Find research datasets worth reusing

openCC (other)Jul 2025View details →

Impacts of microplastics on wetland ecosystem dynamics: a mesocosm study of trophic interactions and community responses, 2021-2025

This dataset documents a mesocosm experiment conducted to evaluate the ecological impacts of microplastics (MP) on wetland communities representative of eastern USA wetlands. The study focused on key organisms across trophic levels, including tadpoles (Lithobates pipiens), snails (Helisoma trivolvis), zooplankton (Daphnia pulex), phytoplankton, and periphyton communities, to assess the effects of three microplastic types (low-density polyethylene–LDPE, medium-density polystyrene–PS, and high-density polyester–PES) at two concentrations (1 mg/L and 5 mg/L), alongside a no-microplastic control. Experimental units consisted of 70 mesocosms (19-L buckets) with 10 replicates per treatment, established between July 1–15, 2021, at Binghamton University’s Ecological Research Facility. Response variables included survival and developmental traits (mass, snout-vent length, shell width) of tadpoles and snails, microplastic ingestion, zooplankton abundance, phytoplankton biomass (chlorophyll and phycocyanin concentrations), and periphyton mass. The dataset provides comprehensive measurements of community responses and water quality parameters, offering insights into the ecological consequences of microplastic pollution in wetland ecosystems. This dataset is suitable for researchers studying ecotoxicology, wetland ecology, and the impacts of anthropogenic pollutants on aquatic food webs.

openCC (other)Aug 2025View details →

Data associated with the FLooded Upland Dynamics EXperiment (FLUDEX), conducted at the IISD Experimental Lakes Area 1997 to 2003, investigating reservoir flooding impacts on ecosystems, particularly the release of mercury and greenhouse gases.

The data included in this repository were collected over the course of the FLooded Upland Dynamics Experiment (FLUDEX) conducted at the IISD Experimental Lakes Area (IISD-ELA) from 1997 to 2003. A plethora of data was collected over five years of flooding three upland reservoir sites, in order to examine the relationship between the amount of flooded, and thus decomposed, terrestrial organic matter and the production of methylmercury (MeHg), total mercury (THg), and greenhouse gases (GHGs) in the reservoirs. Findings from this experiment suggest that the amount of organic carbon stored in a flooded site does not directly influence the amount of THg, MeHg, and GHGs produced, but it does affect the persistence of mercury in the reservoir and food web. This version of the repository contains data collected on water chemistry, benthic invertebrate (chironomid) emergence, mercury and methylmercury concentrations in the water and food web, stable isotopes of carbon and nitrogen in emerging insects and zooplankton, and abundance and biomass of zooplankton, phytoplankton, and bacteria. This data package contains only some of the data from the FLUDEX project. IISD-ELA hopes to add more data in subsequent versions.

openCC (other)Sep 2025View details →

The impact of the presence of the crayfish Faxonius virilis on the excavating behavior of Faxonius propinquus, Michigan, 2025

Faxonius propinquus are native crayfish to the Upper Midwest. They are burrowing crayfish that work the sediment and make small burrows with numerous openings. These crayfish are imperiled by Faxonius virilis which overlap in niche structure. We were interested in the impact of the chemical cues emanating from F. virilis on the sediment and burrowing nature of F. propinquus. We conducted a study at the University of Michigan's Biological Station using F. propinquus caught in nearby Douglas Lake. In addition, we collected marl substrate from where these animals are found. We created flow through mesocosms and placed F. propinquus in the mesocosm with marl substrate. Then upstream of this, we placed a F. virilis in a flow through container to allow chemical cues from F. virilis to reach F. propinquus. We did a 48 hour study where 24 hours were with a competitor chemical cue and 24 were without. This 48 cycle was repeated to provide discrete 48 hour replicates. We monitored sediment working behavior at night and during the day.

Impacts of Land Use on Japanese Barberry Invasion in Central Massachusetts 2005

Despite the recognized importance of historical factors in controlling many native species distributions, few studies have incorporated historical landscape changes into models of invasive species distribution and abundance. We explore the possibility that the current distribution of invasive species may reflect legacies of historical land use despite nearly a century of forest succession and subsequent disturbances. We evaluated the modern distribution and abundance of Berberis thunbergii DC. (Japanese barberry), a problematic non-native shrub in forests of the northeastern U.S., relative to two distinct periods of historical land use, modern forest harvesting activity, and environmental and edaphic characteristics. Species questions addressed in this study include: (1) Do patterns of historical land use influence modern barberry distribution and abundance? (2) What is the influence of disturbance type and timing relative to the timing of introduction on current barberry distribution and abundance? (3) Which disturbance, environmental and edaphic variables best predict modern barberry distribution and abundance? Japanese barberry occurred more frequently and was more abundant in sites historically cleared for agriculture than in historically wooded sites. This relationship was strongest for areas in agriculture in the early 20th century after barberry was introduced to the region. The strong relationship between modern distribution patterns and prior land use suggests historical colonization of abandoned agricultural lands and persistence through subsequent reforestation. Contrary to our expectations, recent forest harvesting did not influence the occurrence or abundance of barberry. Our results indicate that interpretations of both native community composition and modern plant invasions must consider the importance of historical landscape changes and the timing of species introduction along with current environmental and edaphic conditions.

Impacts of Nutrient Availability on Calystegia Spithamaea at Harvard Forest 2013

Low bindweed (Calystegia spithamaea (L.) Pursh ssp. spithamaea, Convolvulaceae), is a low-growing perennial plant of the morning glory family that ranges from Georgia north to Nova Scotia. It is recorded from 3 extant and 8 historic stations in Massachusetts, and 18 total extant populations across New England, where it inhabits dry, open sites with sandy to rocky soils, including sandy roadsides and path edges, inland sandplains, power line rights-of-way, loose talus slopes, and gravel pits. Massachusetts lists the species as S1, Endangered. Factors promoting reproduction in this rare species are largely unknown. Although Calystegia spithamaea has been noted to produce short rhizomes, its ability to spread vegetatively had not been determined as of 2013. Sexual reproduction is very rare in extant New England populations; although herbarium specimens show flowers, fruits are rare and seeds have not been collected at any population. Field studies have been conducted since 2007 of a population of several thousand ramets of Calystegia spithamaea in a minimally managed field on the Army Corps of Engineers Birch Hill Dam property, Royalston, Massachusetts. The population occurs on excessively drained, sandy loam, which supports otherwise low plant diversity and appears to be nutrient-poor. We tested the hypothesis that nutrient limitation may hinder sexual reproduction and ramet growth in this species. From May to August 2013, a greenhouse study was conducted at Harvard Forest to determine the effects of nutrient availability on Calystegia spithamaea growth and reproduction: Ramets were excavated from the field and were found to be propagating on long rhizomes, confirming for the first time that the species is capable of at least limited asexual reproduction. Forty-eight ramets of Calystegia spithamaea were planted in pots in the greenhouse and randomly allocated to one of two treatments: control and nutrient-amendment with 20:20:20 N:P:K fertilizer. Five ramets from a ne

Land-Use Impacts on Ecosystem Services Provisioning in Massachusetts 2001-2011

Meeting fundamental human needs while also maintaining ecosystem function and services is the central challenge of sustainability science. In the densely populated state of Massachusetts, USA, abundant forests and other natural land cover convey a range of ecosystem services. However, after more than a century of reforestation following an agrarian past, Massachusetts is again losing forests, this time to housing and commercial development. We used land-cover maps, ecosystem process models, and land-use data bases to map changes (2001, 2006, 2011) in eight ecosystem service variables and to identify “hotspots,” or areas that produce a high value of five or more services, at three policy-relevant spatial scales. Water-related services (clean water provisioning and flood regulation) experienced local declines in response to shifting land uses, but changed little when measured at the state-level. General habitat quality for terrestrial species declined state-wide during the study period as a consequence of forest loss. In contrast, climate regulation (carbon storage) and cultural services (outdoor recreation) increased, driven by continued forest biomass accrual and land protection, respectively. Timber harvest volume had high inter-annual variability, but no temporal trend. The scale at which hotspots are delineated greatly affects their quantity and spatial configuration, with a higher density in eastern Massachusetts and 10–12% more hotspots overall when they are identified at a town scale as compared to a watershed or state scale. Ecosystem service hotspots cover a small percentage of land area in Massachusetts (2.5–3.5% of the state), but are becoming more abundant as urbanization concentrates ecosystem service provisioning onto a diminished natural land base. This suggests that while ecosystem service hotspots are valuable targets for conservation, more are not necessarily better since hotspot proliferation can reflect the bifurcation of the landscape into servic

Climate Change Impacts on Forest Biodiversity at Harvard Forest since 2011

Climate change is rapidly transforming forests over much of the globe in ways that are not anticipated by current science. Large-scale forest diebacks, apparently linked to interactions involving drought, warm winters, and other species, are becoming alarmingly frequent. Models of biodiversity and climate have not provided guidance on if/where/when such responses will occur. Instead models often predict potential numbers of extinctions, but these forecasts not are linked in any mechanistic way to the processes that could cause them. Both modeling and field studies rely on aggregate metrics of species presence/absence or relative abundance at regional scales, but climate affects individuals. Aggregation of individual data to the species level, hides or even qualitatively changes climate effects. By sampling and analysis at the individual scale across continental variation in climate, this study can link the individual scale processes to regional responses. This study will exploit existing research sites and the new NEON platform of sites for synthesis of models and data to determine when and where predicting climate impacts on biodiversity is a plausible goal, understand where surprises are likely to occur, and attribute those predictions back to individual tree health and vulnerability to climate risk factors. The study will provide climate vulnerability forecasts for forest biodiversity that are directly linked to the process scale. Our goal is provide probabilistic forecasts for the joint distribution of forest responses to climate change, including growth, reproduction, and mortality risk. For scientists, US Forest Service researchers, and policy makers predictions will anticipate combined risks of increasing drought and longer growing seasons. Methods developed under this project will be disseminated through training workshops for postdoctoral associates at other universities and resource managers.

openCC0Mar 2024View details →

Modeling Impacts of Hurricanes on Current Aboveground Forest Carbon in New England 2020-2120

Nature-based climate solutions are championed as a primary tool to mitigate climate change, especially in forested regions capable of storing and sequestering vast amounts of carbon. New England is one of the most heavily forested regions in the United States (over 75% forested by land area), and forest carbon is a significant component of regional climate mitigation strategies. Large infrequent disturbances, such as hurricanes, are a major source of uncertainty and risk for policies that rely on forest carbon for climate mitigation, especially as climate change is projected to alter the intensity and geographic extent of hurricanes. To date, most research into disturbance impacts on forest carbon stocks has focused on fire. Here we show that a single hurricane in the region can down between 121-250 MMTCO2e or 4.6-9.4% of the total aboveground forest carbon, much greater than the carbon sequestered annually by New England’s forests (16 MMTCO2e yr-1). However, the emissions from the storms are not instantaneous; it takes approximately 19 years for the downed carbon to become a net emission, and 100 years for 90% of the downed carbon to be emitted. Using the HURRECON and EXPOS models to reconstruct hurricanes across a range of historical and projected wind speeds, we find that an 8% and 16% increase in hurricane wind speeds leads to a 10.7 and 24.8 fold increase in the extent of high-severity damaged areas (widespread tree mortality). Increased wind speed also leads to unprecedented geographical shifts in damage; both inland and northward into heavily forested regions traditionally unaffected by hurricanes. Given that a single hurricane can emit the equivalent of 10+ years of carbon sequestered by forests in New England, the status of these forests as a durable carbon sink is uncertain. Understanding the risks to forest carbon stocks from large infrequent disturbances is necessary for decision-makers relying on forests as a nature-based climate solution. This data set

openCC0Mar 2025View details →

Microbial, Plant, and Soil Impacts on Soil Nutrient Cycling in Harvard Forest and Greater Boston 2021-2022

Microbes are the driving force behind nutrient cycling within soils, secreting enzymes necessary to break down organic matter, immobilizing nutrients and C, or transferring nutrients to plant hosts. Even though nutrients would almost never move through ecosystems without microbes, we know little about how their composition and activity is related to ecosystem nutrient cycling, and their importance relative to plant and soil abiotic factors. In this study, we sought to determine which commonly measured soil microbial community characteristics best explain soil N and P cycling, and the relative contributions of microbial, plant, and abiotic factors in explaining these processes.

openCC0Apr 2025View details →

Simulations of Historical Impacts of Climate Change and Atmospheric Chemistry at Harvard Forest 1850-2019

This study is a model application aimed at simulating historical carbon (C), nitrogen (N), and water dynamics at a hardwood forest stand at Harvard Forest from 1850 to 2019. We applied the PnET-CN-daily model with a reconstructed historical climate and air quality scenario derived from field observations and regional model simulations. The model outputs were calibrated with field measurements conducted at Harvard Forest. We used field measurements of aboveground biomass (AGB) and foliar mass near the EMS tower to calibrate ecosystem C pools. Gross primary production (GPP), net ecosystem exchange (NEE), and respiration from the EMS eddy flux tower were used to calibrate C fluxes. Net N mineralization data from the chronic N amendment experiment, along with other N dynamics data collected at Harvard Forest, were used to calibrate N pools and fluxes. Additionally, evapotranspiration (ET) and soil water content from the EMS tower were used to calibrate water fluxes. To isolate the effects of individual environmental factors on C, N, and water dynamics, we ran the PnET-CN-daily model with a series of theoretical scenarios. These scenarios were developed based on the reconstructed historical climate and air quality data while keeping non-target input factors at pre-industrial levels. The considered environmental factors include climate, carbon dioxide (CO2) concentration, atmospheric N deposition, and ozone (O3) concentration. This approach allowed us to decompose the influence of each factor on ecosystem dynamics by comparing model outputs across different scenarios.

openCC (other)Dec 2022View details →

Urban Residential Surface and Subsurface Hydrology: Synergistic Effects of Low-Impact Features at the Parcel Scale

Accurately predicting the hydrologic effects of urbanization requires an understanding of how hydrologic processes are affected by low‐impact development practices. In this study, we explored how growing season surface runoff, deep drainage, and evapotranspiration on a residential parcel are affected by several low‐impact interventions, including three "impervious‐centric" interventions (disconnecting downspouts, disconnecting sidewalks, and adding a transverse slope to the driveway and front walk), two "pervious‐centric" interventions (decompacting soil and adding microtopography), and all possible "holistic" combinations. Results were compared to both a highly and moderately compacted baseline parcel under an average and a dry weather scenario for a temperate climate. We find that under reasonable assumptions for highly compacted soil, pervious areas are a major source of runoff and disconnecting impervious surfaces may be relatively less effective without improving soil conditions. Under both highly and moderately compacted soil conditions, combining efforts to decompact soil with impervious disconnection has a synergistic effect on reducing surface runoff and increasing deep drainage and evapotranspiration. All combinations of interventions enhance infiltration, but the partitioning of additional root zone water between deep drainage and evapotranspiration depends on the weather scenario. Importantly, when all low‐impact interventions are applied together, growing season deep drainage is higher than that from a vacant lot with no impervious surfaces. We infer that ecohydrologic interfaces between impervious and pervious areas are strong controls on urban hydrologic fluxes and that high‐resolution, process‐based models can be used to account for these interfaces and thereby improve predictions of the hydrologic effects of low‐impact interventions.

opencc-by-4.0Jan 2021View details →

Monthly aerosol emissions and GHG concentration projections from 2020-2025: modified SSP2-4.5 to account for COVID-19 impacts on sector activity

This repository holds the netcdf files for emissions and concentrations projected by the scenario SSP2-4.5, from the Scenario4MIPs database (<a href="https://esgf-node.llnl.gov/search/input4mips/">https://esgf-node.llnl.gov/search/input4mips/</a>), modified by the country and sector activity levels associated with lockdown, projected out for 5 years after 2020. The details of these activity estimates are available from <a href="https://github.com/Priestley-Centre/COVID19_emissions">https://github.com/Priestley-Centre/COVID19_emissions</a>. The methodology behind these calculations is based on <a href="https://github.com/Rlamboll/modify_COVID19_netCDF_Emissions/">https://github.com/Rlamboll/modify_COVID19_netCDF_Emissions/tree/endof2020</a>, a slight modification of the approach used in <a href="https://zenodo.org/record/3947917#.XxR_qyhKhPZ">https://zenodo.org/record/3947917#.XxR_qyhKhPZ</a> to have a different timeframe.  Funding was provided by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement nos. 820829 (CONSTRAIN) <a href="http://constrain-eu.org/">http://constrain-eu.org/</a>

opencc-by-4.0Aug 2023View details →

Data to 'The updated and improved method for water scarcity impact assessment in LCA, AWARE2.0'

This dataset includes the AWARE2.0 characterization factors as documented in the article "The updated and improved method for water scarcity impact assessment in LCA, AWARE2.0" (<a href="https://www.doi.org/10.1111/jiec.70023" target="_blank" rel="noopener">DOI: 10.1111/jiec.70023</a>). When using the dataset in your own work, please cite the article and provide reference to this zenodo repository. For importing the country-level characterization factors into LCA software, please see the AWARE2.0 implementations (openLCA, SimaPro, brightway2) in IMPACT World+, version 2.1: <a title="IMPACT World+ version 2.1" href="https://doi.org/10.5281/zenodo.14041258">https://doi.org/10.5281/zenodo.14041258</a> <h3>Content</h3> - native resolution (monthly, watershed scale): <ul> <li>AWARE20_Native_CFs_geospatial.gpkg: Geospatial file containing the AWARE2.0 basins as polygons with associated monthly and annual CFs</li> <li>AWARE20_Native_CFs_geospatial.kmz: Version of AWARE20_Native_CFs_geospatial.gpkg for GoogleEarth</li> <li>AWARE20_Native_CFs.xlsx: AWARE2.0 CFs on basin level (monthly and annual) and associated water consumption used for weighting</li> <li>AWARE20_Intermediate_Variables.xlsx: Intermediate Variables from the calculation of the AWARE2.0 CFs, such as the longterm average natural and actual water availability, the AMDs, the EFRs, etc.</li> <li>figures_AWARE_AWARE20_comparison_all_basins.zip: Figures comparing CFs, AMDs, Natural and Actual Availability, EWRs, and EFR coefficients between AWARE and AWARE2.0, for each of the 8149 basins individually. Consult these figures for a visual impression of how and why CFs might have changed between AWARE and AWARE2.0.</li> </ul> - spatiotemporal aggregations: <ul> <li>AWARE20_Countries_and_Regions.xlsx: AWARE2.0 CFs aggregated according to geography definitions of GLAM and ecoinvent <a href="https://geography.ecoinvent.org/#version-2-5-ecoinvent-3-10" target="_blank" rel="noopener">(version 2.5, applicable to ecoinvent 3.10) </a></li> <li>AWARE20_Subnational_Resolution.xlsx: AWARE2.0 CFs aggregated to subnational resolution, using the GADM dataset version 4.1 (<a href="https://gadm.org/old_versions.html" target="_blank" rel="noopener">https://gadm.org/old_versions.html</a>)</li> <li>AWARE20_Crop_Specific.xlsx: AWARE2.0 CFs aggregated according to geography definitions of ecoinvent <a href="https://geography.ecoinvent.org/#version-2-5-ecoinvent-3-10" target="_blank" rel="noopener">(version 2.5, applicable to ecoinvent 3.10)</a>, using crop-specific irrigation water consumption for 27 crop classes as spatiotemporal weights. See readme sheet in Excel file for more information.</li> </ul>   <h3>Changes:</h3> <ul> <li>v1.0.1: <ul> <li>addition of crop-specific spatiotemporal aggregations (AWARE20_Crop_Specific.xlsx)</li> </ul> </li> <li>v1.0.0 (corresponding to published article): <ul> <li>update of readme sheets with appropriate references to corresponding article</li> <li>update of reference "Müller Schmied et al. (2024)"</li> <li>added file: AWARE20_Subnational_Resolution.xlsx</li> </ul> </li> <li> v0.0.3: <ul> <li>use bug-fixed WaterGAP2.2e data from Sept 2023</li> <li>added country and subnational aggregations</li> <li>changed "NoData" to "NotDefined" in the tables</li> <li>added gridcell pHWC to intermediate variables</li> <li>corrected table of water consumption data without post-processing in "Intermediate_Variables"</li> </ul> </li> </ul>   <h3>Caveats:</h3> <ul> <li>Spatial CF aggregations for treaties: <ul> <li>Due to the creation date of the data set, the BRICS aggregations in AWARE20_Countries_and_Regions.xlsx do not include the states that joined after 2023. In AWARE20_Crop_Specific.xlsx, the 10-member BRICS is labeled BRICS+.</li> </ul> </li> </ul>

opencc-by-4.0Apr 2024View details →

On the Moreau–Jean scheme with the Frémond impact law: energy conservation and dissipation properties for elastodynamics with contact, impact and friction — data

This deposit contains the data output of the systems described in <a href="https://hal.science/hal-04230941">On the Moreau–Jean scheme with the Frémond impact law. Energy conservation and dissipation properties for elastodynamics with contact impact and friction.</a> The codes that generated this data are available in another <a href="../records/10953181">deposit</a> archived on Zenodo, as well as in a GitHub repository archived on <a href="https://archive.softwareheritage.org/swh:1:dir:33ff6d960b70505c7939c0ce21c039cabbe1351c;origin=https://github.com/nickcollins-craft/On-the-Moreau-Jean-scheme-with-the-Fremond-impact-law;visit=swh:1:snp:72aede3d3a464732a36ef79c20ef07eebd1f9918;anchor=swh:1:rev:b63b68c25e72d23d7d9ee30225165fa0ebffb3c2">Software Heritage</a>, which is the preferred method of obtaining the codes. Two of the files in this deposit ("deformed_sliding_block_mesh.png" and "sliding_block_mesh.png") are required for one of the codes in the code deposit to run successfully ("block_mesh_plot.py", with the files assumed to be located in the folder specified in the data_folder variable of the file "path_file.py"), but the deposits are otherwise independent.

opencc-by-4.0Mar 2024View details →

Dataset of "A Monte Carlo Approach for Simulating Electrical Conductivity in Highly Porous Ceramic Composites: Impact of Internal Structure"

3D structure of lanthanum strontium manganite and yttria-stabilized zirconia composites is predicted based on conductivity measurements using Monte Carlo 3D equivalent circuit network approach. Validation experimental impedance spectra; scanning electron micrographs; cross sections of model simulation or prediction (MSP).

opencc-by-4.0Jun 2022View details →

Data from: Basin-scale biogeochemical and ecological impacts of islands in the tropical Pacific Ocean

Abstract In the relatively unproductive waters of the tropical ocean, islands can enhance phytoplankton biomass and create hotspots of productivity and biodiversity that sustain upper trophic levels, including fish that are crucial to the survival of islands’ inhabit- ants. This phenomenon, termed the island mass effect 65 years ago, has been widely described. However, most studies focused on individual islands, and very few documented phytoplankton community composition. Consequently, basin-scale impacts on phytoplankton biomass, primary production and biodiversity remain largely unknown. Here we systematically identify enriched waters near islands from satellite chlorophyll concentrations (a proxy for phytoplankton biomass) to analyse the island mass effect for all tropical Pacific islands on a climatological basis. We find enrichments near 99% of islands, impacting 3% of the tropical Pacific Ocean. We quantify local and basin-scale increases in chlorophyll and primary production by contrasting island-enriched waters with nearby waters. We also reveal a significant impact on phytoplankton community structure and biodiversity that is identifiable in anomalies in the ocean colour signal. Our results suggest that, in addition to strong local bio- geochemical impacts, islands may have even stronger and farther-reaching ecological impacts.   Data set and method For each island, an algorithm detected the Island Mass Effect (IME) from climatological satellite chlorophyll maps as a contour enclosing the island and surrounding high-chlorophyll waters, termed IME region. A reference (REF) region of the same size was detected alongside each IME region, enclosing nearby non-IME waters. The IME and REF regions were used to build the IME database described in Messié et al. (2022), that includes variables related to satellite chlorophyll, primary production, and PHYSAT phenoclass diversity metrics in IME and REF regions on a climatological basis. This data set includes 4 files: <ul> <li>island_database.csv: information regarding the 664 islands and shallow reefs where the IME detection was applied</li> <li>IME_masks.nc: monthly climatological masks for the IME and REF regions for all islands,</li> <li>IME_database.nc: IME database as a function of island and climatological month (chlorophyll, primary production, and phenoclass-derived variables calculated within the IME and REF masks).</li> <li>PHYSAT_climatology.nc: climatological maps for each PHYSAT phenoclass, used to calculate phenoclass-derived variables in the IME database.</li> </ul> See details regarding data sources and calculations in <a href="https://rdcu.be/cO4qr">Messié et al. (2022)</a>.

opencc-by-4.0Aug 2022View details →

Benchmarking on Microservices Configurations and the Impact on the Performance in Cloud Native Environments

The peer reviewed publication for this dataset has been published in LCN 2022, 47th Annual IEEE Conference on Local Computer Networks. Please cite this paper when referring to the dataset: https://www.eurecom.fr/publication/6971. Cloud-native and containerization have changed the way to develop and deploy applications. Cloud-native rethinks the application architecture by embracing a microservice approach, where each microservice is packaged into containers to run in a centralized or an edge cloud. When deploying the container running the micro-service, the tenant has to specify the needed computing resources to run their workload in terms of the amount of CPU and memory limit. However, it is not straightforward for a tenant to know in advance the computing amount that allows running the microservice optimally. This will have an impact not only on the service performances but also on the infrastructure provider, particularly if the resource overprovisioning approach is used. To overcome this issue, we conduct an experimental study aiming to detect if a tenant's configuration allows running its service optimally. We run several experiments on a cloud-native platform, using different types of applications under different resource configurations. The obtained results are presented in the accepted IEEE LCN paper (https://www.eurecom.fr/publication/6971) and are shared in this dataset. The datasets are collected for 3 types of applications: Web servers written in python and Golang, RabbitMQ data broker and the OpenAirInterface 5G Core network function AMF (Access and Mobility Management Function).   Web Servers: files:  golang-web-server-performance.csv, python-web-server-performance.csv We used Golang and Python-based web servers for the test. Each request to the web server returns a video of a size 43 MB. For testing we used ApacheBench, a command-line program used for benchmarking HTTP web servers. ApacheBench allows parallel requests from multiple clients. For each web server instance we send a number of requests ranging from 100 to 1000 and a concurrency level between 1 and 100, representing the number of parallel clients performing the requests. The information available in the dataset are as follows: time: timestamp of collection of metrics. ram_limit: the memory allocated to the container in megabytes. cpu_limit: the CPU allocated to the container. ram_usage: the amount of memory used by the container at the time of the metrics collection in byte. cpu_usage: the amount of CPU used by the container at the time of the metrics collection. n: the number of requests sent to the container. c: the concurrency level in the requests. lat50: the least response time for the best 50% requests in microseconds. lat66: the least response time for the best 66% requests in microseconds. lat75: the least response time for the best 75% requests in microseconds. lat80: the least response time for the best 80% requests in microseconds. lat90: the least response time for the best 90% requests in microseconds. lat95: the least response time for the best 95% requests in microseconds. lat98: the least response time for the best 98% requests in microseconds. lat99: the least response time for the best 99% requests in microseconds. lat100: the least response time in microseconds.   5G Core network’s AMF: file: amf-performance.csv For testing we use my5G-RANTester, a tool for emulating control and data planes of the UE and gNB (5G base station). The number of simultaneous registration requests that are sent to each instance of the AMF varies between 10 and 400. The information available in the dataset are as follows: time: timestamp of collection of metrics. ram_limit: the memory allocated to the container in megabytes. cpu_limit: the CPU allocated to the container. ram_usage: the amount of memory used by the container at the time of the metrics collection in byte. cpu_usage: the amount of CPU used by the container at the time of the metrics collection. n: the number of parallel registration requests sent to the AMF. mean: the mean registration time for all the registration requests in microseconds. lat50: the median registration time for registration requests in microseconds. lat75: the least registration time for the best 75% registration requests in microseconds. lat80: the least registration time for the best 80% registration requests in microseconds. lat90: the least registration time for the best 90% registration requests in microseconds. lat95: the least registration time for the best 95% registration requests in microseconds. lat98: the least registration time for the best 98% registration requests in microseconds. lat99: the least registration time for the best 99% registration requests in microseconds. lat100: the least registration time in microseconds.   RabbitMQ data broker: file: rabbitmq-performance.csv For testing we used RabbitMQ PerfTest which is a throughput testing tool that simulates basic workloads and provides the throughput and the time that a message takes to be consumed by a consumer. For each deployed RabbitMQ server we used a number of producers and consumers that ranges from 50 to 500. Each producer sends messages to the broker with a rate of 100 messages per second for a period of time of 90 seconds. The information available in the dataset are as follows: time: timestamp of collection of metrics. ram_limit: the memory allocated to the container in megabytes. cpu_limit: the CPU allocated to the container. ram_usage: the amount of memory used by the container at the time of the metrics collection in byte. cpu_usage: the amount of CPU used by the container at the time of the metrics collection. n: the number of producers sending messages to the RabbitMQ server. Min: the minimum consumption time for the producer messages. lat50: the median consumption time for the producer messages. lat75: the least consumption time for the best 75% messages in microseconds. lat95: the least consumption time for the best 95% messages in microseconds. lat99: the least consumption time for the best 99% messages in microseconds.

opencc-by-4.0May 2024View details →

Dataset for "Impact of the flow-field distribution channel cross-section geometry on PEM fuel cell performance: stamped vs. milled channel"

Experimental data comprises raw data from load curve characterisation of a PEM fuel cell used for the validation of the mathematical model. Model data comprise of space-dependent values of hydrogen and oxygen concentration, local current densities, gas pressures and gas velocities in the modelled cell. These data were used for the investigation of the effect of different geometric parameters of flow-field channels on the performance of a PEM fuel cell.

opencc-by-4.0Mar 2024View details →

Dataset of "Impact of Carbon Corrosion and Denitrogenation on the Deactivation of Fe-N-C Catalysts in Alkaline Media"

In this work, we use a gas diffusion electrode half-cell coupled with inductively coupled plasma mass spectrometry (GDE-ICP-MS) to quantify the Fe dissolution rates in the potential range between 0.93 and 1.5 VRHE. It is shown that Fe dissolution accelerates with increased anodic potential and temperature while it is independent on the presence/absence of O2. The onset potential of Fe dissolution at room temperature agrees with the reported onset potentials of carbon corrosion and denitrogenation, C and N being oxidized to gaseous COx and NOx species, respectively. This correlation supports that the electrochemical oxidation of the N-C matrix triggers the observed catalyst demetallation in these conditions. Using a set of ex situ physicochemical characterization techniques, including spectroscopy and microscopy, the various degrees of degradation under three sets of experimental conditions of interest (O2-RT, O2-HT, and Ar-HT, where RT = 22℃ and HT = 62℃) are rationalized. Combining the GDE-ICP-MS technique and post-mortem analyses, this work provides novel insights into the degradation pathways of various Fe, N, and C species during start-stop events, which may inspire the next generation of durable Fe-N-C catalysts for anion exchange membrane fuel cells.