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2,031 results for “Transformation”
Multi-label Datasets used in "Adapting Transformers for Multi-Label Text Classification"
<p>The three Multi-Label datasets used in the article "Adapting Transformers for Multi-Label Text Classification".</p> <p>- AAPD Dataset (ArXiv Academic Paper Dataset) [Yang et al. 2018]<sup>1</sup></p> <p>- Reuters-21578 Dataset: https://archive.ics.uci.edu/ml/datasets/reuters-21578+text+categorization+collection</p> <p>- MFHAD (Multilabel French HAL Abstracts Dataset)</p> <p> </p> <p><sup>1</sup>Pengcheng Yang, Xu Sun, Wei Li, Shuming Ma, Wei Wu, and Houfeng Wang. 2018.<br> SGM: Sequence Generation Model for Multi-label Classification. In Proceedings<br> of the 27th International Conference on Computational Linguistics. Association for<br> Computational Linguistics, Santa Fe, New Mexico, USA, 3915–3926.</p>
Dataset for the pubblication "Impact of DC Transient Disturbances on Harmonic Performance of Voltage Transformers for AC Railway Applications"
<p>This is the dataset for the paper published:</p> <p>Letizia, P.S.; Signorino, D.; Crotti, G. Impact of DC Transient Disturbances on Harmonic Performance of Voltage Transformers for AC Railway Applications. <em>Sensors</em> <strong>2022</strong>, <em>22</em>, 2270. https://doi.org/10.3390/s22062270</p> <p> </p>
Supplementary material "Designing robust transformation toward a sustainable circular battery production"
<p>Supplementary material for the publication " Designing robust transformation toward a sustainable circular battery production" in Procedia CIRP. The paper is available at <a href="https://doi.org/10.1016/j.procir.2023.02.069">https://doi.org/10.1016/j.procir.2023.02.069</a>.</p> <p> </p> <p>The underlying research of this publication was funded by the German Federal Ministry of Education and Research within the Competence Cluster Recycling & Green Battery (greenBatt) (03XP0302A) and the research project EffizientNutzen (033R240C). The authors are responsible for the content of this publication.</p> <p><em>Accepted for publication</em></p>
Data Set for Predicting the Performance of ATL Model Transformations
<p>Model transformation languages are special-purpose languages, which are designed to define transformations as comfortably as possible, i.e., often in a declarative way. With the increasing use of transformations in various domains, the complexity and size of input models are also increasing. However, developers often lack suitable models for performance testing. We have therefore conducted experiments in which we predict the performance of model transformations based on characteristics of input models using machine learning approaches. This dataset contains our raw and processed input data, the scripts necessary to repeat our experiments, and the results we obtained.</p> <p>Our input data consists of the time measurements for six different transformations defined in the Atlas Transformation Language (ATL), as well as the collected characteristics of the real-world input models that were transformed. We provide the script that implements our experiments. We predict the execution time of ATL transformations using the machine learning approaches linear regression, random forests and support vector regression using a radial basis function kernel. We also investigate different sets of characteristics of input models as input for the machine learning approaches. These are described in detail in the provided documentation.pdf. The results of the experiments are provided as raw data in individual cvs files. Additionally, we calculated the mean absolute percentage error in % and the 95th percentile of the absolute percentage error in % for each experiment and provide these results. Furthermore, we provide our Eclipse plugin, which collects the characteristics for a set of given models, the Java projects used to measure the execution time of the transformations, and other supporting scripts, e.g. for the analysis of the results.</p> <p>A short introduction with a quick start guide can be found in README.md and a detailed documentation in documentaion.pdf.</p>
Time series analysis of tegument ultrastructure of in vitro transformed miracidium to mother sporocyst of the human parasite Schistosoma mansoni
<p>Here is a compilation of all the Scanning Electron Microscopy pictures at our disposal regarding the in vitro transformation of miracidia to mother sporocysts of <em>Schistosoma mansoni</em>. These datas were partially published in:</p> <p><a href="https://doi.org/10.1016/j.actatropica.2023.106840">https://doi.org/10.1016/j.actatropica.2023.106840</a></p> <p> </p>
Interview Transcriptions related to PhD Thesis "Degrowth at a Global Scale? Geographies of Chile's Fruit Production and Export between Extractivism and Socio-Ecological Transformation"
<p>The material is composed of transcriptions of interviews conducted for the empirical work of this PhD Thesis.</p> <p>Not all conducted interviews are included (which can be seen from the accompanying table); those not included are not available mostly due to lack of consent of interviewees or because certain interviews were not registered and only hand-written notes were taken.</p>
Fourier transform infrared spectroscopy as a non-destructive method for analysing herbarium specimens
<p>Dried plant specimens stored in herbaria are an untapped treasure chest of information on environmental conditions, plant evolution and change over many hundreds of years. Due to their delicate nature and irreplaceability, there is limited access for analysis to these sensitive samples, particularly where chemical data is obtained using destructive techniques. Fourier transform infrared spectroscopy (FTIR) is a chemical analysis technique that can be applied non-destructively to understand chemical bonding information and therefore functional groups within the sample. This provides the potential for understanding geographic, spatial and species-specific variation in plant biochemistry. Here we demonstrate the use of mid-FTIR microspectroscopy for the analysis of <em>Drosera</em> <em>rotundifolia</em> herbaria specimens, which were collected 100 years apart from different locations. Principal component and hierarchical clustering analysis enabled successful differentiation between three main regions on the plant (lamina, tentacle stalk and tentacle head), and between the different specimens. Lipids and protein spectral regions were particularly sensitive differentiators of plant tissues. Differences between the different sets of specimens were smaller. This study demonstrates that relevant information can be extracted from herbarium specimens using FTIR, with little impact on the specimens. FTIR therefore provides the potential as a powerful tool to unlock historic information within herbaria.</p>
Datasets for Transformer-based tool recommeder in Galaxy
<p>Datasets for Transformer-based tool recommeder in Galaxy:</p> <p>1. Tool popularity - Contains last one year usage of all Galaxy tools per month (Extracted from Galaxy Europe using query https://github.com/galaxyproject/gxadmin/blob/main/docs/README.query.md#query-tool-popularity)</p> <p>2. Workflow connections - Contains workflows as tabular files as pairs of tools - IN and OUT (Extracted from Galaxy Europe using query https://github.com/galaxyproject/gxadmin/blob/main/docs/README.query.md#query-workflow-connections)</p> <p> </p> <p> </p>
Dataset for the EPSL article: Evidence for low Vp/Vs ratios along the eastern Romanche ridge-transform intersection in the equatorial Atlantic Ocean
<p>The obtained 3-D P-wave and S-wave velocity models in the Romanche eastern ridge-transform intersection, using arrival times from 514 microearthquakes recorded by a recent temporary array of seafloor seismometers.</p> <p>Related article:</p> <p><strong>Yu, Z.</strong>, Singh, S. C. & Maia, M. (2023). Evidence for low Vp/Vs ratios along the eastern Romanche ridge-transform intersection in the equatorial Atlantic Ocean. <strong><em>Earth and Planetary Science Letters, </em></strong>621, 118380.</p>
Data from: Transformation from NHx to NOy deposition aggravated China's forest soil acidification
<p><span>Elevated nitrogen (N) deposition and changes in reduced or oxidized component contribution greatly affect soil acidification. China has experienced a significant transformation of N deposition components from NH<sub>x</sub> to NO<sub>y</sub> over the past 40 years, but the effects of component transformation on soil acidification are poorly understood. Therefore, long-term monitoring data and literature on N deposition, combined with the results of isotope experiments, were used to explore the contributions of different N forms on soil acidification in China's forests. Here, all processes related to NH<sub>x</sub> and NO<sub>y</sub>, including the transformation to NH<sub>4</sub><sup>+</sup> and NO<sub>3</sub><sup>-</sup>, and subsequent N cycling in the soil, were considered. We found that N-induced soil acidification in 80% area of China's forests was dominated by NH<sub>x</sub> deposition, and the other areas (South China) were dominated by NO<sub>y</sub> deposition in 2010s. From 1980 to 2019, the average contribution of NHx was higher than that of NO<sub>y</sub> but the latter contribution continued to increase. Meanwhile, the results showed that soil acidification increased with the decrease of the ratio of NH<sub>x</sub> to NO<sub>y</sub> (R<sub>NHx/NOy</sub>), this is mainly because NO<sub>y</sub> is more easily leached in the form of NO<sub>3</sub><sup>-</sup> than that of NH<sub>x</sub> under the influence of different plant preferences and soil retention rates, resulting in a higher net proton production of NO<sub>y</sub>. Our research has powerful implications for policymaking, provides a theoretical basis for formulating different N reduction policies in different regions, and points out that the synergistic effect of R<sub>NHx/NOy</sub> changes should be considered to alleviate soil acidification.</span></p>
Fourier-transformed infrared (FTIR) spectra of the paper "Untangling the role of biotic and abiotic ageing of various environmental plastics toward the sorption of metals"
<p>The dataset include Fourier-transformed infrared (FTIR) spectra of UV aged and biofouled environmental plastics, used for the publication "Untangling the role of biotic and abiotic ageing of various environmental plastics toward the sorption of metals" (the paper is available at the following link: <a href="https://doi.org/10.1016/j.scitotenv.2023.164807">https://doi.org/10.1016/j.scitotenv.2023.164807</a>).</p> <p>The dataset is organized as follows:</p> <p>-All samples contains metadata considering polymer type (polylactic acid (PLA), polypropylene (PP), and polyethylene (PE)), the type of ageing treatment (UV ageing, biofouling and UV ageing-biofouling), the amount of time (in hours) of treatment and the number of replicate sample analyzed.</p> <p>-for every sample the raw data (scaled for the maximum absorbance value) of the FT-IR spectrum is given.</p> <p>Further experimental details are listed in the manuscript text.</p>
A Transformer-based Function Symbol Name Inference Model from an Assembly Language for Binary Reversing
<p>This is a dataset and pre-trained model for the official implementation of <a href="https://github.com/agwaBom/AsmDepictor"><strong>AsmDepictor</strong></a>, "A Transformer-based Function Symbol Name Inference Model from an Assembly Language for Binary Reversing", In the 18th ACM Asia Conference on Computer and Communications Security <a href="https://asiaccs2023.org/">AsiaCCS '2023</a></p> <p> </p>
Scalable Bayesian divergence time estimation with ratio transformations
<div class="page"> <div class="layoutArea"> <div class="column"> <p><span>Divergence time estimation is crucial to provide temporal signals for dating bio</span><span>logically important events, from species divergence to viral transmissions in space and </span><span>time. With the advent of high-throughput sequencing, recent Bayesian phylogenetic </span><span>studies have analyzed hundreds to thousands of sequences. Such large-scale analyses</span><span> </span><span>challenge divergence time reconstruction by requiring inference on highly-correlated</span><span> </span><span>internal node heights that often become computationally infeasible. To overcome this</span><span> </span><span>limitation, we explore a ratio transformation that maps the original </span><span>N - </span><span>1 internal</span><span> </span><span>node heights into a space of one height parameter and </span><span>N - </span><span>2 ratio parameters. To</span><span> </span><span>make the analyses scalable, we develop a collection of linear-time algorithms to com</span><span>pute the gradient and Jacobian-associated terms of the log-likelihood with respect to </span><span>these ratios. We then apply Hamiltonian Monte Carlo sampling with the ratio trans</span><span>form in a Bayesian framework to learn the divergence times in four pathogenic viruses</span><span> </span><span>(West Nile virus, rabies virus, Lassa virus and Ebola virus) and the coralline red algae.</span><span> </span><span>Our method both resolves a mixing issue in the West Nile virus example and improves</span><span> </span><span>inference efficiency by at least 5-fold for the Lassa and rabies virus examples as well</span><span> </span><span>as for the algae example. Our method now also makes it computationally feasible to</span><span> </span><span>incorporate mixed-effects molecular clock models for the Ebola virus example, confirms</span><span> </span><span>the findings from the original study and reveals clearer multimodal distributions of the</span><span> </span><span>divergence times of some clades of interest.</span></p> </div> </div> </div>
Unbiased single-cell morphology with self-supervised vision transformers -- Cell Painting
<p>The data necessary to reproduce the Cell Painting results in the paper <a href="https://www.biorxiv.org/content/10.1101/2023.06.16.545359v1">Unbiased single-cell morphology with self-supervised vision transformers</a>. </p>
Unbiased single-cell morphology with self-supervised vision transformers -- HPA FOV
<p>The data necessary to reproduce the HPA FOV results in the paper <a href="https://www.biorxiv.org/content/10.1101/2023.06.16.545359v1">Unbiased single-cell morphology with self-supervised vision transformers</a>. </p>
Unbiased single-cell morphology with self-supervised vision transformers -- HPA single cells
<p>The data necessary to reproduce the HPA single cells results in the paper <a href="https://www.biorxiv.org/content/10.1101/2023.06.16.545359v1">Unbiased single-cell morphology with self-supervised vision transformers</a>. </p>
Unbiased single-cell morphology with self-supervised vision transformers -- WTC11
<p>The data necessary to reproduce the WTC11 results in the paper <a href="https://www.biorxiv.org/content/10.1101/2023.06.16.545359v1">Unbiased single-cell morphology with self-supervised vision transformers</a>. </p> <p> </p>
Hindbrain modules differentially transform activity of single collicular neurons to coordinate movements
<p>Seemingly simple behaviors such as swatting a mosquito or glancing at a signpost involve the precise coordination of multiple body parts. Neural control of coordinated movements is widely thought to entail transforming a desired overall displacement into displacements for each body part. Here we reveal a different logic implemented in the mouse gaze system. Stimulating superior colliculus (SC) elicits head movements with stereotyped displacements but eye movements with stereotyped endpoints. This is achieved by individual SC neurons whose branched axons innervate modules in medulla and pons that drive head movements with stereotyped displacements and eye movements with stereotyped endpoints, respectively. Thus, single neurons specify a mixture of endpoints and displacements for different body parts, not overall displacement, with displacements for different body parts computed at distinct anatomical stages. Our study establishes an approach for unraveling motor hierarchies and identifies a logic for coordinating movements and the resulting pose.</p>
The Moderating Effect of Employee Agility on the Link between Employee Vitality, Digital Literacy and Transformational Leadership with Job Performance: An Empirical Study of HR Practitioners in the Manufacturing Sector of Northern Malaysia.
<p>This is a dataset for a study that examines the effects of employee vitality, digital literacy, and transformational leadership on job performance. Additionally, it investigates the moderating role of employee agility in these relationships. Data were collected from HR practitioners in manufacturing companies in the northern region of Malaysia for analysis. The results indicate that the job performance of HR practitioners is positively influenced by employee vitality, digital literacy and transformational leadership. </p>
Surface transforms (sphere.reg) computed with FreeSurfer 6 for all ABIDE I subjects
<p># ABIDE I FreeSurfer 6 'surface transforms' data</p> <p><br> This archive contains files needed to map surface-based subject data to other subjects, templates or spaces.</p> <p><br> ## Credits</p> <p>This data is derived from the MRI scans of the ABIDE I dataset:</p> <p>* ABIDE I dataset: https://fcon_1000.projects.nitrc.org/indi/abide/</p> <p>Quoting from that website:</p> <p> "The Autism Brain Imaging Data Exchange I (ABIDE I) represents the first<br> ABIDE initiative. Started as a grass roots effort, ABIDE I involved 17<br> international sites, sharing previously collected resting state functional<br> magnetic resonance imaging (R-fMRI), anatomical and phenotypic datasets<br> made available for data sharing with the broader scientific community.<br> This effort yielded 1112 dataset, including 539 from individuals with<br> ASD and 573 from typical controls (ages 7-64 years, median 14.7 years<br> across groups). This aggregate was released in August 2012. Its<br> establishment demonstrated the feasibility of aggregating resting<br> state fMRI and structural MRI data across sites; the rate of these<br> data use and resulting publications (see Manuscripts) have shown its<br> utility for capturing whole brain and regional properties of the brain<br> connectome in Autism Spectrum Disorder (ASD). In accordance with<br> HIPAA guidelines and 1000 Functional Connectomes Project / INDI<br> protocols, all datasets have been anonymized, with no protected<br> health information included."</p> <p>Citation: Di Martino, A., Yan, C. G., Li, Q., Denio, E., Castellanos, F. X., Alaerts, K., ... & Milham, M. P. (2014).<br> The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Molecular psychiatry, 19(6), 659-667.</p> <p>## How this data was produced</p> <p>The following steps were used to create the data:</p> <p>* We downloaded all available MRI scans for the ABIDE I subjects (1035 subjects).<br> * We pre-processed all subjects in FreeSurfer version 6 (https://freesurfer.net) by running the full recon-all pipeline for each subject.<br> - We did not run any quality metrics on the scans or exclude any subjects.</p> <p><br> ## Contained files</p> <p>* In order to reduce the size of this dataset, for each subject, we only included the following files:</p> <p> - <subject>/surf/lh.sphere.reg: spherical registration information for left hemisphere</p> <p> - <subject>/surf/rh.sphere.reg: spherical registration information for right hemisphere</p> <p>## What is NOT contained</p> <p>* The ABIDE demographics information (metadata on the subjects, like age, ...) is not included, you can get it from the ABIDE website.</p> <p>## Author and License</p> <p>Note: For the authors of the original ABIDE I dataset, see the Credits section above.</p> <p>This data was created by:</p> <p> Dr. Tim Schäfer<br> Postdoc Computational Neuroimaging<br> Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy<br> University Hospital Frankfurt, Goethe University Frankfurt am Main, Germany<br> http://rcmd.org/ts</p> <p>The data is published under the following license:</p> <p>Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)</p> <p>See https://creativecommons.org/licenses/by-nc-sa/3.0/legalcode.txt or the file LICENSE for the full legal code.</p> <p>See https://creativecommons.org/licenses/by-nc-sa/3.0/ for an easy explanation of what this license means for you.</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.