Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
2,235
datasets available to search
ShareScore release 0.9.0
Dataset results
2,235 results for “Engine”
Environmental, Taxonomic, and Stable Isotope Data from Aquatic Insects sampled from Beaver-Engineered Headwater Streams (Adirondack Park, NY; 2024).
This data package contains environmental and biological data from a field study examining aquatic insect assemblage composition and basal resource use in beaver-engineered headwater streams in Adirondack Park, New York. Data was collected from six streams across two watersheds; the Oswegatchie River Watershed and Upper Hudson River Watershed. Three streams were sampled within the Oswegatchie River Watershed; East Creek, Sucker Brook, and Chair Rock Creek located near the Cranberry Lake Biological Station in St. Lawrence County. Three streams were sampled from the Upper Hudson River Watershed; Big Sucker Brook, Little Sucker Brook, and Panther Brook located near SUNY ESF’s Newcomb Campus in Essex County. Site conditions were characterized using densiometer measurements of canopy cover, visual assessments of substrate composition, and river discharge measurements collected with an OTT MF Pro flow meter. Aquatic insect assemblages were sampled using multihabitat active sampling and Hester–Dendy and leaf-bag passive samplers, with specimens identified to genus and assigned to functional feeding groups. Carbon and nitrogen stable isotopes were analyzed for a subset of insect taxa and three basal resource pools; coarse particulate organic matter (CPOM), fine particulate organic matter (FPOM), and periphytic algae. The Bayesian mixing model MixSIAR was used to estimate the proportional contribution of these primary sources to aquatic insect biomass. All data was collected between June and August 2024.
Dataset of "Balancing Activity and Stability through Compositional Engineering of Ternary PtNi–Au Alloy ORR Catalysts"
<p>A systematic comparative analysis of the activity-stability relationship for compositionally tuned PtNi-Au model layers, prepared by magnetron co-sputtering, was conducted using a diverse range of complementary characterization techniques and electrochemistry, supported by density functional theory calculations. Our study reveals that progressively increasing the Au concentration in the Pt50Ni50 alloy from 3 to 15 at.% leads to opposing catalyst activity and stability trends. Specifically, we observe a decrease in ORR activity accompanied by an increase in catalyst stability, manifested in the suppression of both Pt and Ni dissolution. Despite the reduced activity compared to PtNi, the PtNi–Au alloy with 15 at.% Au still exhibits nearly three times the activity of monometallic Pt. It also demonstrates a significantly improved dissolution stability relative to the PtNi alloy and even monometallic Pt. These findings provide valuable insights into the intricate balance between activity and stability in multimetallic ORR catalysts, paving the way for the design of cost-effective and durable materials for PEMFCs.</p>
Dataset of "Strain-Engineered Ir Shell Enhances Activity and Stability of Ir-Ru Catalysts for Water Electrolysis: An Operando Wide-Angle X-Ray Scattering Study"
<p>Ir-Ru alloys with high Ru content serve as stable and highly active catalysts for the oxygen evolution reaction (OER) in Proton Exchange Membrane Water Electrolyzers (PEM-WEs), enabling efficient operation with remarkably low Ir loadings (150 µg cm-²). Despite this, the mechanisms behind their enhanced stability remain unclear. In this study, we employ operando Wide-Angle X-ray Scattering (WAXS) and complementary ex-situ techniques to investigate the structural evolution of these magnetron-sputtered alloys within a PEM-WE cell. Our results reveal that, upon potential application, Ru is leached from the surface, leading to the formation of a bimetallic Ir-Ru@IrOx core-shell structure. The Ir shell, significantly strained by the underlying Ir-Ru core, exhibits substantially higher catalytic activity than pure Ir. Notably, the Ir-Ru 25:75 catalyst shows superior stability over Ir-Ru 50:50, despite its higher Ru content, due to a more robust Ir shell that protects subsurface Ir and Ru from oxidation and dissolution. This study not only clarifies the performance-enhancing mechanisms of Ir-Ru catalysts but also suggests that other, more economical materials such as Co, Os, or Ti could serve as effective cores in Ir-M systems, offering a pathway to more cost-effective catalysts for PEM-WE applications.</p>
Nucleation-Limited Kinetics of GaAs Nanostructures Grown by Selective Area Epitaxy: Implications for Shape Engineering in Optoelectronics Devices
<p>This dataset corresponds to the following manuscript: </p> <p>Zendrini, M., Dubrovskii, V., Rudra, A., Dede, D., Fontcuberta i Morral, A., Piazza, V. “Nucleation-Limited Kinetics of GaAs Nanostructures Grown by Selective Area Epitaxy: Implications for Shape Engineering in Optoelectronics Devices” <em>ACS Applied Nano Materials 7,16 (2024):</em> 19065–19074</p> <p>DOI: <a href="http://doi.org/10.1021/acsanm.4c02765">doi.org/10.1021/acsanm.4c02765</a></p> <p>The dataset contains raw SEM images in .tif format for all the arrays of nanowires and nanomembranes discussed in the paper. The dataset also contains the AFM scans in .xyz format for all the arrays of nanowires and nanomembranes. The data for the morphological analysis are extracted from the SEM images and the AFM scans and they are collected in two separate .txt files for NWs and NMs.</p>
Raw data to accompany the manuscript 'Data for Engineering Lipid Metabolism of Chinese Hamster Ovary (CHO) Cells for Enhanced Recombinant Protein Production' published in the Journal Data in Brief
<p>This repository consists of the raw western blot, microscopy and mass spectrometry data to accompany the manuscript 'Data for Engineering Lipid Metabolism of Chinese Hamster Ovary (CHO) Cells for Enhanced Recombinant Protein Production' published in the Journal Data in Brief and associated with the article '<a href="https://www.ncbi.nlm.nih.gov/pubmed/31805379">Engineering of Chinese hamster ovary cell lipid metabolism results in an expanded ER and enhanced recombinant biotherapeutic protein production</a>' published in the journal Metabolic Engineering (see DOI: 10.1016/j.ymben.2019.11.007). </p> <p>The western blot raw file is associated with Figure 1a and 1b of the Data in Brief manuscript.</p> <p>The confocal microscopy raw image files (x3) are associated with Figure 1c of the Data in Brief manuscript.</p> <p>The mass spectrometry files are the raw data that refers to the samples presented in Figure 5 of the Data in Brief manuscript. Files are labelled as in the Data in Brief and Metabolic Engineering manuscripts. The file name structures is as follows;</p> <p>CHO-Controlpoolai</p> <p>Where 'a' represents replicate 'a' of three biological replicates and 'i' refers to mass spectrometry technical analysis 1 of 3 technical analyses of each replicate (thus for each cell pool or line there are three biological replicates that are each analysed in triplicate such that there are 9 raw mass spectrometry files for each cell pool or line).</p> <p>All the mass spectrometry files are found in the compressed (zip) file named mass_spectrometry_raw_files_archive.zip</p>
Augmented emission maps: the 1461 cc 81 kW Euro 6 diesel engine: update 1
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 1461 cc 81 kW Euro 6 diesel engine that has been applied in the several Renault, Nissan and Mercedes-Benz models (Kadjar, Megane, Scenic, Talisman, Captur, Clio, Kangoo; Qashqai, Juke, Pulsar, NV200; Citan).</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI 10.5281/zenodo refers to a meta-data document that provides the full description of the standardized emission map.</p>
Histological Dataset for Microvascular Segmentation of Tissue-Engineered Vascular Grafts
<p><strong>Objectives: </strong>The pursuit of understanding vascular tissue regeneration within tissue-engineered vascular grafts (TEVGs) is of paramount importance due to the critical role these grafts play in replacing damaged or diseased blood vessels. TEVGs offer a promising alternative to traditional grafts, with the potential to integrate into the host's tissue and support the natural regenerative processes. However, challenges such as thrombosis, inflammation, and the need for grafts that can adapt to the dynamic biological environment remain. By studying the regenerative processes in TEVGs, researchers can gain insights into the mechanisms that underpin successful graft integration and function, which is essential for improving patient outcomes in vascular surgeries. This dataset, with its detailed annotations of histological features, provides a valuable resource for developing and refining machine-learning models that can analyze and predict patterns of vascular tissue regeneration. The ability to accurately segment and quantify microvessels and immune cells in regenerated arteries is a significant step forward in distinguishing between physiological and pathological regeneration, ultimately contributing to the design of more effective and reliable TEVGs for clinical use.</p> <p><strong>Ethical Approval: </strong>Experimental strategy of the study is described in detail in <a href="https://www.mdpi.com/2073-4360/14/23/5149" target="_blank" rel="noopener">[1]</a> and <a href="https://www.mdpi.com/1422-0067/24/10/8540" target="_blank" rel="noopener">[2]</a>. The study was conducted according to the guidelines of the Declaration of Helsinki, and was approved by the Local Ethical Committee of the Research Institute for Complex Issues of Cardiovascular Diseases (Kemerovo, Russia, protocol code 2020/06, date of approval: 19 February 2020). Animal experiments were performed in accordance with the European Convention for the Protection of Vertebrate Animals (Strasbourg, 1986) and Directive 2010/63/EU of the European Parliament on the protection of animals used for scientific purposes. For the implantation, we used female Edilbay sheep of 42–45 kg body weight which were received from the Animal Core Facility of the Research Institute for Complex Issues of Cardiovascular Diseases (Kemerovo, Russia) and selected for the surgery by Doppler ultrasonography to identify those having carotid artery diameter of 4.0 ± 0.2 mm.</p> <p><strong>Description: </strong>The dataset comprises a collection of Whole Slide Images (WSIs) obtained from biodegradable TEVGs implanted into the carotid arteries of 20 sheep. A total of 104 WSIs were acquired, each measuring an average size of 135,000 x 123,000 pixels. These WSIs were stained using Hematoxylin and Eosin (H&E), a common practice for highlighting the structure of tissue sections, which facilitates the detailed examination of histological features. These WSIs were automatically sliced into 99,831 patches of 3,000 x 3,000 pixels and subsequently filtered, resulting in 1,401 selected patches for manual annotation.</p> <p><strong>Annotation Method:</strong> Two pathologists independently selected and meticulously annotated the 1401 patches, identifying nine distinct histological features associated with vascular tissue regeneration. These features include <em>arteriole lumen (AL)</em>, <em>arteriole media (AM)</em>, <em>arteriole adventitia (AA)</em>, <em>venule lumen (VL)</em>, <em>venule wall (VW)</em>, <em>capillary lumen (CL)</em>, <em>capillary wall (CW)</em>, <em>immune cells (IC)</em>, and <em>nerve trunks (NT)</em>. The annotations were performed using binary masks, delineating each feature within the patches. Subsequently, a senior pathologist conducted a triple verification process, reviewing and refining the annotations to ensure accuracy and consistency. The annotations are provided in the form of binary masks, meticulously defined for each feature within the patches.</p> <p><strong>Dataset Split:</strong> Given the limited number of subjects studied, comprising 20 sheep, we employed a 5-fold cross-validation technique to split our dataset. This method was chosen because it allows for the efficient use of limited data, ensuring that each observation has the opportunity to be used in both the training and testing sets, thus reducing bias and providing a more accurate estimate of the model's performance. In this approach, each fold involved 16 sheep for training and the remaining 4 for testing (see <em>Table 1</em> and <em>Figure 3</em>). This partitioning scheme was consistently applied to maintain the integrity of subject groups within each subset and to prevent data leakage. The 5-fold cross-validation is particularly beneficial for our study's objectives as it maximizes the training data available for developing robust machine learning models while also ensuring that the models are tested on unseen data, thereby enhancing the generalizability of our findings.</p> <p><strong>Access to the Study:</strong> Further information about this study, including curated source code, dataset details, and trained models, can be accessed through the following repositories:</p> <ul> <li><strong>Source code:</strong> <a href="https://github.com/ViacheslavDanilov/histology_segmentation" target="_blank" rel="noopener">https://github.com/ViacheslavDanilov/histology_segmentation</a></li> <li><strong>Dataset:</strong> <a href="https://doi.org/10.5281/zenodo.10838384" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10838384</a></li> <li><strong>Models:</strong> <a href="https://doi.org/10.5281/zenodo.10838431" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10838431</a></li> </ul> <div> </div> <div><em><strong>Table 1.</strong> Patch and feature distributions across folds and subsets</em> <table> <tbody> <tr> <td> <p><strong>Fold</strong></p> </td> <td> <p><strong>Subset</strong></p> </td> <td> <p><strong>Patches</strong></p> </td> <td> <p><strong>AL</strong></p> </td> <td> <p><strong>AM</strong></p> </td> <td> <p><strong>AA</strong></p> </td> <td> <p><strong>VL</strong></p> </td> <td> <p><strong>VW</strong></p> </td> <td> <p><strong>CL</strong></p> </td> <td> <p><strong>CW</strong></p> </td> <td> <p><strong>IC</strong></p> </td> <td> <p><strong>NT</strong></p> </td> <td> <p><strong>Total </strong></p> </td> </tr> <tr> <td> <p>1</p> </td> <td> <p>Train</p> </td> <td> <p>1168</p> </td> <td> <p>510</p> </td> <td> <p>512</p> </td> <td> <p>220</p> </td> <td> <p>675</p> </td> <td> <p>648</p> </td> <td> <p>770</p> </td> <td> <p>765</p> </td> <td> <p>409</p> </td> <td> <p>448</p> </td> <td> <p>4957</p> </td> </tr> <tr> <td>1</td> <td> <p>Test</p> </td> <td> <p>233</p> </td> <td> <p>81</p> </td> <td> <p>84</p> </td> <td> <p>36</p> </td> <td> <p>186</p> </td> <td> <p>169</p> </td> <td> <p>178</p> </td> <td> <p>182</p> </td> <td> <p>91</p> </td> <td> <p>25</p> </td> <td> <p>1032</p> </td> </tr> <tr> <td> <p>2</p> </td> <td> <p>Train</p> </td> <td> <p>1053</p> </td> <td> <p>406</p> </td> <td> <p>411</p> </td> <td> <p>179</p> </td> <td> <p>678</p> </td> <td> <p>638</p> </td> <td> <p>743</p> </td> <td> <p>746</p> </td> <td> <p>423</p> </td> <td> <p>315</p> </td> <td> <p>4539</p> </td> </tr> <tr> <td>2</td> <td> <p>Test</p> </td> <td> <p>348</p> </td> <td> <p>185</p> </td> <td> <p>185</p> </td> <td> <p>77</p> </td> <td> <p>183</p> </td> <td> <p>179</p> </td> <td> <p>205</p> </td> <td> <p>201</p> </td> <td> <p>77</p> </td> <td> <p>158</p> </td> <td> <p>1450</p> </td> </tr> <tr> <td> <p>3</p> </td> <td> <p>Train</p> </td> <td> <p>1127</p> </td> <td> <p>507</p> </td> <td> <p>511</p> </td> <td> <p>222</p> </td> <td> <p>743</p> </td> <td> <p>702</p> </td> <td> <p>759</p> </td> <td> <p>760</p> </td> <td> <p>299</p> </td> <td> <p>423</p> </td> <td> <p>4926</p> </td> </tr> <tr> <td>3</td> <td> <p>Test</p> </td> <td> <p>274</p> </td> <td> <p>84</p> </td> <td> <p>85</p> </td> <td> <p>34</p> </td> <td> <p>118</p> </td> <td> <p>115</p> </td> <td> <p>189</p> </td> <td> <p>187</p> </td> <td> <p>201</p> </td> <td> <p>50</p> </td> <td> <p>1063</p> </td> </tr> <tr> <td> <p>4</p> </td> <td> <p>Train</p> </td> <td> <p>1064</p> </td> <td> <p>466</p> </td> <td> <p>472</p> </td> <td> <p>199</p> </td> <td> <p>611</p> </td> <td> <p>566</p> </td> <td> <p>759</p> </td> <td> <p>758</p> </td> <td> <p>423</p> </td> <td> <p>291</p> </td> <td> <p>4545</p> </td> </tr> <tr> <td>4</td> <td> <p>Test</p> </td> <td> <p>337</p> </td> <td> <p>125</p> </td> <td> <p>124</p> </td> <td> <p>57</p> </td> <td> <p>250</p> </td> <td> <p>251</p> </td> <td> <p>189</p> </td> <td> <p>189</p> </td> <td> <p>77</p> </td> <td> <p>182</p> </td> <td> <p>1444</p> </td> </tr> <tr> <td> <p>5</p> </td> <td> <p>Train</p> </td> <td> <p>1192</p> </td> <td> <p>475</p> </td> <td> <p>478</p> </td> <td> <p>204</p> </td> <td> <p>737</p> </td> <td> <p>714</p> </td> <td> <p>761</p> </td> <td> <p>759</p> </td> <td> <p>446</p> </td> <td> <p>415</p> </td> <td> <p>4989</p> </td> </tr> <tr> <td>5</td> <td> <p>Test</p> </td> <td> <p>209</p> </td> <td> <p>116</p> </td> <td> <p>118</p> </td> <td> <p>52</p> </td> <td> <p>124</p> </td> <td> <p>103</p> </td> <td> <p>187</p> </td> <td> <p>188</p> </td> <td> <p>54</p> </td> <td> <p>58</p> </td> <td> <p>1000</p> </td> </tr> </tbody> </table> </div> <p> </p>
Dataset of the paper "Control of electronic band profiles through depletion layer engineering in core-shell nanocrystals"
<p>This dataset provides the raw data of the paper "Control of electronic band profiles through depletion layer engineering in core-shell nanocrystals"</p>
Données supplémentaires: Repérage automatisé de l'hyponymie dans des corpus spécialisés en français à l'aide de Sketch Engine
<p>Ces figures sont des données supplémentaires de l'article suivant :<br> San Martín A., Trekker C., et León-Araúz P. 2022. Repérage automatisé de l’hyponymie dans des corpus spécialisés en français à l’aide de Sketch Engine. <em>Terminology</em>. doi: 10.1075/term.20044.san</p> <p>Les figures suivantes représentent le résultat complet de l’évaluation des WS. La première colonne représente le terme évalué (c’est-à-dire les termes de recherche) et les trois colonnes suivantes, les trois premiers résultats. Enfin, les colonnes suivantes représentent visuellement la précision de chaque paire, le chiffre à gauche étant le nombre de vrais positifs et celui à droite, le nombre de correspondances associées à la paire. La couleur bleue représente les résultats de la colonne <em>X est le générique de...</em> et la couleur jaune, les résultats de la colonne <em>X est un type de...</em></p> <ul> <li>psychologie.tif: Évaluation des WS du sous-corpus de psychologie</li> <li>chimie.tif: Évaluation des WS du sous-corpus de chimie</li> <li>droit.tif: Évaluation des WS du sous-corpus de droit</li> <li>informatique.tif: Évaluation des WS du sous-corpus d’informatique</li> <li>geographie.tif: Évaluation des WS du sous-corpus de géographie</li> </ul>
Dataset for "Large Language Models as molecular design engines"
<ol> <li><strong>claude-gpt-paper.zip :</strong><br><br>This dataset contains data and results associated with the paper "Large Language Models as molecular design<br>engines" The paper investigates the use of large language models, specifically Claude 3 Opus, for generating and analyzing chemical structures based on various prompts from A-H (as mentioned in the manuscript), and guided design related to electron-withdrawing groups (EWG), electron-donating groups (EDG).</li> </ol> <p>The dataset includes:</p> <ol> <li>PM7 MOPAC energy calculations for generated molecules, along with their SMILES representations and molecule IDs.</li> <li>PM7-calculated charges for the generated molecules.</li> <li>Output files from the Claude 3 Opus language model for each prompt category along.</li> <li>Original dataset (subset of ZINC database) used to build common keys and the initial design space.</li> <li>JSON file containing common keys for featurizing unknown SMILES.</li> <li>PCA object to convert molecule embeddings to 3-dimensional embeddings.</li> </ol> <p>The data is organized into the following folders:</p> <ul> <li><code>pm7_charge_results</code>: Contains HOMO-LUMO energy differences for plotting.</li> <li><code>pm7_charge_calculation</code>: Contains PM7 MOPAC energy calculations and charges.</li> <li><code>out</code>: Contains output files from the Claude 3 Opus language model.</li> <li><code>fact-dropbox</code>: Contains the original dataset, common keys, and PCA object file.</li> </ul> <p>The data can be used to reproduce the results presented in the paper and serve as a foundation for further research in this area.</p> <p>For a detailed description of the folder structure and contents, please refer to the File_descriptions.md file included in the dataset.<br><br><br>2. llm-visulizer-dashapp.zip<br><br>This is the code for the visualizer app for viewing the molecules generated by the LLM. The README.md file has details about running the app.</p> <p>3. claude-gpt-paper-codes.zip </p> <p>This contains the notebook GPT_modification_just_plots.ipynb for plotting, and other codes. The README.md file has details about running the main notebook for getting the plots.</p>
Data of the article Analysis of the self-archiving policies of journals in the highest rank category of the Finnish journal classification system within computer science, physics and electronic engineering
<p>The publication forum level three journals representing the three fields of science of computer science, computer science and electrical engineering were identified by utilizing the MinEdu field search filter while searching for the top-ranked journals from the publication channel search (https://www.tsv.fi/julkaisufoorumi/haku.php?lang=en), which is based on Field of Science, Statistics Finland classification (https://www.stat.fi/meta/luokitukset/tieteenala/001-2010/index_en.html). The data were extracted during august 2017 consists of total of 127 individual journals. It is worth noting that circa 30 journals were classified into more than one fields of sciences under scrutiny. First, the journals were divided into representing gold and hybrid model journals. Second, green open access policies of the identified hybrid journals were analyzed using Laakso’s (2014) publisher policy coding framework. Also publishers of the individual journals were identified and subsequently added to the data.</p> <p>NOTE! The data includes the shortest embargo to either institutional or subject repositories. For example, Elsevier had no embargo to opening accepted manuscripts from arXiv subject repository and thus no embargoes to Elsevier's journals are included within this datasheet.</p> <p>Data is in CSV. format</p> <p> </p> <p> </p>
DPMFA_EU_ENM_2000-2020: Dynamic Probabilistic Material Flows of Engineered Nanomaterials from 2000 to 2020 - Raw results
<p>This dataset is related to the following publication:</p> <p>Title: Dynamic probabilistic material flow analysis of engineered nanomaterials in European waste treatment systems</p> <p>Authors: Sana Rajkovic, Nikolaus A. Bornhöf<span>t</span>, Renata van der Weijden, Bernd Nowack, Véronique Adam</p> <p>Submitted to the journal Waste Management in September 2019.</p> <p>The files contain key values of probability distributions associated with the emissions of selected engineered nanomaterials to the environment.</p>
SolarSMART Engineering Perceptions 2019 Study
<p>SolarSMART Engineering Perceptions 2019 Study dataset provides results from a perception analysis with 42 Engineering students from an advanced Energy Technologies course at the University of Georgia regarding their perceptions of consumer adoption behaviors of multiple clean and renewable energy technologies. The dataset includes the following: demographic information for each participant, draw-a-map responses for their perceptions of where consumers adopt and do not adopt renewable and clean energy technologies (e.g., bioenergy, geothermal, solar, wave, and wind). Respondents were also asked questions about their intended plans after graduation, as well as what coursework they took as part of their studies that was not STEM in nature. </p>
ValRun: GMP-grade Manufacturing and Quality Control of a Non-Virally engineered Advanced Therapy Medicinal Product for Personalized Treatment of Age-Related Macular Degeneration
<p><strong>VaLRun: </strong></p> <p><strong>Raw data of "GMP-grade Manufacturing and Quality Control of a Non-Virally engineered Advanced Therapy Medicinal Product for Personalized Treatment of Age-Related Macular Degeneration"</strong></p> <p>(Excel-, pdf-, GraphPad-files, mp4 videos and a READ-ME text file)</p> <p>The introduction of new therapeutics requires validation of Good Manufacturing Practice (GMP)-grade manufacturing including suitable quality controls. This is challenging for Advanced Therapy Medicinal Products (ATMP) with personalized batches. We have developed a person-alized, cell-based gene therapy to treat age-related macular degeneration and established a vali-dation strategy of the GMP-grade manufacture for the ATMP; manufacturing and quality control were challenging due to a low cell number, batch-to-batch variability and short production duration. Instead of patient iris pigment epithelial cells, human donor tissue was used to produce the transfected cell product (“tIPE”). We implemented an extended validation of 104 tIPE productions. Procedure, operators and devices have been validated and qualified by determining cell number, viability, extracellular DNA, sterility, duration, temperature and volume. Transfected autologous cells were transplanted to rabbits verifying feasibility of the treatment. A container has been engineered to insure a safe transport from the production to the surgery site. Criteria for successful validation and qualification were based on tIPE’s Critical Quality Attributes and Process Parameters, its manufacture and release criteria. The validated process and qualified operators are essential to bring the ATMP into clinic and offer a general strategy for the transfer to other manufacture centers and personalized ATMPs.</p>
The Role of Informal Communication in Building Shared Understanding of Non-Functional Requirements in Remote Continuous Software Engineering
<p><strong>Study Information</strong></p> <p>We conducted an ethnography-informed case study of a remote software organization that adopts CSE practices to explore how the organization builds a shared understanding of NFRs. Our study uses semi-structured interviews with a period of observations to answer the following research questions:</p> <p> </p> <ol> <li> <p>How does a remote software organization that adopts CSE practices reach a shared understanding of NFRs?</p> </li> <li> <p>What are the limitations to the shared understanding of NFRs in a remote software organization that adopts CSE practices?</p> </li> <li> <p>What organizational practices for remote collaboration supported a shared understanding of NFRs?</p> </li> </ol> <p> </p> <p>In our study, we refer to our partner organization as Alpha. We used ethnography-informed methods to study Alpha's practices and processes and how they approach a shared understanding of NFRs in their product development. </p> <p> </p> <p><strong>Data Analysis</strong></p> <p>We performed a qualitative study through semi-structured interviews and observations. We use the open, axial and selective coding approach from grounded theory [1] to create our codebook, which informed the results and discussion of our study. Two independent coders held agreement sessions to discuss the codes, consolidate the codes and calculate the inter-rater reliability using the Cohen Kappa's coefficient for measuring observer agreement for categorical data [2]. </p> <p> </p> <p><strong>Artifact Descriptions</strong></p> <p>Our replication package contains three artifacts:</p> <p>1. Codebook.csv: The codebook contains rows for the list of codes used, including the code name and the description of the codes. The codes are the final set of themes derived during the thematic analysis of the interview responses. For example, 'Gaps in communication' means when interview participants describe miscommunications due to team members making assumptions about a project/process or having unclear expectations for a project.</p> <p>2. kappa-scores.csv: This contains the associated kappa values for each round of inter-rater agreement sessions. For each agreement session, the Cohen Kappa's coefficient was calculated from the number of agreements and disagreements of codes within one or two interview transcripts. The Kappa values represent the level of agreement ranging from 0 to 1, where > 0.6 represents substantial agreement. </p> <p>3. Interview-questions.csv: This contains the interview questions used in the semi-structured interviews. Some of the interview questions varied depending on the interviewee’s role, experience and the flow of the interviews.</p> <p><strong> </strong></p> <p><strong>Usefulness</strong></p> <p>We recognize that the value and usefulness of our replication package are yet-to-be-determined. In the interest of transparency of open science, we published our artifacts. We hope that these artifacts are useful to either replicate our findings or to further analyze them to produce other enlightening results.</p> <p><strong> </strong></p> <p><strong>References</strong></p> <p>1. Rashina Hoda, James Noble, and Stuart Marshall. "Grounded theory for geeks". In: Proceedings of the 18th conference on pattern languages of programs. 2011, pp. 1–17.</p> <p>2. J Richard Landis and Gary G Koch. "The measurement of observer agreement for categorical data". In: biometrics (1977), pp. 159–174.</p> <p><strong> </strong></p> <p> </p>
Modulation Engineering: Stimulation Design for Enhanced Kinetic Information from Modulation-Excitation Experiments on Catalytic Systems
<p>Dataset used in the publication "Modulation Engineering: Stimulation Design for Enhanced Kinetic Information from Modulation-Excitation Experiments on Catalytic Systems" (<a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.1021%2Facscatal.3c00646&data=05%7C01%7CValentijn.DeCoster%40UGent.be%7C2a7a2c81f646405654d308db2f58f8ec%7Cd7811cdeecef496c8f91a1786241b99c%7C1%7C0%7C638155831400735344%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=e%2Fyp50KsegsMtKcY9ijwh3AqUbrsxFLo%2BTXyGmzOLps%3D&reserved=0">https://doi.org/10.1021/acscatal.3c00646</a>).<br> A description document ("Data overview.docx") is included and provides an overview of the dataset.</p>
Replication Data for: "Ocean acidification increases susceptibility to sub-zero air temperatures in ecosystem engineers and limit poleward range shifts"
<p>These datasets contain all the raw data needed to replicate the results from our paper <em>Ocean acidification increases susceptibility to sub-zero air temperatures in ecosystem engineers and limit poleward range shifts</em> published in eLife - <a href="https://doi.org/10.7554/eLife.81080">https://doi.org/10.7554/eLife.81080</a></p>
Dataset for Broadband three-mode converter and multiplexer based on cascaded symmetric Y-junctions and subwavelength engineered MMI and phase shifters
<p>This dataset contains the raw data for the figures (Fig. 5, Fig. 6 and Fig. 7) in the publication entitled "Broadband three-mode converter and multiplexer based on cascaded symmetric Y-junctions and subwavelength engineered MMI and phase shifters" published by Optics and Laser Technology (DOI: 10.1016/j.optlastec.2023.109513). Datafiles are in .txt format.</p> <p>All relevant information regarding the dataset, how it was obtained and its context is contained in the manuscript. </p>
Data set for the journal article: Site-Specific Protein Ubiquitylation Using an Engineered, Chimeric E1 Activating Enzyme and E2 SUMO Conjugating Enzyme Ubc9
<p>Mutations observed in evolved chimeric E1 variants. Top row (1.X to 4.X) describes rounds of evolutions with respective variants in the round. </p> <p>Residues that appear to be enriched are highlighted with gray fill. Star (★) marks residues subjected to saturation mutagenesis in the round 4.</p>
Bibliographic Data from the SoTL in Civil and Structural Engineering Systematic Review
<p>This database contains all the bibliographic information found after applying the Search Strategy used for the SoTL in Civil and Structural Engineering Systematic Review. The following electronic databases were searched:</p> <ul> <li>Scopus.</li> <li>Web of Science.</li> <li>OsloMet Library.</li> <li>Google Scholar (no bibliographic information is presented since this database does not allow to download such data).</li> </ul> <p>A total of 84 records were found in Scopus, 43 in Web of Science, and 55 in OsloMet Library. The search was conducted on September 1, 2023.</p> <p>The information is presented in .ris, .bib, and .csv format.</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.