Find research datasets worth reusing

opencc-by-4.0Sep 2021View details →

Data for the manuscript "Enhanced microscopic dynamics in mucus gels under a mechanical load in the linear viscoelastic regime" (PNAS).

Data files for the figures published in D. Larobina, A. Pommella, A.-M. Philippe, M. Y. Nagazi, and L. Cipelletti, Enhanced Microscopic Dynamics in Mucus Gels under a Mechanical Load in the Linear Viscoelastic Regime, Proc Natl Acad Sci USA 118, e2103995118 (2021). DOI: 10.1073/pnas.2103995118 Each data set is available as a plain text file (description in the file __README__DataDescription.txt), and as an Excel file. The Excel files typically contain the data sets of several panels of a given figure, as separated sheets. See the description provided in the "GeneralInfo" sheet of each Excel file.

opencc-by-4.0Feb 2023View details →

3D model of antenna system embedded into building envelope for improved cellular signal transmission through load-bearing walls

The purpose of this dataset is to supplement the data presented in our journal publication "Electromagnetic–Thermal Analyses of Distributed Antennas Embedded Into a Load-Bearing Wall" (see <a href="https://ieeexplore.ieee.org/document/10151683">https://ieeexplore.ieee.org/document/10151683</a>). This dataset contains the 3-D discretized model, without the internal numerical mesh, of the unit cell of the spiral antenna system embedded in a load bearing wall. The 3D model is in .STP format (see ISO 10303-21:2016), which can be imported into most commercial computer-aided design (CAD) software. The wall's dielectric properties are calculated using the model described in ITU-R P.2040-2 (<a href="https://www.itu.int/rec/R-REC-P.2040/en">https://www.itu.int/rec/R-REC-P.2040/en</a>, material parameter and calculation model are on pages 22-23). Materials used in the antenna system and their electrical and thermal parameters are given in the file materials.txt

opencc-by-4.0Feb 2023View details →

Patient reported outcome measures, load-induced blood marker kinetics, and ambulatory knee load in patients with medial compartment knee osteoarthritis

The goal of this study was (i) to quantify the mechanoresponse of this array of potential blood markers for joint pathology (COMP, MMP-1, MMP-3, MMP-9, CPII, C2C, C2C/CPII, ADAMTS-4, PRG-4, IL-6 and resistin) to a walking stress test in patients with knee OA and to determine the correlation (ii) among the kinetics of these blood markers, (iii) with accumulated knee load during the walking stress, and (iv) with patient reported osteoarthritis outcome and QoL. The dataset includes 24 patients with knee osteoarthritis scheduled to receive high tibial osteotomy. All participants completed questionnaires, and a walking stress test with six blood samples analyzed using enzyme-linked immunosorbent assays for cartilage oligomeric matrix protein (COMP), matrix metalloproteinases (MMP)-1, -3, and -9, epitope resulting from cleavage of type II collagen by collagenases (C2C), type II procollagen (CPII), interleukin (IL)-6, proteoglycan (PRG)-4, A disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS)-4, and resistin, and gait analysis. Joint load was computed from gait analysis data and musculoskeletal modelling in AnyBody Modeling System (AnyBody Technology A/S). Discrete loading parameters were extracted for each step using an inhouse algorithm written in Matlab. The detailed experimental protocol of the umbrella study has been described in Mündermann A, Vach W, Pagenstert G, Egloff C, Nüesch C. Assessing in vivo articular cartilage mechanosensitivity as outcome of high tibial osteotomy in patients with medial compartment osteoarthritis: Experimental protocol. Osteoarthr Cartil Open. 2020 Feb 24;2(2):100043. doi: 10.1016/j.ocarto.2020.100043. PMID: 36474590; PMCID: PMC9718245. The study is registered on clinicaltrials.gov (identifier NCT02622204). The method for computing joint loading has been described in detail in De Pieri E, Nüesch C, Pagenstert G, Viehweger E, Egloff C, Mündermann A. High tibial osteotomy effectively redistributes compressive knee loads during walking. J Orthop Res. 2022 Jun 22. doi: 10.1002/jor.25403. Epub ahead of print. PMID: 35730475.

opencc-by-4.0Oct 2022View details →

Deliverable 2.3 Design Load Case Database for Code-to-Code Comparison

In work package 2 of FLOATECH a detailed validation and verification of the capabilities of QBlade-Ocean was performed. Thereby, three wind turbine models mounted on floating substructures with differing characteristics serve as the means for the validation.This  dataset contains Floating Offshore Wind Turbine (FOWT) calculations in various design situations, computed with three different codes. In more detail, three floating platform archetypes are used in the code-to-code comparison ongoing in work package 2: a semi-submersible-type floater and a spar-type floater as well as the Hexafloat® concept recently proposed by Saipem®. The three test-cases are the NREL 5MW RWT mounted on the DeepCwind semi-submersible platform, the DTU 10MW RWT mounted on the SOFTWIND spar-type platform and the DTU 10MW RWT mounted on the Hexafloat® platform.  More details regarding the dataset structure and the testcases can be found in the accompanying document.    Changelog:  Version 5.0.0 <ul> <li>Changed structural damping ratio (increased) in OpenFAST results (SOFTWIND and Hexafloat models) to match structural damping ratios in QBlade</li> <li>Added wave time series at platform undisplaced position</li> <li>Added TurbSim input files for wind field generation. TurbSim v2.0.0 (https://www.nrel.gov/wind/nwtc/turbsim.html - National Renewable Energy Laboratory)</li> <li>Added detailed DLC and simulation information in "DLC&SimulationList.xlsx"</li> </ul> Version 4.0.0 <ul> <li>Correction of bugs in QB 5MWOC4 and 10MWSOFT models: wind shear exponent in wind fields (0.11 -> 0.14)</li> <li>Update of hydrodynamic database used in OpenFAST and QBlade results of 10MWSOFT model </li> </ul>   <pre><code>Data in version 5.0.0 is used in WES publication: Papi, F., Troise, G., Behrens de Luna, R., Saverin, J., Perez-Becker, S., Marten, D., Ducasse, M.-L., and Bianchini, A.: A Code-to-Code Comparison for Floating Offshore Wind Turbine Simulation in Realistic Environmental Conditions: Quantifying the Impact of Modeling Fidelity on Different Substructure Concepts, Wind Energ. Sci. Discuss. [preprint], https://doi.org/10.5194/wes-2023-107, in review, 2023.</code></pre>

edi48/100

Spatiotemporal variation in internal phosphorus loading, sediment characteristics, water column chemistry, and thermal mixing in a hypereutrophic reservoir in southwest Iowa, USA (2019-2020)

The primary aim of the data product is to quantify seasonal and spatial variation in sediment phosphorus fluxes in a temperate reservoir and evaluate mechanisms responsible for instances of elevated sediment phosphorus release. We studied Green Valley Lake, a hypereutrophic reservoir in southwest Iowa, USA, from 2019 to 2020. We measured sediment phosphorus flux rates and potential explanatory variables at three sites along the longitudinal gradient of the reservoir over six sampling events during winter and summer stratification as well as mixing events in the spring, summer, and fall. Ex situ sediment core incubations were used to measure sediment P release rates under ambient temperature and dissolved oxygen conditions. Explanatory variables measured included sediment phosphorus chemistry, sediment physical characteristics, epilimnetic and hypolimnetic nutrient concentrations, and thermal stratification patterns. These data will be used to identify mechanisms driving hot spots and hot moments of sediment phosphorus release, which will contribute to our understanding of how areas of lakebed and times of the year can disproportionately influence whole-lake water chemistry.

openCC (other)Oct 2021View details →

edi48/100

Stream nitrate concentrations and discharge, stream nitrate uptake, and results of stream network nitrate model to determine lateral nitrate load from land to stream in Oak Creek, Arizona, USA

Data package associated with Handler et al. (2024) "Nitrate loads from land to stream are balanced by in-stream nitrate uptake across season in a dryland stream". The study describes the nitrate dynamics in Oak Creek watershed. Data include measurements from four seasonal synoptic sampling campaigns, nine seasonal stream nitrate uptake experiments on the main stem and tributaries, and the results of a network model that estimates the lateral load of nitrate from surrounding landscape to the stream network as well as network-level stream nitrate uptake and retention.

openCC0Oct 2024View details →

opencc-by-4.0Jan 2020View details →

Damage Monitoring of Structural Resins Loaded with Carbon Fillers: Experimental and Theoretical Study

Dynamic Mechanical Analysis, Electro-Mechanical Measurement, Simulation model, Dynamic Light Scattering,  FTIR spectroscopy Thermogravimetric analysis,  Differential Scanning Calorimetry, Electro-Temperature Measurement,  Thermal Image Camera ,  Water sorption measurement, Transmission Electron Microscopy, Stress Strain

opencc-by-4.0Jan 2021View details →

Experimental measurements of creep deformation of Tournemire shale loaded at specified pressure (10 MPa) and room temperature (26°C)

Following the experimental protocol used in (Geng et al., 2018), we performed the stepping creep experiments at a confining pressure of 10 MPa. We first loaded the samples under hydrostatic conditions up to 10 MPa at a pressure rate of 0.3 MPa/min. Hydrostatic conditions were maintained for ~18 h at 26 °C. Next, differential stress (axial stress minus confining pressure) was increased to a fixed initial stress (30 MPa) and maintained (creep status) for 24 h. The differential stress was repeatedly increased by 5 MPa and maintained for 24 h, until brittle failure. All the experiments were conducted using the triaxial apparatus installed at the Laboratoire de Géologie of ENS-Paris (France). There were few constraints on the natural saturation state of the samples because of their low permeability (10-19 10-21 m2). To avoid exposition redundancy, an additional description of the technical performance of the triaxial apparatus can be referred to (Brantut et al., 2011, Sarout & Guéguen, 2008). Compressive stresses and compactive strains are denoted as positive. Axial creep deformation was measured using three capacitive gap sensors that externally monitored the overall axial displacement of the piston during creep deformation. Volumetric strain during creep was estimated by adding the average of axial strains (axial displacement of the piston divided by the sample length) and two average radial strains measured by four radial strain gauges glued uniformly around the cylindrical rock surface. As the deformation rate generally stabilized during the last 8 h in most creep periods (Geng et al., 2018), we estimated the average axial strain rate over the last 8 h of each step to characterize the creep strain rate under the corresponding axial loading stress. More technical details of the sample configuration and creep rates estimation can be found in (Geng et al., 2018).

opencc-by-4.0Jan 2021View details →

Cr[CH(SiMe3)2]3/SiO2 catalysts for ethene polymerization: the correlation at amolecular level between the chromium loading and the microstructure of the produced polymer

<ul> <li>Data type: Experimental spectroscopic measurements, Computer Simulation and Analysis</li> <li>Files are in txt, spc, par, opj, and m format</li> <li>Information on origin of the data: <ul> <li>EPR spectroscopic measurements in spc and par formats</li> <li>EPR spectroscopic simulation and analyses in m format</li> <li>UV-vis and IR spectroscopic measurements and analyses; and polymer analyses in opj format</li> </ul> </li> <li>Are the data generated (e.g. by a machine) or collected (e.g. by means of a survey)? <ul> <li>EPR spectroscopic measurements were generated by ELEXYS 580 EPR spectrophotometer equipped with SHQ cavity and ER035 M NMR gaussmeter produced by Bruker.</li> <li>FT-IR spectroscopic measurements were generated by Vertex70 produced by Bruker equipped with an MCT detector.</li> <li>UV-Vis-NIR spectroscopic measurements were generated by Cary5000 spectrophotometer produced by Varian equipped with a reflectance sphere.</li> </ul> </li> <li>If t <ul> <li>Files in PARACAT_WP4_20201229_01_EPR folder includes EPR spectroscopic measurements and computer simulations/analyses, original data are in spc/par formats; files in m format were used to process the data of the same name and saved the results in txt format.</li> </ul> </li> <li>Information on: <ul> <li>specialized abbreviations: EPR – Electron Paramagnetic Resonance, GC – Gas Chromatography, GPC – Gel Permeation Chromatography</li> <li>definitions of variables: Magnetic field, Wavenumber, Pressure</li> <li>units of measurement: Gauss (G), milli Tesla (mT), cm-1, milli bar (mbar)</li> <li>abbreviations: IR/EPR/UV are data relate to measurements of IR/EPR/UV-Vis spectroscopy.</li> <li>abbreviation: CO/C2H4 are data relate to methods with CO/ethene dosage.</li> <li>abbreviation: polym is data relates to polymer analysis conducted by GC and GPC</li> </ul> </li> </ul>

opencc-by-4.0Jun 2021View details →

Rye microgrid load and generation data, and meteorological forecasts.

This dataset contains timeseries for Rye Microgrid, Trondheim, Norway. The timeseries include solar and wind power generation, consumption and historical weather forecasts. From <a href="https://github.com/TronderEnergi/tronderenergi-ai-hackathon-2021">https://github.com/TronderEnergi/tronderenergi-ai-hackathon-2021</a>: "The Rye microgrid is a pilot within the EU research project REMOTE. It is a small microgrid placed at Langørgen, in the outskirts of Trondheim, and is a small energy system designed to supply electricity to a modern farm and three households. The REMOTE projects goal for Rye Microgrid is to run the system in islanded mode. The system has two sources of generation – a wind turbine and a rack of PV panels. In addition, the system has two storages – a battery with high charge and discharge response, but with limited storage and losses, and a hydrogen energy system, with lower charge and discharge rates, higher losses and storage capacity. When you want to charge the hydrogen system, electricity is used to run an electrolyser that makes hydrogen from water and stores the resulting hydrogen in a tank. The process can be reversed by producing electricity from hydrogen using a fuel cell. (...) Morover, when local production or discharges from storages are not sufficient to cover the demand, the microgrid can draw electricity from the grid at some costs."   For further details, see: <a href="https://www.remote-euproject.eu/remote18/rem18-cont/uploads/2019/03/REMOTE-D2.2.pdf">https://www.remote-euproject.eu/remote18/rem18-cont/uploads/2019/03/REMOTE-D2.2.pdf</a> and <a href="https://github.com/TronderEnergi/tronderenergi-ai-hackathon-2021">https://github.com/TronderEnergi/tronderenergi-ai-hackathon-2021</a> rye_generation_and_load.csv is a comma-separated csv-file with the following columns (all values in kW and time as UTC): <ul> <li>Consumption: Consumption of loads in system (residential and agriculture).</li> <li>Solar: Total production from all solar PV racks.</li> <li>Wind: Power production from wind turbine.</li> </ul> met_data.h5: Contains historical weather forecasts data from The Norwegian Meteorological Institute (met.no) updated every 6 hours for the given location. The file is in hdf5 format. The forecasts include the following parameters: air_pressure_at_sea_level [Pa], air_temperature_2m [K], cloud_area_fraction [pu], integral_of_surface_downwelling_shortwave_flux_in_air_wrt_time [J/m2s], wind_direction_10m [deg], wind_speed_10m [m/s] The structure of the file is as follows: <ul> <li>lat63_41_lon10_11 (coordinates) <ul> <li>[forecasted parameter] <ul> <li>forecast <ul> <li>2020-01-01T00Z (time forecast was issued) <ul> <li>axis0 (columns, index where each represent a point in a geographical grid. For example if axis=0,1,2,3, the tables contains the forecasts for the four closes points to the microgrid.)</li> <li>axis1 (rows, timestamps)</li> <li>block0_items (equal to axis0)</li> <li>block0_values (matrix, forecast values)</li> </ul> </li> </ul> </li> </ul> </li> </ul> </li> </ul>

opencc-by-4.0Oct 2023View details →

California Electric Vehicle Loads by Feeder Circuit

Open the record for dataset details and reuse information.

opencc-by-4.0Sep 2023View details →

DHM Tensile Loading of 316L Stainless Steel

Video 3D.avi shows the in-situ observation and height measurement of the tensile deformation of 316L stainless steel by DHM Video Plot of aligned stack.avi shows the measured height profile of the segment indicated in image ROI.jpg Inoue Laboratory - Materials Infomatics in Physical Metallurgy Lab, Institute of Industrial Science, The University of Tokyo

opencc-by-4.0Mar 2024View details →

Experimental load-displacement response of a stainless steel specimen under cyclic loading

Experimental load-displacement data was obtained by testing a autenitic stainless steel RHS member under cyclic bending around its major axis following a cantilever loading scheme. The database is comprised of the horizontal displacement measured by a string potentiometer attached at the free end of the specimen and the horizontal force introduced by the actuator.  The data corresponds to the specimen named S1-L1, which was an austenitic stainless steel RHS specimen, with a cross-section S1 (120 × 80 × 6 mm) and an effective length of L1 = 1650 mm.  The full details of the experimental test can be found in: González-de-León I., Nastri E., Arrayago I., Montuori R., Piluso V., Real E. Experimental study on stainless steel tubular members under cyclic loading. Thin-Walled Structures 181, 109969, 2022. DOI: https://doi.org/10.1016/j.tws.2022.109969.

opencc-by-4.0Apr 2024View details →

Data description: Deprivation of loading during early healing of rat Achilles tendons affects extracellular matrix composition and structure, and reduces cell density and cell alignment

<a name="_Hlk158643946"></a>Data description: Deprivation of loading during early healing of rat Achilles tendons affects extracellular matrix composition and structure, and reduces cell density and cell alignment Malin Hammerman, Maria Pierantoni, Hanna Isaksson *, Pernilla Eliasson * * joint last authors This dataset contains microscope images obtained from sections of healing and intact rat Achilles tendons undergoing different in vivo loading protocols and different time points post-transection. The data presented are the full resolution microscope images available in lower resolution in the accompanying manuscript’s Supplementary Figures 4-6. Each zipped folders contain images (tif-files) from all time-points for each respective staining and loading group.    <ul> <li>Col1: Sections stained with Collagen 1 antibodies</li> <li>Col3: Sections stained with Collagen 3 antibodies</li> <li>Elastin: Sections stained with Elastin antibodies</li> <li>Full_loading: Free cage activity</li> <li>Reduced_loading: Paralysis of the calf muscle with Botox</li> <li>Minimal_loading: Botox combined with joint fixation using a steel-orthosis</li> <li>Intact_reference: Contralateral uninjured Achilles tendons, used as reference</li> </ul> More description of the datasets inside the zipped files are available below and in the file 'Data Description.pdf'   Brief re-cap of methods Histological analysis was performed on healing Achilles tendons from Female Sprague-Dawley rats, specific-pathogen free (11-12 weeks, weight 299 ± 15 g), that had undergone full transection [13] of the right Achilles tendon, and been exposed to different levels of loading. Altered loading was imposed through two mechanisms. Reduced loading involved intramuscular Botox injections in the right calf muscles to induce plantar flexor muscle paralysis [24]. Additionally, the rats in the minimal loading group received a steel-orthosis around their right hindlimb directly after surgery [24]. Snap frozen tendons in OCT were sectioned longitudinally (7 μm thickness) and stained with immunofluorescent staining for collagen 1, collagen 3, or elastin. Sections were counterstained with DAPI followed by mounting. The tissue sections were imaged under a microscope (DMi8, Leica Microsystems, Wetzlar, Germany, with a Hamamatsu Orca LT Flash sCMOS camera) where fluorescence was detected at 550 nm (secondary antibody Alexa Fluor 594), 470 nm (secondary antibody Alexa Fluor 488) and 385 nm (DAPI), and exposure time was held constant for each color channel regarding magnification and staining. Mapping images of the entire tendon were obtained for one section per group (n=1 per healing time, loading group and ECM matrix protein). All images were adjusted to the negative control, where the primary antibody was omitted, to correct for unspecific antibody detection. Microscope images and description of file-names All data is presented in the form of .tif files. Please refer to the scale bars in the images. All image-files are named using the following abbreviations, as described below. As an example, the file name “Tendon_col1_FL_1W_col1.tif” refers to a tendon section stained for collagen 1 from a rat exposed to full loading for a period of 1 week after tendon transection, where only the channel for collagen 1 is shown, whereas “Tendon_col1_FL_1W_merged.tif” includes the channels for both staining for collagen 1 and DAPI of the same section. Col1: Sections stained with Collagen 1 antibodies Col3: Sections stained with Collagen 3 antibodies Elastin: Sections stained with Elastin antibodies dapi: Sections stained with 4',6-Diamidino-2-Phenylindole Dihydrochloride. FL:   Full loading (free cage activity), RL:   Reduced loading (paralysis of the calf muscle with Botox), ML:  Minimal loading (Botox combined with joint fixation using a steel-orthosis) IT:    Intact contralateral Achilles tendons, used as reference. 1W: Healing time point 1 week after transection 2W: Healing time point 2 weeks after transection 3W: Healing time point 3 weeks after transection 20W: Healing time point 20 weeks after transection Settings for brightness and contrast Collagen 1 1w FL 2000-12 000, UL 4000-10 000, ML 4000-12 000 2w FL 2500-10 000, UL 4000-10 000, ML 5000-12 000 3w FL 2000-12 000, UL 3500-13 000, ML 3500-14 000 12w FL 3000-12 000 20w FL 3000-11 000 IT 2000-8 000 Collagen 3 1w FL 3000-12 000, UL 4000-10 000, ML 4000-13 000 2w FL 2000 - 7 000, UL 2500-12 000, ML 2000-12 000 3w FL 2000-12 000, UL 3500-13 000, ML 3500-14 000 12w FL 3000-12 000 20w FL 2000-12 000 IT 3000-12 000 Elastin 1w FL 4000-10 000, UL 5000 - 8000, ML 3500-12 000 2w FL 3000-12 000, UL 3000-12 000, ML 3000-12 000 3w FL 2500-12 000, UL 2000-12 000, ML 2500-12 000, 12w FL 3500-12 000 20w FL 3500-12 000 IT 2000-12 000

opencc-by-4.0Nov 2021View details →

Seasonal Terrestrial Water Load Modulation of Seismicity at the Southeastern Margin of the Tibetan Plateau Constrained by GNSS and GRACE Data

Data Set S1. The earthquake catalog is used to decluster aftershocks and background events, and the time range is from July 2004 to July 2021. This data set includes 672585 events in the study area. Data Set S2. Focal mechanism solutions of M ≥ 4 earthquakes at the southeastern margin of the Tibetan Plateau. The data set includes 634 solutions of earthquakes M ≥ 4, and the time range is from 2009 to 2017.

opencc-by-4.0Feb 2022View details →

Spain's marginal electricity mix and its relevance for assessing the environmental performance of installations with variable load or power

This upload contains the Supplementary Information file and the underlying data as Excel-file for the Journal article with the same name. More specifically, it provides time series of the Spanish electricity generation mix for the years 2015-2020 for energy system analysis and the life cycle inventory data for import into openLCA and re-use in combination with the ecoinvent databse (Version 3.7.1). Further details are available on request.

In-situ neutron diffraction during reversible deuterium loading in Ti-rich and Mn-substituted Ti(Fe,Mn)0.90 alloys - Dataset related to publication

Data type: resume of Rietveld refinement outputs and original refinements Date format: .zip, .opj;  .xlsm, .dat, .pcr (Software FullProf package outputs), .inp (Software Topas package outputs) Origin of the data: neutron diffraction patterns from ILL and ISIS, and manual Sievert measurements (PCI curves from home-made Sieverts’ type apparatus from CNRS, ICMPE, Thiais, France) Software needed to plot the data: folders need to be unzipped, Origin, FullProf package and Topas package.

Heidelberg Tributary Loading Program (HTLP) Dataset

This dataset is updated more frequently and can be visualized on NCWQR's <a href="https://ncwqr-data.org/HTLP/Portal">data portal</a>. If you have any questions, please contact <a href="https://www.heidelberg.edu/directory/laura-johnson">Dr. Laura Johnson</a> or <a href="https://www.heidelberg.edu/directory/nathan-manning">Dr. Nathan Manning</a>.   The National Center for Water Quality Research (NCWQR) is a research laboratory at Heidelberg University in Tiffin, Ohio, USA. Our primary research program is the Heidelberg Tributary Loading Program (HTLP), where we currently monitor water quality at 22 river locations throughout Ohio and Michigan, effectively covering ~half of the land area of Ohio.  The goal of the program is to accurately measure the total amounts (loads) of pollutants exported from watersheds by rivers and streams. Thus these data are used to assess different sources (nonpoint vs point), forms, and timing of pollutant export from watersheds.  The HTLP officially began with high-frequency monitoring for sediment and nutrients from the Sandusky and Maumee rivers in 1974, and has continually expanded since then.     Each station where samples are collected for water quality is paired with a US Geological Survey gage for quantifying discharge (<a href="http://waterdata.usgs.gov/usa/nwis/rt">http://waterdata.usgs.gov/usa/nwis/rt</a>).  Our stations cover a wide range of watershed areas upstream of the sampling point from 11.0 km2 for the unnamed tributary to Lost Creek to 19,215 km2 for the Muskingum River. These rivers also drain a variety of land uses, though a majority of the stations drain over 50% row-crop agriculture.  At most sampling stations, submersible pumps located on the stream bottom continuously pump water into sampling wells inside heated buildings where automatic samplers collect discrete samples (4 unrefrigerated samples/d at 6-h intervals, 1974–1987; 3 refrigerated samples/d at 8-h intervals, 1988-current). At weekly intervals the samples are returned to the NCWQR laboratories for analysis. When samples either have high turbidity from suspended solids or are collected during high flow conditions, all samples for each day are analyzed. As stream flows and/or turbidity decreases, analysis frequency shifts to one sample per day. At the River Raisin and Muskingum River, a cooperator collects a grab sample from a bridge at or near the USGS station approximately daily and all samples are analyzed. Each sample bottle contains sufficient volume to support analyses of total phosphorus (TP), dissolved reactive phosphorus (DRP), suspended solids (SS), total Kjeldahl nitrogen (TKN), ammonium-N (NH4), nitrate-N and nitrite-N (NO2+3), chloride, fluoride, and sulfate. Nitrate and nitrite are commonly added together when presented; henceforth we refer to the sum as nitrate.  Upon return to the laboratory, all water samples are analyzed within 72h for the nutrients listed below using standard EPA methods. For dissolved nutrients, samples are filtered through a 0.45 um membrane filter prior to analysis. We currently use a Seal AutoAnalyzer 3 for DRP, silica, NH4, TP, and TKN colorimetry, and a DIONEX Ion Chromatograph with AG18 and AS18 columns for anions. Prior to 2014, we used a Seal TRAACs for all colorimetry.    2017 Ohio EPA Project Study Plan and Quality Assurance Plan <a href="https://ncwqr.files.wordpress.com/2019/04/ncwqr-study-plan-20170127-with-addendums.pdf">Project Study Plan</a> <a href="https://ncwqr.files.wordpress.com/2019/04/quality-assurance-plan_version-6-20170127.pdf">Quality Assurance Plan</a>   Data quality control and data screening The data provided in the River Data files have all been screened by NCWQR staff. The purpose of the screening is to remove outliers that staff deem likely to reflect sampling or analytical errors rather than outliers that reflect the real variability in stream chemistry. Often, in the screening process, the causes of the outlier values can be determined and appropriate corrective actions taken. These may involve correction of sample concentrations or deletion of those data points. This micro-site contains data for approximately 126,000 water samples collected beginning in 1974. We cannot guarantee that each data point is free from sampling bias/error, analytical errors, or transcription errors. However, since its beginnings, the NCWQR has operated a substantial internal quality control program and has participated in numerous external quality control reviews and sample exchange programs. These programs have consistently demonstrated that data produced by the NCWQR is of high quality.   A note on detection limits and zero and negative concentrations It is routine practice in analytical chemistry to determine method detection limits and/or limits of quantitation, below which analytical results are considered less reliable or unreliable. This is something that we also do as part of our standard procedures. Many laboratories, especially those associated with agencies such as the U.S. EPA, do not report individual values that are less than the detection limit, even if the analytical equipment returns such values. This is in part because as individual measurements they may not be considered valid under litigation. The measured concentration consists of the true but unknown concentration plus random instrument error, which is usually small compared to the range of expected environmental values. In a sample for which the true concentration is very small, perhaps even essentially zero, it is possible to obtain an analytical result of 0 or even a small negative concentration. Results of this sort are often “censored” and replaced with the statement “<DL” or “<2”, where DL is the detection limit, in this case 2. Some agencies now follow the unfortunate convention of writing “-2” rather than “<2”. Censoring these low values creates a number of problems for data analysis. How do you take an average? If you leave out these numbers, you get a biased result because you did not toss out any other (higher) values. Even if you replace negative concentrations with 0, a bias ensues, because you’ve chopped off some portion of the lower end of the distribution of random instrument error. For these reasons, we do not censor our data. Values of -9 and -1 are used as missing value codes, but all other negative and zero concentrations are actual, valid results. Negative concentrations make no physical sense, but they make analytical and statistical sense. Users should be aware of this, and if necessary make their own decisions about how to use these values. Particularly if log transformations are to be used, some decision on the part of the user will be required.   Analyte Detection Limits <a href="https://ncwqr.files.wordpress.com/2021/12/mdl-june-2019-epa-methods.jpg?w=1024">https://ncwqr.files.wordpress.com/2021/12/mdl-june-2019-epa-methods.jpg?w=1024</a>   For more information, please visit <a href="https://ncwqr.org/">https://ncwqr.org/</a>

Data from the parametric analysis of masonry buttressed arches with limit analysis subjected to vertical self-weight plus a proportional horizontal live load

For each one of the simulations performed from the parametric analysis of masonry buttressed arches with limit analysis subjected to vertical self-weight plus a proportional horizontal live load, this database contains a .txt, a .vtk and a .png file. In the .txt file the elapsed time and the collapse multiplier of each simulation can be found. The .vtk file contains all the geometry and displacement values of every masonry buttressed arch. Finally, the .png file presents the collapse mechanism obtained.

Data from the parametric analysis of masonry buttressed arches with limit analysis subjected to vertical self-weight plus a proportional concentrated vertical live load applied at mid-span

For each one of the simulations performed from the parametric analysis of masonry buttressed arches with limit analysis subjected to vertical self-weight plus a proportional concentrated vertical live load applied at mid-span, this database contains a .txt, a .vtk and a .png file. In the .txt file the elapsed time and the collapse multiplier of each simulation can be found. The .vtk file contains all the geometry and displacement values of every masonry buttressed arch. Finally, the .png file presents the collapse mechanism obtained.