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5,573 results for “Optimality”
Optimal Catastrophe Risk Pooling
<p>This repository contains the code to reproduce the analysis in the paper: "Increasing countries’ financial resilience through global catastrophe risk pooling" from Ciullo et al..</p>
Datasets for Application of particle swarm optimization to understand the mechanism of action of allosteric inhibitors of the enzyme HSD17ß13
<p>Datasets used in the publication '</p> <p>Application of particle swarm optimization to understand the</p> <p>mechanism of action of allosteric inhibitors of the enzyme HSD17ß13'</p>
Data for: Optimal inference of molecular interaction dynamics in FRET microscopy
<p>Intensity-based time-lapse fluorescence resonance energy transfer (FRET) microscopy has been a major tool for investigating cellular processes, converting otherwise unobservable molecular interactions into fluorescence time series. However, inferring the molecular interaction dynamics from the observables remains a challenging inverse problem, particularly when measurement noise and photobleaching are nonnegligible—a common situation in single-cell analysis. The conventional approach is to process the time-series data algebraically, but such methods inevitably accumulate the measurement noise and reduce the signal-to-noise ratio (SNR), limiting the scope of FRET microscopy. Here, we introduce an alternative probabilistic approach, B-FRET, generally applicable to standard 3-cube FRET-imaging data. Based on filtering theory, B-FRET implements a statistically optimal way to infer molecular interactions and thus drastically improves the SNR. We validate B-FRET using simulated data and then apply it to real data, including the notoriously noisy in vivo FRET time series from individual bacterial cells to reveal signaling dynamics otherwise hidden in the noise.</p>
Optimizing Sparse Matrix-Matrix Multiplication for the GPU supplementary data
<p>This contains the matrices for the SpGEMM tests presented in "Optimizing Sparse Matrix-Matrix Multiplication for the GPU", by Steven Dalton, Nathan Bell, and Luke N. Olson.</p> <p>Each A matrix from Table 3 has an companion matrix P in the directory. The storage scheme appends "_P" to the end of the A matrix filename.<br> </p>
Results of optimal biocomposite mixture as best sound and thermal insulator
<p>Biobased composites are increasingly used. One of the most frequently used material is hemp shives, which is agricultural waste. However, as the quantities of this material are lacking, there is a tendency towards finding new and more available materials. Corncob and sawdust are bio by-products that have great potential as insulation materials. In order to use these aggregates, it is necessary to examine their characteristics. New composite materials based on sawdust, corncobs, polystyrene granules and the mixture of lime and plaster as the binder, were tested within this research. This paper presents the properties of these composites obtained by determining the porosity of samples, volume mass, water absorption, airflow resistance and heat flux, which was followed by calculation of the thermal conductivity coefficient. Three mixtures of the new composite material, whose samples were 1cm-5cm thick for each type of mixture, were investigated. The aim of this research was to analyze the results of different mixtures and sample thickness in order to determine the optimum composite material of the proper thickness so that the best possible thermal and sound insulation could be obtained. New composite materials can be used as an alternative to conventional materials.</p>
The optimal time to approach an unfamiliar object: A Bayesian model
<p>Many organisms take time before approaching unfamiliar objects. This caution forms the basis of some well-known assays in the fields of behavioral ecology, comparative psychology and animal welfare, including quantifying the personality traits of individuals and evaluating the extent of their neophobia. In this paper we present a mathematical model which identifies the optimal time an observer should wait before approaching an unfamiliar object. The model is Bayesian, and simply assumes that the longer the observer goes without being attacked by an unfamiliar object, the lower will be the observer's estimated probability that the object is dangerous. Given the information gained, a time is reached at which the expected benefits from approaching the object begin to exceed the costs. The model not only explains why latency to approach may be repeatable among individuals and vary with the object's appearance, but also why individuals habituate to the stimulus, approaching it more rapidly over repeated trials. We demonstrate the applicability of our model by fitting it to published data on the time taken by chicks to attack artificial caterpillars which share no, one, or two signaling traits with snakes (eyespots and posture). We use this example to show that while the optimal time to attack an unfamiliar object reflects the observer's expectation that the object is dangerous, the rate at which habituation arises is also a function of the observer's certainty in their belief. In so doing, we explain why observers become more rapidly habituated to "weaker" stimuli than "stronger" ones. </p>
Optimal prey for red fox cubs – an example of dual optimizing foraging strategy in foxes from a dynamic wetland habitat
<p>The red fox (<em>Vulpes</em> <em>vulpes</em>) is the most abundant mesopredator in the Central-European region. Detailed knowledge about their feeding behavior is important both from ecological and wildlife management reasons. Food choices of foxes are poorly predictable in high-biodiversity marshlands. The main aim of our study was to sample parallel the main food-type abundances in the study area and analyze the diet of fox cubs and cohabiting adults across three years during the period of maternal dependence of the cubs. According to the optimal foraging theory, we predicted that the cubs' diet would show higher energy content, would be more varied, and the individual prey species fed to the young would be larger. We analyzed the composition of adult fox and cub fecal samples collected separately around dens in a marshland of western Hungary, May 2014, 2017 and 2020, when the abundance values of main food sources differed. Rodents and waterfowl dominated the diet, but their relative occurrence in the samples showed yearly variations. We found that vixens follow a dual optimizing foraging strategy regarding their provisioning of the cubs and their own diet. Adult foxes optimized their diet according to the actual yearly abundances of their main food sources. Additionally, they preferred prey items that can be consumed at the site of capture (large carrion and small individual prey items). Cubs on the other hand were provisioned with optimal high-energy food, even if those in question became less abundant in that year. Vixens mostly fed to their young either larger rodents and waterfowl, or multiple small rodents at a time – these types of prey are both optimal for transportation as a single load. Providing optimal prey at an early age in a changing environment may contribute to the ecological success of the red fox.</p>
Supporting Data for "Does a Machine-Learned Potential Perform Better Than an Optimally Tuned Traditional Force Field? A Case Study on Fluorohydrins"
<p>Supporting Data for "Does a Machine-Learned Potential Perform Better Than an Optimally Tuned Traditional Force Field? A Case Study on Fluorohydrins"</p>
Optimized structures for Optical control of ultrafast structural motion in a fluorescent protein
<p>QM-MM Optimized structures of the<strong> </strong>hydrogen bonding configuration in states A1, A2 and Transition State (TS) between them for rsKiiro protein on ground (s0) and first excited (s1) states. Structures were optimized at PBE0-D3/cc-pVDZ//Amber03 level.</p>
Automated control and optimization of laser-driven ion acceleration: Data
<p>This data repository contains python scripts that can recreate the plots from the article on 'Automated control and optimization of laser-driven ion acceleration'.</p>
[DATA LINK] Clearing the way to the external world: do ants make optimal decisions when removing obstacles from their subterranean galleries?
<p>Data repository of the submitted paper:</p> <p>“Clearing the way to the external world: do ants make optimal decisions when removing obstacles from their subterranean galleries?”</p> <p>Authors : Louis Devers (0009-0001-3726-1891), Clémentine Cléradin, Zoé Bescond-Michel, Gérard Latil and Vincent Fourcassié (0000-0002-3605-6351).</p> <p>Contains :</p> <ul> <li>Extraction.csv [database] : the observed orientations of the obstacle extraction</li> <li>Traction.csv [database] : censing the orientation of mandibular grasps and effective pulls observed</li> <li>Model_traction.csv [database] : censing the orientation of virtual pulls</li> <li>Model_extraction.csv [database] : censing the orientation of virtual extraction, resulting from sequential tractions presented in model_traction.csv</li> <li>TreatmentAndGraphs [R script] : script including statistical analysis, and survival analysis graphs</li> </ul>
Dataset for Optimal reactive nitrogen control pathways identified for cost-effective PM2.5 mitigation in Europe
<p>This folder includes six folders:</p> <p>The "Nr anthropogenic emissions" folder includes the anthropogenic Nr emissions used in the baseline simulations for January, April, July, and October 2015.</p> <p>The "Concentration" folder includes daily surface ammonia (NH<sub>3</sub>), nitric acid (HNO<sub>3</sub>), nitrate (NO<sub>3</sub><sup>-</sup>), ammonium (NH<sub>4</sub><sup>+</sup>), sulfate (SO<sub>4</sub><sup>2-</sup>), and fine particulate matter (PM<sub>2.5</sub>) concentrations for January, April, July, and October 2015 from WRF-Chem simulations (one BASE simulation and twelve sensitivity simulations as stated in Method).</p> <p>The "N-share" folder includes the N-share caused by anthropogenic Nr (NH<sub>3</sub> and NO<sub>x</sub>)/ NH<sub>3</sub>/NO<sub>x</sub> emissions in 2015.</p> <p>The "Health" folder includes the PM2.5-related premature deaths from WRF-Chem combined with GEMM simulations in 2015. </p> <p>The "Instant efficiency" folder includes the instant efficiency of Nr/ NH<sub>3</sub>/NO<sub>x</sub> emission controls from WRF-Chem simulations in 2015. </p> <p>The "G ratio" folder includes the G ratio from WRF-Chem simulations for the year 2015 and the indicator months (January, April, July, and October). </p> <p>For any questions, please contact Zehui Liu<br> Email: liuzh18@pku.edu.cn<br> </p>
56th CIRP Conference on Manufacturing Systems, CIRP CMS '23, South Africa - Enhancing SLM Stainless Steel: Model-Based Parameter Optimization
<p> SLM (selective laser melting) has faced challenges in ensuring consistent mechanical properties for various geometries in the past. However, the authors have developed a system that solves this issue by calculating the optimal process parameters for each scan vector on each layer. This approach ensures consistent melt pool geometry, derived from the most robust in conduction welding mode. The results from the single melt-line experiments and the presented thermal conduction solver demonstrate the effectiveness of this approach in achieving a stable melt pool geometry in stainless steel (1.4404 or 316L). Furthermore, a rigorous testing regimen has been implemented to evaluate the system under different changing boundary conditions, to further demonstrate its usefulness. By utilizing this system, manufacturers will achieve consistent and high-quality mechanical properties for small lot sizes, including spare and obsolescent parts.</p>
Data for: Early radial positional information in the cochlea is optimized by a precise linear BMP gradient and enhanced by SOX2
<p>Positional information encoded in signaling molecules is essential for early patterning in the prosensory domain of the developing cochlea. The sensory epithelium, the organ of Corti, contains an exquisite repeating pattern of hair cells and supporting cells. This requires precision in the morphogen signals that set the initial radial compartment boundaries, but this has not been investigated. To measure gradient formation and morphogenetic precision in developing cochlea, we developed a quantitative image analysis procedure measuring SOX2 and pSMAD1/5/9 profiles in mouse embryos at embryonic day (E)12.5, E13.5, and E14.5. Intriguingly, we found that the pSMAD1/5/9 profile forms a linear gradient up to the medial ~75% of the PSD from the pSMAD1/5/9 peak in the lateral edge during E12.5 and E13.5. This is a surprising activity readout for a diffusive BMP4 ligand secreted from a tightly constrained lateral region since morphogens typically form exponential or power-law gradient shapes. This is meaningful for gradient interpretation because while linear profiles offer the theoretically highest information content and distributed precision for patterning, a linear morphogen gradient has not yet been observed. Furthermore, this is unique to the cochlear epithelium as the pSMAD1/5/9 gradient is exponential in the surrounding mesenchyme. In addition to the information-optimized linear profile, we found that while pSMAD1/5/9 is stable during this timeframe, an accompanying gradient of SOX2 shifts dynamically. Last, through joint decoding maps of pSMAD1/5/9 and SOX2, we see that there is a high-fidelity mapping between signaling activity and position in the regions that will become Kölliker's organ and the organ of Corti. Mapping is ambiguous in the prosensory domain precursory to the outer sulcus. Altogether, this research provides new insights into the precision of early morphogenetic patterning cues in the radial cochlea prosensory domain.</p>
Measurement of layer thicknesses with an improved optimization method for depolarizing Mueller matrices
<p>Measurement and simulation data of layer thickness standards</p>
Reproduction Package for ASE 2023 Submission `Improving Verification through Compiler Optimizations'
<p><strong>Artifact</strong></p> <p>In order to run this artifact please clone <a href="https://github.com/sosy-lab/sv-benchmarks">sv-benchmarks</a> into this folder. Afterwards you can just run the program using the running instructions down below. The results used in the paper can be found in the folder <code>transformation-for-verification-data</code>.</p> <p><strong>Setup</strong></p> <p>In order to setup this project, first initialize the submodules or clone this repository with the flag <code>--recursive</code>. Afterwards execute <code>python3 src/setup.py</code> in this directory, in order to add the required files to the submodules.</p> <p><strong>Running</strong></p> <p>In order to run this locally inside <code>./src</code></p> <pre><code>./main_bench.py --specification specification/path.prp program/to/verify.c</code></pre> <p>For example:</p> <pre><code>./main_bench.py --specification ../setup-files/test-run/unreach-call.prp ../setup-files/test-run/test_program.c </code></pre> <p>In order to execute with benchexec, execute the following insider <code>./src</code>, after adapting <code>bench.xml</code> to suit your purposes:</p> <pre><code>./benchmark_local.sh</code></pre>
Compact RINEX dataset of: Optimizing simultaneous water level and wave measurements from multi-GNSS interferometric reflectometry over one year at an exposed coastal site
<p>Compact-RINEX files (Hatanaka-compressed format) for each day of the deployment. Sampling frequency is 1 Hz.</p>
Dataset pro práci Algoritmus Brain storm optimization: aplikace a varianty
<p>Veškerá data pro práci Algoritmus Brain storm optimization: aplikace a varianty</p>
Data and code for Body colour drives optimal insect phenology via thermoregulation
<p>Data and code for the manuscript entitled: "Body colour drives optimal insect phenology via thermoregulation"<br> by Roberto Novella-Fernandez, Roland Brandl, Stefan Pinkert, Dirk Zeuss, Christian Hof.</p>
Data for GECCO2023 Paper "Pareto Local Optimal Solutions Networks with Compression, Enhanced Visualization and Expressiveness"
<p><strong>Data for Paper "Pareto Local Optimal Solutions Networks with Compression, Enhanced Visualization and Expressiveness"</strong></p> <ul> <li><strong>instances.tar.xz</strong> contains 𝜌mnk-landscape instances</li> <li><strong>metrics.csv</strong> contains the (C)PLOS-net metric-values</li> <li><strong>performance.csv</strong> contains the performance of the different algorithms on each instance</li> <li><strong>merged.csv</strong> contains the merged data from the 2 csv files above</li> </ul> <p><strong>Reference</strong></p> <p>Arnaud Liefooghe, Gabriela Ochoa, Sébastien Verel, and Bilel Derbel. 2023. <strong>Pareto Local Optimal Solutions Networks with Compression, Enhanced Visualization and Expressiveness</strong>. In Genetic and Evolutionary Computation Conference (GECCO ’23), July 15–19, 2023, Lisbon, Portugal. ACM, New York, NY, USA, 9 pages. <a href="https://doi.org/10.1145/3583131.3590474">https://doi.org/10.1145/3583131.3590474</a></p> <p><strong>Abstract</strong></p> <p>The structure of local optima in multi-objective combinatorial optimization and their impact on algorithm performance are not yet properly understood. In this paper, we are interested in the representation of multi-objective landscapes and their multi-modality. More specifically, we revise and extend the network of Pareto local optimal solutions (PLOS-net), inspired by the well-established local optima network from single-objective optimization. We first define a compressed PLOS-net which allows us to enhance its perception while preserving the important notion of connectedness between local optima. We then study an alternative visualization of the (compressed) PLOS-net that focuses on good-quality solutions, improves the distinction between connected components in the network, and generalizes well to landscapes with more than 2 objectives. We finally define a number of network metrics that characterize the PLOS-net, some of them being strongly correlated with search performance. We visualize and experiment with small-size multi-objective nk-landscapes, and we disclose the effect of PLOS-net metrics against well-established multi-objective local search and evolutionary algorithms.</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.