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565 results for “escapement”
Microbial narrow-escape is facilitated by wall interactions: Simulation Supplementary material
<p>Simulation codes and simulation results for the paper "Microbial narrow-escape is facilitated by wall interactions".</p>
Changes in gene expression during germination reveal pea genotypes with either 'quiescence' or 'escape' mechanisms of waterlogging tolerance
<p>Waterlogging causes germination failure in pea (<em>Pisum sativum</em> L.). Three genotypes (BM-3, NL-2 and Kaspa) contrasting in ability to germinate in waterlogged soil were exposed to different durations of waterlogging. Whole genome RNAseq was employed to capture differentially expressing genes. The ability to germinate in waterlogged soil was associated with testa colour and testa membrane integrity as confirmed by electrical conductivity measurements. Among the most differentially regulated genes, upregulated gene tyrosine protein kinase responsible for metabolic regulation and downregulated LOX5 involved in fat metabolism indicated energy preservation in tolerant Kaspa, while in the other tolerant NL-2 subtilase family protein and PNC2 involved in protein and fat metabolism respectively showed upregulated expression suggesting energy utilization during waterlogging. By contrast, in sensitive genotype BM-3 high upregulation was recorded for the kunitz-type trypsin/protease inhibitor whose role is blocking the activity of protein metabolism leading to excessive lipid metabolism causing membrane leakage and subsequent seed damage. Pathway analyses based on gene ontologies showed seed storage protein metabolism as upregulated in tolerant genotypes and downregulated in the sensitive genotype. Understanding the tolerance mechanism provides a platform to breed for adaptation to waterlogging stress at germination in pea. </p>
Changes in gene expression during germination reveal pea genotypes with either 'quiescence' or 'escape' mechanisms of waterlogging tolerance
<p>Waterlogging causes germination failure in pea (<em>Pisum sativum</em> L.). Three genotypes (BM-3, NL-2 and Kaspa) contrasting in ability to germinate in waterlogged soil were exposed to different durations of waterlogging. Whole genome RNAseq was employed to capture differentially expressing genes. The ability to germinate in waterlogged soil was associated with testa colour and testa membrane integrity as confirmed by electrical conductivity measurements. Among the most differentially regulated genes, upregulated gene tyrosine protein kinase responsible for metabolic regulation and downregulated LOX5 involved in fat metabolism indicated energy preservation in tolerant Kaspa, while in the other tolerant NL-2 subtilase family protein and PNC2 involved in protein and fat metabolism respectively showed upregulated expression suggesting energy utilization during waterlogging. By contrast, in sensitive genotype BM-3 high upregulation was recorded for the kunitz-type trypsin/protease inhibitor whose role is blocking the activity of protein metabolism leading to excessive lipid metabolism causing membrane leakage and subsequent seed damage. Pathway analyses based on gene ontologies showed seed storage protein metabolism as upregulated in tolerant genotypes and downregulated in the sensitive genotype. Understanding the tolerance mechanism provides a platform to breed for adaptation to waterlogging stress at germination in pea. </p>
Ferry et al. 2024 - Prey that is attractive but not repelled by predators suggests an asymmetric investment in the encounter-avoid-escape sequence. - R Code and Datasets
<p>R code for formating data and running PAMMs for all different combinations of predator-prey.</p> <p>Data of camera trap observation.</p> <p>Data of environmental variable associated to camera trap sites.</p>
Escape from NK cell tumor surveillance by NGFR-induced lipid remodeling in melanoma
<p>Metabolomics Data used in the publication</p> <p>1) raw files obtained by the FGCZ (<a href="https://fgcz.ch/">Functional Genomics Center Zurich</a>):</p> <p>QCpools (technical replicate of all sample pooled: p2947_o5292_SOP3_DDA5_pos_QCpool_cells</p> <p>Sample of M010817 CMVTOEV cells not induced: p2947_o5292_SOP3_DDA5_pos_EV_cells_noninduced_sample</p> <p>Sample of M010817 CMVTOEV cells induced: p2947_o5292_SOP3_DDA5_pos_EV_cells_induced_sample</p> <p>Sample of M010817 CMVTONGFR cells not induced: p2947_o5292_SOP3_DDA5_pos_p75_cells_noninduced_sample</p> <p>Sample of M010817 CMVTONGFR cells induced: p2947_o5292_SOP3_DDA5_pos_p75_cells_induced_sample</p> <p>2) method description LC-MS</p> <p>LC-MS-based lipidomic analysis was performed with M010817 CMVTOEV and CMVTONGFR cells pretreated with 1 μg/ml doxycycline for 24 h. Cells were detached with PBS 2 mM EDTA, washed and resuspended in 1-butanol/methanol (1:1). Cells were vortexed for 15 sec and subsequently sonicated on ice with a pulse of 3x 10 sec and 1x 30 sec at an amplitude of 15% using a SONOPULS HD 2070 Ultrasonic Homogenizer (Bandelin). Cell extracts were centrifuged at 16’000 g, 20°C for 10 min to remove macromolecules and subsequently diluted (1:3) with water/methanol (1:2) solution. The dilution was vortexed and centrifuged (16,000 x g, 20 °C, 10 min). 100 μl of the supernatant was transferred to a glass vial with narrowed bottom (Total Recovery Vials, Waters) for LC-MS injection. <br> Lipids were separated on a nanoAcquity UPLC (Waters) equipped with a HSS T3 capillary column (150 μm x30mm, 1.8 μm particle size, Waters), applying a gradient of 5 mM ammonium acetate in water/acetonitrile 95:5 (A) and 5 mM ammonium acetate in isopropanol/acetonitrile 90:10 (B) from 5% B to 100% B over 10 min. The following 5 min conditions were kept at 100% B, followed by 5 min reequilibration to 5% B. The injection volume was 1 μL. The flow rate was constant at 2.5 μl/min. The UPLC was coupled to QExactive mass spectrometer (Thermo) by a nanoESI source. MS data was acquired using positive polarization and data-dependent acquisition (DDA). Full scan MS spectra were acquired in profile mode from 80-1200 m/z with an automatic gain control target of 1e6, an Orbitrap resolution of 70`000, and a maximum injection time of 200 ms. The 5 most intense charged (z = +1 or +2) precursor ions from each full scan were selected for collision induced dissociation fragmentation. Precursor was accumulated with an isolation window of 0.4 Da, an automatic gain control value of 5e4, a resolution of 17`500, a maximum injection time of 50 ms and fragmented with a normalized collision energy of 20, 30 and 40 (arbitrary unit). Generated fragment ions were scanned in the linear trap. Minimal signal intensity for MS2 selection was set to 500.</p> <p> </p> <p>3) csv result files were generated by the FGCZ (<a href="https://fgcz.ch/">Functional Genomics Center Zurich</a>)</p> <p>adducts found: adducts_p2947_o5292_new_10K_20210910</p> <p>identifications found: identifications_p2947_o5292_new_10K_20210910</p> <p>abundances of features: measurements_p2947_o5292_new_10K_20210910</p> <p>Metaboanalyst file statistics: Metabo_p2947_o5292_10k_cells_CVcleaned_20210916</p> <p>Metaboanalyst file enrichment: Metabo_Enrichment_p2947_o5292_10k_cells_20210910 _p75</p> <p>4) method description data analysis</p> <p>Data sets were evaluated with Progenesis QI software (Nonlinear Dynamics), which aligns the ion intensity maps based on a reference data set, followed by a peak picking on an aggregated ion intensity map. Detected ions were identified based on accurate mass, detected adduct patterns and isotope patterns by comparing with entries in the LipidMaps Data Base (LM) and KEGG database. Considered adducts were M+H, M+NH4, 2M+H M+H-H2O. A mass accuracy tolerance of 5 ppm was set for the searches. Fragmentation patterns were considered for 600 the identifications of metabolites. Putative identifications were further ranked based on Mass error (observed mass – exact mass), isotope similarity (observed versus theoretical).</p> <p> </p>
Hiding in the heterochromatin: Endogenous pararetroviruses escape elimination from the genome of sugar beet (Beta vulgaris)
<p>Here we provide supplementary data for our study of endogenous pararetroviruses in the sugar beet genome (beetEPRVs).</p> <p>Our genome-wide screen showed the presence of three beetEPRVs families in the genome of sugar beet (<em>Beta vulgaris</em>). This dataset contains the consensus sequence for each beetEPRV family (Data S1) and the underlying multiple sequence alignments of individual, genomic beetEPRV copies (Data S2-S5). All data are provided in FASTA format. Sequence names include information on the analysed sugar beet assembly (EL10.1; genebank accession SAMN07736104; Funk <em>et al.</em>, 2018), chromosomal position (chromosome identifier; start and stop position), and sequence orientation (forward = plus; reverse = minus).</p>
sunset: A database of synthetic atmospheric-escape transmission spectra for nearly every transiting exoplanet
<div> <div> <p><strong>This sunset version belongs to the A&A paper. The sunset database belonging to the arXiv pre-print can be found as version 1 of this Zenodo repository.</strong></p> <p>This repository contains the sunset database of atmospheric-escape transmission spectra for most currently known transiting exoplanets. This database is described in Linssen et al. (2025). The complete zipped (unzipped) database is ~5GB (~28GB). To prevent a huge download just to access a specific single planet model, we have uploaded sunset in a few different batches. The "zip_dictionary.txt" file lists each planet and which zip batch it is in. </p> <p>For each planet, there are three files:<br>- The "info" file contains warnings that pertain to that planet specifically (for general warnings that apply to each planet, see Linssen et al. 2025). It also lists the used planetary parameters, and the transit depth, equivalent width, S/N prefactors and transmission spectroscopy metrics for a few spectral lines. Finally, it gives simple step-by-step instructions on how to reproduce the model results using sunbather.<br>- The "spectrum_sparse" file contains the transmission spectrum. In principle, the spectrum runs from 911 to 11,000 angstroms in 1,000,000 bins (translating to R~400,000). However, in large portions of this wavelength grid, there are no spectral lines and the transit spectrum is simply equal to the continuum. To keep the file size to a minimum, we have removed those continuum regions from the spectrum, resulting in a "sparse" spectrum.<br>- The "structure" file contains the radial atmospheric structure profiles of the density, velocity, temperature and mean molecular weight.</p> <p>Additionally, this repository includes "included_lines_by_species.txt" and "included_lines_by_wavelength.txt", which list all the spectral lines that are present in the transmission spectra. Lines are labeled by the specific ion that they originate from, as well as the energy level. The energy level is expressed as a number, where 1 is the ground state, 2 is the first excited state, etc. Translating this energy level into the atomic configuration can be done by looking in the sunbather source code: in the /sunbather/src/sunbather/RT_tables/ folder, each ion has a file such as "Fe+_levels_processed.txt", which lists the energy levels and their atomic configurations.</p> <p>Finally, there is a large tabular file called "sunset_overview.csv". This file includes the NASA Exoplanet Archive parameters of each exoplanet. Additionally, there are some columns that we added, with calculated variables such as the atmospheric mass-loss rate, the Parker wind temperature, and line depths, equivalent widths, S/N prefactors and TSM metrics for various spectral lines. See the file header for explanation of each column. The file can easily be read in Python using pandas.read_csv("sunset_overview.csv", comments="#")</p> </div> </div>
Mosquitoes escape looming threats by actively steering into the bow-wave induced by the attacker
<p>To detect and escape a threat, night flying insects must rely on other senses than vision alone. Here we study how anthropophilic malaria mosquitoes can escape a swatting hand in the dark using high-speed videography and numerical simulations. We show that these night flying mosquitoes escape looming objects by using the object-induced airflow in two ways. They first actively steer into the <a>bow-wave</a><span><span> </span></span> produced by the attacker, and then passively travel with this bow-wave away from the attacker; these two aspects explain two-thirds and one-third of their escape accelerations, respectively. Thus, flying mosquitoes being attacked in the dark rely both on airflow-sensing to trigger their escape, and on attacker-induced airflow to maximize their escape performance. Similar escape strategies are probably common among small lightweight insects.</p> <div> <div> <div></div> </div> </div>
Data and model code for article "Wildflower phenological escape differs by continent and spring temperature"
<p>This dataset contains seven spreadsheets and one R script. The spreadsheet "NC_Lee_etal_data.xls" contains the master data file associated with the article "Wildflower phenological escape differs by continent and spring temperature", along with a metadata sheet that describes the column names. The other six spreadsheets contain the continent (EA = East Asia, ENA = Eastern North America, and EU = Europe) x lifeform (forbs or trees) specific datasets used in the supplementary models containing spatial autocorrelation terms.</p> <p>The script contains annotated example code to run the models used in the final analysis.</p> <p>Questions about the code or analysis should be directed to the lead author (Benjamin R Lee).</p>
The Gloria2 fish farm escapes identification dataset (v1.0)
<p>This is version 1.0 of the <strong>GLORiA<sup>2</sup> dataset</strong>, which can be used for the training of computer vision models aimed at <strong>detecting fish farm escapes caused by sea storms</strong>. Escaped fish can be recognized based on their appearance from pictures taken in lab conditions, when compared to farmed and wild specimens. Several images of fish specimens raised in <strong>captivity</strong> (C), farm <strong>escapes</strong> (E), and the <strong>sea</strong> (S) are provided for each of the <strong>three</strong> considered commercial <strong>species</strong>: Mediterranean <strong>sea bream</strong> (<em>S. aurata</em>), <strong>sea bass</strong> (<em>D. labrax</em>), and <strong>meagre</strong> (<em>A. regius</em>).</p> <p>The images provided are 224x224 crops of the original images, centred around the fish in the image, as <strong>preprocessed</strong> by the <strong>accompanying Python scripts</strong>.</p> <p><strong>Acknowledgement: </strong>GLORiA<sup>2</sup> is a project supported by the Biodiversity Foundation of the Ministry for the Ecological Transition, through the FEMP Pleamar Programme. It is also part of the LIFE IP INTEMARES project "Integrated, innovative and participatory management of the Natura 2000 Network in the Spanish marine environment", coordinated by the Ministry, through the Biodiversity Foundation.</p> <p> </p>
Source data files for manuscript "Closed Magnetic Topology in the Venusian Magnetotail and Ion Escape at Venus"
<p>The zip file contains source data files for all figures in the manuscript "Closed Magnetic Topology in the Venusian Magnetotail and Ion Escape at Venus" published in Nature Communications. DOI: 10.1038/s41467-024-50480-0.</p>
Pilotierung eines hybriden Escape Games zur altersübergreifenden Förderung digitaler Souveränität
<p>Mithilfe des entwickelten hybriden Escape Games <a href="https://doi.org/10.5281/zenodo.12763039" target="_blank" rel="noopener"><em>Die rätselhafte Karte</em></a> sollen grundlegende<sub> </sub>Digitalkompetenzen<sub> </sub>als<sub> </sub>Voraussetzung<sub> </sub>für<sub> </sub>die<sub> </sub>Entwicklung<sub> </sub>und<sub> </sub>Förderung<sub> </sub>digitaler<sub> </sub>Souveränität<sub> </sub>altersübergreifend<sub> </sub>auf<sub> </sub>explorierbare,<sub> </sub>erlebbare<sub> </sub>und<sub> </sub>somit<sub> </sub>nachvollziehbare<sub> </sub>sowie<sub> </sub>motivationsfördernde<sub> </sub>Weise vermittelt werden. Im Rahmen erster praktischer Erprobungen gilt es somit zu ermitteln, ob sich dieses im Aufbau und im Design neuartige Escape Game grundsätzlich für einen praktischen Einsatz im schulischen Kontext und im Freizeitbereich sowie für die intendierte Kompetenzvermittlung eignet.</p>
Data for "Computational design of developable therapeutic antibodies: efficient traversal of binder landscapes and rescue of escape mutations"
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Data for the manuscript: "Self-organization of collective escape in pigeon flocks"
<p>This repository contains all data (empirical and simulated) used and generated for the paper "Self-organization of collective escape in pigeon flocks" (2022) <em>PLoS Comput Biol 18(1): e1009772. <a href="https://doi.org/10.1371/journal.pcbi.1009772">https://doi.org/10.1371/journal.pcbi.1009772</a></em>. More information can be found in the README file and the connected GitHub repository: https://github.com/marinapapa/SelfOrg-ColEsc-Pigeons/</p>
Civil war is associated with longer escape distances among Sri Lankan birds - flight-initiation distances of Sri Lankan birds
<p>War influences wildlife in a variety of ways but may influence their escape responses to approaching threats, including humans, because of its effect on human populations and behaviour, and landscape change. We collected 1,400 Flight-Initiation Distances (FIDs) from 157 bird species in the dry zone of Sri Lanka, where civil war raged for 26 years, ending in 2009. Accounting for factors known to influence FIDs (phylogeny, starting distance of approaches, body mass, prevailing human density, group size and location), we found birds have longer FIDs in the part of the dry zone which experienced civil war. Larger birds, often preferred by human hunters, showed greater increases in FID in the war zone, consistent with the idea that war was associated with greater hunting pressure, that larger birds experienced longer-lasting trauma, or had more plastic escape behaviour, than smaller species. While the mechanisms linking the war and avian escape responses remain ambiguous, wars evidently leave legacies which extend to behavioural responses in birds.</p>
gonzaloprb/Deep_Bleaching_French_Polynesia: Mesophotic coral communities escape thermal coral bleaching in French Polynesia
<p>Mesophotic coral communities escape thermal coral bleaching in French Polynesia</p> <p>Ecological assessment of coral bleaching along an extreme depth gradient (6-90 m) in French Polynesia.</p> <p>Unique Rmarkdown "Code_and_Analysis" to generate all analysis and figures. Including Supplementary figures.</p> <p>Date: 17/08/2021</p>
A close-in giant planet escapes engulfment by its star
<p>Data for Nature article 'A close-in giant planet escapes engulfment by its star'.</p> <p>Included in this repository are:</p> <p>TESS oscillation spectra of host star -- tess_oscillation_spectra.zip<br> CHFT ESPaDOnS spectropolarimetry of host star and control red giant -- espadons_polarimetric_spectra.zip<br> Least squares deconvolution profiles of spectropolarimetry data -- lsd_profiles.zip<br> Markov chain Monte Carlo chains for radial velocity fitting -- mcmc.zip<br> Inlists for MESA binary simulations -- mesa_binary.zip<br> Keck/HIRES radial velocity measurements of host star and control red giant -- rv.zip<br> Keck/HIRES S_HK indices of host star and control red giant -- s_hk.zip<br> Measurements and model of host star spectral energy distribution -- sed.zip<br> Hipparcos, ASAS-SN, and TESS light curves for host star -- other_photometry.zip</p>
Data from: Breeding Sternula antillarum (Least Terns) disturbance distances and duration of escape behaviors: pedestrians necessitate larger conservation buffers than do passing vehicles
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Data from: the flashy escape: support for dynamic flash colouration as anti-predator defence
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Data from: Genetic and habitat complexity effects on unpredictability in escape behavior of a grasshopper species
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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.
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