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47,155 results for “evaluations”
Dual-modal imaging of two-phase flows with electromagnetic flow tomography and electrical tomography -- experimental evaluation of the state estimation approach
<p>The supplementary files included are associated with our experimental research on two-phase flow estimation. This study experimentally investigates the feasibility of a state estimation approach for dynamic image reconstruction in dual-modal tomography of two-phase oil-water flows using electromagnetic flow tomography (EMFT) and electrical tomography (ET). By approximating the process with a convection-diffusion model, the extended Kalman filter and fixed-interval Kalman smoother are applied to reconstruct temporally evolving velocity and phase fraction distributions. The results demonstrate that the Kalman smoother-based reconstructions, along with uncertainty estimates, outperform conventional methods and provide feasible volumetric flow rate estimates for oil and water phases in a laboratory setup.</p>
scMARK an 'MNIST' like benchmark to evaluate and optimize models for unifying scRNA data
<p>Here we present a novel benchmark dataset (scMARK.v2), that consists of 11 published cancer scRNA-seq studies, for which we standardized cell-type author labels and gene identifiers. scMARK.v2 can be used to ask how well models integrate data from different scRNA studies. We also provide a 12th standardized study (Wu et al 2021) that we held-out for evaluation of alignment of data "never seen" before, and a 13th study of newly generated in-vitro scRNA-seq data from cancer and fibroblast cells.</p> <ul> <li>Data is provided as aData *h5ad files that can be read with Python's library <a href="https://scanpy.readthedocs.io/en/stable/">Scanpy</a>.</li> <li>Studies inclided in scMARK.v2 were downsampled to 10,000 cells per study.</li> <li>The difference between <a href="https://zenodo.org/record/5765804">scMARK.v1</a> and scMARK.v2, is that in v2, we provide at least two studies for each cancer type and each cell type; whereas in v1 a handfull of cell types were present only in one study.</li> </ul>
Advanced photochemical processes for the manufacture of nanopowders: an evaluation of long-term pilot plant operation
<p>Dataset for the publication:</p> <p>Advanced photochemical processes for the manufacture of nanopowders: an evaluation of long-term pilot plant operation</p> <p>React. Chem. Eng., 2022, 7, 968–977</p> <p>DOI: 10.1039/d1re00374g</p>
FIG. 3 in An evaluation of the endemic bryophyte flora of Guadeloupe
FIG. 3. — Riccardia innovans (Steph.) Pagán. A, habit; B, main axis in cross section (from the lectotype).Scale bars: A, 1 mm; B, 50 µm. Photographs by C. Reeb.
FIG. 5 in An evaluation of the endemic bryophyte flora of Guadeloupe
FIG. 5.— Lectotype of Trichosteleum glaucinum (Besch.) A.Jaeger (PC-hb.Bescherelle "Antillean Bryophytes").
NUMAC: Description of the Nested Unified Model with Aerosols and Chemistry, and evaluation with KORUS-AQ data: supporting data
<p>Simulated data presented in manuscript with title above, generated with the Met Office Unified Model, together with observations from KORUS-AQ and MODIS that are used in the model evaluation.</p> <p>The Terra/MODIS aerosol datasets were acquired from the Level-1 and Atmosphere Archive & Distribution<br> System (LAADS) Distributed Active Archive Center (DAAC), located in the Goddard Space Flight Center in Greenbelt, Maryland https://ladsweb.nascom.nasa.gov/. All surface and aircraft observation data is freely and publicly available at https://www-air.larc.nasa.gov/cgi-bin/ArcView/korusaq, last access 10 June 2022.</p>
Proactive Conflict Detection for Collaborative Model-driven Software Engineering (Evaluation Data)
<p>Results of the evaluation for the paper "Proactive Conflict Detection for Collaborative Model-driven Software Engineering"</p>
Supplementary data for "WebQUAST: online evaluation of genome assemblies"
<p>Supplementary data for A. Mikheenko, V. Saveliev, P. Hirsch, A. Gurevich. WebQUAST: online evaluation of genome assemblies.</p> <p><br> Reference genomes of two <em>Escherichia coli</em> K-12 substrains (MG1655 and W3110) and genome annotation of MG1655.</p> <p><em>De novo</em> assemblies of the <em>Escherichia coli</em> K-12 MG1655 short-read Illumina dataset (<a href="https://trace.ncbi.nlm.nih.gov/Traces/index.html?view=run_browser&acc=ERR008613&display=metadata">ERR008613</a>) with ABySS, MEGAHIT, SPAdes, and Velvet.</p> <p>WebQUAST reports in three evaluation modes: <br> * Use Case 1: reference-free evaluation (<em>sample_data_no_ref</em>)<br> * Use Case 2: reference-based evaluation (<em>sample_data_true_ref</em>) <br> * Use Case 3: evaluation based on a close reference (<em>sample_data_close_ref</em>)</p> <p>The snapshot (<a href="https://github.com/ablab/quast/commit/2bd50600bcf63ee826965c10f6ca4cdc2aa046e5">commit 2bd5060</a>) of the QUAST command-line version used by WebQUAST for generating the reports.</p>
Evaluating Institutional Commitments to Open Scholarly Infrastructure: A Review of Open Access Collection Development Policies
<p>Data prepared for the publication "Evaluating Institutional Commitments to Open Scholarly Infrastructure: A Review of Open Access Collection Development Policies."</p> <p><strong>oa-cd-policies.csv</strong></p> <p>Scope: This data represents collection development policies that contain substantial mention of open access.</p> <p>Data collection: The policies were sourced using an Advanced Google Search for "open access" AND "collection development policy" at ".edu" domains.</p> <p>Variables:</p> <ul> <li>institution: Free text, name of the institution.</li> <li>carnegie_class: One of <a href="https://carnegieclassifications.acenet.edu/carnegie-classification/classification-methodology/basic-classification/">these options</a>; the Carnegie classification of the institution.</li> <li>institution_type: One of public or private; the funding source of the institution.</li> <li>policy_name: Free text; the title of the policy.</li> <li>supplemental_policy: Link to a supplemental open access policy if linked in the collection development policy.</li> <li>cd_policy_link: Link to the policy.</li> <li>infrastructure: TRUE or FALSE; whether the policy includes a commitment to open access scholarly infrastructure development, including open source platforms, locally hosted platforms, consortia, or an institutional repository.</li> <li>excerpt: Free text; text from the policy that mentions infrastructure.</li> </ul> <p><strong>principles-policies.csv</strong></p> <p>Scope: This data represents those collection development policies from oa-cd-policies.csv that contain commitments in line with the <a href="https://openscholarlyinfrastructure.org/">Principles for Open Scholarly Infrastructure</a>.</p> <p>Variables:</p> <ul> <li>institution: Free text, name of the institution.</li> <li>carnegie_class: One of <a href="https://carnegieclassifications.acenet.edu/carnegie-classification/classification-methodology/basic-classification/">these options</a>; the Carnegie classification of the institution.</li> <li>institution_type: One of public or private; the funding source of the institution.</li> <li>policy_name: Free text; the title of the policy.</li> <li>supplemental_policy: Link to a supplemental open access policy if linked in the collection development policy.</li> <li>cd_policy_link: Link to the policy.</li> <li>principle: One of the three main <a href="https://openscholarlyinfrastructure.org/">Principles</a>.</li> <li>sub_principle: One of the <a href="https://openscholarlyinfrastructure.org/">Sub-Principles</a>.</li> <li>excerpt: Free text; text from the policy that illustrates the sub_principle.</li> </ul>
Fig. 3 in The genus Schistostoma Becker from southern Africa, with an evaluation of its generic status (Diptera: Dolichopodidae s. l.: Microphorinae)
Fig. 3. Schistostoma kalkgat sp. n.: (A) Hypopygium, right lateral view; (B) Hypopygium, hypandrium and cercus removed, left lateral view, (C) Hypandrium, dorsal view. Abbreviations: cerc – cercus; epand – epandrium; ej apod – ejaculatory apodeme; hypd – hypandrium; pgt – postgonite; ph – phallus; sur – surstylus. Scale bar = 0.1 mm.
Fig. 2 in The genus Schistostoma Becker from southern Africa, with an evaluation of its generic status (Diptera: Dolichopodidae s. l.: Microphorinae)
Fig. 2. Schistostoma brandbergensis sp. n.: (A) Hypopygium, right lateral view; (B) Hypopygium, hypandrium and cercus removed, left lateral view; (C) Hypandrium, dorsal view; (D) Phallus and internal structures, right lateral view.Abbreviations: cerc – cercus; epand – epandrium; ej apod – ejaculatory apodeme; hypd – hypandrium; hypd arm – hypandrial arm; pgt – postgonite; ph – phallus; sur – surstylus. Scale bar = 0.1 mm.
Fig. 1 in The genus Schistostoma Becker from southern Africa, with an evaluation of its generic status (Diptera: Dolichopodidae s. l.: Microphorinae)
Fig. 1. Schistostoma albopilosum (Becker): (A) Hypopygium, right lateral view; (B) Hypopygium, hypandrium and cercus removed, left lateral view; (C) Hypandrium, dorsal view; (D) Apical part of female terminalia, dorsal view. Abbreviations: cerc – cercus; epand – epandrium; ej apod – ejaculatory apodeme; hypd – hypandrium; pgt – postgonite; ph – phallus; sur – surstylus; T – tergite. Scale bars = 0.1 mm.
Fig. 4 in The genus Schistostoma Becker from southern Africa, with an evaluation of its generic status (Diptera: Dolichopodidae s. l.: Microphorinae)
Fig. 4. Acacia Karoo stand on the farm Kalkgat Noord (C. kalkgat type locality), in the north-eastern Knersvlakte, October 2000. Photograph by Ute Schmiedel.
Sound stimuli: Considerations for the perceptual evaluation of steady-state and time-varying sounds using psychoacoustic metrics
<p>The current dataset provides all the sound stimuli (wav files) to recreate the figures from the study with the title "Considerations for the perceptual evaluation of steady-state and time-varying sounds using psychoacoustic metrics" by the same authors. There are three datasets: <strong>dataset 1</strong> for fly-by aircraft sounds (directory <em>1-Aircraft-fly-by</em>), <strong>dataset 2</strong> for pass-by train sounds (directory <em>2-Train-pass-by</em>), and <strong>dataset 3</strong> for sounds from a resonating tube called hummer (directory <em>3-Hummer-resonances</em>). A brief description of the datasets is included. The reproduction of figures requires the installation of the sound quality analysis toolbox (SQAT) for MATLAB.</p> <p><strong>Use these data</strong>:<br> Download all these data, locate them in a local directory of your computer. If you have MATLAB and you downloaded a local copy of the <strong>SQAT toolbox</strong> (open access at: <a href="https://github.com/ggrecow/SQAT">https://github.com/ggrecow/SQAT</a>) you can recreate the figures of our paper. After downloading and initialising the toolbox (type 'startup_SQAT;', without quotation marks in MATLAB), run the script <strong>copy_sounds_for_pub_Osses2023c_to_SQAT.m</strong>. This last step is not required but recommended. Subsequently, you can run the toolbox script pub_Osses2023c_Forum_Acusticum_SQAT.m and follow the instructions on screen.</p>
Evaluation of a simple score-based Natural Language Processing (NLP) algorithm: Intermediary Result
<p>The intermediary result of the experiment "Evaluation of a simple score-based Natural Language Processing (NLP) algorithm".</p>
Evaluation of a simple score-based Natural Language Processing (NLP) algorithm: Category Confusion Matrix
<p>Resulting category confusion matrix for the experiment "Evaluation of a simple score-based Natural Language Processing (NLP) algorithm".</p>
Evaluation of a simple score-based Natural Language Processing (NLP) algorithm: Result
<p>The result for the experiment "Evaluation of a simple score-based Natural Language Processing (NLP) algorithm".</p>
PIsToN: Evaluating Protein Binding Interfaces with Transformer Networks (dataset)
<p>Computational protein-binding studies are widely used to investigate fundamental biological processes and facilitate the development of modern drugs, vaccines, and therapeutics. Scoring functions aim to assess and rank the binding strength of the predicted protein complex. Accurate scoring of protein binding interfaces remains a challenge. PIsToN (evaluating Protein binding Interfaces with Transformer Networks) represents a novel approach to distinguish native-like protein complexes from incorrect conformations. Protein interfaces are transformed into a collection of 2D images (interface maps), each corresponding to a geometric or biochemical property. Pixel intensities represent the feature values. A neural network was adapted from a popular vision transformer (ViT) with several enhancements: a hybrid component to accept empirical-based energy terms, a multi-attention module to highlight essential features and binding sites, and the use of contrastive learning for better ranking performance. The resulting PIsToN model significantly outperforms state-of-the-art scoring functions on well-known datasets.</p> <p>This repository contains proteins and pre-computed interface maps for the PIsToN work.</p>
Quality Attributes Assessment in Self-Adaptive Systems: An Empirical Evaluation
<p>Self-adaptive Systems (SAS) can monitor themselves and their context. They can detect changes and react to unexpected conditions with minimal human supervision during their execution. One of the challenges behind developing SAS is dealing with the decision-making process while analyzing the tradeoff points among the multiple quality attributes (QA). In Software Engineering, a widely accepted method of evaluating QA goals in software projects is the Architecture Tradeoff Analysis Method (ATAM). However, despite its importance and wide acceptance, there are few reports of empirical studies on analyzing QA tradeoffs in SAS. In this sense, the present investigation proposes an adapted version of ATAM called ATAM-4SAS to deal with the particularities of SAS. To achieve the research goal, we employed the UPPAAL SMC (statistical verification model) to analyze a set of QA. To evaluate the feasibility of the proposed method, we performed an empirical study on the execution of the ATAM-4SAS in a SAS developed according to the MAPE-K model. This model encompasses the Monitoring, Analysis, Planning, and Execution phases. Such steps share a knowledge base (K), which is fundamental in supporting decision-making. We complemented the empirical evaluation by conducting a focus group, which sought to assess the perceived ease of use and the perceived usefulness of the ATAM-4SAS to support the strategic choice of QA in a SAS. As a result, we observed that most participants agreed that ATAM-4SAS provides adequate support for the strategic choice of QA in SAS.</p>
Input data for the case study reported in "DREAM: an R package for druggability evaluation of human complex diseases".
<p>The data included in this record constituted the input for the case study reported in the manuscript "DREAM: an R package for druggability evaluation of human complex diseases", by Antonio Federico, Michele Fratello, Alisa Pavel, Lena Möbus, Giusy del Giudice, Angela Serra, Dario Greco. The data derive from transcriptomics experiments executed on lesional skin from atopic dermatitis patients and unaffected skin counterparts. The data consists of two files in ".txt" format reporting gene expression data in tabular format, where on the rows are reported genes and on the columns are reported samples. The data is an aggregated and batch-corrected collection of datasets originally downloaded by Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/). The file "GE_Mic_AD_Pamr_MAARS.txt" reports gene expression estimates of lesional skin of atopic dermatitis patients, while the file "GE_Mic_AD_Pamr_nl_MAARS.txt" reports gene expression estimates of non-lesional skin of atopic dermatitis patients.</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.