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10,554 results for “measurements”
Experimental data for a 5MHz acoustic measuring probe: partⅠ
<p>This is the data base about the study on a newly developed acoustic probe. The frequency of the probe is 5MHz. The sand sample used in the study is relatively small and all come from Changjiang River. BSI means back scattered sound intensity, SSC means suspended sediment concentration. Exponential method and power method are put forward to the fit of the experimental data, the correlation coefficient and parameters of the two method are calculated. </p> <p>This data base including:</p> <p>(1) recorded time-averaged BSI of each group with different SSC.</p> <p>(2) changes of recorded BSI plot against SSC.</p> <p>(3) calculation table for correlation coefficient of exponential method and power method.</p> <p>BSI is obtained from analyzing time domain signals. </p>
Quantifying capital vs. income breeding: new promise with stable isotope measurements of individual amino acids
<p>1. Capital breeders accumulate nutrients prior to egg development, then use these stores to support offspring. In contrast, income breeders rely on local nutrients consumed contemporaneously with offspring development. Understanding such nutrient allocations is critical to assessing wildlife reliance on different habitats.</p> <p>2. Despite the contrast between these strategies, it remains challenging to trace nutrients from endogenous stores or exogenous food intake into offspring. Here, we tested a new solution to this problem.</p> <p>3. Using tissue samples collected opportunistically from wild emperor penguins (<i>Aptenodytes forsteri</i>), which exemplify capital breeding, we hypothesized that the stable carbon (δ<sup>13</sup>C) and nitrogen (δ<sup>15</sup>N) isotope values of individual amino acids (AA) in endogenous stores (e.g., muscle) and in egg yolk and albumen reflect the nutrient sourcing that distinguishes capital versus income breeding. Unlike other methods, this approach does not require untested assumptions or diet sampling.</p> <p>4. We found that over half of essential AA had δ<sup>13</sup>C values that did not differ between muscle and yolk or albumen, suggesting that most of these AA were directly routed from muscle into eggs. In contrast, almost all non-essential AA differed in δ<sup>13</sup>C values between muscle and yolk or between muscle and albumen, suggesting <i>de novo</i> synthesis. Over half of AA that have labile nitrogen atoms (i.e., "trophic" AA) had higher δ<sup>15</sup>N values in yolk and albumen than in muscle, suggesting that they were transaminated during their routing into egg tissue. This effect was smaller for AA with less labile nitrogen atoms (i.e., "source" AA).</p> <p>5. Our results indicate that the δ<sup>15</sup>N offset between trophic-source AA (Δ<sup>15</sup>N<sub>trophic-source</sub>) may provide an index of the extent of capital breeding. The value of emperor penguin Δ<sup>15</sup>N<sub>Pro-Phe</sub> was higher in yolk and albumen than in muscle, reflecting the mobilization of endogenous stores; in comparison, the value of Δ<sup>15</sup>N<sub>Pro-Phe</sub> was similar across muscle and egg tissue in previously-published data for income-breeding herring gulls (<i>Larus argentatus smithsonianus</i>). Our results provide a quantitative basis for using AA δ<sup>13</sup>C and δ<sup>15</sup>N, and isotopic offsets among AA (e.g., Δ<sup>15</sup>N<sub>Pro-Phe</sub>), to explore the allocation of endogenous versus exogenous nutrients across the capital versus income spectrum of avian reproduction.</p>
A 5% measurement of the gravitational constant in the Large Magellanic Cloud
<p><strong>Reproduction package for the paper "A 5% measurement of the gravitational constant in the Large Magellanic Cloud".</strong></p> <p><strong>The package contains inlist and run_star_extra.f files for MESA that can be used to simulate Cepheid variable stars under different values of the gravitational constant. Also included is a Python MCMC script for sampling MESA Cepheid models and comparing with measurements from Pilecki et al., ApJ 862 43 (2018).</strong></p>
Measures of Freight Network Resiliency During the Covid-19 Pandemic
<p>Recent headlines depict significant shifts in operations within the freight community in particular, e.g., HOS laws suspended at a national level for the first time in 82 years1; national carriers shifting operations completely to grocery supply chains2; fleet operators laying off employees in response to manufacturing closures3. As a result of the current COVID-19 pandemic, there is a great need to capture freight movement data (not otherwise collected) to measure the effects of the COVID-19 response and recovery practices on freight network resiliency. In this project, we consider an expanded definition of the freight network, beyond roads and warehouses, to include truck drivers and driver support systems. </p> <p>Driver support systems include physical infrastructure like public and private rest stops as well as operational protections like Hours of Service (HOS). COVID-19 responses by public agencies and private citizens have affected drivers and driver support systems by three mechanisms. First, increased demand for medical supplies, food and packaged goods creates a need for more trucks and drivers, and the increased need for quick shipments promotes an environment in which speeding and unsafe driving practices may prevail. Second, with HOS restrictions lifted by the National Highway Transportation Safety Administration (NHTSA) driver fatigue may occur at greater frequency leading to unsafe driving conditions and higher likelihood of accidents. Third, the effects of social distancing mandates can lead to closures of critical, but oft forgotten, freight infrastructure like rest areas and truck stops, leaving drivers without necessary rest opportunities. While any single mechanism has detrimental effects on driver health and safety, the economy, and national recovery efforts, when combined, the system can be pushed to failure. Pandemic responses have only exacerbated critical industry issues like driver shortages, lack of available parking, and HOS compliance issues stemming from electronic logbooks. The purpose of this work was to develop and implement a driver health and safety survey during the pandemic. </p>
IASI/Metop-A formic acid total column measurements v3R (2010-2012)
<p>This dataset includes the formic acid (HCOOH) total columns (in molecules cm<sup>-2</sup>) obtained from the IASI/Metop-A satellite observations over 2010-2012, using the Artificial Neural Network for IASI (ANNI) v3R retrieval framework. The data are already filtered for clouds and poor measurement sensitivity. Description of the formic acid product and retrieval method can be found in Franco et al. (2018). Before the use of this dataset, please get in touch first with the main developers (Bruno Franco (bfranco@ulb.ac.be) and Lieven Clarisse (lclariss@ulb.ac.be) from which use advices and more recent product versions can be obtained.</p> <p>Franco, B., Clarisse, L., Stavrakou, T., Müller, J.-F., Van Damme,M., Whitburn, S., et al. (2018). A general framework for global retrievals of<br> trace gases from IASI: Application tomethanol, formic acid, and PAN. Journal of Geophysical Research: Atmospheres, 123, 13,963–13,984. https://doi.org/10.1029/2018JD029633</p>
MFS-M-00006 Air temperature measured at 2m, raised bog-ryam, ROTRONIC HygroClip S3
<p>Air temperature at 2m measured in a raised bog ecosystem (treed bog community) by ROTRONIC HygroClip S3 (temperature logger), 2010-continues, 30 min frequency, several gaps in data, N60.89164 E68.67690, as part of meteorological monitoring in Mukhrino Field Station (https://mukhrinostation.com/).</p>
MFS-M-00007 Air temperature measured at 2m, raised bog-lawn, ROTRONIC HygroClip S3
<p>Air temperature at 2m measured in a raised bog ecosystem (treed bog community) by ROTRONIC HygroClip S3 (temperature logger), 2010-continues, 30 min frequency, several gaps in data, N60.89164 E68.67690, as part of meteorological monitoring in Mukhrino Field Station (https://mukhrinostation.com/).</p>
MFS-M-00157 Snow precipitation measured manually (Tretyakov rain gauge), raised bog (ridge-hollow complex), 2010-present
<p>A raine gauge or Russian hydro-meteorological network standard (Tretyakov' construction) was installed as part of manual meteorological station in Mukhrino research polygon in 2010. The bucket installed at 2m height and protected by wind shield. Since 2014 only winter measurements were collected to supplement rain precipitation measurements measured in summer by automatic rain gauges (see also MFS-M-00154, MFS-M-00307, MFS-M-00308 for summer measurements in the same location).</p>
MFS-M-00308 Rain precipitation measured in raised bog (ridge-hollow complex), HOBO rain gauge RG3-M, 2017-present
<p>A raine gauge HOBO RG3-M was installed at the Mukhrino field station reseach polygon in the raised bog, treed bog community (ryam) in 2017, installation on the ground level (to prevent wind turbulence), measurement frequency - by event. This series is duplicated by MFS-M-00154 and MFS-M-00307 to cover variability and in case of breakdown. See also MFS-M-157 for winter (snow) precipitation at the same site measured manually.</p>
MFS-M-00154 Rain precipitation measured in raised bog (ridge-hollow compleх), HOBO rain gauge RG3-M, 2008-2019
<p>A raine gauge HOBO RG3-M was installed at the Mukhrino field station reseach polygon in the raised bog (ridge-hollow complex) in 2008, installation on the ground level (to prevent wind turbulence), measurement frequency - by event. This series was stopped by 2019 and replaced by another in close proximity (50 m), see MFS-M-00308 for precipitation after 2019.</p>
MFS-M-00156 Rain precipitation measured nearby Shapsha field station (in the village), HOBO rain gauge RG3-M, 2016-present
<p>A raine gauge HOBO RG3-M was installed in Shapsha village in an open space (Shapsha field station) as part of macrofungi long-term plots monitoring in Shapsha vicinity. Installation on the ground level to prevent wind turbulence.</p>
MFS-M-00155 Rain precipitation measured in coniferous forest, HOBO rain gauge RG3-M, 2015
<p>A raine gauge HOBO RG3-M was installed at the Mukhrino field station research polygon, in coniferous mixed forest to measure precipitation under tree canopy. But this installation worked only for one year (2015), after this was stopped.</p>
MFS-M-00307 Rain precipitation measured in raised bog (ryam), HOBO rain gauge RG3-M, 2017-present
<p>A raine gauge HOBO RG3-M was installed at the Mukhrino field station reseach polygon in the raised bog, treed bog community (ryam) in 2017, installation on the ground level (to prevent wind turbulence), measurement frequency - by event. This series is duplicated by MFS-M-00154 and MFS-M-00308 to cover variability and in case of breakdown. See also MFS-M-157 for winter (snow) precipitation at the same site measured manually.</p>
Quality control for modern bone collagen stable carbon and nitrogen isotope measurements
<p><strong>(1)</strong> Isotopic analyses of collagen, the main protein preserved in sub fossil bone and tooth, has long provided a powerful tool for the reconstruction of ancient diets and environments. Although isotopic studies of contemporary ecosystems have typically focused on more accessible tissues (e.g., muscle, hair), there is growing interest in the potential for analyses of collagen because it is often available in hard tissue archives (e.g., scales, skin, bone, tooth), allowing for enhanced long-term retrospective studies. The quality of measurements of the stable carbon and nitrogen isotopic compositions of ancient samples are subject to robust and well-established criteria for detection of contaminants and digenesis. Among these quality control (QC) criteria, the most widely utilized is the atomic C:N ratio (C:N<sub>Atomic</sub>), which for ancient samples has an acceptable range between 2.9 and 3.6. While this QC criterion was developed for ancient materials, it has increasingly being applied to collagen from modern tissues.</p> <p><strong>(2)</strong> Here we use a large survey of published collagen amino acid compositions (n<em> </em>= 436) from 193 vertebrate species as well as recent experimental isotopic evidence from 413 modern collagen extracts to demonstrate that the C:N<sub>Atomic</sub> range used for ancient samples is not suitable for assessing collagen quality of modern and archived historical samples.</p> <p><strong>(3) </strong>For modern tissues, collagen C:N<sub>Atomic</sub> falling outside 3.00–3.30 for fish and 3.00–3.28 for mammals and birds can produce systematically skewed isotopic compositions and may lead to significant interpretative errors. These findings are followed by a review of protocols for improving C:N<sub>Atomic</sub> criteria for modern collagen extracts.</p> <p><strong>(4)</strong> Given the tremendous conservation and environmental policy-informing potential that retrospective isotopic analyses of collagen from contemporary and archived vertebrate tissues have for addressing pressing questions about long-term environmental conditions and species behaviours, it is critical that QC criteria tailored to modern tissues are established.</p>
MORPHOMETRIC MEASUREMENTS (CM) OF THE BOBO CROAKER Pseudotolithus elongatus OBTAINED FROM THE CROSS RIVER, NIGERIA
<p>Morphometric measurements of the bobo croaker (Pseudotolithus elongatus) obtained from islands and estuary mouth of the Cross River, Nigeria.</p>
Data archive for the peer-reviewed journal article "Detailed characterization of the CAPS single scattering albedo monitor (CAPS PMssa) as a field-deployable instrument for measuring aerosol light absorption with the extinction-minus-scattering method"
<p>Data archive accompanying the peer-reviewed journal article "Detailed characterization of the CAPS single scattering albedo monitor (CAPS PMssa) as a field-deployable instrument for measuring aerosol light absorption with the extinction-minus-scattering method". In 2020 this article was accepted for publication in the journal <em>Atmospheric Measurement Techniques</em>. Data are uploaded in the form of ascii text files, Igor Pro experiment files (.pxp), and Jupyter notebook files. In addition, a Jupyter notebook file is included containing an implementation of the error model used in the paper.</p>
Data of normal spectral emissivity measurements for Ta, Mo, W and Nb
<p>Data aquired during my master thesis about the normal spectral emissivty of Ta, Mo, W and Nb measured with an ohmic pulse heating apparatus and a us-DOAP</p>
Measurement of ocular counter-roll using iris images during binocular fixation and head tilt
<p>All images and datas used in the study "Measurement of ocular counter-roll using iris images during binocular fixation and head tilt"</p>
June 2020 Eclipse Festival of Frequency Measurement - 10 MHz Frequency Estimation Data
<p>Frequency estimation and amplitude output from fldigi during the June Eclipse Festival of Frequency Measurement, synchronized as timetables in MATLAB. </p> <p>JEF_List: Station list with coordinates and basic information. <br> Freq.txt, Vpk.txt: short period of overlap between stations.<br> Freq_full.txt, Vpk_full.txt: Complete data, including practice and bonus data collection days. </p> <p>Thanks to all who collected data: 3V1E, 3V8SS, 9V1AW, 9V1KB, A45VU, A47RS, AD7TS, AD8Y, DK4BU, EAllUO, El7IG, F1ABL, F4IEW, GOLHZ, HZ1HM-SU9HM, JF9PKH, J13XOK/8, JJ1BDX, K1FR, K6FOD, K6RGI, KA3JAW, KD8CGH, KF5SMH, Luo Zhiwen, N7MN, NAOB, OE3WYC, PAOSLT, PAORWT, PA4WE, PD4C, PE1RCW, PE1RWP, PU3VRW, SA6EAL, SP9MUF, SP9WPN, SV1GRB, SV1IT, SV1ONK, SV1VC, SV2BBO, SV7BOT, Andrew Klekociuk, VK2DLR, VK3DFR, VK7KPC, W3LLA, and ZS6YZ.</p> <p>__________________________________________________________</p> <p><strong>Errata:</strong><br> Coordinate error: G0LHZ is <em>west</em> of the Greenwich line:<strong> G0LHZ Jim Carter 51.507468 - 1.080013</strong></p>
ImPACT Notary Service and Presidio Performance Measurements
<p>Performance data collected from <a href="https://github.com/RENCI-NRIG/notary-service">Notary Service</a> and <a href="https://github.com/RENCI-NRIG/impact-presidio">Presidio</a> components of <a href="http://cyberimpact.us">ImPACT</a> prototype implementation for inclusion with publications.</p>
ScienceDex guides
Understand access before you commit
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.