating the strontium radiogenic isotope ratios (<sup>87</sup>Sr/<sup>86</sup>Sr) and comparing them with those of reference hosts and insects. Since trapping data and the <sup>87</sup>Sr/<sup>86</sup>Sr values of trapped insects didn't support <em>S. frugiperda</em>'s winter breeding on the northernmost island, Tanegashima, further analysis was limited to the 4 southern islands. The <sup>87</sup>Sr/<sup>86</sup>Sr values of reference host plants and reared insects on the 4 islands ranged from 0.70929 to 0.71009, while those of catch insects ranged from 0.70885 to 0.71090. The <sup>87</sup>Sr/<sup>86</sup>Sr values of the catch insects and the reference on the 4 islands did not differ significantly. In addition, the monthly averages of daily mean air temperature in January and February 2020–2022 were above 10°C, and the wind direction at the surface was mostly from the northeast or northwest. These pieces of evidence, together with winter host availability, suggested that <em>S. frugiperda</em> occurs year-round on the islands. In other words, the year-round occurrence area of <em>S. frugiperda</em> in East Asia extends to the Japanese southwestern islands below Amamioshima Island.</p>
Spatiotemporal changes in riverine input into the Eocene North Sea revealed by strontium isotope and barium analysis of bivalve shells
<p>Extended data and calculations belonging to this study are summarized in the supplementary material. These supplements contain the following supplementary data files: </p> <ul> <li>Supplementary material: supplementary Figure S1</li> <li>Supplementary data 1: Element and isotope data for each individual shell</li> <li>Supplementary data 2: <sup>87</sup>Sr/<sup>86</sup>Sr salinity variability reconstruction</li> <li>Supplementary data 3: Stratigraphy for sampling locations</li> <li>Supplementary data 4: <sup>87</sup>Sr/<sup>86</sup>Sr data for recent oyster shells</li> <li>Supplementary data 5: Extended strontium isotope data</li> </ul>
Data from: Rearing in strontium-enriched water induces vaterite otoliths in the Japanese rice fish, Oryzias latipes
<p>Sagittal otoliths, typically composed of aragonite, are frequently laid down rather as vaterite during growth in hatchery-reared fish populations. Sagittal vateritisation is believed to impair individual hearing/balancing abilities, but the causal mechanism remains unclear. Here we experimentally demonstrated that rearing in Sr-rich water induces sagittal vateritisation in the HdrR-II1 inbred strain of the Japanese rice fish, <em>Oryzias latipes</em>. Both sagittae were partly vateritised in 70% of individuals subjected to the Sr<sup>2+</sup> treatment (n = 10), whereas fish reared in normal tap water showed no sagittal vateritisation (n = 8). Our result is consistent with the theoretical prediction that vaterite becomes thermodynamically more stable than aragonite as the Sr<sup>2+</sup> concentration in solution increases. A vateritic layer develops surrounding the original aragonitic sagitta in vateritised otoliths, some of which take on a comma-like shape. Electron probe microanalysis demonstrates that the vateritised phase is characterised by lower Sr<sup>2+</sup> and higher Mg<sup>2+</sup> concentrations than the aragonitic phase. It is unlikely that increased environmental Sr<sup>2+</sup> is responsible for the sagittal vateritisation in farmed fish. However, our findings likely help to establish an in vivo assay using <em>O. latipes</em> to understand the physiological process underlying the sagittal vateritisation in farmed fish.</p>
Chemotherapy With or Without Strontium-89 in Treating Patients With Prostate Cancer
ClinicalTrials.gov study NCT00024167. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Instant and Lasting Relief Effects of Strontium Chloride/Potassium Nitrate Dentifrice on Dentin Hypersensitivity
ClinicalTrials.gov study NCT01426360. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Zoledronate, Vitamin D, and Calcium With or Without Strontium 89 or Samarium 153 in Preventing or Delaying Bone Problems in Patients With Bone Metastases From Prostate Cancer, Lung Cancer, or Breast C
ClinicalTrials.gov study NCT00365105. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Analysis of the occurrence of the fall armyworm (Spodoptera frugiperda) in the winter season on the southwestern islands of Japan using the insect’s strontium radiogenic isotope ratio (87Sr/86Sr)
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Data from: Evaluating tooth strontium and barium as indicators of weaning age in Pacific walruses
Open the record for dataset details and reuse information.
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