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289 results for “data reduction”
Data from: Evidence for reductions in physical and chemical plant defense traits in island flora
<p>Reduced defense against large herbivores has been suggested to be part of the "island syndrome" in plants. However, empirical evidence for this pattern is mixed. In this paper, we present two studies that compare putative physical and chemical defense traits from plants on the California Channel Islands and nearby mainland based on sampling of both field and common garden plants. In the first study, we focus on five pairs of woody shrubs from three island and three mainland locations and find evidence for increased leaf area, decreased marginal leaf spines, and decreased concentrations of cyanogenic glycosides in island plants. We observed similar increases in leaf area and decreases in defense traits when comparing island and mainland genotypes grown together in botanic gardens, suggesting that trait differences are not solely driven by abiotic differences between island and mainland sites. In the second study, we conducted a common garden experiment with a perennial herb—<em>Stachys bullata </em>(Lamiaceae)—collected from two island and four mainland locations. Compared to their mainland relatives, island genotypes show highly reduced glandular trichomes and a nearly 100-fold reduction in mono- and sesquiterpene compounds from leaf surfaces. Island genotypes also had significantly higher specific leaf area, somewhat lower rates of gas exchange, and greater aboveground biomass than mainland genotypes across two years of study, potentially reflecting a broader shift in growth habit. Together, our results provide evidence for reduced expression of putative defense traits in island plants, though these results may reflect adaptation to both biotic (i.e., the historical absence of large herbivores) and climatic conditions on islands.</p>
Data of "Recurrent Neural Networks (RNNs) with dimensionality reduction and break down in computational mechanics; application to multi-scale localization step."
<p>Data related to<br> ===========<br> title = "Recurrent Neural Networks (RNNs) with dimensionality reduction and break down in computational mechanics; application to multi-scale localization step.",<br> journal = "Computer Methods in Applied Mechanics and Engineering",<br> volume ="390",<br> year = "2022",<br> doi = "https://doi.org/<a href="http://dx.doi.org/10.1016/j.cma.2021.114476">10.1016/j.cma.2021.114476</a> ",<br> pages = "114476 ",<br> author = "Wu, Ling and Noels, Ludovic"</p> <p>We would be grateful if you could cite the paper in the case in which you are using the data</p> <p> </p> <p>The files replace version 1 whose zip was corrupted.</p> <p> </p>
Data from: The 2018 European heatwave led to stem dehydration but not to consistent growth reductions in forests
<p>Heatwaves exert disproportionately strong and sometimes irreversible impacts on forest ecosystems. These impacts remain poorly understood at the tree and species level and across large spatial scales. Here, we investigate the effects of the record-breaking 2018 European heatwave on tree growth and tree water status using a collection of high-temporal resolution dendrometer data from 21 species across 53 sites. Relative to the two preceding years, annual stem growth was not consistently reduced by the 2018 heatwave but stems experienced twice the temporary shrinkage due to depletion of water reserves. Conifer species were less capable of rehydrating overnight than broadleaves across gradients of soil and atmospheric drought, suggesting less resilience toward transient stress. In particular, Norway spruce and Scots pine experienced extensive stem dehydration. Our high-resolution dendrometer network was suitable to disentangle the effects of a severe heatwave on tree growth and desiccation at large-spatial scales in situ, and provided insights on which species may be more vulnerable to climate extremes.</p>
Raw and analyzed data for manuscript "Dielectric barrier discharge plasma reduction of oxidized copper surfaces in an Ar/SiH4 atmosphere"
<p><strong>Abstract:</strong></p> <p>Nowadays, cold plasma techniques like dielectric barrier discharge (DBD) plasmas have attracted considerable interest in view of high deoxidation efficiencies as well as relative simplicity of setups. Although DBD plasma deoxidation of copper has been mainly studied in Ar/H<sub>2</sub> mixtures, there is no information on reduction performance of such methods in other protective atmospheres. In this study, the reduction of natively oxidized copper surfaces using a DBD plasma in an Ar/SiH<sub>4</sub> atmosphere at 100 hPa and 20 °C was investigated. The influence of a silane gas on the deoxidation performance was studied by varying the SiH<sub>4</sub> concentration from 0.0 to 0.5 vol%. An addition of a SiH<sub>4</sub> gas to an Ar atmosphere results in the increase of the deoxidation effect of a DBD plasma, so almost all Cu<sub>2</sub>O was reduced after around 10 s of treatment in 0.1 vol% silane. Surface morphology analysis showed formation of particles after Ar/SiH<sub>4</sub> plasma treatments, which can be cleaned from the surfaces by wiping. Additionally, characterization of the plasma phase indicated the presence of SiH<sup>*</sup> radicals, which likely play a role in the deoxidation effect. Moreover, an elimination of residual oxygen and nitrogen species in Ar by addition of SiH<sub>4</sub> was observed.</p>
Raw data for "Fluorescence crosstalk reduction by modulated excitation-synchronous acquisition for multispectral analysis in high-throughput droplet microfluidics."
<p>Raw data to quantify the crosstalk reduction and signal resolution improvement by MESA used in Figure 3 and 4.</p> <p><br> </p>
Data from: Operando Proton Transfer Reaction-Time of Flight-Mass Spectrometry of Carbon Dioxide Reduction Electrocatalysis
<p>Seven top-level folders</p> <p>GC-PTR-TOF-MS<br> - Raw data and Jupyter Notebook used for analysis of GC-PTR-TOF-MS data</p> <p>LSV-PTR-TOF-MS<br> - Raw data and Jupyter Notebook used for analysis of PTR-TOF-MS data under linear sweep voltammetry</p> <p>MSCP-PTR-TOF-MS<br> - Raw data and Jupyter Notebook used for analysis of PTR-TOF-MS data under multi-step chronopotentiometry</p> <p>PTR-TOF-MS-Calibration<br> - Raw data and Jupyter Notebook used for analysis of PTR-TOF-MS calibration data</p> <p>SEM<br> - Raw images from scanning electron microscope</p> <p>Stability<br> - Raw data of electrochemical stability</p> <p>TEM<br> - Raw images from transmission electron microscopy</p>
Data set for the journal article: Tandem electrocatalytic CO2 reduction with Fe-porphyrins and Cu nanocubes enhances ethylene production
<p>Copper-based tandem schemes have emerged as promising strategies to promote the formation<br> of multi-carbon products of the electrocatalytic CO2 reduction reaction. In such approaches,<br> the CO-generating component of the tandem catalyst increases the local concentration of CO<br> and thereby enhances the intrinsic carbon-carbon (C-C) coupling on copper. However, the<br> optimal characteristics of the CO-generating catalyst for maximizing eventual C2 production<br> are currently unknown. In this work, we developed tunable tandem catalysts comprising iron<br> porphyrin (Fe-Por), as the CO-generating component, and Cu nanocubes (Cucub) to understand<br> how the turnover frequency for CO (TOFCO) of the molecular catalysts impacts C-C coupling<br> on the Cu surface. First, we tuned the TOFCO of the Fe-Por by varying the number of orbitals<br> involved in the π-system. Then, by coupling these molecular catalysts with the Cucub, we<br> assessed the current densities and faradaic efficiencies, discovering that all of the designed Fe-<br> Por boost ethylene production. The most efficient Cucub/Fe-Por tandem catalyst was the one<br> including the Fe-Por with the highest TOFCO and exhibited a nearly 22-fold increase in the<br> ethylene selectivity and 100 mV positive shift of the onset potential with respect to the pristine<br> Cucub. These results reveal that coupling the TOFCO tunability of molecular catalysts along with<br> copper nanocatalysts opens up new possibilities towards the development of Cu-based catalysts<br> with enhanced selectivity for multi-carbon product generation at low overpotential.</p>
Data Archive for "Speckle Noise Reduction via Linewidth Broadening for Planetary Laser Reflectance Spectrometers"
<p>This archive contains the raw speckle images and experimental notes for the data contained in the journal article: "Speckle Noise Reduction via Linewidth Broadening for Planetary Laser Reflectance Spectrometers".</p> <p>The data available are:</p> <p>Raw speckle images for each of 5 illumination sources:</p> <ol> <li>Single-Frequence diode (files are named "IPS")</li> <li>Dual Mode pump diode (files are named "II-IV")</li> <li>Fabry Perot didoe (files are names "FP")</li> <li>Superluminescent Diode (files are named "SLD")</li> <li>Whilte light halogen source (files are named "WL")</li> </ol> <p>For each of theses source there are 5 images for each reflectance target, four speckle patterns and one background image with the laser source off. The naming convention is:</p> <p>LaserName_TargetReflectance_Target Rotation State or BKG.tiff</p> <p>For example, IPS_50_2 is the single-frequency laser using the 50% reflectance target and second rotation state of the target.</p> <p>The integration time for each image is give in the file "Experiment Paramters.csv" and was manually change to keep the maximum intensity at roughly 75% saturation.</p> <p>The spectra of the three laser sources presented in the manuscript are also included as .csv files</p>
Adequate vs. Inadequate Test Suite Reduction Approaches. Raw Data
<p>Context: Regression testing is an important activity that allows ensuring the correct behavior of a system after a change. As the system grows, the time and resources to perform regression testing increase. Test Suite Reduction (TSR) approaches aim to speed up regression testing by removing obsolete or redundant test cases. These approaches can be classified as adequate or inadequate. Adequate TSR approaches reduce test suites and completely preserve test requirements (e.g., covered statements) of the original test suites. Inadequate TSR approaches do not preserve test requirements. The percentage of satisfed test requirements indicates the inadequacy level.</p> <p>Objective: We compare some state-of-the art adequate and inadequate TSR approaches with respect to the size of the reduced test suites and their fault-detection capability. Specifcally, we aim to increase our body of knowledge on TSR approaches by performing the following comparisons: (i) well-known adequate TSR approaches; (ii) their inadequate variants; and (iii) several variants of a novel Clustering-Based (CB) approach for (adequate and inadequate) TSR.</p> <p>Method: We conducted an experiment to compare adequate and inadequate TSR approaches and this comparison is founded on a public dataset containing information on real faults.</p> <p>Results: The most important findings from our experiment can be summarized as follows: (i) there is not an inadequate TSR approach that performs better than others; (ii) some variants of the CB approach, and a few well-known inadequate approaches, outperform the adequate ones in terms of the reductions in test suite size with a negligible, or no, eect on fault-detection capability; and (iii) the CB approach is less sensitive than the other inadequate approaches, that is, variations in the inadequacy level have a small effect on the reduction in test suite size and on the loss in fault-detection capability.</p> <p>Conclusions: These findings imply that inadequate TSR approaches and especially the CB approach might be appealing because they lead to a greater reduction in test suite size (with respect to the adequate ones) at the expense of a small loss in fault-detection capability.</p>
Nonlinear methods for dimensionality reduction and clustering of bacterial single-cell sequencing data - intermediate data and figures (MSc thesis)
<p>Data, intermediate results and figures for analyses of my master's thesis in biostatistics at LMU Munich. I took a look on how to use Nonlinear Matrix Decomposition (NMD) (<a href="https://doi.org/10.1137/21M1405769">Saul, L., 2022</a>) in the context of bacterial scRNA-seq analysis (Heumos, L., et. al. 2023), replacing Principal Component Analysis in the optimized workflow, as outlined in Ostner, J. (2024).</p> <p>My thesis was structured along the following objectives:</p> <ul> <li>implement the algorithms from <a href="https://arxiv.org/abs/2305.08687">Seraghiti, G., et. al. (2023)</a> in the Python module <a href="https://github.com/flatironinstitute/nomad/">nomad</a> in cooperation with <a href="https://www.simonsfoundation.org/flatiron/" rel="nofollow">Flatiron Institute</a></li> <li>code for the simulation study of the algorithms in <a href="https://arxiv.org/abs/2305.08687">Seraghiti, G., et. al. (2023)</a> with varying sparsity can be found in <code>/simulation</code></li> <li>apply NMD in the context of the BacSC workflow (<a href="https://www.biorxiv.org/content/10.1101/2024.06.22.600071v1">Ostner, J., et. al. (2024)</a>) on raw and normalized counts (found in <code>/application/analysis</code>), also for manually set number of latent dimensions</li> <li>explore NMD's potential for imputation of <a href="https://www.nature.com/articles/s41467-021-27729-z" rel="nofollow">sampling zeros</a> (check <code>/application/NMD_zero_imputation /</code>)</li> <li>potential of Poisson-Hurdle model-based clustering (<a href="https://academic.oup.com/bioinformatics/article/39/1/btac782/6873739">Qiao, Z., et. al. (2023)</a>) for scRNA-seq (<code>/application/poisson_hurdle</code>).</li> </ul>
Genome streamlining: effect of mutation rate and population size on genome size reduction: simulated data
<p>Lineages data of populations simulated with Aevol (<a href="https://gitlab.inria.fr/aevol/aevol">https://gitlab.inria.fr/aevol/aevol</a>), and the Wild-Types sequences used for that.</p> <p>Conditions: change of mutation rate, population size, or both.<br>Mutational bias: none, insertion bias or deletion bias</p>
Raw and analyzed data for manuscript "Reduction of copper surface oxide using a sub-atmospheric dielectric barrier discharge plasma"
<p><strong>Abstract:</strong> Oxide layers on metal surfaces adversely affect processability and material properties in many industrial applications. Although several plasma-based approaches for deoxidation were investigated in the past, oftentimes they either work under conditions expensive to create or require long processing times. In this study, the deoxidation effect of a non-thermal dielectric barrier discharge plasma in an Ar/H<sub>2</sub> gas mixture at 100 hPa and 20 °C was investigated on copper surfaces with a native oxide layer. The chemical structure of surfaces before and after deoxidation was analyzed by X-ray photoelectron spectroscopy (XPS). The results revealed that ~98 % of the surface lattice oxide Cu<sub>2</sub>O was reduced to Cu after around 20 s of plasma treatment, whereas all oxygen contaminants were almost completely removed from Cu surface after around 50 s. Additionally, the kinetics of the reduction of surface oxide was studied and a Johnson-Mehl-Avrami-Erofeev-Kholmogorov kinetic model was proposed. The analysis of the morphology of surfaces was performed with atomic force microscopy (AFM), showing minor changes in the roughness after deoxidation. Moreover, optical emission spectroscopy (OES) showed atomic hydrogen radicals in the plasma phase, which likely causes deoxidation effect.</p>
Replication Data for "Exploring Developer Views on Software Carbon Footprint and its Potential for Automated Reduction"
<p># Replication Data for "Exploring Developer Views on Software Carbon Footprint and its Potential for Automated Reduction"</p> <p>## Overview</p> <p>Reducing software carbon footprint could contribute to efforts to avert climate change. Past research indicates that developers lack knowledge on energy consumption and carbon footprint, and existing reduction guidelines are difficult to apply. Therefore, we propose that automated reduction methods should be explored. However, such tools must be voluntarily adopted and regularly used to have an impact.</p> <p>In this study, we have conducted interviews and a survey (a) to explore developers' existing opinions, knowledge, and practices with regard to carbon footprint and energy consumption, and (b), to identify the requirements that automated reduction tools must meet to ensure adoption. Our findings offer a foundation for future research on practices, guidelines, and automated tools that address software carbon footprint.</p> <p>## Data Contained in This Package</p> <p>- interview_survey_guide.pdf</p> <p>This file contains the interview and survey questions.</p> <p>- interview_responses.docx</p> <p>This file contains relevant material from the interviews.</p> <p>- survey_responses.xlsx</p> <p>This file contains all survey responses.</p> <p>Both interview and survey data has been anonymized to protect the privacy of the participants.</p>
Tables and Data for "Synthesis of Satellite and Surface Measurements, Model Results, and FRAPPÉ Study Findings to Assess the Impacts of Oil and Gas Emissions Reductions on Maximum Ozone in the Denver Metro and Northern Front Range Region in Colorado"
<p>These are data sets and tables used in the paper "Synthesis of Satellite and Surface Measurements, Model Results, and FRAPPÉ Study Findings to Assess the Impacts of Oil and Gas Emissions Reductions on Maximum Ozone in the Denver Metro and Northern Front Range Region in Colorado" to be submitted to Earth and Space Science. The monitor site 2016 and 2017 counts files have gridded HYSPLIT back trajectory counts for the 4 highest ozone concentration days at each site, as described in the manuscript.</p>
Raw and analyzed data for manuscript "Atmospheric non-thermal plasma reduction of natively oxidized iron surfaces"
<p> Raw and analyzed data for manuscript "Atmospheric non-thermal plasma reduction of natively oxidized iron surfaces"</p>
Data and code_Ombadi et al., Nature (2023)_A warming induced reduction in snow fraction amplifies rainfall extremes
<p>This repository contains intermediary and final outputs of the analysis presented in the article: "Ombadi et al., Nature (2023), A warming-induced reduction in snow-fraction amplifies rainfall extremes.". Additionally, the repository also contains codes for analysis and visualization of results presented in this article. The codes are primarily written in Python and provided as Jupyter Notebooks (.py files) with the exception of one code written in R language. </p>
Data for Coupling Covariance Matrix Adaptation with Continuum Modeling for Determination of Kinetic Parameters Associated with Electrochemical CO2 Reduction
<p>This data set contains digitized and tagged polarization and partial current density data for 18 datasets of CO<sub>2</sub> reduction to H<sub>2</sub> and CO over Ag catalysts, as well as 8 datasets of CO<sub>2</sub> reduction to HCOO<sup>-</sup>, CO, and H<sub>2</sub> over Sn catalysts. We analyze this data using a coupled continuum modeling and covariance matrix adaptation approach for which the codebase is provided in DOI: 10.5281/zenodo.7866195.</p>
Surface Charge Boundary Condition Often Misused in CO2 Reduction Models (raw data for graphs)
<p>This contains the raw data, in text file format, for the figures in the journal article "Surface Charge Boundary Condition Often Misused in CO2 Reduction Models" published in Journal of Physical Chemistry C, DOI 10.1021/acs.jpcc.3c05364.</p> <p>The files are in directories corresponding to their figure number, and the files are named with the capacitance. </p> <p> </p> <p> </p>
Data for: Effectiveness of forest density reduction treatments for increasing drought resistance of ponderosa pine growth
Open the record for dataset details and reuse information.
Data from: Evidence for reductions in physical and chemical plant defense traits in island flora
Open the record for dataset details and reuse information.
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.