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3,363 results for “Replication”
Experiment replication - Sendivogius 1604 (Johns Hopkins University, Baltimore, USA, 6/6/2022)
<p>Replication in laboratory of an experiment reported by Michael Sendivogius, <em>De lapide philosophorum/Novum lumen chymicum</em> (1604):</p> <p>In explaining the operation of the mineral seed (“Sperma”): “Exempli gratia, habeatur in aliqua mensa plana vasculum aquae, quod locetur in mensae medium, et circumcirca ponantur res variae, et colores varii, item sal et cetera, quodque separatim: effundatur postea aqua in medium, videbis illam aquam hic inde diffluere, et dum rivulus uno attinget colorem rubeum, rubefiet ab illo, si ad salem, salis saporem mutabitur, et sic de caeteris. Aqua enim loca non mutat, sed locorum diversitas mutat aquam. Simili modo e centro Terrae semen vel sperma a quatuor elementis in centrum proiectum ad varia loca transit, et secundum loci Naturam naturatur res, si pervenit ad locum terrae et aquae purum, fit res pura” (pp. 22-23)</p> <p>Date: June 6, 2022</p> <p>Place: Johns Hopkins University, Baltimore (MD), US</p> <p>Project and Funding Source: Horizon 2020 – MGA MSCA-IF – Grant agreement No. 101019781 – SOUNDEPTH</p> <p>Work Package: 4</p>
Analysis of division and replication cycles in E. coli using time-lapse microscopy, microfluidics and the MoMA software
<p>Dataset used in the publication "Initiation of chromosome replication controls both division and replication cycles in E. coli through a double-adder mechanism" by Guillaume Witz, Erik van Nimwegen and Thomas Julou (<a href="https://doi.org/10.1101/593590">https://doi.org/10.1101/593590</a>).</p> <p>The zip folder contains four subfolders each containing data corresponding to a given growth condition. Each subfolder contains one folder with images of time-lapses of E. coli cells growing in single microfluidics growth lanes and one folder with data obtained by analysing those images with the software MoMA (<a href="https://github.com/fjug/MoMA">https://github.com/fjug/MoMA</a>).</p>
Auxiliary files for invasion resistance in multispecies systems based on the replicator equation
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Data from: Spatial replication is important for developing landscape genetic inferences for a wetland salamander
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Replication data for: Mapping oak wilt disease from space using land surface phenology
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Replicated functional evolution in cichlid adaptive radiations
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Replicated differential expression analysis in a green-brown polymorphic grasshopper reveals role of beta-carotene-binding protein in body coloration
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Data from: Predicting fitness in future climate: Insights from temporally replicated field experiments in Arabidopsis thaliana
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Data from: Metabarcoding of soil environmental DNA replicates plant community variation but not specificity
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Replication data for impact evaluation of two large-scale forestry incentive programs in Guatemala
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SIMBED+ - Replicable Real Wireless Networking Experiments using ns-3
<p>Wireless networking R&D depends on experimentation to make realistic evaluations of networking solutions, as simulation is inherently a simplification of the real-world. However, despite more realistic, experimentation is limited in aspects where simulation excels, such as repeatability and reproducibility.</p> <p>Real wireless experiments may be difficult to repeat. For the same input they can produce very different output results, since wireless communications are influenced by external phenomena such as noise, interference, and multipath. Even if repeatable, experiments may still be difficult to reproduce. Namely, other researchers may be unable to reproduce an experiment and confirm previous experimental results right away, because either the testbed is unavailable – offline or running other experiments when using a community testbed –, or inaccessible at all when a custom testbed was originally used.</p> <p>Fed4FIRE+ testbeds such as w-iLab.t, although operating in controlled environment, do not fully address the problem. This is even more evident in testbeds running in non-controlled and very dynamic environments, such as CityLab, where they may suffer from radio interference and competition from existing networks sharing the same radio spectrum.</p> <p>What if we could make any wireless experiment repeatable and reproducible? What if we could share the same Fed4FIRE+ testbed execution conditions among an "infinite" number of users? What if we could run wireless experiments faster than in real time?</p> <p>INESC TEC has developed the Offline Experimentation (OE) approach that combines the best of simulation and experimentation to achieve the above-mentioned goals. By relying on Network Simulator 3 (ns-3) and its good simulation capabilities from the MAC to the Application layer, we have been exploring how ns-3 can be used to replicate real-world wireless experiments using real traces containing 1) position of nodes and 2) the quality of each radio link.</p> <p>The previous <strong>SIMBED </strong>project validated the OE approach for controlled environments and helped identifying some of its limitations. The OE approach was then improved to support experiments using Multiple-In-Multiple-Out (MIMO) and shared radio spectrum with concurrent networks. To further validate the improved OE approach, the <strong>SIMBED+</strong> project aimed at running a set of experiments on top of the controlled and non-controlled environments of w-iLab.t and CityLab Fed4FIRE+ testbeds. For that purpose, we configured different fixed experimental scenarios, representative of Wi-Fi range of operation, subjected to controlled and non-controlled interference from concurrent experiments. For each experiment the achieved network throughput was measured. Then, we repeated each experiment using, both, Pure Simulation (PS) and OE approaches (now with MIMO and channel occupancy information) based on ns-3, also measuring the network throughput for the same set of experiments.</p> <p>To compare the network throughput of the real experiments with their PS and OE counterparts, Cumulative Distribution Function (CDF) curves were used, plotting all 1-second average throughput samples. For all the experiments performed in SIMBED+, using the improved OE approach resulted in network throughput considerably closer to real than using the PS approach. This is even more evident in non-controlled environments using MIMO and shared radio spectrum.</p> <p>These results were important for further validating the OE approach, producing two conference papers and one journal paper. The SIMBED+ results increased our confidence on the OE approach ability of reproducing past experiments, and are envisioned to foster the adoption of the OE approach by the networking community, in complement to the use of real experimentation.</p> <p> </p> <p>The following dataset presents the results of the SIMBED+ project, organized in different folders, for each subset of experiments carried on:</p> <ul> <li><strong><em>SubExp#1: </em></strong><em>Trace-based PHY rate with SISO support (802.11a, BW 20 MHz) </em></li> <li><strong><em>SubExp#2: </em></strong><em>Trace-based PHY rate with MIMO support (802.11n/ac, BW 20/40 MHz, MIMO 3x3) </em> <ul> <li><strong><em>SubExp#2.1: </em></strong><em>IEEE 802.</em><em>11n, 20 MHz, MIMO 3x3</em></li> <li><strong><em>SubExp#2.2: </em></strong><em>IEEE 802.</em><em>11n, 40 MHz, MIMO 3x3</em></li> <li><strong><em>SubExp#2.3: </em></strong><em>IEEE 802.</em><em>11ac, 40 MHz, MIMO 3x3</em></li> </ul> </li> <li><strong><em>SubExp#3: </em></strong><em>Shared radio spectrum support (occupancy at the sender)</em></li> <li><strong><em>SubExp#4: </em></strong><em>Shared radio spectrum support (occupancy at the receiver)</em></li> <li><strong><em>SubExp#5:</em></strong> <em>Trace-based PHY rate, MIMO and shared radio spectrum support</em></li> </ul> <p>Each experiment has an individual folder, named according to the date and time of the experiment and the nodes used. Inside, there’s a folder for the <strong>parsed</strong> experimental results, which contains</p> <p>This folder contains the details and parsed logs of the experiment, as follows:</p> <ul> <li><em>date_time</em><strong>.cfg </strong>– configuration details of the experiment</li> <li><em>date_time_NodeID<sup><a href="#_ftn1"><strong>[1]</strong></a></sup>_SenderID<sup><a href="#_ftn2"><strong>[2]</strong></a></sup>_ReceiverID<sup><a href="#_ftn3"><strong>[3]</strong></a></sup>_FlowType<sup><a href="#_ftn4"><strong>[4]</strong></a></sup>_Params<sup><a href="#_ftn5"><strong>[5]</strong></a></sup></em><strong>.snr </strong>– logs of the Signal/Noise ratio (1 file per node/flow) </li> <li><em>date_time_NodeID_SenderID_ReceiverID_FlowType_Params</em><strong>.stats</strong> – logs of the packets received (1 file per node/flow) </li> <li><em>NodeID</em><strong>.</strong><strong>waypoints</strong> – coordinates of the static nodes</li> <li><em>date_time_MobileNodeID</em><strong>.</strong><strong>waypoints</strong> – waypoints of the mobile nodes (when applicable)</li> </ul> <p>The experiment’s folder also contains a folder for the simulations <strong>output</strong> with the simulations statistics files, for the multiple simulations approaches considered, as follows:</p> <ul> <li><em>date_time_NodeID_SenderID_ReceiverID_FlowType_Params</em>.<strong>simstats </strong>– logs of the packets received (simulation)</li> </ul> <p> </p> <p><sub><a href="#_ftnref1">[1]</a> ID of the node Logging node</sub></p> <p><sub><a href="#_ftnref2">[2]</a> ID of the Sender node</sub></p> <p><sub><a href="#_ftnref3">[3]</a> ID of the Receiver node</sub></p> <p><sub><a href="#_ftnref4">[4]</a> Flow type: Unidirectional, Bidirectional or Unidirectional with Multiple Access</sub></p> <p><sub><a href="#_ftnref5">[5]</a> Configurable parameters: Sender/Receiver Transmission Power and Data Rate (when applicable)</sub></p>
Replication code and data for: "Machine Learning Predicts Large Scale Declines in Native Plant Phylogenetic Diversity."
<p>Replication code and data for the paper: "Machine Learning Predicts Large Scale Declines in Native Plant Phylogenetic Diversity." The following files are included in this repository:</p> <p>1) R scripts (numbered 0 through 9) include replication code for data analysis</p> <p>2) Datasets (6 zip folders) contain the data analyzed in the R scripts</p> <p> </p> <p> </p>
The relationship between code smells and design patterns: an external replicated experiment
<p>Dataset of the paper "The relationship between code smells and design patterns: an external replicated experiment"</p> <p>File descriptions in readme.txt.</p>
Mass spectrometry output SILAC labelled (F/Y) biological replicate 2 - anti-HLA-A29 antibody DK1G8
<p>Mass spectrometry output from SILAC labelled (F/Y) ERAP2 WT versus (CRISPR Cas9-mediated) ERAP2-KO lymphoblastoid cell line from a Birdshot Uveitis patient (ERAP1 hap10/10 ERAP2 hapA/A). Peptides were eluted from immuno-purifications with anti-HLA-A29 antibody DK1G8. The dataset was used for subsequent filtering and differential expression analysis by <em>limma</em>. </p>
Mass spectrometry output SILAC labelled (F/Y) biological replicate 2 - anti-HLA-ABC antibody W6/32
<p>Mass spectrometry output from SILAC labelled (F/Y) ERAP2 WT versus (CRISPR Cas9-mediated) ERAP2-KO lymphoblastoid cell line from a Birdshot Uveitis patient (ERAP1 hap10/10 ERAP2 hapA/A). Peptides were eluted from immuno-purifications from HLA-A29-negative (DK1G8-negatively selected) fractions with anti-HLA-ABC antibody W6/32. The dataset was used for subsequent filtering and differential expression analysis by <em>limma</em>. </p>
Replication Package for "Function-as-a-Service Performance Evaluation: A Multivocal Literature Review"
<p><strong>Paper</strong></p> <p>J. Scheuner and P. Leitner, “Function-as-a-Service Performance Evaluation: A Multivocal Literature Review,” Accepted at the <a href="https://www.journals.elsevier.com/journal-of-systems-and-software">Journal of Systems and Software (JSS)</a>, Preprint: <a href="https://arxiv.org/abs/2004.03276">arXiv:2004.03276</a>.</p> <blockquote> <p>Function-as-a-Service (FaaS) is one form of the serverless cloud computing paradigm and is defined through FaaS platforms (e.g., AWS Lambda) executing event-triggered code snippets (i.e., functions). Many studies that empirically evaluate the performance of such FaaS platforms have started to appear but we are currently lacking a comprehensive understanding of the overall domain. To address this gap, we conducted a multivocal literature review (MLR) covering 112 studies from academic (51) and grey (61) literature. We find that existing work mainly studies the AWS Lambda platform and focuses on micro-benchmarks using simple functions to measure CPU speed and FaaS platform overhead (i.e., container cold starts). Further, we discover a mismatch between academic and industrial sources on tested platform configurations, find that function triggers remain insufficiently studied, and identify HTTP API gateways and cloud storages as the most used external service integrations. Following existing guidelines on experimentation in cloud systems, we discover many flaws threatening the reproducibility of experiments presented in the surveyed studies. We conclude with a discussion of gaps in literature and highlight methodological suggestions that may serve to improve future FaaS performance evaluation studies.</p> </blockquote> <pre>@article{scheuner:20-jss, author = {Joel Scheuner and Philipp Leitner}, title = {Function-as-a-Service Performance Evaluation: A Multivocal Literature Review}, journal = {J. Syst. Softw.}, volume = {170}, pages = {110708}, year = {2020}, doi = {10.1016/j.jss.2020.110708} }</pre> <p><strong>Dataset</strong></p> <p>All extracted data originating from academic and grey literature studies are available as machine-readable CSV (<a href="https://github.com/joe4dev/faas-performance-mlr/blob/master/data/faas_mlr_raw.csv">./data/faas_mlr_raw.csv</a>) and human-readable XLSX (<a href="https://github.com/joe4dev/faas-performance-mlr/blob/master/data/faas_mlr_raw.xlsx">./data/faas_mlr_raw.xlsx</a>). The Excel file also contains all 700+ comments with guidance, decision rationales, and extra information. It is configured with a filtered view to display only <em>relevant</em> sources but contains the complete data (i.e., including discussion for sources considered to be <em>not relevant</em> in our context).</p> <p>Find further documentation in the README.md or on Github: <a href="https://github.com/joe4dev/faas-performance-mlr/">https://github.com/joe4dev/faas-performance-mlr/</a></p> <p>The latest version is also available online as an interactive Google spreadsheet (GSheet): <a href="https://docs.google.com/spreadsheets/d/1EK9yg9fMZIDybnbi7thsnBx1NdqDmkW86sMygH9r8q8">https://docs.google.com/spreadsheets/d/1EK9yg9fMZIDybnbi7thsnBx1NdqDmkW86sMygH9r8q8</a></p> <p> </p>
Replication data for: Conservation Gaps in Traditional Vegetables Native to Europe and Fennoscandia
<p>Vegetables are rich in vitamins and other micronutrients and are important crops for healthy diets and diversification of the food system, and many traditional (also termed underutilized or indigenous) species may play a role. The current study analyzed 35 vegetables with a European region of diversity with the effort to map the conservation status in Fennoscandia and beyond. We mapped georeferenced occurrences and current genebank holdings based on global databases and conducted conservation gaps analysis based on representativeness scores in situ and ex situ. Out of the 35 target species, 19 got at a high priority score for further conservation initiatives, while another 14 species got a medium priority score. We identified a pattern where traditional vegetables are poorly represented in genebank holdings. This corresponds well to a lack of attention in the scientific community measured in number of published papers. Considering the grand challenges ahead in terms of climate change, population growth and demand for sustainability, traditional vegetables deserve greater attention. Our contribution is to provide a basis for conservation priorities among the identified vegetables species native to Fennoscandia.</p>
Data from: Are replication rates the same across academic fields? community forecasts from the DARPA SCORE program
The DARPA program "Systematizing Confidence in Open Research and Evidence" (SCORE) aims to generate confidence scores for a large number of research claims from empirical studies in the social and behavioral sciences. The confidence scores will provide a quantitative assessment of how likely a claim will hold up in an independent replication. To create the scores we follow earlier approaches and use prediction markets and surveys to forecast replication outcomes. Based on an initial set of forecasts for the overall replication rate in SCORE and its dependence on the academic discipline and the time of publication, we show that participants expect replication rates to increase over time. Moreover, they expect replication rates to differ between fields, with the highest replication rate in economics (average survey response 58%), and the lowest in Psychology and in Education (average survey response of 42% for both fields). These results reveal insights into the academic community's views of the replication crisis, including for research fields for which no large-scale replication studies have been undertaken yet.
Replication package for: A Model of Relative Thinking
<p>Data replication package for Bushong, Benjamin, Matthew Rabin, and Joshua Schwartzstein, "A Model of Relative Thinking", forthcoming, <em>The </em><em>Review of Economic Studies.</em></p> <p> </p> <p>Contents: Stata data from two experiments and Stata .do files to replicate analyses. </p>
Reproducible Validation and Replication Studies in Nanoscale Physics (repro results plots - Ellis et al., 2016)
<p>This archive contains the Jupyter notebooks needed to reproduce the figures of the paper that are related to the Validation results and replication of Ellis et al. 2016. For further information direct to the README.md file.</p>
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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)
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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.