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4,725 results for “Normalization”
Normalized CT images and reference segmentations of thoracic and lumbar vertebrae from the CSI 2014 workshop
<p>This is the dataset of the vertebra segmentation challenge of the <a href="http://csi-workshop.weebly.com/challenges.html">CSI 2014 workshop</a> that was held in conjunction with MICCAI 2014.</p> <ul> <li><strong>1-10</strong>: Training set, scans of 10 young adult (16-35 years old)</li> <li><strong>11-15</strong>: Test set, scans of 5 young adult (20-35 years old)</li> <li><strong>16-20</strong>: Test set, scans of 5 patients with vertebral compression fractures </li> </ul> <p>Scans were acquired at the Department of Radiological Sciences, University of California, Irvine, School of Medicine and were published under the <a href="http://opendatacommons.org/licenses/pddl/1.0/">ODC Public Domain Dedication and License</a> on <a href="http://spineweb.digitalimaginggroup.ca/">SpineWeb</a> (datasets 2 and 15). The dataset and challenge is further described in this publication: <a href="http://dx.doi.org/10.1016/j.compmedimag.2015.12.006">A multi-center milestone study of clinical vertebral CT segmentation</a></p> <p>The data that is published here has been normalized:</p> <ul> <li>Voxel values are Hounsfield values and have been clipped to [-1000, 3095]</li> <li>Image origin has been set to 0,0,0</li> <li>Image orientation has been standardized to RAI orientation</li> <li>Small islands and other obvious mistakes have been removed</li> <li>Segmentation masks have been smoothed with a 2x2x2 median filter</li> <li>Vertebrae have been anatomically labeled (8 = T1, 9 = T2, ..., 24 = L5)</li> <li>Because not always all visible vertebrae were segmented in the original data, only segmentations of the thoracic and lumbar vertebrae have been retained</li> </ul> <p><strong>License</strong></p> <p>This dataset is released under the <a href="https://opendatacommons.org/licenses/by/1-0/">Open Data Commons Attribution License</a> (which the original license allows me to do). When using this dataset for publication of any kind, please reference the following paper to meet the attribution requirement:</p> <blockquote> <p>Yao J, Burns JE, Forsberg D, Seitel A, Rasoulian A, Abolmaesumi P, Hammernik K, Urschler M, Ibragimov B, Korez R, Vrtovec T, Castro-Mateos I, Pozo JM, Frangi AF, Summers RM, Li S. A multi-center milestone study of clinical vertebral CT segmentation. Comput Med Imaging Graph. 2016; 49:16-28. doi: 10.1016/j.compmedimag.2015.12.006.</p> </blockquote> <p>There is no need to reference this upload, referencing the original authors is sufficient.</p> <p><strong>Notes</strong></p> <p>The dataset contains 2 cases with only 4 lumbar vertebrae in which L5/S1 has not been segmented (i.e., label 25 is missing).</p> <p>The resolution and segmentation quality of the diseased cases (16-20) is quite low.</p>
MUSES Normalized Difference Vegetation Index (NDVI) 16-Day 30m Geographic Grid over Beijing Since 1984
<p>The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (<a href="https://muses.bnu.edu.cn/">https://muses.bnu.edu.cn/</a>).</p> <p>This dataset is the MUSES NDVI product at 30 m spatial resolution and 16-day temporal resolution over Beijing. The MUSES NDVI product is provided on Geographic grid and spans from 1984 to 2021 (continuously updated). It was generated from the Landsat collection 2 surface reflectance data using a temporally continuous vegetation indices-based land-surface reflectance reconstruction (VIRR) method (Xiao <em>et al</em>., 2015; Xiao <em>et al</em>., 2017). The MUSES NDVI product is spatially complete and temporally continuous.</p> <p><strong>Dataset Characteristics:</strong></p> <ul> <li>Spatial Coverage: 115.416599º E – 117.508219º E, 39.441929º N – 41.059283º N</li> <li>Temporal Coverage: 1984 – 2021</li> <li>Spatial Resolution: 0.000269469º (approximately 30 m)</li> <li>Temporal Resolution: 16 days</li> <li>Projection: Geographic</li> <li>Data Format: HDF</li> <li>Scale: 0.0001</li> <li>Valid Range: 0 – 10000</li> </ul> <p><strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong></p> <ol> <li>Xiao Zhiqiang, <em>et al</em>. (2015). Reconstruction of Satellite-Retrieved Land-Surface Reflectance Based on Temporally-Continuous Vegetation Indices. <em>Remote Sensing</em>, 7, 9844-9864</li> <li>Xiao Zhiqiang, <em>et al</em>. (2017). Reconstruction of Long-Term Temporally Continuous NDVI and Surface Reflectance From AVHRR Data. <em>IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing</em>, 10, 5551-5568</li> </ol> <p>If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).</p> <p> </p>
The transcriptomic landscape of normal and ineffective erythropoiesis at single cell resolution
<p><span>Ineffective erythropoiesis, the death of maturing erythroid cells, is a common cause of anemia. To better understand why this occurs, we studied the fates and adaptations of single erythroid marrow cells from individuals with Diamond Blackfan anemia (DBA), del(5q) myelodysplastic syndrome (del(5q) MDS), and normal controls, and defined an unhealthy (vs. healthy) differentiation trajectory, using velocity pseudotime and cell surface protein assessment. The pseudotime trajectories diverge immediately after the cells upregulate transferrin receptor (CD71), import iron, and initiate heme synthesis, although cell death occurs much later. Cells destined to die highly express heme-responsive genes, including ribosomal protein and globin genes. In contrast, surviving cells downregulate heme synthesis, while upregulating DNA damage response, hypoxia, and HIF1 pathways. Surprisingly, 24±12% of cells from controls follow the unhealthy trajectory, implying that heme also regulates cell fate decisions during normal red cell production. Del(5q) MDS (unlike DBA) results from somatic mutations, so many normal (unmutated) erythroid cells persist. By independently tracking their trajectory, we gained insight into why they cannot expand to prevent anemia. In addition, we show that intron retention is especially prominent during red cell differentiation. The additional information provided by messages with retained introns also allowed us to align data from multiple independent experiments and thus accurately query the transcriptomic changes that occur as single erythroid cells mature. </span></p>
Data and analysis for: Differential effects of ankle constraints on foot placement control between normal and split belt treadmills
<p>Here we compared the effect of ankle moment constraints (LesSchuh; a shoe with a narrow ridge along the length of the shoe's sole), on a single and a split-belt treadmill. To this end we considered the foot placement model as proposed by Wang and Srinivasan (2014), and used the R^2 of this model as an outcome measure. In addition, step width, stride frequency and toe-out angles have been computed. The results have been written up in our publication in the journal of biomechanics.<br> <br> Wang, Y., & Srinivasan, M. (2014). Stepping in the direction of the fall: the next foot placement can be predicted from current upper body state in steady-state walking. <em>Biology letters</em>, <em>10</em>(9), 20140405.</p>
Basílica de Lourdes, Quinta Normal
Modelo 3D de la Basílica de Lourdes Source: Objaverse 1.0 / Sketchfab
RNAseq of partially paralyzed zebrafish embryos at 5 days post-fertilization compared to normal siblings
<p>Sofa potato (sop) is a mutant zebrafish line, whose synaptic transmission at the neuromuscular junction is absent due to a point mutation in the δ subunit gene of the acetylcholine receptor (AChR), leading to paralysis of its skeletal muscles. To explore genetic changes in embryos caused by the lack of synaptic transmission, we performed RNA-seq analysis of normal siblings (<em>sop</em><sup>+/?</sup>) and <em>sop </em>homozygous embryos<em> (sop<sup>-/-</sup>) </em>at 5 days post-fertilization.</p>
Normal Saline versus Lactated Ringer's Solution: Effects on Organ Function and Inflammatory Responses in Heat Stroke in Rat
<p>The data set includes the data generated during the experiment, including vital signs, test indicators, etc. The image file includes the expression of inflammasome proteins measured using WB.</p>
Meshes, volume fractions, and normal vectors for paraboloid fit verification
<p>These datasets are used to verify the results of the paper "A Paraboloid Fitting Technique for Calculating Curvature from Piecewise-Linear Interface Reconstructions on 3D Unstructured Meshes" by Z. Jibben, N. N. Carlson, and M. M. Francois.</p>
Normalization references for LCIA methods based on ecoinvent
<p>ecoinvent version 3.5</p> <p>see the corresponding article:</p> <p>Consistent normalization approach for Life Cycle Assessment based on inventory databases</p> <p><a href="https://doi.org/10.1016/j.scitotenv.2019.134583">https://doi.org/10.1016/j.scitotenv.2019.134583</a></p>
Processed data - DegNorm: Normalization of generalized transcript degradation improves accuracy in RNA-seq analysis
<p>Processed data from DegNorm:</p> <ul> <li>"_raw.txt": raw read counts matrix;</li> <li>"_DI.txt": Degradation index score matrix;</li> <li>"_DegNorm.txt": normalized read counts matrix from DegNorm output;</li> <li>"_coverage.Rdata": list of coverage matrix for the sample;</li> <li>"_countsTIN.txt": TIN normalized counts.</li> </ul> <p> </p>
Deep Neural Models for Medical Concept Normalization in User-Generated Texts
<p>PsyTar folds used for experiments in the paper "Deep Neural Models for Medical Concept Normalization in User-Generated Texts" to be published at ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Student Research Workshop. </p> <p>All other datasets used in the paper can be found in the following places:</p> <p>Cadec random: https://zenodo.org/record/55013#.XPE1MC1eN24<br> Cadec custom: https://yadi.sk/d/GZoWm1wBxzyW_w</p> <p>SMM4H dataset: in the paper "Data and systems for medication-related text classification and concept normalization from Twitter: insights from the Social Media Mining for Health (SMM4H) - 2017 shared task"<br> <br> Bibtex:</p> <p>@inproceedings{miftahutdinov2019,<br> title = "Deep Neural Models for Medical Concept Normalization in User-Generated Texts",<br> author = "Miftahutdinov, Zulfat and Tutubalina, Elena",<br> booktitle = "Proceedings of {ACL} 2019, Student Research Workshop",<br> month = jul,<br> year = "2019",<br> address = "Florence, Italy",<br> publisher = "Association for Computational Linguistics",<br> }</p>
Dataset of AD and normal aging in the hippocampus
<p>Alzheimer's disease (AD) is the most common type of dementia in the elderly, characterized by irreversible degenerative memory, language, learning, and other cognitive impairments. It is estimated that nearly 500,000 new cases of AD, which is the fifth-leading cause of death for those 65 and older in the United States in 2016. AD brings immense suffering and heavy financial burdens. However, few therapeutic strategies are available to prevent or cure AD due to complex pathogenesis. Due to the high morbidity and mortality of AD, revealing its causes and potential pathogenesis, identifying molecular biomarkers for the early diagnosis, prevention, and treatment are a vital event. However, existing studies have shown that Tau, amyloid-β (Aβ) and APOE play important roles in the pathogenesis of AD, but the above-mentioned aspects as a targeted treatment have not achieved good results. It is imperative in the search for hub gene and pathways in AD. Thus, we extracted mRNA expression data with AD and normal aging in the same tissue and used an integrative network-based method for combining transcriptomic and protein-protein interaction data to find <a>differential</a>ly <a>expressed</a> <a>genes</a> (DEGs) and pathways that may reflect key biological processes in AD.</p>
MOVIE S4. Normal clearance of murine respiratory tract is mediated by discontinuous Muc5b and Muc5ac mucus clouds
<p><strong>Movie S4. Mucus transport of the Muc5b on the trachea of </strong><strong><em>Muc5ac<sup>–/–</sup></em></strong> <strong>mice. </strong>The mouse trachea was mounted and submerged in a buffer containing Alcian blue, tilted and the mucus transport in the distal part of the tissue recorded by video microscopy.</p>
Results for the Pareto analysis on the POTG Normal Instances
<p>The .xlsx file contains the results for the multi-objective POTG (double drop, Hybrid ILS heuristic) formulation. For each scenario, all dominated and non-dominated solutions are reported for the normal instances which are available at https://zenodo.org/records/10032290.</p> <p>The sizing configuration, cost and total wait times for 1. traditional charging station and 2. POTG framework (under the investment sizing) is reported. Additionally, the total time a driver would take to drive to a charging station under the traditional setup and the runtime for the Hybrid heuristic are also reported.</p>
Data for "Earthquake nucleation and slip behavior altered by stochastic normal stress heterogeneity"
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Geomagnetic field instability linked to mantle activity during the Cretaceous Normal Superchron
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Research data supporting: "Extended sampling of macromolecular conformations from uniformly distributed points on multidimensional normal mode hyperspheres"
<p>This repository contains protein structures generated by the approach "distributed points Molecular Dynamics using Normal Modes" (dpMDNM). dpMDNM is an enhanced-sampling approach that allows large protein conformational sampling based on normal mode (NM) vector combinations.</p> <p>Input parameter and equilibrated files for Lysozyme and CYP3A4 are provided, including their respective ensemble of structures after conformational exploration combining from 2 to 8 NMs.</p> <p>For more information, please visit the <a href="https://github.com/antonielgomes/dpMDNM">dpMDNM GitHub repository</a>.</p>
Spatial Dissection of the Distinct Cellular Responses to Normal Aging and Alzheimer's Disease in Human Prefrontal Cortex at Single-Nucleus Resolution
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Neurology paper "Sequence of Alzheimer disease biomarker changes in cognitively normal adults: A cross-sectional study" Table e-1
<p>Our Neurology 2020 paper titled "<span><a><b>Sequence of Alzheimer disease biomarker changes </b></a><b>in cognitively normal </b></span><b>adults: A cross-sectional study" explores the cascades of </b>changes of several well-known Alzheimer disease (AD) markers including cerebrow spinal fluid (CSF), imaging (PET-PIB and MRI) and cognitive markers in cognitively normal participants. The baseline marker data of participants is modeled as a piecewise linear function of baseline age allowing one change point, without and with adjustment for covariates. The change point of a marker incicates the acceleration time of point after which a greater percentage of the participants present preclinical AD compared to before the change point. Cosnistent with previous research, the study confirmed that Abeta42 showed the earliest change-point around 50 years old and cognition had a late change point around 62. The study further found Tau, pTau and MRI hippalcampal volume had their change point closer to cognition. We identified change points in all participants, as well as by stratification of APOE4 status. The data here displays the Supplemental table Table e-1 accompanying the paper where the change point results by stratification of APOE4 status are presented.</p> <div> <div> <div class="msocomtxt"> </div> </div> </div> <p> </p>
FIGURE 3. Bromus husainii. A. Normal Spikelet. B. Lower glume. C. Upper glume. D. Lower Lemma. E. Palea. F. Anther. G. Gynoecium. H in Bromus husainii (Poaceae:Bromeae), a new species from Valley of Flowers National Park, Uttarakhand, India
FIGURE 3. Bromus husainii. A. Normal Spikelet. B. Lower glume. C. Upper glume. D. Lower Lemma. E. Palea. F. Anther. G. Gynoecium. H. Lodicules.
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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.