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315 results for “Zeros”
JMIP 2 Net Zero CDR dataset
<p>Scenario data of Sugiyama, Fujimori, Wada, Kato, Matsuo, Nishiura, Oshiro, and Otsuki (2024, Environmental Research Communications) https://doi.org/10.1088/2515-7620/ad4af2 as part of the Japan model intercomparison project (JMIP 2) on long-term climate policy. For previous rounds, please visit https://github.com/UTokyo-mip/JMIP_dataset / https://zenodo.org/record/4817656</p>
Region-specific sourcing of lignocellulose residues as renewable feedstocks for a net-zero chemical industry
<p><span>data_1_lignocellulose_residue_grid_all_years_scenarios – datasets presenting the <em>theoretical</em>, <em>ecological</em>, and <em>available</em> potential of various lignocellulose residues on the GLOBIOM grid level (200 km </span><span>×</span><span> 200 km)</span></p> <p><span>data_2_lignocellulose_feedstock_potential_impacts_country_level_all_scenarios – datasets presenting the <em>theoretical</em>, <em>ecological</em>, and <em>available</em> potential of various lignocellulose residues on the country level and their corresponding climate-change impacts, water stress, and land-use-related biodiversity loss impacts</span></p> <p><span>LUID_CTY – shapefile for the global map with GLOBIOM grids</span></p> <p> </p>
Dataset and code: One-tenth of EU's biomethane potential combined with carbon capture and storage can shift the region's ammonia production to net-zero
<h2>Overview</h2> <p>Repository to share the data and code associated with the scientific article <strong>Istrate et al. One-tenth of EU’s biomethane potential combined with carbon capture and storage can shift the region’s ammonia production to net-zero. One Earth (2024)</strong>. The repository contains data files and code to import the life cycle inventories (LCIs), reproduce the results, and generate the figures presented in the article.</p> <div> <h2>Repository structure</h2> </div> <p>The data folder includes:</p> <ul> <li><code>inventories.xlsx</code> contains the LCI datasets for biomethane and ammonia production formatted for use with <a href="https://github.com/brightway-lca">Brightway</a>.</li> <li><code>sustainable_biomethane_potential_Europe.xlsx</code> contains data on the sustainable biomethane potential in Europe disaggregated by feedstock and country.</li> <li><code>ammonia_production_europe.xlsx</code> contains ammonia production levels in the EU in 2021.</li> <li><code>SA_methane leakage_for presample.xlsx</code> contains data to perform sensitivity analysis on the methane leakage with <a href="https://github.com/PascalLesage/presamples">presamples</a></li> <li><code>SA_upgrading technology_presamples.xlsx</code> contains data to perform sensitivity analysis on upgrading technologies with <a href="https://github.com/PascalLesage/presamples">presamples</a></li> <li><code>results</code> folder within data contains csv files with the results, which are used in <code>05_visualization.ipynb</code> for analysis and visualization purposes.</li> </ul> <p>The notebooks folder includes:</p> <ul> <li><code>01_project_setup.ipynb</code> sets up a new Brightway project and imports the ecoinvent database.</li> <li><code>02_lci.ipynb</code> imports the LCIs and regionalize some datasets (e.g., biomethane supply based on the bimethane potential).</li> <li><code>03_lcia.ipynb</code> calculates life cycle impacts and all the additional results presented in the paper (e.g., calculation of blending ratios).</li> <li><code>04_sensitivity_analysis.ipynb</code> performs the sensitivity analysis.</li> <li><code>05_visualization.ipynb</code> imports all results and generates the figures presented in the scientific article.</li> </ul> <p>The src folder contains supporting functions required to regionalize LCIs and perform the calculations.</p> <div> <h2>How to get propertary data</h2> </div> <p>Some of the LCI datasets in the <code>inventories.xlsx</code> file are partially based on data from the ecoinvent LCI database. To comply with licensing requirements, the file shared in this repository does not include these data points. If you hold a valid ecoinvent license, please contact me directly to receive the full input files containing all ecoinvent data points.</p> <h2>Contact</h2> <p>Robert Istrate: i.r.istrate@cml.leidenuniv.nl</p>
ZIRFs: zero-inflated random forests for estimating gene regulatory networks from single cell RNA-seq data (assessment of predictive accuracy and VIM stability)
<p>We developed a zero-inflated random forests (ZIRFs) algorithm to produce a metric of connection strength between regulator genes and target genes. This file contains SCENIC results for the aorta and diaphragm tissue data sets from the Tabula Muris Consortium results. SCENIC is a genetic regulatory network analysis published by Aibar et al. (2017). The purpose of the data sets and R source code are described by README files in each directory.</p>
Meta-analysis on necessary investment shifts to reach net zero pathways in Europe
<p>This is the code and the data necessary to reproduce the six main figures and the t-test presented in the supplementary information of the publication "Meta-analysis on necessary investment shifts to reach net zero pathways in Europe". DOI: 10.1038/s41558-022-01549-5</p>
SM: Economy-wide impacts of socio-politically driven net-zero energy in Europe
<p><strong>Supplementary Material (SM): Economy-wide impacts of socio-politically driven net-zero energy in Europe</strong></p> <p>Two zipped folders</p> <p>(a) Euro-Calliope.zip includes</p> <p>-Energy system configurations by storyline (market-driven, government-directed, people-powered) and year (2030, 2050).</p> <p>(b) WEGDYN.zip includes</p> <p>-Supplementary Material (SM_Regionaleconomiceffects.pdf)<br>-Processed Euro-Calliope output data to WEGDYN input data (EC2WD_data.xlsx)<br>-WEGDYN results (WEGDYN_data.xlsx)<br>-WEGDYN resolution, nesting trees, elasticities (WEGDYN_model.xlsx)</p>
Zero marking and word order of core arguments
<p>This material contains the dataset from the <a href="https://version.helsinki.fi/hals/sinnemaki/sinnemaki2010">gitlab repository</a> of the following article, with corrections and some additions. Please cite the article when using the data.</p> <p>Sinnemäki, Kaius 2010. Word order in zero-marking languages. <em>Studies in Language</em> 34(4): 869–912.</p>
Dataset and scripts for "Non-zero temperature study of spin 1/2 charmed baryons using lattice gauge theory"
<p><strong>charmJ12Scripts</strong></p> <p>A set of scripts and folders to reproduce the analysis and plots in the spin 1/2 charm baryon paper which can be found at <a href="https://doi.org/10.1140/epja/s10050-024-01261-2">EPJA</a></p> <p> </p> <p>This repository includes the raw correlator data, the scripts and software used to analyse them as well as a script which can be run in order to reproduce the entire analysis, and particularly the figures in the manuscript.</p> <p> </p> <p><strong>correlators</strong></p> <p>Correlators from openqcd-fastsum-hadspec are zipped in the correlators folder. These are unzipped automatically by the script. The correlators are plain text files.</p> <p> </p> <p><strong>output</strong></p> <p>Analysis output is placed here. You do not need to look here in order to see the figures in the paper</p> <p> </p> <p><strong>code</strong></p> <p>The python code and scripts that do the analysis. There is some modularity here with the libraries in the lib folder</p> <p> </p> <p><strong>paperPlots</strong></p> <p>The plots from the paper will be generated here. They are not supplied with this repo as they can be found in the paper</p> <p> </p> <p><strong>plotXYData</strong></p> <p>The x-y and y-error data of each plot in the paper. Only 'scatter' style data is included. This is generated by the run script, but also supplied herein. It will be overwritten by the runscript</p> <p> </p> <p><strong>run</strong></p> <p>The folder where the main script needed to run all the analysis is.</p> <p> </p> <p><strong>Conda Notes</strong></p> <p>Install your favourite conda solution, such as <a href="https://docs.conda.io/en/latest/miniconda.html">https://docs.conda.io/en/latest/miniconda.html</a></p> <p> </p> <p>Switch to a faster environment solver</p> <p>This is optional, but likely will solve the dependencies much much faster. See <a href="https://www.anaconda.com/blog/a-faster-conda-for-a-growing-community">https://www.anaconda.com/blog/a-faster-conda-for-a-growing-community</a> <code>conda update -n base conda</code> <code>conda install -n base conda-libmamba-solver</code> <code>conda config --set solver libmamba</code></p> <p> </p> <p>Install Environment</p> <p><code>conda env create -f environment.yml</code></p> <p> </p> <p>Activate/Use</p> <p><code>conda activate charm</code></p> <p> </p> <p>Update (w. new packages)</p> <ol> <li>Edit <code>environment.yml</code></li> <li>Deactivate conda environment with <code>conda deactivate</code></li> <li>Update conda environment with <code>conda env update -f=environment.yml</code></li> </ol>
Water chemistry data including nitrate stable isotopes sampled from zero-tension lysimeters in an Iowa corn-soybean field in 2017 and 2018
These data were used in the manuscript titled "Mechanisms underlying episodic nitrate and phosphorus leaching from poorly drained agricultural soils" published in the Journal of Environmental Quality. We measured nitrate, ammonium, and phosphate concentrations in zero-tension lysimeters installed along a topographic gradient in a corn and soybean field in north-central Iowa, USA, during 2017 and 2018. We measured nitrate stable isotope compositions in a subset of lysimeter samples. Concentrations of nitrate, ammonium, and ferrous and ferric iron were measured in periodic soil extractions co-located with the lysimeters.
Retrofitting coal-fired power plants with biomass co-firing and CCS for net zero carbon emission: A plant-by-plant assessment based on GIS-LCA framework
<p>Dataset for "Retrofitting coal-fired power plants with biomass co-firing and CCS for net zero carbon emission: A plant-by-plant assessment based on GIS-LCA framework"</p>
Snow flies self-amputate freezing limbs to sustain behavior at sub-zero temperatures
<p><span>All living things are profoundly affected by temperature. In spite of the thermodynamic constraints on biology, some animals have evolved to live and move in extremely cold environments. Here, we investigate behavioral mechanisms of cold tolerance in the snow fly (<em>Chionea</em> spp.), a flightless crane fly that is active throughout the winter in boreal and alpine environments of the northern hemisphere. Using thermal imaging, we show that adult snow flies maintain the ability to walk down to an average body temperature of -7 °C. At this supercooling limit, ice crystallization occurs within the snow fly's hemolymph and rapidly spreads throughout the body, resulting in death. However, we discovered that snow flies frequently survive freezing by rapidly amputating legs before ice crystallization can spread to their vital organs. Self-amputation of freezing limbs is a last-ditch tactic to prolong survival in frigid conditions that few animals can endure. Understanding the extreme physiology and behavior of snow insects is important at this moment when the alpine ecosystems they inhabit are rapidly changing due to anthropogenic climate change.</span></p>
Data for: Curbing global solid waste emissions toward net-zero warming futures
<p>No global analysis has considered the warming that could be averted through improved solid waste management and how much that could contribute to meeting the Paris Agreement's 1.5° and 2°C pathway goals or the terms of the Global Methane Pledge. With our estimated global solid waste generation of 2.56 to 3.33 billion tonnes by 2050, implementing abrupt technical and behavioral changes could result in a net-zero warming solid waste system relative to 2020, leading to 11 to 27 billion tonnes of carbon dioxide warming–equivalent emissions under the temperature limits. These changes, however, require accelerated adoption within 9 to 17 years (by 2033 to 2041) to align with the Global Methane Pledge. Rapidly reducing methane, carbon dioxide, and nitrous oxide emissions is necessary to maximize the short-term climate benefits and stop the ongoing temperature rise.</p>
Source code and simulation results: Poles and zeros of electromagnetic quantities in photonic systems
<h4><strong>Summary</strong></h4> <p>This publication supplements the article "Poles and zeros of electromagnetic quantities in photonic systems" with tabulated data and matlab code that allows to reproduce the results. The article elaborates how evaluating resonances based on contour integrals of scalar electromagnetic quantities extends to computing zeros. Furthermore, direct differentiation of underlying scattering problems is used to compute sensitivities with respect to design parameters.</p> <h4><strong>Structure</strong></h4> <p>The script 'main_text.m' can be used to reproduce the results provided in the paper. In tabulated form the results are contained in the directory <strong>tabulated</strong>. Furthermore, the script 'supplement.m' can be used to reproduce results presented in the supplement. The directory <strong>RPExpand </strong>contains the software RPExpand v2, which is available on <a href="https://doi.org/10.5281/zenodo.10371002">Zenodo</a> with additional examples. </p> <h4><strong>Compute residues</strong></h4> <p>The modal expansion of the Fourier transform is based on its residues at the dominant resonances. If the poles are simple, which often is the case, the residues can be obtained directly from the eigenvectors of the generalized eigenvalue problem used to obtain the poles or the zeros. Introducing the Vandermonde matrix</p> <p>\(V = \begin{bmatrix} 1 & \dots & 1 \\ w_1 & \dots & w_M \\ \vdots & & \vdots \\ w_1^{M-1} &\dots & w_M^{M-1} \end{bmatrix}\),</p> <p>the Hankel matrix \(H\) can be written as \(H = V A V^T\) with \(A\) being the diagonal matrix \(\mathrm{diag}(a_1,\dots,a_M)\) containing the residues \(a_m \). This decomposition is a consequence of the Cauchy's reisdue theorem if the poles are simple. Furthermore, we now that \(V^{-T}\) solves the generalized eigenproblem \(H^<X = HX\Omega\) (Eq. 2 in the original paper) and hence the eigenvectors we get from Matlabs eig routine are \(X = V^{-T}D\) where \(D\) is some scaling. It follows that we obtain the residues using \(A = X^T H X (X V^T)^{-2}\)</p> <h4><strong>Derivatives</strong></h4> <p>Similarly, our framework provides a straight forward approach to the derivatives of zeros and poles if they are simple. Using direct differentiation we have access to partial derivatives of the quantity \(q(\omega)\) and hence the derivatives of the moments \(s_k = \frac{1}{2\pi i} \oint_C \omega^k q(\omega) \mathrm{d}\omega\). For the zeros the inverse \(1/q(\omega)\) and the respective derivative are considered. Using Cauchy's residue theorem the derivatives \(\frac{\partial w_m}{\partial p}\)are solutions of the linear system of equations \(\frac{\partial s_k}{\partial p} = \sum_{m = 1}^{M}\left[k\omega_m^{k-1}\frac{\partial w_m}{\partial p} a_m + \omega_m^k\frac{\partial a_m}{\partial p} \right]\).</p> <h4><strong>Higher order singularities</strong></h4> <p>Finding higher order poles and zeros is possible without further adaptation. Computing derivatives and residues requires some special care. The moments are then given by \(s_k = \sum_{m=1}^{M} \sum_{n = 1}^{N_m} a_{m,n} \frac{k! \, \omega^{k-n+1}}{(k-n+1)!(n-1)!}\)with \(a_{m,n}\) being the residue of the pole \(\omega_m\) and \(n \) refers to the order. Accordingly expressions for the derivatives are available.</p> <h4><strong>Error estimates</strong></h4> <p>The estimated errors in Table 1 refer to the number of integration points, i.e. we are interested in the question how close we get with a given number of integration points to the exact solution of the chosen approximate model of the physical system. Due to propagation of the error the convergence of the derivatives is shifted towards a larger number of integration points.</p> <h4><strong>Requirements</strong></h4> <ul> <li>JCMsuite (version 5.4.3 or newer)</li> <li>MATLAB (tested with version R2019b)</li> </ul> <p>In order to run the scripts you must replace the corresponding place holder in 'zeros_poles.m' by a path to your installation of JCMsuite. Free trial licenses are available, please refer to the homepage of <a href="https://jcmwave.com/">JCMwave</a>.</p> <h4><strong>References</strong></h4> <p>[1] Felix Binkowski, Fridtjof Betz, Rémi Colom, Patrice Genevet, Sven Burger, Poles and zeros of electromagnetic quantities in photonic systems, https://doi.org/10.48550/arXiv.2307.04654</p> <p>[2] Anthony P. Austin, Peter Kravanja, Lloyd N. Trefethen, Numerical algorithms based on analytic function values at roots of unity, SIAM Journal of Numerical Analysis 52, 1795 (2014), https://doi.org/10.1137/130931035</p> <p>[3] Felix Binkowski, Fridtjof Betz, Martin Hammerschmidt, Philipp-Immanuel Schneider, Lin Zschiedrich, Sven Burger, Computation of eigenfrequency sensitivities using Riesz projections for efficient optimization of nanophotonic resonators, Communications Physics <strong>5</strong>, 202 (2022), https://doi.org/10.1038/s42005-022-00977-1</p>
MatSeg DataSet and Benchmark For Zero-Shot Material States Segmentation From images
<h2>This is an old version for the new version see <a href="../records/11331618">https://zenodo.org/records/11331618</a></h2> <p> </p> <p>A Dataset and Benchmark for zero-shot segmentation of materials states described in: “Learning Zero-Shot Material States Segmentation, by Implanting Natural Image Patterns in Synthetic Data” Described in <strong><a href="https://arxiv.org/pdf/2403.03309.pdf">https://arxiv.org/pdf/2403.03309.pdf</a> </strong></p> <p>See ReadMe in the zip file for technical details.</p> <p> </p> <h2><strong>MatSeg Benchmark </strong></h2> <p>A benchmark for zero-shot material state segmentation. The benchmark contains 820 real-world images with a wide range of material states and settings. For example: food states (cooked/burned..), plants (infected/dry.), to rocks/soil (minerals/sediment), construction/metals (rusted, worn), liquids (foam/sediment), and many other states in a class-agnostic manner. The goal is to evaluate the segmentation of material materials without knowledge or pretraining on the material or setting. The focus is on materials with complex scattered boundaries, and gradual transition (like the level of wetness of the surface). The annotation of the benchmark is point-based and similarity-based. Hence, for each image, we select several points and regions (Figure 4). We group the points of the same materials into the same label, we also define a group of points that have partial similarity. For example points in group A are more similar to points in group B than to points in group C (In case materials A and B are similar to each other but not identical). This approach allows us to capture the complexity of gradual transition and partial similarities in the world. While also enabling dealing with complex scattered and blurry shapes without needing to annotate the full shape which in many cases is unclear or very hard.</p> <p>Files <a href="../api/records/10801191/draft/files/MatSegBenchmarkPart1of3.zip/content" target="_blank" rel="noopener noreferrer">MatSegBenchmark</a>*.zip</p> <h2><strong>MatSeg synthetic Dataset Samples </strong></h2> <p>Synthethic dataset of images of materials spread on object surfaces and their segmentation map.</p> <p>The synthetic dataset is a very big, sample of the dataset as been uploaded.</p> <p>Files: MatSegSynthehticDataSample*.zip</p> <p>The full dataset can be found in this URLS:</p> <p><a href="https://e.pcloud.link/publink/show?code=kZHCcnZOfzqInb3anSl7xzFBoqCDmkr2JKV">https://e.pcloud.link/publink/show?code=kZHCcnZOfzqInb3anSl7xzFBoqCDmkr2JKV</a></p> <p><a href="https://icedrive.net/s/SBb3g9WzQ5wZuxX9892Z3R4bW8jw">https://icedrive.net/s/SBb3g9WzQ5wZuxX9892Z3R4bW8jw</a></p> <p> </p> <p>Generation Script for the synthetic data:</p> <p><a href="https://github.com/sagieppel/MatSeg-Synthethic-Dataset-Generation-Script">https://github.com/sagieppel/MatSeg-Synthethic-Dataset-Generation-Script</a></p> <p><a href="../records/10822596/files/sagieppel/MatSeg-Synthethic-Dataset-Generation-Script-3.zip?download=1">https://zenodo.org/records/10822596</a></p> <p> </p> <p> </p> <p> </p>
Zero-Shot Information Extraction to Enhance a Knowledge Graph Describing Silk Textiles - English and Spanish neighborhood sub-graphs
<p>Two language-specific sub-graphs (English and Spanish) based on the ConceptNet Knowledge Graph. These two files are required to run the code for reproducing the results reported in the paper <a href="https://aclanthology.org/2021.latechclfl-1.16/">"Zero-Shot Information Extraction to Enhancea Knowledge Graph Describing Silk Textiles"</a> at the <a href="https://sighum.wordpress.com/events/latech-clfl-2021/">LaTeCH-CLfL 2021</a> workshop co-located with <a href="https://2021.emnlp.org/">EMNLP 2021</a>.</p>
Decoupling of Spin Decoherence Paths near Zero Magnetic Field
<p>We demonstrate a method to quantify and manipulate nuclear spin decoherence mechanisms that are active in zero to ultralow magnetic fields. These include (i) nonadiabatic switching of spin quantization axis due to residual background fields and (ii) scalar pathways due to through-bond couplings between <sup>1</sup>H and heteronuclear spin species, such as <sup>2</sup>H used partially as an isotopic substitute for <sup>1</sup>H. Under conditions of free evolution, scalar relaxation due to <sup>2</sup>H can significantly limit nuclear spin polarization lifetimes and thus the scope of magnetic resonance procedures near zero field. It is shown that robust trains of pulsed dc magnetic fields that apply π flip angles to one or multiple spin species may switch the effective symmetry of the nuclear spin Hamiltonian, imposing decoupled or coupled dynamic regimes on demand. The method should broaden the spectrum of hyperpolarized biomedical contrast-agent compounds and hyperpolarization procedures that are used near zero field.</p> <p>Entry contains processed experimental data for Figures 4-5 of the main paper, and Figures 2-5 of the Supporting Information.</p>
Exact solution and Majorana zero mode generation on a Kitaev chain composed out of noisy qubits
<p>Attached are the data sets in forms of python pickle files from the following submission https://arxiv.org/abs/2108.07235</p> <p>Abstract:</p> <p>Majorana zero modes were predicted to exist as edge states of a physical system called the Kitaev chain. Such zero modes should host particles that are their own antiparticles and could be used as a basis for a qubit that is to large extent immune to noise - the topological qubit. However, all attempts to prove their existence gave inconclusive results. Here, I experimentally show that Majorana zero modes do in fact exist on a Kitaev chain composed out of 3 noisy qubits on a publicly available quantum computer. The signature of Majorana zero modes is a degeneracy with the ground state which is not lifted by noise of the quantum computer. I also confirm that Majorana zero modes have a number of theoretically predicted features: a well-defined parity with switches at specific points and a non-conserved particle number. Furthermore, I show that Majorana zero modes favour long-range Majorana pairing at low chemical potential and short-range pairing at large values of the chemical potential. The results presented here are a most comprehensive set of validations ever conducted towards confirming the existence of Majorana zero modes in nature. I foresee that the findings presented here would allow any user with an internet connection to perform experiments with Majorana zero modes. Furthermore, the noisy intermediate scale quantum computing community can start building topological processors composed out of contemporary noisy qubits.</p>
National Net Zero (or adjacent) targets
<p>This dataset gives an overview of national net zero (or adjacent) targets. There is a specific focus on participation in global governance (e.g. specific check of submitted NDC's)</p> <p>The dataset provides the following data points: </p> <ul> <li>Name of the country (in full)</li> <li>Country ISO3 code</li> <li>End target description (e.g. Net zero, carbon neutral(ity), Ecosystem neutral, etc.</li> <li>End target year (e.g. net zero by 2050 > 2050)</li> <li>End target status: <ul> <li>Achieved (self-declared)</li> <li>In law</li> <li>In policy document (e.g. NDC or INDC, government plans, ...)</li> <li>Declaration / pledge (e.g. target announcement in a press release, ...)</li> <li>Proposed / in discussion (e.g. countries stating they are considering a target or a pledge with an alliance/initiative)</li> </ul> </li> <li>Date of the status (for legislation: the moment it takes into effect)</li> <li>Text of the target</li> <li>Notes on the target</li> <li>Source URL(s)</li> <li>Source of the data entry</li> <li>Year the entry relates to</li> </ul>
Zero G photo of Paul Bechly with Astronaut Dan Barry
<p>Please excuse my bewildered look, but this is the beginning of my first loop in full Zero G. Meanwhile, NASA astronaut Dan Barry is at right with an expression that says, "I'm back".</p>
Molecular dynamics trajectories obtained from simulations of mechanically-controlled break-junctions and associated zero-bias conductance.
<p>This data set contains structural information and the associated zero-bias conductance of mechanically-controlled break-junction experiments. It contains:</p> <ul> <li>Six (multi) xyz files (trajectory_0X.xyz), which contain different trajectories produced by molecular dynamic simulations (using <a href="https://www.lammps.org/">LAMMPS</a> and <a href="https://docs.lammps.org/Packages_details.html#pkg-reaxff">reactive force fields</a>) of a mechanically-controlled break-junction. These simulations start from a gold wire with attached molecules. One side of the wire is slowly pulled away, until the gold wire is broken apart and a molecular junction is formed. The outermost six layers of the goldwire are frozen in the simulation. The temperature of the simulation was set to 300K.</li> <li>Six files (transmission_0X.dat) with the calculated zero-bias conductance (G/G<sub>0</sub>). Each entry corresponds to the zero-bias conductance of the corresponding structure from the xyz files. The zero-bias conductance was calculated using non-scc DFTB+, as, e.g., described <a href="https://dftbplus-recipes.readthedocs.io/en/latest/transport/carbon2d-trans.html">here</a>.</li> </ul> <p>For more information see dx.doi.org/XXXXXXX.</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.