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opencc-by-4.0Aug 2020View details →

Amplitude and Phase Data for VLF Transmitter Observed in Delaware

This data set includes the mixed down amplitude and phase of two VLF transmitters operated by the U. S. Navy. These are the NLK transmitter located in Jim Creek, WA (48.2 N, 121.9  W) radiating 250 kW at 24.8 kHz and the NML transmitter, located in LaMoure, ND (46.4 N, 98.3 W) radiating 500 kW at 25.2 kHz.  The observation location is in Delaware (39.3N, 75.6 W).  The time of the recordings corresponds to 12 atmospheric  lightning events that created perturbations in these signals.  The format is MATLAB version 4.

opencc-by-4.0Aug 2020View details →

Observations of near-inertial wave variability and seabed reflection

From April 2008 to October 2008, our research group carried out continuous observation of moorings in the northern slope of the South China Sea. Three moorings were deployed in the southwest slope area of Dongsha Islands. One mooring was located at a depth of about 1500 meters  and two moorings were located in shallow water area to obtain the near bottom current. The observation objective was to obtain the spatial-temporal evolution characteristics of internal waves in the continental slope of the South China Sea.

Observational data for "A New Lake Classification System based on Thermal Profiles to Better Understand the Most Dominant Lake Type on Earth"

Previously unpublished continuous water temperature data used in the study "A New Lake Classification System based on Thermal Profiles to Better Understand the Most Dominant Lake Type on Earth". Table S1 links to previously published data in other manuscripts.

Figure 2 from: Starr CK, Bhukal R, Ballah ST (2020) Observations of neotropical social wasps (Hymenoptera, Vespidae) preying on eggs and tadpoles of the frog Engystomops pustulosus (Amphibia, Leptodactylidae). Journal of Hymenoptera Research 78: 91-96. https://doi.org/10.3897/jhr.78.54409

Figure 2 Angiopolybia pallens burrowing into an Engystomops pustulosus foam nest.

Observed (S) and expected mollusk species based on sample rarefaction curves

Observed (S) and expected mollusk species based on sample rarefaction curves, with nonparametric indices, unique, and duplicate species from sites in Bahia Chamela, Mexico.

Synthetic XCO2, CO and NO2 observations for the CO2M and Sentinel-5 satellites

The SMARTCARB project was funded by the European Space Agency (ESA) to study the use of satellite measurements of auxiliary reactive trace gases for fossil fuel carbon dioxide emission estimation. In the project, synthetic satellite observations were generated from high-resolution CO2, CO and NO2 fields (1×1 km2 resolution) simulated with the COSMO-GHG model. The vertically integrated model fields, the synthetic satellite observations, and the code for generating additional satellite observations (Level-2 creator) were delivered to ESA as "data1 package". This dataset is a subset of the SMARTCARB "data1 package" that includes the vertically integrated model fields and synthetic satellite observations. The satellite observations were generated for a CO2, CO and NO2 imaging satellite with 2 km x 2 km resolution and a 250-km wide swath and a CO and NO2 imaging satellite with 7 km x 7 km resolution at nadir and a 2650 km wide swath. The instrument specifications are based on the Copernicus CO2 monitoring (CO2M) mission and the Sentinel 5 instrument, respectively. The SMARTCARB study is described in the final report of the project: <ul> <li>G. Kuhlmann, V. Clément, J. Marshall, O. Fuhrer, G. Broquet, C. Schnadt-Poberaj, A. Löscher, Y. Meijer, and D. Brunner: SMARTCARB – Use of Satellite Measurements of Auxiliary Reactive Trace Gases for Fossil Fuel CarbonDioxideEmissionEstimation,FinalreportofESAstudycontractn°4000119599/16/NL/FF/mg, <a href="https://doi.org/10.5281/zenodo.4034266">https://doi.org/10.5281/zenodo.4034266</a>, 2018.</li> </ul> Furthermore, the following publications have been published in peer-reviewed journals: <ul> <li>Brunner, D., Kuhlmann, G., Marshall, J., Clément, V., Fuhrer, O., Broquet, G., Löscher, A., and Meijer, Y.: Accounting for the vertical distribution of emissions in atmospheric CO2 simulations, Atmos. Chem. Phys., 19, 4541–4559, <a href="https://doi.org/10.5194/acp-19-4541-2019">https://doi.org/10.5194/acp-19-4541-2019</a>, 2019.</li> <li>Kuhlmann, G., Broquet, G., Marshall, J., Clément, V., Löscher, A., Meijer, Y., and Brunner, D.: Detectability of CO2 emission plumes of cities and power plants with the Copernicus Anthropogenic CO2 Monitoring (CO2M) mission, Atmos. Meas. Tech., 12, 6695–6719, <a href="https://doi.org/10.5194/amt-12-6695-2019">https://doi.org/10.5194/amt-12-6695-2019</a>, 2019.</li> <li>Kuhlmann, G., Brunner, D., Broquet, G., and Meijer, Y.: Quantifying CO2 emissions of a city with the Copernicus Anthropogenic CO2 Monitoring satellite mission, Atmos. Meas. Tech. Discuss., <a href="https://doi.org/10.5194/amt-2020-162">https://doi.org/10.5194/amt-2020-162</a>, in review, 2020.</li> </ul>

Figure 1 from: Chaplynska N, Rudnyk V, Skrypnyk L, Matkovska N (2020) Clinical observation of generalized sarcoidosis with damage of bones. Pharmacia 67(4): 193-197. https://doi.org/10.3897/pharmacia.67.e54473

Figure 1 Radiography of the thoracic organs of the patient M., born 1987, made14.06.2017.

Figure 2 from: Chaplynska N, Rudnyk V, Skrypnyk L, Matkovska N (2020) Clinical observation of generalized sarcoidosis with damage of bones. Pharmacia 67(4): 193-197. https://doi.org/10.3897/pharmacia.67.e54473

Figure 2 Fluorography of the thoracic organs of the patient M., born 1987, made 12.09.2016.

Empirical Model of Thermospheric NO cooling Based on SABER observation

This thermospheric NO cooling model is deverived from SABER observation within 100-280 km altitude. The vertical structure is derived from PCA method and the horizontal distribution is reconstruced by the consequence nonlinear regression technic.

Allen Telescope Array polarimetric observation of GNSS satellites

This dataset contains polarimetric observations of several GNSS satellites done with two antennas at Allen Telescope Array in the E1 (1575.42 MHz) frequency band. The dataset consists of power spectra and cross-spectra for the X and Y linear polarizations of each antenna. A total of 1024 FFT channels are used with an input sample rate of 24.576Msps (IQ sampling) to give a frequency resolution of 24kHz. The |X|^2, |Y|^2 and X*conjugate(Y) cross-spectra are coherently averaged in windows of 0.1 seconds. Note: only one out of every four 1024 IQ sample vectors was processed in order to reduce the CPU load during data recording, so the effective averaging of each spectrum is only 25ms. The recording was done with antennas 1h and 4g on 2020-10-24, and it includes several minutes of measurements for the Galileo satellites E01, E13, E26, E31, E33, and the GPS satellite G05. The hardware configuration was as follows: the antennas were connected to RFCB LO d, which was tuned to a frequency of 1475.42 MHz and used an output IF of 512 MHz. A USRPs N321 and a USRP N320 were connected to the IF output of the RFCB. Each of the USRPs was used to digitized both polarizations from one of the antenna. The USRPs used external 10 MHz reference and PPS coming from the observatory distribution system. LO sharing was configured between all of the USRPs channels. The dataset contains a flat .tar.xz archive with several files having names such as E01_2020-10-24T11:37:38.353705_0xx. The beginning of the filename indicates the target of the observation, then there is the UTC timestamp corresponding to the beginning of the observation, and finally a code that indicates the measurement channel. The first character of the code is either 0 or 1 to indicate antenna 1h or antenna 4g respectively. The remaining characters can be either xx or yy for the power spectra of polarizations X and Y respectively or xy for the cross-spectra of polarizations X and Y. The timestamp for the data is only approximate, because it refers to the instant at which the data collection script started. The USRPs take some 10 to 30 seconds to initialize after this. The format for the xx and yy power spectra files is raw binary in IEEE 754 32 bit floats, with every 1024 elements of the file constituting a power spectra. The format for the xy cross spectra files is raw binary in IEEE 754 32 bit floats. Each pair of floats represents the real and imaginary parts of a complex number. Every 1024 pairs of floats constitute a cross-spectra. Consecutive spectra are separated 0.1 seconds apart in both cases. More information about the dataset can be found in the blog post "<a href="https://destevez.net/2020/10/ata-polarimetry-test-with-gnss-satellites/">ATA polarimetry test with GNSS satellites</a>" by the first author.

Allen Telescope Array polarimetric observation of 3C286

This dataset contains a polarimetric interferometry observation of the quasar 3C286 done with two dishes from Allen Telescope Array on 2020-10-31. The observation was done during two hours around transit, so it has large parallactic angle coverage. Eight different frequency bands between 1 and 8 GHz were observed in turns. Scans of 100 seconds were done with a frequency change between each scan. The frequency bands observed are 1413 MHz, 1665 MHz, 2675 MHz, 4820 MHz, 6663 MHz, and 8665 MHz. A total of 30.72 MHz of spectrum divided in 256 frequency bins were observed in each band. This data set contains the same data in two formats: the raw measurements produced with GNU Radio, and the observations in UVFITS format. The raw measurements consists of power spectra and cross-spectra for the X and Y linear polarizations of each antenna, using a coherent averaging interval of 0.1 seconds. The observation was done with antennas 1h and 4g from the array, using two USRP N32x to digitize the signals, and GNU Radio to perform the digital signal processing. Both of the antennas were connected to LO d in the RF converter board, which downconverted the signals to a 512 MHz IF. The two channels of each USRP were used to digitize the two polarization channels of each antenna. The USRPs were configured to share the LO between all the channels, and were synchronized to the 10 MHz and 1PPS signals from the telescope timing distribution system. The raw measurements are not phased to the source: instrumental and geometric delays are not corrected in any way. All the raw measurements are stored in GNU Radio Metdata files with detached headers, contained in a flat .tar.xz archive. These files have names such as 3c286_2020-10-31T17:47:32.114581_cross_0. The beginning of the filename indicates the target of the observation, then there is the UTC timestamp corresponding to the beginning of the observation, and finally a code that indicates the measurement channel. Measurement channels are divided in "power" for (real-valued) PSD and "cross" for (complex-valued) cross spectra. The "power" channels are numbered 0 through 3 and correspond to |X1|^2, |Y1|^2, |X2|^2 and |Y2|^2, where Xj and Yj denote the X and Y polarizations of antenna j (here j = 1 corresponds to antenna 1h and j = 2 corresponds to antenna 4g). The "cross" channels are numbered 0 through 5 and correspond to <X1,Y1>, <X1,X2>, <X1,Y2>, <Y1,X2>, <Y1,Y2>, <X2,Y2>. Each file corresponds to one channel and one scan. The metadata detached header contains useful information, such as the precise timestamping of the samples and the observation frequency. Note that some of the files have invalid timestamps in the metadata (they are easy to distinguish because their first timestamp is zero). The timestamp in the filename is only a coarse estimate, and is typically within 1 second error of the precise timestamp in the metadata. The UVFITS files contain only the cross-spectra between different antennas (correlations XX, YY, XY and YX). The data is phased to the source, but the same number of frequency channels and integration interval is maintained. There is one UVFITS file per frequency band. More information about this observation and dataset can be found in the post "<a href="https://destevez.net/2020/11/polarimetric-observation-of-3c286-with-allen-telescope-array/">Polarimetric observation of 3C286 with Allen Telescope Array</a>" by the first author.

Figure 7 from: Li D, Hao J, Yao X, Liu Y, Peng T, Jin Z, Meng F (2020) Observations of the foraging behavior and activity patterns of the Korean wood mouse, Apodemus peninsulae, in China, using infra-red cameras. ZooKeys 992: 139-155. https://doi.org/10.3897/zookeys.992.57028

Figure 7 The activity rhythm of A. peninsulae during the study.

Figure 4 from: Li D, Hao J, Yao X, Liu Y, Peng T, Jin Z, Meng F (2020) Observations of the foraging behavior and activity patterns of the Korean wood mouse, Apodemus peninsulae, in China, using infra-red cameras. ZooKeys 992: 139-155. https://doi.org/10.3897/zookeys.992.57028

Figure 4 Proportion of feeding behaviors of A. peninsulae.

Figure 1 from: Li D, Hao J, Yao X, Liu Y, Peng T, Jin Z, Meng F (2020) Observations of the foraging behavior and activity patterns of the Korean wood mouse, Apodemus peninsulae, in China, using infra-red cameras. ZooKeys 992: 139-155. https://doi.org/10.3897/zookeys.992.57028

Figure 1 Some behaviors of A. peninsulae.a forage b feeding c alert d coexistence.

Figure 9 from: Li D, Hao J, Yao X, Liu Y, Peng T, Jin Z, Meng F (2020) Observations of the foraging behavior and activity patterns of the Korean wood mouse, Apodemus peninsulae, in China, using infra-red cameras. ZooKeys 992: 139-155. https://doi.org/10.3897/zookeys.992.57028

Figure 9 Interactions between illumination and feeding behavior of A. peninsulae.

Figure 3 from: Li D, Hao J, Yao X, Liu Y, Peng T, Jin Z, Meng F (2020) Observations of the foraging behavior and activity patterns of the Korean wood mouse, Apodemus peninsulae, in China, using infra-red cameras. ZooKeys 992: 139-155. https://doi.org/10.3897/zookeys.992.57028

Figure 3 Proportion of motor behaviors of A. peninsulae.

Figure 6 from: Li D, Hao J, Yao X, Liu Y, Peng T, Jin Z, Meng F (2020) Observations of the foraging behavior and activity patterns of the Korean wood mouse, Apodemus peninsulae, in China, using infra-red cameras. ZooKeys 992: 139-155. https://doi.org/10.3897/zookeys.992.57028

Figure 6 The night activity rhythm of A. peninsulae in different months.

Figure 5 from: Li D, Hao J, Yao X, Liu Y, Peng T, Jin Z, Meng F (2020) Observations of the foraging behavior and activity patterns of the Korean wood mouse, Apodemus peninsulae, in China, using infra-red cameras. ZooKeys 992: 139-155. https://doi.org/10.3897/zookeys.992.57028

Figure 5 Proportion of sentinel behaviors of A. peninsulae.

Figure 8 from: Li D, Hao J, Yao X, Liu Y, Peng T, Jin Z, Meng F (2020) Observations of the foraging behavior and activity patterns of the Korean wood mouse, Apodemus peninsulae, in China, using infra-red cameras. ZooKeys 992: 139-155. https://doi.org/10.3897/zookeys.992.57028

Figure 8 Interactions between temperature and feeding behavior of A. peninsulae.

Figure 2 from: Li D, Hao J, Yao X, Liu Y, Peng T, Jin Z, Meng F (2020) Observations of the foraging behavior and activity patterns of the Korean wood mouse, Apodemus peninsulae, in China, using infra-red cameras. ZooKeys 992: 139-155. https://doi.org/10.3897/zookeys.992.57028

Figure 2 Proportion of three types behaviors of A. peninsulae.