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Supplementary material 1 from: Brix S, Lorz A-N, Jazdzewska AM, Hughes L, Tandberg AHS, Pabis K, Stransky B, Krapp-Schickel T, Sorbe JC, Hendrycks E, Vader W, Frutos I, Horton T, Jazdzewski K, Peart R, Beermann J, Coleman CO, Buhl-Mortensen L, Corbari L, Havermans C, Tato R, Campean AJ (2018) Amphipod family distributions around Iceland. In: Brix S, Lorz A-N, Stransky B, Svavarsson J (Eds) Amphipoda from the IceAGE-project (Icelandic marine Animals: Genetics and Ecology). ZooKeys 731: 1-53. https://doi.org/10.3897/zookeys.731.19854
Table 1. Samples used for present study. : Explanation note: Stations are organised according to the percentage of amphipods identified to the family level. Only the stations marked in green were used for primer analysis, while all were the basis for map preparation. Amphipod taxa are presented from the most to the least abundant in all samples.
Supplementary material 1 from: Lörz A-N, Tandberg AHS, Willassen E, Driskell A (2018) Rhachotropis (Eusiroidea, Amphipoda) from the North East Atlantic. In: Brix S, Lörz A-N, Stransky B, Svavarsson J (Eds) Amphipoda from the IceAGE-project (Icelandic marine Animals: Genetics and Ecology). ZooKeys 731: 75–101. https://doi.org/10.3897/zookeys.731.19814
Table S1. Extended overview of all samples used in analyses with geographical and environmental details : Explanation note: Depths indicated in red have been found using the latitude and longitude information with the datapoint and the bathymetry-layer on Google Earth Pro. Depths indicated in blue are inferred from the general depths in the named (no latitude or longitude given) geographical location, given bathymetry-layer on Google Earth Pro.
Supplementary material 1 from: Jażdżewska AM, Corbari L, Driskell A, Frutos I, Havermans C, Hendrycks E, Hughes L, Lörz A-N, Stransky B, Tandberg AHS, Vader W, Brix S (2018) A genetic fingerprint of Amphipoda from Icelandic waters – the baseline for further biodiversity and biogeography studies. In: Brix S, Lörz A-N, Stransky B, Svavarsson J (Eds) Amphipoda from the IceAGE-project (Icelandic marine Animals: Genetics and Ecology). ZooKeys 731: 55–73. https://doi.org/10.3897/zookeys.731.19931
Table S1 : Explanation note: Amphipod and outgroup accession numbers in BOLD, GenBank and station data.
Supplementary material 4 from: Lörz A-N, Tandberg AHS, Willassen E, Driskell A (2018) Rhachotropis (Eusiroidea, Amphipoda) from the North East Atlantic. In: Brix S, Lörz A-N, Stransky B, Svavarsson J (Eds) Amphipoda from the IceAGE-project (Icelandic marine Animals: Genetics and Ecology). ZooKeys 731: 75–101. https://doi.org/10.3897/zookeys.731.19814
Figure S2. Bayesian consensus tree from COI sequences. Numbers on branches are posterior probabilities. See text for further information. :
Data: A 3/2-approximation algorithm for the Student-Project Allocation problem
<p>This data corresponds to the data and experiments described in Section 5 of<br> the following paper submitted to SEA conference 2018:</p> <p>A 3/2-approximation algorithm for the Student-Project Allocation problem<br> Authors: Frances Cooper and David Manlove</p> <p>The data is located at: https://doi.org/10.5281/zenodo.1186823<br> The software is located at: https://doi.org/10.5281/zenodo.1183221</p> <p>See the README for more information.</p>
List of editions used in CEEC-400 surveyed for the ERRATAS project (as of January 2018)
<p>A list of editions of printed English historical correspondence used in the compilation of CEEC-400 (see <a href="http://www.helsinki.fi/varieng/CoRD/corpora/CEEC/">www.helsinki.fi/varieng/CoRD/corpora/CEEC/</a>), surveyed for the ERRATAS project (as of January 2018).</p>
Nutrient uptake of Humulus lupulus in a rockwool hydroponic drip-system. Bachelor Project Jorian Flik
<p>The complete dataset for my bachelor project "Nutrient uptake of Humulus lupulus in a rockwool hydroponic drip-system"</p> <p>Also contains a copy of the research report sent in at the end of the experiment.</p> <p>date: 3-7-2018</p> <p>Student: jorian Flik, 3rd year biology</p> <p> </p>
Identifying Unmaintained Projects in GitHub
<p>The dataset used in the paper "Identifying Unmaintained Projects in GitHub" accepted at 12th International Symposium on Empirical <em>Software Engineering</em> and Measurement (<em>ESEM),</em> 2018.</p>
Dataset: Dopamine neurons projecting to medial shell of the nucleus accumbens drive heroin reinforcement.
<p>This dataset contains the data presented in the paper Dopamine neurons projecting to medial shell of the nucleus accumbens drive heroin reinforcement. (doi: 10.7554/eLife.39945 )</p>
jEPlus project files and results of simulation of apartment room model with NURBS lined shading
<p>This archive consists of two sets of jEPlus project files for simulation of apartment room model, based on PNNL high-rise apartment building, with a window shading lined by NURBS curves. The difference between the two sets of project files is that in one control points of NURBS can be set independently of each other, while in the other control points are divided in six predetermined groups with the same depth within each group.</p> <p>The archive also contains results of genetic optimisation with jEPlus+EA for locations representing main USA climate zones. For each climate zone there is an obj file, containing generated population of shading variants, and a csv file, containing values of shading parameters and the respective heating and cooling loads.</p> <p>Further, the archive contains two directories, one with Java code and another with gnuplot code, that had been used to process simulations results and create diagrams for the manuscript.</p>
Llars més segures amb el Projecte FIVER - Informatius Canal 9 Radio Televisió Valenciana
<p>Media interview at Valencian TV Canal 9 about European Project FP7-ICT-FIVER on 11 November 2010.</p>
On the abandonment and survival of open source projects: An empirical investigation
<p>This replication package contains the results of our analysis as well as other data and scripts used in the process, which allows to reproduce and extend the results presented in the paper study.</p>
Data for: Projected effects of climate-change-induced flow alterations on stream macroinvertebrate abundances
<p>Global change has the potential to affect river flow conditions which are fundamental determinants of physical habitats. Predictions of the effects of flow alterations on aquatic biota have mostly been assessed based on species ecological traits (e.g., current preferences), which are difficult to link to quantitative discharge data. Alternatively, we used empirically derived predictive relationships for species’ response to flow to assess the effect of flow alterations due to climate change in two contrasting central European river catchments. Predictive relationships were set up for 294 individual species based on (1) abundance data from 223 sampling sites in the Kinzig lower-mountainous catchment and 67 sites in the Treene lowland catchment, and (2) flow conditions at these sites described by five flow metrics quantifying the duration, frequency, magnitude, timing and rate of flow events using present-day gauging data. Species’ abundances were predicted for three periods: (1) baseline (1998–2017), (2) horizon 2050 (2046–2065) and (3) horizon 2090 (2080–2099) based on these empirical relationships and using high-resolution modeled discharge data for the present and future climate conditions. We compared the differences in predicted abundances among periods for individual species at each site, where the percent change served as a proxy to assess the potential species responses to flow alterations. Climate change was predicted to most strongly affect the low-flow conditions, leading to decreased abundances of species up to −42%. Finally combining the response of all species over all metrics indicated increasing overall species assemblage responses in 98% of the studied river reaches in both projected horizons and were significantly larger in the lower-mountainous Kinzig compared to the lowland Treene catchment. Such quantitative analyses of freshwater taxa responses to flow alterations provide valuable tools for predicting potential climate-change impacts on species abundances and can be applied to any stressor, species, or region.</p>
Introduction of RISIS project by Philippe Laredo
<p>Introduction of RISIS project by Philippe Laredo</p>
DATS 6401- Individual Project - Mo Zhou
<p>These are images I used in my project.</p>
Description of project Metaphore
<p>Draft of the public project description and the corresponding figures</p>
Stacked Dense Denoise-Segmentation FBP reconstruction from 3601 projection
<p>The FBP recontruction from 3601 projection of the dataset used in the Stacked Dense Denoise-Segmentation Network. For the reconstruction the Savu Python package was used (https://doi.org/10.5281/zenodo.32840). We acknowledge Diamond Light Source for the time on I13-2 under proposal mt9396.</p>
Stacked Dense Denoise-Segmentation CGLS reconstruction from 91 projection
<p>The CGLS recontruction from 91 projection of the dataset used in the Stacked Dense Denoise-Segmentation Network. For the reconstruction the Savu Python package was used (https://doi.org/10.5281/zenodo.32840). We acknowledge Diamond Light Source for the time on I13-2 under proposal mt9396.</p>
GATEMAN project -- Wide-bandwidth, high-precision GNSS and jammer raw data
<p>This dataset contains high quality GNSS and jammer raw data generated during the in-lab validation activities of jamming detection and localization performed in the frame of the GATEMAN project. These files are grouped for each type of validation scenario defined. The scenarios are combinations of three different GNSS and three different jamming signals.</p> <p><strong>Content:</strong></p> <p>The archive contains a folder for each validation scenario. Each folder contains two files. One contains the GNSS data and the second file contains jamming data. A function to read the data with GNU Octave/Matlab is also included.</p> <p>├── GALE1+AMtone<br> │ ├── AMtone@20MSps.bin<br> │ └── GALE1@20MSps.bin<br> ├── GALE1+Chirp10MHz<br> │ ├── Chirp10MHz@20MSps.bin<br> │ └── GALE1@20MSps.bin<br> ├── GALE1+Chirp20MHz<br> │ ├── Chirp20MHz@20MSps.bin<br> │ └── GALE1@20MSps.bin<br> ├── GPSL1+AMtone<br> │ ├── AMtone@20MSps.bin<br> │ └── GPSL1@20MSps.bin<br> ├── GPSL1+Chirp10MHz<br> │ ├── Chirp10MHz@20MSps.bin<br> │ └── GPSL1@20MSps.bin<br> ├── GPSL1+Chirp20MHz<br> │ ├── Chirp20MHz@20MSps.bin<br> │ └── GPSL1@20MSps.bin<br> ├── GPSL5+AMtone<br> │ ├── AMtone@20MSps.bin<br> │ └── GPSL5@20MSps.bin<br> ├── GPSL5+Chirp10MHz<br> │ ├── Chirp10MHz@20MSps.bin<br> │ └── GPSL5@20MSps.bin<br> ├── GPSL5+Chirp20MHz<br> │ ├── Chirp20MHz@20MSps.bin<br> │ └── GPSL5@20MSps.bin<br> └── readBinData.m</p> <p> </p> <p><strong>Data format:</strong></p> <p>Each file stores the received baseband samples as an array of complex, 16-bit signed integer data (range -32,768 to 32,767) of the corresponding signal. The data is stored in Big-endian, network order format, i.e. the most-significant byte occupies the lowest memory address. The real and imaginary components of the data correspond to the in-phase (I) and quadrature-phase (Q) data, respectively. I and Q-samples are interleaved [I, Q, I, Q, ...] in the array.</p> <p> </p> <p><strong>Data:</strong></p> <p>The recorded data of each validation scenario consists of two files, one containing the GNSS signal (L1, L5 or E1 band), the other one containing the jamming signal (tone, chirp 10 & 20 MHz bandwidth). The RF GNSS signal was generated with a GNSS signal generator, it contains only a single spreading sequence. The RF jamming signal was generated with a Vector Signal Transceiver. Both signals of a scenario were recorded synchronously with an USRP at an I\Q rate of 20 MS/s.</p> <p>GNSS signals:</p> <ul> <li>Startime: 30.05.2018 at 12:00 (approximately)</li> <li>Latitude: N 50 deg, 50.4864 min</li> <li>Longitude: E 4 deg, 21.3499 min</li> <li>Altitude: 50m</li> <li>Trajectory: Static</li> <li>Ephemeris file: brdc1500.18.n</li> </ul> <p><br> GNSS band PRN Elevation (deg) Azimuth (deg) Power (dBm)<br> GPS L1 4 85 187 -70<br> GPS L5 4 85 193 -70<br> Galileo E1 E14 66 274 -68.5</p> <p>Jamming signals:</p> <ul> <li>The tone is simple a sinosoidal waveform in the centre of the GNSS bands.</li> <li>The chirps are linear frequency modulated waveforms (sawtooth) in the centre of the GNSS bands with sweep range of 10 MHz and 20 MHz and sweep period of 8.64 µs.</li> </ul> <p> </p> <p> </p> <p>The data uploaded here are a truncated samples. Longer samples of data are available upon request.</p>
"45' Reception" Our Mythical Childhood ERC Consolidator Grant Project: Episode 1: "Atlantis. A City Guide" ["Atlantyda. Przewodnik po mieście"], a book by Natalia Olbińska
<p>A video in the OurMythicalChildhood popularizing cycle "45 Seconds Reception".</p> <p>This video presents briefly a Polish black and white picturebook entitled "Atlantyda. Przewodnik po mieście" ["Atlantis. A City Guide"] written by Natalia Olbińska (2017). Beginning with the description of the town itself, the author tells us how to get there, which places are worth visiting (Poseidon’s temple, Guggenheim Museum, etc.), and provides a good deal of practical information (including how to travel within Atlantis, where to sleep, eat, and drink)<em>. </em>Both in the text and the illustrations, the author refers to classical sources: Plato’s "Timaeus" and "Critias", the Punic Wars, Greek ships and pieces of art (Artemision Bronze, Aphrodite of Knidos, Riace bronzes, Myron’s "Discobolus"), mythical sea creatures (Hippocamp, the Sirens), and a god (Poseidon). Besides "Atlantyda" contains also ecological message.</p> <p>Graphic designs by Mirosław Kaźmierczak, also: Katarzyna Marciniak - idea of the cycle, Anna Mik - edition, Elżbieta Olechowska - English proofreading.</p> <p>The video is also available here: <a href="https://www.youtube.com/watch?v=LswwdWnA3_g">https://www.youtube.com/watch?v=LswwdWnA3_g</a>.</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.