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1,197 results for “flexibility”
Supplementary data: "Influence of flexibility options on the German transmission grid — A sector-coupled mid-term scenario"
<p>This repository contains result data for the paper <i> "Influence of flexibility options on the German transmission grid — A sector-coupled mid-term scenario"</i>.</p><p>The published data includes optimization results of the three main scenarios in the mentioned publication. </p><p>The data for each scenario is stored as csv-files, which allows analysing it with many different tools. In addition, the data can be imported in Python as a network object of the open-source tool PyPSA by using the function <a href="https://pypsa.readthedocs.io/en/latest/api_reference.html#pypsa.Network.import_from_csv_folder">import from csv folder </a>. </p><p> </p><p>The authors thank the Federal Ministry for Economic Affairs and Climate Action for funding the research project eGon (funding code: 03EI1002).</p>
Code and example images from: recolorize: An R package for flexible color segmentation of biological images
<p>Color pattern variation provides biological information in fields ranging from disease ecology to speciation dynamics. Comparing color pattern geometries across images requires color segmentation, where pixels in an image are assigned to one of a set of color classes shared by all images. Manual methods for color segmentation are slow and subjective, while automated methods can struggle with high technical variation in aggregate image sets. We present recolorize, an R package toolbox for human-subjective color segmentation with functions for batch-processing low-variation image sets and additional tools for handling images from diverse (high variation) sources. The package also includes export options for a variety of formats and color analysis packages. This paper illustrates recolorize for three example datasets, including high variation, batch processing, and combining with reflectance spectra, and demonstrates the downstream use of methods that rely on this output.</p>
Increase of active-power-based flexibility (data for KPI evaluation)
<p>There are stored data collected from new EV charging stations – this will be used as an aggregated source of active power-based flexibility procured for system operator (DSO) and managed through non frequency platform. Data originated from part of the CZ DEMO run directly by ČEZ distribuce called "e – fleet". At Zenodo there are data from all sites (EV charging poles while the first excel sheet contains calculation of the KPI “Increase of active-power-based flexibility”. Detailed explanation on KPI evaluation, data format and main findings from the tests are included in the <a title="link" href="https://www.onenet-project.eu/wp-content/uploads/2024/03/OneNet_D10.5_V1.0.pdf">Deliverable 10.5 (section 2.1.2). </a></p>
HDX-MS dataset for: "Glycan-induced structural activation softens the human papillomavirus capsid for entry through reduction of intercapsomere flexibility"
<p>Hydrogen/deuterium exchange mass spectrometry dataset used in: <strong>Glycan-induced structural activation softens the human papillomavirus capsid for entry through reduction of intercapsomere flexibility.</strong> Yuzhen Feng*, Dominik van Bodegraven*, Alan Kádek*, Ignacio L.B. Munguira, Laura Soria-Martinez, Sarah Nentwich, Sreedeepa Saha, Florian Chardon, Daniel Kavan, Charlotte Uetrecht#, Mario Schelhaas#, Wouter H. Roos#. <em>Nature Communications</em> 10076 (2024). doi: 10.1038/s41467-024-54373-0</p> <p>* - authors contributing equally</p> <p># - corresponding authors</p> <p><strong>Description:</strong></p> <p>Hydrogen/deuterium exchange mass spectrometry (HXMS) analysis of the effect of heparin on the conformational dynamics of human papillomavirus 16 pseudovirus (PsV).</p> <p><strong>Sample processing:</strong></p> <p>HPV16 PsV were prepared according to (Buck & Thompson: Current Protocols in Cell Biology 2007). In short, p16Shell and pClneo-EGFP were transfected into HEK293TT cells. After 48 h, cells were harvested and lysed followed by maturation of the virus particles for 24 h. For purification, the particles were purified using a CsCl step gradient (27 % w/V and 38.8 % w/V CsCl in 10 mM Tris-HCl pH 7.4, 207570 x g, 3 h 50 min, 4 °C) followed by dialysis in Float-A-Lyzer devices (1 mL, Spectra/Por) against a total of 3 L HPV virion buffer (1x PBS, 635 mM NaCl, 0.9 mM CaCl2, 0.5 mM MgCl2, 2.1 mM KCl, pH 7.4).</p> <p>PsV were pre-incubated for 1 h either with or without heparin (H4784, Sigma-Aldrich) at room temperature. To initiate deuterium labelling the samples were 6-fold diluted with the virion buffer they were obtained in, only made of 99.9% D2O (150 mM NaCl, 4.8 mM KCl, 10 mM Na2HPO4, 1.8 mM KH2PO4, 0.9 mM CaCl2, 0.5 mM MgCl2, pD 7.2). This resulted in a final concentration of 0.5 µM L1 monomer in the form of PsV with or without 1 mg/ml heparin during deuterium labelling. The exchange reaction was left to proceed at room temperature until aliquots of 45 µl were removed at predetermined time points (1 min, 5 min, 15 min, 1 h and 4 h). In the aliquots, the exchange was immediately stopped by twofold dilution with ice-cold quench buffer (0.25 M glycine, 100 mM TCEP, 8 M urea, indicated pH 2.7), resulting in final pH 2.5. For samples with heparin, the quench buffer additionally contained 1 mg/ml protamine sulphate (P4020, Sigma-Aldrich). After 30 s incubation on ice, the samples were centrifuged at 10.000 x g for 1 min at 0 °C. Each supernatant was transferred to a fresh tube and flash frozen in liquid nitrogen. Low binding microtubes and low binding pipette tips (both Axygen) were used throughout for all handling of viral particles.</p> <p>The frozen samples were quickly thawed and injected into a refrigerated (1°C) HPLC system (Infinity 1260, Agilent Technologies), through a porcine pepsin column (≥ 3200 units/mg, Sigma-Aldrich) in-house immobilized onto POROS-20AL perfusion resin (Thermo Scientific) as described previously (Wang et al.: Molecular & Cellular Proteomics 2002), which was kept at 4°C. Pepsin digestion was performed at isocratic 200 µl/min flow rate (0.4 % formic acid in water). After the digestion, peptides were online desalted for 3 min on a peptide microtrap (OPTI-TRAP, Optimize Technologies) and then eluted on a reversed-phase analytical column (ZORBAX 300SB-C18, 0.5 x 35 mm, 3.5 µm, 300Å, Agilent Technologies). There LC separation proceeded at 25 µl/min flow rate through an 8 min gradient of 8–30% solvent B, followed by a 3 min gradient of 30-90 % solvent B (solvent A: 0.4 % formic acid in water, solvent B: 0.4 % formic acid in acetonitrile). The outlet of the HPLC system was connected to an electrospray ionization (ESI) source of an Orbitrap Fusion Tribrid Mass Spectrometer (Thermo Scientific). The instrument was operated in positive ESI MS-only mode for deuterated samples, scan range 300-2000 m/z, using 4 microscans at resolving power setting 120,000. In a separate measurement on non-deuterated sample, the instrument was used in positive data-dependent ESI MS/MS mode with 30% HCD dissociation, 1 microscan and 240,000 resolving power setting for the identification of all peptides produced by non-specific pepsin cleavage.</p> <p>In total 22 pmol and 50 pmol L1 protein were injected per MS and MS/MS analysis, respectively. To minimize sample carry-over on the protease column, two washing solutions were always injected between sample injections modified from Majumdar et al. 69 (wash solution 1: 5% acetonitrile, 5% isopropanol, 20% acetic acid; wash solution 2: 4 M Urea, 1 M glycine, pH 2.5). All HDX samples were analysed in technical triplicates, except for the 15 min time point for PsV without heparin, which was measured in duplicate.</p> <p><br><strong>Data processing:</strong></p> <p>Peptides were identified from the MS/MS data by the Andromeda search algorithm implemented in MaxQuant (version 1.6.5.0) using a custom protein database containing the sequences of HPV16 L1 and L2 proteins. Deuterium uptake for the identified peptides was calculated with DeutEx (in-house developed), manually inspected and the statistical significance of the observed differences in deuteration was evaluated by applying an unpaired two-tailed Student’s T-test with single pooled variance evaluated with alpha ≤ 0.05 using the Holm-Šidák correction for multiple comparisons in Prism 8.0.1 (GraphPad Software). The processed data were visualized using MSTools (https://peterslab.org/MSTools/, Kavan & Man: International Journal of Mass Spectrometry 2011) and open-source PyMol 2.6.0a0 (Schrödinger, Inc).</p> <p>For ZENODO the datafiles were deposited as native Thermo .raw files (including instrumental parameters metadata) while all peaks in the spectra were additionally exported into plain m/z vs intensity .txt files per each scan in the LC-MS analysis as also used for the DeutEx HDX-MS processing.</p>
Ptychographic lensless coherent endomicroscopy through a flexible fiber bundle Dataset
<p>This data repository presents representative data of the data we use in the paper "Ptychographic lensless coherent endomicroscopy through a flexible fiber bundle" on the study of the USAF-1951 resolution target measurements. It includes a raw dataset of 3,000 measurements used for the reconstruction given in Fig. 2e-h.</p> <p>Directory Structure<br>LED Repository: This repository contains images using an LED to identify the fiber core centers for the sampling of the measurements. </p> <p>Core reflection Directory: Features back-reflected core measurements captured when illuminating the laser core by core. This dataset is collected without the USAF target at the distal facet, providing baseline data for the core reflection so that it can be removed from the measurements digitally.</p> <p>Measurements Directory: Consists of the raw data for the measurements taken with the USAF target placed at a 700-micron distance. This directory is the core of our dataset, offering raw, unprocessed measurements crucial for the analysis presented in our paper.</p> <p>Contact_LED_transmission: Contains a contact transmission image of the resolution target, captured with the target placed at contact distance and illuminated by an LED from behind. This serves as a reference image for transmission (Fig.2h).<br>Data Usage</p> <p>For more information, refer to Weinberg, Gil, et al. "<a href="https://arxiv.org/abs/2402.00148">Ptychographic lensless coherent endomicroscopy through a flexible fiber bundle</a>." arXiv preprint arXiv:2402.00148 (2024).</p>
Dataset of the publication: Reversible tuning of luminescence and magnetism in a structurally flexible erbium-anilato MOF
<p>Dataset of the publication: Reversible tuning of luminescence and magnetism in a structurally flexible erbium-anilato MOF</p> <p>DOI: 10.1039/d2sc00769j</p> <p>N. Monni, J. J. Baldoví, V. García-López, M. Oggianu, E. Cadoni, F. Quochi, M. Clemente-León, ML. Mercuri, E. Coronado</p> <p>Chem. Sci., 13, 25,7419-7428 (2022)</p>
How Binding Site Flexibility Promotes RNA Scanning in TbRGG2 RRM: A Molecular Dynamics Simulation Study
<p>The data necessary to independently reproduce the MD simulations and the first part of the simulation trajectories reported in the paper "<strong>How Binding Site Flexibility Promotes RNA Scanning in TbRGG2 RRM: A Molecular Dynamics Simulation Study</strong>", by Lemmens et al.</p> <p>Due to Zenodo data deposition limits, every 10th frame of the MD simulation trajectories is included. Due to Zenodo deposition limits, MD trajectory files for this paper are also available at 10.5281/zenodo.14260246.</p>
Support Data to "Interface flexibility controls the nucleation and growth of supramolecular networks"
<p><strong>Overview</strong></p> <p>This repository contains the inputs and support data for the publication "Interface Flexibility Controls the Nucleation and Growth of Supramolecular Networks," which is currently under review in Nature Chemistry.</p> <p><strong>Folder Structure</strong><br>Each subfolder is named after the primary method used to obtain the data. The internal structure may vary depending on whether it was more convenient to organize the data by the figure they were used for or by the structures analyzed. Each folder includes a detailed README.md file providing further information.<br><br><strong>Notes<br></strong>In the second version we added the data for Figure S27, which was not uploaded before due oversight.</p>
Floral preferences of mountain bumble bees are constrained by functional traits but flexible through elevation and season
Patterns of resource use by animals can clarify how ecological communities have assembled in the past, how they currently function, and how they are likely to respond to future perturbations. Bumble bees (Hymentoptera: Bombus spp.) and their floral hosts provide a diverse yet tractable system in which to explore resource selection in the context of plant-pollinator networks. Under conditions of resource limitation, the ability of bumble bees species to coexist should depend on dietary niche overlap. In this study, we report patterns and dynamics of floral morphotype preferences in a mountain bumble bee community based on ~13,000 observations of bumble bee floral visits recorded along a 1400 m elevation gradient. We found that bumble bees are highly selective generalists, rarely visiting floral morphotypes at the rates predicted by their relative abundances. Preferences also differed markedly across bumble bee species, and these differences were well-explained by variation in bumble bee tongue length, generating patterns of preference similarity that should be expected to predict competition under conditions of resource limitation. Within species, though, morphotype preferences varied by elevation and season, possibly representing adaptive flexibility in response to the high elevational and seasonal turnover of mountain floral communities. Patterns of resource partitioning among bumble bee communities may determine which species can coexist under the altered distributions of bumble bees and their floral hosts caused by climate and land use change.
Chaos and irreversibility of a flexible filament in periodically--driven Stokes flow
<pre>This directory contains a jupyter notebook file, generate_plots.ipynb which generate all the plots for paper "Chaos and irreversibility of a flexible filament in periodically driven Stokes flow" (arXiv:2111.14638) by Vipin Agrawal and Dhrubaditya Mitra. Readme.md file contains the information on how to use the data. If anything turns out to be incomplete, please reach to vipinagrawal25@gmail.com.</pre>
Data for "How flexible electrification can integrate fluctuating renewables"
<p>This upload provides the files used to compile and compute the input data used in the aforementioned working paper.</p>
How flexible, slit and rigid barriers mitigate two-phase geophysical mass flows: a numerical appraisal
<p>The supplementary videos SV1 and SV2 (presented in Figures 4 and 5) show geophysical flows impacting flexible, slit, and rigid barriers via pile-up mode and runup mode, respectively.</p> <p>The measurement data used for comparison in Figure 7 from 14 centrifuge tests with bouldery and the boulder-debris mixture flows (Song et al., 2018b, 2019), and dry granular flow against open-type dams (Choi et al., 2020) were published open access in their articles.</p> <p>The unique dataset, comprising normalized data obtained from analytical models (Li et al., 2021; Song et al., 2021a), empirical relations (Cui et al., 2015), experiments (Armanini et al., 2020; Choi et al., 2020; Cui et al., 2015; Hu et al., 2020; Song et al., 2021a, 2021b; Tiberghien et al., 2007; Vicari et al., 2021), field events (Hübl et al., 2009), and practical design values (Armanini, 1997; Hungr et al., 1984; Kwan & Cheung, 2012; Wendeler, 2016), is plotted in Figure 10 for comparison.</p> <p>All these articles can be found in the PDF file entitled “References in Figures 7 and 10”.</p>
Supplementary Movies and Dataset for Debris Flows, Debris Avalanches and Rock Avalanches Impacting A Flexible Ring Net Barrier.
<p>The supplementary movies S1, S2, and S3 (presented in Figures 1, S4, and S6) show typical debris flow, debris avalanche, and rock avalanche impacting a flexible ring net barrier with = 6 m/s, respectively.</p> <p>The experimental data used for comparison in Figure 2b from the large-scale flume test V6-B1 with a flexible ring net barrier was published open access in the below article (Vicari <em>et al.,</em> 2021).</p> <p>Vicari, H., Ng, C. W., Nordal, S., Thakur, V., De Silva, W. R. K., Liu, H., & Choi, C. E. (2021). The Effects of Upstream Flexible Barrier on the Debris Flow Entrainment and Impact Dynamics on a Terminal Barrier. <em>Canadian Geotechnical Journal</em>, <em>59</em>(6), 1007-1019. <a href="https://doi.org/10.1139/cgj-2021-0119">https://doi.org/10.1139/cgj-2021-0119</a></p>
Great tits (Parus major) flexibly learn that herbivore-induced plant volatiles indicate prey location – an experimental evidence with two tree species
<p>1. When searching for food, great tits (Parus major) can use herbivore-induced plant volatiles (HIPVs) as an indicator of arthropod presence. Their ability to detect HIPVs was shown to be learned, and not innate, yet the flexibility and generalization of learning remains unclear. 2. We studied if, and if so how, naïve and trained great tits (Parus major) discriminate between herbivore-induced and non-induced saplings of Scotch elm (Ulmus glabra) and cattley guava (Psidium cattleyanum). We chemically analysed the used plants and showed that their HIPVs differed significantly and overlapped only in a few compounds. 3. Birds trained to discriminate between herbivore-induced and non-induced saplings preferred the herbivore-induced saplings of the plant species they were trained to. Naïve birds did not show any preferences. Our results indicate that the attraction of great tits to herbivore-induced plants is not innate, rather it is a skill that can be acquired through learning, one tree species at a time. 4. We demonstrate that the ability to learn to associate HIPVs with food reward is flexible, expressed to both tested plant species, even if the plant species has not coevolved with the bird species (i.e. guava). Our results imply that the birds are not capable of generalising HIPVs among tree species but suggest that they either learn to detect individual compounds or associate whole bouquets with food rewards.</p>
Imaging data of mechanically loaded, micro-patterned, silk-reinforced cellulose films with gold coating for flexible electrodes in medical implants
<p>Neurodegenerative diseases can be treated using a functional interface between the physically soft tissue such as brain and the man-made electrodes. The orders of magnitude harder neural probes cause local injuries, due to periodic micromovements owing to breathing and pulsatile blood flow leading to encapsulation and related collapsing signals. An alternative to the currently used neural implant films including polyimide, poly(p-xylylene), SU-8 - epoxy-based negative photoresist, liquid crystal polymer, and benzocyclobutene is the natural polymer cellulose with an elastic modulus between 100 and 200 MPa. This article elucidates the measurement of the mechanical properties of bare as well as mono- and double-layer silk-reinforced cellulose in phosphate-buffered saline using a universal testing machine. In addition, the article contains electron microscopy data of these micro-structured, gold-coated films subsequent to peel-off tests to access the impact of micro-structures on gold adhesion on cellulose. These imaging data were completed by electron micrographs of mechanically loaded gold-coated cellulose films to demonstrate the impact of micro-structures on crack formation. Finally, the phosphate-buffered saline-induced swelling of the micro-structure was visualized by electron micrographs obtained before and after two-month storage in air and phosphate-buffered saline, respectively.</p>
Data for manuscript "rMATS-turbo: an efficient and flexible computational tool for alternative splicing analysis of large-scale RNA-seq data"
<p>Output files generated by rMATS-turbo for the two example datasets described in the manuscript titled "rMATS-turbo: an efficient and flexible computational tool for alternative splicing analysis of large-scale RNA-seq data".</p> <table> <tbody> <tr> <td>File</td> <td>Description</td> <td>Cell lines</td> <td>BioProject</td> </tr> <tr> <td>PC3E-GS689.tar.gz</td> <td>Compressed folder containing all 36 rMATS-turbo output files for Example 1 described in the manuscript</td> <td>PC3E and GS689 cell lines</td> <td>PRJNA438990</td> </tr> <tr> <td>CCLE.tar.gz</td> <td>Compressed folder containing all 36 rMATS-turbo output files for Example 2 described in the manuscript</td> <td>1,019 CCLE human cancer cell lines</td> <td>PRJNA523380</td> </tr> </tbody> </table> <p>A detailed description of the output files is available in the manuscript and the rMATS-turbo software GitHub repository (https://github.com/Xinglab/rmats-turbo).</p>
Two-dimensional vanadium sulfide flexible graphite/polymer films for near-infrared photoelectrocatalysis and electrochemical energy storage
<p>Raw data of published article "Two-dimensional vanadium sulfide flexible graphite/polymer films for near-infrared photoelectrocatalysis and electrochemical energy storage", DOI: 10.1016/j.cej.2022.135131</p>
Flexible Graphite−Poly(Lactic Acid) Composite Films as Large-Area Conductive Electrodes for Energy Applications
<p>Raw data of energy storage part -author Kalyan Ghosh </p>
Non-acoustic speech sensing system based on flexible piezoelectric
<p>The non-acoustic speech sensing system based on flexible piezoelectric is designed to satisfy specific needs around testing device models (in high-noise, complex environments). The system collected vibration signals from the jaws of six males and five females containing ten different control commands at 90 dB of background noise. The dataset is reliable with high intelligibility and is able to achieve 93.7% recognition accuracy by calculation. In general, this paper provides a non-acoustic speech dataset for Mandarin, including the parts collected, the number of people collected, and the environment.</p> <p><br> The dataset is available at:</p> <p>https://doi.org/10.5281/zenodo.7095762</p> <p><br> The data descriptor paper with details of data collection and cleaning process is under submission. For proper citation of the manuscript, please refer to the latest version of this dataset which includes the details.</p> <p>This dataset and its descriptor paper were created by:</p> <p>Shiji Yuan, Ying Sun, Dezhi Zheng, Xinlei Chen,Ying Ding, Shuai Wang, Shangchun Fan</p> <p>For questions or suggestions, please e-mail Dezhi Zheng <zhengdezhi@buaa.edu.cn></p> <p><br> <strong>Description:</strong><br> <br> Ten common words were chosen as the core of the vocabulary in this dataset. These ten command words can be used for commands in IoT or robotics applications: "forward", "backward", "right", "left", "stop", "up", "down", "draw", "drop", and "reset".</p> <p>The recording was carried on by software named Adobe Audition 2022. We set monophonic recording, 16-bit storage format, and 16 kHz sampling frequency before recording and saved the recorded voice in wav format. The dataset is provided with two storage rules, which are stored by subject number and command number as classification. In the first rule, the speech data of 11 subjects were stored in different folders with the subject serial number as the folder name. Each folder contains subfolders categorized by command. In the second rule, the speech data of ten commands are stored in different folders, and the names of the folders are the command contents. </p> <p><br> The subject number, command number and record order are given for each data entry. For example, the data obtained when subject 1 recorded command 10 for the first time was labeled as "1-10_1".</p> <p>After the data collection process, a filtering algorithm for automatic detection of low non-acoustic speech data was designed to remove problematic data that were very short or very quiet.The script of the data filtering algorithm is provided in this repository. </p> <p>For specific detail of the data filtering process, please refer to the script (speech data filtering algorithm in MATLAB) in this repository and the data descriptor paper.</p> <p>The dataset in this repository is the processed version. The raw dataset and removed audio files are not included in this repository.</p> <p><br> <br> <strong>File list:</strong></p> <p><br> Non-acoustic Speech Dataset.zip</p> <p>speech data filtering algorithm.zip</p> <p>Readme.txt </p>
Code and data used in "A Tool for Air Pollution Scenarios (TAPS v1.0) to enable global, long-term, and flexible study of climate and air quality policies"
<p>Data and code for Tool for Air Pollution Scenarios (TAPS v1.0) as submitted to Geoscientific Model Development for publication. See the enclosed README and full user manual (https://github.com/watkin-mit/TAPS/wiki) for more information. </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.