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380 results for “Pressure Data”
Data from: First-principles calculations of structural, electronic, magnetic and elastic properties of Mo2FeB2 under high pressure
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Data from: Loss of biotic resistance and high propagule pressure promote invasive grass-fire cycles
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Data from: Virtual patients and sensitivity analysis of the Guyton model of blood pressure regulation: towards individualized models of whole-body physiology
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First ISCCP Regional Experiment (FIRE) Atlantic Stratocumulus Transition Experiment (ASTEX) SOFIA Le Suroit Radiation Pressure Data
The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to improve basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between the ISCCP data, GCM parameterizations, and higher space and time resolution cloud data.To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13-November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29-July 20, 1987); a second cirrus IFO in southeastern Kansas (November 13-December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1-June 28, 1992). Each mission combined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud systems.SOFIA (Surface of the Ocean, Fluxes and Interaction with the Atmosphere) is a research program carried out by French groups from the Centre de Recherches en Physique de l'Environnement (CRPE), Laboratoire l'Aerologie (LA)-Toulouse, Centre de Meteorologie Marine (CMM)-Brest, Institut Francais de Rechercher sur la Mer (IFREMER)-Brest, Service d'Aeronomie-Paris, and Laboratoire de Meteorologie Dynamique (LMD)-Palaiseau with cooperation from Centre National de Recherche Meteorologique (CNRM)-Toulouse.The scientific objective of SOFIA during ASTEX was the study of energy transfer (heat, humidity and momentum fluxes) between the sea surface and the atmospheric boundary layer at scales ranging from the local scale to the mesoscale (50 km). The general concept of the program was to develop a measurement strategy based on nested boxes in which instrumentation would be used to estimate and quantify fluxes. These instruments, from which flux estimates at different scales would be measured, were used in connection with satellite measurements to understand and, hence, to validate the satellite integration of fluxes, particularly in the presence of mesoscale oceanic andatmospheric structures responsible for spatial inhomogeneity of fluxes.This data set contains the radiation and pressure measurements collected on Le Suroit during Astex.
Collection of Anonymised Blood Pressure Data During High Risk Surgery
ClinicalTrials.gov study NCT03653624. IPD Sharing: NO. Countries: 0. Publications: 0.
Post-marketing Study to Supplement Data on Safety, Tolerability and Efficacy of Micardis® With Special Emphasis on the Control of Blood Pressure
ClinicalTrials.gov study NCT02242331. IPD Sharing: Not stated. Countries: 0. Publications: 0.
OBPM_HARMONY: Physiological Data Recording Over 24 Hours Using the Continual Optical Hilo Blood Pressure Monitor and an Ambulatory Blood Pressure Monitor
ClinicalTrials.gov study NCT07099716. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Expression data from mouse optic nerve head after elevation in intraocular pressure
GEO Series GSE40009. Mus musculus. 10 samples. Type: Expression profiling by array.
Data from Sustainability Base Characterizing Hot Water Pump Differential Pressure Spikes for ACCEPT
During the heating season in Sustainability Base, a critical alarm associated with a hot water pump circulating heating water for the radiative system which exchanges heat via a geothermal heat pump was found. After further investigation it was ascertained that many such alarms were experienced throughout the entire heating season. These alarms are triggered as a result of the excursion of the hot water differential pressure outside of a nominal operating envelope for a fixed duration. There is a control system associated with regulating the hot water pump differential pressure to a fixed operating setpoint, and there are natural variations in the system that allow the pressure to be regulated and maintained within these nominal operating bounds. However, when system changes occur such as valves opening or closing to support the distribution of hot water through PVC piping to areas of the building where heating demand is called for in response to zone temperature requirements, the pump's operating speed must change accordingly to maintain this setpoint. If the pump speed does not change quickly enough to accommodate heating demand, these alarms can result and consequentially water hammer can occur, which may lead to accelerated aging of the PVC piping infrastructure as well as fittings, elbows, etc. In the worst case scenario it could cause leaking or bursting pipes. The zip file linked contains three subdirectories and a parameter list to be used for processing using ACCEPT. Datafiles are partitioned into training, validation, and testing sub-directory structures. A text file contains all parameter identifiers associated with the cold complaint prediction scenario. Please note that the parameter list is a text file containing the following lines: DCHWSSF - South Wing water flow rate DCHWSNF - North Wing water flow rate DCHWDP - Hot Water Pump Differential Pressure DCHWP1SP - Hot Water Pump Differential Speed DCHWP1S - Hot Water Pump Status Indicator The last parameter in this list is intended only to provide indication of ground truth (pump exceedances), and is not meant to construct models in ACCEPT. Data was collected from November 03, 2014 to February 03, 2015, and the alarm threshold limits of operation are flagged above 6.0 psid and below 4.5 psid. It should be noted the normal operation for the pump includes periods when it is off, when it retains a residual static pressure (~ 1.0 psid). The static binary indicator provides this information.
VL1/VL2 MARS METEOROLOGY DATA CALIBRATED DATA PRESSURE V1.0
This data set contains the martian surface atmospheric pressure readings obtained through much of the duration of the Viking Lander 1 and 2 missions (data are included for Viking Lander 1 sols 0 - 2245 and Viking Lander 2 sols 0 - 1050). The data are derived from the ambient pressure sensor carried onboard the Landers and values are presented on a point by point basis. The sampling rate was variable throughout the mission maximum sampling rate was one measurement per second, but ranged up to 65 minutes for Lander 1 and 105 minutes for Lander 2. For further background information on the Viking Meteorology Instrument System (VMIS) and results from this experiment, see CHAMBERLAIN_ETAL1976, HESS_ETAL_1976A, HESS_ETAL_1976B, and HESS_ETAL_1977. For discussions of analyses of experiment data, see also TILLMAN_1977, HESS_ETAL_1980, and TILLMAN_1988. An earlier version of this data set is archived at the NSSDC (NSSDC ID 75-075C-07D and 75-083C-07D).
Turbulent boundary layer wall pressure flight data
Wall pressure data acquired during flight tests at three flight conditions are provided: 48k feet altitude at Mach 0.86; 32k feet at Mach 0.70; and 24k feet at Mach 0.56. Details of the flight test, sensors, and sensor locations are given in a journal article that is referenced in the supporting documents datafile.
IBEX High Energy Neutral Atom Imager (ENA-Hi) Data Release-13, Compton Getting, no Survival Probability, Antiram direction, West Ecliptic Pressure and Flux Power Law Slope Maps, Level H3 (H3), annually averaged Data
The IBEX ENA-Hi data sets are from Release 13 of all-sky map data for the first ten years, 2009-2018, in the form of ram direction Hydrogen, H, energetic neutral atom fluxes with Compton-Getting corrections for spacecraft motion and with no corrections for ENA survival probability between 1 and 100 AU. All-sky maps have been compiled for the whole 1 yr time interval. The Interstellar Boundary Explorer, IBEX, has operated in space since 2008 updating our knowledge of the outer heliosphere and its interaction with the local interstellar medium. Start-time: 2008-12-25. There are currently 14 releases of IBEX ENA-Hi and/or IBEX ENA-Lo data covering 2009-2018. The data consist of all-sky maps in Solar Ecliptic Longitude, east and west, and Latitude angles for Energetic Neutral Atom, ENA, Hydrogen fluxes from either IBEX ENA-Hi from energy band 2 through energy band 6, see the first table below, or from IBEX ENA-Lo from energy band 5 through energy band 8, see the second table below. Details of the data and enabled science from Release 13 are given in the following journal publications that describe the 1-yr data results and the IBEX-Hi and IBEX-Lo Instruments: McComas, D.J., et al. (2018), Heliosphere Responds to a Large Solar Wind Intensification: Decisive Observations from IBEX, Astrophys. J. Lett., 856(1), L10, (6 pp.), http://doi.org/10.3847/2041-8213/aab611 Funnsten, H.O., et al. (2009), The Interstellar Boundary Explorer High Energy (IBEX-Hi) Neutral Atom Imager, Space Sci. Rev., 146, 75-103, https://doi.org/10.1007/s11214-009-9504-y Fuselier, S.A., et al. (2009), The IBEX-Lo Sensor, Space Sci. Rev., 146, 117-147, https://doi.org/10.1007/s11214-009-9495-8 The IBEX ENA-Hi band/channel center energies and full width half maximum, FWHM, energy ranges are listed in a table below: +-----------------------------------------------------+ Energy Band Center Energy Energy Range ----------------------------------------------------- Channel 2 ~0.71 keV 0.52 keV to 0.95 keV Channel 3 ~1.11 keV 0.84 keV to 1.55 keV Channel 4 ~1.74 keV 1.36 keV to 2.50 keV Channel 5 ~2.73 keV 1.99 keV to 3.75 keV Channel 6 ~4.29 keV 3.13 keV to 6.00 keV +-----------------------------------------------------+ The IBEX ENA-Lo band/channel center energies are listed in a table below: +-----------------------------+ Energy Band Center Energy ----------------------------- Channel 1 0.015 keV Channel 2 0.029 keV Channel 3 0.055 keV Channel 4 0.110 keV Channel 5 0.209 keV Channel 6 0.439 keV Channel 7 0.872 keV Channel 8 1.821 keV +-----------------------------+ This particular IBEX-Hi CDF data product was constructed from the original ascii files named using the pattern hvset_noSP_antiram_cg_yearN for N=1,10, includes pixel map data from the antiram direction, with corrections, cg, for the Compton-Getting effect no corrections, nosp, for ENA survival probability between 1 AU and 100 AU, and a map compilation cadence equal to one year. In all, there are two IBEX ENA-Hi Release 13 CDF data products with one Compton-Getting correction setting, two survival probability settings, and one directional setting: ram. The table below defines how the file naming pattern is constructed for the two data products. Note that "ibex_h3_ena_hi_r13" is the file naming pattern root for these IBEX ENA-Hi CDF data products. The asterisk symbols in the last column of the table shows the line corresponding to this CDF data product within the expanded file naming pattern schema. +---------------------------------------------------------------------------------------------------+ C-G Corr. SP Corr. Dir. Acronym ENA Hi/Lo File Naming Pattern for 1 yr Skymaps --------------------------------------------------------------------------------------------------- cg nosp ram ENA Hi ibex_h3_ena_hi_r13_cg_nosp_ram_1yr cg nosp antiram ENA Hi ibex_h3_ena_hi_r13_cg_nosp_antiram_1yr *** +---------------------------------------------------------------------------------------------------+ The first column in the above table shows whether Compton-Getting, C-G, corrections have been applied to the data. C-G corrections account for how ENA measurements are affected by the the orientation of the IBEX spacecraft velocity vector relative to the arrival direction of the ENAs. * cg: Compton-Getting corrections applied * nocg: Compton-Getting corrections not applied The second column in the above table shows whether Survival Probability, SP, corrections have been applied to the data. SP corrections account for the loss of ENAs due to radiation pressure, photoionization and ionization via charge exchange with solar wind protons as they stream through the heliosphere. This correction scales the data out from IBEX at 1 AU to approximately 100 AU. In the original data this mode is denoted as Tabular. * sp: Survival Probability corrections applied *
RENU2 Ion Gauge (IG2) Sensor Pressure, High Time Resolution (H0), 1 ms Data
Rocket Experiment for Neutral Upwelling 2, RENU2, Ionization Gauge, Neutral Gas Pressure Measurements
Data set from Dellafiore F, Arrigoni C, Ghizzardi G, Baroni I, Conte G, Turrini F, Castiello G, Magon A, Pittella F, Caruso R. Development and validation of the pressure ulcer management self-efficacy scale for nurses. J Clin Nurs. 2019 Sep;28(17-18):3177-3188. doi: 10.1111/jocn.14875. Epub 2019 Apr 21. PMID: 30938908.
<p>Data set from Dellafiore F, Arrigoni C, Ghizzardi G, Baroni I, Conte G, Turrini F, Castiello G, Magon A, Pittella F, Caruso R. Development and validation of the pressure ulcer management self-efficacy scale for nurses. J Clin Nurs. 2019 Sep;28(17-18):3177-3188. doi: 10.1111/jocn.14875. Epub 2019 Apr 21. PMID: 30938908</p> <p> </p> <p>This is the abstract:</p> <p><strong>Background: </strong>Pressure ulcers (PUs) represent a current issue for healthcare delivery. Nurse self-efficacy in managing PUs could predict patients' outcome, being a proxy assessment of their overall competency to managing PUs. However, a valid and reliable scale of this task-specific self-efficacy has not yet been developed.</p> <p><strong>Objectives: </strong>To develop a valid and reliable scale to assess nurses' self-efficacy in managing PUs, that is, the pressure ulcer management self-efficacy scale for nurses (PUM-SES).</p> <p><strong>Methods: </strong>This study had a multi-method and multi-phase design, where study reporting was supported by the STROBE checklist (File S1). Phase 1 referred to the scale development, consisting in the items' generation, mainly based on themes emerged from the literature and discussed within a panel of experts. Phase 2 focused on a three-step validation process: the first step aimed to assess face and content validity of the pool of items previously generated (initial version of the PUM-SES); the second aimed to assess psychometrics properties through exploratory factorial analysis; the third step assessed construct validity through confirmative factorial analysis, while concurrent validity was evaluated describing the relationships between PUM-SES and an established general self-efficacy measurement. Reliability was assessed through the evaluation of stability and internal consistency.</p> <p><strong>Results: </strong>PUM-SES showed evidence of face and content validity, adequate construct and concurrent validity, internal consistency and stability. Specifically, PUM-SES had four domains, labelled as follows: assessment, planning, supervision and decision-making. These domains were predicted by the same second-order factor, labelled as PU management self-efficacy.</p> <p><strong>Conclusion: </strong>PUM-SES is a 10-item scale to measure nurses' self-efficacy in PU management. A standardised 0-100 scoring is suggested for computing each domain and the overall scale. PUM-SES might be used in clinical and educational research.</p> <p><strong>Relevance to clinical practice: </strong>Optimising nurses' self-efficacy in PU management might enhance clinical assessment, determining better outcomes in patients with PUs.</p> <p> </p>
TRIPOD - A Treadmill Walking Dataset with IMU, Pressure-distribution and Photoelectric Data for Gait Analysis
<p>The peer-reviewed paper associated with this dataset can be found <a href="https://doi.org/10.3390/data6090095">here</a>. Please consider citing this when<br> re-using the dataset.</p> <p>Inertial measurement units (IMUs) enable easy to operate and low-cost data recording for gait analysis. When combined with treadmill walking, a large number of steps can be collected in a controlled environment without the need of a dedicated gait analysis laboratory. In order to evaluate existing and novel IMU-based gait analysis algorithms for treadmill walking, a reference dataset that includes IMU data as well as reliable ground truth measurements for multiple participants and walking speeds is needed. This dataset contains data from of 15 healthy young adults who walked on a treadmill at three different speeds. Data was acquired using seven IMUs placed on the lower body, two different reference systems (Zebris FDMT-HQ and OptoGait) and two RGB cameras. Additionally, in order to validate an existing IMU-based gait analysis algorithm by using the dataset, an adaptable modular data analysis pipeline was built. Our results show close agreement between the Zebris and OptoGait systems (r=0.99), demonstrating the high quality of our reference data. </p>
Data_Influence of flow and pressure distribution inside a gas diffusion electrode on the performance of a flow-by CO2 electrolyzer
<p>The folder contains the processed data of figures 3, 4, 6, 7, 8, 10, S1 and S2 that appear in:</p> <p>Bert De Mot, Jonas Hereijgers, Miguel Duarte, Tom Breugelmans, Influence of flow and pressure distribution inside a gas diffusion electrode on the performance of a flow-by CO2 electrolyzer, Chemical Engineering Journal, Volume 378, 2019, 122224, ISSN 1385-8947, https://doi.org/10.1016/j.cej.2019.122224.</p>
expression data from Zbtb17 cKO mouse heart after pressure overload
GEO Series GSE50638. Mus musculus. 16 samples. Type: Expression profiling by array.
VL1/VL2 MARS METEOROLOGY DATA CALIBRATED DATA PRESSURE V1.0
This data set contains the martian surface atmospheric pressure readings obtained through much of the duration of the Viking Lander 1 and 2 missions (data are included for Viking Lander 1 sols 0 - 2245 and Viking Lander 2 sols 0 - 1050). The data are derived from the ambient pressure sensor carried onboard the Landers and values are presented on a point by point basis. The sampling rate was variable throughout the mission maximum sampling rate was one measurement per second, but ranged up to 65 minutes for Lander 1 and 105 minutes for Lander 2. For further background information on the Viking Meteorology Instrument System (VMIS) and results from this experiment, see CHAMBERLAIN_ETAL1976, HESS_ETAL_1976A, HESS_ETAL_1976B, and HESS_ETAL_1977. For discussions of analyses of experiment data, see also TILLMAN_1977, HESS_ETAL_1980, and TILLMAN_1988. An earlier version of this data set is archived at the NSSDC (NSSDC ID 75-075C-07D and 75-083C-07D).
Effects of acute exposure to moderate altitude on blood pressure and sleep breathing patterns - RAW DATA
<p>Raw data of the study "Effects of acute exposure to moderate altitude on blood pressure and sleep breathing patterns" by <strong>Torlasco Camilla</strong>, Bilo Grzegorz Marek, Giuliano Andrea, Soranna Davide, Ravaro Silvia, Oliverio Giorgio, Faini Andrea, Zambon Antonella, Lombardi Carolina, Parati Gianfranco. <em>INTERNATIONAL JOURNAL OF CARDIOLOGY</em> 2020.</p>
qPCR raw data - Effect of pressure and temperature on survivability and proliferation of microorganisms in bentonite
<p>Quantitative PCR (qPCR) raw data includes numeric source data that corresponds to the figure 2 (pressure experiment) and figure 6 (temperature experiment) in the research article “Effect of pressure and temperature on survivability and proliferation of microorganisms in bentonite”. The data demonstrates the relative quantification calculation of microbial abundance in the pressurized (10, 12 and 15 MPa)/heated ( 60, 70, 80, 90°C) samples and their respective non-template controls (con) based on total microbial biomass detection using universal primers U16SRT-F (5′-ACTCCTACGGGAGGCAGCAGT-3′) and U16SRT-R (5′ ATTACCGCGGCTGCTGGC-3′) to target all bacteria encoding the V3 region of the 16S rRNA gene. The magnitude of the relative difference in microbial abundance was calculated using the ΔΔCq calculation method, using the formula RQ = PCR effectivity <sup>(-ΔCq)</sup>. The PCR effectivity of the marker used was estimated beforehand as the mean slope of the Cq curves constructed by serial dilution of DNA templates from five internal environmental standards. The resulting Cq values were normalized by the sample weight used for DNA extraction prior to calculation. Using the ΔΔCq calculation method, we then related the Cq value of each sample to the mean Cq value of zero-point samples for each treatment. Each sample was run in duplicate, with the resulting differences between duplicate Cq values always below 0.5 (values of 0.5 represent a maximum 1.5-fold change in relative quantity in the duplicate sample). Mean values of duplicate samples, together with their standard deviation, are shown for each sample type and sampling time for data visualization. The raw data also includes values for additional control samples and primer efficiency calculation.</p>
ScienceDex guides
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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.