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1,368 results for “Proximity”
Trajectory Design for Proximity Operations: The Relative Orbital Elements' Perspective
<p>The data sets provided here can be used to recreate the plots of the paper “Trajectory Design for Proximity Operations: The Relative Orbital Elements’ Perspective” available at this <a href="https://arc.aiaa.org/doi/full/10.2514/1.G006175">link</a>.</p> <p>That paper presents how to rigorously transform back-and-forth the equations of the relative motion in the close-range regime between Hill-Clohessy-Wiltshire and Relative Orbital Elements formulations. As straightforward application, it is presented a methodology to generate piecewise constant acceleration profiles from an impulsive guidance solution, setting up a control grid that minimizes the difference between impulsive and equivalent delta-v burns corresponding to the acceleration profile.</p> <p>Applications are implementation of autonomous guidance and control policies for close-range satellite proximity operations.</p>
Impact of Snowmelt Timing and Tree Proximity on Dutchman's Breeches Phenology and Performance in Mont Megantic National Park (Quebec, Canada; 2018-2019)
Data herein were collected in 2018 and 2019 in Mont Megantic National Park, Quebec, Canada, in a sugar maple-dominated temperate deciduous forest. Individuals of Dutchman's breeches (Dicentra cucullaria), a common understory spring ephemeral plant that is only active in the spring, were transplanted into a fully factorial experiment of snowmelt timing (early vs. late) and tree proximity (near vs. far) to determine the role of thaw circle formation in the local clustering of this species near canopy tree trunks. Plant phenology (emergence, senescence, and growing season length) and performance (stem abundance and leaf area) were tracked during two years of snow manipulation. Additionally, microclimate temperature data were collected in a subset of plots in 2018.
D4.1 Review on Accuracy of Proximal Soil Sensors Dataset
<p><span lang="EN-US">The dataset includes the raw data about PSS accuracy based on the root-mean-square error (RMSE) and wet chemistry analytical data on which we based our analysis, organized in a comma-separated value (CSV) file. A table with the metadata of the accuracy dataset is included in this document. A previous version of the dataset present in this supplementary has already been published in the Zenodo repository with the following associated DOI: <a href="https://doi.org/10.5281/zenodo.14035520">https://doi.org/10.5281/zenodo.14035520</a>. The current version updates the previous one due to incongruencies found after the upload. The PDF file contains a table that give information about the fields in the CSV.</span></p>
Vent-Proximal Deposits South of Ascraeus Mons, Mars
<p>The data repository contains the mapping shapefiles of geological units, data pertaining to the thickness measurements of the vent-proximal deposits, and Excel sheets that allow to reproduction of the spatter rampart deposits investigation south of Ascraeus Mons, Mars. The mapping and thickness measurements were conducted based on the CTX stereo-pair images P02_001774_1848, centered at 4.86°N, 254.60°E, and B01_009949_1844, centered at 4.46°N, 254.62°E, from which the digital elevation model was produced using MarsSI system (Mars System of Information) designed by Quantin-Nataf et al. (2018). To calculate vertical errors on elevations, we used an additional CTX-based DEM (B01_009949_1844 centered at 4.46°N, 254.62°E, and F02_036427_1847, centered at 4.80°N, 254.61°E).</p>
Synthetic AIS Dataset of Vessel Proximity Events
<p>The Automatic Identification System (AIS) allows vessels to share identification, characteristics, and location data through self-reporting. This information is periodically broadcast and can be received by other vessels with AIS transceivers, as well as ground or satellite sensors. Since the International Maritime Organisation (IMO) mandated AIS for vessels above 300 gross tonnage, extensive datasets have emerged, becoming a valuable resource for maritime intelligence.</p> <p>Maritime collisions occur when two vessels collide or when a vessel collides with a floating or stationary object, such as an iceberg. Maritime collisions hold significant importance in the realm of marine accidents for several reasons:</p> <ol> <li>Injuries and fatalities of vessel crew members and passengers.</li> <li>Environmental effects, especially in cases involving large tanker ships and oil spills.</li> <li>Direct and indirect economic losses on local communities near the accident area.</li> <li>Adverse financial consequences for ship owners, insurance companies and cargo owners including vessel loss and penalties.</li> </ol> <p>As sea routes become more congested and vessel speeds increase, the likelihood of significant accidents during a ship's operational life rises. The increasing congestion on sea lanes elevates the probability of accidents and especially collisions between vessels.</p> <p>The development of solutions and models for the analysis, early detection and mitigation of vessel collision events is a significant step towards ensuring future maritime safety. In this context, a synthetic vessel proximity event dataset is created using real vessel AIS messages. The synthetic dataset of trajectories with reconstructed timestamps is generated so that a pair of trajectories reach simultaneously their intersection point, simulating an unintended proximity event (collision close call). The dataset aims to provide a basis for the development of methods for the detection and mitigation of maritime collisions and proximity events, as well as the study and training of vessel crews in simulator environments.</p> <p>The dataset consists of 4658 samples/AIS messages of 213 unique vessels from the Aegean Sea. The steps that were followed to create the collision dataset are:</p> <p>Given 2 vessels X (vessel_id1) and Y (vessel_id2) with their current known location (LATITUDE [lat], LONGITUDE [lon]): </p> <ol> <li>Check if the trajectories of vessels X and Y are spatially intersecting.</li> <li>If the trajectories of vessels X and Y are intersecting, then align temporally the timestamp of vessel Y at the intersect point according to X’s timestamp at the intersect point. The temporal alignment is performed so the spatial intersection (nearest proximity point) occurs at the same time for both vessels.</li> <li>Also for each vessel pair the timestamp of the proximity event is different from a proximity event that occurs later so that different vessel trajectory pairs do not overlap temporarily.</li> </ol> <p>Two csv files are provided. vessel_positions.csv includes the AIS positions vessel_id, t, lon, lat, heading, course, speed of all vessels. Simulated_vessel_proximity_events.csv includes the id, position and timestamp of each identified proximity event along with the vessel_id number of the associated vessels. The final sum of unintended proximity events in the dataset is 237. Examples of unintended vessel proximity events are visualized in the respective png and gif files.</p> <p>The research leading to these results has received funding from the European Union's Horizon Europe Programme under the CREXDATA Project, grant agreement n° 101092749. </p>
Heavy metals in mammal tissue over the last 100 years and their proximity to populated places in Minnesota
This dataset makes use of the University of Minnesota's Bell Museum of Natural History collection examining specimens of four mammal species (a mouse, shrew, bat and squirrel) to ask how tissue metal content has changed over a 94-year time period (1911-2005), and implications for measures of individual performance (body size and cranial capacity). The metal content of organisms is often elevated closer to cities, so these specimens were examined for spatial variation in metal exposure based on their proximity to human populations and the size of those populated areas at the time of collection. Analysis of mammal tissues focused on six heavy metals associated with human activity (Pb, Cd, Zn, Cu, Cr, Ni, Mn), to address whether these anthropogenic metal pollutants vary in concert with human activity.
Intuitive 3D Control of a Quadrotor in User Proximity with Pointing Gestures (Dataset)
<p>The accompanying dataset and code for the ICRA 2020 publication:</p> <p>B. Gromov, J. Guzzi, L. Gambardella, and A. Giusti, "Intuitive 3D Control of a Quadrotor in User Proximity with Pointing Gestures," in 2020 IEEE International Conference on Robotics and Automation (ICRA), 2020.</p> <p>The dataset contains a log of user actions and states of the system collected during the user study. The subjects had to fly a nano quadcopter (Bitcraze Crazyflie 2.0) between three targets placed at different heights by using a conventional joystick interface (Logitech F710) and pointing. The pointing is reconstructed using an inertial sensor (mbientlab MetaWearR+) placed on the user's wrist.</p>
The proximity interactome of the peach-potato aphid (Myzus persicae) cathepsin B in Arabidopsis thaliana
<p><strong>Introduction</strong></p> <p>In agriculture, the peach-potato aphid <em>Myzus persicae</em> (Sulzer) has one of the broadest host ranges among insects and cause devastating crop losses worldwide (CABI, 2022). They are highly adaptable, displaying a wide range of plastic responses to environmental cues, including the ability to develop as either winged or wingless forms and to reproduce through either asexual or sexual means (Brisson, 2010; Ogawa and Miura, 2014; Grantham and Brisson, 2018). Remarkably, <em>M. persicae </em>differentially regulate the transcription of certain gene clusters to facilitate colonization of diverse plant species (Mathers et al., 2017; Chen et al., 2020). Among these gene clusters are members of the cysteine protease family, cathepsin B (CathB).</p> <p>Host responsive CathB genes are organized in tandemly repeated clusters in the <em>M. persicae</em> genome and belong to a recently expanded clade in phylogeny (Mathers et al., 2017). They are upregulated when aphids feed on <em>Arabidopsis thaliana </em>and <em>Brassica rapa</em> and knock down of their expression using RNA interference reduces aphid reproduction on <em>A. thaliana </em>(Chen et al., 2020). Intriguingly, peptides corresponding to CathB proteins are detected in <em>M. persicae</em> oral secretion (OS), indicating that at least some CathB proteins are directly delivered into plant cells during aphid feeding (Guo et al., 2020; Liu et al., 2024).</p> <p>Among <em>M. persicae</em> CathB proteins, CathB6 is most highly expressed in aphids on <em>A. thaliana</em> (Chen et al., 2020) and most abundant in <em>M. persicae</em> OS (Liu et al., 2024). To identify the potential plant targets of <em>M. persicae</em> CathB, we optimized the TurboID-based proximity labelling and MS (PL-MS) protocol (Fig. 1).</p> <p>As a first step, we generated stable transgenic <em>A. thaliana</em> lines producing GFP or CathB6 as C-terminal TurboID-3×FLAG fusions (GFP-TurboID or CathB6-TurboID). Seedlings of these plants were treated with biotin followed by affinity capture with streptavidin beads (Fig. 2A). Enrichment of biotinylated proteins was confirmed by western blotting (Fig. 2B), followed by nanoLC-MS/MS analyses.</p> <p>Principal component analysis (PCA) of the MS data showed that the three CathB6-TurboID samples were grouped together, separately from three GFP-TurboID samples (Fig. 2C). Furthermore, MA plot confirmed that the CathB6-TurboID and GFP-TurboID samples are distinct (Fig. 2D). From the complete dataset, 267 <em>A. thaliana</em> proteins exhibited statistically significant enrichment (<em>p</em>-value < 0.05) of more than 2-fold and were consistently identified in at least two replicates of the CathB6-TurboID samples compared to the GFP-TurboID controls (Fig. 2E, Table 1). This compares to 223 proteins in the GFP-TurboID samples versus CathB6-TurboID samples (Fig. 2E, Table 1). Additionally, we identified 20 unique peptides corresponding to CathB6 in the CathB6-TurboID samples and 19 unique peptides corresponding to GFP in the GFP-TurboID samples (Table 1). These data suggest that this PL-MS protocol worked dnd identified genuine interactors of CathB6.</p> <p>Together, this dataset identifies 267 potential plant interactors of aphid CathB6, which may contribute to CathB6 modulation of <em>A. thaliana</em> plant for colonization. Further mechanistic studies should be done to characterize if these potential interactors are involved and how the relevant pathways are affected after CathB delivery through aphid feeding.</p> <p> </p> <p><strong>Materials and Methods</strong></p> <p><em>Plasmid construction</em></p> <p>For the construction of plasmids producing CathB6-TurboID-3×FLAG, the coding sequences corresponding to the catalytic domain (without signal peptide and prodomain regions) of CathB6 (Arg61-Asn338) and TurboID-3×FLAG were separately amplified. Then, the two fragments were connected using overlap PCR (Nelson and Fitch, 2011). After cloning of the sequence corresponding to the CathB6-TurboID-3×FLAG fragment into the pJET vector and sequencing, CathB6-TurboID-3×FLAG was amplified with primers containing <em>attB</em> extensions and cloned into the pDONOR207 vector, followed by the ligation to Gateway destination vector pB7WG2 containing a 35S promoter. Similar cloning methods were used for construction of GFP-TurboID-3×FLAG.</p> <p><em>Plant transformation</em></p> <p>The constructed plasmids were introduced into <em>Agrobacterium tumefaciens</em> strain GV3101, and the cultures were grown on plates at 28 °C for 24–48 hrs. Then, positive colonies were identified via PCR using plasmids extracted from overnight liquid cultures and gene-specific primers. Positive colonies were grown at 28 °C in liquid cultures and transformed into <em>A. thaliana</em> Col-0 plants using the floral dipping method (Bechtold, 1993). Transgenic seeds were harvested and selected on Murashige and Skoog (MS) medium supplemented with 20 μg/mL phosphinothricin (BASTA) and screened for ratio of 3:1 alive/dead segregation. After screening for two or three generations, transgenic plants were deemed to harbor single homozygous transgenes and were used for proximity labeling once germinated seeds achieved a 100% survival rate.</p> <p><em>Proximity labelling</em></p> <p>Seeds of <em>A. thaliana</em> plants stably expressing GFP-TurboID-3×FLAG or CathB6-TurboID-3×FLAG were sowed on ½ MS plates containing 1.0% sucrose and 0.3% phytagel and placed under long-day condition (16 h light/8 h dark) at 22 °C. After 10 days, 2.5 g seedlings were collected and submerged in 50 µM biotin solution for 4 hrs at RT. Afterwards, seedlings were rinsed with ice-cold MilliQ water for 5 times. After removing excess liquid with paper towel, seedings were ground with pestle, mortar and nitrogen to a fine powder. Protein extraction was performed in 5 mL of extraction buffer [150 mM Tris-HCl (pH 7.5), 150 mM NaCl, 1 mM EDTA, 10% Glycerol, 10 mM DTT, 0.4% Nonidet-40, 0.1% (w/v) Deoxycholic acid, 2% (w/v) PVPP, 1 tablet of cOmplete protease Inhibitor cocktail (Roche, Catalog number 10697498001)] and incubation on a rotor wheel at 4 °C for 30 min, followed by centrifugation of the tubes at 5000 g for 15 min to remove the cell debris. The upper soluble fraction was then run through the Zeba Spin Desalting Column (Thermo Fisher Scientific, Catalog number 89893) to remove excess biotin from the lysates. Fifty (50) µL of desalted lystate was used as input for western blot analysis, while the rest of the desalted lysate was incubated with High Capacity Streptavidin Agarose Resin (Thermo Fisher Scientific, Catalog number 20361) on a rotor wheel at 4 °C overnight. The next day, Streptavidin beads were sequentially washed once in 1 mL Buffer 1 (2% SDS in water), once in 1 mL Buffer 2 [150 mM Tris-HCl (pH 7.5), 150 mM NaCl, 1 mM EDTA, 10% Glycerol, 0.1% (w/v) Deoxycholic acid (w/v), 1% Triton X-100], once in buffer 3 [10 mM Tris-HCl (pH 7.4), 250 mM LiCl, 1 mM EDTA, 0.1% (w/v) Deoxycholic acid, 1% (v/v) NP40], twice in Buffer 4 [50mM Tris-HCl (pH 7.5)], and six times in Buffer 5 (50mM ammonium bicarbonate, pH 8.0). Finally, the streptavidin beads were resuspended in 200 µL of 50 mM ammonium bicarbonate. For quality control of the TurboID immunoprecipitation, 10% (20 µL) of the suspension was taken out for Western blot analysis, and the remaining bead suspension was flash-frozen in liquid nitrogen and stored at -80 °C and submitted to nano LC-MS/MS analysis.</p> <p>For western blot analysis, 20 µL of suspended streptavidin beads in washing buffer 5 were added to 10 µL of 4× LDS Sample Loading Buffer, 10 mM DTT and 2 mM biotin, and boiled for 10 min. Samples were loaded onto 12% SDS-PAGE gels (Invitrogen) and transferred to 0.22 μm PVDF membranes using the Bio-Rad mini-PROTEAN Electrophoresis system. Membranes were hybridized with Streptavidin-HRP.</p> <p><em>NanoLC-MS/MS</em></p> <p><em> </em>Biotinylated proteins enriched with streptavidin beads were processed with trypsin via on bead digestion. The beads were washed in water and resuspended in of 1.5% sodium deoxycholate (SDC; Merck) in 0.2 M EPPS-buffer (Merck) to 50% bead slurry vol/vol, pH 8.5 and vortexed under heating. Cysteine residues were reduced with dithiothreitol, alkylated with iodoacetamide, and the proteins digested with trypsin in the SDC buffer according to standard procedures for 8 hrs. The beads were then pelleted by centrifugation and the supernatant was collected for SDC precipitation by adding trifluoroacetic acid (TFA) to a final concentration of 0.2%. The clear supernatant was subjected to C18 SPE using home-made stage tips with C18 Reprosil_pur 120, 5 µm (Dr. Maisch GmbH, Germany). Aliquots were analyzed by nano LC-MS/MS on an Orbitrap Eclipse™ Tribrid™ mass spectrometer equipped with a FAIMS Pro Duo interface coupled to an UltiMate® 3000 RSLC nano LC system (Thermo Fisher Scientific, Hemel Hempstead, UK). The samples were loaded onto a trap cartridge (PepMap™ Neo Trap Cartridge, C18, 5um, 0.3x5mm, Thermo) with 0.1% TFA at 15 µl min-1 for 3 min. The trap column was then switched in-line with the analytical column (Aurora Frontier TS, 60 cm nanoflow UHPLC column, ID 75 µm, reversed phase C18, 1.7 µm, 120 Å; IonOpticks, Fitzroy, Australia) for separation at 55°C using the following gradient of solvents: A (water, 0.1% formic acid) and B (80% acetonitrile, 0.1% formic acid) at a flow rate of 0.26 µl min-1 : 0-3 min 1% B (parallel to trapping); 3-10 min increase B (curve 4) to 8%; 10-102 min linear increase B to 48; followed by a ramp to 99% B and re-equilibration to 0% B. Total runtime was 140 min.</p> <p>Mass spectrometry data were acquired between 10 and 110 min with the FAIMS device set to three compensation voltages (-35V, -50V, -65V) at standard resolution for 1.0 s each with the following MS settings in positive ion mode: OT resolution 120K, profile mode, mass range m/z 300-1600, normalized AGC target 100%, max inject time 50 ms; MS2 in IT Turbo mode: quadrupole isolation window 1 Da, charge states 2-5, threshold 1e4, HCD CE = 30, AGC target standard, max. injection time dynamic, dynamic exclusion 1 count for 15 s with mass tolerance of ±10 ppm, one charge state per precursor only.</p> <p>The mass spectrometry raw data were processed and quantified in Proteome Discoverer 3.1 (PD3.1) (Thermo) using the search engine CHIMERYS (MSAID, Munich, Germany); all mentioned tools of the following workflow are nodes of the proprietary Proteome Discoverer (PD) software. The <em>A. thaliana</em> protein sequence database (TAIR10, 35,386 entries, from 14/12/2010), the two sequences of the used TurboID constructs, and the MaxQuant contaminants database (240812, 246 entries) were imported into PD adding a reversed sequence database for decoy searches.</p> <p>The database search was performed using the search engine CHIMERYS (MSAID, Munich, Germany). The processing workflow started with spectrum recalibration, Minora Feature Detection with min. trace length 5, S/N 2.5, PSM confidence high, and Top N Peak Filter with 20 peaks per 100 Da. For CHIMERYS, the inferys_3.0.0_fragmentation prediction model with FDR targets 0.01 (strict) and 0.05 (relaxed), a fragment tolerance of 0.3 Da, enzyme trypsin with 2 missed cleavages, variable modification oxidation (M), fixed modification carbamidomethyl (C) were used.</p> <p>The consensus workflow in the PD3.1 software was used to evaluate the peptide identifications and to measure the abundances of the peptides based on the LC-peak intensities. For chromatographic alignment and feature mapping, a retention time tolerance of 2 min, a mass tolerance of 1 ppm, and an S/N threshold of 5 were used. For quantification, three replicates per condition were measured. In PD3.1, the following parameters were used for ratio calculation: normalization on total peptide abundances, protein abundance-based ratio calculation using the Top3 most abundant peptides, missing values imputation by low abundance resampling, hypothesis testing by t-test (background based), adjusted <em>p</em>-value calculation by BH-method. The results were exported into a Microsoft Excel table including data for protein abundances, ratios, <em>p</em>-values, number of peptides, protein coverage, the CHIMERYS identification score and other important values.</p> <p> </p> <p><strong>Data availability statement</strong></p> <p>The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier with the dataset identifier PXD057789 and 10.6019/PXD057789.</p> <p> </p> <p><strong>Acknowledgements</strong></p> <p><strong> </strong>This research was funded by UK Research and Innovation (UKRI) Biotechnology and Biological Sciences Research Council (BBSRC) grants to SAH (BB/V008544/1 and BB/R009481/1). Additional Support is provided by the BBSRC Institute Strategy Programmes (BBS/E/J/000PR9797 and BBS/E/JI/230001B) awarded to the JIC. The JIC is grant-aided by the John Innes Foundation.</p> <p> </p> <p><strong>Conflicts of Interest</strong></p> <p><strong> </strong>The authors declare that no conflicts of interest exist.</p> <p> </p> <p><strong>Legends of figures and tables</strong></p> <p><strong>Figure 1. Principle of CathB6-TurboID based proximity labelling with MS (PL-MS). </strong>The TurboID biotin ligase (TurboID) is fused to C-terminus of CathB6. Exogenous addition of biotin (yellow stars) biotinylates proteins in the proximity of CathB6-TurboID fusion protein, whereas distal proteins are not biotinylated. The biotinylated proteins are captured by incubating total proteins extracts with streptavidin beads. Peptides derived from biotinylated proteins, most of which are in the proximity of CathB6-TurboID, are detected by nanoLC-MS.</p> <p><strong>Fig. 2. Sample preparation and quantification for CathB6-TurboID interactome in <em>A. thaliana</em>. </strong>(<strong>A</strong>) Sample preparation working flow for TurboID-based proximity labeling. GFP-TurboID and CathB6-TurboID seedlings were treated with 50 µM biotin for 4 hrs at room temperature. (<strong>B</strong>) Visualization on western blots of biotinylated proteins detected after desalting step (input) and 12 wash steps of Streptavidin beads (Streptavidin IP) as per workflow shown in (A). (<strong>C</strong>) Principal component analysis (PCA) of three replicates of GFP-TurboID and CathB6-TurboID samples. (<strong>D</strong>) MA plot of three replicates of GFP-TurboID and CathB6-TurboID samples. (<strong>E</strong>) Venn diagrams showing the overlap of proteins identified in three biological replicates of GFP-TurboID (left) and CathB6-TurboID (right) upon a fold-change of CathB6-TurboID/GFP-TurboID > 2, n = 267. </p> <p><strong>Table 1. Full list of proteins detected from CathB6-TurboID PL-MS.</strong></p> <p> </p> <p> </p> <p><strong>References</strong></p> <p><strong>Bechtold, N.</strong> (1993). In planta Agrobacterium-mediated gene transfer by infiltration of adult Arabidopsis thaliana plants. CR Acad. Sci. Paris, Life Sci. <strong>316, </strong>1194-1199.</p> <p><strong>Brisson, J.A.</strong> (2010). Aphid wing dimorphisms: linking environmental and genetic control of trait variation. Philos Trans R Soc Lond B Biol Sci <strong>365, </strong>605-616.</p> <p><strong>CABI, C.f.A.a.B.I.</strong> (2022). Myzus persicae (green peach aphid). CABI Compendium.</p> <p><strong>Chen, Y., Singh, A., Kaithakottil, G.G., Mathers, T.C., Gravino, M., Mugford, S.T., van Oosterhout, C., Swarbreck, D., and Hogenhout, S.A.</strong> (2020). An aphid RNA transcript migrates systemically within plants and is a virulence factor. Proc Natl Acad Sci U S A <strong>117, </strong>12763-12771.</p> <p><strong>Grantham, M.E., and Brisson, J.A.</strong> (2018). Extensive Differential Splicing Underlies Phenotypically Plastic Aphid Morphs. Mol Biol Evol <strong>35, </strong>1934-1946.</p> <p><strong>Guo, H., Zhang, Y., Tong, J., Ge, P., Wang, Q., Zhao, Z., Zhu-Salzman, K., Hogenhout, S.A., Ge, F., and Sun, Y.</strong> (2020). An Aphid-Secreted Salivary Protease Activates Plant Defense in Phloem. Curr Biol <strong>30, </strong>4826-4836.e4827.</p> <p><strong>Liu, Q., Goldberg, J.K., Mugford, S.T., Saalbach, G., Martins, C., Singh, A., Kaithakotti, G.G., Swarbreck, D., and Hogenhout, S.A.</strong> (2024). The salivary proteome of the green peach aphid/peach-potato aphid (Myzus persicae) (Sulzer, 1776) (Hemiptera, Aphididae) (Zenodo).</p> <p><strong>Mathers, T.C., Chen, Y., Kaithakottil, G., Legeai, F., Mugford, S.T., Baa-Puyoulet, P., Bretaudeau, A., Clavijo, B., Colella, S., Collin, O., Dalmay, T., Derrien, T., Feng, H., Gabaldón, T., Jordan, A., Julca, I., Kettles, G.J., Kowitwanich, K., Lavenier, D., Lenzi, P., Lopez-Gomollon, S., Loska, D., Mapleson, D., Maumus, F., Moxon, S., Price, D.R., Sugio, A., van Munster, M., Uzest, M., Waite, D., Jander, G., Tagu, D., Wilson, A.C., van Oosterhout, C., Swarbreck, D., and Hogenhout, S.A.</strong>(2017). Rapid transcriptional plasticity of duplicated gene clusters enables a clonally reproducing aphid to colonise diverse plant species. Genome Biol <strong>18, </strong>27.</p> <p><strong>Nelson, M.D., and Fitch, D.H.</strong> (2011). Overlap extension PCR: an efficient method for transgene construction. Methods Mol Biol <strong>772, </strong>459-470.</p> <p><strong>Ogawa, K., and Miura, T.</strong> (2014). Aphid polyphenisms: trans-generational developmental regulation through viviparity. Front Physiol <strong>5, </strong>1.</p>
Raw Metrics and Rankings for "Exploratory Analysis on Pixelwise Image Segmentation Metrics with an Application in Proximal Sensing"
<p>These datasets accompany the article published in <em>Remote Sensing </em>entitled: "Exploratory Analysis on Pixelwise Image Segmentation Metrics with an Application in Proximal Sensing".</p> <p>For each of the three segmentation models presented in the paper (DTSM, SVM and CIVE) two types of datasets are included: </p> <ul> <li><strong>Raw Metrics: </strong>the raw evaluations for each image returned by each of the 12 evaluation metrics. </li> <li><strong>Rankings:</strong> the ranking of each image in the dataset based on its raw evaluation. This dataset has been created by sorting in ascending order the dissimilarity metrics (GCE and HDD) and descending order the similarity metrics (all the other metrics). </li> </ul> <p>The datasets are in Excel (.xlsx) format and can be easily loaded in R and used to reproduce the results presented in the article.</p>
Evaluating the influence of structural properties on proximity metric performance in single cell RNA-seq data - Datasets
<p>Includes raw and processed copies of the scRNA-seq datasets used for the paper: '<strong>How does data structure impact cell-cell similarity? Evaluating the influence of structural properties on proximity metric performance in single cell RNA-seq data.'</strong></p> <p><strong>Real scRNA-seq.zip </strong>contains the Abundant (subset1) and Rare (subset 2) subsets generated to represent discretely structured datasets (sourced from<strong> </strong> Wegmann et al. 2019) and the continuously structured data (sourced from Popescu et al. 2019).</p> <p><strong>Simulated scRNA-seq.zip</strong> contains the Abundant, Moderately-Rare and Ultra-Rare subsets for discretely and continuously structured datasets. All data was simulated using the PROSSTT package in Python 3.8, as well as the dataset containing the labels to re-produce Figure 3 of the manuscript.</p> <p><strong>Results.zip </strong>contains the results for all datasets from the full analysis, in a pickled python dictionary. Code to read in and visualise results is available on the projects github</p> <p>The scripts for the dataset generation, processing and visualisation of results are available at <a href="https://github.com/Ebony-Watson/scProximitE">our github for the scProcimitE package</a>, and documentation is available <a href="https://ebony-watson.github.io/scProximitE/">here</a>.</p>
Large cortical bone pores in the tibia are associated with proximal femur strength - data for reproduction
<p>Results tables for the reproduction of:</p> <p>Iori G, Schneider J, Reisinger A, Heyer F, Peralta L, Wyers C, et al. Large cortical bone pores in the tibia are associated with proximal femur strength. PLOS ONE. doi:10.1371/journal.pone.0215405</p>
Open-Access Data for "Received SignalStrength Measurements with BLE Signals for Contact Tracing and Proximity Detection"
<p>This archive contains three folders which are supplementary material for the paper accepted for publishing in IEEE Sensors Journal.</p> <p><strong>Contents:</strong></p> <ul> <li> The folder `open-access-data/upb/` contains the measurements acquired at UPB. The subfolders are named as `upb_ble_*`, where an asterisk masks the directory number. Whenever UPB is specified, use the data sets from the corresponding directory.</li> <li>The folder `open-access-data/tau/` contains the measurements acquired at TAU. The subfolders are named as `tau_ble_*`, where an asterisk masks the directory number. Whenever TAU is specified, use the data sets from the corresponding directory.</li> <li>The folder `open-access-data/wifi-on-off/` contains a sample code to read the files and plot the data from Fig. 14 in `open-access-data/wifi-on-off/wifi_on_off_read_plot.py` and Fig. 15 in `open-access-data/wifi-on-off/wifi_on_off_read_plot.ipynb`.</li> </ul> <p><strong>Results based on the data have been presented in the paper:</strong><br> Flueratoru, L., Shubina, V., Niculescu, D., Lohan, E.S. (2021). On the High Fluctuations of Received Signal Strength Measurements with BLE Signals for Contact Tracing and Proximity Detection, IEEE Sensors, Special Issue on Advanced Sensors and Sensing Technologies for Indoor Positioning and Navigation</p> <p><strong>To cite these data sets please use the following:</strong><br> Laura Flueratoru, Viktoriia Shubina, Dragoș Niculescu, & Elena Simona Lohan. (2021). Open Access Data for "Received SignalStrength Measurements with BLE Signals for Contact Tracing and Proximity Detection" [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4643668</p>
Data from: Nest orientation and proximity to snow patches are important for nest site selection of a cavity breeder at high elevation
<p><strong>Abstract</strong></p> <p>Reproductive timing and location are central to breeding success across taxa. Many species have evolved specific strategies to cope with environmental variability including shifts in timing of reproduction tracking resource availability or selecting favourable nest location. In mountain ecosystems, complex topography and pronounced seasonality result in particularly high spatiotemporal variability of environmental conditions, and the risk of climate-induced resource mismatches is particularly acute given that temperature is increasing more rapidly than in the lowlands.<br>We investigated how a high-elevation passerine, the white-winged snowfinch <em>Montifringilla nivalis</em>, selects its nest site in relation to nest cavity characteristics, habitat composition and snow condition. We used a combination of field habitat mapping and satellite remote sensing to compare occupied nest sites with randomly selected pseudo-absence sites. In the first half of the breeding season, snowfinches preferred nest cavities oriented towards the morning sun while they used cavities proportional to their availability later on. This preference might relate to the nest microclimate offering eco-physiological advantages, namely thermoregulatory benefits for incubating adult and nestlings under the harsh conditions typically encountered in the alpine environment. Nest sites were consistently located in areas with greater-than-average snow cover at hatching date, likely mirroring the foraging preferences for tipulid larvae developing in meltwater along snowfields. Due to the particularly rapid climate shifts typical of mountain ecosystems, spatiotemporal mismatches between foraging grounds and nest sites are expected in the future, which may negatively influence demographic trajectories of the species concerned. The installation of well-designed nest boxes in optimal habitat configurations could to some extent help mitigate this risk.</p> <p> </p>
Sagittal otolith of Lota lota (total length=28 cm) from bottom (distal, concave, anti-sulcus side) and top (proximal, convex, with sulcus acusticus) view.
<p>This image shows the left sagittal otolith of <em>Lota lota </em>(total length=28 cm) from bottom (distal, concave, anti-sulcus side) and top (proximal, convex, with sulcus acusticus) view.</p>
Sagittal otolith of Perca fluviatilis (total length=17 cm) from bottom (distal, concave, anti-sulcus side) and top (proximal, convex, with sulcus acusticus) view.
<p>This image shows the left sagittal otolith of <em>Perca fluviatilis </em>(total length=17 cm) from bottom (distal, concave, anti-sulcus side) and top (proximal, convex, with sulcus acusticus) view.</p>
Distal prong of MA fairly broad and curved, not protruding beyond cymbium in ventral view; indentation between distal and proximal prong round- ed (3b) in A revision of the African wolf spider genus Amblyothele Simon
Distal prong of MA fairly broad and curved, not protruding beyond cymbium in ventral view; indentation between distal and proximal prong round- ed (3b)
Distal prong of MA long and slender, protruding beyond cymbium in ventral view; indentation between distal and proximal prong narrow, rectangular (3a) in A revision of the African wolf spider genus Amblyothele Simon
Distal prong of MA long and slender, protruding beyond cymbium in ventral view; indentation between distal and proximal prong narrow, rectangular (3a)
Distal prong of MA short, hardly longer than proximal one, straight (6a); TA fairly long and spiniform (6b) in A revision of the African wolf spider genus Amblyothele Simon
Distal prong of MA short, hardly longer than proximal one, straight (6a); TA fairly long and spiniform (6b)
Data from: Proximate and ultimate drivers of variation in bite force in the insular lizards Podarcis melisellensis and Podarcis sicula
<p>Bite force is a key performance trait in lizards since biting is involved in many ecologically relevant tasks, including foraging, fighting, and mating. Several factors have been previously suggested to impact bite force in lizards, such as head morphology (proximate factors), or diet, intraspecific competition, and habitat characteristics (ultimate factors). However, these have been generally investigated separately and mostly at the interspecific level. We tested which factors drive variation in bite force at the population level and to what extent. Our study includes 20 populations of two closely-related lacertid species, <i>Podarcis melisellensis </i>and <i>Podarcis sicula</i>, which inhabit islands in the Adriatic. We found that lizards with more forceful bites have relatively wider and taller heads, and consume more hard prey and plant material. Island isolation correlates with bite force, likely by driving the resource availability. Bite force is only poorly explained by proxies of intraspecific competition. The linear distance from a large island and the proportion of difficult-to-reduce food items consumed are the ultimate factors that explain most of the variation in bite force. Our findings suggest that the way in which morphological variation affects bite force is species-specific, likely reflecting the different selective pressures operating on the two species.</p>
SMART2: Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys
<p>To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area.</p> <p> </p> <p>Enrollment in the Social Mixing and Respiratory Transmission (SMART) study operated on an opt-out basis, and all students registered in a participating school before the start of the study were eligible to participate. Students in kindergarten (typically aged 5 years) to 12<sup>th</sup> grade (typically aged 18 years) from two elementary (K to 4<sup>th</sup> grade, K to 5<sup>th</sup> grade), two middle (5<sup>th</sup> to 6<sup>th</sup> grade, 7<sup>th</sup> to 8<sup>th</sup> grade), two elementary-middle (K to 8<sup>th</sup> grade), and two high (both 9<sup>th</sup> to 12<sup>th</sup> grade) schools were eligible to participate in SMART. Participation rates were high in all schools (82 to 99%). Each school provided aggregate demographic information about the school population, and individual grade and sex of participating students.</p> <p><em>Proximity sensor deployments</em></p> <p>The details of proximity sensor deployments have been described in detail elsewhere (60). In brief, participating students were given proximity sensors in plastic pouches and instructed to wear the pouch around their neck for the duration of the school day without removing or otherwise tampering with the sensor. In six of the eight schools, all participating students were given a sensor; in two schools, the large student population limited the deployment to randomly selected classrooms in each grade. Deployments typically lasted from the first class period (08:00 – 09:00) to the last class period (14:00 – 15:00). Deployment days in each school were chosen to be representative of a typical school day, without any special schoolwide or grade-specific activities that could modify normal contact patterns.</p> <p> </p> <p>We used TelosB wireless sensors (61) programmed in the NesC language to send beacons every 20 seconds (beacon frequency 3 per minute). The receiving sensor recorded the contacting sensor’s identity, an internal time stamp, and a radio strength signal indicator (RSSI). Signal strength provided an estimate of physical proximity, but was highly dependent on the orientation of the two sensors and any obstructions between them and therefore could not be used to define an exact distance between contacts. Based on pilot studies and previous work on effective distances of respiratory virus transmission (29, 62), we chose a signal threshold (-80 dBm) that should correspond to contacts of relevance to respiratory disease transmission.</p> <p> </p> <p>The number of unique proximity sensor contacts recorded for a participant was defined as the total number of other participants with whom their proximity sensor recorded at least one interaction during each deployment. To explore patterns of contacts of varying length, we considered several values of the contact threshold, or the minimum number of recorded interactions between two proximity sensors required to be considered a unique contact. The number of interactions between any given pair of sensors was taken to be the maximum number of interactions recorded by either sensor, to account for battery failure, measurement error, or other malfunctions.</p> <p> </p> <p><em>Contact survey design</em></p> <p>Contact surveys were completed by participants in school under the supervision of project staff and teachers. Each sheet of the paper version allowed for information on up to 30 contacts to be recorded; additional sheets could be requested. Two versions were designed: one for middle- and high-school students, and a simplified version for elementary school students (although some elementary school children completed the middle- and high-school version, upon consultation with school administrators and teachers). Classrooms were randomly selected to participate from each grade, and students of several classrooms completed more than one contact survey over the course of the study period.</p> <p> </p> <p>Participants were asked to report information about any individual they talked with, played with, or touched the previous day, including the contact’s age and sex, whether they attended the same school as the participant, the context in which the contact was made, whether the contact involved direct or indirect (through a shared object) touch, and approximate duration of the contact. Students reported the total number of contacts made in the previous day, without detailed information, and additional demographic information about themselves and their household. The surveys were completed either on paper or by computer, depending on resources available in each school.</p> <p> </p> <p>We defined total survey contacts as the total number of individuals a student reported having interacted with on the day before the survey was completed. Detailed contacts were the subset of total contacts for which the student reported contact age, sex, duration, and context. We considered further subsets of detailed survey contacts, including those occurring within school, those reported to have lasted more than 10 minutes over the course of the day, and those occurring on the same day as a sensor deployment.</p> <p> </p>
ScienceDex guides
Understand access before you commit
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.