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5,771 results for “Strategy”
Dataset for publication "Cell design strategies for sodium-zinc chloride (Na-ZnCl2) batteries, and first demonstration of tubular cells with 38 Ah capacity"
<p><span lang="EN-US">stationary energy storage; ZEBRA battery; high-temperature metal chloride battery; molten-salt battery; molten sodium anode.</span></p> <p>Measured data to recreate Figures 1-8 in the above manuscript.</p>
Supplementary Figure 1 Gating strategy for Treg phenotype analysis.
<p><strong>Supplementary Figure 1. Gating strategy for Treg phenotype analysis. |</strong> Isolated and purified cells (see Methods) were analysed by flow cytometry with <strong>(A)</strong> gating performed as indicated including the exclusion of dead cells (by Live/Dead staining kit) and analysing only CD4+CD25+ double-positive cells. <strong>(B)</strong> These cells were then stained with indicated marker antibodies. The histogram quantification areas indicated by the black bars were set against control staining performed with non-specific isotype antibodies corresponding to each marker antibody.</p>
Data for "Ecosystem size filters life-history strategies to shape community assembly in lakes"
<p>Dataset 1. List of 71 fish species collected from north temperate lakes in Wisconsin USA. Data include critical life-history data used for strategy classifications according to Winemiller and Rose (1992), principal component scores, and strategy classification according to the cluster analysis.</p> <p>Dataset 2. Species occurrence data in all study lakes along with results from the 'soft classification" according to Euclidean distance.</p> <p>Dataset 3. Limnological and fish community characteristics of study lakes including species richness, lake area, estimated lake volume, and convex hull statistics for the overall fish community and each life-history strategy type.</p>
Dataset to the manuscript "Deciduous tundra shrubs shift toward more acquisitive light absorption strategy under climate change treatments"
<p>The three datasets were used for the statistical analysis for the manuscript entitled "Deciduous tundra shrubs shift toward more acquisitive light absorption strategy under climate change treatments".</p>
Data for: The function of stilt roots in the growth strategy of Socratea exorrhiza (Arecaceae) at two neotropical sites
<p>We provide the raw and processed data used in the following study: Goldsmith, G. R., & Zahawi, R. A. (2007). The function of stilt roots in the growth strategy of Socratea exorrhiza (Arecaceae) at two neotropical sites. <em>Revista de Biología Tropical</em>, <em>55</em>(3-4), 787-793.</p> <p><strong>Methods</strong> can be found in the file entitled "README-GoldsmithZahawi-SocrateaData-5Mar23F.txt," while metadata for data columns can be found in the file entitled: "GoldsmithZahawi-SocrateaMetaData-5March2023.csv."</p> <p><strong>Original Published Abstract</strong>: Arboreal palms have developed a variety of structural root modifications and systems to adapt to the<br> harsh abiotic conditions of tropical rain forests. Stilt roots have been proposed to serve a number of functions<br> including the facilitation of rapid vertical growth to the canopy and enhanced mechanical stability. To examine<br> whether stilt roots provide these functions, we compared stilt root characteristics of the neotropical palm tree<br> Socratea exorrhiza on sloped (>20º) and flat locations at two lowland neotropical sites. S. exorrhiza (n=80 trees)<br> did not demonstrate differences in number of roots, vertical stilt root height, root cone circumference, root cone<br> volume, or location of roots as related to slope. However, we found positive relationships between allocation<br> to vertical growth and stilt root architecture including root cone circumference, number of roots, and root cone<br> volume. Accordingly, stilt roots may allow S. exorrhiza to increase height and maintain mechanical stability<br> without having to concurrently invest in increased stem diameter and underground root structure. This strategy<br> likely increases the species ability to rapidly exploit light gaps as compared to non-stilt root palms and may also<br> enhance survival as mature trees approach the theoretical limits of their mechanical stability.</p>
Energy-Saving Strategies for Mobile Web Apps and their Measurement: Results from a Decade of Research - Dataset
<p>In 2022, over half of the web traffic was accessed through mobile devices. By reducing the energy consumption of mobile web apps, we can not only extend the battery life of our devices, but also make a significant contribution to energy conservation efforts. For example, if we could save only 5% of the energy used by web apps, we estimate that it would be enough to shut down one of the nuclear reactors in Fukushima. This paper presents a comprehensive overview of energy-saving experiments and related approaches for mobile web apps, relevant for researchers and practitioners. To achieve this objective, we conducted a systematic literature review and identified 44 primary studies for inclusion. Through the mapping and analysis of scientific papers, this work contributes: (1) an overview of the energy-draining aspects of mobile web apps, (2) a comprehensive description of the methodology used for the energy-saving experiments, and (3) a categorization and synthesis of various energy-saving approaches.</p>
Supplementary Material of the Manuscript: "The effects of blank size and knapping strategy on the estimation of core's reduction intensity"
<p>This repository hosts the R-markdown and dataset that allow reproducibility and replicability of the statistical analyses implemented in the paper: Lombao, D., Cueva-Temprana, A., Rabuñal, J.R., Morales, J.I., Mosquera, M. The effects of blank size and knapping strategy on the estimation of core’s reduction intensity. <em>Archaeol Anthropol Sci</em> <strong>11</strong>, 5445–5461 (2019). https://doi.org/10.1007/s12520-019-00879-4<br> For further information, please open first the readme.txt. document.</p>
Result dataset for our experimental analysis on multi-cepstral projection representation strategies for dysphonia detection
<p>Database containing the results of the analyzed versions of the framework proposed in our paper submitted to the journal Sensors (Basel) under the title "An experimental analysis on multi-cepstral projection representation strategies for dysphonia detection".</p> <p>In this database, we have the following information:</p> <p>"gender": Gender of individuals referring to the selected voice database. For this field, we have the following possible values: “male” for a selection of male individuals, “female” for a selection of female individuals, and “both” for a selection considering both genders.</p> <p>“Techniques”: Concerns about the techniques for extracting cepstral coefficients that we are analyzing. The identifier “nonceps” refers to the use of non-cepstral features.</p> <p>“vowel”: Vowel considered in the database selection. The following values are possible: “a”, “i” and “u”.</p> <p>“intonation”: Tone used by individuals when pronouncing the analyzed vowel. Possible values are: “h” for high; “l” for low; “n” is normal; and “lhl” for low-high-low.</p> <p>“coordinates”: Number of coordinates that make up the feature vector that represents the voice signal after the dimensionality reduction routines.</p> <p>“scale”: Normalization function used on the feature vector. The possible values of this field are the following: “MinMax” for the min-max scale; “Robust” for the robust scale; “Standard” for the standard scale; and “Unscaled” for the unscaled vector.</p> <p>“ACC”: Accuracy obtained by the analyzed version on the considered voice database clipping.</p> <p>“AUC”: Area under the ROC curve obtained by the analyzed version on the considered voice database clipping.</p> <p>“EER”: Equal Error Rate obtained by the analyzed version on the considered voice database clipping.</p> <p>“F1”: F1-score obtained by the analyzed version on the considered voice database clipping.</p> <p>“EH”: Rate of healthy voice signals classified as pathological on the considered voice database clipping.</p> <p>“EP”: Rate of pathological voice signals classified as healthy on the considered voice database clipping.</p> <p>“KFCV”: Average accuracy score of a 5-fold Cross Validation over the training dataset on the considered voice database clipping.</p> <p>“Balancing”: Indication of the use of balancing technique (SMOTE) by the considered framework version.</p> <p>“Classifier”: Classifier used, being possible the use of Random Forest (RF), Logistic Regression (LR), and Support Vector Machine (SVM).</p> <p>“Multi-Projection”: Multi-projection strategies employed by the evaluated technique.</p> <p>“Features”: Type of feature that defines the feature vector. In this case, the following values are possible in this field: “NonCeps” for non-cepstral features; “Ceps” for cepstral features only; and “Ceps and NonCeps” for features of cepstral and non-cepstral types.<br> .</p> <p>It is worth noting that the symbol “-”, present in some fields, represents the “non-use” of any technique of the type indicated by the field. For example, in the case of the “Balancing” field, the value “-” means that no data balancing technique was used in the evaluated version of the framework.</p>
A Simple Strategy to Eliminate Glycation Bias in the Relative Quantification of Protein N-glycosylation
<p><strong>Contents</strong></p> <p>Supplementary files for “A Simple Strategy to Eliminate Glycation Bias in the Relative Quantification of Protein <em>N</em>-glycosylation” by Esser-Skala et al (2020):</p> <ul> <li> <p><em>cafog_raw_data.tar.gz</em>: Raw data for denosumab and NISTmAb.</p> </li> <li> <p><em>cafog_source_code.zip</em>: Supplementary file 1 from the manuscript. This ZIP archive contains the source code of CAFOG.</p> </li> <li> <p><em>data.zip</em>: Supplementary file 2 from the manuscript. Files in this ZIP archive allow to reproduce all results presented in the manuscript.</p> </li> </ul> <p> </p> <p><strong>Changelog</strong></p> <ul> <li>1.1.0 – 2023-05-25 <ul> <li>added supplementary files 1 and 2 mentioned in the manuscript, since those were not published along with the manuscript</li> </ul> </li> <li>1.0.0 – 2020-01-30 <ul> <li>initial release</li> </ul> </li> </ul>
Diagnostic strategies for muscular dystrophies: a Cross-Sectional Study
<p>Datos obtenido producto de un estudio de corte transversal con el fin de establecer la prevalencia de base hospitalaria en distrofias musculares, a través de un diseño de muestreo en fases.</p>
Simulation code and simulated data for: Transient polymorphisms in parental care strategies drive divergence of sex roles
<p>This repository contains C++ code, simulated datasets, an R-script for data analysis and a Mathematica notebook for mathetical analysis.</p><p>Datasets are organised into ZIP files named after the corresponding figure in the publication. All of the figures based on simulation data in the manuscript and supplementary materials can be created with the R-script. For further information see the article published in <i>Nature Communications (</i>doi:<i> </i>https://doi.org/10.1038/s41467-023-42607-6).</p><p> </p><p> </p><p> </p>
Meshing strategies for 3D geo-electromagnetic modeling in the presence of metallic infrastructure
<p>Accompanying data to journal article</p> <blockquote> <p>Castillo-Reyes, O., Rulff, P., Schankee Um, E., Amor-Martin, A. (2023) Meshing strategies for 3D geo-electromagnetic modeling in the presence of metallic infrastructure. Accepted for publication in Computational Geosciences.</p> </blockquote>
Voltage-based strategies for preventing battery degradation under diverse fast-charging conditions
<p>Here are the simulated datasets for the work 'Voltage-based strategies for preventing battery degradation under diverse fast-charging conditions', published in ACS Energy Letters, September 2023. The utilization of these datasets is demonstrated in the associated GitHub project folder https://github.com/zachkonz/Voltage-based-plating-prevention.</p>
(POST) Socio-economic and cultural dataset in relation to Persuasive Strategies to boost Energy Efficiency and in the UK, Spain, Greece and Austria
<p>The dataset has been created from obtaining post-pilot answers from 106 participants of four different countries in the EU (the questionnaire can be studied in <strong>GreenSoul_Validation_Questionnaire-POST.pdf</strong>). It is composed by several factors which are explained in<strong> POST-coding.ods </strong>file. All these factors are contained in: "<strong>POST-results-socio-economic-model.ods</strong>" and "<strong>POST-results-treatments-evaluation.ods</strong>" along with their answers by participants.</p> <p>Finally, we provided a cleaned version of the dataset to study how can a researcher is able to forecast the ranking that a user will give to different persuasion strategies according to user profiles: "<strong>POST-results-ranking-model.ods</strong>"</p>
Simulated Solar Spectra for Testing Stellar Activity Mitigation Strategies
<p>Recent and upcoming stabilized spectrographs are pushing the frontier for Doppler spectroscopy to detect and characterize low-mass planets. Specifications for these instruments are so impressive that intrinsic stellar variability is expected to limit their Doppler precision for most target stars (Fischer et al. 2016). In order to realize their full potential, astronomers must develop new strategies for distinguishing true Doppler shifts from intrinsic stellar variability. Stellar variability due to starspots, faculae, and other rotationally-linked variability is particularly concerning, as the stellar rotation period is often included in the range of potential planet orbital periods. In order to robustly detect and accurately characterize low-mass planets via Doppler planet surveys, the exoplanet community must develop statistical models capable of jointly modeling planetary perturbations and intrinsic stellar variability. Towards this effort, we present simulations of extremely high-resolution solar-like spectra created with SOAP 2.0(Dumusque et al. 2014) that includes multiple evolving starspots to aid in developing and testing future statistical methods.</p>
Experiment Results: Evaluation of different parallelisation strategies with regard to the performance of parallel program execution
<p><br> Modern processors achieve an increase in performance by adding multiple cores. This means that during software development, care must be taken to parallelise the program sequences. To make predictions about the performance of a software design, there is Palladio. This is very accurate for single core processors.<br> In this bachelor thesis the influence of the chosen parallelization strategy on the performance of software is examined. Different hardware requirements are used for this purpose. They are used to generate individual work packages. These are executed by different parallelization strategies. The used parallelization strategies are: Java Threads, Java ParallelStreams, OpenMp and Akka Actor. Runtime and cache behavior are measured during each execution. In addition, the experiments are performed on different servers. The evaluation is done using acceleration curves and the Cache Miss Rate. The results show that the parallelization strategies differ only slightly in the work packages used.</p>
Hackathons as a Pedagogical Strategy to Engage Students to Learn and to Adopt Software Engineering Practices
<p>Teaching Software Engineering is not a trivial duty since several pedagogical strategies can be used and sometimes the impact of these on students is uncertain. Hackathons are similar to marathons, however used to produce solutions to solve a specific problem in a short period of time and based on intense collaboration. Educational hackathons aim to promote learning in such an environment. The Undergraduate computing programs of PUCRS decided to use a hackathon as a pedagogical strategy aiming to motivate the students to practice the adoption of software development practices and to work in groups as a means to practice the development of social skills. Therefore, we conducted a case study to investigate: 1) The motivations to students to attend or not attend an educational hackathon, 2) The students perceptions about this hackathon, 3) The Software Engineering practices adopted by students. In this study, we identified factors that may affect students motivation to participate (e.g., improve the teamwork skills), some students expectations about the hackathon (e.g., work in teams), and the practices adopted by the students (e.g., pair programming). Some of our findings include that students enjoy participating in an informal educational environment (e.g., hackathons) to improve their technical skills and to build network with some colleagues. This study can provide insights to teachers that wants to organize some activity than traditional teaching and the students perspective about this kind of strategy.</p>
Data accompanying the manuscript "Protocol Discovery for the Quantum Control of Majoranas by Differentiable Programming and Natural Evolution Strategies"
<p>Dataset for figures 2, A6 and A8 for the manuscript: "Protocol Discovery for the Quantum Control of Majoranas by Differentiable Programming and Natural Evolution Strategies." The dataset contains the optimal protocols for Majorana transport in both the Kitaev Chain model as well as the Proximity Coupled Semiconduncting Nanowire model obtained with Differentiable Programming and Natural Evolution Strategies. Also the Simulated Annealing (SA) optimal protocols for the Kitaev chain are included.</p>
Grouping strategies in number estimation extend the subitizing range
<p>In the calculation folder: each file contains a matrix called “MATR”. Each row of the matrix “MATR” is a trial. </p> <p>The columns contain the following information:</p> <p>1<sup>st</sup>: Number of trial</p> <p>2<sup>nd: Subject response</sup></p> <p>4<sup>th</sup>: Response time</p> <p>5<sup>th</sup>: first number </p> <p>6<sup>th</sup>: math symbol (1=*; 2= +; 3= –)</p> <p>7<sup>th</sup>: second number </p> <p>8<sup>th</sup>: third number </p> <p> </p> <p>In the calculation folder: each file contains a matrix called “matr”. Each row of the matrix “matr” is a trial. </p> <p>The columns contain the following information:</p> <p>1<sup>st</sup>: subject response in the numerosity task</p> <p>2<sup>nd</sup>: the presented numerosity </p> <p>3<sup>rd</sup>: subject response in the numerosity task</p> <p>4<sup>th</sup>: zero</p> <p>5<sup>th</sup>: stimulus duration</p> <p>6<sup>th</sup>: Response time in the numerosity task</p> <p>7<sup>th</sup>: Grouped (1) or random (2) presentation </p> <p>8<sup>th</sup>: 1</p> <p>9<sup>th</sup>: 1</p> <p>10<sup>th</sup>: Number of items of the upper-left quadrant</p> <p>11<sup>th</sup>: Number of items of the lower-left quadrant</p> <p>12<sup>th</sup>: Number of items of the upper-right quadrant</p> <p>13<sup>th</sup>: Number of items of the lower - right quadrant</p> <p>14<sup>th</sup>: odd shape presented (1=diamond; 2=triangle; 3=circle)</p> <p>15<sup>th</sup>: subject response in the shape task</p> <p>16<sup>th</sup>: 0.2 in the single task response time in the shape task when dual task</p> <p>17<sup>th</sup>: single (0) or dual (1) task</p> <p>18<sup>th</sup>: time stimulus on</p> <p>19<sup>th</sup>: time stimulus off</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
Code and data for: Is habitat selection in the wild shaped by individual-level cognitive biases in orientation strategy?
<p>This repository is a companion to the manuscript "<em>Is habitat selection in the wild shaped by individual-level cognitive biases in orientation strategy?</em>" and is linked to <a href="https://github.com/CBeardsworth/Pheasant_OrientStrat_Habitat">Github</a>.</p> <p>For any questions about the code please contact Christine at <a href="mailto:c.e.beardsworth@gmail.com">c.e.beardsworth@gmail.com</a></p> <p>To use any data contained in this repository contact Joah at <a href="mailto:j.r.madden@exeter.ac.uk">j.r.madden@exeter.ac.uk</a> for permission.</p> <p>In this repository, we have included a run-through of the R analysis <a href="https://cbeardsworth.github.io/Pheasant_OrientStrat_Habitat/">here</a> to show the outputs of the analysis without the need to run the code. For those that might want to run the code themselves, we have included three R scripts (<a href="https://github.com/CBeardsworth/NavigationHabitat/blob/master/R">/R</a>) and their accompanying datasets (<a href="https://github.com/CBeardsworth/NavigationHabitat/blob/master/Data">/Data</a>). A description of the code and the data needed to run them is below:</p> <p><em>Cognition analysis and figs.R</em> = Run the cognition analysis for the first section of the manuscript and create the figures. For this, the datasets mazeData.csv (the learning trials) and mazeRotationResults.csv (the probe trial) are required. </p> <p><em>iSSA analysis and bootstrapping.R</em> = Run iSSA models and bootstrapping. This produces the datasets required for the next stage of analysis. For this code, the datasets habitat.grd (habitat information), atlas2018-strategy.csv (atlas data + id and strategy data for each bird) and FeederCoords2017_27700.csv (coordinates of feeder locations from 2017-2018) are required. The produced datasets are included in <a href="https://github.com/CBeardsworth/NavigationHabitat/blob/master/Data">/Data</a> therefore to run subsequent analyses, this code does not need to be run. To develop this code we relied heavily on the code included in the supplementary material of <a href="https://doi.org/10.1002/ece3.4823">Signer et al. (2019)</a> as well as an <a href="https://bsmity13.github.io/log_rss">online tutorial</a> from Brian J. Smith for calculating log-RSS.</p> <p><em>Habitat analysis and Figs.R</em> = Run the statistical models for the final section of the manuscript and create the figures. For this code, the datasets produced in the previous R script are required (habitatOrientation_coefs.csv and habitatOrientation_avail.csv). We have included <a href="https://github.com/CBeardsworth/NavigationHabitat/blob/master/Data">these datasets</a> so users do not need to run the iSSA analysis and bootstrapping.R script themselves. </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.