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FIGURE 1 in Description of a new species of Lutosa Walker, 1869 (Orthoptera: Anostostomatidae: Lutosinae) from the Brazilian Atlantic Forest, with biological and behavioral information
FIGURE 1. Lutosa horribilis sp. nov. holotype Ƌ. A) habitus in dorsal view; B) same in lateral view; C) head in frontal view; D) head and pronotum in dorsal view; E) same in lateral view; F) fore tibia in right lateral view; G) fore tibia in left lateral view; H) apex of hind tibia and base of tarsus in dorsal view; I) Pro, meso and metasternum in ventral view; J) apex of abdomen in dorsal view; K) same in ventral view; L) same in lateral view.
Supplementary material 1: Global Biodiversity Information Facility: Taxa and Records from: Integrating and visualizing primary data from prospective and legacy taxonomic literature - Biodiversity Data Journal 3: e5063 (12 May 2015) https://doi.org/10.3897/BDJ.3.e5063
All records in GBIF with taxonomic ranks (kingdom, phylum, class, order, and species), basis of record (e.g., preserved specimen), and count of records, exported from GBIF on 7 December 2014.
Update and expansion of the database of bio-ecological information on non-target arthropod species
<p>The current database updates and extends the database on arthropods inhabiting European arable crops established in 2012 (Meissle <em>et al.</em> 2012). The data was collected to support environmental risk assessment of genetically modified (GM) crops in the European Union and provides a detailed overview of the arthropod fauna in arable crops across Europe.The data was obtained from systematic literature searches conducted to identify publications on small grain cereals and to identify additional publications on the crops covered by the previous database (maize, beet, potato, oilseed rape, rice, cotton, soy). The final database contains information on more than 4000 arthropod species, > 27700 records, and > 2000 references.</p> <p>The database consists of three tables containing information on species (taxonomy, ecological function, feeding guild, habitat), abundances (crop, collection method, location, sampling duration, collected species), and references (authors, year, title, source). Taxonomy was verified with European and global taxonomic catalogues and taxonomic experts. Ecological information, in particular feeding guilds of adults and juveniles, was double checked with appropriate literature, and provided in detail. References for taxonomic and ecological information were included for each species record</p> <p>For maize, beet, potato, oilseed rape, rice, and soybean, 258 additional studies were found and entered into the database, resulting in 2774 additional records. For those crops, the updated database contains 16610 records of 3264 species. Most of the records are available for maize (6648), followed by beet, potato, and oilseed rape (ca. 3000 records each). Relatively few records are available for rice (601), soy (231), and cotton (184). Overall, small grain cereals in Europe were reported to harbour more than 2000 arthropod species. Most information is available for wheat (7626 records and 1664 species), followed by barley (2308 records and 893 species). Rye, oats, and triticale are represented by 453, 369, and 273 records and 269, 187, and 171 species, respectively. Only few records are available for buckwheat and sorghum, and no records for millet and canary seed. Overall, small grain cereals in Europe are reported to harbour more than 2000 arthropod species. For the other crops, the updated database contains more than 3200 species. Most of the species recorded in small grain cereals are predators (63% of the abundance records), followed by herbivores (21%), decomposers (8%), parasitoids (7%), and pollinators (1%). </p> <p>The database contains reports from 37 countries in Europe and was extracted from references with a publication date ranging from 1925-2014.</p>
Inbred Strain Variant Database (ISVdb): A repository for probabilistically informed sequence differences among the Collaborative Cross strains and their founders
<p>Data files for the development of a database for storing (and a GUI for retrieving) the imputed variants for 72 Collaborative Cross strains of mice. Files include the inputs for the imputation, as well as the final results. See File_S1_Readme for more details on the included files.</p>
Supplementary information for "Anharmonic origin of large thermal displacements in the metal-organic framework UiO-67"
<p>Supplementary information for DOI: 10.1021/acs.jpcc.7b04757</p> <p>POSCAR-XXX: DFT optimised structures</p> <p>Phonons-XXX.zip: Folders containing the force constants (FORCE_SETS), the resulting phonon frequencies (mesh.yaml), phonon partial density of states (partial_dos.dat), animations of all phonon modes (anime.ascii) e.g. to be visualized in VMD and gifs of selected phonon modes. </p> <p>XDATCAR-XXX: MD trajectories</p>
Video S1–3, Model S1, 2 & Figure S1: Oxfordiana motturii gen. et sp. nov. supplemental information
<p><strong>Video S1.</strong> Animation of the isosurface-based false-coloured three-dimensional model for specimen BU 5265.1. Full 360-degree rotation on the x-axis followed by the y-axis. Scale bar = 0.5 cm [MOV format 13MB, AVI format 44MB; 1920x1080 px; 1:04 min]</p> <p><strong>Video S2.</strong> Animation of the isosurface-based false-coloured three-dimensional model for specimen BU 5265.2. Full 360-degree rotation on the x-axis followed by the y-axis. Scale bar = 0.5 cm. [MOV format 20MB, AVI format 44MB; 1920x1080 px; 1:04 min]</p> <p><strong>Video S3.</strong> Tomographic data set showing raw X-ray contrast data as produced by the I12 JEEP beamline at the Diamond Light Source for specimen BU 5265.1. Scale bar = 0.25 mm. [MOV format 42MB, AVI format 53MB; 1004x1002 px; 1:15 min]</p> <p><strong>Model S1.</strong> Zenodo hosted three-dimensional model file of BU 5265.1 isosurface-based false-coloured reconstruction. This model is saved as a ZIP compressed VAXML datasets. VAXML uses one or more STL files to define the geometry of objects that comprise the dataset, together with one VAXML file that provides metadata on the dataset as a whole, and specifies how the STL/PLY files are to be put together. Additionally, a native SPV file has been included for direct viewing in SPIERSview. We therefore recommend the free SPIERS software to view this model format (http://spiers-software.org/). Additional information on the VAXML format can be found here: http://spiers-software.org/VAXML.htm. [ZIP/VAXML format 198.4 MB; SPV format 4MB]</p> <p><strong>Model S2.</strong> Zenodo hosted three-dimensional model file of BU 5265.2 isosurface-based false-coloured reconstruction. This model is saved as a ZIP compressed VAXML datasets. VAXML uses one or more STL files to define the geometry of objects that comprise the dataset, together with one VAXML file that provides metadata on the dataset as a whole, and specifies how the STL/PLY files are to be put together. Additionally, a native SPV file has been included for direct viewing in SPIERSview. We therefore recommend the free SPIERS software to view this model format (http://spiers-software.org/). Additional information on the VAXML format can be found here: http://spiers-software.org/VAXML.htm. [ZIP/VAXML format 173.6 MB; SPV format 3MB]</p> <p><strong>Figure S1. </strong>High resolution volume rendered images from Drishti showing the anatomy of BU 5265 and BU 5266. A) 16 longitudinal virtual thin-sections through BU 5265.1 at 500 µm spacing; B) 40 transverse virtual thin-sections through BU 5265.1 at 500 µm spacing; C) 28 transverse virtual thin-sections through BU 5265.2 at 500 µm spacing; D) 38 transverse virtual thin-sections through BU 5265.3 at 500 µm spacing; E) Reconstruction of BU 5265.1 showing longitudinal view of whole specimen fragment; F) Reconstruction of thick section slide BU 52665.30<strong>, </strong>a: oblique view of slide looking from the outer surface toward the inside of the ovule near the apex, b: oblique view of the slide looking out from the inside of the ovule, c: top-down view of the slide looking towards the ovule base, d: 3D section virtually cut from the slide showing the orientation of integumentary layers. G) Reconstruction of thick section slide BU 52665.1, a: view of slide looking from the inner surface toward the outside of the ovule, b: view of the slide looking towards the inside of the ovule, c: longitudinal section through the virtual slide. H) Reconstruction of thick section slide BU 52665.38, a: outer anatomy seen looking to the ovule centre from the base, b: inner anatomy seen looking from the ovule centre towards the base, c: longitudinal section through the virtual slide. I) Reconstruction of thick section slide BU 52665.3, a: view of slide looking towards the ovule centre, b: view of slide looking from ovule centre towards the external surface, c: longitudinal section through the virtual slide. J) Reconstruction of thick section slide BU 52665.37, a: view of slide looking away from the ovule centre, b: view of slide looking towards the ovule centre, c: longitudinal section through the virtual slide. Notes: A–D) These images show the two phases of mineralization which have preserved the ovule anatomy, blue = carbonate (calcite), yellow = pyrite, each having differing x-ray attenuation characteristics; E–J) These images highlight just the pyrite within the ovule, in particular that which infills the cells. Scale bars sizes are indicated on the figure. [PNG format 76MB]</p>
Actionable Information During a Disaster (Self-organize Relief Efforts via #PorteOuverte)
<p><strong>Abstract</strong> (our paper)</p> <p>Web-based social and communication technologies enable citizens to self-organize relief efforts in response to crises. This work focuses on a question fundamental to the concept of collective intelligence: how effective are such self-organized channels, ungoverned by any central authority, in conforming to their intended function? In this study we examine the hashtag #PorteOuverte ("#OpenDoor") introduced during the 2015 Paris terrorist attacks, as an "improvised logistical channel" (ILC) to help individuals to find a safe shelter near the attack sites. We analyze the dynamics and effectiveness of #PorteOuverte by comparing its proportion of relevant logistical messages -- individuals requesting or offering shelter -- to other messages such as those offering emotional consolation or commenting on the hashtag itself. Our results reveal that the vast majority of messages are not relevant, however the crowd senses and spreads relevant messages more than others. We further demonstrate that relevant messages can be automatically detected and thus algorithmic promotion may be possible.</p> <p><strong>Data</strong></p> <p>The #PorteOuverte hashtag ("opendoor" in English), created right after the 2015 terrorist attacks in Paris, was used by individuals to offer shelter to strangers stranded by the attacks and by individuals in need of shelter to request help and post their whereabouts. The file #PorteOuverte _tweet_ids.txt contains all the original tweet ids that used this hashtag.</p> <p>The first tweet was posted on Friday, 13 Nov 2015 21:34:06 GMT.</p> <p>Duration: 2015-11-13 to 2015-11-16 (retweets not included).</p> <p>Total number of tweets: 75547</p> <p><strong>Publication</strong></p> <p>This data set was created for our study. If you make use of this data set, please cite:</p> <p>He, X., Lu, D., Margolin, D., Wang, M., Idrissi, S., Lin, Y.-R. (2017). "The Signals and Noise: Actionable Information in Improvised Social Media Channels During a Disaster," Proceedings of Web Science 2017 (WebSci 2017), 2017. doi:10.1145/3091478.3091501</p>
Data + Analyses: "Gaze-dependent Coding of Somatosensory Reach Targets after Effector Movement: Testing the Impact of Online Information, Movement Timing, and Target Distance"
<p>This upload contains the experiment scripts (written in Presentation), data, and analyses (performed with MATLAB and SPSS) underlying the publication<strong> </strong>by Mueller & Fiehler (2017). <em>PloS one</em>. doi:<strong>10.1371/journal.pone.0180782</strong></p>
Data from Hesse et al. 2017: Preattentive Processing of Numerical Visual Information, Front Hum Neurosci., 11:70, 2017. doi: 10.3389/fnhum.2017.00070.
<p><strong>Data related to the following publication: </strong></p> <p>Hesse Philipp N., Schmitt Constanze, Klingenhoefer Steffen, Bremmer Frank (2017). Preattentive Processing of Numerical Visual Information. Frontiers in Human Neuroscience, 11: 70. doi: 10.3389/fnhum.2017.00070</p> <p><strong>Brief description of dataset:</strong></p> <p>The stimulus was presented on a TFT monitor (size: 41,8° x 24,3°) 52 cm in front of the participants in a dark, sound attenuated and electrically shielded room. During the experiment EEG was recorded continuously. We used 64 Ag/AgCl active electrodes located according to the extended international 10-20 system. </p> <p>The numerosity stimulus consisted of a continuously displayed black fixation target in the center of the gray screen. Additionally in each trial either one, two or three circular white patches were shown 200 ms after trial onset. These were presented for a random duration between 400 ms and 500 ms either in the left or right visual field. Two different types of patches were presented: i) the radius of the patches had the same value (0.65°) and therefore the patch size was the same (“SizeCon”) ii) the total area of the patches was conserved which resulted in the same total luminance independent of the number of patches (“LumCon”). After a random time between 400 ms and 700 ms after stimulus offset the trials ended.</p> <p>In this study we conducted an oddball experiment with an oddball-ratio of 1:4. In each block consisting of 30 trials a standard-amount of patches (one, two or three) was presented in 80% of all trials (24 trials). The two remaining quantities of patches were shown in 10% (3 trials) of the trials each. This presentation scheme allowed us to compare trials with identical physical properties because each amount of patches served as deviant and standard trial in different blocks. Attention of the participants was drawn off the white patches by a demanding detection task at the fixation target. A total number of 432 blocks consisting of 30 trials was presented to each of the 10 participants.</p> <p>EEG data were evaluated offline. The mastoids (TP9 and TP10) were chosen as new reference. A second-order, zero phase shift Butterworth filter with cutoff frequencies 0.5 and 40 Hz was applied to the continuously recorded data before it was sliced in individual trials that had a time range from 200 ms before to 500 ms after stimulus onset. A baseline correction was performed using with the signals from -110 ms to 0 ms. As a last step trials with eye movement artifacts or electrode signals that exceeded a difference of ±100 µV within an interval of 100 ms were excluded in an artifact rejection step.</p> <p> </p>
Unequal - but fair? Weights in the serial integration of haptic texture information
<p>The sense of touch is characterized by its sequential nature. In texture perception, enhanced spatio-temporal extension of exploration leads to better discrimination performance due to combination of repetitive information. We have previously shown that the gains from additional exploration are smaller than the Maximum Likelihood Estimation (MLE) model of an ideal observer would assume. Here we test if this suboptimal integration can be explained by unequal weighting of information. Participants stroke 2 to 5 times across a virtual grating and judged the ridge period in a 2IFC task. We presented slightly discrepant period information in one of the strokes in the standard grating. Results show linearly decreasing weights of this information with spatio-temporal distance (number of intervening strokes) to the comparison grating. For each exploration extension (number of strokes) the stroke with the highest number of intervening strokes to the comparison was completely disregarded. The results are consistent with the notion that memory limitations are responsible for the unequal weights. This study raises the question if models of optimal integration should include memory decay as an additional source of variance and thus not expect equal weights.</p> <p><strong>Lezkan</strong>, A. & <strong>Drewing</strong>, K. (2014). Unequal - but fair? Weights in the serial integration of haptic texture information. <em>Haptics: Neuroscience, Devices, Modeling, and Applications</em> (pp. 386-392). Springer: Heidelberg.</p> <p> </p> <p>The Zip file contains all data relative to the publication. The data of each participant is contained in a separate file.</p> <p>A description of the variables is contained in the file VARIABLE_CODES.txt</p>
Integration of serial sensory information in haptic perception of softness
<p>Redundant estimates of an environmental property derived simultaneously from different senses or cues are typically integrated according to the Maximum Likelihood Estimation model (MLE): Sensory estimates are weighted according to their reliabilities, maximizing the percept"s reliability. Mechanisms underlying the integration of sequentially derived estimates from one sense are less clear. Here we investigate the integration of seriallysampled redundant information in softness perception. We developed a method to manipulate haptically perceived softness of silicone rubber stimuli during bare finger exploration. We then manipulated softness estimates derived from single movement segments (indentations) in a multi-segmented exploration to assess their contributions to the overall percept. Participants explored two stimuli in sequence, using 2-5 indentations and reported which stimulus felt softer. Estimates of the first stimulus' softness contributed to the judgments similarly, whereas for the second stimulus estimates from later as compared to earlier indentations contributed less. In line with unequal weighting, the percept"s reliability increased with increasing exploration length less than predicted by the MLE model. This pattern of results is well explained by assuming that the representation of the first stimulus fades when the second stimulus is explored, which fits with a neurophysiological model of perceptual decisions (Deco et al., 2010).</p> <p> </p> <p>There are zip files for every experiment (1 & 2a-d), which contain all data relative to the publication. The data of each participant is contained in a separate folder. This folder contains a *.raw file for each session of the experiment and a "data" folder, which contains movement trajectories (*.trj files) and the staircase reversals for each condition (*.pse files) in separate folders for each session. In every experiment folder there is a list of trials which were excluded from the analyses.</p> <p>Variables of Experiment 1 are described in the file VARIABLE_CODES_EXP1.txt and the variables of Experiment 2a-d are described in the file VARIABLE_CODES_EXP2.txt.</p> <p> </p>
Supplementary information
<p>Integrative evolutionary analyses that are based upon fossil and extant species provide a unique source of evidence for understanding past diversification events and for assessing the tempo of evolution across the Tree of Life. Herein, we demonstrate the importance of integrating fossil and extant species for inferring patterns of lineage diversification that would otherwise be masked in analyses that examine only one source of evidence. </p>
Datasets and supplemental information accompanying the corneal meta-atlas
<p>This repository currently contains datasets and files needed for cPredictor: <a href="https://github.com/Arts-of-coding/cPredictor">https://github.com/Arts-of-coding/cPredictor</a>.</p> <p> </p> <p>Additionally, "cornea_v1_pnas_nexus.h5ad" contains the integrated and pre-processed single-cell object with raw counts only.</p>
Comprehensive epigenomic profiling reveals the extent of disease-specific chromatin states and informs target discovery in ankylosing spondylitis
<p>We performed comprehensive epigenetic profiling in immune cell samples from patients with ankylosing spondylitis and healthy controls. <br><br><em>Note: Due to Zenodo updating their maximum file limit to 100 files, version 4 </em>(v4) <em>of this archive has been split into 5 compressed archive (tar.gz) files containing all previous and additional files. <br><br></em>Version 4 of this archive (updated 03/06/2025) adds 4 files to the archive that were omitted in previous versions which have now been made available. These were: <em><br></em></p> <ul> <li>RNA_CD8_raw_counts.txt.gz</li> <li>RNA_CD8_normalised_counts.txt.gz</li> <li>RNA_CD14_raw_counts.txt.gz</li> <li>RNA_CD14_normalised_counts.txt.gz </li> </ul> <p><em>--------------------------------------------------------------------------------------------------------------------------</em></p> <p><strong>RNA-seq/ATAC-seq/ChIPm/eRNA: </strong>Raw and normalised count data for each gene or epigenetic peak in CD4+ T cells, CD8+ T cells, and CD14+ monocytes from AS patients and healthy controls. File name is in the format: "modality_cell-type_raw/normalised_counts.txt.gz". Table S2 shows which experiments were performed on which samples. </p> <p>This data can be found in the "Raw_Counts.tar.gz" and "Normalised_Counts.tar.gz" archives. </p> <p>--------------------------------------------------------------------------------------------------------------------------</p> <p><strong>ChromHMM: </strong>We used ChromHMM to integrate epigenomic data into a 14-emission state model detailing chromatin functionality in AS patients and healthy controls. ChromHMM filenames are in the format: "ChromHMM_sampleID_celltype_n.bed.gz" where n is the number of states in the ChromHMM emission model.</p> <p>This data can be found in the "ChromHMM_AS_HV.tar.gz" archive. </p> <p>--------------------------------------------------------------------------------------------------------------------------</p> <p><strong>Capture-C: </strong>We performed Capture-C to detect chromosome looping interactions between gene promoters and SNPs associated with ankylosing spondylitis. Capture-C count data are shown in the format: "CaptureC_celltype_gene_Pro/SNP_normalised.unionbdg". We used PeakY to calculate a score for each interaction. PeakY scores are given in the following format: "PeakY_AS/HV_celltype_tier_chrloc_gene_Pro/SNP.txt". gene_Pro and gene_SNP relate to the baitsets given in Table S8.</p> <p>This data can be found in the "CapC_Count_Data.tar.gz" and "PeakY_regions.tar.gz" archives. </p>
Can accurate demographic information about people who use prescription medications non-medically be derived from Twitter?
<p>This archive contains over 3 billion Tweet IDs associated with the paper:<br>"Can accurate demographic information about people who use prescription medications non-medically be derived from Twitter?"</p> <p>The data provides:<br>X (Twitter) IDs of posts included in the study. The IDs can be used to retrieve the original posts via the Twitter API. Posts removed by the original subscribers or whose visibilities are no longer public cannot be retrieved by the poster. </p> <p>Full citation:<br>Yang YC, Al-Garadi MA, Love JS, Cooper HLF, Perrone J, Sarker A. Can accurate demographic information about people who use prescription medications nonmedically be derived from Twitter? Proc Natl Acad Sci U S A. 2023 Feb 21;120(8):e2207391120. doi: 10.1073/pnas.2207391120. Epub 2023 Feb 14. PMID: 36787355; PMCID: PMC9974473.</p> <p>Python scripts related to the analysis are available as supplementary material with the paper. </p> <p>Contact: <br>Abeed Sarker<br>abeed@dbmi.emory.edu</p> <p>Funding:<br>National Institute on Drug Abuse (R01DA057599).</p>
Supporting Information for "Electron and proton peak intensities as observed by a five-spacecraft fleet in solar cycle 25"
<p>Table of parameters employed in the study "Electron and proton peak intensities as observed by a five-spacecraft fleet in solar cycle 25". The table contains the original peak intensities directly taken from the <em>SERPENTINE SEP event catalog</em>, without any scaling or inter-calibration factors that are applied in the study. All information provided in the table is based on the <em>SERPENTINE SEP event catalog</em> and <em>SERPENTINE CME and coronal shocks catalog</em><strong>,</strong> only limiting the variables to those used in this study. The dataset is in CSV format.</p> <p>For more information, and if you use this table, please refer to the corresponding publication:</p> <blockquote> <div> <p>Electron and proton peak intensities as observed by a five-spacecraft fleet in solar cycle 25<br>G. U. Farwa, N. Dresing, J. Gieseler, L. Vuorinen, I. G. Richardson, C. Palmroos, S. Valkila, B. Heber, S. Jensen, P. Kühl, L. Rodríguez-García and R. Vainio<br>A&A, 693 (2025) A198<br>DOI: <a href="https://doi.org/10.1051/0004-6361/202450945">10.1051/0004-6361/202450945</a></p> </div> </blockquote> <div> <div> </div> </div> <p><strong>Field descriptions</strong></p> <ul> <li>id: ID</li> <li>date: Event date [UTC]</li> <li>flare_time: Flare time [UTC]</li> <li>flare_lat: Flare Carrington latitude [deg]</li> <li>flare_lon: Flare Carrington longitude [deg]</li> <li>flare_class: Flare class (GOES)</li> <li>flare_comments: Flare Comments</li> <li>radio_type2: Radio type II bursts</li> <li>decametric_type2_start: Decametric type II burst start time [UT]</li> <li>decametric_type2_stop: Decametric type II burst end time [UT]</li> <li>radio_type2_start: Metric radio type II burst start time [UT]</li> <li>radio_type2_stop: Metric radio type II burst end time [UT]</li> <li>solar_mach_link: Solar-Mach link</li> <li>S/C codes <ul> <li>BepiC: BepiColombo</li> <li>L1: L1 (SOHO/Wind)</li> <li>PSP: Parker Solar Probe</li> <li>STA: STEREO A</li> <li>SolO: Solar Orbiter</li> </ul> </li> <li>S/C related field descriptions <ul> <li>{sc}_sc_lat: S/C Carrington latitude [deg]</li> <li>{sc}_sc_lon: S/C Carrington longitude [deg]</li> <li>{sc}_dist: S/C radial distance [au]</li> <li>{sc}_p25MeV_onset_date: S/C protons 25 MeV onset date [UTC]</li> <li>{sc}_p25MeV_onset_time: S/C protons 25 MeV onset time [UTC]</li> <li>{sc}_p25MeV_onset_time_formatted: S/C protons 25 MeV onset time [UTC] (Formatted)</li> <li>{sc}_p25MeV_onset_averaging: S/C protons 25 MeV averaging used for onset [min]</li> <li>{sc}_p25MeV_onset_sector: S/C protons 25 MeV sector used for onset</li> <li>{sc}_p25MeV_peak_date: S/C protons 25 MeV peak date [UTC]</li> <li>{sc}_p25MeV_peak_time: S/C protons 25 MeV peak time [UTC]</li> <li>{sc}_p25MeV_peak_time_formatted: S/C protons 25 MeV peak time [UTC] (Formatted)</li> <li>{sc}_p25MeV_peak_flux: S/C protons 25 MeV original peak flux [cm^-2 s^-1 sr^-1 MeV^-1]</li> <li>{sc}_p25MeV_peak_flux_formatted: S/C protons 25 MeV original peak flux [cm^-2 s^-1 sr^-1 MeV^-1] (Formatted)</li> <li>{sc}_p25MeV_peak_averaging: S/C protons 25 MeV averaging used for peak [min]</li> <li>{sc}_p25MeV_peak_sector: S/C protons 25 MeV sector used for peak</li> <li>{sc}_p25MeV_injection_date: S/C protons 25 MeV inferred injection date [UTC]</li> <li>{sc}_p25MeV_injection_time: S/C protons 25 MeV inferred injection time [UTC]</li> <li>{sc}_p25MeV_sw_speed: S/C protons 25 MeV onset solar wind speed [km/s]</li> <li>{sc}_p25MeV_comments: S/C protons 25 MeV comments</li> <li>{sc}_e100keV_onset_date: S/C electrons 100 keV onset date [UTC]</li> <li>{sc}_e100keV_onset_time: S/C electrons 100 keV onset time [UTC]</li> <li>{sc}_e100keV_onset_time_formatted: S/C electrons 100 keV onset time [UTC] (Formatted)</li> <li>{sc}_e100keV_onset_averaging: S/C electrons 100 keV averaging used for onset [min]</li> <li>{sc}_e100keV_onset_sector: S/C electrons 100 keV sector used for onset</li> <li>{sc}_e100keV_peak_date: S/C electrons 100 keV peak date [UTC]</li> <li>{sc}_e100keV_peak_time: S/C electrons 100 keV peak time [UTC]</li> <li>{sc}_e100keV_peak_time_formatted: S/C electrons 100 keV peak time [UTC] (Formatted)</li> <li>{sc}_e100keV_peak_flux: S/C electrons 100 keV original peak flux [cm^-2 s^-1 sr^-1 MeV^-1]</li> <li>{sc}_e100keV_peak_flux_formatted: S/C electrons 100 keV original peak flux [cm^-2 s^-1 sr^-1 MeV^-1] (Formatted)</li> <li>{sc}_e100keV_peak_averaging: S/C electrons 100 keV averaging used for peak [min]</li> <li>{sc}_e100keV_peak_sector: S/C electrons 100 keV sector used for peak</li> <li>{sc}_e100keV_injection_date: S/C electrons 100 keV inferred injection date [UTC]</li> <li>{sc}_e100keV_injection_time: S/C electrons 100 keV inferred injection time [UTC]</li> <li>{sc}_e100keV_sw_speed: S/C electrons 100 keV onset solar wind speed [km/s]</li> <li>{sc}_e100keV_comments: S/C electrons 100 keV comments</li> <li>{sc}_e1MeV_onset_date: S/C electrons 1 MeV onset date [UTC]</li> <li>{sc}_e1MeV_onset_time: S/C electrons 1 MeV onset time [UTC]</li> <li>{sc}_e1MeV_onset_time_formatted: S/C electrons 1 MeV onset time [UTC] (Formatted)</li> <li>{sc}_e1MeV_onset_averaging: S/C electrons 1 MeV averaging used for onset [min]</li> <li>{sc}_e1MeV_onset_sector: S/C electrons 1 MeV sector used for onset</li> <li>{sc}_e1MeV_peak_date: S/C electrons 1 MeV peak date [UTC]</li> <li>{sc}_e1MeV_peak_time: S/C electrons 1 MeV peak time [UTC]</li> <li>{sc}_e1MeV_peak_time_formatted: S/C electrons 1 MeV peak time [UTC] (Formatted)</li> <li>{sc}_e1MeV_peak_flux: S/C electrons 1 MeV original peak flux [cm^-2 s^-1 sr^-1 MeV^-1]</li> <li>{sc}_e1MeV_peak_flux_formatted: S/C electrons 1 MeV original peak flux [cm^-2 s^-1 sr^-1 MeV^-1] (Formatted)</li> <li>{sc}_e1MeV_peak_averaging: S/C electrons 1 MeV averaging used for peak [min]</li> <li>{sc}_e1MeV_peak_sector: S/C electrons 1 MeV sector used for peak</li> <li>{sc}_e1MeV_injection_date: S/C electrons 1 MeV inferred injection date [UTC]</li> <li>{sc}_e1MeV_injection_time: S/C electrons 1 MeV inferred injection time [UTC]</li> <li>{sc}_e1MeV_sw_speed: S/C electrons 1 MeV onset solar wind speed [km/s]</li> <li>{sc}_e1MeV_comments: S/C electrons 1 MeV comments</li> <li>{sc}_ep_ratio: Ratio of Electrons (~1MeV) / Protons (25-40 MeV)</li> </ul> </li> <li>CME related descriptions <ul> <li>cme_id: CME ID</li> <li>L1_date: Date of CME identification at L1</li> <li>L1_time: Time of CME identification at L1</li> <li>L1_pos_speed: Plane of sky speed of CME measured at L1</li> </ul> </li> </ul> <div><strong>CHANGELOG:</strong></div> <div> <ul> <li>2025-06-12 <ul> <li>Updated peak fluxes and peak times of PSP 1 MeV electrons, as well as PSP's e/p ratios (the previous flux values are erroneous!)</li> </ul> </li> </ul> </div>
Supplementary material for "Playback experiments highlight the importance of nearest-neighbor distance and social information for nest site selection in the House Martin (Delichon urbicum)"
<p><strong>Abstract</strong></p> <p>Understanding nest site selection is crucial for species conservation. Bird conservation often involves installing nesting aids to increase nest site availability and induce colonization of unoccupied sites. However, prospecting individuals must find nesting aids, which may be facilitated by social information. Here, we investigated the effectiveness of artificial nests and playback in the declining, migratory House Martin <em>Delichon urbicum</em>. We selected unoccupied sites with artificial nests along a distance gradient to occupied sites and broadcasted conspecific vocalizations during prospection times of House Martins in both the post- and the following pre-breeding periods. Visitation and colonization rates increased considerably in proximity to occupied sites. Playback during the post-breeding and pre-breeding periods enhanced visitation rates, while pre-breeding-only and post-breeding-only playback had smaller positive effects. Colonization rate increased exclusively with pre-breeding-only playback. Colonized playback and non-playback sites had similar breeding success, indicating that playback did not create ecological traps by attracting House Martins to suboptimal sites. Hence, broadcasting conspecific vocalizations informs prospecting birds of nest site availability, thereby increasing visitation, and to some degree, colonization of unoccupied House Martin sites. To boost colonization, we recommend installing artificial House Martin nests within approximately 500 meters of occupied sites and using playback of conspecific vocalizations.</p>
Information flows around agricultural best management practices in central Pennsylvania
<p>This dataset was collected between February and April 2019, to assess the information network of agricultural Best-Management Practices (BMPs) in central Pennsylvania, a sub-region of the Chesapeake Bay watershed.</p> <p>It contains information flows (or "messages") relating to 16 specific BMPs, including:</p> <ul> <li>the BMP it relates to (e.g. riparian buffers, manure management planning, no-till, cover-cropping, etc.);</li> <li>the source and target of the information (actors);</li> <li>the kind of message (e.g. funding, regulation, technical assistance, etc.);</li> <li>the weight (strength) of messages (only for those received by farmers directly).</li> </ul> <p>Over 3900 messages/information flows were recorded, involving 57 actors.</p> <p>This data was used to conduct the study "Navigating agricultural nonpoint source pollution governance: A social network analysis of best management practices in central Pennsylvania".</p>
Database for article: "Privacy Perceptions in Digital Games: A Study with Information Technology (IT) Undergraduates"
<p>This database is an addendum to the article "<strong>Privacy Perceptions in Digital Games: A Study with Information Technology (IT) Undergraduates</strong>" to provide information regarding the anonymously collected data.</p><p><strong>Abstract of the article</strong></p><p>This study explores the perceptions and practices of undergraduates in Information Technology (IT) regarding privacy issues in digital games. This topic becomes relevant in the current scenario where artificial intelligence (AI) is increasingly integrated into digital games, providing an enhanced experience for players. However, this integration poses security and privacy challenges, the understanding of which is crucial for both players and developers.<br>The primary objective of this research is to comprehend the participants' perceptions and understandings of privacy in digital games. We employed a qualitative and quantitative methodology to address our research inquiries. Through an online form of data collection, we obtained 61 responses. Among the obtained information, we observed that 40\% of the students are interested in pursuing a career in game development, and 49.18% would consider this possibility. Noteworthy among the identified issues is the necessity for companies to devise more effective means of communicating their privacy policies to players/users, adapting the language to their target audience. Participants reported attacks related to online multiplayer games and expressed concerns about the security of personal data.</p>
Additional information to Research Letter "Immunogenicity of Cephalosporin Components in Non-IgE Mediated Cephalosporin Allergy"
<p>The file contains the following information:</p><p><strong>Additional information</strong></p><p><strong>Description</strong></p><p><strong>Page</strong></p><p>Materials and Methods</p><p>Study materials, syntheses of degradation products and enzyme-linked immunospot assay used in the study</p><p>1-3</p><p>Table 1</p><p>In vitro reactivity to different components of ceftriaxone degradation products in patients with positive ELISpot to ceftriaxone or cephalosporine with similar R1 side chain to ceftriaxone (N=21), categorized by underlying diseases and drug allergic phenotypes</p><p>4</p><p>Table 2</p><p>Clinical characteristics of patients with a confirmed non-IgE mediated hypersensitivity reaction to ceftriaxone or cephalosporin with a similar R1 side chain to ceftriaxone</p><p>5-6</p><p>Table 3</p><p>Frequencies of IFN-γ releasing cells and proportions of positive IFN-γ ELISpot assay upon stimulation with the suspected culprit drugs and different cephalosporins in patients with a history of non-IgE mediated reaction to ceftriaxone or cephalosporins with a similar R1 side chain (N= 21)</p><p>7-9</p><p>Figure captions and Figure legends</p><p> </p><p>Figure captions and figure legends for figures 1, 2, 3A, 3B, and 4.</p><p> </p><p>10</p><p> </p><p>Figure 1</p><p> </p><p>Mass spectrum results of the synthesized octalysine-ceftriaxone conjugates</p><p> </p><p> Figure 2</p><p>Chemical structures of cephalosporin components in this study</p><p> </p><p>Fig 3</p><p>Representative figures of IFN-γ releasing cells after stimulating PBMCs with different cephalosporins and their components, as demonstrated by ELISpot assay in two patients with a history of ceftriaxone-induced DRESS. Figure 3A shows the results for a single cephalosporin reactor, and Figure 3B shows the results for a multiple cephalosporin reactor.</p><p> </p><p>Fig 4</p><p>The frequencies of IFN-γ releasing cells and proportions of positive IFN-γ ELISpot assay upon stimulation with the suspected culprit drugs, other cephalosporins, and different components in patients with a history of non-IgE mediated reaction to ceftriaxone or cephalosporins with a similar R1 side chain (N= 21)</p><p> </p><p> </p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.