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Pacemaker neurons exert control over neuronal circuit function by their intrinsic ability to generate rhythmic bursts of action potential. Recent work has identified rhythmic gut contractions in human, mice and hydra to be dependent on both neurons and the resident microbiota. However, little is known about the evolutionary origin of these neurons and their interaction with microbes. In this study, we identified and functionally characterized prototypical ANO/SCN/TRPM ion channel expressing pacemaker cells in the basal metazoan Hydra by using a combination of single-cell transcriptomics, immunochemistry, and functional experiments. Unexpectedly, these prototypical pacemaker neurons express a rich set of immune-related genes mediating their interaction with the microbial environment. Functional experiments validated a model of the evolutionary emergence of pacemaker cells as neurons using components of innate immunity to interact with the microbial environment and ion channels to generate rhythmic contractions. Data includes: Full count matrices for all the plates: - SS_038.rsem_counts.txt.gz - SS_039.rsem_counts.txt.gz - SS_040.rsem_counts.txt.gz Full expression matrix after cell filtering: raw_count_table_seurat_filter_cluster_ID_191009_SG.txt.gz Metadata with cluster assignment: cell_seurat_clusters_identity.txt.gz
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Results of reliability assessment of punching shear resistance models for flat slabs without shear reinforcement through three different reliability analysis techniques: Mean Value First Order Second Moment Method (MVFOSM), First Order Second Method (FOSM) and a Monte-Carlo Simulation with Importance Sampling (MC-IS).
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The dataset contains the data collected in a user study carried out to evaluate the impact of using domain knowledge, ontologies, in the creation of global post-hoc explanations of black-box models. The research hypothesis was that the use of ontologies could enhance the understandability of explanations by humans. To validate this research hypothesis we ran a user study where participants were asked to carry out several tasks. In each task, the answers, time of response, and user understandability and confidence were collected and measured. The data analysis revealed that the use of ontologies do enhance the understandability of explanations of black-box models by human users, in particular, in the form of decision trees explaining artificial neural networks.
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In the current data article, we present detailed characteristics of voids in carbon/epoxy composite laminates as well as the original image stacks, obtained via X-ray micro-Computed Tomography (micro-CT) . Five different lay-ups are produced with altering the recommended cure cycle in order to intentionally induce voids in the material. For each lay-up, an image stack (consisting of tomographic slices) and a dataset are provided. The image slices are in 8-bit TIF format. The datasets (spreadsheets) include the volume, size parameters, shape parameters, orientation, and location of all the detected voids in the specimen. The segmentation of the images and quantification of voids are performed in VoxTex, an in-house software for processing of micro-CT results. The data is linked to a Data in Brief article "Mehdikhani et al., A dataset of voids’ characteristics in multidirectional carbon fiber/epoxy composite laminates, obtained using X-ray micro-computed tomography, DIB 27 (2019) 104686" and linked to the article "Mehdikhani et al. Detailed characterization of voids in multidirectional carbon fiber/epoxy composite laminates using X-ray micro-computed tomography. Comp Part A 125 (2019) 105532".
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The dataset provides a chaos game representation (CGR) of SARS-CoV-2 virus nucleotide sequences. The dataset is composed of 100 virus instances of SARS-CoV-2. In addition, the dataset also provides a CGR representation of 11540 viruses from the Virus-Host DB dataset and the other three Riboviria viruses from NCBI.
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  • Tabular Data
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This data set contains the derived data products for the published manuscript Orgel et al. (2020) "Re-examination of the population, stratigraphy, and sequence of mercurian basins: Implications for Mercury´s early impact history and comparison with the Moon" at Journal of Geophysical Research Planets. This data package includes GIS-ready shapefiles of Mercurian basins, crater counting measurements, and Craterstats files.
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Identifying Factors Affecting E-customer Loyalty in Gamified Trusted Store Platforms: A Case Study Analysis in Iran
Data Types:
  • Software/Code
  • Dataset
  • Text
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The micro x-ray CT images of two rock samples have been reconstructed. The data type of images: uint8 Spatial Resolution: 1.2 micrometer/voxel Size: 400X400X400 The reconstructed or "Original" images are suffering from existence of artifacts, roundoff errors, and different types of visual or mathematical noises in the reconstructed CT images. Each image has been applied with a series of bandpass and bilateral filters.
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Supplementary Data. Includes Excel data tables for ages and shapefiles for ages, geomorphology and ice-sheet reconstruction.
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Non-marginal (average) AWARE CFs and WSI CFs: We provide a shapefile, CSV file and KML file of the average AWARE characterization factors (CFs) based on the marginal AWARE CFs from Boulay et al. (2018). We also provide it together with average WSI factors from Pfister and Bayer (2014), since based on the UNEP SETAC recommendation, AWARE should be used together with an alternative scarcity method to test sensitivities (Jolliet et al. 2018). The XLS version of the average AWARE CFs is available from the original publication: Pfister S, Scherer L, Buxmann K (2020) Water scarcity footprint of hydropower based on a seasonal approach - Global assessment with sensitivities of model assumptions tested on specific cases. Science of The Total Environment. https://doi.org/10.1016/j.scitotenv.2020.138188 DATA structure: The CSV files lists CFs for each month (01 to 12) and each methods: AWARE_01 stands for original marginal AWARE CFs of January, AWARE_a_01 represents the newly calculated average AWARE CFs for January, WSI_01 are the marginal WSI CFs for January and WSI_AVG_01 the average WSI CFs for January. The CSV file can be linked to WaterGAP watersheds based on the "BAS34S_ID" . The WaterGAP shapefile is e.g. available at http://www.wulca-waterlca.org/aware.html. The Shapefile and KML file follows the same order but are already linked to the watershed shapefile.
Data Types:
  • Geospatial Data
  • Tabular Data
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