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Dataset for the IntoValue 1 + 2 studies on results dissemination from clinical trials conducted at German university medical centers completed between 2009 and 2017
<p>The IntoValue dataset contains clinical trials conducted at one of 35 German UMCs and registered on ClinicalTrials.gov or the German Clinical Trials Registry (DRKS). All trials were reported as complete between 2009 and 2017 on the trial registry at the time of data collection. The dataset also includes a results publication found via manual searches; if multiple results publications were found, the earliest was included.</p> <p>Trials were associated with a German UMC by searching for trials with a UMC listed as responsible party or lead sponsor, or with a principle investigator (PI) from a UMC ('lead_city'). Version 1 additionally includes trials with a UMC only as a facility (`facility_city`). A lookup table of regular expressions used to identify German UMCs is available at <a href="https://github.com/quest-bih/IntoValue2/blob/master/data/1_sample_generation/city_search_terms.csv">https://github.com/quest-bih/IntoValue2/blob/master/data/1_sample_generation/city_search_terms.csv</a>.</p> <p>Trials include all interventional studies and are not limited to investigational medical product trials, as regulated by the EU's Clinical Trials Directive or Germany's Arzneimittelgesetz (AMG) or Novelle des Medizinproduktegesetzes (MPG).</p> <p>DRKS data were searched (pre-filtered for completion years and study status as well as Germany as 'Country of recruitment') and downloaded as CSVs from the DRKS website (<a href="https://www.drks.de/">https://www.drks.de/</a>). ClinicalTrials.gov data were downloaded downloaded as pipe files from Clinical Trials Transformation Initiative (CTTI) Aggregate Content of ClinicalTrials.gov (AACT) (<a href="https://aact.ctti-clinicaltrials.org/pipe_files">https://aact.ctti-clinicaltrials.org/pipe_files</a>). DRKS and ClinicalTrials.gov use different terminology for various trial aspects, such as phase and masking; these different levels are captured in the data dictionary as `levels_drks` and `levels_ctgov`. For later analyses requiring parity across registries, levels for some variables were collapsed and a lookup table is provided in `iv_data_lookup_registries.csv`.</p> <p>These data were generated and used for two publications (Wieschowski et al., 2019; Riedel et al. 2021) and therefore comprises two versions (indicated as `iv_version`).</p> <p>For version 1, registry data was collected on April 17, 2017 from ClinicalTrials.gov and on July 27, 2017 for DRKS and was limited to trials with a completion date on DRKS and primary completion date on ClinicalTrials.gov between 2009 and 2013. Version 1 manual searches for results publications were conducted from 2017-07-01 to 2017-12-01.<br> For version 2, registry data was collected on June 3, 2020 and was limited to trials with a completion date on DRKS and ClinicalTrials.gov between 2014 and 2017. Version 2 manual searches for results publications were conducted from 2020-07-01 to 2020-09-01.</p> <p>Raw registry data for versions 1 and 2 is available in `raw-registries.zip`.</p> <p>Publication identifiers (DOI, PMID, URL) were manually entered during the publication search and then further enhanced using the API of Internet Archive's open-source Fatcat catalog of research publications, to add PMIDs based on DOIs, and vice versa.</p> <p>Manual search steps differed slightly in the two versions and are indicated and described in `identification_step`.<br> Version 1 includes trials with a German UMC as either a `lead_city` or a `facility_city`, whereas version 2 is limited to trials a German UMC as a `lead_city`.</p> <p>Each row indicates a single trial registration. Due to changes in completion dates, some trials are duplicated between versions as indicated in `is_dupe`. Cross-registered trials were manually deduplicated, and some cross-registered duplicates remain (e.g., DRKS00004156 and NCT00215683) and are not indicated in the dataset.</p> <p>All dates are provided as `yyyy-mm-dd`.</p> <p>Additional documentation on each variable (type, description, levels) is provided in `iv_data_dictionary.csv`.</p> <p>Additional information on the project and methods for generating the dataset is available in associated publications and at the project's OSF page (<a href="https://osf.io/98j7u/">https://osf.io/98j7u/</a>). Code for the project is available at <a href="https://github.com/quest-bih/IntoValue2">https://github.com/quest-bih/IntoValue2</a>.</p> <p><strong>References:</strong></p> <p>Wieschowski, S., Riedel, N., Wollmann, K., Kahrass, H., Müller-Ohlraun, S., Schürmann, C., Kelley, S., Kszuk, U., Siegerink, B., Dirnagl, U., Meerpohl, J., & Strech, D. (2019). Result dissemination from clinical trials conducted at German university medical centers was delayed and incomplete. Journal of Clinical Epidemiology, 115, 37–45. <a href="https://doi.org/10.1016/j.jclinepi.2019.06.002">https://doi.org/10.1016/j.jclinepi.2019.06.002</a></p> <p>Riedel, N., Wieschowski, S., Bruckner, T., Holst, M. R., Kahrass, H., Nury, E., Meerpohl, J. J., Salholz-Hillel, M., & Strech, D. (2021). Results dissemination from completed clinical trials conducted at German university medical centers remained delayed and incomplete. The 2014-2017 cohort. Journal of Clinical Epidemiology, 0(0). <a href="http://doi.org/10.1016/j.jclinepi.2021.12.012">https://doi.org/10.1016/j.jclinepi.2021.12.012</a><br> </p>
Data associated with the 2019 Freshwater Oil Spill Remediation Study (FOReSt) assessing the use of enhanced Monitored Natural Recovery (eMNR) and shoreline washing agent (SWA) of diluted bitumen spills conducted in shoreline enclosures at the IISD Experimental Lakes Area, ON, Canada from 2019 to 2020
The following package includes data from the 2019 Freshwater Oil spill Remediation Study (FOReSt) at the IISD Experimental Lakes Area studying the use of enhanced monitored natural recovery (eMNR) and shoreline washing agent (SWA) as a secondary remediation method for diluted bitumen spills in freshwater shoreline enclosures. This package includes data tables on polycyclic aromatic compound chemistry in water and sediments, basic water quality, nutrient chemistry, and tritium chemistry monitored in the experimental and reference enclosures, and lake reference sites over the duration of the study. Data included in this package was first collected and used in the paper by Palace et al., titled Polycyclic aromatic compounds in freshwater ecosystems following non-invasive remediation of controlled diluted bitumen spills: The Freshwater Oil Spill Remediation Study (FOReSt) at the Experimental Lakes Area, Canada.
Hydrochemical Data from a Tropical Andean Glacierized Catchment: δ18O, electrical conductivity, maximum fluorescence intensity, and dissolved organic carbon concentrations from short-term sampling campaigns, Ecuador (2022 and 2024)
Fluorescent dissolved organic matter (FDOM) quality, dissolved organic carbon (DOC) concentration, electrical conductivity (EC), and stable water isotopes (δ¹⁸O and δ2H) were determined in water, snow, and ice samples from a tropical glacierized catchment in the Ecuadorian Andes. The sampling locations were selected to capture the major hydrologic inputs to the main stream channel (glacial melt, tributaries, wetlands, and groundwater springs) and constrain the in-stream spatiotemporal variation in DOM quality and other hydrochemical characteristics. Two sets of high-resolution time series were collected on Oct 13, 2022 and Jun 14, 2024. Time series samples were collected at various upper catchment locations and the outlet simultaneously. DOM quality was characterized via fluorescence spectroscopy and processed using parallel factor analysis (PARAFAC). The DOM quality data are expressed as %FMax values obtained through a 4-component PARAFAC model, where %Fmax 1– 4 are interpreted as terrestrial humic-like, tyrosine-like, tryptophan-like, and microbial humic-like fluorescent components, respectively. DOC concentrations were quantified using high-temperature catalytic combustion, stable water isotopes were analyzed using laser-based spectroscopy, and EC was measured in situ with handheld multiparameter water quality probes.
The 2021 Freshwater Oil Spill Remediation Study (FOReSt), assessing the use of enhanced Monitored Natural Recovery (eMNR) of conventional heavy crude oil spills conducted in freshwater shoreline enclosures at the IISD Experimental Lakes Area, ON, Canada from 2021 to 2022.
The following package includes data from the 2021 Freshwater Oil spill Remediation Study (FOReSt) at the IISD Experimental Lakes Area studying the use of enhanced monitored natural recovery (eMNR) as a secondary remediation method for conventional heavy crude oil spills in freshwater shoreline enclosures. This package includes data tables on polycyclic aromatic compound chemistry in water and sediments, basic water quality, nutrient chemistry monitored in the experimental and reference enclosures, and lake reference sites over the duration of the study. As well as tables detailing enclosure metrics (depth), tritium chemistry, and a treatment key. Data included in this package was first collected and used in the paper by Stanley et al., titled Rapid Chemical Remediation of Freshwater Enclosures Treated with Conventional Heavy Crude Oil Spills Followed by Enhanced Monitored Natural Recovery
Light-saturated photosynthetic rate, dark respiration, stomatal conductance and ratio of internal to external carbon dioxide concentration from the 1980-82 Eriophorum vaginatum reciprocal transplant plots from Eagle Creek to Prudhoe Bay, Alaska, 2010
In 1980-1982, six transplant gardens were established along a latitudinal gradient in interior Alaska from Eagle Creek, AK, in the south to Prudhoe Bay, AK, in the north (Shaver et al. 1986) .Three sites, Toolik Lake (TL), Sagwon (SAG), and Prudhoe Bay (PB) are north of the continental divide and the remaining three, Eagle Creek (EC), No Name Creek (NN), and Coldfoot (CF), are south of the continental divide. Each garden consisted of 10 individual tussocks transplanted back to their home-site, as well as 10 individuals from each of the other transplant sites. Data were collected in July 2010 for tussocks transplanted in 1980-82 in a reciprocal transplant experiment and then harvested in 2011. Important variables are garden name, source population, light-saturated photosynthetic rate, dark respiration, stomatal conductance and ratio of internal to external carbon dioxide concentration.
Quarterly porewater salinity and conductivity measurements from the GCE-LTER Seawater Addition Long-Term Experiment (SALTEx) Project
The Georgia Coastal Ecosystems LTER Seawater Addition Long-Term Experiment (SALTEx) is a large-scale field experiment designed to simulate saltwater intrusion in a tidal freshwater wetland to predict how chronic (Press) and acute (Pulse) salinization will affect this and other tidal freshwater ecosystems. Thirty porewater well samples were collected every 2-3 months from all 30 treatment plots using a peristalsis pump. Salinity, conductivity and water temperature were measured from the samples using a handheld conductivity/salinity meter.
Chloride Concentrations, Conductivity, and Water Temperature Data from Upper Yahara River Watershed Tributaries in Dane County, WI: December 2019 – April 2021
Conductivity and chloride were measured for 2 years in nine tributaries of Lake Mendota and Lake Monona in Dane County, WI. HOBO Conductivity loggers continuously measured absolute conductivity and water temperature every 30 minutes. Breaks in data collection were due to a calibration period or if the loggers were out of the water. Grab samples for chloride concentration occurred weekly or biweekly. Conductivity and water temperature were measured with a field meter at each sampling excursion. This data was needed for a master’s research thesis with the goal of characterizing the spatial distribution and loading of chloride in the Upper Yahara River Watershed.
PsPM-SCBD: Skin conductance response from a delay fear conditioning task with auditory CS (monophones/triads)
<p>This dataset includes skin conductance response (SCR) measurements for 10 healthy unmedicated participants (5 females and 5 males, age range: 18 - 33 years, mean age: 24.1 +/- 4.7) participating in a classical (Pavlovian) discriminant delay fear conditioning experiment with auditory CS. Also included are CS and US information, and ratings of CS after the experiment. Simple and complex CS were simple sine tones (4 s), and triads in root position or in first inversion, respectively. US was a train of electric square pulses delivered with a constant current stimulator (Digitimer DS7A, Digitimer, Welwyn Garden City, UK) on participants' dominant forearm through a pin-cathode/ring-anode configuration. After the fear conditioning task, participants were first asked to report their subjective estimate of how likely they were to receive a shock after a given CS in the future, on a visual analogue scale of 0-100. Then they were asked to rate pairs of CS sounds with respect to which of the two stimuli they liked less.</p>
PsPM-SCRV6: Skin conductance responses to pain by electric stimulation
<p>This dataset includes skin conductance response (SCR) measurements for each of 20 healthy unmedicated participants (10 males and 10 females aged 21.8+/-3.3 years) in response to 10 discomforting electric shocks. Stimuli are 0.5ms wide square current pulse repeated at 500Hz for 100ms. Amplitude is varied (mean +/- SD: 0.78mA +/- 0.43mA). ITI is selected randomly on each trial from 29s, 34s or 39s.</p>
Investigation of the properties of conductivity signals in BK channels by Empirical Mode Decomposition
<p>The idea of the project is the comprehensive time-frequency analysis of ion current data registered from BK channels of the different cell lines and measured under the different experimental conditions. Decomposition of signals into individual frequency modes and application of non-linear measures in the form of Information Entropy or Hurst exponent to individual signal components will allow for a more detailed analysis of the information hidden behind the complex ionic conduction sequences. The sample data contains patch-clamp sequences. </p>
Organic Matter, Geochemical, Visible Spectrocolorimetric Properties, Radiocesium Properties, and Grain Size of Potential Source Material, Target Sediment Core Layers and Laboratory Mixtures for Conducting Sediment Fingerprinting Approaches in the Mano Dam Reservoir (Hayama Lake) Catchment, Fukushima Prefecture, Japan
<p>The current dataset was compiled to study sediment fingerprintings practices, i.e tracer selection and contribution modelling. Organic matter, elemental geochemistry, visible difuse spectrocolorimetric properties, radiocesium properties, and grain size were analysed were analysed in potential source material that may supply sediment to coastal rivers, here the upper part of the Mano river, draining the main Fukushima radioactive pollution plume (Japan). Four potential soil source materials (<em>n</em> = 68) were considered: undecontaminated cropland (<em>n</em> = 24), as non-decontaminated soil before the application of local decontamination policies, remediated cropland (<em>n</em> = 10), as decontaminated soil after the application of local decontamination policies, forest soils (n = 24) and subsurface material originating from channel bank collapse or landslides (<em>n</em> = 10; referred to as subsoil). A sediment core was collected in the Mano Dam lake (Hayama lake) on the 6th June 2021 and was sectionned into 1-cm layers (<em>n</em> = 38). Laboratory mixtures (<em>n</em> = 27) were made to assess different contribution levels from the sources.</p> <p>The current dataset comprises four .csv files including data and metadata information and their respective descriptions of variables. The data set is composed of soil samples, sediment core layer and laboratory mixtures. Laboratory mixtures were prepared to provide a dataset to calibrate/validate un-mixing models implemented to address this research question and analysed in the same conditions and using the same equipment as the source/target material.</p> <p>Recommended encoding format: <strong>latin1</strong></p>
Photorheological study of conductive polyaniline/acrylic composites
<p>This data set corresponds to the analyses carried out in the following article: Arias-Ferreiro, G.; Ares-Pernas, A.; Lasagabáster-Latorre, A.; Aranburu,N.; Guerrica-Echevarria, G.; Dopico-García,M.S.; Abad,M.-J. Printability Study of a Conductive Polyaniline/Acrylic Formulation for 3D Printing. Polymers 2021, 13, 2068. https://doi.org/10.3390/polym13132068</p>
Opinions and Views of the Population of Ukraine: May 2024 (KIIS Omnibus 2024/05) – Data from a nationwide public opinion poll conducted by KIIS in May 2024
"Opinions and Views of the Population of Ukraine" is a regular omnibus survey, conducted by Kyiv International Institute of Sociology (KIIS) among Ukraine's adult population and covering a wide range of topics. The data presented here is a subset of the survey conducted in May 2024 and include KIIS's own research questions. Questions included are: readiness for concessions for peace, views on Ukraine's relationship with Russia, perceptions of the war between Russia and Ukraine, views on security agreements, perceptions of Ukrainian society's unity, attitudes toward criticism of the government, attitudes toward the legalization of medical cannabis, and perceptions of Ukraine's statehood during the Soviet era. Data collection took place from May 16 to 22, 2024, with 1,067 respondents interviewed. The data is available in an SAV format (Ukrainian, English) and a converted CSV format (with a codebook). The Data Documentation (pdf file) also includes a short overview and discussion of survey results as well as the relevant parts of the original questionnaire.
Opinions and Views of the Population of Ukraine: February 2024 (KIIS Omnibus 2024/02) – Data from a nationwide public opinion poll conducted by KIIS in February 2024
"Opinions and Views of the Population of Ukraine" is a regular omnibus survey, conducted by Kyiv International Institute of Sociology (KIIS) among Ukraine's adult population and covering a wide range of topics. The data presented here is a subset of the survey conducted in February 2024 and include KIIS's own research questions. The questions cover the following topics: readiness for concessions for peace; perceptions of Russia, its people, and leadership; sources of information; perceptions of the war between Russia and Ukraine; views on Western support for Ukraine; factors contributing to Ukraine's success in the war; perceptions of recent investigations into large businesses and businessmen in Ukraine; state control over online information; state policy on the Russian language in Ukraine; the level of democracy in Ukraine; opportunities for personal success; and favorite national holidays. Data collection took place from February 17 to 28, 2024. Some of the survey questions were asked to all respondents (n=2,008), while others were directed to a sub-sample of 1,052 respondents. The data is available in an SAV format (Ukrainian, English) and a converted CSV format (with a codebook). The Data Documentation (pdf file) also includes a short overview and discussion of survey results as well as the relevant parts of the original questionnaire.
Polyaniline conductive composites with lignin.
<p>This data set corresponds to the analyses carried out in the following article: Arias-Ferreiro, G., Lasagabáster-Latorre, A., Ares-Pernas, A., Ligero, P., García-Garabal, S. M., Dopico-García, M. S., & Abad, M. J. (2022). <br>Lignin as a High-Value Bioaditive in 3D-DLP Printable Acrylic Resins and Polyaniline Conductive Composite. Polymers, 14(19), 4164. <br>DOI:10.3390/polym14194164</p>
Stream discharge, stage, electrical conductivity & temperature dataset from Otemma glacier forefield, Switzerland (from July 2019 to October 2021)
<p>Stream data collected in the Otemma forefield (Switzerland) from July 2019 to Ocober 2021.<br> Data were collected by the research teams of Bettina Schaefli<sup>2</sup> and Stuart N. Lane<sup>1</sup>.</p> <p><sup>1</sup> Institute of Earth Surface Dynamics (IDYST), University of Lausanne, 1015 Lausanne, Switzerland</p> <p><sup>2</sup> Institute of Geography (GIUB), University of Bern, 3012 Bern, Switzerland</p> <p>For further information, please contact:</p> <ul> <li>tom.muller.1@unil.ch</li> <li>floreana.miesen@unil.ch</li> </ul> <p><strong>Description of data </strong></p> <p>A detailed description of the dataset is provided in the <strong>data_description_analysis.pdf</strong> file. In particular, the methodology and stage-discharge rating curves are provided in this file. Stream data were measured in three locations from glacier snout (Station 1); after the outwash plain (Station 2) and at the end of the glacier forefield (Station 3) (<strong>see overview_GS.png</strong>). A <strong>shapefile </strong>is also provided (coordinate system LV95).</p> <p>2 datasets are available in the data.zip file:</p> <ul> <li> <p><strong>River_2019_2021_10T.csv</strong> : contains the measured River Electrical conductivity (EC) [μS/cm], Stage [meters] and Temperature [°C] data for all stations in a tidy data format (see pdf for detailed description), with a 10 minutes timestep.</p> </li> <li> <p><strong>Discharge2020_10T.csv </strong>&<strong> Discharge2021_10T.csv </strong>: contains the estimated discharge [m<sup>3</sup>/s] at Station 1 and Station 2 from July 2020 to October 2021 and estimated error (2 standard deviations) in a tidy data format (see pdf for detailed description), with a 10 minutes timestep.</p> </li> </ul> <p>Additionally, the point discharge measurements covering peak summer discharge to minimal winter baseflow are provided in the <strong>Point_discharge_measurements_2020_2021.xlsx</strong> file.</p> <p>Plots of river parameters and discharge are also provided in data.zip for vizualisation.</p> <p> </p>
Simultaneously Enhanced Tenacity, Rupture Work, and Thermal Conductivity of Carbon Nanotubes Fibers by Raising Effective Tube Portion
<p>Although individual carbon nanotubes (CNTs) are superior as constituents to polymer chains, the mechanical and thermal properties of CNT fibers (CNTFs) remain inferior to synthetic fibers due to the failure of embedding CNTs effectively in superstructures. Conventional techniques resulted in a mild improvement of target properties while achieving parity at best on others. Here, a Double-Drawing technique is developed to rearrange the constituent CNTs in both mesoscale and nanoscale morphology. Consequently, the mechanical and thermal properties of the resulting CNTFs can simultaneously reach their highest performances with specific strength ~3.30 N/tex, work of rupture ~70 J/g, and thermal conductivity ~354 W/m/K, despite starting from low-crystallinity materials (<em>I</em><sub>G</sub>:<em>I</em><sub>D</sub>~5). The processed CNTFs are more versatile than comparable carbon fiber, Zylon and Dyneema. Based on evidence of load transfer efficiency on individual CNTs measured with In-Situ-Stretching-Raman, we find the main contributors to property enhancements are the increasing of the effective tube contribution, in addition to the known optimization on CNTs alignment and stacking.</p>
Mixed ionic-electronic conduction in Ruddlesden-Popper and Dion-Jacobson layered hybrid perovskites with aromatic organic spacers
<p>Characterisation dataset for “Mixed ionic-electronic conduction in Ruddlesden-Popper and Dion-Jacobson layered hybrid perovskites with aromatic organic spacers”, DOI:10.1039/d4tc01010h. Data provided as *.xlsx, *.csv, *tif and *.png files.</p> <p> </p> <p> </p> <p> </p>
Shipboard Conductivity–Temperature–Depth (CTD) and dissolved oxygen profile data collected during hypoxia surveys along six hydrographic sampling lines within Olympic Coast National Marine Sanctuary, 2004–2015
<p>This data set includes Conductivity-Temperature-Depth (CTD) and dissolved oxygen profile data that were collected along Washington State’s outer coast within Olympic Coast National Marine Sanctuary (OCNMS). Measurements were made along six cross-shelf hydrographic sampling lines during a series of hypoxia survey cruises from 2004 – 2015. The 398 CTD profiles were acquired using Sea-Bird Scientific 19 SeaCAT or 19plus SeaCAT CTD profilers with associated SBE-43 (Sea-Bird Electronics) or Beckman or YSI-type (Yellow Springs Instruments) dissolved oxygen sensors. The data were processed via Sea-Bird Scientific’s SBE Data Processing application using six of the modules in the following order: Data Conversion, Filter, Align CTD, Loop Edit, Derive, and Bin Average. These processing steps and associated methods are the same as those used to process CTD data collected during OCNMS mooring maintenance cruises (<a href="https://www.sciencedirect.com/science/article/pii/S2352340924001422">Risien et al., 2024</a>) and along the Newport Hydrographic Line (<a href="https://www.sciencedirect.com/science/article/pii/S2352340922001342">Risien et al., 2022</a>) located off the central Oregon coast.</p> <table> <tbody> <tr> <td><strong>Station Name </strong></td> <td><strong>Latitude</strong></td> <td><strong>Longitude</strong></td> <td><strong>Water Depth (m, MLLW)</strong></td> </tr> <tr> <td><strong>Cape Alava (CA)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>CA010</td> <td>48.1661oN</td> <td>124.7540oW</td> <td>10</td> </tr> <tr> <td>CA020</td> <td>48.1661oN</td> <td>124.7598oW</td> <td>20</td> </tr> <tr> <td>CA030</td> <td>48.1659oN</td> <td>124.7783oW</td> <td>30</td> </tr> <tr> <td>CA040</td> <td>48.1659oN</td> <td>124.7852oW</td> <td>40</td> </tr> <tr> <td>CA045</td> <td>48.1659oN</td> <td>124.8335oW</td> <td>45</td> </tr> <tr> <td>CA050</td> <td>48.1658oN</td> <td>124.8578oW</td> <td>50</td> </tr> <tr> <td>CA060</td> <td>48.1659oN</td> <td>124.8843oW</td> <td>60</td> </tr> <tr> <td>CA070</td> <td>48.1655oN</td> <td>124.9011oW</td> <td>70</td> </tr> <tr> <td>CA080</td> <td>48.1657oN</td> <td>124.9141oW</td> <td>80</td> </tr> <tr> <td>CA090</td> <td>48.1659oN</td> <td>124.9247oW</td> <td>90</td> </tr> <tr> <td>CA100</td> <td>48.1658oN</td> <td>124.9319oW</td> <td>100</td> </tr> <tr> <td><strong>Teahwhit Head (TH)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>TH030</td> <td>47.8759oN</td> <td>124.6481oW</td> <td>30</td> </tr> <tr> <td>TH035</td> <td>47.8761oN</td> <td>124.7024oW</td> <td>35</td> </tr> <tr> <td>TH040</td> <td>47.8760oN</td> <td>124.7281oW</td> <td>40</td> </tr> <tr> <td>TH050</td> <td>47.8761oN</td> <td>124.7567oW</td> <td>50</td> </tr> <tr> <td>TH060</td> <td>47.8765oN</td> <td>124.7822oW</td> <td>60</td> </tr> <tr> <td>TH070</td> <td>47.8765oN</td> <td>124.8084oW</td> <td>70</td> </tr> <tr> <td>TH080</td> <td>47.8768oN</td> <td>124.8415oW</td> <td>80</td> </tr> <tr> <td>TH090</td> <td>47.8769oN</td> <td>124.8868oW</td> <td>90</td> </tr> <tr> <td>TH100</td> <td>47.8769oN</td> <td>124.9182oW</td> <td>100</td> </tr> <tr> <td><strong>Hoh Head (HH)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>HH025</td> <td>47.7688oN</td> <td>124.5605oW</td> <td>25</td> </tr> <tr> <td>HH042</td> <td>47.7688oN</td> <td>124.6428oW</td> <td>42</td> </tr> <tr> <td>HH065</td> <td>47.7688oN</td> <td>124.7401oW</td> <td>65</td> </tr> <tr> <td><strong>Raft River (RR)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>RR015</td> <td>47.4632oN</td> <td>124.3748oW</td> <td>15</td> </tr> <tr> <td>RR020</td> <td>47.4644oN</td> <td>124.4510oW</td> <td>20</td> </tr> <tr> <td>RR042</td> <td>47.4632oN</td> <td>124.5199oW</td> <td>42</td> </tr> <tr> <td>RR065</td> <td>47.4629oN</td> <td>124.6074oW</td> <td>65</td> </tr> <tr> <td><strong>Cape Elizabeth (CE)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>CE010</td> <td>47.3541oN</td> <td>124.3347oW</td> <td>10</td> </tr> <tr> <td>CE020</td> <td>47.354oN</td> <td>124.3608oW</td> <td>20</td> </tr> <tr> <td>CE030</td> <td>47.3538oN</td> <td>124.3913oW</td> <td>30</td> </tr> <tr> <td>CE040</td> <td>47.3534oN</td> <td>124.4678oW</td> <td>40</td> </tr> <tr> <td>CE050</td> <td>47.3532oN</td> <td>124.5064oW</td> <td>50</td> </tr> <tr> <td>CE060</td> <td>47.3529oN</td> <td>124.5510oW</td> <td>60</td> </tr> <tr> <td>CE070</td> <td>47.3528oN</td> <td>124.5823oW</td> <td>70</td> </tr> <tr> <td>CE080</td> <td>47.3527oN</td> <td>124.6158oW</td> <td>80</td> </tr> <tr> <td>CE090</td> <td>47.3526oN</td> <td>124.6491oW</td> <td>90</td> </tr> <tr> <td>CE100</td> <td>47.3522oN</td> <td>124.6754oW</td> <td>100</td> </tr> <tr> <td><strong>Moclips (MO)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>MO010</td> <td>47.2214oN</td> <td>124.2394oW</td> <td>10</td> </tr> <tr> <td>MO015</td> <td>47.2214oN</td> <td>124.2599oW</td> <td>15</td> </tr> <tr> <td>MO020</td> <td>47.2214oN</td> <td>124.2791oW</td> <td>20</td> </tr> <tr> <td>MO030</td> <td>47.2195oN</td> <td>124.3347oW</td> <td>30</td> </tr> <tr> <td>MO042</td> <td>47.2195oN</td> <td>124.3958oW</td> <td>42</td> </tr> </tbody> </table>
Accompanying data for paper "Electrical and Thermal Conductivity of Complex-Shaped Contact Spots"
<div> </div> <div>This repository contains the numerical data of the conductivity of complex-shaped contact spots on isotropic and linear conducting half-space obtained by Boundary and Finite Element methods. These data were used to construct some figures from the manuscript "Electrical and Thermal Conductivity of Complex-Shaped Contact Spots". The data is organized in folders corresponding to different types of contact spots: annular, flower-, star- and gear-shaped, Koch's snowflake, and self-affine spots. Each folder contains the results of numerical simulations in the form of `.npz` files, which can be loaded using `numpy` library in Python. The data is used to construct figures in the manuscript and can be used to reproduce the results or to perform additional analysis.</div> <div> </div>
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