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33 results for “observation operator”
Very high rate GPS observables from UCOE, UJUR, TNGF and OXUM continously operating stations, 17-19 Feb 2020. Dataset for the study "Assesment of Morelian meteoroid impact on Mexican environment" Part 3
<p>Archived data is Trimble raw T02 format from Trimble NetR9 receivers. Complete metadata for the stations can be obtained at the TLALOCNet archive at http://tlalocnet.udg.mx.</p> <p>This dataset includes high rate (5 and 50hz) versions of the UCOE, UJUR, TNGF and OXUM continous GPS station observables that is otherwise available as a 15 sec recording on the TLALOCNet archive (http://tlalocnet.udg.mx).</p> <p>Any use of this dataset or parts of it must give the proper acknowledgement , including the Zenodo assigned DOI as follows:</p> <p>This material is based on GPS data provided by the Trans-boundary, Land and Atmosphere Long-term Observational and Collaborative Network (TLALOCNet; Cabral-Cano et al., 2018) jointly operated by Servicio de Geodesia Satelital (SGS) at the Instituto de Geofísica-Universidad Nacional Autónoma de México in collaboration with and the GAGE facility operated by UNAVCO Inc. We gratefully acknowledge Armando Carrillo-Vargas and all the personnel from SGS and UNAVCO Inc. for station maintenance, data acquisition, IT support and data curation and distribution. TLALOCNet and related GPS operations at SGS are supported by the Consejo Nacional de Ciencia y Tecnología (CONACyT) projects 253760, 256012 and 2017-01-5955, UNAM-Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica (PAPIIT) projects IN104213, IN111509, IN109315-3, IN104818-3, NSF grant 2025104 and supplemental support from UNAM-Instituto de Geofísica. UNAVCO's initial support for TLALOCNet (now part of NOTA) was performed under EAR-1338091 and is currently supported by the National Science Foundation and the National Aeronautics and Space Adminsitration under NSF Cooperative Agreement EAR-1724794. </p>
Very high rate GPS observables at San Pedro Martir, Mexico (SPIG) continously operating station: dataset for the case study. Part 4.
<p>Archived data is on a Trimble raw T02 format from a Trimble NetR9 receiver. Complete metadata for the station can be obtained at the TLALOCNet archive at <strong>http://tlalocnet.udg.mx</strong>.</p> <p>This dataset is a high rate (50hz) version of the SPIG continous GPS station observables that is otherwise available as a 15 sec recording on the TLALOCNet archive (<strong>http://tlalocnet.udg.mx</strong>).</p> <p>Any use of this dataset or parts of it must give the proper acknowledgement, including the Zenodo assigned DOI (10.5281/zenodo.4002090) as follows:</p> <p>This material is partly based on GPS data provided by the SSN-Trans-boundary, Land and Atmosphere Long-term Observational and Collaborative Network (TLALOCNet; Cabral-Cano et al., 2018 and Pérez-Campos et al., 2018) jointly operated by Servicio de Geodesia Satelital (SGS) and Servicio Sismológico Nacional (SSN) at the Instituto de Geofísica-Universidad Nacional Autónoma de México in collaboration with UNAVCO, Inc. We gratefully acknowledge all the personnel from SGS, SSN and UNAVCO for station installation, maintenance, data acquisition, permanent IT support and data distribution. TLALOCNet and related GPS operations at SGS are supported by the Consejo Nacional de Ciencia y Tecnología (CONACyT) projects 253760 and 2017-01-5955, by the National Science Foundation grant EAR-1338091 and supplemental support from UNAM-Instituto de Geofísica.<br> <br> <strong>References</strong>.</p> <p>E. Cabral-Cano, X. Pérez-Campos, B. Márquez-Azúa, M. A. Sergeevaa, L. Salazar-Tlaczani, C. DeMets, D. Adams, J. Galetzka, K. Feaux, Y. L. Serra, G. S. Mattioli, and M. Miller, 2018. TLALOCNet: A Continuous GPS-Met Backbone in Mexico for Seismotectonic, and Atmospheric Research. Seismological Research Letters, v. 89, n. 2ª, p. 373-381. https://doi.org/10.1785/0220170190.</p> <p>X. Pérez‐Campos, V.H. Espíndola, J. Pérez, J. A. Estrada C. Cárdenas Monroy, D. Bello, Adriana González‐López, Daniel González Ávila, Moisés Gerardo Contreras Ruiz Esparza, Rafael Maldonado, Yi Tan, Iván Rodríguez Rasilla, Miguel Ángel Vela Rosas, José Luis Cruz, Arturo Cárdenas, Fernando Navarro Estrada, Alejandro Hurtado, Antonio de Jesús Mendoza Carvajal, Edgar Montoya‐Quintanar, Miguel A. Pérez‐Velázquez, 2018. The Mexican National Seismological Service: An Overview. Seismological Research Letters, v. 89, n. 2ª, p.318-323. https://doi.org/10.1785/0220170186.</p>
Very high rate GPS observables at Coeneo, Mexico (UCOE) continously operating station: dataset for the case study. Part 3.
<p>Archived data is on a Trimble raw T02 format from a Trimble NetR9 receiver. Complete metadata for the station can be obtained at the TLALOCNet archive at <strong>http://tlalocnet.udg.mx</strong>.</p> <p>This dataset is a high rate (50hz) version of the UCOE continous GPS station observables that is otherwise available as a 15 sec recording on the TLALOCNet archive (<strong>http://tlalocnet.udg.mx</strong>).</p> <p>Any use of this dataset or parts of it must give the proper acknowledgement, including the Zenodo assigned DOI (10.5281/zenodo.4002072) as follows:</p> <p>This material is partly based on GPS data provided by the Trans-boundary, Land and Atmosphere Long-term Observational and Collaborative Network (TLALOCNet; Cabral-Cano et al., 2018) jointly operated by Servicio de Geodesia Satelital (SGS) at the Instituto de Geofísica-Universidad Nacional Autónoma de México in collaboration with UNAVCO, Inc. We gratefully acknowledge Armando Carrillo-Vargas and all the personnel from SGS and UNAVCO at for station installation, maintenance, data acquisition, permanent IT support and data distribution. TLALOCNet and related GPS operations at SGS are supported by the Consejo Nacional de Ciencia y Tecnología (CONACyT) projects 253760 and 2017-01-5955, by the National Science Foundation grant EAR-1338091 and supplemental support from UNAM-Instituto de Geofísica.<br> <br> <strong>References</strong>.</p> <p>E. Cabral-Cano, X. Pérez-Campos, B. Márquez-Azúa, M. A. Sergeevaa, L. Salazar-Tlaczani, C. DeMets, D. Adams, J. Galetzka, K. Feaux, Y. L. Serra, G. S. Mattioli, and M. Miller, 2018. TLALOCNet: A Continuous GPS-Met Backbone in Mexico for Seismotectonic, and Atmospheric Research. Seismological Research Letters, v. 89, n. 2ª, p. 373-381. https://doi.org/10.1785/0220170190.</p>
Data from the micrometeorological tower of the Antarctic Modeling Observation System (ATMOS) project of the 40th Brazilian Antarctic Operation (OPERANTAR XL) to calculate the CO2 flux (FCO2)
<p>Micrometeorological tower data obtained by the "Antarctic Modeling Observation System" (ATMOS) project. These data were collected in the southern summer of 2021/2022 during the 40th Brazilian Antarctic Operation (OPERANTAR XL) and were used to calculate CO2 fluxes (FCO2).</p> <p>A 9 m high metal micrometeorological tower was installed on the bow of the Polar Ship Almirante Maximiano, 8.75 m above sea level, for sampling atmospheric variables. In the tower, the Motion Pack II was installed, on the main shaft of the tower, to determine the ship's movement in the orthogonal directions xp, yp and zp of the platform's coordinate system, at a frequency of 20 Hz. As well as, a GPS (Global Positioning System) and an electronic compass, to determine the ship's geographic position and speed. The movement of the ship influences wind speed measurements, and as a solution, a wind speed correction was carried out.<br>An IRGASON sensor (Campell Scientific®) was placed on the secondary shaft of the tower, configured to perform measurements at 20 Hz. The IRGASON has an open path infrared gas analyzer that measures the concentrations of CO2 and water vapor (H2O), a three-dimensional sonic anemometer, which measures the 3 vector components of the wind, and a thermohygrometer that measures air temperature and humidity. From the IRGASON collections, it is possible to calculate the CO2 flux using the Vortex Covariance method.</p>
LI-COR (LI-850) sensor data obtained by the Antarctic Modeling Observation System (ATMOS) project during the 40th Brazilian Antarctic Operation (OPERANTAR XL) and were used to calculate the partial pressure of CO2 (pCO2)
<p>LI-COR (LI 850) sensor data obtained by the "Antarctic Modeling Observation System" (ATMOS) project. These data were collected in the southern summer of 2021/2022 during the 40th Brazilian Antarctic Operation (OPERANTAR XL) and were used to calculate the partial pressure of seawater CO2 (pCO2sea)</p> <p>The LI-850 carbon dioxide analyzer was installed in the laboratory aft of H41 together with a balancer to measure the CO2 concentration of the water. The collection system occurs as follows: the ship's saltwater piping system collects seawater, when this water enters the balancer it generates turbulence. The turbulence generated causes the CO2 present in the water to come into balance with the air. The air that comes out of the balancer is pumped into the LI-850, by its internal pump, and thus, the equipment measures the concentration of CO2 present in the water. To ensure that the air inside the balancer is actually balanced with the seawater, the air leaving the LI-850 is pumped back into the balancer, closing the circuit. From these data it is possible to calculate pCO2sea.</p>
Comparative observational study of gastric content in women scheduled for caesarean section or operative hysteroscopy: The ECHOCESAR study
<p class="MsoNoSpacing"><em><span>Objective:</span></em><span> There is a large literature concerning the estimation of gastric content in third-trimester pregnant women but their conclusions remain contradictory. Our objective was to compare gastric content in pr</span><span>egnant women and in non-pregnant ones using gastric ultrasound. </span></p> <p class="MsoNormal"><em><span>Design: </span></em><span>An observational two centres study was designed.</span></p> <p class="MsoNoSpacing"><em><span>Methods:</span></em><span> The antral cross-sectional area (CSA) in the semi-recumbent position (SRP), primary outcome, and in the right lateral position (RLD) were measured in pregnant women scheduled for a caesarean section (CS group) or non-pregnant women who underwent hysteroscopy (HS group) just before surgery. Perlas' score was also evaluated.</span></p> <p class="MsoNoSpacing"><em><span>Results:</span></em><span> One hundred and twenty-six patients were analysed, 61 patients in the CS group and 65 in the HS group. Antral CSA, measured in the SRP, was greater in the CS group than in the HS group (350 mm2 [236 - 415] vs 247 mm2 [180 - 318]; (P=0.001). This difference remained significant when the analysis was adjusted for fasting duration (P<0.001) or anxiety (P=0.001) or both (P<0.001). Among secondary outcomes, Perlas scores did not differ between groups (P=0.860). Concordance between antral CSA, categorised as corresponding to an empty or full stomach, and Perlas score was very poor.</span></p> <p class="MsoNoSpacing"><em><span>Conclusions: </span></em><span>Our results bring arguments to consider that individuals among pregnant women could have a delayed gastric emptying and support performing a gastric ultrasound in term pregnant patients prior to general anaesthesia.</span></p>
Observations of shortwave downward radiation from the operational observation network of Météo-France
<p>This dataset contains the hourly surface shortwave downward radiation (SWD) from the pyranometers of the network operated by Météo-France for the year 2020. This dataset was used to evaluate AROME SWD forecasts in the manuscript "Evaluation of surface surface shortwave downward radiation forecasts by the numerical weather prediction model AROME" by Marie-Adèle Magnaldo et al., submitted to Atmospheric Chemistry and Physics.</p>
Observational Study of Intra-operative Partial Irradiation of Invasive Ductal Breast Carcinomas With a Good Prognosis
ClinicalTrials.gov study NCT04414202. IPD Sharing: NO. Countries: 1. Publications: 12.
Comparative observational study of gastric content in women scheduled for caesarean section or operative hysteroscopy: The ECHOCESAR study
Open the record for dataset details and reuse information.
Effects of nonlinear observation operators for visible and infrared radiances in ensemble data assimilation
<p><br>Description</p> <p>Dataset to accompany the first revision of the manuscript "Effects of nonlinear observation operators for visible and infrared radiances in ensemble data assimilation" for the QJRMS.</p> <p>Contains <br>- experiments (one folder per experiment)<br> each contains <br> - diagnostics (DART format) for each assimilation time<br> - obs_seq.final: assimilation output <br> - obs_seq.final-linear: contains linear posterior as "prior" ("evaluate" at +1s after analysis)<br> - obs_seq.final-evaluate: at analysis time (includes DART clamping), at 1s after analysis time: "nonlinear posterior"<br> - config file DART-WRF for each experiment (python format)</p> <p>- code<br> assim_tools_mod.f90: DART code modification to compute the linear posterior</p> <p>- other data: see v1 of this repository!<br> nature run initial conditions (WRF format)<br> forecast ensemble initial conditions (WRF format)<br> script to read "obs_seq.final"-files into pandas.DataFrame (python format)</p> <p><br>Experiment naming:<br>VIS ... visible reflectance 0.6 micrometer assimilation<br>WV73 ... infrared 7.3 micrometer assimilation<br>obs10 ... observation density: 1 observation per 10x10 km of domain area<br>obs30 ... 1 observation per 30x30 km<br>loc10 ... localization radius: 10 km<br>inf0 ... no prior nor posterior covariance inflation in the assimilation<br>sec0 ... no sampling error correction<br>reject ... not assimilating observations with a small first-guess departure <= 0.03</p> <p><br>Experiment names used in Figures</p> <p>Section 3.1<br>- Figure 2a: exp_v1.23_P2_rr+1_VIS_obsi211_loc20_inf0<br>- Figure 2b: exp_v1.23_P2_rr+1_VIS_obsi360_loc20_inf0</p> <p>Section 3.2.1 <br>- Figure 3: exp_v1.23_P2_rr+1_VIS_obs30_loc14_inf0</p> <p>Section 3.2.2<br>- Figure 4: exp_v1.23_P2_rr+1_VIS_obs10_loc20, exp_v1.23_P2_rr+1_VIS_obs10_loc20_reject</p> <p>Section 3.3<br>- Figures 5a,c: exp_v1.23_P2_rr+1_T2M_obs10_loc20_inf0_sec0<br>- Figures 5b,5d,7a: exp_v1.23_P2_rr+1_VIS_obs10_loc20_inf0_sec0<br>- Figure 6a,6b,7b: exp_v1.23_P2_rr+1_WV73_obs10_loc20_inf0_sec0</p> <p> </p>
Inverse observation operator parameters/models for master's dissertation: Updating a conceptual rainfall-runoff model based on radar observation and machine learning
<p>Both saved models and results of hyperparameter tuning are given. </p> <p>Code related to this dataset can be found <a href="http://github.com/olivierbonte/master_thesis">here</a></p> <p> </p>
Relationship Between Acute Phase Markers and Post-operative Pain in Open Tension-free Inguinal Hernia Repair: An Observational Study
ClinicalTrials.gov study NCT06380140. IPD Sharing: NO. Countries: 1. Publications: 9.
Relationship Between Acute Phase Markers and Post-operative Pain in Laparoscopic Cholecystectomy: An Observational Study
ClinicalTrials.gov study NCT06375057. IPD Sharing: NO. Countries: 1. Publications: 3.
Drug Wastage : Observational Study in the Operating Rooms of France
ClinicalTrials.gov study NCT05609864. IPD Sharing: NO. Countries: 4. Publications: 4.
International obServational sTudy on AiRway manaGement in operAting Room and Non-operaTing Room anaEsthesia
ClinicalTrials.gov study NCT05759299. IPD Sharing: Not stated. Countries: 5. Publications: 12.
Clinical Observation of V-P Shunt and Application of "Three-step Disinfection" to Reduce Post-operative Infection Rate
ClinicalTrials.gov study NCT04785248. IPD Sharing: NO. Countries: 1. Publications: 7.
Correlation of the "Preliminary Universal Surgical Invasiveness Score" (pUSIS) With Short Term Post-operative Clinical Outcome Parameters. An Observational Study
ClinicalTrials.gov study NCT04261231. IPD Sharing: NO. Countries: 1. Publications: 2.
Safety of a Powder-free Latex Allergy Protocol in the Operating Theatre: A Prospective, Observational Cohort Study
ClinicalTrials.gov study NCT02575053. IPD Sharing: Not stated. Countries: 1. Publications: 5.
An International Prospective, Observational, Multi-centre Study on the Duration of Pre-operative Liquid Fasting
ClinicalTrials.gov study NCT06527703. IPD Sharing: NO. Countries: 1. Publications: 1.
Observational Study on the Preparation of the Implant Site With Piezosurgery vs Drill: Comparison Between the Two Methods in Terms of Post-operative Pain, Surgical Times and Operational Advantages
ClinicalTrials.gov study NCT03978923. IPD Sharing: NO. Countries: 1. Publications: 1.
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