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40 results for “design framework”
Rapid Design of Top-Performing Metal-Organic Frameworks with Qualitative Representations of Building Blocks
<p>Dataset used in the publication of Rapid Design of Top-Performing Metal-Organic Frameworks with Qualitative Representations of Building Blocks. The paper is published at <a href="https://www.nature.com/articles/s41524-023-01125-1">npj Computational Materials</a> (https://www.nature.com/articles/s41524-023-01125-1)</p> <p> </p> <p><strong>May 19, 2023:</strong></p> <p>- Updated the format in CSV files to be comma-separated.</p> <p>- Updated the building block labels.</p> <p>- Updated README.txt to include additional information.</p>
Towards a practical framework to "ethics by design" data sharing and machine learning applications
<p>Responsible AI and data-driven applications can only be developed when teams integrate the ethical principles directly into the development process. An important prerequisite is the involvement of a diverse group of stakeholders who build and are affected by AI and data systems. We present a practical framework that helps teams build trustworthy AI systems and data strategies by combining expertise and training from philosophy, law, machine learning and design.</p>
Supplementary Data for "Tuning the Redox Activity of Metal–Organic Frameworks for Enhanced, Selective O2 Binding: Design Rules and Ambient Temperature O2 Chemisorption in a Cobalt–Triazolate Framework"
<p>Supplementary dataset to support "Tuning the Redox Activity of Metal–Organic Frameworks for Enhanced, Selective O<sub>2</sub> Binding: Design Rules and Ambient Temperature O<sub>2</sub> Chemisorption in a Cobalt–Triazolate Framework"</p>
Open Data Package: Lessons Learned from Developing a Sustainability Awareness Framework for Software Engineering Using Design Science.
<p>Open Data Package for the paper: Stefanie Betz, Birgit Penzenstadler, Leticia Duboc, Ruzanna Chitchyan, Sedef Akinli Kocak, Ian Brooks, Shola Oyedeji, Jari Porras, Norbert Seyff, and Colin C. Venters. 2024. Lessons Learned from Developing a Sustainability Awareness Framework for Software Engineering Using Design Science. ACM Trans. Softw. Eng. Methodol. 24 00, JA, Article 00 (March 2024), 39 pages. https://doi.org/10.1145/3649597 25</p>
Chemical Design and Magnetic Ordering in Thin Layers of 2D Metal–Organic Frameworks (MOFs)
<p>Relevant data for publication with DOI: <a title="DOI URL" href="https://doi.org/10.1021/jacs.1c07802">10.1021/jacs.1c07802</a></p>
Multi-Scale Computational Design of Metal-Organic Frameworks for Carbon Capture Using Machine Learning and Multi-Objective Optimization
<p>This repository contains CIF files for metal-organic frameworks and Grand canonical Monte Carlo (GCMC) simulation results for the article <em>Multi-Scale Computational Design of Metal-Organic Frameworks for Carbon Capture Using Machine Learning and Multi-Objective Optimization</em> by Zijun Deng and Lev Sarkisov.</p>
Data set supplementing "A Use-Case Specific Framework for Designing Representative Vignettes (RepVig) and Evaluating Triage Accuracy of Laypeople and Symptom-Assessment Applications"
<p>This is the de-identified data set used to conduct the analyses of our study "A Use-Case Specific Framework for Designing Representative Vignettes (RepVig) and Evaluating Triage Accuracy of Laypeople and Symptom-Assessment Applications" (<a href="https://doi.org/10.1101/2024.04.02.24305193">https://doi.org/10.1101/2024.04.02.24305193</a>). The data comprises the answers to cases given by laypeople, symptom-assessment applications, and large language models and the corresponding solutions for each case. The cases were developed in the study with a focus on external validity.</p> <p>The dataset contains three datafiles: collected data for laypeople, for symptom-assessment applications, and for large language models. </p>
Digital Design and Discovery of Biological Metal-Organic Frameworks for Gas Signaling
<p>This repository contains the structures, features and compositions of Bio-hMOFs database.</p> <ol> <li>Fragments and Composition: Contains the building block fragments used to generate the Bio-hMOFs.</li> <li>Structures-CIFs: Contains the structures of Bio-hMOFs</li> <li>Geometric and RACs: Contains the geomtric and RACs features of Bio-hMOFs</li> <li>Adsorption Capacity: Contains the adsorption uptake of NO and CO adsorption simulated under 298K under 1 bar and 10 bar.</li> <li>Mechanical Properties; Computed mechanical properties</li> </ol>
Extension of Towards Large Scale Automated Algorithm Design by Integrating Modular Benchmarking Frameworks
<p>This provides the dataset and the corresponding parsing scripts that extend the "Towards Large Scale Automated Algorithm Design by Integrating Modular Benchmarking Frameworks" study.</p>
Design Principles Guided by DFT Calculations and High-Throughput Frameworks for the Discovery of New Diamond-like Chalcogenide Thermoelectric Materials
<p>Dataset of ShengBTE calculations for In2CuAgSe4 system considered in the article.</p>
Rational Design of 7-Azaindole-Based Robust Microporous Hydrogen-Bonded Organic Framework for Gas Sorption
Open the record for dataset details and reuse information.
A generic framework for hierarchical de novo protein design
<p><strong>A small MASTER database</strong> that (most of the time) will be enough for most of the design tasks. The data includes the PDB files <em>master_pdb</em>, PDS files <em>maps</em>, structure fragments <em>frags</em>, ABEG0 torsions <em>master_abego.fa.gz</em>, and secondary structure <em>master_sse.fa.gz</em>.</p>
Figure 1 in Towards a framework for invasive aquatic plant survey design in Great Lakes coastal areas
Figure 1. Great Lakes basin showing the five sites where aquatic vegetation sampling occurred. Data credits: Lakes: Great Lakes Aquatic Habitat Framework (GLAHF) Great Lakes shoreline v 1.1, 2014. Basin: Institute for Fisheries Research Great Lakes GIS basin outline GLB_basin_outline_noSLS_IFR, 2004. States/Provinces: ArcGIS Content Team U.S. States and Canada Provinces, 2010.
Figure 4 in Towards a framework for invasive aquatic plant survey design in Great Lakes coastal areas
Figure 4. The predicted richness surface (from forest classification model) showing, (A) predicted plant richness for each grid (sample unit), (B) the grids sampled with rakes (highlighted), and (C) the cells intersected with boat track during the 2019 Milwaukee survey (highlighted).
An Optimization Framework to Combine Operable Space Maximization with Design of Experiments - Data
<p>Data from figures to accompany paper</p>
Schematic representing the vehicle–to–cell hierarchical overview of a typical electrified powertrain architecture. This represents the system-level context within which the proposed layer optimisation framework has been developed. Two xEV powertrains — a) BEV and b) series PHEV — are chosen as examples to demonstrate how the methodology facilitates common module designs for such battery packs.
<p>Schematic representing the vehicle–to–cell hierarchical overview of a typical electrified powertrain architecture. This represents the<br> system-level context within which the proposed layer optimisation framework has been developed. Two xEV powertrains — a) BEV and b) series PHEV — are chosen as examples to demonstrate how the methodology facilitates common module designs for such battery packs.</p>
Exploring the Chemical Design Space of Metal-Organic Frameworks for Photocatalysis
<p>In this work, we employ a chemical insights-based diversity-driven approach to search for metal-organic framework (MOF) photocatalysts. With an in silico design based on chemical insights, we populated areas in the chemical design space related to MOFs with photocatalytic potential. We selected a balanced dataset of DFT-based photocatalytic descriptors computed for 314 MOFs, comprising our in silico structures, a diverse subset of the QMOF database, and experimental MOF photocatalysts. With such a balanced dataset, we could fine-tune supervised machine-learning models from literature that allowed us to draw insights into relevant areas in the chemical design space for photocatalysis and potential bottlenecks.<br>Among our in silico MOFs, a few motifs stood out, such as Au-pyrazolate, Ti clusters and rod-shaped metal nodes, and a particular MOF designed with the Mn4Ca cluster, which mimics the OER center in the photosystem II of photosynthesis.<br>Overall, by combining three pillars --- the design of potential MOF photocatalysts guided by chemical insights, the DFT evaluation of photocatalytic descriptors, and the machine-learning approach --- we were able to gain insights into structure-property relationship, and identify trends in the chemical design space that can open new avenues for advancing the field of photocatalysis.</p>
Calculation template for the unit-scale framework for designing step-pool sequences
<p>This is the calculation template for the manuscript titled "A unit-scale framework for designing step-pool sequences" by Chendi Zhang, Marwan A. Hassan, Matteo Saletti, André E. Zimmermann, Mengzhen Xu and Zhaoyin Wang. The design method described in the manuscript is specifically for river restoration using artificial step-pool sequence (Zhang et al., 2018, 2020; Zimmermann et al., 2020). Version 1.0 of the calculation template was applied to a total of 21 artificial step-pools built in the Maso di Spinelle River in Italy (Lenzi 2002; Lenzi and Comiti 2003; Comiti et al. 2009). A natural step-pool sequence including 20 units in the Erlenback in Switzerland (Golly et al., 2019) was used in the Version 2.0 of the template. The instructions are included in the file. With changes in the inputs, this template can also be used for other cases where design for artificial step-pools is needed. The flow competence estimation method (Richardson and Carling, 2021) has been incorporated in the Version 2.1.</p>
We Designed and Implemented the 'MASTER Framework' as a Theoretical Framework to Guide the Design and Delivery of PE and Sports.
ClinicalTrials.gov study NCT06496464. IPD Sharing: Not stated. Countries: 0. Publications: 0.
A Framework for Designing Efficient Deep Learning-Based Genomic Basecallers
<p>Trained models and basecalled reads.</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.