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1,444 results for “mitigation”
Data from: Chronic Rapamycin administration via drinking water mitigates the pathological phenotype in a Krabbe disease mouse model through autophagy activation.
<p>ABSTRACT </p><p>Krabbe disease (KD) is a rare disorder caused by a deficiency of the lysosomal enzyme galactosylceramidase (GALC), resulting in the accumulation of the cytotoxic metabolite psychosine (PSY) in the nervous system. This accumulation triggers demyelination and neurodegeneration. Despite ongoing research, the underlying pathogenic mechanisms remain incompletely understood, and there is currently no cure available.</p><p>Previous studies from our lab revealed the presence of autophagy dysfunctions in KD pathogenesis, as evidenced by the presence of p62-tagged protein aggregates in the brains of KD mice and increased p62 levels in the KD sciatic nerve. We also demonstrated that the autophagy inducer Rapamycin (RAPA) can partially restore the wild-type (WT) phenotype in KD primary cells by reducing the number of p62 aggregates.</p><p>In this study, we tested RAPA in the Twitcher (TWI) mouse, a spontaneous KD mouse model. We administered the drug ad libitum via drinking water (15 mg/L) starting from post-natal day (PND) 21-23. We longitudinally monitored the motor performance of the mice through grip strength and rotarod tests, along with various biochemical parameters related to KD pathogenesis (i.e. autophagy markers expression, myelination, astrogliosis, and PSY accumulation).</p><p>Our findings demonstrate that RAPA significantly enhances motor functions at specific treatment time points and reduces astrogliosis in TWI brain, spinal cord, and sciatic nerves. Using western blot and immunohistochemistry, we observed a decrease in p62 aggregates in TWI nervous tissues, which corroborates our earlier in-vitro results. Furthermore, RAPA treatment partially reduces PSY levels in the spinal cord.</p><p>In conclusion, our results support the consideration of RAPA as a supportive therapy for KD. Importantly, as RAPA is already available in pharmaceutical formulations for clinical use, its potential for KD treatment can be promptly evaluated in clinical trials.</p>
The potential of nitric acid-functionalized carbon nanotubes to mitigate bacterial biofilms
<p>Pristine multi-walled carbon nanotubes were functionalized with nitric acid, followed by thermal treatment at 600 °C, and incorporated into a poly(dimethylsiloxane) matrix. The composites were characterized and their antibiofilm activity and antibacterial mechanisms were assessed by biofilm cell culturability and flow cytometry, respectively.</p>
Agricultural Mitigation Initiatives
<p>This dataset is an ongoing effort to explore the main international mitigation initiatives related to the agrarian sector. The dataset has been created by a research team based at the Geneva Graduate Institute since 2020 based on studies of the sector, conversations with experts and internet searches. The internet search has been conducted using key words, including notions such as:</p><ul><li>Climate change mitigation initiatives/projects/programs/campaigns</li><li>netzero</li><li>nature based solutions</li><li>natural capital</li><li>ecosystem services</li><li>carbon market initiatives</li><li>low carbon agriculture</li><li>afforestation initiatives</li><li>Soil carbon initiatives</li><li>Paludiculture initiatives</li><li>Land use change and climate change mitigation</li></ul><p>Findings have been narrowed down to include only initiatives directly or indirectly related to the agrarian sector. These included netzero campaigns, climate action coalitions, national mitigation programs, non-governmental projects and other mitigation initiatives. Many of the findings were interconnected. For example, a mitigation initiative could be part of a wider mitigation program or coalition. We have therefore tried to reflect these interconnections in the structure of the dataset. For each entry we also included a description with the main characteristics of the entry (coalition, campaign, program or project) the main thematic of the entry and the main actors involved. The main thematic found were:</p><ul><li>carbon sequestration in soils</li><li>advocacy for action</li><li>food systems transformations (climate smart agriculture)</li><li>Land use management</li><li>natural capital initiatives</li><li>carbon accounting standards</li><li>biodiversity conservation and restoration</li><li>technical guidelines for GHGs emission reductions in agriculture</li><li>dissemination</li><li>ecosystems' accounting</li><li>pollution and waste reduction</li></ul><p>The dataset also includes a second spreadsheet where we have started to map some of the actors of the carbon market involved in the development, certification, validation and verification of GHGs emission reductions and removals for agrarian initiatives. </p>
Database of best practice for pondscape NbS for CC adaptation and mitigation
<p>We built an inventory (database) of Nature-based Solutions (NbS) actions (creation, restoration, and management) in ponds and pondscapes (ponds at the landscape scale) in a diversity of social-ecological settings to assess the best practices. We formulated an online questionnaire that was shared with pond stakeholders. The questionnaire asked general (e.g., number of ponds, area of the pondscape, etc.) and specific (e.g., costs of the action, stakeholders involved, etc.) information on the NbS action implemented, and on 11 associated Nature's Contributions to People (NCPs). Among the NCPs we included, for instance, habitat creation for biodiversity, regulation of climate, learning or physical and physiological experiences. The database contains information gathered through the questionnaire, research papers and relevant web pages and platforms.</p> <p>We used three different approaches to obtain information on NbS actions implemented in ponds/pondscapes and the associated NCPs mainly focusing on Europe and Uruguay: 1) the development of a user-friendly online questionnaire on NbS implemented in ponds/pondscapes and associated NCPs, which was shared in the form of a survey through the platform Survey Monkey with PONDERFUL members and pond Stakeholders; 2) the search of information in research papers; and 3) the search of information on web pages such as <a href="https://oppla.eu/" target="_blank" rel="noopener">https://oppla.eu</a>, <a href="https://renature-project.eu/" target="_blank" rel="noopener">https://renature-project.eu</a>, <a href="https://climate-adapt.eea.europa.eu/" target="_blank" rel="noopener">https://climate-adapt.eea.europa.eu</a>, <a href="https://una.city/" target="_blank" rel="noopener">https://una.city</a>. We requested permissions from the respondents to make the data available.</p>
User study data: Nudges to Mitigate Confirmation Bias during Web Search for Opinion Formation, automatic vs. reflective study
<p>Data of two user studies (282 and 307 participants), investigating the risks and benefits of warning labels with and without obfuscations to mitigate confirmation bias during web search on debated topics.</p> <p> </p> <p>Study Variables (study 1 and study 2)</p> <p> </p> <p> display_con: Search result display<br> - Study 1<br> - 1: targeted warning label with obfuscation<br> - 2: random warning label with obfuscation<br> - 3: regular (no intervention)<br> - Study 2<br> - 1: targeted warning label with obfuscation<br> - 2: targeted warning label without obfuscation<br> - 3: random warning label with obfuscation<br> - 4: random warning label without obfuscation<br> - 5: regular (no intervention)<br>- CRT_cat: Cognitive reflection<br> - 1: intuitive<br> - 2: analytic<br>- topic: Assigned debated topic<br> - 1: Is drinking milk healthy for humans? <br> - 2: Is homework beneficial?<br> - 3: Should people become vegetarian?<br> - 4: Should students have to wear school uniforms?<br>- clicksup_prop: Clicks on attitude-confirming (AC) search results (proportion of all clicks)<br>- clickwarn_prop: Clicks on warning label (WL) search results (proportion of all clicks)<br>- show_clicked: Clicks on show-button (number of clicks, only in conditions with obfuscation)<br>- accuracy_bias: Accuracy bias estimation (Difference between a) observed bias (as the proportion of attitude-confirming clicks) and b) perceived bias (reported in the post-interaction questionnaire and re-coded into values from 0 to 1), positive values indicate an overestimation of bias)<br>- att_change: Attitude change (Difference between attitude reported in the pre-interaction questionnaire and the post-interaction questionnaire. Negative values indicate an attitude change in the attitude-opposing direction, while positive values indicate an attitude strengthening in the attitude-supporting direction.)<br>- knowledge_1: Self-reported prior knowledge (Reported on a seven-point Likert scale ranging from non-existent to excellent as a response to how they would describe their knowledge on the topic they were assigned to)<br>- N_clicks: Cumulative clicks (Number of all clicks on search results)<br>- NFC: Need for Cognition (Mean response to 4-item subset of the NFC questionnaire)<br>- UX_usability: Usability (Mean of responses on a seven-point Likert scale to the module "usability"from the meCUE 2.0 questionnaire)<br>- UX_usefulness: Usefulness (Mean of responses on a seven-point Likert scale to the module "usefulness"from the meCUE 2.0 questionnaire)</p>
Resources for Mitigating Chemotherapy Side Effects through Targeted Gamma-Ray Delivery and CNNs
<p>This repository includes datasets and code used in the study "Mitigating Chemotherapy Side Effects through Targeted Gamma-Ray Delivery and Convolutional Neural Networks." The resources comprise:<br>- Binding Affinity Data: Used for simulations.<br>- Brain Tumor MRI and Chest CT Scan Datasets: Used for model training.<br>- Lightweight Deep CNN: Code for building and testing models.</p>
Cyberhate that targets people who are plus-size in the news: The role of bystanders in mitigating social pathologies (CYBERPLUS)
<p>The dataset was created for the project "Cyberhate that targets people who are plus-size in the news: The role of bystanders in mitigating social pathologies (CYBERPLUS)". The data was collected between July 12 and July 26, 2024, from 1,030 young Czech people aged 16-25. The survey asked young people about their sociodemographic information, attitudes toward and perceptions of entitativity of three groups (overweight people, underweight people, people with physical disabilities), group identification, bystander appraisals and behavioural intentions, hate speech perception, and internet use. It included an experimental part in which the participants were exposed as bystanders to social media news posts about overweight people and comments under the posts. The dataset is accompanied by a data dictionary and a technical report.</p>
Analyzing and Mitigating (with LLMs) the Security Misconfigurations of Helm Charts from Artifact Hub
<p>In the corresponding scientific paper, we proposed a pipeline to mine Helm charts from Artifact Hub, a popular centralized repository, and analyze them using state-of-the-art open-source tools like Checkov and KICS. First, such a pipeline runs several chart analyzers and identifies the common and unique misconfigurations reported by each tool. Secondly, it uses LLMs to suggest mitigation for each misconfiguration. Finally, the chart refactoring previously generated is analyzed again by the same tools to see whether it satisfies the tool's policies.</p> <p>In this dataset, you can find all the Helm chart templates downloaded from Artifact Hub (available in June 2024), all the outputs of the tools analyzing such templates, the CSV result files with all LLM queries and answers, and the snippets selected for the manual analysis.</p>
Emilia-Romagna coastal area NBS (OAL ITALY) for storm surge mitigation
<p>Within the framework of the OPEn-air laboRAtories for Nature baseD solUtions to Manage environmental risks (OPERANDUM) project, the seagrass NBS is presented within a simulation design methodology consisting of the comparison between validated wave numerical simulations for the present/ future climate, and modified wave simulations with marine seagrass. Ten years of WWIII simulations have been executed to generate the wave climatology, particularly over the Emilia-Romagna coastal strip for the present (2010-19) and future climate (2040-49) using MedCordex winds (based on RCP8.5). The WWIII model was modified to include a modified bottom dissipation stress due to submerged vegetation, thereby incorporating the NBS4 as a potential mechanism for wave amplitude reduction. The seagrass species <em>‘Zostera marina’</em> was chosen in this study and an along-shore seagrass belt was first inserted in WWIII and sensitivity experiments were carried out to assess the effects of different types of seagrass landscape designs in the Bellocchio beach. Simulation experiments with and without seagrass (NBS4) were carried out for the present and future climates. Based on the present and future climate simulations, it is noted that the seagrass landscaping is an important aspect in the numerical modelling of vegetation. A combination of broken vegetation stripes and clusters were seen to be effective in reduction of wave energy at the coast in comparison to other landscape designs. The wave height comparisons in the Bellocchio beach, with and without vegetation showed a considerable reduction in wave heights specifically in the higher ranges for both the present and future climates. There exists a strong seasonality in the attenuation rates along the coastal belt with higher attenuations during winter and comparatively lower in summer. In comparison to the present climate, a slightly increased rate of mean attenuation is expected in the future scenarios. Overall, the Zostera Marina seagrass applied for the Emilia-Romagna coastal belt was found to be efficient in reduction of wave energy (> 50%). The limitation being that the experiments were done with rigid seagrass and in the future, we look for advanced parameterization using flexible seagrass.</p> <p>This dataset contains wave model outputs for the OAL-ITALY, mainly:</p> <ul> <li>Bathymetry of the model domain, Spatial maps of mean significant wave height (Hs in m) for present (2010-19) and future climate (2040-49), Seagrass belt position in the Bellocchio beach, Time-series comparison of Hs, with & without vegetation, and Wave attenuation maps.</li> </ul> <ul> <li>Selected locations (station map) for the time series in the Emilia-Romagna coastal belt during the period 2010-19, and 2040-49 (8 stations), Selected locations (station map) in the Emilia-Romagna coastal belt for the time series comparison (with and without vegetation) during the period 2010-19, and 2040-49 (5 stations).</li> </ul> <ul> <li>WW3 time series of wave parameters (wave height, peak period, & direction) for 8 stations in the Emilia-Romagna coastal belt (2010-19, present climate).</li> <li>WW3 time series of significant wave height (Hs in metres) with and without vegetation for 5 stations in the Emilia-Romagna coastal belt (2010-19, present climate).</li> <li>WW3 time series of wave parameters (wave height, peak period, & direction) for 8 stations in the Emilia-Romagna coastal belt (2040-49, future climate).</li> <li>WW3 time series of significant wave height (Hs in metres) with and without vegetation for 5 stations in the Emilia-Romagna coastal belt (2040-49, future climate).</li> </ul>
Modeling robust COVID-19 intensive care unit occupancy thresholds for imposing mitigation to prevent exceeding capacities
<p>Simulation output files for 'Modeling robust COVID-19 intensive care unit occupancy thresholds for imposing mitigation to prevent exceeding capacities'.</p> <p>Simulating COVID-19 transmission and hospital burden to assess at which intensive care unit (ICU) occupancies mitigation, that reduces transmission, needs to be triggered to avoid exceeding ICU capacity limits, using the city of Chicago, Illinois as an example.</p> <p>Manuscript is under review for scientific publication, (see <a href="https://www.medrxiv.org/content/10.1101/2021.06.27.21259530v1">preprint on medRxiv</a>) and scripts are available from the GitHub repository at https://github.com/numalariamodeling/ICUtrigger_covid_chicago_paper_2021. </p> <p>Simulation output files uploaded per scenario including projected COVIID-19 transmission and burden trajectories for Chicago city for March 2020 to May 2021 per day.</p> <p>Simulation scenarios:</p> <p><reopening % above ICU capacity>_<delay after reaching ICU threshold>_<%mitigation>_<common simulation name> i.e. `50perc_1daysdelay_pr6_triggeredrollback_reopen`</p> <ul> <li>`emodl` file <ul> <li>required file for COVID-19 transmission model in the <a href="https://docs.idmod.org/projects/cms/en/latest/index.html">Compartmental Modeling Software</a> (see <a href="https://github.com/numalariamodeling/ICUtrigger_covid_chicago_paper_2021">GitHub repository</a> for details)</li> </ul> </li> <li>sampled_parameters.csv <ul> <li>simulation input and scenario parameters, (nrow=4400, 400 unique parameter combinations * 11 scenario values)</li> </ul> </li> <li>rt_trajectoriescovidregion_11.csv <ul> <li>estimated reproductive numbers per trajectory for complete timeline per day</li> </ul> </li> <li>trajectoriesDat_region_11_traces.csv <ul> <li>filtered to include top 100 trajectories fitted to ICU data</li> </ul> </li> <li>trajectoriesDat_region_trimfut.csv <ul> <li>truncated to only include projections after September 1st 2020</li> </ul> </li> </ul> <p>The folder `mainfigures_csvs.zip` includes processed simulation output data for the publication figures.</p>
Data and ancillary data for publication: Natural infrastructure and water erosion mitigation in the Andes
<p>The data contain information on the effectiveness of natural infrastructure to mitigate soil erosion. Data were compiled from 118 case studies from the Andean region, whereby information on natural infrastructure interventions, soil erosion and soil quality were tabulated and analysed.</p> <p>The data contains the following documents:<br> -Database with data on soil erosion, soil quality for different types of natural infrastructure (118 case studies)<br> -Metadata<br> -Summary of terms used in the systematic review of the literature (in Spanish and English)<br> -List of bibliographic data sources that were searched with the search terms<br> -Full bibliographic references of all 118 case studies</p> <p><strong>Full reference </strong></p> <p><em>Vanacker V, Molina A, Rosas-Barturen M, Bonnesoeur V, Román-Dañobeytia F, Ochoa-Tocachi B, Buytaert W (2022). The effect of natural infrastructure on water erosion mitigation in the Andes. </em></p> <p> </p> <p> </p>
Raw data for the journal article "Cracks as efficient tools to mitigate flooding in gas diffusion electrodes used for the electrochemical reduction of carbon dioxide"
<p>This data set corresponds to the article by Kong et al. entitled "Cracks as efficient tools to mitigate flooding in gas diffusion electrodes used for the electrochemical reduction of carbon dioxide", published in Small Methods</p>
Van de Ven et al 2022_Mitigation_DATASET
<p>This dataset contains the underlying scenario protocol, input (socioeconomic assumptions), and output (model results) for the study by Van de Ven et al. on post-Glasgow climate action and feasibility gap</p>
Data archive for "Flight behaviour of Red Kites within their breeding area in relation to local weather variables: Conclusions with regard to wind turbine collision mitigation"
<p>The archive contains the data files to reproduce the results presented in the article “Flight behaviour of Red Kites within their breeding area in relation to local weather variables: Conclusions with regard to wind turbine collision mitigation” published in the Journal of Applied Ecology.</p>
Resource heterogeneity leads to unjust effort distribution in climate change mitigation
<p>Climate change mitigation is a shared global challenge that involves the collective action of a set of individuals with different tendencies to cooperation. However, we lack an understanding of the effect of resource inequality when diverse actors interact together toward a common goal. Here, we report the results of a collective-risk dilemma experiment in which groups of individuals were initially given either equal or unequal endowments. We found that the effort distribution was highly inequitable, with participants with fewer resources contributing significantly more to the public goods than the richer - sometimes twice as much. An unsupervised learning algorithm classified the subjects according to their individual behavior, finding the poorest participants within two "generous clusters'" and the richest into a "greedy cluster''. Our results suggest that policies would benefit from educating about fairness and reinforcing climate justice actions addressed to vulnerable people instead of focusing on understanding generic or global climate consequences.</p> <p>Vicens J, Bueno-Guerra N, Gutiérrez-Roig M, Gracia-Lázaro C, Gómez-Gardeñes J, Perelló J, et al. (2018) Resource heterogeneity leads to unjust effort distribution in climate change mitigation. PLoS ONE 13(10): e0204369. https://doi.org/10.1371/journal.pone.0204369</p>
Climate change impact and mitigation cost data - The economically optimal warming limit of the planet
<p>This climate change impact data (future scenarios on temperature-induced GDP losses) and climate change mitigation cost data (REMIND model scenarios) is published under doi: 10.5281/zenodo.3541809 and used in this paper:</p> <p>Ueckerdt F, Frieler K, Lange S, Wenz L, Luderer G, Levermann A (2018) The economically optimal warming limit of the planet. Earth System Dynamics. <a href="https://doi.org/10.5194/esd-10-741-2019">https://doi.org/10.5194/esd-10-741-2019</a></p> <p>Below the individual file contents are explained. For further questions feel free to write to Falko Ueckerdt (ueckerdt@pik-potsdam.de).</p> <p> </p> <p><strong>Climate change impact data</strong></p> <p>File 1: Data_rel-GDPpercapita-changes_withCC_per-country_all-RCP_all-SSP_4GCM.csv</p> <p>Content: Data of relative change in absolute GDP/CAP levels (compared to the baseline path of the respective SSP in the SSP database) for each country, RCP (and a zero-emissions scenario), SSP and 4 GCMs (spanning a broad range of climate sensitivity). Negative (positive) values indicate losses (gains) due to climate change. For figure 1a of the paper, this data was aggregated for all countries.</p> <p> </p> <p>File 2: Data_rel-GDPpercapita-changes_withCC_per-country_all-SSP_4GCM_interpolated-for-REMIND-scenarios.csv</p> <p>Content: Data of relative change in absolute GDP/CAP levels (compared to the baseline path of the respective SSP in the SSP database) for each country, SSP and 4 GCMs (spanning a broad range of climate sensitivity). The RCP (and a zero-emissions scenario) are interpolated to the temperature pathways of the ten REMIND model scenarios used for climate change mitigation costs. Hereby the set of scenarios for climate impacts and climate change mitigation are consistent and can be combined to total costs of climate change (for a broad range of mitigation action).</p> <p> </p> <p>File 3: Data_rel-GDPpercapita-changes_withCC_per-country_SSP2_12GCM_interpolated-for-REMIND-scenarios.csv</p> <p>Content: Same as file 2, but only for the SSP2 (chosen default scenario for the study) and for all 12 GCMs. Data of relative change in absolute GDP/CAP levels (compared to the baseline path of the respective SSP in the SSP database) for each country, SSP-2 and 12 GCMs (spanning a broad range of climate sensitivity). The RCP (and a zero-emissions scenario) are interpolated to the temperature pathways of the ten REMIND model scenarios used for climate change mitigation costs. Hereby the set of scenarios for climate impacts and climate change mitigation are consistent and can be combined to total costs of climate change (for a broad range of mitigation action).</p> <p><br> In addition, reference GDP and population data (without climate change) for each country until 2100 was downloaded from the SSP database, release Version 1.0 (March 2013, <a href="https://tntcat.iiasa.ac.at/SspDb/">https://tntcat.iiasa.ac.at/SspDb/</a>, last accessed 15Nov 2019).</p> <p> </p> <p><strong>Climate change mitigation cost data</strong></p> <p>The scenario design and runs used in this paper have first been conducted in [1] and later also used in [2].</p> <p>File 4: REMIND_scenario_results_economic_data.csv</p> <p>File 5: REMIND_scenarios_climate_data.csv</p> <p>Content: A broad range of climate change mitigation scenarios of the REMIND model. File 4 contains the economic data of e.g. GDP and macro-economic consumption for each of the countries and world regions, as well as GHG emissions from various economic sectors. File 5 contains the global climate-related data, e.g. forcing, concentration, temperature.</p> <p>In the scenario description “FFrunxxx” (column 2), the code “xxx” specifies the scenario as follows. See [1] for a detailed discussion of the scenarios.</p> <p>The first dimension specifies the climate policy regime (delayed action, baseline scenarios):</p> <p>1xx: climate action from 2010<br> 5xx: climate action from 2015<br> 2xx climate action from 2020 (used in this study)<br> 3xx climate action from 2030<br> 4x1 weak policy baseline (before Paris agreement)</p> <p>The second dimension specifies the technology portfolio and assumptions:</p> <p>x1x Full technology portfolio (used in this study)<br> x2x noCCS: unavailability of CCS<br> x3x lowEI: lower energy intensity, with final energy demand per economic output decreasing faster than historically observed<br> x4x NucPO: phase out of investments into nuclear energy<br> x5x Limited SW: penetration of solar and wind power limited<br> x6x Limited Bio: reduced bioenergy potential p.a. (100 EJ compared to 300 EJ in all other cases)<br> x6x noBECCS: unavailability of CCS in combination with bioenergy</p> <p>The third dimension specifies the climate change mitigation ambition level, i.e. the height of a global CO2 tax in 2020 (which increases with 5% p.a.).</p> <p>xx1 0$/tCO2 (baseline)<br> xx2 10$/tCO2<br> xx3 30$/tCO2<br> xx4 50$/tCO2 <br> xx5 100$/tCO2<br> xx6 200$/tCO2<br> xx7 500$/tCO2<br> xx8 40$/tCO2<br> xx9 20$/tCO2<br> xx0 5$/tCO2</p> <p>For figure 1b of the paper, this data was aggregated for all countries and regions. Relative changes of GDP are calculated relative to the baseline (4x1 with zero carbon price).</p> <p> </p> <p>[1] Luderer, G., Pietzcker, R. C., Bertram, C., Kriegler, E., Meinshausen, M. and Edenhofer, O.: Economic mitigation challenges: how further delay closes the door for achieving climate targets, Environmental Research Letters, 8(3), 034033, doi:10.1088/1748-9326/8/3/034033, 2013a.</p> <p>[2] Rogelj, J., Luderer, G., Pietzcker, R. C., Kriegler, E., Schaeffer, M., Krey, V. and Riahi, K.: Energy system transformations for limiting end-of-century warming to below 1.5 °C, Nature Climate Change, 5(6), 519–527, doi:10.1038/nclimate2572, 2015.</p>
Parametric Study of the Radiative Load Distribution on the EU-DEMO First Wall Due to SPI-Mitigated Disruptions and in Steady-State (dataset)
<p>Database for reproducing the calculations presented in the publication "Parametric Study of the Radiative Load Distribution on the EU-DEMO First Wall Due to SPI-Mitigated Disruptions", submitted to <em>Fusion Engineering and Design</em>.</p> <p>Work carried out within the framework of the EUROfusion Consortium.</p>
Model-driven mitigation measures for reopening schools during the COVID-19 pandemic.
<p>Complete simulation-generated datasets analyzed in McGee et al. (2021) Model-driven mitigation measures for reopening schools during the COVID-19 pandemic. PNAS. In press at time of upload. (medRxiv 2021.01.22.21250282).</p> <p>Data is uploaded in tab-separated .csv files which have been compressed using gzip. Descriptions of data columns can be found in the column_descriptions.csv file.</p>
Data and code: Kuipers et al. (2023) Land use diversification may mitigate on-site land use impacts on mammal popultions and assemblages. Global Change Biology
<p>Zip folder conaining the data and code that support the findings of <em>Kuipers et al. (2023) Land use diversification may mitigate on-site land use impacts on mammal popultions and assemblages. Global Change Biology.</em></p> <p>The <em>Data_code.zip</em> folder contains four subfolders with the following files:</p> <ul> <li>Data_raw <ul> <li>AgriDiv_data.csv</li> <li>AgriDiv_metadata.docx</li> <li>Species_data.csv</li> <li>Species_metadata.docx</li> <li>Landscape_data.csv</li> <li>Landscape_metadata.docx</li> </ul> </li> <li>Data_derived <ul> <li>RIA_RSR_effect_sizes.csv</li> <li>MSA_effect_sizes.csv</li> </ul> </li> <li>Data_output <ul> <li>Response_estimation.csv</li> </ul> </li> <li>R_scripts <ul> <li>01_Effect_size_calculation.R</li> <li>02_Null_model_analysis.R</li> <li>03_Model_selection.R</li> <li>04_Model_analysis.R</li> <li>05_Response_estimation.R</li> <li>06_Figures.R</li> <li>README.md</li> </ul> </li> </ul>
Simulation results for study on pulsed electron lenses for space charge mitigation
<p>Simulation results for beam loss in the FAIR SIS100 synchrotron for a comprehensive study on pulsed electron lenses for space charge mitigation. The affiliated manuscript "Pulsed electron lenses for space charge mitigation" describing the study parameters is published on arxiv.org (https://arxiv.org/abs/2310.02365) and submitted for journal publication.</p> <p>For the "ffsc" files, each file contains the tabulated beam survival rate of 1000 simulated particles for a given bare tune. A file typically gathers results from scanning the betatron tune quadrant 18.5 <= Qx,y <= 19.0 in tune steps of 0.01.</p> <p>Explanation of file names:</p> <p>- "ffsc": using the fixed frozen Gaussian field map model for space charge (as established in https://doi.org/10.1103/PhysRevAccelBeams.25.054402 );</p> <p>- "nel": number of pulsed electron lenses placed symmetrically in the straight sections of the SIS100 ring;</p> <p>- "alpha": linear compensation degree, alpha=1.0 corresponds to a total electron lens tune implied tune shift equal to the linear rms-equivalent KV space charge tune shift;</p> <p>- "N": intensity in percent units of the FAIR design intensity for Uranium-28+ beams, i.e. N=100 corresponds to the FAIR design intensity;</p> <p>- "2D" or "3D": the 3D results correspond to the full simulation model with (nonlinear) synchrotron motion, the 2D results assume a fixed longitudinal phase-space distribution and only simulate the transverse dynamics (thus, periodic resonance crossing is suppressed by construction).</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.