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FIGURE 4 in Bouchetaria (Gastropoda: Cypraeidae), a new genus for the Riddle cowry, B. aenigma (Lorenz 2002), from the deep waters of the Mozambique Channel

FIGURE 4. Detail of the anterior extremity from labral view. Note the differences in the formation of the labral margins and the terminal ridges. a. Praerosaria meyeri (BOETTGER 1883) (24 mm) Sulzheim, Germany. Upper Oligocene. b. Praerosaria biacuta (DOLIN & LOZOUET 2004) (17 mm) Saint Paul lès Dax, France. Oligocene. Holotype MNHN IM-2000-3764. Photos courtesy Recolnat, Lozouet. c. Bouchetaria aenigma (Lorenz 2002) (28 mm) Glorioso Is. MNHN IM-2013-69876. d. Nesiocypraea midwayensis midwayensis (AZUMA & KUROHARA 1967) 23 mm. Taiwan.

FIGURE 3. a–d in Bouchetaria (Gastropoda: Cypraeidae), a new genus for the Riddle cowry, B. aenigma (Lorenz 2002), from the deep waters of the Mozambique Channel

FIGURE 3. a–d. Bouchetaria aenigma (28-33 mm) Glorieuses Islands, at 220–300 m. Coll. MNHN. e. Bouchetaria aenigma (36 mm) Geyser Bank, between Mayotte and the Glorieuses Islands, at 340 m. Coll. MNHN.

FIGURE 2 in Bouchetaria (Gastropoda: Cypraeidae), a new genus for the Riddle cowry, B. aenigma (Lorenz 2002), from the deep waters of the Mozambique Channel

FIGURE 2. Bayesian phylogenetic tree obtained based on the concatenated cox1 and 16S gene datasets. Posterior probabilities (> 0.79) and ultrafast bootstrap values (> 80) are shown for each node.

FIGURE 1 in Bouchetaria (Gastropoda: Cypraeidae), a new genus for the Riddle cowry, B. aenigma (Lorenz 2002), from the deep waters of the Mozambique Channel

FIGURE 1. Type material of Nesiocypraea aenigma Lorenz, 2002. a. Holotype collected at unknown depth off northern KwaZulu Natal, South Africa. b. Paratype collected at 250 m depth off Mozambique in the 1970s, current disposition unknown.

opencc-by-4.0Apr 2024View details →

Dynamic conformational changes of acid-sensing ion channels in different desensitizing conditions

Peer-reviewed manuscript, supplemental file, and source data related to the article 'Dynamic conformational changes of acid-sensing ion channels in different desensitizing conditions'.

opencc-by-4.0Apr 2024View details →

Ancient Craton-wide Mid-lithosphere Discontinuity Controlled by Pargasite Channels

APPENDIX FILES for GRL publication Ancient Craton-wide Mid-lithosphere Discontinuity Controlled by Pargasite Channels by Sudholz and Zhang et al. (2024).

opencc-by-4.0Nov 2023View details →

Data for Seismic Noise and Subsurface Velocity Characterization for a Unique Bedload Monitoring Observatory in a Dryland Ephemeral Channel

Seismic dataset used in submitted manuscript "Seismic Noise and Subsurface Velocity Characterization for a Unique Bedload Monitoring Observatory in a Dryland Ephemeral Channel".

Morph_CNeT: A new GIS tool to extract morphometric attributes characterising channel network topology of Indian catchments

Morph_CNeT” (Morphometric Channel Network Extraction Tool) can facilitate extraction of the topology based new morphometric attributes by processing DEM datasets within GIS framework. Morph_CNeT tool is used to create a repository named as Morph_CNeT-India of topological catchment attributes for 1749 gauging stations maintained by the Central Water Commission (CWC) across 22 River basin Systems of India.

Dataset from Rummel et al.: "Spatially resolved salt intrusion mechanisms in a tidal estuary and the impact of channel deepening" - Part 1

Model data from the numerical setup of the Weser River Estuary used in Rummel et al. (submitted to JGR:Oceans): "Spatially resolved salt intrusion mechanisms in a tidal estuary and the impact of channel deepening" - Part 1. The dates in the file names are connected to specific model runs and do not explain the modelled time period. Explanation of datasets: <ul> <li>2D_elev*  -  2D model output for the entire year 2016  for validation at one location each (associated station name included in file name), original topography.</li> <li>3D_stat*  -  3D model output for the entire year 2016 for validation at one location each (associated station name included in file name), original topography.</li> <li>3D_cross_30_80*  -  3D model output for one month of 2016 for the model domain from Weser km 30 to 80 including variables needed for the salt transport decomposition. <ul> <li>2024-05-23  -  March 2016, original topography</li> <li>2024-06-07  -  March 2016, dredged topography</li> <li>2024-06-06  -  September 2016, original topography (different temporal resolution)</li> <li>2024-06-10  -  September 2016, dredged topography</li> </ul> </li> <li>3D_channel*  -  3D model output for the navigational channel in the entire model domain for the entire year 2016. <ul> <li>2024-04-02  -  original topography</li> <li>2024-05-16  -  dredged topography</li> </ul> </li> <li>3D_cross_55/65_2024-09-02*  -  3D model output for September 2016, original topography for crosssections at Weser km 55 and 65 including variables needed for the salt transport decomposition.</li> </ul>

Dataset from Rummel et al.: "Spatially resolved salt intrusion mechanisms in a tidal estuary and the impact of channel deepening" - Part 2

Dataset from Rummel et al.: "Spatially resolved salt intrusion mechanisms in a tidal estuary and the impact of channel deepening" - Part 3

Dataset underlying publication "Optical-comb-based frequency stability transfer across the spectrum with a multi-channel FPGA

This archive contains datasets underlying plots of the publication "Optical-comb-based frequency stability transfer across the spectrum with a multi-channel FPGA". Datasets contain header, and a minimum script to reproduce figures is provided This work was supported by the European Metrology Program for Innovation and Research (EMPIR), Project 20FUN08 Nextlasers, which received funding from the EMPIR programme cofinanced by the Participating States and from the European Union’s Horizon 2020 research and innovation program.

MD Source Data for "Subunit-specific conductance of single HCN pacemaker channels at femtosiemens resolution"

This dataset is the MD source data for the research paper ''Subunit-specific conductance of single HCN pacemaker channels at femtosiemens resolution''. It includes the following parts: <ol> <li>Figures.zip. This file provides high resolution MD related figures, including main figures and supplementary figures.</li> <li>Figure_source_data.zip. This is the source data for the figures in the paper.</li> <li>Homology_Modelling_result.zip. This file provides the input (rHCN4, PDB ID: 7NP3) and output files (mHCN1-4, hHCN4) of homology modelling.</li> <li>MD_input.zip. This is the MD setup input data. It includes starting structure, topology file, .mdp file and force field file. Due to the limitation of storage space (50 GB), it is a pity we couldn't upload all trajectories files (~180 GB). But these files are enough for rerunning the MD simulations.</li> <li>Movie 1. K+ permeation in mHCN2 channel during a 250 ns trajectory.</li> </ol>

opencc-by-4.0Feb 2024View details →

Bluetooth Low Energy Separate Channel Fingerprinting dataset with Frequency-Scanned Antennas and Monopole

This dataset contains Bluetooth Low Energy Separate Channel (SC BLE) Fingerprinting (FP) data recorded in an indoor facility. The dataset includes Received Signal Strength Information (RSSI) data collected from two independent location systems: one created with four BLE beacons connected to four traditional monopole antennas, and the other four beacons connected to two dual-port Frequency-Scanned Leaky Wave Antennas (FS LWA). Both systems are installed covering the same 7m x 5m area located in a basement zone.  The dataset includes a reference radiomap file for each point equidistant 50cm to generate Fingerprinting techniques. The calibrated radiomap files are included in the Calibration_21112023 folder. In the name of each file, the {x, y} position where the data were recorded is included, with a total of 130 reference points. The data labelled as P1 and P2 are the RSSI recorded from beacons connected to FS LWA1, while P3 and P4 data corresponds to RSSI obtained from beacons of FS LWA2. Finally, P5, P6, P7 and P8 data sets belong to beacons connected to individual monopole antennas. Each calibration file contains 100 samples of RSSI received from the corresponding beacons at each one of the 130 reference points forming the calibration grid.  The dataset also includes test samples for different days. These days are labelled as day 1, 8, 15, 22, 29, 51, 86 and 94 after the calibration day 0. This way, the variation of the different SC FP BLE antenna systems’ performance over time, can be studied. This classification of the data as a function of time, is categorized in the folders with the names Test_day_XX_date. As done with the reference calibration information for day 0, a file with the RSSI collected in each reference point (within a total of 130 grid points) can be found in each folder. The name of the file indicates the reference point where the data were collected. Different to the reference calibration data of day 0 (where 100 RSSI samples were considered for each one of the 130 calibrated {x, y} positions), the test data obtained in different subsequent days is composed by ten samples of RSSI for each one of the 130 test point.  Moreover, to test the performance of the systems when some modifications occur where the calibration was performed, some data tests are collected adding several offices' furniture on the days 15, 22, 29, 51 and 94 after the calibration procedure performed at day 0. These data are stored in folders with the name Test_day_XX_with_furnitures_date. Similar to the previous test data, the name of the file includes 130 reference {x,y} points, with 10 RSSI samples each, and for the corresponding eight beacons (P1..P8), which are labelled for both monopole (P5, P6, P7 and P8) and FS LWA antenna systems (P1 and P2 for FS LWA1 and P3 and P4 for FS LWA2).

openMar 2024View details →

Data of Västilä & Jilbert (2024): Evaluating multiannual sedimentary nutrient retention in agricultural two-stage channels

This dataset contains measured and modelled data on the flow-sediment-nutrient interactions in a two-stage (compound) agricultural channel in Sipoo, Finland. The whole dataset is analyzed by Västilä & Jilbert (2024), but parts of the data have been previously described and analyzed by <a href="https://www.tandfonline.com/doi/full/10.1080/15715124.2011.572888" target="_blank" rel="noopener">Västilä & Järvelä (2011)</a>, <a href="https://ascelibrary.org/doi/full/10.1061/%28ASCE%29HY.1943-7900.0001058" target="_blank" rel="noopener">Västilä et al. (2016)</a>, <a href="https://link.springer.com/article/10.1007%2Fs11368-017-1776-3" target="_blank" rel="noopener">Västilä & Järvelä (2018)</a> and <a href="https://www.mdpi.com/2071-1050/13/16/9349" target="_blank" rel="noopener">Västilä et al. (2021)</a>. The dataset contains three separate files:  1) repeated elevation surveys of the cross-sectional geometry in six channel cross-sections in years 2010, 2012 and 2019  2) vertical distributions of total phosphorus, nitrogen, carbon and sulphur in the main channel bed, floodplain and channel bank sediments 3) experimentally determined daily average discharges, suspended sediment loads and total phosphorus loads in years 2009-2012, as well as modelled daily average discharges and loads of suspended sediment, total phosphorus, total nitrogen and total organic carbon in years 2009-2019 Brief metadata descriptions (read-me) are included in each Excel file. Further details are described in the original scientific publications listed below.  Västilä, K. 2010. Cohesive sediment processes in vegetated flows: preliminary field study results. In Dittrich, A., Koll, Ka., Aberle, J. & Geisenhainer, P. (eds.), Proceedings of River Flow 2010, Fifth International Conference on Fluvial Hydraulics, 8–10 September 2010, Braunschweig, Germany, pp. 317–324. Bundesanstalt für Wasserbau, Karlsruhe. ISBN-13: 978-3939230007. Västilä, K. & Jilbert, T. 2024 Evaluating multiannual sedimentary nutrient retention in agricultural two-stage channels. Scientific Reports, doi: 10.1038/s41598-024-84956-2. Västilä, K. & Järvelä, J. 2011 Environmentally preferable two-stage drainage channels: considerations for cohesive sediments and conveyance. International Journal of River Basin Management, 9(3–4): 171–180. doi: 10.1080/15715124.2011.572888.  Västilä, K. & Järvelä, J. 2018 Characterizing natural riparian vegetation for modeling of flow and suspended sediment transport. Journal of Soils and Sediments, 18(10): 3114–3130. doi: 10.1007/s11368-017-1776-3. Västilä, K., Järvelä, J., and Koivusalo, H. 2016 Flow–vegetation–sediment interaction in a cohesive compound channel. Journal of Hydraulic Engineering, 142(1): 04015034. doi:10.1061/(ASCE)HY.1943-7900.0001058. Västilä, K., Väisänen, S., Koskiaho, J., Lehtoranta, V., Karttunen, K., Kuussaari, M., Järvelä, J., Koikkalainen, K. 2021 Agricultural Water Management Using Two-Stage Channels: Performance and Policy Recommendations Based on Northern European Experiences. Sustainability, 13(16), 9349. doi: 10.3390/su13169349

opencc-by-4.0Aug 2024View details →

Effects of the fungicide penconazole on the leaf litter associated aquatic mycobiome in artificial stream channel and flask experiments

Open the record for dataset details and reuse information.

Fig. 6 in A novel filamentous cyanobacterium Microseira minor sp. nov. (Oscillatoriaceae, Cyanobacteria) from the Ganfu Channel, Jiangxi, China

Fig. 6. Bayesian inference (BI) phylogenetic tree based on nifH gene sequences. Bootstrap values of Bayesian posterior probabilities greater than 0.50 are showed on the BI tree. The novel filamentous species of this study is indicated in bold. Bar, 0.05.

Fig. 4 in A novel filamentous cyanobacterium Microseira minor sp. nov. (Oscillatoriaceae, Cyanobacteria) from the Ganfu Channel, Jiangxi, China

Fig. 4. Bayesian inference (BI) phylogenetic tree based on 16S rRNA gene sequences. Bootstrap values of Bayesian posterior probabilities greater than 0.50 are showed on the BI tree. The novel filamentous strains of this study is indicated in bold. Bar, 0.03.

Fig. 2 in A novel filamentous cyanobacterium Microseira minor sp. nov. (Oscillatoriaceae, Cyanobacteria) from the Ganfu Channel, Jiangxi, China

Fig. 2. Ultrastructure of Microseira minor strains. (Cw, cell wall, Th, thylakoids, Nu, nucleoplasm, Sh, sheath). Scale bars: A–D, 2 μm.

Fig. 1 in A novel filamentous cyanobacterium Microseira minor sp. nov. (Oscillatoriaceae, Cyanobacteria) from the Ganfu Channel, Jiangxi, China

Fig. 1. Light microscopy of Microseira minor strains. A–C. Immature filaments with colourless sheaths (Arrow indicates sheath). D–G. Trichome fragmentation and formation of necridia (Arrows indicate fragmentation of trichomes and formation of necridias). H–I. Old filaments with lamellated sheaths (Arrows indicate lamellated sheaths). Scale bars: 20 μm.