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Proxies' response times measured by clients in an emulated community network

13 virtual nodes were deployed in Planetlab testbed (https://www.planet-lab.org) to emulate a small community network with 8 clients and 5 proxies. Each client probed all proxies every 10 seconds during two days. The same file (http://ovh.net/files/1Mb.dat) was requested in all probes. A probe was considered successful if the file was completely downloaded by the client. In this case, the response time was registered by the client, considering the time elapsed from the moment the client sent the request until the last byte of the response was received. This dataset contains the proxies' response times that were measured by clients in sucessful probes.

Festival of Frequency Measurement 1 October 2019

Festival of Frequency Measurement 1 October 2019 J. Kommers KN6CYU Latitude: 34.0556 / 34° 3' 20" N Longitude: -118.443 / 118° 26' 34" W Grid: DM04sb Files starting 30 Sep 2019 at 18:42 PDT through 1 Oct 2019 at 4:18 PDT 70 ft random wire antenna, SDR Play RSPduo tuned to 4.999 MHz with diversity reception - screenshots included for configuration details

Festival of Frequency Measurement 1 October 2019

Steve VK3ZAZ Hamilton Victoria Australia QF12ag 37:30 South 142:01 East Sunset October 1 700pm local 0900 UTC Yaesu FTDX5000MP with OCXO  Delta Loop  east west oriented WWV Centennial  08:00 apprx  5.000 MHZ

Festival of Frequency Measurement dataset - WV5L 34.10 -84.46 5 MHz Oct 1 2019

Festival of Frequency Measurement Submission event: WWV Centenial UTC Date: 01 Oct 2019 (starting 30 Sep 2300z, ending 2 Oct 0100z) beacon frequency: 5 MHz station name: WV5L, operated by Vance Loen lat long: 34.10 -84.46 city: Woodstock state: Georgia US difficulties: poor propagation Oct 01 from about 1600 to 2000 UTC between Ft. Collins and Woodstock equipment: Icom IC-7610 with Leo Bodnar GPSDO, antenna 96-foot dipole with ladder line (ZS6BKW design) tuning technique: receiver was tuned to 4999.00 KHz, upper sideband, 2.1KHz bandwidth, preamp off, AGC mid, 1 KHz detected audio captured from internal sound card, calibrated and logged by FLDIGI 4.1.08. propagation path: sky wave, about 1215 miles/1955 Km

WWV Centennial Frequency Measurement

Radio is a ICOM IC 7610    fldigi version 4.0.18 grid EN16aw Stopped data collection at 23:15.  The station was needed as the operator was Net Control for the North Dakota Evening net.

Festival of Frequency Measurement Submission

The location of this measurement was La Canada, California A very stable GPS locked receiver was used.  (Icom 7610)  Test measurements of GPS locked broadcast stations on 980, 1070 and 1260 kHZ showed a system frequency error of .03 Hz high.  This .03 Hz high error existed before and after the 24 hour 5 mHz measurement.  Thus for absolute frequencies a .03 Hz must be subtracted. The antenna used was a ground mounted electrostatic shielded loop antenna. Software used was fldigi.

WWV October 1st UTC 5 MHz Frequency Measurment from Prosser, WA

station name: N7QNM grid square: DN06ce city and state: Prosser, WA 99350 equipment: Elecraft K3 Factory Calibration HyGain AV18HT (Omni Vertical) beacon frequency: 5MHz

Hourly U.S. Building Electricity Use, Cost, and Emissions Baselines to Support Time-Sensitive Analyses of Energy Efficiency and Flexibility Measures

These data underpin an analysis of the time-sensitive impacts of energy efficiency and flexibility measures in the U.S. building sector using Scout (<a href="https://scout.energy.gov">scout.energy.gov</a>), a reproducible and granular model of U.S. building energy use developed by the U.S. national labs for the U.S. Department of Energy's Building Technologies Office. The analysis applies sub-annual adjustments to U.S. baseline building energy use, cost, and emissions in order to characterize how these metrics vary across hour of the day, season, and geographic region in the U.S. building sector. These adjustments are based on daily energy load, price, and emissions shapes from various data sources and are used to re-apportion baseline energy, cost, and emissions totals from <a href="https://www.eia.gov/outlooks/aeo/data/browser/%20/%20%7b%20/%20# \ }/?id=2-AEO2018 \ { \ & \ }cases=r ef2018 \ { \ & \ }sourcekey=0">EIA's Annual Energy Outlook (AEO) Reference Case projections</a> across all hours of a year. The resulting sub-annual baselines are specified by building sector, end use, region, and season and can be used in analyses of building efficiency and flexibility measures to quantify their time-sensitive impacts at the national scale. Analyses of these data demonstrate that energy efficiency measures continue to show strong value under a time-sensitive framework while the value of flexibility depends on assumed electricity rates, measure magnitude and duration, and the amount of savings already captured by efficiency. The data uploaded below include CSV files that show hourly energy use, cost, and emissions totals for the U.S. building sector as well as by end-use, region, and season. An additional CSV includes residential and commercial price intensities (USD/quad) for all hours of the day based on different time-of-use (TOU) rate data from the U.S. Utility Rate Database (URDB). Further detail on each of these CSVs is given below: <ul> <li>'TSV_baseline_totals.csv': this file shows hourly total energy, cost, and emissions estimates for commercial and residential buildings in 2018 and 2030. It presents these estimates in Quads (source), Quads (site), and TWh (site). For the cost totals, it presents two estimates for each year and building sector, including one using the median TOU rate from the URDB and one using the average retail rate for the corresponding building sector. For converting source energy to site, total delivered electricity and electricity-related losses data for the residential and commercial sector are drawn from <a href="https://www.eia.gov/outlooks/aeo/data/browser/#/?id=2-AEO2018&sourcekey=0">AEO Summary Table A2</a>.</li> <li>'TSV_baseline_end-use.csv': this file shows hourly energy, cost, and emissions estimates for commercial and residential buildings in 2018 and 2030 broken out by building end-use. It presents totals in terms of both source and site energy as above and presents cost totals based on the median TOU rate for each building sector from the URDB.</li> <li>'TSV_baseline_region.csv': this file shows hourly energy, cost, and emissions estimates for commercial and residential space heating and cooling end uses in 2018 and 2030 for each <a href="https://www.eia.gov/consumption/residential/maps.php">American Institute of Architects (AIA) climate zone</a>. It presents totals in terms of both source and site energy as above and presents cost totals based on the median TOU rate for each building sector from the URDB.</li> <li>'TSV_baseline_region_season.csv': this file shows a similar disaggregation of the data as ‘TSV_baseline_region.csv’, but it further disaggregates results by season. The seasonal definitions are as follows: 'intermediate' (October to November; March to April), 'winter' (November to February), and 'summer' (May to September).</li> <li>'TSV_annual_price_intensities.csv': this file presents annual hourly price intensities for the commercial and residential building sectors in 2018 and 2030 based on different TOU rate data from the URDB. Three different rate structures are included for each building sector, and these are the 5th, 50th, and 95th percentile of all existing commercial and residential TOU rates in the URDB in terms of their peak to off-peak price ratio.</li> </ul>

Data and code for figures in "Two-tone optomechanical instability and its fundamental implications for backaction-evading measurements"

Here we prepare the data and process scripts to reconstruct figure 4 of the paper (Two-tone optomechanical instability and its fundamental implications for backaction-evading measurements). The folder contains several subfolders and files: “Raw data”: In this folder, you can find the raw data recorded by measurement devices during the experiment. It follows the hierarchical structure. We have three pairs of folders corresponding to three cooperativities (3.5, 7, 14). One folder of each pair contains raw data files in text format (.dat) and the other one contains plots and a Numpy dictionary of the extracted parameter for each cooperativity (superdict.npy). If you need to redo the extraction process from the raw data you can simply run “181031_CXX_Final_NOQT_BAE_2D_post_processeing.py” (XX: 3.5 or 7 or 14) python code to rewrite superdict.npy files and replot all plots in the Raw data folder. “NRBcodes”: A side package for the circle fit (Lorentzian fitting) in the complex plane. “Dicts”: A folder containing Numpy dictionaries needed for the final plot. “superdictXX.npy” are copies of Numpy dictionaries in the Raw data folder. “powers_XX.npy” and “Ds_nor_XX.npy” are Numpy dictionaries needed for the theory plots. You can reproduce them by the uncommenting first part of the “Final_plot.py” and correcting the corresponding cooperativity. “getdata.py” and “postprocessing_libs.py”: Side packages help to read the raw data files.   All post-processes are done on the raw data and you just need to run the “Final_plot.py” to reproduce the plot. If you want to access the post-processed data you can simply read “superdictXX.npy” in the Dicts folder.  Please do not hesitate to contact us in case of any questions.  amir.youssefi@epfl.ch

opencc-by-4.0May 2019View details →

Network analysis highlights increased generalisation and evenness of plant-pollinator interactions after conservation measures

DATASET used in the article entitled “Network analysis highlights increased generalisation and evenness of plant-pollinator interactions after conservation measures”. We supply weighted and binary matrices used for plant-pollinator network analyses, before and after the implementation of conservation measures. We also supply the list of plant and pollinator species recorded in this study.

opencc-by-4.0Jun 2019View details →

PsPM-SMD: SCR, EMG, ECG, and respiration measurement in response to auditory startle probes

This dataset includes skin conductance response (SCR), orbicularis oculi electromyogram (EMG), electrocardiogram (ECG) and bellows-based respiration measurements as well as sound channel recordings for each of 19 healthy unmedicated participants (6 males and 13 females aged 24.9 +/- 4.1 years, age stated in Khemka et al. 2017 was based on incomplete information) in response to 25 startle probes, as described in Khemka et al. (2017). ITI was determined randomly on each trial between 7-11 s. For 25% of the participants, SCR/ECG/respiration was not recorded. One data file contains only responses to 24 startle probes.

opencc-by-4.0Nov 2019View details →

data for "Mismeasurement of the core-shell structure of black carbon-containing ambient aerosols by SP2 measurements"

The data for "Mismeasurement of the core-shell structure of black carbon-containing ambient aerosols by SP2 measurements"

opencc-by-4.0Nov 2021View details →

Figure 5 in Assessing a ReviTec Measure to Combat Soil Degradation by studying Acari and Collembola from Ngaoundéré, Adamawa, Cameroon

Figure 5. Temporal variation of total Acari and Collembola in the ReviTec plots (ctrl1: ReviTec control; cpmy: compost + mycorrhiza; cpbcbo: compost + biochar + bokashi). Details as in Fig. 3.

opencc-by-4.0Nov 2021View details →

Figure 3 in Assessing a ReviTec Measure to Combat Soil Degradation by studying Acari and Collembola from Ngaoundéré, Adamawa, Cameroon

Figure 3. Temporal variation of total Acari and Collembola in control plots (sav: savanna; ctrl1: ReviTec control plot; tsd. ind./m2, 0–10 cm). Significant differences between 2017 sampling campains are marked by different letters.(n = 5); Asterisk: Difference to sav significant (n = 5, p <0.05). (Kruskal-Wallis test with subsequent Mann-Whitney U-test to test pairs [p ˂ 0.05]). Error bars: standard error.

opencc-by-4.0Aug 2011View details →

Text-fig. 6a. Z-score profile for Moča skull. Comparison of Moča skull measurements with LUP and recent sample, –1.96 and +1.96: 95% tolerance interval (95% of the LUP and recent variability), 0: LUP and recent sample mean, gray band: 95% confidence interval of mean z-scores. Only those samples having more than n = 5 in the particular group are included. in A Late Upper Palaeolithic Skull From Moča (The Slovak Republic) In The Context Of Central Europe

Text-fig. 6a. Z-score profile for Moča skull. Comparison of Moča skull measurements with LUP and recent sample, –1.96 and +1.96: 95% tolerance interval (95% of the LUP and recent variability), 0: LUP and recent sample mean, gray band: 95% confidence interval of mean z-scores. Only those samples having more than n = 5 in the particular group are included.

opencc-by-4.0Sep 2017View details →

Figure. Measurement data plotted for all nestlings as a function of age for the black stork: a) wing length (WL), b) head length (HL), c) bill length (BL), and d) tarsus length. in Age estimation of black stork (Ciconia nigra) nestlings from wing, bill, head, and tarsus lengths at the time of ringing

Figure. Measurement data plotted for all nestlings as a function of age for the black stork: a) wing length (WL), b) head length (HL), c) bill length (BL), and d) tarsus length.

opencc-by-4.0Apr 2020View details →

Figure 1 in The study of fidelity measures in the context of using them as a threshold criterion in the allocation of diagnostic species

Figure 1. Detection of optimal number of clusters by the Optimclass-2 approach. From left to right: the case study of the test data set 1 and 2.

opencc-by-4.0Apr 2020View details →

Figure 2 in The study of fidelity measures in the context of using them as a threshold criterion in the allocation of diagnostic species

Figure 2. Representing distributions of some fidelity measures with different degree of asymmetry with kernel density estimates. From left to right: the case study of the test data set 1 and 2.

opencc-by-4.0Jul 2024View details →

Figure 8 in Assessment of the accuracy of determining the Caspian Sea surface temperature by Landsat-5, -7 satellites based on the measurements of drifters

Figure 8. The relationship between the temperature of the sea surface layer obtained from drifters and SST according to Landsat-5, -7 Level-2 data: (a) measurements that have a time difference of no more than two hours with the flight of the satellite; (b) all measurements on the day of the satellite flyby.