Find research datasets worth reusing

opencc-by-4.0Jan 2024View details →

A new repository of electrical resistivity tomography and ground penetrating radar data from summer 2022 near Ny-Ålesund, Svalbard.

We present the geophysical data set acquired in summer 2022 close to Ny-Ålesund (Western Svalbard, Brøggerhalvøya peninsula, Norway) as part of the project ICEtoFLUX (MUR/PRA2021 project-0027). The data set is composed of Electrical Resistivity Tomography (ERT) and GroundPenetrating Radar (GPR) surveys, which are well-known geophysical techniques for the characterization of glacial and hydrological processes and features. 18 ERT profiles and 10 GPR lines were acquired, for a total surveyed length of 9.3 km. The data have been organized in a consistent repository that includes both raw and processed (filtered) data. Some representative examples of 2D models of the subsurface are provided, that is, 2D sections of electrical resistivity (from ERT) and 2D radargrams (from GPR). These examples can support the identification of the active layer and the occurrence of spatial variation of soil conditions at depth. The aim of the investigation is to characterize the role of groundwater flow in correspondence of the active layer as well as through and/or below the permafrost. The data set is of major relevance because scant attention has been paid to the publication of geophysical data from the Ny-Ålesund area so far. Moreover, these geophysical data can foster multidisciplinary scientific collaborations in the fields of hydrology, glaciology, climate, geology, geomorphology, etc. To a large extent, the data set can provide new insight into the hydrological dynamics and polar and climate changes studies on the Ny-Ålesund area.

opencc-by-4.0Dec 2021View details →

45 Vulnerability Discoverability Timelines from the 2019 Collegiate Penetration Testing Competition

Description This is a collection of manually curated timelines from the 2019 Collegiate Penetration Testing Competition (CPTC). Collection and annotation are described in detail in this publication: <ul> <li>Benjamin S. Meyers, Sultan Fahad Almassari, Brandon N. Keller, and Andrew Meneely. Examining Penetration Tester Behavior in the Collegiate Penetration Testing Competition. Forthcoming at Transactions on Software Engineering and Methodology. https://dl.acm.org/doi/10.1145/3514040</li> </ul> Included Files <ul> <li>2019_cptc_timelines.csv: Completed timelines for ten teams from the 2019 CPTC nationals competition.</li> <li>2019_cptc_timeline_columns.csv: Descriptions of the columns in 2019_cptc_timelines.csv.</li> <li>2019_cptc_vulnerabilities.csv: Brief vulnerability descriptions and CWE mappings.</li> </ul> Other Resources <ul> <li>Complete Splunk log data dumps are available <a href="http://mirrors.rit.edu/cptc/2019/mirrors/nationals/">here</a>. These must be ingested and viewed with a Splunk instance.</li> <li>To request access to the CPTC team reports, please contact Brock Wagehoft (<a href="mailto:bew1127@rit.edu">email</a>).</li> </ul> Contact Please contact Benjamin S. Meyers (<a href="mailto:bsm9339@rit.edu">email</a>) with questions about this data and its collection. Acknowledgments Collection of this data has been sponsored in part by the National Science Foundation grant 1922169, and by a Department of Defense DARPA SBIR program (grant 140D63-19-C-0018).

opencc-by-4.0Dec 2021View details →

PIANO (Penetration and Interruption of Alpine Foehn) – flux station data set

ABSTRACT This resource comprises meteorological and turbulence data from four flux stations operated during the PIANO (Penetration and Interruption of Alpine Foehn) field campaign. The campaign took place in and around Innsbruck, Austria, during autumn and early winter 2017. The goal of the PIANO campaign was to study south foehn events, in particular the interaction between cold air pools and foehn, the mechanisms by which foehn can break through to reach the valley floor and the processes affecting the subsequent breakdown of foehn. This dataset provides near-surface turbulence observations (including surface fluxes obtained using the eddy covariance technique), along with radiation and soil measurements, as well as meteorological information. DATA SET DESCRIPTION 1. Spatial coverage and locations Three eddy covariance (EC) stations were operated at grassland sites during the PIANO campaign. One station (‘EC_South’) was installed in the Wipp Valley near to the village of Patsch, south of the city of Innsbruck. Two stations were installed in the Inn Valley, one to the east of Innsbruck in the region of Thaur (‘EC_East’) and one to the west of Innsbruck at Innsbruck Airport (‘EC_West’). Data from a fourth EC station at the Innsbruck Atmospheric Observatory (IAO, Karl et al. (2020)) in the centre of Innsbruck (‘EC_Centre’) was also used. Precise station co-ordinates are provided in the data files. Three of the stations were located on grassland surrounded by mixed agricultural fields: the two stations in the Inn Valley (EC_East, EC_West) were installed on the fairly flat valley floor, while the site in the Wipp Valley (EC_South) gently sloped downwards to the west. During the campaign the vegetation was generally short at 5-10 cm. As far as possible, sites were selected to have a clear fetch for at least a few hundred metres. All three grassland sites experienced snow cover during winter. The urban station (EC_Centre) is a long-term site installed above roof level and representative of the surrounding neighbourhood close to the city centre of Innsbruck. 2. Temporal coverage The temporal coverage of the datasets for the PIANO campaign are as follows: • EC_West: 15 Sep 2017 - 31 Dec 2017 • EC_South: 08 Sep 2017 – 15 Dec 2017 • EC_East: 13 Oct 2017 – 15 Dec 2017 • EC_Centre: 1 Sep 2017 – 31 Dec 2017 The timeseries for EC_East begins later than the other sites because electrical interference thought to be from a nearby transmitter meant there was no useable flux data for the first month. The site was relocated on 13 October 2017 (no data is included before this date). Repeated theft of the batteries at EC_East resulted in gaps for the last few days of the dataset in December 2017. Due to issues with remote data collection, data availability at EC_West is low in September 2017. The PIANO campaign took place during autumn and early winter 2017 but the EC_West station was operated for longer (until 22 May 2018 after which use of the site was no longer permitted) as it provided a useful rural comparison station for the urban measurements (Karl et al., 2020; Ward et al., submitted). Data for 1 January – 22 May 2018 are available from the first author on request. Data collection at the long-term EC_Centre/IAO site began in spring 2017 and is ongoing. 3. Instrument details At EC_West a closed-path eddy covariance system (CPEC200, Campbell Scientific) provided fast response measurements of the three wind components, temperature, water vapour mixing ratio and carbon dioxide mixing ratio. At EC_East and EC_South a sonic anemometer (CSAT3B, Campbell Scientific) and krypton hygrometer (KH20, Campbell Scientific) provided fast response measurements of the three wind components, temperature and water vapour. These fast data were logged at 20 Hz (CR6, Campbell Scientific). All three stations were equipped with a four-component radiometer (CNR4, Kipp and Zonen) to provide incoming and outgoing shortwave and longwave radiation. Meteorological measurements included air temperature and humidity (Rotronic HC2A-S3, mounted in an actively ventilated radiation shield Rotronic RS12T), atmospheric pressure (Campbell CS100, mounted inside the logger box) and precipitation (ARG100 tipping bucket gauge, Campbell Scientific). Soil instruments comprised two soil heat flux plates at 0.05 m depth (HFP01, Hukseflux), two soil temperature sensors (107, Campbell Scientific) at 0.02 and 0.04 m depth and a soil probe (ACC-SEN-SDI, Acclima) providing soil moisture and soil temperature at 0.05 m depth. At each site, the fast-response anemometer and gas analyser were mounted on a tripod at around 2.5 m above ground, while the radiometer and temperature-humidity probe were slightly lower, at around 2.0 m (exact sensor heights are provided in the data files). At EC_Centre a closed-path eddy covariance system (CPEC200, Campbell Scientific) provided fast response measurements of the three wind components, temperature, water vapour mixing ratio and carbon dioxide mixing ratio at 10 Hz (CR3000, Campbell Scientific) measured at 42.8 m above ground level on a lattice mast installed on top of a university building. A four-component radiometer (CNR4, Kipp and Zonen) provided incoming and outgoing shortwave and longwave radiation and air temperature and humidity are also measured (Rotronic HC2A-S3, mounted in a ventilated radiation shield). Atmospheric pressure is measured by a pressure sensor mounted inside one of the electronics boxes supplied as part of the CPEC200 (EC100, Campbell Scientific). No soil or precipitation measurements were made at the urban station. 4. Data processing The fast-response eddy covariance data were processed to 30-min statistics following standard procedures using EddyPro version 7.0.7 (LI-COR Biosciences, 2021). These include despiking of raw data, time-lag compensation using maximum covariance, double coordinate rotation (meaning the 30-min mean vertical wind speed is forced to zero), simple block averaging (i.e. no filtering was applied), humidity correction of sonic temperature (Schotanus et al., 1983), and spectral corrections at low frequencies (Moncrieff et al., 2004) and high frequencies (after Fratini et al. (2012) for the closed-path CPEC200 data and Moncrieff et al. (1997) for the krypton hygrometer data). Oxygen (Tanner et al., 1993; van Dijk et al., 2003) and density (Webb et al., 1980) corrections were also applied at the sites with krypton hygrometers. Automated calibration (zero and span for carbon dioxide and zero for water vapour) was performed for the CPEC instruments once per day at EC_West and twice per day at EC_Centre. In addition to the standard processing described above, gust speeds were calculated from the sonic data. First the instantaneous horizontal wind speed was calculated (neglecting any vertical component). A 3-s running mean of the horizontal wind speed was then obtained, and the gust speed taken as the maximum of this 3-s running mean over a 1-min averaging interval. The dissipation rate of turbulent kinetic energy was obtained from the fast-response measurements of the three wind components (u, v, w) as follows. First, spectra were calculated for u, v and w using evenly spaced logarithmic frequency bins. The inertial subrange was identified as the region around 1 Hz where a local linear fit to the spectral slope was within ±20% of the expected -5/3 slope. The dissipation rate was calculated for each frequency bin in the identified inertial subrange according to Kolmogorov theory (e.g. Kaimal and Finnigan, 1994), using a value of 0.55 for u and 0.73 for v and w for the Kolmogorov inertial subrange constants, and the mean value over the frequency bins was used to provide the dissipation rate for u, v, and w for each 30-min period. Further discussion can be found in Ward et al. (in prep.). Quality control removed data during times of power outage and instrument malfunction and data adversely affected by rainfall (all KH20 data during rainfall were removed). To exclude any potential effects of turbulence distortion, data were removed when the wind direction was within ±10° of the mounting structure. Data falling outside physically reasonable thresholds were removed, including times when the rotation angle exceeded 45°. Stationarity tests following Foken and Wichura (1996) were applied with a threshold of 100 (i.e. data were excluded when the difference between 5-min and 30-min statistics exceeded 100%). For the meteorological, radiation and soil data, quality control removed data during times of power outage and instrument malfunction (including when dew on the radiometer adversely affected readings). 5. Data file structure Two files in netCDF format are provided containing processed and quality-controlled data: • PIANO_EC_MetData_QC_1min_v1-00.nc containing the meteorological, radiation and soil data for each site at 1-min resolution. This file also contains horizontal wind speed (before co-ordinate rotation), wind direction and gust speed for each site at 1-min resolution. • PIANO_EC_FluxData_QC_30min_v1-00.nc containing processed statistics and fluxes for each site at 30-min resolution. There are also quicklook plots (provided in PNG format, monthly and for the whole period) showing the data contained in these files. Four sets of files in ASCII format are provided containing the fast (10/20 Hz) eddy covariance data for each site for every 30-minute period. These files are timestamped with the time corresponding to the end of the period and are named: • PIANO_EC_FastData_SITENAME_yyyymmdd_HHMM.csv. These sets of files are provided as a single .zip folder for each site which is named according to the site. All timestamps are given in UTC (in seconds since 00:00 UTC 01 January 1970) and denote the end of the averaging period. The following variables can be found in the MetData file: air temperature (ta), relative humidity (rh), atmospheric pressure (pa), precipitation (prec), soil temperature (ts1, ts2, ts3), soil volumetric water content (vwc), soil heat flux from each heat flux plate (shf1, shf2), incoming shortwave radiation (swin), outgoing shortwave radiation (swout), incoming longwave radiation (lwin), outgoing longwave radiation (lwout), wind speed (wspeed, i.e. vector average horizontal wind speed before double rotation), wind direction (wdir) and gust speed (gust). The following variables can be found in the FluxData file: friction velocity (ustar), sensible heat flux (h), latent heat flux (le), carbon dioxide flux (fco2), stability parameter (zeta), turbulent kinetic energy (tke), wind speed (wspeed, i.e. vector average wind speed after double rotation), wind direction (wdir), unrotated vertical wind velocity (wunrot, i.e. before double rotation), the standard deviation of the wind components and temperature (sigu, sigv, sigw, sigt), and dissipation rate of turbulent kinetic energy calculated from u, v and w spectra (epu, epv, epw). The following variables can be found in the RawData files: unrotated lateral, longitudinal and vertical wind components (in m s-1), temperature (in degree C), water vapour concentration (supplied for EC_West and EC_Centre as the mixing ratio (in mmol m-1) and supplied for EC_South and EC_East as the absolute humidity (g m-3) and carbon dioxide mixing ratio (in μmol mol-1) for EC_West and EC_Centre. Note that the absolute value of the water vapour concentration from the krypton hygrometers should not be used. These lateral, longitudinal and vertical wind components are as measured in the co-ordinate system of the sonic anemometers and the angle of installation of the sonic needed to convert to north-south east-west co-ordinates is given in the FluxData file. 6. Publications Data from these flux stations have been included in multiple publications as part of the PIANO project (Haid et al., 2020; Haid et al., 2021; Muschinski et al., 2021; Umek et al., 2021; Umek et al., submitted) as well as publications as part of a related study on turbulent exchange in complex environments (Ward et al., in prep.; Ward et al., submitted). 7. Contact Contact helen.ward(at)uibk.ac.at for any questions regarding the data set. 8. Acknowledgements The PIANO campaign was supported by the Austrian Science Fund (FWF) and the Weiss Science Foundation under Grant P29746-N32. Collection of this dataset was also supported by an FWF Lise Meitner project (M2244-N32) and a research stipend from Innsbruck University. Measurements at IAO are supported by the Bundesministerium für Wissenschaft, Forschung und Wirtschaft (Hochschulraum-Strukturmittel grant), the European Commission for funding ALP-AIR within FP7-PEOPLE and the FWF (P30600_NBL, P33701-N). The PIANO campaign was also supported by KIT IMK-IFU, Austro Control GmbH, Zentralanstalt für Meteorologie und Geodynamik (ZAMG), the Hydrographic Service of Tyrol, Innsbrucker Kommunalbetriebe AG (IKB), Bergisel Betriebsgesellschaft m.b.H., Innsbrucker Nordkettenbahnen Betriebs GmbH, T-Mobile Austria GmbH, Unser Lagerhaus Warenhandelsgesellschaft, PEMA Immobilien GmbH, HTL Anichstraße, Hilton Innsbruck, TINETZ-Tiroler Netze GmbH, Land Tirol, and the communities Patsch and Völs. 9. References Foken T, Wichura B (1996) Tools for quality assessment of surface-based flux measurements. Agric. For. Meteorol. 78: 83-105 doi: 10.1016/0168-1923(95)02248-1 Fratini G, Ibrom A, Arriga N, Burba G, Papale D (2012) Relative humidity effects on water vapour fluxes measured with closed-path eddy-covariance systems with short sampling lines. Agric. For. Meteorol. 165: 53-63 doi: 10.1016/j.agrformet.2012.05.018 Haid M, Gohm A, Umek L, Ward HC, Muschinski T, Lehner L, Rotach MW (2020) Foehn–cold pool interactions in the Inn Valley during PIANO IOP2. Q. J. R. Meteorol. Soc. 146: 1232-1263 doi: 10.1002/qj.3735 Haid M, Gohm A, Umek L, Ward HC, Rotach MW (2021) Cold-air pool processes in the Inn Valley during foehn: A comparison of four cases during PIANO. Boundary Layer Meteorology doi: 10.1007/s10546-021-00663-9 Kaimal JC, Finnigan JJ (1994) Atmospheric Boundary Layer Flows: Their structure and management. Oxford University Press, 289 pp. Karl T et al. (2020) Studying urban climate and air quality in the Alps - The Innsbruck Atmospheric Observatory. Bull. Amer. Meteorol. Soc. doi: 10.1175/BAMS-D-19-0270.1 LI-COR Biosciences (2021) Eddy Covariance Processing Software - version 7.0.7, Available at www.licor.com/EddyPro. Moncrieff JB, Clement R, Finnigan JJ, Meyers T (2004) Averaging, detrending and filtering of eddy covariance time series. In: X Lee, Massman WJ and Law BE (Editors), Handbook of Micrometeorology: a guide for surface flux measurements. Moncrieff JB et al. (1997) A system to measure surface fluxes of momentum, sensible heat, water vapour and carbon dioxide. Journal of Hydrology 188-199: 589-611 Muschinski T, Gohm A, Haid M, Umek L, Ward HC (2021) Spatial heterogeneity of the Inn Valley Cold Air Pool during south foehn: Observations from an array of temperature. Meteorol. Z. 30: 153-168 doi: 10.1127/metz/2020/1043 Schotanus P, Nieuwstadt FTM, Bruin HAR (1983) Temperature measurement with a sonic anemometer and its application to heat and moisture fluxes. Bound.-Layer Meteor. 26: 81-93 doi: 10.1007/bf00164332 Tanner B, Swiatek E, Greene J (1993) Density fluctuations and use of the krypton hygrometer in surface flux measurements. Management of irrigation and drainage systems: integrated perspectives. American Society of Civil Engineers, New York, NY: 945-952 Umek L, Gohm A, Haid M, Ward HC, Rotach MW (2021) Large eddy simulation of foehn-cold pool interactions in the Inn Valley during PIANO IOP2. Quart J Roy Meteorol Soc 147: 944-982 doi: 10.1002/qj.3954 Umek L, Gohm A, Haid M, Ward HC, Rotach MW (submitted) Influence of grid resolution of large-eddy simulations on foehn-cold pool interaction. Quart J Roy Meteorol Soc van Dijk A, Kohsiek W, de Bruin HAR (2003) Oxygen Sensitivity of Krypton and Lyman-α Hygrometers. J. Atmos. Ocean. Technol. 20: 143-151 doi: 10.1175/1520-0426(2003)020<0143:osokal>2.0.co;2 Ward HC, Rotach MW, Gohm A, Graus M, Karl T, Haid M, Umek L, Muschinski T (submitted) Energy and mass exchange at an urban site in mountainous terrain – the Alpine city of Innsbruck. Atmos. Chem. Phys. Ward HC, Rotach MW, Graus M, Karl T, Gohm A, Umek L, Haid M (in prep.) Turbulence characteristics at an urban site in highly complex terrain. Webb EK, Pearman GI, Leuning R (1980) Correction of flux measurements for density effects due to heat and water-vapor transfer. Q. J. R. Meteorol. Soc. 106: 85-100

opencc-by-4.0Jul 2022View details →

25 years of high-frequency ground penetrating radar measurements of snow studies in Svalbard - metadata and GPS tracks

Surveys by ground penetrating radar (GPR) are accurate and cost-efficient, and have been conducted on Svalbard for more than 25 years, thus permitting the assessment of long term changes. The campaigns so far have covered various areas and the data is dispersed. The purpose of this report is to collect information about the conducted GPR snow cover measurements. The activities initiated in this project will be continued in the coming years and extended with a comprehensive data analysis. The dataset includes a description of metadata from GPR snow cover measurements in 1997-2022 (.CSV file) and GPS traces (.SHP files) of measurements taken in Svalbard. This study is part of the State of Environmental Science in Svalbard Report 2022 published by Svalbard Integrated Arctic Earth Observing System (SIOS).

opencc-by-4.0Feb 2023View details →

Ground Penetrating Radar survey of San Quintin glacier, Northern Patagonia Icefield

Measured ice thickness, Residual Bedrock Reflection Power (BRP) and Internal Reflection Power (IRP) of San Quitin glacier, Northern Patagonia Icefield.   Data for the preprint  "Frontal collapse of San Quintín glacier (Northern Patagonia Icefield), the last piedmont glacier lobe in the Andes" in review for The Cryosphere (https://doi.org/10.5194/tc-2023-10)

opencc-by-4.0Mar 2023View details →

IceAq Project - Ground Penetrating Profiles Data

Ground Penetrating Radar profiles on 47 sections. Equipment used: Cobra Plug-In by Radarteam 45 .sgy files containing the GPR data, 45 text files containing the corresponding GPS data, 1 spreadsheet giving the correlation table between the .sgy and GPS text files. Total 424 Mb. Origin: MSCA Project Number: 885891 Project Acronym: IceAq Project title: Proglacial and subglacial aquifers: their evolution under climate change and the potential impacts in terms of resources and natural hazards, through the case of eastern Iceland Period of data collection: June 2022, precise periods specified for each file. Area of data collection: Iceland, south-east of Vatnajökull, Suðursveit and Mýrar. Accessibility: The data can be read using e.g. the following open source softwares: LibreOffice (https://www.libreoffice.org), QGIS (<a href="https://qgis.org/">https://qgis.org</a>), and Geopsy (https://www.geopsy.org/).

edi44/100

Percent light penetration: BioCON : Biodiversity, Elevated CO2, and N Enrichment

BioCON (Biodiversity, CO2, and Nitrogen) is an ecological experiment started in 1997 at the University of Minnesota's Cedar Creek Ecosystem Science Reserve. BioCON's goal is to explore the ways in which plant communities will respond to three environmental changes that are known to be occurring on a global scale: increasing nitrogen deposition, increasing atmospheric CO2, and decreasing biodiversity. Why Biodiversity, CO2, and Nitrogen? While there are many uncertainties in global change biology, there are also some well documented facts. Some of these are: 1. The amount of carbon dioxide (CO2) in the atmosphere is rising. Since the industrial revolution, the CO2 concentration in the atmosphere has increased from approximately 275 parts per million (ppm) to about 378 ppm today. This has been largely the result of fossil fuel burning. It is expected that CO2 levels will continue to rise, and that by the year 2050 these levels will be approximately 550 ppm. CO2 is the raw material for photosynthesis and is known to affect plant growth and development. 2. The amount of nitrogen moving through terrestrial ecosystems has increased in the recent past. While natural "background" levels of nitrogen fixation have remained constant, human additions to the system through fertilizer production and fossil fuel use have increased dramatically. Nitrogen is a key nutrient for plant growth and plays a critical role in plant community structure and composition in many environments. 3. Biodiversity levels are falling. While the research and data are not as complete as they are for CO2 and nitrogen, data indicate that the number of species globally, is being reduced. Perhaps more important for ecosystem function, diversity levels on local to regional scales have fallen due to land use change, biotic invasion and many other drivers. While much is known about how each of these factors affects ecosystem functioning, many questions remain. There is also little data on how these issues affe

openCC0Mar 2024View details →

Fig. 7 in Thoridae (Crustacea: Decapoda) can penetrate the Abyss: a new species of Lebbeus from the Sea of Okhotsk, representing the deepest record of the family

Fig. 7. Phylogenetic relationships within Thoridae (Hippolyte Leach, 1814 as outgroup) based on COI mtDNA gene markers. Bootstrap support (> 50%) is shown by the numbers along the branches (BA/ML analysis). Line thickness is also correlated with support values.

Fig. 4 in Thoridae (Crustacea: Decapoda) can penetrate the Abyss: a new species of Lebbeus from the Sea of Okhotsk, representing the deepest record of the family

Fig. 4. Lebbeus sokhobio sp. nov., ♀ from st. 4-3 (paratype, ZMMU Ma6097) (A–H, J–K, M) and ♂ from st. 4-9 (paratype, SMF 51579) (I, L). A. Basal segments of pereiopods I–III. B. Maxilliped III. C. Antepenultimate segment of maxilliped III. D. Pereiopod I. E. Chela of pereiopod I. F. Proximal segments of pereiopod I. G. Pereiopod II. H. Pereiopod III. I. Merus of pereiopod III. J. Dactylus of pereiopod III. K. Pereiopod IV. L. Merus of pereiopod IV. M. Pereiopod V.

Fig. 2 in Thoridae (Crustacea: Decapoda) can penetrate the Abyss: a new species of Lebbeus from the Sea of Okhotsk, representing the deepest record of the family

Fig. 2. Lebbeus sokhobio sp. nov., general view, ♀ from st. 4-3 (paratype, ZMMU Ma6097) and ♂ from st. 4-9 (paratype, SMF 51579).

Fig. 3 in Thoridae (Crustacea: Decapoda) can penetrate the Abyss: a new species of Lebbeus from the Sea of Okhotsk, representing the deepest record of the family

Fig. 3. Lebbeus sokhobio sp. nov., ♀ from st. 4-3 (paratype, ZMMU Ma6097) (A–I) and ♂ from st. 4-10 (paratype, MIMB 39426) (J–K). A–B. Anterior part of carapace. C. Abdominal pleonites IV–V, lateral view. D–E. Antennula. F. Antenna. G. Telson and uropods. H. Distal margin of telson. I. Distolateral margin of exopod. J. Endopod of pleopod I. K. Endopod of pleopod II.

opencc-by-4.0Dec 2021View details →

Supporting data for Wu et al. "Penetrating Electric Field Simulated by the MAGE and Observed by ICON" paper

This dataset contains the necessary data supporting the paper titled "Penetrating Electric Field Simulated by the MAGE and Observed by ICON", to be submitted by Wu et al., 2022. The dataset includes the Multiscale Atmosphere-Geospace Environment (MAGE) model simulation for two intervals to support 2020 Sep 26 9-10 UT and 2020 Sep 24 5-6 UT. The data contain neutral wind, ion drift, and electron density output.

opencc-by-4.0Mar 2024View details →

Relationship between sediment particle size, compaction and penetration resistance.

Data on median grain size, compaction (measured with a vane tester) and penetration resistance (measured with a light penetrometer) of intertidal sediments. These data are the source of a mathematical function showing the relationship between them presented in a paper describing a new light penetrometer for intertidal and infralittoral sediments.

opencc-by-4.0Jul 2021View details →

Ground Penetrating Radar data acquired over Von Postbreen, Svalbard, March 2018.

GPR data and diffraction focusing Madagascar code Data authors: Richard Delf and Robert Bingham, University of Edinburgh. Data and code associated with Delf et al. "Reanalysis of polythermal glacier thermal structure using radar diffraction focussing" Ground-Penetrating Radar data was acquired over Von Postbreen, Svalbard, to investigate the internal velocity structure by diffraction focusing. Data were acquired in March 2018 over 2 days, using a PulseEkko Pro 25 MHz system, towed behind a snowscooter in an in-line, common-offset configuration. Data are stored in the SEGY format. Differential GPS was used for positioning; coordinates are included in the SEGY data. Data Description Three groups of data are present here within the .zip file. data with no preprocessing: files in ./data/aq_data/18_VP_0_*.SGY     SEGY Radar data with pre-processing applied. Significant ringing is observed in the upper regions of the radargrams. Note file names do not correlate with the files in subsequent folders. data with preprocessing: filenames in ./data/raw_data/18_VP_1_*.SGY     SEGY Radar data with pre-processing applied to remove ringing and other noise using an SVD filter and bandpass filtering. Radargrams are sorted into shorter lines across and up the glacier. See associated paper for additional details. processed_data: filenames  18_VP_2_*.SGY     The same data as above, with diffraction coherence after Schwarz et al (2019) applied. See associated paper for additional details.   Processing files: SConstruct: Madagascar SConstruct file for processing the above profiles to derive the velocity profiles described in the associated (Delf et al) paper.

opencc-by-4.0Jan 2022View details →

Dynamic cone penetration tests conducted at the NBS site in OAL-Austria

Dynamic cone penetration tests conducted at the NBS site in OAL-Austria to infer the regolith depth and penetration resistance A light-weight CPT device was used, dropping a defined weight of 10kg from a defined height, while recording the number of strokes required for penetrating the soil material in vertical increments of 10 cm.

opencc-by-4.0Dec 2014View details →

Рис. 8. 3D–диаграммы пространственного распределениЯ обилиЯ моллюска M. catrusiana (А), фитомассы (В), твердости грунта на глубине 5–10 см (C) и доли агрегатных фракций 3–5 мм (D) на участке № 2 в 2011 г. (единицы иЗмерениЯ осей Х и Y даны в метрах). Fig. 8. 3D–diagrams of the abundance spatial distribution of the land snail M. catrusiana (A), phytomass (B), 0–10 cm layer soil penetration resistance (C), aggregate particle size 3–5 mm (D) at the site 1 in 2011 (axes X and Y presented in meters). in Analysis of the spatial distribution patterns of the land snail populations: a geostatistic method approach

Рис. 8. 3D–диаграммы пространственного распределениЯ обилиЯ моллюска M. catrusiana (А), фитомассы (В), твердости грунта на глубине 5–10 см (C) и доли агрегатных фракций 3–5 мм (D) на участке № 2 в 2011 г. (единицы иЗмерениЯ осей Х и Y даны в метрах). Fig. 8. 3D–diagrams of the abundance spatial distribution of the land snail M. catrusiana (A), phytomass (B), 0–10 cm layer soil penetration resistance (C), aggregate particle size 3–5 mm (D) at the site 1 in 2011 (axes X and Y presented in meters).

opencc-by-4.0Dec 2014View details →

Рис. 7. 3D–диаграммы пространственного распределениЯ обилиЯ моллюска B. cylindrica (А), фитомассы (В), проективного покрытиЯ (С), твердости грунта на глубине 5–10 см (D) на участке № 1 в 2010 г. (единицы иЗмерениЯ осей Х и Y даны в метрах). Fig. 7. 3D–diagrams of the abundance spatial distribution of the snail B. cylindrica (A), phytomass (B), plants projective cover (C), 0–10 cm layer soil penetration resistance (D) at the site 1 in 2010. (axes X and Y presented in meters). in Analysis of the spatial distribution patterns of the land snail populations: a geostatistic method approach

Рис. 7. 3D–диаграммы пространственного распределениЯ обилиЯ моллюска B. cylindrica (А), фитомассы (В), проективного покрытиЯ (С), твердости грунта на глубине 5–10 см (D) на участке № 1 в 2010 г. (единицы иЗмерениЯ осей Х и Y даны в метрах). Fig. 7. 3D–diagrams of the abundance spatial distribution of the snail B. cylindrica (A), phytomass (B), plants projective cover (C), 0–10 cm layer soil penetration resistance (D) at the site 1 in 2010. (axes X and Y presented in meters).

opencc-by-4.0Dec 2015View details →

Figure 1 in Angiostrongylus cantonensis cathepsin B-like protease (Ac-cathB-1) is involved in host gut penetration

Figure 1. Selection and identification of the stably expressed cell line. (A) Schematic diagram of vector construction. Replacement of the GFP with a sequence containing 50 IgK SP and 30 myc-His sequence using an isocaudamer technique resulted in the creation of pBobi-IMHIP vector. Lentiviral vector pBobi-cathB1 was generated by insertion of Ac-cathB-1 coding sequence excluding SP into the pBobi-IMHIP vector by XbaI and BamHI restriction sites. (B) Lentiviral packaging of pBobi-cathB1 and pBobi-GFP. Under the fluorescence microscope, more than 90% of cells in the pBobi-GFP transfected group displayed green fluorescence. (C) Assessment of the establishment of 293T-cathB1. Anti-Myc IF staining was performed in the two cell lines. All cells in 293T-cathB1 showed red fluorescence representing 100% positive, while all cells in 293T-GFP showed no fluorescence under the red fluorescent filter due to the lack of myc-tag expression. (D) Tests for rAccathB-1 expression. Total RNA and protein samples were extracted from two groups of cells. Results of RT-PCR (top two panels) and western blot (lower two panels) showed that rAc-cathB-1 was highly expressed in 293T-cathB1 at both mRNA and protein levels. Actb, RT-PCR control and B-actin, loading control for western blot; WL, white light; and bar = 100 µm.

opencc-by-4.0Dec 2015View details →

Figure 2 in Angiostrongylus cantonensis cathepsin B-like protease (Ac-cathB-1) is involved in host gut penetration

Figure 2. Purification and identification of rAc-cathB-1. (A) Purification of rAc-cathB-1 from the cell culture supernatant. Lanes: MW, molecular weight markers (listed in kDa on the side); 1, concentrated culture supernatant in binding buffer; 2, column flowthrough; 3, binding buffer wash; 4–6, successive eluate fractions (during the elution step, the eluate was collected in one 5 ml tube after another); 7, eluate from gel filtration. (B) Identification of purified rAc-cathB-1 by western blot with an antiserum against Ac-cathB-1 expressed in E. coli and an anti-Myc antibody.