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140 results for “Spy”
5G-EMIT Project: EMF measurements of 2G/3G/4G/5G frequency bands captured with a MVG EME Spy Evolution sensor in a building behind the window in LOS to one antenna in the Esch-Belval Area, Luxembourg (2023-01-19)
<p>During the 5G-EMIT project, EMF measurements of relevant mobile frequency bands have been taken at various sites around known antennas.</p> <p>Focus was in measuring the the following standard frequency bands:</p> <ul> <li>5G 700 <ul> <li>Band 28 FDD down</li> <li>758 - 803 MHz (Luxembourg: 758 - 788 MHz)</li> </ul> </li> <li>LTE 800 <ul> <li>Band 20 FDD down<br> 791 - 821 MHz</li> </ul> </li> <li>GSM 900 <ul> <li>Band 8 FDD down</li> <li>925 - 960 MHz</li> </ul> </li> <li>GSM/LTE 1800 <ul> <li>Band 3 FDD down</li> <li>1805 - 1880 MHz</li> </ul> </li> <li>UMTS 2100 <ul> <li>Band 1 FDD down</li> <li>2110 - 2170 MHz</li> </ul> </li> <li>LTE 2600 <ul> <li>Band 38 TDD</li> <li>2570 - 2620 MHz</li> </ul> </li> <li>LTE 2600 <ul> <li>Band 7 FDD down</li> <li>2620 - 2690 MHz</li> </ul> </li> <li>5G 3500 <ul> <li>Band 78 TDD</li> <li>3300 - 3800 MHz (Luxembourg: 3400 - 3800 MHz)</li> </ul> </li> </ul> <p><br> Two sensor have been used: The MVG EME Spy Evolution and a sensor developed by IMEC/University of Ghent.</p> <ul> <li>The MVG Spy Evolution sensor is able to measure all of the requested frequency bands as defined by the standard.</li> <li>The IMEC/University of Ghent sensor is only able to measure the LTE 800, GSM 900, GSM/LTE 1800 bands as defined by the standard.<br> In the 5G 3500 band it is only able to measure the range of 3550-3700 MHz (3465-3785 MHz within a -5db response).</li> </ul> <p>The datasets of the ZIP file has following structure:</p> <ul> <li>measurements: <ul> <li>the files of the measurements as provided by the sensor or application</li> <li>combined file of measurements in case the measurements have been split into several parts</li> <li>potentially analysis files of the measurements </li> </ul> </li> <li>pictures: <ul> <li>pictures of the antennas</li> <li>pictures of the sensor</li> <li>pictures of the location of the sensor</li> </ul> </li> <li>Readme.txt: <ul> <li>Used time-zone in the tables</li> <li>Used units in the tables</li> <li>Calculation of the total values in the tables</li> <li>Used labels of the the frequency bands</li> <li>Used sensor (MVG EME Spy Evolution or IMEC/University of Ghent)</li> <li>Locations of the target antennas</li> <li>Potentially location of the fixed sensor</li> </ul> </li> </ul>
5G-EMIT Project: EMF measurements of 2G/3G/4G/5G frequency bands captured with a MVG EME Spy Evolution sensor in a building behind the window in LOS to one antenna in the Esch-Belval Area, Luxembourg (2022-10-19)
<p>During the 5G-EMIT project, EMF measurements of relevant mobile frequency bands have been taken at various sites around known antennas.</p> <p>Focus was in measuring the the following standard frequency bands:</p> <ul> <li>5G 700 <ul> <li>Band 28 FDD down</li> <li>758 - 803 MHz (Luxembourg: 758 - 788 MHz)</li> </ul> </li> <li>LTE 800 <ul> <li>Band 20 FDD down<br> 791 - 821 MHz</li> </ul> </li> <li>GSM 900 <ul> <li>Band 8 FDD down</li> <li>925 - 960 MHz</li> </ul> </li> <li>GSM/LTE 1800 <ul> <li>Band 3 FDD down</li> <li>1805 - 1880 MHz</li> </ul> </li> <li>UMTS 2100 <ul> <li>Band 1 FDD down</li> <li>2110 - 2170 MHz</li> </ul> </li> <li>LTE 2600 <ul> <li>Band 38 TDD</li> <li>2570 - 2620 MHz</li> </ul> </li> <li>LTE 2600 <ul> <li>Band 7 FDD down</li> <li>2620 - 2690 MHz</li> </ul> </li> <li>5G 3500 <ul> <li>Band 78 TDD</li> <li>3300 - 3800 MHz (Luxembourg: 3400 - 3800 MHz)</li> </ul> </li> </ul> <p><br> Two sensor have been used: The MVG EME Spy Evolution and a sensor developed by IMEC/University of Ghent.</p> <ul> <li>The MVG Spy Evolution sensor is able to measure all of the requested frequency bands as defined by the standard.</li> <li>The IMEC/University of Ghent sensor is only able to measure the LTE 800, GSM 900, GSM/LTE 1800 bands as defined by the standard.<br> In the 5G 3500 band it is only able to measure the range of 3550-3700 MHz (3465-3785 MHz within a -5db response).</li> </ul> <p>The datasets of the ZIP file has following structure:</p> <ul> <li>measurements: <ul> <li>the files of the measurements as provided by the sensor or application</li> <li>combined file of measurements in case the measurements have been split into several parts</li> <li>potentially analysis files of the measurements </li> </ul> </li> <li>pictures: <ul> <li>pictures of the antennas</li> <li>pictures of the sensor</li> <li>pictures of the location of the sensor</li> </ul> </li> <li>Readme.txt: <ul> <li>Used time-zone in the tables</li> <li>Used units in the tables</li> <li>Calculation of the total values in the tables</li> <li>Used labels of the the frequency bands</li> <li>Used sensor (MVG EME Spy Evolution or IMEC/University of Ghent)</li> <li>Locations of the target antennas</li> <li>Potentially location of the fixed sensor</li> </ul> </li> </ul>
5G-EMIT Project: EMF measurements of 2G/3G/4G/5G frequency bands captured with a MVG EME Spy Evolution sensor in a building behind the window in LOS to one antenna in the Esch-Belval Area, Luxembourg (2022-11-08)
<p>During the 5G-EMIT project, EMF measurements of relevant mobile frequency bands have been taken at various sites around known antennas.</p> <p>Focus was in measuring the the following standard frequency bands:</p> <ul> <li>5G 700 <ul> <li>Band 28 FDD down</li> <li>758 - 803 MHz (Luxembourg: 758 - 788 MHz)</li> </ul> </li> <li>LTE 800 <ul> <li>Band 20 FDD down<br> 791 - 821 MHz</li> </ul> </li> <li>GSM 900 <ul> <li>Band 8 FDD down</li> <li>925 - 960 MHz</li> </ul> </li> <li>GSM/LTE 1800 <ul> <li>Band 3 FDD down</li> <li>1805 - 1880 MHz</li> </ul> </li> <li>UMTS 2100 <ul> <li>Band 1 FDD down</li> <li>2110 - 2170 MHz</li> </ul> </li> <li>LTE 2600 <ul> <li>Band 38 TDD</li> <li>2570 - 2620 MHz</li> </ul> </li> <li>LTE 2600 <ul> <li>Band 7 FDD down</li> <li>2620 - 2690 MHz</li> </ul> </li> <li>5G 3500 <ul> <li>Band 78 TDD</li> <li>3300 - 3800 MHz (Luxembourg: 3400 - 3800 MHz)</li> </ul> </li> </ul> <p><br> Two sensor have been used: The MVG EME Spy Evolution and a sensor developed by IMEC/University of Ghent.</p> <ul> <li>The MVG Spy Evolution sensor is able to measure all of the requested frequency bands as defined by the standard.</li> <li>The IMEC/University of Ghent sensor is only able to measure the LTE 800, GSM 900, GSM/LTE 1800 bands as defined by the standard.<br> In the 5G 3500 band it is only able to measure the range of 3550-3700 MHz (3465-3785 MHz within a -5db response).</li> </ul> <p>The datasets of the ZIP file has following structure:</p> <ul> <li>measurements: <ul> <li>the files of the measurements as provided by the sensor or application</li> <li>combined file of measurements in case the measurements have been split into several parts</li> <li>potentially analysis files of the measurements </li> </ul> </li> <li>pictures: <ul> <li>pictures of the antennas</li> <li>pictures of the sensor</li> <li>pictures of the location of the sensor</li> </ul> </li> <li>Readme.txt: <ul> <li>Used time-zone in the tables</li> <li>Used units in the tables</li> <li>Calculation of the total values in the tables</li> <li>Used labels of the the frequency bands</li> <li>Used sensor (MVG EME Spy Evolution or IMEC/University of Ghent)</li> <li>Locations of the target antennas</li> <li>Potentially location of the fixed sensor</li> </ul> </li> </ul>
Holy Trinity Brompton Spy Drop Statue
A statue of St Francis of Assisi in the bushes at the north east corner of Holy Trinity Brompton Church, London. This statue was used by the KGB during the Cold War as a "dead letter drop" where they could hide secret materials (behind the statue). https://www.culture24.org.uk/history-and-heritage/military-history/tra14010 https://www.telegraph.co.uk/travel/destinations/europe/united-kingdom/england/london/articles/londons-coolest-espionage-locations/ 212 photos taken in November 2020 with a Sony a6000 and processed in Reality Capture. Source: Objaverse 1.0 / Sketchfab
GPR-BMP-SPI: High spatial resolution multi-scale SPI datasets over China from January 1984 to December 2020
<p>The datasets include standard precipitation index (SPI) at 1-month, 3-month, 6-month, 9-month and 12-month scales over the main terrestrial lands of China from January 1984 to December 2020. The SPI datasets were produced by blending the information from meteorological stations, and precipitation products, as well as topographical and geographical variables based on Gaussian process regression (GPR) models.</p> <p>The meteorological station data are from the China Meteorological Data Service Centre. Five precipitation products are used: (1) CHIRPS Daily: Climate Hazards Group InfraRed Precipitation With Station Data (Version 2.0 Final); (3) ERA5-Land Monthly Averaged by Hour of Day - ECMWF Climate Reanalysis; (3) FLDAS: Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System; (4) PERSIANN-CDR: Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record; (5) TerraClimate: Monthly Climate and Climatic Water Balance for Global Terrestrial Surfaces.</p> <p>The maps of the difference of the confidence intervals (the upper prediction limit minus the lower prediction limit) at a significance level of 95% are also provided to show the spatial uncertainty of every single SPI map.</p> <p>The drought events were counted during 1984-2020 at annual and seasonal scales. The variables related to the drought events are presented in “Drought_Event.zip”.</p> <p>Reference: He, Q., Wang, M., Liu, K., Li, B., & Jiang, Z. (2023). Spatiotemporal analysis of meteorological drought across China based on the high-spatial-resolution multiscale SPI generated by machine learning. <em>Weather and Climate Extremes</em>, <em>40</em>, 100567.</p> <p> </p>
INTEGRAL light curves of GRB150101B detected by SPI-ACS and IBIS/PICsIT
<p>We have analyzed archival INTEGRAL data of the SPI-ACS and IBIS/PICsIT in coincidence with GRB 150101B (GCN 17267, GCN 17276) due to the recent results from Troja et al. (2018, arXiv:1806.10624) in which they suggest that GRB 150101B is a kilonova event comparable to GW170817/GRB170817A, but at cosmological distance and without the observations of a gravitational-wave trigger. </p> <p>We confirm the independent detection by SPI-ACS and IBIS/PICsIT of a short duration (~0.012 sec) event, consistent with that reported in Troja et al.. The signal in SPI-ACS (75 keV-10 MeV) and in IBIS/PICsIT (200 keV-1.2 MeV) has a S/N of 5.1, and 4.2, respectively.</p>
DataSet Literature review on cyberlaw and Spy
<p>Merupakan data artikel cyberlaw dengan Spy</p>
DeliCS Testing Data + DL Checkpoints - SPI-TGAS-MRF+GRE
<p>This data set consists of raw MRI k-space data from 3 healthy volunteers (train_case000, test_case000, and test_case001) and 3 patients (test_case002, test_case003, and test_case004). The data were acquired on a 3T Premier MRI scanners (GE Healthcare, Waukesha, WI) with 48-channel head receiver-coils. The raw data was saved as numpy-arrays to remove any potentially identifying meta-data, and to work in the reconstruction pipeline presented in [1]. </p> <p>Each case tarball contains three files: <strong>raw_mrf.npy, gre_mrf.npy, noise.npy</strong></p> <p>SPI-TGAS-MRF (files named <strong>raw_mrf.npy</strong>):</p> <p>The acquisition consists of an initial adiabatic inversion pulse followed by a 500 TR long readout train (TI/TE/TR = 20/0.7/12ms) with varying flip angles (10 to 75 degrees) and a rotating 3D center-out spiral trajectory. 48 repeats of the TR train are used for a 6 min acquisition. Details available in [2]. The data shape is: (2000, 48, 24000) = (data along spiral readout, number of receive channels, number of spirals across 500 TR's and 48 repeats)</p> <p>GRE (files named <strong>raw_gre.npy</strong>):</p> <p>A 20 second, low resolution (6.9 mm isotropic) gradient echo (GRE) pre-scan with a large FOV of 440x440x440mm^3. The data shape is: (64, 48, 4096) = (data along readout, number of receive channels, number of phase encode lines (64x64))</p> <p>Noise estimation (files named <strong>noise.npy</strong>):</p> <p>Data from a noise scan acquired using all receive channels to calculate the noise coherence matrix. The data shape is: (48, 4096) = (number of receive channels, noise measurement points)</p> <ul> </ul> <p>Finally, <strong>checkpoints.tar.gz</strong> contains the pre-trained weights used for the deliCS network.</p> <p> </p> <p>[1] Iyer S, Schauman S, Sandino C, et al. Deep Learning Initialized Compressed Sensing (Deli-CS) in Volumetric Spatio-Temporal Subspace Reconstruction. <em>BioRxiv: </em><a href="https://www.biorxiv.org/content/10.1101/2023.03.28.534431v1">https://www.biorxiv.org/content/10.1101/2023.03.28.534431v1</a></p> <p>[2] Cao, X, Liao, C, Iyer, SS, et al. Optimized multi-axis spiral projection MR fingerprinting with subspace reconstruction for rapid whole-brain high-isotropic-resolution quantitative imaging. <em>Magn Reson Med</em>. 2022; 88: 133- 150. doi:<a href="https://doi.org/10.1002/mrm.29194">10.1002/mrm.29194</a></p>
Ring Width Index (RWI) and Standard Precipitation Index (SPI) data for Atmospheric River reconstruction
<p>These are the two datasets used for reconstructing atmospheric river activity along the U.S. west coast (under review at the Journal of Geophysical Research: Atmosphere). The first file rwi.mat contains the ring-width-index for the chronologies used to develop the second dataset (SPI_recon.nc). This file is used as the covariate to develop the AR reconstructions (with Poisson regression) and goes back to 1400 CE. </p>
A Standardized Precipitation Index (SPI) Climatology for the Continental U.S.
<p>The standardized precipitation index SPI (McKee et al. 1993) was designed to standardize precipitation timeseries across an observational record in order to compute precipitation anomalies in both time and space. The SPI is a widely used drought index that represents the number of standard deviations that observed precipitation deviates from the climatological average precipitation measured at the same location and time period. We calculated the SPI using monthly 4 kilometer resolution precipitation data from the Parameter-elevation with independent slopes model (PRISM; Daly et al. 1994) for the conterminous United States. Monthly PRISM data from 1948-2022 were aggregated to warm season (May-September) and annual (calendar year) totals. SPI anomalies were calculated for each seasonal time window relative to the 1948-2022 timeperiod.</p> <p>Each timeseries of annual precipitation totals was fit to a Gamma probability distribution based on the L-moments of the data. We computed the cumulative distribution function (CDF) associated with the observations using the parameters from the aforementioned Gamma distribution. The CDF values were then evaluated within an inverse Gaussian function with a mean of zero and a standard deviation of one to obtain the final SPI value</p> <p>Coordinate Reference System (CRS) = EPSG:4326</p> <p>McKee, T.B., N.J. Doesken and J. Kleist, 1993: The relationship of drought frequency and duration to time scale. In: Proceedings of the Eighth Conference on Applied Climatology, Anaheim, California,17–22 January 1993. Boston, American Meteorological Society, 179–184.</p> <p>Daly, C., R.P. Neilson, and D.L. Phillips. 1994. A statistical-topographic model for mapping climatological precipitation over mountainous terrain. J. Appl. Meteor., 33, 140-158.</p>
SPI-1005 for the Treatment of Meniere's Disease
ClinicalTrials.gov study NCT04677972. IPD Sharing: NO. Countries: 1. Publications: 3.
I-SPY COVID-19 TRIAL: An Adaptive Platform Trial for Critically Ill Patients
ClinicalTrials.gov study NCT04488081. IPD Sharing: YES. Countries: 1. Publications: 5.
The Effect of Concord Grape Polyphenol-soy Protein Isolate Complex (GP-SPI) on Gut Microbiota
ClinicalTrials.gov study NCT04018066. IPD Sharing: NO. Countries: 1. Publications: 1.
SPI-1005 for Prevention and Treatment of Tobramycin Induced Ototoxicity
ClinicalTrials.gov study NCT02819856. IPD Sharing: UNDECIDED. Countries: 1. Publications: 5.
SPI-1005 for the Treatment of Patients With Meniere's Disease
ClinicalTrials.gov study NCT03325790. IPD Sharing: NO. Countries: 1. Publications: 4.
Otoprotection With SPI-1005 for Prevention of Temporary Auditory Threshold Shift
ClinicalTrials.gov study NCT01444846. IPD Sharing: Not stated. Countries: 1. Publications: 10.
SPI-1005 Treatment in Severe COVID-19 Patients
ClinicalTrials.gov study NCT04483973. IPD Sharing: NO. Countries: 1. Publications: 7.
Phase 2 Study of SPI-2012 or Pegfilgrastim for the Management of Neutropenia in Participants With Breast Cancer
ClinicalTrials.gov study NCT01724866. IPD Sharing: NO. Countries: 6. Publications: 1.
Study to Evaluate SPI-1005 in Adults With Meniere's Disease
ClinicalTrials.gov study NCT02603081. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Data from: Mucus-derived glycans are inhibitory signals for <em>Salmonella</em> Typhimurium SPI-1-mediated invasion
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