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10,561 results for “Mechanisms”
Identifying the mechanisms by which irrigation can cool urban green spaces in summer
<p>This dataset contains the measured soil moisture and microclimate data from two (2021 and 2022) urban green space irrigation experiments conducted in Burnley, Melbourne, Australia. The experiments consisted of two treatments, irrigated turf and unirrigated turf. The purpose of the experiments was to provide testing (2021) and evaluation (2022) data for an urban ecohydrological model, UT&C. </p> <p><br>After evaluating the performance of UT&C in modelling soil moisture and microclimate, UT&C was used to model the surface energy balance and evapotranspiration processes of the irrigated and unirrigated turf. This dataset also contains the modelled soil moisture, microclimate, surface energy balance and evapotranspiration data, as well as the measured background climate data at the reference climate station and the forcing data for the model.</p> <p><br>The aims of this study were to:<br>i) identify the proportional contribution of different evapotranspiration processes to irrigation cooling effect, and <br>ii) quantify the impacts of different irrigation amounts (from 2 to 30 mm/d) on the cooling effect of irrigating turfgrass in Melbourne, Australia during normal summer conditions.</p> <p>This study was published in:<br>Pui Kwan Cheung, Naika Meili, Kerry A. Nice, Stephen J. Livesley (2024). Identifying the mechanisms by which irrigation can cool urban green spaces in summer. Urban Climate. 55,101914. https://doi.org/10.1016/j.uclim.2024.101914.</p>
Temperature-dependent fold-switching mechanism of the circadian clock protein KaiB
<p>Derived data accompanying publication of <em>Temperature-dependent fold-switching mechanism of the circadian clock protein KaiB</em> (Zhang et al., PNAS 2024).</p> <p> </p> <p>This dataset contains data for fold-switching of KaiB from simulations performed using the Upside coarse-grained model (Jumper et al. PLoS Comput. Bio 2017). Files contained include collective variables, kinetic quantities (committors), and initial structures used to seed unbiased simulations. These data should be sufficient recreate the analysis shown in the associated publicaion. Raw trajectory files have not been deposited due to their size; contact the author (Spencer Guo) to request.</p>
Artificial Intelligence for Quality Control of manufacturing operations: Macro-mechanical milling in the Pilot Line GAMHE 5.0.
<p>Quality is defined as the extent to which a product conforms to the design specifications and how it complies with the requirements of component functionality. For some industries, such as automotive and aeronautical, the quality of their parts is very important given the high requirements to which they are subject. However, difficulties arise from the fact that a measure of quality can only be evaluated ‘‘out-of-process”, resulting in losses because there is no alternative to removing defective parts from the production line. Therefore, it is necessary to apply Artificial Intelligence-based kits/solutions that provide in-process estimation to predict quality from some measured variables. </p> <p>The main goal of these datasets is to monitor the final quality of the manufactured components or parts by estimating surface roughness from vibration signals and cutting parameters information using Artificial Intelligence-based solutions. Surface roughness is an essential feature in quality control defined by the deviation in the direction of the normal vector of a real surface from its ideal form. Because the roughness measurement is an offline and post process procedure, being able to estimate this value online brings a series of benefits in terms of time and cost reduction in manufacturing lines, energy efficiency, unnecessary wear of tools and machines, etc. Once a part has been detected with a surface quality below what is desired, a series of corrective measures can be applied for the following operations, such as: reducing the feed rate percentage, increasing the percentage of spindle speed or reducing the axial depth per pass, etc.</p>
Mechanically Resistant Poly(N-vinylcaprolactam) Microgels with Sacrificial Supramolecular Catechin Hydrogen Bonds
<p>Original data corresponding to the plots of Figures 2, 4, 5 of the manuscript and S1-S16 of the Supporting Information in *.csv format and raw data for NMR measurements.</p>
Artificial Intelligence for quality control in manufacturing operations: Micro-mechanical milling in the Pilot Line GAMHE 5.0
<p>Quality is defined as the extent to which a product conforms to the design specifications and how it complies with the requirements of component functionality. For some industries, such as automotive and aeronautical, the quality of of manufactured parts is very important due to the high requirements. However, difficulties arise from the fact that a measure of quality can only be evaluated ‘‘out-of-process”, resulting in losses because there is no alternative to removing defective parts from the production line. Therefore, it is necessary to incorporate AI-based kits/solutions that provide in-process estimation to predict quality from some measured variables.</p> <p>The main goal of these datasets is to enable monitoring of final quality of the manufactured components or parts by estimating surface roughness from vibration signals and cutting parameters information. Surface roughness is an essential feature in quality control defined by the deviation in the direction of the normal vector of a real surface from its ideal form. Because the roughness measurement is an offline and post process procedure, being able to estimate this value online brings a series of benefits in terms of time and cost reduction in manufacturing lines, energy efficiency, unnecessary wear of tools and machines, etc. Once a part has been detected with a surface quality below what is desired, a series of corrective measures can be applied for the following operations, such as: reducing the feed rate percentage, increasing the percentage of spindle speed or reducing the axial depth per pass, etc.</p> <p>Workstation 4 (WS4) of the GAMHE 5.0 pilot line is a Kern Evo high-precision machining centre, with a maximum spindle speed of 50 000 rpm and Blum laser system and is used to run micro-milling and micro-drilling operations. In this experimental dataset, five cutting parameters were considered in the processes: spindle speed, <em>n</em>; feed rate, <em>f</em>; and axial depth of cut, <em>a<sub>P</sub></em>. The radial depth of cut, <em>a<sub>e</sub></em>; was equal to the mill tool radius, <em>r</em>, in all of the slots.</p> <p>These experiments were micro-milling operations with 0.3 mm, 0.5 mm, 0.8 mm and 1 mm-diameter mills on a sintered tungsten-copper alloy (W78Cu22). The data collected for each micro milling operation was the rms and peak value of the vibrations in the three-machine axis. In addition, five cutting parameters were also collected: position in <em>X</em> of the last point of the sample, feed rate, spindle speed, tool radius and axial depth.</p>
Mechanical characterisation of the developing cell wall layers of tension wood fibres by Atomic Force Microscopy
<p>This dataset corresponds to the Arnould et al. (2022) paper (available at https://www.biorxiv.org/content/10.1101/2021.09.23.461481v1.full) on the mechanical characterization of developing cell wall layers of tension wood fibers by Atomic Force Microscopy. It contains all raw AFM files (Bruker format .spm, readable by the free software Gwyddion for example) corresponding to mechanical measurements of poplar reaction wood cells (clone 717-1B4) along 3 radial lines/rows, starting from the cambium. Each cell is identified by its "macroscopic" distance from the cambium (value in µm in the name of each file corresponding to the displacement of the sample in the AFM) which was corrected after using the AFM optical image captures. Some files, with a -z extension after the distance value, correspond to a zoom into the cell wall. The data also contain measurements made for mechanical calibration on epoxy embedded Kevlar fibers, controlled measurements in the embedding resin between each radial line and measurements in normal wood cells. Two csv files containing final data extracted from AFM measurements that give the value of the indentation modulus and the relative thickness to cell diameter ratio (by AFM and by phase contrast optical microscopy) in each cell wall layer as a function of cambium distance are also provided.</p>
Dataset accompanying the publication: Acoustic cues of keyboard mechanics enable auditory localization of upright piano tones
<p>Dataset accompanying the publication: Acoustic cues of keyboard mechanics enable auditory localization of upright piano tones (in J. Acoust. Soc. Am., 2024)</p>
Anthropomorphic Mechanisms for User Acceptance in Human-Robot Interaction - PRISMA pass data
<p>This is the data produced in the course of selecting relevant literature for the <em>"User Acceptance in Human-Robot Interaction"</em> literature review article.</p> <p><strong>Contents:</strong></p> <ul> <li>Initial pass records: <em>prisma0_wos.xlsx + prisma0_scopus.xlsx</em></li> <li>Initial pass eligibility assessment:<em><strong> </strong>prisma0_eval.xlsx</em></li> <li>Second pass records, filtering and coarse assessment:<em><strong> </strong>prisma1.xlsx</em></li> <li>Third pass records, filtering and coarse assessment:<em><strong> </strong>prisma2.xlsx</em></li> <li>Fine eligibility assessment of 2nd and 3rd pass: <em>prisma_avalanche_1_and_2_report_update_04_26.pdf</em></li> </ul> <p> </p>
Multi-omic Insights into Molecular Mechanism and Therapeutic Targets in Spinocerebellar Ataxia type 7
<p>The molecular mechanism in spinocerebellar ataxia type 7 is currently poorly understood. To provide understandings, a multi-omic study was performed using SCA7266Q/5Q mice. At week 12, entire brain tissue samples were collected and RNA sequencing, methylation analysis, and proteomic analysis were performed. Results were integrated to identify genes with identical trends in expression. Data was also compared with SCA patient serum proteomic analysis, and based on common differentially expressed proteins, a Naïve Bayesian network model was constructed to predict nilotinib treatment response. Data from RNA sequencing and methylation analysis revealed 58 significantly hypomethylated-upregulated genes and 62 hypermethylated-downregulated genes, mostly enriched in GO terms of regulation of axonogenesis, channel activity, and monoamine signaling. In the proteomic analysis, 211 upregulated and 281 downregulated DEPs associated mostly with immune response and cellular mobility were identified. Two genes, Fam107b and Tph2, showed differential expression in both transcriptomic and proteomic analysis. Forty-two overlapping proteins were identified compared with SCA patient serum, and Bayesian network analysis revealed that nilotinib treatment response was associated with the protein expression of CLU, CA2, GLUL, PRDX6, C1QA, PLXNB1, and age. These findings will serve as an important reference for future studies on the pathogenesis and discovery of druggable targets. </p>
Data for the manuscript "Enhanced microscopic dynamics in mucus gels under a mechanical load in the linear viscoelastic regime" (PNAS).
<p>Data files for the figures published in</p> <p>D. Larobina, A. Pommella, A.-M. Philippe, M. Y. Nagazi, and L. Cipelletti, <em>Enhanced Microscopic Dynamics in Mucus Gels under a Mechanical Load in the Linear Viscoelastic Regime</em>, Proc Natl Acad Sci USA <strong>118</strong>, e2103995118 (2021).</p> <p>DOI: 10.1073/pnas.2103995118</p> <p>Each data set is available as a plain text file (description in the file __README__DataDescription.txt), and as an Excel file.<br> The Excel files typically contain the data sets of several panels of a given figure, as separated sheets. See the description<br> provided in the "GeneralInfo" sheet of each Excel file.</p>
Kinetochore life histories reveal an Aurora B dependent error correction mechanism in anaphase
<p>Dataset of kinetochore tracks in human RPE1 cells showing chromosome dynamics and segregation from prometaphase through to anaphase as described in detail in Sen, Harrison, Burroughs and McAinsh, 2021, https://doi.org/10.1101/2021.03.30.436326 Tracks correspond to 3D time-lapse movies of Ndc80-eGFP and were acquired in the 488nm channel using 1\% laser power, 50 ms exposure time/z-plane, 93 z-planes, 307 nm z-step, which results in 4.7 s/z-stack time frame. Cells are subject to nocodazole arrest-and-release or equivalent treatment with DMSO as indicated in the folder names, and some cells are subject to additional treatment with ZM to inhibit Aurora B (also indicated in folder names). Tracks were produced using kinetochore tracking software, KiT v2.3 (see Armond et al., 2016, Bioinformatics), available from https://github.com/cmcb-warwick/KiT/ </p>
Molecular mechanism for the synchronized electrostatic coacervation and co-aggregation of alpha-synuclein and tau
<p><strong><em>The following metadata refers exclusively to electron paramagnetic resonance (EPR) measurements, which represent the contribution of the PARACAT students to this work</em></strong></p> <ul> <li><strong>Data type</strong>: EPR spectroscopic measurements and simulations</li> <li>Files are in <strong>.DTA, .DSC, .m, .mat, and .xlxs, </strong>formats</li> <li>Information on <strong>origin of the data</strong>: <ul> <li>EPR spectroscopic measurements in <strong>.DTA </strong>and<strong> .DSC</strong> formats</li> <li>EPR spectroscopic simulation and analyses in .<strong>m </strong>and<strong> .mat</strong> format</li> <li>“Ready-to-plot”, processed EPR spectra are in <strong>.xlxs</strong> format.</li> </ul> </li> <li>The data are <strong>generated</strong> by: <ul> <li>CW-EPR measurements were performed with a Bruker ELEXSYS E580 X-band spectrometer equipped with a Bruker ER4118 SPT-N1 resonator operating at a microwave (MW) frequency of ∼9.7 GHz. The temperature was set to 25 °C and controlled by a liquid nitrogen cryostat.</li> </ul> </li> </ul> <p> </p> <ul> <li><strong>If the dataset includes multiple files that relate to each other:</strong> <ul> <li>Files in <strong>PARACAT_WP3_20221219_EPR </strong>folder includes EPR spectroscopic measurements and computer simulations/analyses, original data are in <strong> .DTA/.DSC</strong> formats; files in .<strong>m</strong> format were used to process the data.</li> </ul> </li> </ul> <p>NB. See the “READ ME” text file for more detailed information on files organization.</p> <p> </p> <ul> <li><strong>Information on</strong>: <ul> <li>Abbreviations: <ul> <li><strong>avg</strong> = averaged</li> <li><strong>aS_24</strong> = alpha-synuclein protein with TEMPOL spin label at position 24 of the polypeptidic chain</li> <li><strong>aS_122</strong> = alpha-synuclein protein with TEMPOL spin label at position 122 of the polypeptidic chain</li> <li><strong>pLK</strong> = poly-lysine</li> <li><strong>Tau441</strong> = Tau protein with complete amino-acid sequence</li> <li><strong>Tau_DNt</strong> = truncated Tau protein lacking N-terminal (see paper methods for further details)</li> </ul> </li> <li>Units of measurement: <ul> <li>Temperature: <strong>°</strong><strong>C</strong> (Celsius)</li> <li>Microwave Frequency: <strong>GHz</strong> (Giga-Hertz), <strong>MHz</strong> (Mega-Hertz), <strong>kHz</strong> (kilo-Hertz)</li> <li>Microwave Power: <strong>mW</strong> (milli-Watt)</li> <li>Magnetic Field: <strong>mT</strong> (milli-Tesla)</li> <li>Time: <strong>s</strong> (seconds)</li> <li>Concentration: <strong>μM</strong> (micro-Molar), <strong>% w/v</strong> (percentage weight-volume)</li> </ul> </li> </ul> </li> </ul>
Mechanism for the Uplift of Gongga Shan in the Southeastern Tibetan Plateau Constrained by 3D Magnetotelluric Data
<p>The *.data, *.rho, and *.zip files are associated with a paper titled 'Mechanism for the Uplift of Gongga Shan in the Southeastern Tibetan Plateau Constrained by 3D Magnetotelluric Data' in Geophysical Research Letters published in 2022. On the basis of this data and inversion model, we addressed that the rapid uplift of the Gongga Shan massif likely occurred by the underthrusting of the Yangtze Craton. More details about the electrical resistivity model and its interpretations can be found in our journal paper. </p> <p>All the resulting files from ModEM are included in the 'ModEM_Inversion_Results.zip'. All the figures in the paper and supplementary are included in the 'GRL_All_Figures.zip' and 'Figure_S5_All_Responses.zip'.</p> <p>The resulting model and data output in ModEM format can be found in .rho and .data files. The ModEM is an open-source code package for MT 3D inversion, which is provided by Gary Egbert, Anna Kelbert, and Naser Meqbel and can be found on this website: <a href="https://sites.google.com/site/modularem/download">https://sites.google.com/site/modularem/download</a>. </p> <p>Please note that the 3D resistivity model files in general format includes four columns -- longitude, latitude, depth, and resistivity, the one who wants to plot the model via GMT, MATLAB, Surface, etc., can find these files in 'Gongga_3D_Resistivity_Model_Files.zip'. In this zip, you will find the resistivity model of each horizontal slice of different depths and a file including all the slices. A MATLAB script called 'see_slice.m' is included in the folder which can help to quickly view these resistivity slices.</p>
Data to reproduce analysis in "Systematic analysis of transcriptional and epigenetic effects of genetic variation in Kupffer cells enables discrimination of cell intrinsic and environment-dependent mechanisms"
<p>Here you can find the datasets necessary to reproduce all analyses described in the Glass lab paper by <a href="https://www.biorxiv.org/content/10.1101/2022.09.22.509046v1">Bennett et al</a>. The python and R code for reproducing analysis and figures can be found on our linked <a href="https://github.com/HunterBennett/KupfferCell_NaturalGeneticVariation">github repository.</a></p> <p>Briefly, this paper explores the effect of natural genetic variation <em>in vivo</em>, using Kupffer cells as a model cell type. We collect and analyze transcriptional and epigenetic data (ATAC-seq, H3K27Ac ChIP-seq) to identify putative <em>trans</em> regulators driving differential gene expression across inbred strains of mice. Additionally, we provide evidence that <em>trans</em> effects control a majority of strain differential genes at homeostasis while <em>cis</em> effects dominate the transcriptional response to an external signal (lipopolysaccharide).</p> <p>References:</p> <p>Hunter Bennett, Ty D. Troutman, Enchen Zhou, Nathanael J. Spann, Verena M. Link, Jason S. Seidman, Christian K. Nickl, Yohei Abe, Mashito Sakai, Martina P. Pasillas, Justin M. Marlman, Carlos Guzman, Mojgan Hosseini, Bernd Schnabl, Christopher K. Glass bioRxiv 2022.09.22.509046; doi: <a href="https://doi.org/10.1101/2022.09.22.509046">https://doi.org/10.1101/2022.09.22.509046</a></p> <p> </p>
Understanding the formation mechanisms of silicon particles from the thermal disproportionation of hydrogen silsesquioxane
<p><strong>Data set</strong> from Understanding the formation mechanisms of silicon particles from the thermal disproportionation of hydrogen silsesquioxane.<br> <br> - Publication : Cibaka-Ndaya C., O'Connor K., Opeyemi Idowu E., Parker M. A., Lebraud E., Lacomme S., Montero D., Sanz Camacho P., Veinot J. G.-C., Roiban I.-L., Drisko G. L.. Understanding the formation mechanisms of silicon particles from the thermal disproportionation of hydrogen silsesquioxane. <em>Chemistry of Materials</em>, In press, <a href="https://dx.doi.org/10.1021/acs.chemmater.3c01448">⟨10.1021/acs.chemmater.3c01448⟩</a>. <a href="https://hal.science/hal-04211253">⟨hal-04211253⟩</a><br> <br> <strong>Dataset production context : </strong> Crystalline silicon particles sustaining Mie resonances are readily obtained from the thermal processing of hydrogen silsesquioxane (HSQ). Here, the mechanisms involved in silicon particle formation and growth from HSQ are investigated through real time in situ analysis in an environmental transmission electron microscope and X-ray diffractometer. The nucleation of Si nanodomains are observed starting around 1000 °C. For the first time, a highly mobile intermediate phase is experimentally observed, thus demonstrating a previously unknown growth mechanism. At least two growth processes occur simultaneously: the coalescence of small particles into larger particles and a growth mode by particle displacement through the matrix toward the HSQ grain surface. Post-synthetic characterization by scanning electron microscopy further evidences the latter growth mechanism. The gaseous environment employed during synthesis impacts particle formation and growth under both in situ and ex situ conditions, impacting particle yield and structural homogeneity. Understanding the formation mechanisms of particles provides promising pathways for reducing the energy cost of this synthetic route.<br> <br> <br> <strong>For more information see the article.</strong></p>
Minute-timescale free-energy calculations reveal a pseudo-active state in the adenosine A2A receptor activation mechanism
<p>Dataset of the paper "Minute-timescale free-energy calculations reveal a pseudo-active state in the adenosine A2A receptor activation mechanism" accepted for publication on ACS Chem journal.</p>
Mechanisms mediating plant distributions across estuarine landscapes in a low-latitude tidal estuary
Understanding of how plant communities are organized and will respond to global changes requires an understanding of how plant species respond to multiple environmental gradients. We examined the mechanisms mediating the distribution patterns of tidal marsh plants along an estuarine gradient in Georgia using a combination of field transplant experiments and monitoring. Our results could not be fully explained by the “competition-to-stress hypothesis” (the current paradigm explaining plant distributions across estuarine landscapes). This hypothesis states that the upstream limits of plant distributions are determined by competition, and the downstream limits by abiotic stress. We found that competition was generally strong in freshwater and brackish marshes, and that conditions in brackish and salt marshes were stressful to freshwater marsh plants, results consistent with the competition-to-stress hypothesis. Four other aspects of our results, however, were not explained by the competition-to-stress hypothesis. First, several halophytes found the freshwater habitat stressful, and performed best (in the absence of competition) in brackish or salt marshes. Second, the upstream distribution of one species was determined by the combination of both abiotic and biotic (competition) factors. Third, marsh productivity (estimated by standing biomass) was a better predictor of relative biotic interaction intensity (RII) than was salinity or flooding, suggesting that productivity is a better indicator of plant stress than salinity or flooding gradients. Fourth, facilitation played a role in mediating the distribution patterns of some plants. Our results illustrate that even apparently simple abiotic gradients can encompass surprisingly complex processes mediating plant distributions.
Neural mechanisms of musical syntax and tonality, and the effect of musicianship
Open the record for dataset details and reuse information.
DNA Crookedness Regulates DNA Mechanical Properties at Short Length Scales
<p>Data presented in the annual conference DPG conference 2019 (<a href="https://regensburg19.dpg-tagungen.de/">https://regensburg19.dpg-tagungen.de/</a>). </p> <p>Here we discuss how DNA sequence allow us to modulate its structure and mechanical properties, thus proving for the first time a one to one map between sequence and mechanical code. This is intended to provide an overview of the results published in the following peer-reviewed freely available papers:<br> Phys. Rev. Lett. 122, 048102 (2019) [DOI: 10.1103/PhysRevLett.122.048102 or https://doi.org/10.1101/283648]<br> Nanoscale Nanoscale 11, 21471 (2019) [DOI: 10.1039/C9NR07516J]<br> PNAS 114, 7049 (2017) [DOI: 10.1073/pnas.1705642114]<br> Nucleic Acids Research, gkaa225 [DOI: 10.1093/nar/gkaa225]<br> (Please cite them, if you found this information useful.)</p>
iNRACM: Incorporating 15N into the Regional Atmospheric Chemistry Mechanism (RACM) for assessing the role photochemistry plays in controlling the isotopic composition of NOx, NOy, and atmospheric nitrate
<p><sup>15</sup>N compounds and reactions were incorporated into Regional Atmospheric Chemistry Mechanism (RACM), based on recent experimental or calculated values of isotope fractionation factors (α), to simulate δ<sup>15</sup>N values in NO<sub>y</sub> compounds.</p>
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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.