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opencc-by-4.0Apr 2023View details →

Data-set of CO2, CH4, N2O dissolved concentrations and ancillary data in 15 Ecuadorian high-altitude lakes

Data-set of the dissolved concentrations of CO2, CH4 and N2O and ancillary data in 15 lakes located in the northern region of Ecuadorian Andes along an elevational gradient from 2,213 to 4,361 m above sea level, as well as a gradient of lake surface area (0.003 to 6.1 km2) and depth (0.9 to 74 m) (Fig. 1). Most lakes were located in the páramos of Salve Facha and Antisana y Mojanda. Sampling was carried out over a period from April 2019 to March 2022, with an inflatable boat approximately in the center of the lake, during day-time only (early morning to late afternoon). Water temperature, specific conductivity, pH, and %O2 were measured in surface water with a YSI multi-parameter probe (ProPlus). Water for CH4 and N2O samples was collected with a sampling devise consisting of a 2L polyethylene bottle with the bottom cut and fitted with a silicone tubing at the stopper (Abril et al. 2007). Two borosilicate serum bottles (Weathon) with a volume of 40 ml were filled with the silicone tubing, poisoned with 100 µl of a saturated solution of HgCl2 and sealed with a butyl stopper and crimped with an aluminium cap. Measurements were made, after over-night equilibration, on an headspace (Weiss 1981) (created by injecting 15 ml of high-purity N2 into the 40 ml sample bottles), with a gas chromatograph (SRI 8610C) with a flame ionisation detector for CH4 and electron capture detector for N2O calibrated with CH4:N2O:N2 gas mixtures (Air Liquide Belgium) with mixing ratios of 1, 10 and 30 ppm for CH4, and 0.2, 2.0 and 6.0 ppm for N2O. The precision of measurement based on duplicate samples was ±10.9% for CH4 and ±5.8% for N2O. The partial pressure of CO2 (pCO2) was measured in the field with a Li-Cor Li-820 infra-red gas analyser based on the headspace technique with four 60 ml polypropylene syringes that were filled directly with surface water. The pCO2 in the atmosphere was measured by injecting ambient air sampled with an additional polypropylene syringe. The Li-Cor Li-820 was calibrated with pure N2 and CO2:N2 gas mixtures (Air Liquide Belgium) of 388, 804, 3,707 and 8,146 ppm. The final pCO2 value was computed taking into account the partitioning of CO2 between water and the headspace, as well as equilibrium with HCO3- (Dickson et al. 2007) using water temperature measured in-situ and after equilibration, and total alkalinity (TA). The precision of pCO2 measurement was ±5.2%. The CO2 concentration is expressed as partial pressure in parts per million (ppm) and as dissolved concentration for CH4 (nmol L-1), in accordance with convention in existing topical literature. Variations of N2O were modest and concentrations fluctuated around atmospheric equilibrium, so data are presented as percent of saturation level (%N2O, where atmospheric equilibrium corresponds to 100%), computed from the global mean N2O air mixing ratios given by the Global Monitoring Division (GMD) of the Earth System Research Laboratory (ESRL) of the National Oceanic and Atmospheric Administration (NOAA) (https://www.esrl.noaa.gov/gmd/hats/combined/N2O.html), using the Henry’s constant (Weiss and Price 1980). Samples for the stable isotope composition of DIC (δ13C-DIC) were collected in 12 ml Exetainer vials (Labco) and poisoned with 50 µL of a saturated solution of HgCl2. Prior to the analysis of δ13C-DIC, a 2 ml helium headspace was created and 100 µL of phosphoric acid (H3PO4, 99%) was added in the vial in order to convert CO32- and HCO3- to CO2. After overnight equilibration, up to 1 mL of the headspace was injected with a gastight syringe into a coupled elemental analyser - IRMS (EA-IRMS, Thermo FlashHT or Carlo Erba EA1110 with DeltaV Advantage). The obtained data were corrected for isotopic equilibration between dissolved and gaseous CO2 as described by Gillikin and Bouillon (2007). Calibration was performed with certified standards (NBS-19 or IAEA-CO-1, and LSVEC). Reproducibility of measurement based on duplicate injections of samples was typically better than ±0.2 &permil;. Water was collected in surface water with a 2L polyethylene bottle. The water filtered through 47 mm diameter GF/F Whatman glass fibber filters was collected and further filtered through polyethersulfone syringe encapsulated filters (0.2 µm porosity) for nitrate (NO3-), nitrite (NO2-), ammonium (NH4+), TA, major elements (Na+, Mg2+, Ca2+, K+), as well as dissolved silicate (DSi) and Fe, stable isotope composition of O and H of H2O (δ18O-H2O and δ2H-H2O) and dissolved organic carbon (DOC). An additional water filtration was made on 25 mm diameter GF/F Whatman glass fibber filters for particulate organic carbon (POC) analysis. Samples for NO3-, NO2-, and NH4+ were stored frozen (-20°C) in 50 ml polypropylene vials. NO3- and NO2- were determined with the sulfanilamide colorimetric with the vanadium reduction method (American Public Health Association, 1998), and NH4+ with the dichloroisocyanurate-salicylate-nitroprussiate colorimetric method (Standing committee of Analysts, 1981). Detection limits were 0.3, 0.01, and 0.15 µmol L-1 for NH4+, NO2- and NO3-, respectively. Precisions were ±0.02 µmol L-1, ±0.02 µmol L-1, and ±0.1 µmol L-1 for NH4+, NO2- and NO3-, respectively. Samples for TA were stored at ambient temperature in polyethylene 55 ml vials and measurements were carried out by open-cell titration with HCl 0.1 mol L-1 according to Gran (1952), and data quality checked with certified reference material obtained from Andrew Dickson (Scripps Institution of Oceanography, University of California, San Diego, USA), with a typical reproducibility better than ±3 µmol kg-1. Samples for δ18O-H2O and were δ2H-H2O stored at ambient temperature in polypropylene 8 ml vials. δ2H-H2O was measured on H2 gas derived from a high‐temperature (1,030°C) Cr‐based reactor by automated injections of water using a TriPlus autosampler on an elemental analyzer (Thermo Flash HT/EA; Thermo Finnigan) coupled to a continuous‐flow isotope‐ratio mass spectrometer (Delta V Advantage; Thermo Finnigan). δ18O-H2O values were measured on a Thermo GasBench II coupled to a Thermo Delta XP IRMS after equilibration with CO2. The long-term uncertainty for standard δ18O values was ±0.1&permil;. Samples for major elements were stored at ambient temperature in 20 ml scintillation vials and preserved with 50 μl of HNO3 (65%). Major elements were measured with inductively coupled plasma MS (ICP-MS; Agilent 7700x) calibrated with the following standards: SRM1640a from National Institute of Standards and Technology, TM-27.3 (lot 0412) and TMRain-04 (lot 0913) from Environment Canada, and SPS-SW2 Batch 130 from Spectrapure Standard. Limit of quantification was 0.5 µmol L-1 for Na+, Mg2+ and Ca2+, 1.0 µmol L-1 for K+ and 8 µmol L-1 for DSi. Samples to determine DOC were stored at ambient temperature and in the dark in 40 ml brown borosilicate vials with polytetrafluoroethylene (PTFE) coated septa and poisoned with 50 µL of H3PO4 (85%), and DOC concentration was determined with a wet oxidation total organic carbon analyzer (IO Analytical Aurora 1030W), with a typical reproducibility better than ±5%. Filters for POC analysis were decarbonated with HCl fumes for 4h and dried before encapsulation into silver cups; POC concentration was analysed on an EA-IRMS (Thermo FlashHT with DeltaV Advantage), with a reproducibility better than ±5%. Data were calibrated with certified (IAEA-600: caffeine) and in-house standards (leucine, tuna muscle tissue) that were previously calibrated versus certified standards. References Abril, G., Commarieu, M.-V., Guérin, F., 2007. Enhanced methane oxidation in an estuarine turbidity maximum. Limnol. Oceanogr. 52, 470-475. https://doi.org/10.4319/lo.2007.52.1.0470 American Public Health Association. Standard methods for the examination of water and wastewater, (APHA, 1998). Dickson, A.G., Sabine, C.L., Christian, J.R., 2007. Guide to best practices for ocean CO2 measurements. PICES Special Publication 3, 191 pp., https://doi.org/10.25607/OBP-1342 Gillikin, D.P., Bouillon, S., 2007. Determination of δ18O of water and δ13C of dissolved inorganic carbon using a simple modification of an elemental analyzer – isotope ratio mass spectrometer (EA-IRMS): an evaluation, Rapid Comm. Mass Spectrom. 21, 1475-1478, https://doi.org/10.1002/rcm.2968 Gran, G., 1952. Determination of the equivalence point in potentiometric titrations Part II, The Analyst, 77, 661-671, https://doi.org/10.1039/AN9527700661. Standing committee of Analysts (1981). Ammonia in waters. Methods for the examination of waters and associated materials. 16 pp (HMSO, 1981). Weiss, R.F., Price, B.A., 1980. Nitrous oxide solubility in water and seawater. Mar. Chem. 8, 347-359. https://doi.org/10.1016/0304-4203(80)90024-9 Weiss, R.F., 1981. Determinations of carbon dioxide and methane by dual catalyst flame ionization chromatography and nitrous oxide by electron capture chromatography. J. Chromatogr. Sci. 19, 611-616. https://doi.org/10.1093/chromsci/19.12.611

opennotspecifiedNov 2022View details →

FIG. 3 in Immediate skin-to-skin contact for low birth weight infants is safe in terms of cardiorespiratory stability in limited-resource settings.

FIG. 3. Map of home ranges using 95% kernel density estimates (KDE-href) for radio-tracked turtles at the study site in the Ten Thousand Islands National Wildlife Refuge and Rookery Bay National Estuarine Research Reserve, Florida, USA.

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FIG. 1. Study site for the 2016–2017 in Immediate skin-to-skin contact for low birth weight infants is safe in terms of cardiorespiratory stability in limited-resource settings.

FIG. 1. Study site for the 2016–2017 Terrapene bauri home range assessment located in southwestern Florida within the Ten Thousand Island National Wildlife Refuge (TTINWR) and Rookery Bay National Estuarine Research Reserve (RBNERR), Collier County, Florida, USA. TTINWR boundaries are delineated in green and RBNERR are delineated in blue.

opennotspecifiedNov 2022View details →

FIG. 2 in Immediate skin-to-skin contact for low birth weight infants is safe in terms of cardiorespiratory stability in limited-resource settings.

FIG. 2. Map of home ranges using 100% minimum convex polygons (MCP) for radio-tracked turtles at the study site in the Ten Thousand Islands National Wildlife Refuge and Rookery Bay National Estuarine Research Reserve, Florida, USA.

opencc-by-4.0Apr 2023View details →

Data Sets for the study "What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms"

This is the dataset of the paper "What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms" <ul> <li>figures.ipynb provides postprocessing codes for using the attached data to generate tables and figures in the paper.</li> <li>the csv folder consists of the raw data of function evaluations that algorithms used to hit each solution the first time.</li> <li>the metric folder consists of the processed data, which records the convergence process of two single objectives (y1 and y2), Hypervolume, and the number of obtained Pareto solutions.</li> <li>the gif folder consists of the gif files plotting the convergence process of solving LOTZ.</li> </ul>   The code used to generate this data is available at https://github.com/FurongYe/GSEMO

opencc-by-4.0Apr 2023View details →

Figures and Data Set of "The Effelsberg survey of FU Orionis and EX Lupi objects II. - H2O maser observations"

This is the full version of the fits files for each source with H2O maser detection for the paper "The Effelsberg survey of FU Orionis and EX Lupi objects II. - H2O maser observations”. We also provide the figures from the paper.  The paper is published in Astronomy & Astrophysics, and can be found at: https://doi.org/10.1051/0004-6361/202245032 The fits files are given for each source and for each observing date. For the data behind Figure 4, we also provide the multiplied data for V512 Per. The units are in Jy in all cases.

Synthetic Datasets from the 2023 ECXAI Workshop Paper on Principled Benchmarking for Rule Set Learning Algorithms

Synthetic datasets generated as part of the demonstration given in the paper Towards Principled Synthetic Benchmarks for Explainable Rule Set Learning Algorithms presented at the Evolutionary Computing and Explainable Artificial Intelligence (ECXAI) workshop taking place as part of the 2023 GECCO conference.

Maintenance Data Set for Car Rental Company

Maintenance records for a car rental company. The column details are provided as below: <ul> <li>CARID: Unique ID for each of the cars in the fleet</li> <li>Brand: Brand of the car</li> <li>Model : Model of the car </li> <li>SubModel : Submodel for the brand and model of the car</li> <li>Segment: there are segments for the cars ( for further information please refer to wikipedia : https://en.wikipedia.org/wiki/Car_classification ) </li> <li>Year : Model year of the car</li> <li>Fuel Type: Fuel consumption Type ( like Diesel, Petrol, Hybrid or Electric)</li> <li>Gear : Gear type of the car</li> <li>Milage: is the of the call of the maintenance (expected milage for the maintenance), the actual milage might be different than the scheduled one, this column indicates the scheduled milage for maintenance.</li> <li>MaintenanceMile : is the actual mile during the call </li> <li>CallID: a unique id for each maintenance call. </li> <li>StockID: ID of the parts or services provided during the call</li> <li>Quantity: Quantity of the parts or duration of service or amount of items used during the maintenance</li> <li>UnitPrice : unit price for the parts, services or consumption</li> <li>SubTotal : Line bases subtotal for the invoice (the actual total value in US Dollars for the quantity and the unit price : unitprice x quantity)</li> <li>Discount: Line based discount for the stockid, quantity and unitprice</li> <li>Tax : Legal taxes in USD</li> <li>GrandTotal : invoice based total amount (total amount of each lines in the same invoice)</li> <li>InvoiceDate : Data of invoice in Year - Month - Day Hour - Minute - Seconds , you can skip the hour, minute and seconds </li> <li>VendorID: Unique ID of each vendor providing the maintenance service</li> <li>CityID: Location of the maintenance</li> <li>MaintenanceType : It can be a regular maintenance ( 0) , request based maintenance (1) or unknown (2) </li> </ul>

opencc-by-4.0Feb 2023View details →

Multi-Posture Leg Tracker Data Set

This data repository contains sensor data depicting people in different postures. The data contains <ul> <li>2D radar data generated by indurad iSDR-C,</li> <li>2D laser data generated by SICK S300,</li> </ul> and depicts the postures "standing" and "squatting" complemented by background data. The robot hardware is a Robotnik Summit XL Steel with omniwheels. See README file for extensive information on data content and meta-data. The data is directly related to following publication, which we appreciate to be cited with the data set: <ul> <li>Mandischer N., Hou R., Corves B.: "Multiposture leg tracking for temporarily vision restricted environments based on fusion of laser and radar sensor data", Journal of Field Robotics, Wiley. DOI: 10.1002/rob.22195</li> </ul> The data is loosely related to following publication: <ul> <li>Mandischer N., Koop I., Granich A., Heberling D., Corves B.: "Radar Tracker For Human Legs Based On Geometric And Intensity Features", European Signal Processing Conference 2021, online. DOI: 10.23919/EUSIPCO54536.2021.9616134</li> </ul>

IsoCloud4 Data Sets for Depositional Ice Growth Analysis

Data sets used in the publication Re-evaluating cloud chamber constraints on depositional ice growth in cirrus clouds-- Part 1: Model description and sensitivity tests  K.D. Lamb, J. Harrington, B.W. Clouser, E.J. Moyer, L. Sarkozy, V. Ebert, O. Möhler, H. Saathoff. Atmospheric Chemistry and Physics (2023)

Dataset for a systematic review on the costs and cost-effectiveness of treatment setting for children with wasting, oedema and growth failure/faltering

This dataset contains data extraction tables, and results graphs, figures and other visualizations from the systematic review on the costs and cost-effectiveness of treatment setting for children with wasting, oedema and growth failure/faltering.

Chirality-Induced Spin Selectivity: An Enabling Technology for Quantum Applications. Open data set

Data supporting the original figures 5, 6 and 7 of the related publication.

SimuComp Bus Study Data Set

Raw data set and calculations of the study for the paper "Simulink bus usage in practice: an empirical study" accepted at the 19th European Conference on Modelling Foundations and Applications (ECMFA 2023)

On the Correspondence between Information Flow, Noninterference, and Symbolic Execution - Benchmark Set

The benchmark set the paper ``On the Correspondence between Information Flow, Noninterference, and Symbolic Execution'' evaluates.

On the Correspondence between Information Flow, Noninterference, and Symbolic Execution - Benchmark Set

The benchmark set the paper ``On the Correspondence between Information Flow, Noninterference, and Symbolic Execution'' evaluates.

Supplemental Data Set for "Constraining Changes in Surface Dust Thickness on Mars Using Diurnal Surface Temperature Observations from EMIRS"

Supporting data set for manuscript "Constraining Changes in Surface Dust Thickness on Mars Using Diurnal Surface Temperature Observations from EMIRS". Provides the binned and averaged EMIRS surface temperatures acquired before and after the January 2022 dust storm for each region of interest to derive changes in surface dust thickness.

Data set and analytic codes supporting "Direct observation to assess the effects of habitat structure and complexity on resource-use behaviour of butterflies: a study case in smallholding oil palm plantations in Peninsular Malaysia"

This deposit contains data set and analytic codes (with a meta data) supporting "Direct observation to assess the effects of habitat structure and complexity on resource-use behaviour of butterflies: a study case in smallholding oil palm plantations in Peninsular Malaysia". We investigated how habitat structure and complexity within smallholding oil palm plantations affected resource-use behaviours of two common butterfly species in the study areas (oil palm plantations in Banting, Selangor, Malaysia): Leptosia nina (Pieridae) and Ypthima spp. (Nymphalidae). Using direct-observation methods we developed, we followed seven and nine individuals of each species respectively, for three minutes in smallholder-owned immature monoculture and polyculture oil palm, and mature monoculture oil palm plantations. We recorded distance travelled by each individual from both straight line and the sums of distances between all perching points, and the position and characteristics of each perch location, where the individual landed. We compared our observations to control runs, generated by pairing observed distances travelled, but selecting the direction for each movement at random. By comparing the distance travelled and characteristics of locations used by butterflies and paired control points across habitats, we assessed how individuals in the two species used the local environment and whether this differed with habitat structure and complexity. Funding and research permission: Jardine Foundation, the Cambridge Trust, and Tim Whitmore Fund funded MFH, the Biotechnology and Biological Sciences Research Council (BBSRC) funded JS (USN: 304338625), and BBSRC (BB/T012366/1) funded the establishment of the plots and surveys of environmental parameters. Research permission was granted by the Economic Planning Unit (EPU) of Malaysia’s Prime Minister’s Department for MFH (Ref: EPU 40/200/19/3727) and JS (Ref: MEA 40/200/19/3705).

Classification Data set: End-to-end Learning for Land Cover Classification using Irregular and Unaligned SITS by Combining Attention-Based Interpolation with Sparse Variational Gaussian Processes

Classification data set (train, validation, test) from the study area based on 27 tiles on the south of the France. This dataset contains irregular and unaligned SITS with their corresponding masks. 9 different random sampling are provided. This data set was used to train mTAN-GP, mTAN-MLP, mTAN-LTAE and raw-LTAE. For further details see the pre-print article "End-to-end Learning for Land Cover Classification using Irregular and Unaligned SITS by Combining Attention-Based Interpolation with Sparse Variational Gaussian Processes ". This article is available : <a href="https://hal.science/hal-04112115">here</a>. The implementation of the models is available in the <a href="https://gitlab.cesbio.omp.eu/belletv/land_cover_southfrance_mtan_gp_irregular_sits">open source repository</a>.

Data set for the article 'Gold-FISH enables targeted NanoSIMS analysis of plant-associated bacteria'

This dataset contains data that support the manuscript Schmidt et al () "Gold-FISH enables targeted NanoSIMS analysis of plant-associated bacteria", The New Phytologist, accepted on 14.06.2023. It contains the following data: NanoSIMS imaging data, which was used for Fig. 2-3, as well as for Fig. S1-4. Data are provided as the original NanoSIMS images (.im) as well as their associated checkfiles (.chk_im).