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149 results for “R2*”
LMD Inconel 718 Random Tracks 2021-03-03 r2
<p>Description of dataset 10.5281/zenodo.5607279</p> <p>Deposition of 4 Inconel 718 random tracks with process parameters:<br> - Nominal power = 300 (W)<br> - Nominal velocity = 600 (mm/min)<br> - Powder flux = 0.0825 (g/s)<br> - Spiral size: 60 mm side, 3 mm step<br> - Nr. nozzles = 4<br> - Argon carrier flux = 4 (l/min)<br> - Argon shielding gas flux = 15 (l/min)<br> - Substrate temperature = Ambient<br> - Machine: Laserdyne 430</p> <p>The dataset is constituted by:<br> - Melt pool images, in file Deposition_2021_03_03__15_42_36.zip, acquired at 200fps with 850 nm narrow band filter, 1ms exposure time. 400x400 px size<br> - trAll.csv containing:<br> - t: timestamp in ms. Synchronized with imAll.csv<br> - Xpos: laser spot X position in workspace<br> - Ypos: laser spot Y position in workspace<br> - Zpos: laser spot Z position in workspace<br> - G1: binary signal indicating active deposition (G1=1) or not<br> - D: track width measured at [Xpos(t), Ypos(t), Zpos(t)]<br> - H: track heigth measured at [Xpos(t), Ypos(t), Zpos(t)]<br> - A: track section area measured at [Xpos(t), Ypos(t), Zpos(t)]<br> - sdres: roughness index of section profile (std. deviation w.r.t. smoothed profile)<br> - Vnom: laser spot translational speed in m/s (computed from Xpos, Ypos, Zpos and t data)<br> - Pnom: nominal power<br> - V: Vnom in mm/min<br> - imAll.csv containing:<br> - t: timestamp in ms. Synchronized with trAll.csv<br> - I_mean: mean image intensity (only on red channel)<br> - I_mean_crop: mean image intensity computed on central cropped image area (180x180 pixels)<br> - M_I_mean: I_mean after application of 8-sample moving average<br> - M_I_mean_crop: I_mean_crop after application of 8-sample moving average<br> - fileName: associated image file name<br> - beamON: laserON signal obtained from thresholding on images (background noise = off, minimal intensity level = on)</p> <p>Additional source files:<br> - G-Code part program RandomTrack_0_rot_False.cnc<br> - Machine log file Scope 20210303-154513 RANDOMTRACK_r2.mos<br> - 3D scan of sample geometry randomTrack_r2_keyence_2_skip3_surface<br> - Sample photo 20210303_RandomTracks_r2.jpeg</p>
Reducing cardiac-induced noise in brain maps of R2* and magnetic susceptibility
<p>This high resolution dataset contain MR images of one participant acquired with a standard linear sampling and a cartesian pseudo-spiral sampling, with 3 repetitions each. It also contain the corresponding R2* and QSM maps shown in the paper. The data are presented both as .nii and .mat files.</p>
It takes Tau to tango : Investigating the fuzzy interaction between the Tau-R2 repeat domain and the C-terminal tails of tubulins
<p>The microtubule-associated protein (MAP) tau plays a key role in the regulation of microtubule assembly and spatial organisation. Tau hyperphosphorylation affects its binding on the tubulin surface and has been shown to be involved in several pathologies such as Alzheimer disease. As the tau binding site on the microtubule lays close to the disordered and highly flexible tubulin C-terminal tails (CTTs), these are likely to impact the tau-tubulin interaction. Since the disordered tubulin CTTs are missing from the available experimental structures, we used homology modeling to build two complete models of tubulin heterotrimers with different isotypes for the β-tubulin subunit (βI/αI/βI and βIII/αI/βIII). We then performed long timescale classical Molecular Dynamics simulations for the tauR2-tubulin assembly (in systems with and without CTTs) and analyzed the resulting trajectories to obtain a detailed view of the protein interface in the complex and the impact of the CTTs on the stability of this assembly. Additional analyses of the CTTs mobility in the presence, or in the absence, of tau also highlight how tau might modulate the CTTs activity as hooks that are involved in the recruitment of several MAPs.</p>
Text-fig. 1. a: Idealised section of the Intra-Sudetic Basin (from Opluštil et al. 2016); b: Geological sketch map of the IntraSudetic Basin, here simplified (after Prouza and Tásler 2001, Pešek 2004). Explanations: 1 – Bohdašín Formation (Triassic), 2 – Bohuslavice Formation (Thuringian), 3 – Trutnov Formation (Saxonian), 4–13 Broumov Formation (Autunian): 4 – Martínkovice Member, 5 – Martínkovice Member with Jetřichovice, Hejtmánkovice and Vižňov horizons, 6–13 – Olivětín Member: 6 – Walchia bone coal facies, 7 – Basaltoides of the Šonov Group, 8 – Volcanoclastic facies, 9 – Aleuropelites, 10 – Ignimbrites, 11 – Rhyolite tuffs, 12 – Ruprechtice Limestone Horizon, 13 – Otovice Limestone Horizon. Localities: O1 – Otovice "Černý potok", O2 – Otovice "Stěnava", O3 – Otovice "Chmelnice", O4 – Otovice "Vápenka", R1 – Ruprechtice "Vápencové lomy", R2 – Ruprechtice "Pod Světlinou", R3 – Olivětín "Nad náhonem". in Actinopterygians Of The Broumov Formation (Permian) In The Czech Part Of The Intra-Sudetic Basin (The Czech Republic)
Text-fig. 1. a: Idealised section of the Intra-Sudetic Basin (from Opluštil et al. 2016); b: Geological sketch map of the IntraSudetic Basin, here simplified (after Prouza and Tásler 2001, Pešek 2004). Explanations: 1 – Bohdašín Formation (Triassic), 2 – Bohuslavice Formation (Thuringian), 3 – Trutnov Formation (Saxonian), 4–13 Broumov Formation (Autunian): 4 – Martínkovice Member, 5 – Martínkovice Member with Jetřichovice, Hejtmánkovice and Vižňov horizons, 6–13 – Olivětín Member: 6 – Walchia bone coal facies, 7 – Basaltoides of the Šonov Group, 8 – Volcanoclastic facies, 9 – Aleuropelites, 10 – Ignimbrites, 11 – Rhyolite tuffs, 12 – Ruprechtice Limestone Horizon, 13 – Otovice Limestone Horizon. Localities: O1 – Otovice "Černý potok", O2 – Otovice "Stěnava", O3 – Otovice "Chmelnice", O4 – Otovice "Vápenka", R1 – Ruprechtice "Vápencové lomy", R2 – Ruprechtice "Pod Světlinou", R3 – Olivětín "Nad náhonem".
Рис. 1. Nipponacmea fuscoviridis: A–С – раковины (А – длина 17.9 мм, В – длина 19.5 мм, С – длина 20.2 мм), № 45631/Ga-9507 (ZMFU); D – расположение радулЯрного меШка (R1 – переднЯЯ праваЯ петлЯ, R2 – ЗаднЯЯ петлЯ); E, F – скульптура раковины (СЭМ). МасШтаб: D – 5 мм, E, F – 0.3 мм. in Nipponacmea fuscoviridis (Teramachi, 1949) (Gastropoda: Lottiidae) - a new limpet species for Russia
Рис. 1. Nipponacmea fuscoviridis: A–С – раковины (А – длина 17.9 мм, В – длина 19.5 мм, С – длина 20.2 мм), № 45631/Ga-9507 (ZMFU); D – расположение радулЯрного меШка (R1 – переднЯЯ праваЯ петлЯ, R2 – ЗаднЯЯ петлЯ); E, F – скульптура раковины (СЭМ). МасШтаб: D – 5 мм, E, F – 0.3 мм.
Stable Modeling on Resource Usage Parameters of MapReduce Application-Figure 6. RSE and R2 of regression models of MapReduce applications
<p>Figure 6 shows the fit quality of regression models. It is following.The left panel and the right panel of figure 6 show the residual standard error (RSE) distribution and R2 distribution of each application. The good fit quality corresponds to a taller R2 bar and a shorter RSE bar. The R2 almost 1 and small RSE show the best fit quality of the regression models on memory usage as the response. The overall higher RSE and lower R2 of regression models on CPU as the response show the worse quality of fitting goodness. The regression models on read rate as the response also show a moderate fitting quality. For the regression models on write rate as the response, Terasort application exhibits the best quality and Teragen application as well. Others show the worse fitting quality. The results show that the regression models on intensive usage parameters as response exhibit the good fitting quality.</p>
Supplement of manuscript FWB-P-Nov-18-0586.R2
<p>This folder contains analysis data from the study published as Article (Manuscript ID FWB-P-Nov-18-0586.R2):</p> <p>TITLE:</p> <p>Phylogenetic placement of environmental sequences using taxonomically reliable databases helps to rigorously assess dinophyte biodiversity in Bavarian lakes (Germany)</p> <p>JOURNAL:</p> <p>Freshwater Biology MS-ID: FWB-P-Nov-18-0586.R2</p> <p>FILES:</p> <p>FWB-P-Nov-18-0586.R2_metadata.csv (geo-references and metadata)</p> <p>FWB-P-Nov-18-0586.R2_OTU-table.csv (OTU-table)</p>
Fig. 1. Recent Cape hare Lepus capensis Linnaeus, 1758 RAM R2 in Head and neck posture in sauropod dinosaurs inferred from extant animals
Fig. 1. Recent Cape hare Lepus capensis Linnaeus, 1758 RAM R2 in right lateral view, illustrating maximally extended pose (A) and ONP (B): skull, cervical vertebrae 1–7 and dorsal vertebrae 1–2. Note the very weak dorsal deflection of the base of the neck in ONP, contrasting with the much stronger deflection illustrated in a live rabbit by Vidal et al. (1986: fig. 4).
A characterization of cardiac-induced noise in R2* maps of the brain
<p>A subset of data used in the original publication for computations of the results. These data contain 5D k-space data (kx/ky/kz/cardiac phase/TE) from one of the participants and can be used to perform the cardiac-induced noise characterization and retrieve the results from the paper.</p>
68Ga-PSMA-R2 in Patients With Biochemical Relapse (BR) and Metastatic Prostate Cancer (mPCa)
ClinicalTrials.gov study NCT03490032. IPD Sharing: YES. Countries: 1. Publications: 0.
Annotated genes harboring major effect markers (R2 ≥ 15%). Highlighted in green are genes annotated from Rhodes et al. 2014,2017, in orange genes annotated as similar to Peroxidase, in yellow new annotations from sorghum genome in Atlas. In the first three columns start and stop position on the sorghum genome and transcript name, followed by the nearest marker name and the distance of the gene from the nearest marker, then a column where are shown the GWAS methods and target traits for which the linked SNP was significant, the last column shows the category of the genes.
<p><strong>We conducted a comprehensive genomics study to map genomic loci determining the production of antioxidants in sorghum grains. Encouraging results were obtained and published in peer-reviewed article with impact factor (https://doi.org/10.1371/journal.pone.0225979). Annotated genes harboring major effect markers (R<sup>2</sup> ≥ 15%) were identified and will be of worldwide interest. </strong></p>
'A posteriori' genes harboring major effect marker (R2 ≥ 15%)
<p>In The process of our comprehensive mapping of the genomic loci governing the production of antioxidants in sorghum, we identified a posteriori genes harboring major effect marker. All genes involved in polyphenols metabolic pathway were considered 'a priori' candidates, including those genes that were reported in previous works. Regardless of their annotation and putative function, all genes containing a significant marker within their sequence were considered 'a posteriori' candidates. <strong> </strong> </p>
Data for: Free-Breathing Water, Fat, R2∗ and B0 Field Mapping of the Liver Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (MERLOT)
<p>Data for our manuscript with title "Free-Breathing Water, Fat, R2∗ and B0 Field Mapping of the Liver Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (MERLOT)"</p>
Figure R2
<p><span>(Left) Original data of magnetic domains in the MO sensor collected with <em>B</em> = -1.1 mT (Ref. 11). (Right) Binalized data, a part of which is shown in panel 2 of Figure 3 in the main text. Note that the black/white is inverted compared with the left figure for clarity.</span></p>
Supplementary Raw Data JASN-2021-05-0680.R2
<p>Raw data from experimental procedures published in the paper "Decreased renal gluconeogenesis is a hallmark of chronic kidney disease"</p>
Modelos de regresión y su desviación estándar, ajustados para la pérdida de peso en función del tiempo para la hojarasca evaluada en el delta del Rio Ranchería - brazo Riíto. K: tasa de descomposición (g/día). R2: coeficiente de determinación, 5g (días): días que se necesitan para descomponer 5g.
<p>Publicado en:</p> <p>Hernández Escobar, L., Granados-Martínez, C. & Fuentes-Reinés, J. (2022). Descomposición acuática de la hojarasca foliar en tres especies de mangle en la desembocura del río Ranchería (Brazo Riíto) y su relación con los macroinvertebrados en el municipio de Riohacha, departamento de La Guajira. <em>Ciencia e Ingeniería</em>, 9 (1):e6709388. https://www.doi.org/10.5281/zenodo.6709388</p>
Survey of postdoctoral affairs infrastructure at U.S. R1 and R2 institutions
<p><strong>Introduction: </strong>The number of postdoctoral scholars working at academic institutions in the United States (U.S.) has grown consistently over the past 40 years, driving calls for better infrastructure to support their specific needs. In response, some institutions have built postdoctoral affairs offices that serve as clearinghouses for information, foster improved mentorship between postdoctoral scholars and their supervisors, and provide training opportunities that contribute to professional development. We assessed postdoctoral affairs infrastructure and the associated training opportunities currently offered at the largest academic institutions within the United States as of spring 2022.</p> <p><strong>Methods: </strong>To carry out this survey, we compiled a list of all R1 and R2 institutions in 2021 as determined by the Carnegie classification system. We first placed any institution classified as an R1 or an R2 into one of four categories, based on the information publicly available on each institution’s website:</p> <ol> <li>Institution has a clear “Office of Postdoctoral Affairs (OPA),” or similar infrastructure that is run by the institution. This may include joint offices for graduate and postdoctoral affairs when it is clear that the distinct needs of postdocs are recognized.</li> <li>Institution has a “Postdoctoral Association (PDA)” that is run by current postdocs on a voluntary basis. Funding may be provided by the institution.</li> <li>Institution has a postdoc landing webpage, such as a list of links or online resources, but has no clear OPA or PDA.</li> <li>Institution has no postdoc landing webpage.</li> </ol> <p>There were several instances where a combination of categories 1, 2, and 3 were evident. In some cases, schools/colleges within an institution (e.g., medical school) had resources for their postdocs, but these were not clearly available for all postdoctoral scholars at the institution and thus were not considered for these purposes.</p> <p>For each institution classified as 1, 2, 3 or a combination thereof, we categorically assessed (Yes/No) whether or not postdocs were offered any postdoc-specific, in-house training by their OPA or PDA by searching the postdoctoral affairs website. We defined “in-house training” as any event that was led or organized by, or otherwise originated in the host institution. We did not include events run by national organizations such as the National Postdoc Association (NPA), or National Center for Faculty Development and Diversity (NCFDD), as we considered these to be separate. While there are areas in which the needs of graduate students and postdocs overlap, for this study we identified postdoc-specific training as events that were clearly and intentionally aimed at postdocs (i.e., were not events combining postdocs with graduate students, faculty and staff, or the wider university community). For those institutions that offered in-house postdoc training, we then categorized each training opportunity or event into one of seven broad themes:</p> <ol> <li>Research skills (e.g., data management, grant writing)</li> <li>Teaching skills (e.g., pedagogy, curriculum development)</li> <li>Professional skills (e.g., leadership, mentorship, project management)</li> <li>Job market preparation (e.g., preparing job application materials, career talks from academia and industry)</li> <li>Institutional onboarding (e.g., orientations, library information sessions)</li> <li>Mental health and wellness (e.g., work-life balance)</li> <li>Diversity, equity and inclusion (e.g., understanding the value of diversity in the workplace)</li> </ol> <p>To standardize data and align with the R1 & R2 2021 Carnegie classification update, we limited our search of postdoc training opportunities to the 2021 calendar year. We did not include every training opportunity within the full calendar year; once we had found an event to fit each of the seven categories, we ended our search for that individual institution. In cases where the events calendar was blank, restricted to current or future events (2022), or located behind an institutional login page, we attempted to locate other publicly available sources of information. Nevertheless, we have likely captured all of the institutions that do actually have training opportunities. After completing the categorization of events, we also summed the total number of different postdoctoral training opportunity themes addressed by the institution.</p> <p><strong>Acknowledgements: </strong>This survey was supported by the Grand Challenges Initiative at Chapman University. </p>
Data for "Workhorse minimally-empirical dispersion-corrected density functional, with tests for weakly-bound systems: r2 SCAN + rVV10"
<p>VASP inputs and outputs for the:</p> <ul> <li>Ar2 binding energy curve (Ar2_bpara.tar.gz)</li> <li>L28 set of layered-solid geometries and interlayer binding energies (L28.tar.gz)</li> <li>S22 set of interaction energies of weakly-bound complexes (S22.tar.gz)</li> </ul> <p>All POTCAR files have been replaced by "potcar.txt" files containing the title(s) of the POTCAR(s) needed to reproduce the calculations. A preprint is available from the arXiv:2204.11717 (<a href="https://arxiv.org/abs/2204.11717">link</a>).</p>
SMART-R2 Ground based C-band mobile radar observations of Hurricane Harvey landfall 2017
<p>This dataset contains radar scans collected by Shared Mobile Atmospheric Research and Teaching Radar #2 (SMART-R2) near Woodsboro, Texas during Hurricane Harvey landfall, 25-26 August 2017.</p> <p>Extract the data on a Unix system with the command "tar zxf hurricane_harvey.smart-r2.tar.gz"</p> <p>Directory harvey/SR2/iris_data/product_raw contains the data. The files are in Sigmet raw product format, documented at:<br> ftp://ftp.sigmet.com/outgoing/manuals/IRIS_Programmers_Manual.pdf</p> <p>Directory hurricane_harvey.smart-r2/SR2/log/ contains the radar operator's log.</p> <p>The deployment was funded by RAPID grant AGS-1759479 from the National Science Foundation, funds from the School of Meteorology at the University of Oklahoma, and a NASA Earth and Space Science Fellowship Program grant 17-EARTH17R-72.</p> <p>For more information, please contact:<br> M. I. Biggerstaff drdoppler@ou.edu<br> G. D. Carrie gordon.carrie-1@ou.edu</p> <p> </p>
Primrose16 r2 Downsampling
This dataset contains genomic sequences downsampled from the Primrose16 genome.
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International Brain Laboratory public data
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OpenNeuro
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