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5,573 results for “Optimality”
Data for: Characterization, comparison, and optimization of lattice light sheets (Part 3/3)
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Data for: Characterization, comparison, and optimization of lattice light sheets (Part 2/3)
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Data for: Characterization, comparison, and optimization of lattice light sheets (Part 1/3)
Open the record for dataset details and reuse information.
Tandem Tag Assay Optimized for Semi-automated in vivo Autophagic Activity Measurement in Arabidopsis thaliana roots
<p>This is demo data set for AuTToFlux, the semi-automated assay for <em>in vivo</em> autophagic activity measurement in <em>Arabidopsis thaliana</em> roots.</p> <p>The protocol and software required for the assay are available here: <a href="https://github.com/jonasoh/AuTToFlux">https://github.com/jonasoh/AuTToFlux</a></p>
BIDS Data for "An Optimized Registration Workflow and Standard Geometric Space for Small Animal Brain Imaging"
<p>Base data package for the “An Optimized Registration Workflow and Standard Geometric Space for Small Animal Brain Imaging” article, formatted corresponding to the Brain Imaging Data Structure.</p>
Data to "Near-optimal combination of disparity across a log-polar scaled visual field"
<p>This record contains experimental and analysis scripts (written in Matlab) as well as raw and processed data to reproduce the results shown in:</p> <p>Maiello, G., Chessa, M., Bex, P. J., & Solari, F. (2020) Near-optimal combination of disparity across a log-polar scaled visual field. <em>PLOS Computational Biology, 16</em>(4), e1007699. <a href="https://doi.org/10.1371/journal.pcbi.1007699">https://doi.org/10.1371/journal.pcbi.1007699</a></p>
SHYFEM set-up for model driven optimization of the tide gauge monitoring network in the Venice Lagoon
<p>This database include all configuration files, script and data for running the<br> simulations and elaborate the results presented in the work entitled "Model-driven<br> optimization of coastal sea observatories through data assimilation in a finite<br> element hydrodynamic model (SHYFEM v. 7_5_65)" to be submitted in Geoscientific Model<br> Development (GMD).</p>
Tagged original datasets for 'Genetically Optimized Massively Parallel Binary Neural Networks for Intrusion Detection Systems'
<p>Tagged, non-formatted, original datasets used in 'Genetically Optimized Massively Parallel Binary Neural Networks for Intrusion Detection Systems', T. Murovič, A. Trost.</p> <p>Available from the original authors:</p> <p>1. <a href="https://www.unsw.adfa.edu.au/unsw-canberra-cyber/cybersecurity/ADFA-NB15-Datasets/">https://www.unsw.adfa.edu.au/unsw-canberra-cyber/cybersecurity/ADFA-NB15-Datasets/</a> (UNWS-NB15 dataset)</p> <p>2. <a href="https://www.unb.ca/cic/datasets/nsl.html">https://www.unb.ca/cic/datasets/nsl.html</a> (NSL-KDD dataset)</p>
Optimal resource allocation and prolonged dormancy strategies in herbaceous plants
<p>1. Understanding the fitness consequences of different life histories is critical for explaining their diversity and for predicting effects of changing environmental conditions. However, current theory on plant life histories relies on phenomenological, rather than mechanistic, models of resource production.</p> <p>2. We combined a well-supported mechanistic model of ontogenetic growth that incorporates differences in the size-dependent scaling of gross resource production and maintenance costs with a dynamic optimization model to predict schedules of reproduction and prolonged dormancy (plants staying below ground for ≥ 1 growing season) that maximize lifetime offspring production.</p> <p>3. Our model makes three novel predictions: First, maintenance costs strongly influence the conditions under which a monocarpic or polycarpic life history evolves and how resources should be allocated to reproduction by polycarpic plants. Second, in contrast to previous theory, our model allows plants to compensate for low survival conditions by allocating a larger proportion of resources to storage and thereby improving overwinter survival. Incorporating this ecological mechanism in the model is critically important because without it our model never predicts significant investment into storage, which is inconsistent with empirical observations. Third, our model predicts that prolonged dormancy may evolve solely in response to resource allocation tradeoffs.</p> <p>4. Significance: Our findings reveal that maintenance costs and the effects of resource allocation on survival are primary determinants of the fitness consequences of different life history strategies, yet previous theory on plant life history evolution has largely ignored these factors. Our findings also validate recent arguments that prolonged dormancy may be an optimal response to costs of sprouting. These findings have broad implications for understanding patterns of plant life history variation and predicting plant responses to changing environments.</p>
Data from: Assessing support for Blaberoidea phylogeny suggests optimal locus
<p>Phylogenomics seeks to use next-generation data to robustly infer an organism's evolutionary history. Yet, the practical caveats of phylogenomics motivates investigation of improved efficiency, particularly when quality of phylogenies are questionable. To achieve improvements, one goal is to maintain or enhance the quality of phylogenetic inference while severely reducing dataset size. We approach this by assessing which kinds of loci in phylogenomic alignments provide the majority of support for a phylogenetic inference of cockroaches in Blaberoidea. We examine locus substitution rate, saturation, evolutionary divergence, rate heterogeneity, stabilizing selection, and<i> a priori</i> information content as traits that may determine optimality. Our controlled experimental design is based on 265 loci for 102 blaberoidean taxa and 22 outgroup species. Loci with high substitution rate, low saturation, low sequence distance, low rate heterogeneity, and strong stabilizing selection derive more support for phylogenetic relationships. We found that some phylogenetic information content estimators may not be meaningful for assessing information content <i>a priori</i>. We use these findings to design concatenated datasets with an optimized subsample of 100 loci. The tree inferred from the optimized subsample alignment was largely identical to that inferred from all 265 loci but with less evidence of long branch attraction, improved statistical support, and potential 4-6x improvements to computation time. Supported by phylogenetic and morphological evidence, we erect three newly named clades (Anallactinae Evangelista & Wipfler <i>subfam. nov.,</i> Orkrasomeria <i>tax. nov. </i>Evangelista, Wipfler, & Béthoux, and Hemithyrsocerini Evangelista <i>tribe nov</i>.) and propose other taxonomic modifications. The diagnosis of Pseudophyllodromiidae Grandcolas, 1996 is modified to accommodate Anallactinae and Pseudophyllodromiinae Vickery & Kevan, 1983. The diagnosis of<i> </i>Ectobiidae Brunner von Wattenwyl, 1865 is modified to add novel morphological characters.</p>
Data from: Optimizing enrichment of deadwood for biodiversity by varying sun exposure and tree species: an experimental approach
<p>1. The enrichment of deadwood is essential for the conservation of saproxylic biodiversity in managed forests. However, existing strategies focus on a cost-intensive increase of deadwood amount, while largely neglecting increasing deadwood diversity.</p> <p>2. Deadwood objects, i.e. logs and branches, from six tree species were experimentally sun-exposed, canopy-shaded, and artificially shaded for four years, after which the alpha-, beta-, and gamma-diversity of saproxylic beetles, wood-inhabiting fungi, and spiders were analyzed. Analyses of beta-diversity included the spatial distance between exposed deadwood objects. A random-drawing procedure was used to identify the combination of tree species and sun exposure that yielded the highest gamma-diversity at a minimum of exposed deadwood amount.</p> <p>3. In sun-exposed plots, species numbers in logs were higher than in shaded plots for all taxa, while in branches we observed the opposite for saproxylic beetles. Tree species affected the species numbers only of saproxylic beetles and wood-inhabiting fungi. The beta-diversity of saproxylic beetles and wood-inhabiting-fungi among logs was influenced by sun exposure and tree species, but beta-diversity of spiders by sun exposure only. For all saproxylic taxa recorded in logs, differences between communities increased with increasing spatial distance.</p> <p>4. A combination of canopy-shaded <i>Carpinus</i> logs and sun-exposed <i>Populus</i> logs resulted in the highest species numbers of all investigated saproxylic taxa among all possible combinations of tree species and sun-exposure treatments.</p> <p>5. <i>Synthesis and applications</i>. We recommend incorporating the enrichment of different tree species and particularly the variation in sun exposure into existing strategies of deadwood enrichment. Based on the results of our study, we suggest to combine logs of softwood broadleaf tree species (e.g. <i>Carpinus, Populus</i>), hardwood broadleaf tree species (e.g. <i>Quercus</i>) and coniferous tree species (e.g. <i>Pinus</i>) under different conditions of sun exposure and distribute them spatially in a landscape to maximize the beneficial effects on overall diversity.</p>
Supplementary information to the article by van Beijnum et al. "Integrating phenotypic search and phosphoproteomic profiling of active kinases for optimization of drug mixtures for RCC treatment"
<p>Supplementary information to the article "Integrating phenotypic search and phosphoproteomic profiling of active kinases for optimization of drug mixtures for RCC treatment".</p> <p><strong>Judy R. van Beijnum<sup>1</sup>, Andrea Weiss<sup>2, 3</sup>, Robert H. Berndsen<sup>1,2 </sup>, Tse J. Wong<sup>1</sup>, Louise C. Reckman<sup>1</sup>, Sander R. Piersma<sup>4,5</sup>, Marloes Zoetemelk<sup>2,3</sup>, Richard de Haas<sup>1,4,5</sup>, Olivier Dormond<sup>6</sup>, Axel Bex<sup>7,8</sup>, Alexander A. Henneman<sup>4,5</sup>, Connie R. Jimenez<sup>4,5</sup>, Arjan W. Griffioen<sup>1</sup>, Patrycja Nowak-Sliwinska<sup>2,3,9</sup>*</strong></p> <p> </p> <p><sup>1</sup> Angiogenesis Laboratory, Department of Medical Oncology, Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Oncology, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands;</p> <p><sup>2</sup> Molecular Pharmacology Group, School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland*;</p> <p><sup>3 </sup>Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland</p> <p><sup>4 </sup>Department of Medical Oncology, Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Oncology, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands</p> <p><sup>5</sup> OncoProteomics Laboratory, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands</p> <p><sup>6</sup> Department of Visceral surgery, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland<sup> </sup> </p> <p><sup>7</sup> Royal Free London NHS Foundation Trust, Renal Cancer Centre, UCL Division of Surgical and Interventional Science, London, UK</p> <p><sup>8</sup> Netherlands Cancer Institute, Amsterdam, The Netherlands</p> <p><sup>9 </sup> Translational Research Centre in Oncohaematology, Geneva, Switzerland</p> <p> Correspondence: <a href="mailto:Patrycja.Nowak-Sliwinska@unige.ch">Patrycja.Nowak-Sliwinska@unige.ch</a></p>
OPLA-Tool v2.0: a Tool for Product Line Architecture Design Optimization
<p>The Multi-objective Optimization Approach for Product Line Architecture Design (MOA4PLA) is the seminal approach that successfully optimizes Product Line Architecture (PLA) design using search algorithms. The tool named OPLA-Tool was developed in order to automate the use of MOA4PLA. Over time, the customization of the tool to suit the needs of new research and application scenarios led to several problems. The main problems identified in the original version of OPLA-Tool are environment configuration, maintainability and usability problems, and PLA design modeling and visualization. Such problems motivated the development of a new version of this tool: OPLA-Tool v2.0, presented in this work. In this version, those problems were solved by the source code refactoring, migration to a web-based graphical user interface (GUI) and inclusion of a new support tool for PLA modeling and visualization. Furthermore, OPLA-Tool v2.0 has new functionalities, such as new objective functions, new search operators, intelligent interaction with users during the optimization process, multi-user authentication and simultaneous execution of several experiments to PLA optimization. Such a new version of OPLA-Tool is an important achievement to PLA design optimization as it provides an easier and more complete way to automate this task. </p>
YaCoS: a Complete Infrastructure to the Design and Exploration of Code Optimization Sequences
<p>The growing popularity of machine learning frameworks and algorithms has greatly contributed to the design and exploration of good code optimization sequences. Yet, in spite of this progress, mainstream compilers still provide users with only a handful of fixed optimization sequences. Finding optimization sequences that are good in general is challenging because the universe of possible sequences is potentially infinite. This paper describes a infrastructure that provides developers with the means to explore this space. Said infrastructure, henceforth called YaCoS, consists of benchmarks,search algorithms, metrics to estimate the distance between programs, and compilation strategies. YaCoS’s features let users build learning models that predict, for unknown pro-grams, optimization sequences that are likely to yield good results for them. In this paper, as a case study, we have used YaCoS to find good optimization sequences for LLVM, using code size as the objective function. Such study lets us evaluate three feature sets: two variations of the feature vectors proposed by Namolaru at al in 2010, plus the optimization statistics produced by LLVM. Our results show that YaCoSis able to find sequences that improve onto clang -Oz by3.75% on average. Our experiments do not indicate a dominant feature set out of the three approaches that we have investigated—it is possible to find programs in which one of them is strictly better than the others.</p>
Targeted Intracellular Degradation of SARS-CoV-2 via Computationally-Optimized Peptide Fusions
<p>The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has elicited a global health crisis of catastrophic proportions. With only a few vaccines approved for early or limited use, there is a critical need for effective antiviral strategies. In this study, we report a unique antiviral platform, through computational design of ACE2-derived peptides which both target the viral spike protein receptor binding domain (RBD) and recruit E3 ubiquitin ligases for subsequent intracellular degradation of SARS-CoV-2 in the proteasome. Our engineered peptide fusions demonstrate robust RBD degradation capabilities in human cells and are capable of inhibiting infection-competent viral production, thus prompting their further experimental characterization and therapeutic development. </p>
Pareto Fronts and metrics for the optimization design water distribution networks (Hanoi, Fossolo, Modena, and Balerma)
<p>Approximations to the Best-known PFs using NSGA-II retrofitted by OPUS for Hanoi, Fossolo, Modena, and Balerma, Approximations to the Best-known PFs using NSGA-II for Hanoi, Fossolo, Modena and Balerma, Hypervolume (HV) and Modified Inverted Generational Distance (IGD+) for Hanoi, Fossolo, Modena, and Balerma.</p> <ul> <li>Hanoi (30 simulations)</li> <li>Fossolo (30 simulations)</li> <li>Modena (1 simulation)</li> <li>Balerma (1 simulation)</li> </ul>
Data from: Constrained optimization of landscape indices in conservation planning to support ecological restoration in New Caledonia
<p>1. Curbing habitat loss, reducing fragmentation, and restoring connectivity are frequent concerns of conservation planning. In this respect, the incorporation of spatial constraints, fragmentation, and connectivity indices into optimization procedures is an important challenge for improving decision support.</p> <p>2. Here we present a novel optimization approach developed to accurately represent a broad range of conservation planning questions with spatial constraints and landscape indices. Relying on constraint programming, a technique from artificial intelligence based on automatic reasoning, this approach provides both constraint satisfaction and optimality guarantees.</p> <p>3. We applied this approach in a real case study to support managers of the ``Côte Oubliée -- `Woen Vùù -- Pwa Pereeù'' provincial park project, in the biodiversity hotspot of New Caledonia. Under budget, accessibility, and equitable allocation constraints, we identified restorable areas optimal for reducing forest fragmentation and improving inter-patch structural connectivity, respectively measured with the effective mesh size and the integral index of connectivity.</p> <p>4. Synthesis and applications. Our work contributes to more effective and policy-relevant conservation planning by providing a spatially-explicit and problem-focused optimization approach. By allowing an exact representation of spatial constraints and landscape indices, it can address new questions and ensure whether the solutions will be socio-economically feasible, through optimality and satisfiability guarantees. Our approach is generic and flexible, thus applicable to a wide range of conservation planning problems such as ecological restoration planning, reserve or corridor design.</p>
Development and Optimization of an IQF USP5 Activity Assay
<p>Development and optimization of a fluorescence based deubiquitinase (DUB) activity assay for USP5 with internally quenched fluorophore pair (IQF) substrates: di-ubiquitin lysine linked K48 and K63 (Ub2K48, Ub2K63). The inhibitory capability of USP5 zinc-finger ubiquitin binding domain (ZnF-UBD) ligands was investigated. </p>
Data for "Bayesian inference for biophysical neuron models enables stimulus optimization for retinal neuroprosthetics"
<p>Experimental and precomputed data for the paper "Bayesian inference for biophysical neuron models enables stimulus optimization for retinal neuroprosthetics" by Oesterle et al. 2020 (DOI: <a href="https://doi.org/10.7554/eLife.54997">10.7554/eLife.54997</a>).</p> <p>The cone bipolar cell data has been described and published in the paper "Inhibition decorrelates visual feature representations in the inner retina" by Franke et al. 2017 (DOI: <a href="https://doi.org/10.1038/nature21394">10.1038/nature21394</a>). </p> <p>This data is both a supplement to the Oesterle et al. paper and the code for this paper.</p> <p>The code is available in this <a href="http://github.com/berenslab/CBC_inference">GitHub repository</a>.</p> <p>We recommend downloading the GitHub repository and to follow the instructions there.</p>
Optimizing the Geometric Configuration and Manufacturing Process of High Mast Illumination Poles
<p>This work presents the development of a high-fidelity model that accounts for the cumulative effect of welding and hot- dip galvanizing on the determining the resulting residual stresses and deformations induced during the manufacturing process of high mast illumination poles (HMIPs). This model is meant to elucidate the root causes of weld toe cracks in HMIPs. A TxDOT pole-to-base plate connection detail was used as the reference model in the analysis. Welding was modeled using the plug-in Abaqus Welding Interface (AWI), which automatically implements a series of sequential thermal and mechanical analyses. Then, the welding stress results were used as initial input to the galvanizing analysis. The cumulative stress results were compared against simulations that only considered the galvanizing process. A parametric study was then conducted to quantify the variation in the residual stresses and equivalent plastic strain magnitudes induced during the welding and galvanizing of HMIPs due to changes in welding and galvanizing practices. The results revealed that the cumulative effects of the different processes involved in the manufacturing of HMIPs contribute to the formation of galvanizing cracks in HMIPs. Also, increasing the dipping submersion speed during galvanizing and lowering the torch temperature magnitude during welding results in fewer zones prone to cracking. Altering the angle of inclination effect did not have a significant impact on the results. Performing variations in the manufacturing practices used for the fabrication of HMIPs can contribute to reducing the extensive inspection procedures conducted post-galvanizing to identify cracks.</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.