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528 results for “ACE”
Raw multibeam bathymetry data collected in the wider polynya area around the Mertz glacier, East Antarctica on board the R/V Akademik Tryoshnikov during the austral summer of 2016/2017 as part of the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>An ELAC Nautik 3020 multibeam echo sounder with a 20 kHz transducer mounted on the hull of the R/V Akademik Tryoshnikov, was used to collect multibeam bathymetry data during the Antarctic Circumnavigation Expedition (ACE). This particular dataset was collected in the wider polynya area around the Mertz glacier, East Antarctica in the austral summer of 2016/2017.</p> <p>Bathymetry data were used live during the cruise to look for suitable locations where benthic trawling and remotely-operated vehicle deployments could take place, rather than to undertake specific bathymetric surveys.</p> <p>This raw dataset is provided without calibration information for the surface sound velocity or instrumentation itself and should be used with due caution.</p> <p><strong>Dataset contents</strong></p> <ul> <li>lineYYYYDDmonHHMMSS.xse, data file, proprietary format</li> <li>location.hydrostar, ancillary file, ASCII</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This raw multibeam bathymetry dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/l</p>
Raw multibeam bathymetry data collected around the Mertz glacier, East Antarcica on board the R/V Akademik Tryoshnikov during the austral summer of 2016/2017 as part of the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>An ELAC Nautik 3020 multibeam echo sounder with a 20 kHz transducer mounted on the hull of the R/V Akademik Tryoshnikov, was used to collect multibeam bathymetry data during the Antarctic Circumnavigation Expedition (ACE). This particular dataset was collected around the Mertz glacier, East Antarcica in the austral summer of 2016/2017.</p> <p>Bathymetry data were used live during the cruise to look for suitable locations where benthic trawling and remotely-operated vehicle deployments could take place, rather than to undertake specific bathymetric surveys.</p> <p>This raw dataset is provided without calibration information for the surface sound velocity or instrumentation itself and should be used with due caution.</p> <p><strong>Dataset contents</strong></p> <ul> <li>lineYYYYDDmonHHMMSS.xse, data file, proprietary format</li> <li>location.hydrostar, ancillary file, ASCII</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This raw multibeam bathymetry dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Raw multibeam bathymetry data collected around the Balleny Islands, Antarctica on board the R/V Akademik Tryoshnikov during the austral summer of 2016/2017 as part of the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>An ELAC Nautik 3020 multibeam echo sounder with a 20 kHz transducer mounted on the hull of the R/V Akademik Tryoshnikov, was used to collect multibeam bathymetry data during the Antarctic Circumnavigation Expedition (ACE). This particular dataset was collected around the Balleny Islands, Antarctica in the austral summer of 2016/2017.</p> <p>Bathymetry data were used live during the cruise to look for suitable locations where benthic trawling and remotely-operated vehicle deployments could take place, rather than to undertake specific bathymetric surveys.</p> <p>This raw dataset is provided without calibration information for the surface sound velocity or instrumentation itself and should be used with due caution.</p> <p><strong>Dataset contents</strong></p> <ul> <li>lineYYYYDDmonHHMMSS.xse, data file, proprietary format</li> <li>location.hydrostar, ancillary file, ASCII</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This raw multibeam bathymetry dataset is made available the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Hydrogen sulfide release via the ACE inhibitor Zofenopril prevents intimal hyperplasia in human vein segments and in a mouse model of carotid artery stenosis
<p>The current strategies to reduce intimal hyperplasia (IH) principally rely on local drug delivery, in endovascular approach. The oral angiotensin converting enzyme inhibitor (ACEi) Zofenopril has additional effects compared to other non-sulfyhydrated ACEi to prevent intimal hyperplasia and restenosis. Given the number of patients treated with ACEi worldwide, these findings call for further prospective clinical trials to test the benefits of sulfhydrated ACEi over classic ACEi for the prevention of restenosis in hypertensive patients.</p> <p>Abstract</p> <p>Objectives</p> <p>Hypertension is a major risk factor for intimal hyperplasia (IH) and restenosis following vascular and endovascular interventions. Pre-clinical studies suggest that hydrogen sulfide (H2S), an endogenous gasotransmitter, limits restenosis. While there is no clinically available pure H2S releasing compound, the sulfhydryl-containing angiotensin-converting enzyme inhibitor Zofenopril is a source of H2S. Here, we hypothesized that Zofenopril, due to H2S release, would be superior to other non-sulfhydryl containing angiotensin converting enzyme inhibitor (ACEi), in reducing intimal hyperplasia in the context of hypertension.</p> <p>Materials</p> <p>Spontaneously hypertensive male Cx40 deleted mice (Cx40-/-) or WT littermates were randomly treated with Enalapril 20 mg (Mepha Pharma) or Zofenopril 30 mg (Mylan SA). Discarded human vein segments and primary human smooth muscle cells (SMC) were treated with the active compound Enalaprilat or Zofenoprilat.</p> <p>Methods</p> <p>IH was evaluated in mice 28 days after focal carotid artery stenosis surgery and in human vein segments cultured for 7 days ex vivo. Human primary smooth muscle cell (SMC) proliferation and migration were studied in vitro.</p> <p>Results</p> <p>Compared to control animals (intima/media thickness=2.3±0.33), Enalapril reduced IH in Cx40-/- hypertensive mice by 30% (1.7±0.35; p=0.037), while Zofenopril abrogated IH (0.4±0.16; p<.0015 vs. Ctrl and p>0.99 vs. sham-operated Cx40-/-mice). In WT normotensive mice, enalapril had no effect (0.9665±0.2 in control vs 1.140±0.27; p>.99), while Zofenopril also abrogated IH (0.1623±0.07, p<.008 vs. Ctrl and p>0.99 vs. sham-operated WT mice). Zofenoprilat, but not Enalaprilat, also prevented intimal hyperplasia in human veins segments ex vivo. The effect of Zofenopril on carotid and SMC correlated with reduced SMC proliferation and migration. Zofenoprilat inhibited the MAPK and mTOR pathways in SMC and human vein segments.</p> <p>Conclusion</p> <p>Zofenopril provides extra beneficial effects compared to non-sulfhydryl ACEi to reduce SMC proliferation and restenosis, even in normotensive animals. These findings may hold broad clinical implications for patients suffering from vascular occlusive diseases and hypertension.</p>
Solar Wind properties measured with instruments on the Advanced Composition Explorer (ACE)
<p>Combined ACE/SWEPAM, ACE/Mag, and ACE/SWICS data set<br> ACE/MAG and ACE/SWEPAM data are taken from the ACE Science center (https://izw1.caltech.edu/ACE/ASC/) and binned to the 12-minute time resolution of SWICS.<br> The SWICS data is based on the PHA data and analyzed as described in Berger (2008).<br> This data set is used in the following two publications:<br> Teichmann, S. Heidrich-Meisner, V, Berger, L, Wimmer-Schweingruber, R.F. (2023, submitted), "Influence of solar wind parameters on unsupervised solar wind classification with k-means" source code available: 10.5281/zenodo.7695074<br> Hecht, M, Heidrich-Meisner, V, Berger, L, Wimmer-Schweingruber, R.F. 2023 (in preparation) "Scope and limitations of ad-hoc neural network reconstructions of solar wind parameters", source code available: 10.5281/zenodo.7681047.</p> <p>Contact: Verena Heidrich-Meisner, CAU Kiel heidrich@physik.uni-kiel.de</p> <p>We thank the science teams of ACE/SWEPAM, ACE/MAG as well as<br> ACE/SWICS for developing, maintaining and calibrating the instruments and for providing the respective level 2 and level 1 data products.<br> This work was supported by the Deutsches Zentrum für Luft- und Raumfahrt (DLR) as SOHO/CELIAS 50 OC 2104.</p> <p>Data products description:<br> year: year of observation (int)<br> time: day of year in current year as float<br> yeartime: time in years as float (UTC)<br> vsw: solar wind proton speed in km/s, measured by ACE/SWEPAM (level 2 from ACE Science Center) and rebinned to 12 minute time resolution<br> dsw: solar wind proton density in cm^{-3}, measured by ACE/SWEPAM (level 2 from ACE Science Center)and rebinned to 12 minute time resolution<br> tsw: solar wind proton temperature in K, measured by ACE/SWEPAM (level 2 from ACE Science Center) and rebinned to 12 minute time resolution<br> B: magnetic feld strength in nT, measured by ACE/MAG (level 2 from ACE Science Center)<br> colage: proton-proton collisional age computed as 6.4* 1e8 * dsw /(vsw* tsw**(3/2)) in K^{3/2} s^2 cm^3 km^{-1}<br> dO7_6: ratio of the O7+ to O6+ charge state densities, measured by ACE/SWICS, derived directly from PHA (pulse height analysis) data<br> eO7_6: estimate of the relative error of dO7_6 based on the counting statistics<br> ldO7_6: decadic logarithm of dO7_6<br> elO7_6: estimate of the relative error of the decadic logarithm dO7_6 based on the counting statistics<br> mcsFe: mean charge state of Fe, based on SWICS PHA of Fe8+, Fe9+, Fe10+, Fe11+, and Fe12+ in units of the elementary charge e. At least 10 counts distributed over Fe8+, Fe9+, Fe10+, Fe11+ and Fe12+ are required<br> emcsFe: estimate of the relative error of dO7_the mean Fe charge state in e (assumes 10% relative error for each Fe charge state)<br> cor_hole: coronal hole wind category in the categorization of Xu&Borovsky (2015) The ejecta category is disregarded, see for example Heidrich-Meisner (2020). Entries are 0 or 1, 1 of the data point is assigned to this type.<br> sec_rev: sector reversal plasma wind category in the categorization of Xu&Borovsky (2015) The ejecta category is disregarded, see for example Heidrich-Meisner (2020). Entries are 0 or 1, 1 of the data point is assigned to this type.<br> stream_belt: streamer belt wind category in the categorization of Xu&Borovsky (2015) The ejecta category is disregarded, see for example Heidrich-Meisner (2020). Entries are 0 or 1, 1 of the data point is assigned to this type.<br> ICME: interplanatery coronal mass ejections time periods (with a six hour safety margin before and after each ICME) from the Jian (2006,2011) and Richardson & Cane (2014, 2018) ICME lists. Entries are 0 or 1, 1 of the data point is assigned to this type.<br> totalCountsFe: number of counts in ACE/SWICS distributed over Fe8+-Fe12+<br> The data set is restricted to data points where valid data points are available for all listed data products. Only for the mean charge state of Fe invalid data points are indicated with nan (not a number)</p> <p>References:<br> Berger, L. 2008, PhD thesis, Kiel, Christian-Albrechts-Universität, Diss., 2008<br> Gloeckler, G., Cain, J., Ipavich, F., et al. 1998, in The Advanced Composition Explorer Mission (Springer), 497–539<br> McComas, D., Bame, S., Barker, P., et al. 1998b, in The Advanced Composition Explorer Mission (Springer), 563–612<br> Smith, C. W., L’Heureux, J., Ness, N. F., et al. 1998, in The Advanced Composition Explorer Mission (Springer), 613–632</p> <p>Xu, F. & Borovsky, J. E. 2015, Journal of Geophysical Research: Space Physics, 120, 70<br> Heidrich-Meisner, V., Berger, L., & Wimmer-Schweingruber, R. F. 2020, Astronomy & Astrophysics, 636, A103<br> Jian, L., Russell, C., & Luhmann, J. 2011, Solar Physics, 274, 321<br> Jian, L., Russell, C., Luhmann, J., & Skoug, R. 2006, Solar Physics, 239, 393<br> Richardson, I. G. 2004, Space Science Reviews, 111, 267<br> Richardson, I. G. 2018, Living reviews in solar physics, 15, 1</p> <p>Teichmann, S. Heidrich-Meisner, V, Berger, L, Wimmer-Schweingruber, R.F. (2023), "Influence of solar wind parameters on unsupervised solar wind classification with k-means" source code available: 10.5281/zenodo.7695074<br> Hecht, M, Heidrich-Meisner, V, Berger, L, Wimmer-Schweingruber, R.F. 2023 (in preparation) "Scope and limitations of ad-hoc neural network reconstructions of solar wind parameters", source code available: 10.5281/zenodo.7681047.</p> <p>year/1 time/day of year yeartime/UTC vsw/km/s dsw/cm^{-3} tsw/K B/nT colage/(K^{3/2} s^2 cm^3 km^{-1}) dO7_6/1 eO7_6/1 ldO7_6/1 elO7_6/1 mcsFe/e emcsFe/e cor_hole/bool sec_rev/bool stream_belt/bool ICME/bool totalCountsFe/1</p>
Raw meteorological dataset from the Southern Ocean collected on board the Antarctic Circumnavigation Expedition (ACE) during the austral summer of 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>A Vaisala MAWS240 meteorological station was installed on the R/V Akademik Tryoshnikov during a circumnavigation of Antarctica in the austral summer season of 2016/2017. This dataset contains the raw text files of meteorology data collected in the Southern Ocean and Atlantic Ocean as part of the Antarctic Circumnavigation Expedition (ACE). Data coverage is from 17th November 2016 until 11th April 2016.</p> <p>Data files have undergone no processing or quality-checking and are as-recorded, directly from the instrumentation.</p> <p>Wind speed and direction parameters were recorded with a resolution of three seconds. Air temperature, relative humidity, dew point, solar radiation, ultraviolet radiation, cloud level and sky cover were recorded with a resolution of 30 seconds.</p> <p>Time of the measurement should be used with the TIMEDIFF to convert it to UTC. Latitude and longitude recorded are not corrected. Underway seawater measurements were recorded as null values.</p> <p><strong>Dataset contents</strong></p> <ul> <li>MAWS__SMSAWS__YYYYMMDD.txt, data file, ASCII tab-separated</li> <li>data_file_header, metadata, text format</li> <li>README.txt, metadata, text format</li> <li>ace_raw_meteorology_data_change_log.txt, metadata, text format</li> </ul> <p>Data files contain data for one day and are named by that date.</p> <p>Null values are recorded as ///, // or /</p> <p><strong>Change log</strong></p> <p><strong>v1.1</strong> - Added additional data files with coverage from 2016-11-17 - 2016-11-22 inclusive. Updated README.txt with information about data coverage. Added this change_log file.</p> <p><strong>v1.0</strong> - Initial release of raw meteorological data.</p> <p><strong>Dataset license</strong></p> <p>This raw meteorological dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Five-minute average cruise track and ship velocity of the Antarctic Circumnavigation Expedition (ACE) undertaken during the austral summer of 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>The ship's cruise track, velocity, course over ground and heading at one-minute resolution for all five legs of the Antarctic Circumnavigation Expedition (ACE) are derived from a combination of:<br> - the latitude/longitude record of the Quality-checked, one-second cruise track for 21.12.2016 to 11.04.2017.<br> - the latitude/longitude record of the Uncorrected inertial navigation dataset (one-second resolution) for 27.11.2016 to 21.12.2016<br> - the latitude/longitude record of the raw meteorological data (30-second resolution) from 17.11.2016 to 27.11.2016<br> - where no latitude/longitude record at one-second resolution is available and the ship's velocity was above 2 meters per second, the three-second resolution record of the true and relative wind speed and direction, as well as the heading are used to re-calculate the ship's velocity under the assumption that the course of the ship equalled the heading.</p> <p>Basic filtering are applied to remove erroneous observations before the data are averaged to a one-minute resolution (DOI: 10.5281/zenodo.3752667).<br> The one-minute time series are averaged to five-minute resolution, whereby the vector averaging is used for the platform velocity and orientation.<br> For the latitude and longitude coordinates a simple average is calcualted, i.e., ignoring the curvature of the Earth.<br> Short stretches of missing coordinates are filled with linear interpolation between neighbouring observations.</p> <p><strong>Dataset contents</strong></p> <ul> <li>cruise-track-5min-legs0-4.csv, data file, comma-separated values</li> <li>data_file_header, metadata, text format</li> <li>README.txt, metadata, text format</li> <li>ace-cruise-track-5min-legs0-4-change-log.txt, metadata, text format</li> </ul> <p><strong>Change log</strong></p> <p><strong>v1.1</strong> - Added additional data coverage from 2016-11-17 - 2016-11-22 inclusive. Updated README.txt with information about data coverage. Added this change_log file.</p> <p><strong>v1.0</strong> - Initial release of averaged cruise track data set.</p> <p><strong>Dataset license</strong></p> <p>This five-minute averaged cruise track and velocity dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Example inference dataset for the Ai2 Climate Emulator (ACE)
<h1>Dataset for Ai2 Climate Emulator</h1> <p> </p> <div>This dataset contains a minimal example set of files and configuration to use for inference with the Ai2 Climate Emulator (ACE). Please see https://github.com/ai2cm/ace to install the necessary software. The included checkpoint is the same ace checkpoint as referenced in (https://zenodo.org/records/10791087). See README.md for a description of the included files.<br><br>v1.1: The initial condition zarr stores were erroneously missing all values in the first upload. These files have been fixed in this update. </div> <div> </div>
Dataset for "A general purpose potential for glassy and crystalline phases of Cu-Zr alloys based on the ACE formalism"
<p>This dataset was used to fit a general purpose machine learning interatomic potential for the Cu-Zr system. It supports the paper "A general purpose potential for glassy and crystalline phases of Cu-Zr alloys based on the ACE formalism".</p>
Phytoplankton pigment concentrations of seawater sampled during the Antarctic Circumnavigation Expedition (ACE) during the Austral Summer of 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>This dataset contains phytoplankton pigment concentrations sampled during the Antarctic Circumnavigation Expedition (ACE) Leg 1-3 and analysed using high performance liquid chromatography. Water samples were collected from the underway seawater supply every 3 hours and at multiple depths from select CTD (conductivity, temperature and depth) rosette deployments. Pigment concentrations have been quality controlled. This circumpolar dataset contains the main pigment concentrations of phytoplankton and can be used to infer phytoplankton biomass and class composition.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ace_phytoplankton_pigments_20200511CURRSGCMR.csv, data file, comma-separated values</li> <li>ace_phytoplankton_pigments_lod.csv, metadata, comma-separated values</li> <li>ace_phytoplankton_pigment_concentrations_change_log.txt, metadata, text</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p>Pigment concentration values below the limit of detection are reported with fill value ‘NaN’. Any null values are reported with fill value ‘NaN’.</p> <p><strong>Change log</strong></p> <p><strong>v1.1</strong><br> - Added statement to ReadMe in original data collection statement acknowledging analysis performed by Celine Dimier<br> - Added statement to Acknowledgements section of DOI acknowledging analysis performed by Celine Dimier<br> - Metadata for samples have been updated: AT/ACE/2/1/28/1026/DA/13 A_C07N17 and AT/ACE/1/1/14/402/DA/10<br> - Corrected ship name to R/V Akademik Tryoshnikov<br> - Corrected citation DOI for one minute cruise track</p> <p><strong>v1.0 </strong><br> - Initial release of phytoplankton pigment concentration dataset.</p>
Dissolved inorganic nitrate, nitrite, silicate and phosphate concentrations of seawater sampled during the Antarctic Circumnavigation Expedition (ACE) during the Austral Summer of 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>This dataset contains dissolved inorganic nitrate, nitrite, silicate and phosphate concentrations of seawater sampled during the Antarctic Circumnavigation Expedition (ACE) Legs 1-3. Water samples were collected from the underway seawater supply every 3 hours, preserved and analysed for dissolved inorganic nutrient concentrations using flow injection and colorimetric methods. These samples provide an estimate of the dissolved concentrations of inorganic macronutrients essential for phytoplankton growth.</p> <p><strong>Dataset contents</strong></p> <ul> <li>README.txt, metadata, text</li> <li>data_file_header.txt, metadata, text</li> <li>ace_uw_nutrients_20200527CURRSGCMR.csv, data file, comma-separated values</li> <li>change_log.txt, metadata, text</li> </ul> <p><strong>Change log</strong></p> <p>v1.1 - changed order of authors in publication and citation in README</p> <p>v1.0 - initial release of dataset</p>
Seawater temperature profiles from Expendable Bathythermograph (XBT) probe deployments during the Antarctic Circumnavigation Expedition (ACE)
<p><strong>Dataset abstract</strong></p> <p>This data set contains vertical seawater temperature profiles measured by Expendable Bathythermograph (XBT) probes that were deployed in the Southern Ocean during the Antarctic Circumnavigation Expedition (ACE) on board the R/V Akademik Tryoshnikov. 40 XBT probes were deployed during legs 2 and 3 of the expedition in the period 25th January, 2017 to 17th March, 2017. The XBT probes are manufactured and distributed by T.S.K./Sippican Tsurumi-Seiki Co. Ltd., Yokohama, Japan (http://www.tsk-jp.com) and are of the type T-07, which is rated at a ship speed of up to 15 knots. These probes have a measuring time of 123 seconds and maximum measurement depth of about 789 m. Probes were launched from a handheld device from the stern of the ship either on the port or starboard side while the ship was moving. The deck unit recorded the temperature and the time since the probe was launched. This time was then converted to depth using the known fall rate of the probe in seawater and the coefficients provided by the manufacturer (WMO standards; Hanawa et al., 1995). The profiles were corrected for known surface biases (Kizu and Hanawa, 2002; Uehara et al., 2008). We provide the raw data, the data produced by using the coefficients provided by the manufacturer, and a corrected version in which we apply an empirical correction based on a comparison with CTD data (Henry et al., 2019), where XBT profiles were launched alongside the CTD deployment. The data has been quality controlled by comparing it to a number of CTD profiles. Data is provided at full vertical resolution and a 1-m averaged resolution. In addition, we provide derived variables such as surface mixed layer depth (temperature threshold) estimates. We are grateful to the crew of the R/V Akademik Tryoshnikov and AARI for donating these probes to our project. Their use-by date had expired, however this was not seen as an issue. This data set provides insights into the hydrography of the Southern Ocean during one austral summer season and complements the CTD temperature profiles measured during ACE by filling in the gaps between CTD stations.</p> <p><strong>Dataset contents</strong></p> <p>Data:</p> <ul> <li>ace_xbt_raw/ace_xbt_YYYYMMDD_xxxx_uuuuuuuuuuuu.RAW, data file, comma-separated values</li> <li>ace_xbt_wmo_hanawa95_fullres/ace_xbt_YYYYMMDD_xxxx_uuuuuuuuuuuu.XBT, data file, comma-separated values</li> <li>ace_xbt_wmo_hanawa95_1m/ace_xbt_YYYYMMDD_xxxx_uuuuuuuuuuuu_1m.XBT, data file, comma-separated values</li> <li>ace_xbt_corrected_fullres/ace_xbt_YYYYMMDD_xxxx_uuuuuuuuuuuu.XBT, data file, comma-separated values</li> <li>ace_xbt_corrected_1m/ace_xbt_YYYYMMDD_xxxx_uuuuuuuuuuuu_1m.XBT, data file, comma-separated values</li> </ul> <p>Auxiliary data:</p> <ul> <li>ace_xbt_mld_tavg.csv, data file, comma-separated values</li> <li>ace_merged_ctd_xbt_mld_tsavg.csv, data file, comma-separated values</li> </ul> <p>Figures:</p> <ul> <li>figure1.pdf, metadata, portable document format</li> <li>ace_xbt_figures/ace_xbt_YYYYMMDD_xxxx_1m.pdf, metadata, portable document format</li> </ul> <p>Metadata:</p> <ul> <li>ace_xbt_deployment_summary.csv, metadata, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This seawater temperature profile dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Particulate methylsulfonic acid (MSA), sodium and chloride concentrations from high-volume air filter samples over the Southern Ocean during austral summer of 2016/2017 on board the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>Aerosol particles come from a variety of sources: a look at the chemical composition gives insights on the particle origin. Ion chromatography was performed for aerosol particles smaller than 10 micrometers (PM10 inlet), giving concentrations of sodium and chloride, as well as particulate methylsulfonic acid (MSA). For this, aerosol particles where sampled on quartz fibre filters for 24 hours each. The sampled filters were stored at -20 degrees C on the research vessel, transported frozen back to the chemistry lab of TROPOS and analysed for main ions. Temporal coverage is from December 20, 2016 to March 20, 2017. We give 24-hour quality controlled particulate MSA, sodium and chloride concentrations in microgram per cubic meter for the Antarctic Circumnavigation Expedition (ACE) cruise over the Southern Ocean, as part of the ACE-SPACE project.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ACESPACE_ particulate_MSA_Sodium_Chloride_PM10, data file, comma-separated values</li> <li>data_file_header, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul>
Mean age of air anomaly derived from ACE-FTS N2O
<p>The deseasonalized mean age of air (AoA) anomaly is derived using N2O observations from ACE-FTS and simulations of N2O and AoA from CLaMS. Results are provided as a monthly zonal mean in 10 degree latitude bins and on 19 pressure levels ranging from 100 hPa to 3.162 hPa. Four different versions of the AoA are provided, each using CLaMS simulations that were forced with a different reanalysis (ERA5, MERRA-2, JRA-55, ERA-Interim). AoA based on ERA5 is available from 2004/2 to 2021/12. AoA based on the other reanalyses is available from 2004/2 to 2017/12.</p>
ACE gene haplotypes and social networks: Using a biocultural framework to investigate blood pressure variation in African Americans
<p>This dataset contains all processed data used in analyses reported in the manuscript, ACE gene haplotypes and social networks: Using a biocultural framework to investigate blood pressure variation in African Americans. This project is part of a larger study focused on investigating the role of stress, discrimination, genetic variants, and other sociocultural factors in hypertension in African Americans.</p> <p> </p> <p> </p> <p>Variable Names and Descriptions:</p> <p>HHID: Participant Identification number</p> <p>sbp-10: Average of two Systolic Blood Pressure readings without 10 point correction for blood pressure medication (mmHg)</p> <p>sbp: Average of two Systolic Blood Pressure readings with 10 point correction for blood pressure medication (mmHg)</p> <p>dbp-5: Average of two Diastolic Blood Pressure readings without 5 point correction for blood pressure medication (mmHg)</p> <p>dbp: Average of two Diastolic Blood Pressure readings with 5 point correction for blood pressure medication (mmHg)</p> <p>ACE.Genotype: ACE genotype (0= Deletion/Deletion, 1= Insertion/Deletion, 2= Insertion/Insertion)</p> <p>WNK1.Genotype: WNK1 Genotype (0= Deletion/Deletion, 1= Insertion/Deletion, 2= Insertion/Insertion)</p> <p>age: age (years)</p> <p>sex: sex (Male =1, Female = 2)</p> <p>bpmedtake: Whether the participant uses blood pressure medication</p> <p>bmi: Body Mass Index (calculated from height and weight)</p> <p>ALTER GENDER|Answer:Male|Value:0|Count: Number of male alters (social network members)</p> <p>Alter Gender Male: Percentage of alters that are male</p> <p>ALTER GENDER|Answer:Female|Value:1|Count: Number of female alters (social network members)</p> <p>Alter Gender Female: Percentage of alters that are female</p> <p>Closeness_Mean: Average closeness centrality of the network</p> <p>Between_Mean: Average between-ness centrality of the network</p> <p>percentage of family in structural percentage: Percentage of central network positions occupied by family members</p> <p>relationship max close family: The most close (centrally) network member is a family member</p> <p>Average distance: Average distance of individuals in a network</p> <p>Hap B: ACE gene haplotypes</p> <p> </p>
Quality-checked, one-second cruise track of the Antarctic Circumnavigation Expedition (ACE) undertaken during the austral summer of 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>The Antarctic Circumnavigation Expedition (ACE), undertaken in the austral summer of 2016/2017 recorded the cruise track using two independent geo-location instruments: one using GLobal NAvigation Satellite Systems (GLONASS; hereafter referred to as GLONASS) and another primarily using the Global Positioning System (GPS; hereafter referred to as the Trimble GPS). Daily log files were recorded in real-time from both instruments during the expedition and added to MySQL database tables. Following the expedition, quality-checking work has been undertaken to provide a one-second resolution set of positions for the cruise track, which is presented here.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ace_cruise_track_1sec_YYYY-MM.csv, data file, comma-separated values</li> <li>ace_cruise_track_trimble_example_deviation_2016-12-24.png, metadata, portable network graphics</li> <li>README.txt, metadata, text file</li> <li>data_file_header.txt, metadata, text file</li> </ul> <p><strong>Dataset license</strong></p> <p>This quality-checked cruise track dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Single-cell profiling identifies ACE+ granuloma macrophages as a non-permissive niche for intracellular bacteria during persistent Salmonella infection
<p>Macrophages mediate key antimicrobial responses against intracellular bacterial pathogens, such as <em>Salmonella enterica</em>. Yet, they can also act as a permissive niche for these pathogens to persist in infected tissues within granulomas, which are immunological structures comprised of macrophages and other immune cells. We apply single-cell transcriptomics to investigate macrophage functional diversity during persistent <em>Salmonella</em> <em>enterica</em> serovar Typhimurium (<em>S</em>Tm) infection in mice. We identify determinants of macrophage heterogeneity in infected spleens and describe populations of distinct phenotypes, functional programming, and spatial localization. Using a <em>S</em>Tm mutant with impaired ability to polarize macrophage phenotypes, we find that angiotensin converting enzyme (ACE) defines a granuloma macrophage population that is non-permissive for intracellular bacteria and their abundance anticorrelates with tissue bacterial burden. Disruption of pathogen control by neutralizing TNF is linked to preferential depletion of ACE<sup>+</sup> macrophages in infected tissues. Thus ACE<em><sup>+</sup></em> macrophages have limited capacity to serve as cellular niche for intracellular bacteria to establish persistent infection.</p>
Dataset for: Ace and ace-like genes of invasive redlegged earth mite: Copy number variation, target-site mutations, and their associations with organophosphate insensitivity
<p class="MsoNormal">This repository contains the scripts and data required to replicate the analyses in Thia et al.'s, "Evolution of an acetylcholinesterase<em> </em>gene complex and its contribution toward organophosphate insensitivity in an invasive mite pest", submitted to <em>Pest Management Science</em>.</p> <p class="MsoNormal">In this work, Thia et al. use a combination of experimental selection and pool-seq genomic analyses to understand the genetic mechanisms underpinning organophosphate insensitivity in the redlegged earth mite, <em>Halotydeus destructor</em>. There is a special emphasis on disentangling the roles of copy number variation and target-site mutations in the acetylcholinesterase genes, <em>ace,</em> and radiated <em>ace</em>-like genes<span>.</span></p> <p class="MsoNormal">There are three major analyses: (1) an F<sub>ST</sub> genome scan to identify outlier loci between alive (insensitive) and dead (sensitive) mites; (2) an analysis of <em>ace </em>copy number variation between alive and dead mites; and (3) an analysis of candidate target-site mutations in the <em>ace</em> gene.</p>
Prospective ARNI vs ACE Inhibitor Trial to DetermIne Superiority in Reducing Heart Failure Events After MI
ClinicalTrials.gov study NCT02924727. IPD Sharing: YES. Countries: 41. Publications: 9.
The Impact of an Adapted Version of the Strengthening Families Program on IPV Among Caregivers and ACEs Among Children
ClinicalTrials.gov study NCT05129501. IPD Sharing: NO. Countries: 1. Publications: 1.
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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)
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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.