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5,573 results for “optimality”
Test file for optimization of Zanfona
<p>.</p>
Empirical optimal localization / Vertical covariance localization
<p>Data and code / Necker et al. 2022 - "Guidance on how to improve vertical covariance localization based on a 1000-member ensemble"<br> Revised version (R2) of the code and results after reviews</p>
Greedy optimization of the geometry of Majorana Josephson junctions
<p>Code used to produce figures of "Greedy optimization of the geometry of Majorana Josephson junctions".</p>
All data support the published articel "Loop-optimization of Trichoderma reesei endoglucanases for balancing the activity–stability trade-off through cross-strategy between machine learning and the B-factor analysis"
<p><em>Trichoderma reesei</em> endoglucanases (EGs) have limited industrial applications due to its low thermostability and activity. Here, we aimed to improve the thermostability of EGs from<em> T.reesei</em> without reducing its activity counteracting the activity-stability trade-off. A cross-strategy combination of machine learning and B-factor analysis was used to predict beneficial amino acid substitution in EG loop optimization. Experimental validation showed single-site mutated EG concomitantly improved enzymatic activity and thermal properties by 17.21%–18.06% and 49.85%–62.90%, respectively, compared with wild-type EGs. Furthermore, the mechanism explained mutant variants had lower RMSD values and a more stable overall structure than the wild type. According to this study, EGs loop optimization is crucial for balancing the activity-stability trade-off, which may provide new insights into how loop region function interacts with enzymatic characteristics. Moreover, the cross-strategy between machine learning and B-factor analysis improved superior enzyme activity-stability performance, which integrated structure-dependent and sequence-dependent information.</p>
dataset for "A location and dispersion effects-based ridge analysis method using desirability functions for multi-response optimization"
<p>dataset and code for “A location and dispersion effects-based ridge analysis method using desirability functions for multi-response optimization”</p>
Data for: Fluid fermionic fragments for optimizing quantum measurements of electronic Hamiltonians in the variational quantum eigensolver
<p>Data for publication: S. Choi, I. Loaiza, and A. F. Izmaylov, "Fluid fermionic fragments for optimizing quantum measurements of electronic Hamiltonians in the variational quantum eigensolver" arXiv:2208.14490 (2022).</p> <p> </p> <p> </p>
#DeOlhoNosCorais: a polygonal annotated dataset to optimize coral monitoring
<p>The first version of the #DeOlhoNosCorais dataset was built in collaboration with the Laboratory of Marine Ecology (LECOM) at the Federal University of Rio Grande do Norte (UFRN). The dataset contains images extracted from social networks with the hashtag “#DeOlhoNosCorais” and images provided by the LECOM. It contains 1411 images and 21 classes. Each image has two labels, its major class and the segmentation map. The labeling was performed by the LECOM researchers using the Labelme tool. The duplicate images were removed using the FiftyOne tool. </p> <p>One of the objectives of the dataset is to measure the viability to use machine learning to speed up the processing of analyses of the images extracted from the Instagram. So, the extra images taken by divers from the researcher group were used to augmented the train set. The Instagram images were divided into train, validation, and test accordingly to their date. The rules for the division was:</p> <ul> <li>Train set: images dated until 12/31/2019 + extra images from LECOM-UFRN</li> <li>Validation set: images dated between 01/01/2019 to 06/30/2019</li> <li>Test set: images dated between 07/01/2019 to 08/24/2021</li> </ul> <p>The test set includes an interval of 2 years, due to the drop in the number of posts during the Covid-19 pandemic.The full dataset folder contains the raw labeling using the Labelme. The experiments folder contains treated datasets for the following tasks:</p> <ul> <li>Full images classification</li> <li>Sub images classification</li> <li>Binary semantic segmentation</li> <li>Binary object detection</li> </ul> <p>In addition, the experiments folder has an extra data from the Pacific Labeled Corals (PLC). The extra data contains 12 classes of the 20 present in the PLC, and the images patches were extracted centered in the labeled pixels with size of 224 x 224.</p>
Optimization used in in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data
<p>OptimizationResults contain the expanded input model for each data set, in the C field are the indices of the core reactions in the expanded input model used to build the multi-cell population for the 121 different parameters, A contains the indices of reaction in the multi-cell population model for the 121 runs, thresh the parameter setting for the cover and REI. The REI is given in %. So 5 REI means 0.05. While A might change because of alternative optimals when run on a different computer, C and the expanded Input model will remain unchanged.</p> <p> </p> <p>Multi_cell_population_CRC and Multi_cell_population_NM are the models obtained by scFASTCORMICS with the optimal setting for Dataset1 and Dataset2, respectively. </p> <p>Please, check the publication (scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data) for more details.</p>
Knowledge-driven design and optimization of potent symmetric anticancer molecules: A case study on PKM2 activators
<p>All the raw data files including 3D structures of all the 200 virtually designed palindromic and non-palindromic activators, 3D structures of top 5 palindromic and non-palindromic activators in complex with PKM2 protein, starting and ending conformations of MD simulation structures with the .tpr files for all six simulations for PDA116 and NPDA4 are available in this dataset.</p>
Electronic Companion -- Optimal Management of Distribution-Connected Assets Operating under Carbon and Energy Day-Ahead Markets
<p>This release is associated with a paper entitled "Optimal Management of Distribution-Connected Assets Operating under Carbon and Energy Day-Ahead Markets".</p> <p>In this document, we provide information regarding the transmission and distribution power systems adopted to present the results shown in the paper. These systems are modified versions of the IEEE <a href="https://icseg.iti.illinois.edu/ieee-14-bus-system/">14-bus</a> and the IEEE <a href="https://cmte.ieee.org/pes-testfeeders/resources/">34-bus</a>, respectively. Five dispatchable generators were added to the distribution system and 13 load shapes were considered. The data regarding the costs and physical parameters of each of the power system's elements are provided in this document.</p>
Supplementary files to the paper "Optimal Offering of Energy Storage in Electricity Markets with Loop Blocks"
<p>These files include the retrieved optimal offering decisions, corresponding to the case studies of Section IV.C of the paper Optimal Offering of Energy Storage in Electricity Markets with Loop Blocks. A README.txt file is included, describing the format of all other files.</p>
Likely accelerated weakening of AMOC emerges in optimal fingerprint
<p>POP2 source data and NCL scripts for main figures.</p>
Dataset for "Optimization and Evaluation of Stochastic Unified Convection Using Single-Column Model Simulations at Multiple Observation Sites"
<p>SCAM5 and LES outputs from "Optimization and Evaluation of Stochastic Unified Convection Using Single-Column Model Simulations at Multiple Observation Sites". Includes simulation outputs of stochastic UNICON and original UNICON. The LES intercomparison data of DYCOMSRF01 is available at https://gcss-dime.giss.nasa.gov/pub/DYCOMS-II/GCSS7-RF01/gcss7.nc, and the data of CGILS is available at http://www.atmos.washington.edu/~bloss/CGILS2data.tar.</p>
Data explanation for Manuscript "'An optimized hydroponic pipeline for large-scale identification of wheat genotypes with resilient biological nitrification inhibition (BNI) activity'"
<p>Data explanation for Manuscript "'An optimized hydroponic pipeline for large-scale identification of wheat genotypes with resilient biological nitrification inhibition (BNI) activity'"</p>
Benchmark Systems for Paper: Optimization-Based Model Order Reduction of Port-Hamiltonian Descriptor Systems
<p>Benchmark Systems for Paper: Optimization-Based Model Order Reduction of Port-Hamiltonian Descriptor Systems</p> <p>Contains:</p> <p>Index 2 Oseen Models and Index1/2 RCL circuits in port-Hamiltonian form.</p>
Multi-objective near-optimal necessary conditions for multi-sectoral planning - Dataset
<p>Dataset (input and output) of the paper 'Multi-objective near-optimal necessary conditions for multi-sectoral planning'</p>
Quantum Enhanced Greedy Solver for Optimization Problems
<p>The dataset includes the experimental data of the paper <em>Quantum-Enhanced Greedy Combinatorial Optimization Solver [<a href="https://arxiv.org/abs/2303.05509">https://arxiv.org/abs/2303.05509</a>].</em></p>
Data of optimal IBO for battery-powered OFDM transmitter
<p>Data generated by numeric calculations.</p>
DFT, potential optimization and LAMMPS MD data for BaZrO3
<p>Data generated as part of the Automated Potential Development (APD) workflow applied to BaZrO3. Includes: CASTEP DFT data, including the original molecular dynamics (MD) and also query-by-committee single-shot calculations; potential optimization jobs using MEAMfit; and LAMMPS MD simulations.</p>
Dataset and source code for the paper "Finding Near-Optimal Configurations in Colossal Product Spaces with Statistical Confidence"
<p>Dataset and source code for the paper "Finding Near-Optimal Configurations in Colossal Product Spaces with Statistical Confidence"</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.