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4,725 results for “Normalization”
Data and movies for "Flow of the normal component of He II about bluff objects as recorded by 〖He〗_2^* excimers"
<p>The directory is subdivided for the cylinder and flat plate bluff objects. Each subdirectory is further subdivided into data and movie subdirectories.</p> <p>"Data" consists of raw data collected from the camera. In the data directory is a listing of the filename with the power applied to the heater. Filenames of background data are also listed. </p> <p>"Movie" consists of frames integrated over 0.5 second intervals (28 frames). The movies include only excimer peaks for which the intensity of the peak is >3 sigma (~45). Where sigma is the standard deviation of the per frame background.</p> <p>A basic Jupiter Notebook is included in the top-level directory. This notebook (and the python code used by the notebook) will allow a user to upload a data file and a background file, subtract the background and place the net result into a NumPy array with dimensions of 256 x 256 x 1500, which represent the 2 directions in position and time in seconds.</p>
UAV-based DEM across the Peiku Co-Gyirong Rift normal faults, southernmost Tibetan
<p>These data are the unmanned aerial vehicle (UAV) topography surveying data (.tif) of several offset fluvial terraces/fans and lake shorelines across the Peiku Co-Gyirong Rift normal faults. The UAV data were acquired by ~100-200-m-high aerial photographs using a DJI (Dajiang Innovations Science and Technology Co., Ltd.) Phantom 4 RTK. High-resolution digital elevation models (DEM) were produced by Agisoft Metashape Professional software.</p> <p> </p>
Carved Block Normal Map RTI
A test of RTI on carved wood. Scans were done by AISOS, a part of LATIS Labs in the College of Liberal Arts at the University of Minnesota, Twin Cities. Source: Objaverse 1.0 / Sketchfab
SmokeTube. Homework XYZ. Bake normal.
SmokeTube. Homework XYZ. Bake normal. First step on road to bake normal maps. First baking normal map - first bread on my 3D-kitchen. Домашняя работа по запечке карт нормалей и АО. Source: Objaverse 1.0 / Sketchfab
Deer Stamp Normal Map RTI & Specular
I decided to try some photoshop filtering to get a loose specular map for this model. I think it turned out pretty nice. Normal map is from RTI method and the model was generated in Blender. As usual with RTI stuff, the matcap is definitely worth looking at. Scans were done by AISOS, a part of LATIS Labs in the College of Liberal Arts at the University of Minnesota, Twin Cities. Source: Objaverse 1.0 / Sketchfab
Photoreceptor glucose metabolism determines normal retinal vascular growth
<p>The neural cells and factors determining normal vascular growth are not well defined even though vision-threatening neovessel growth, a major cause of blindness in retinopathy of prematurity (ROP) (and diabetic retinopathy), is driven by delayed normal vascular growth. We examined if hyperglycemia and low adiponectin (APN) levels delayed normal retinal vascularization, driven primarily by dysregulated photoreceptor metabolism.</p> <p>One part of the experiments was to use targeted quantitative proteomics to measure the expression of proteins with selected reaction monitoring. We measured the enzymes in glycolysis, the Krebs cycle, and several addition mitochondrial proteins.</p> <p>We found that in a neonatal mouse model of postnatal hyperglycemia modeling early ROP, hyperglycemia caused photoreceptor dysfunction and delayed neurovascular maturation associated with changes in the APN pathway; recombinant mouse APN or APN receptor agonist adipoRon treatment normalized vascular growth. APN deficiency decreased retinal mitochondrial metabolic enzyme levels particularly in photoreceptors, suppressed retinal vascular development and decreased photoreceptor platelet-derived growth factor (Pdgfb). APN pathway activation reversed these effects. Blockade of mitochondrial respiration abolished adipoRon-induced Pdgfb increase in photoreceptors. Photoreceptor-knockdown of Pdgfb delayed retinal vascular formation. Stimulation of the APN pathway might prevent hyperglycemia-associated retinal abnormalities andsuppress Phase I ROP in premature infants.</p>
Data from: The classical and alternative circulating renin-angiotensin system in normal dogs and dogs with stage B1 and B2 myxomatous mitral valve disease
<p>The behavior of the comprehensive circulating renin‐angiotensin system (RAS) in dogs with myxomatous mitral valve disease (MMVD) before the onset of congestive heart failure remains largely unexplored.</p> <p>Hypothesis/Objectives: The classical and alternative RAS activity and aldosterone concentrations will be significantly higher in dogs with American College of Veterinary Internal Medicine (ACVIM) stage B2 MMVD compared to normal dogs and dogs with ACVIM stage B1 MMVD.</p> <p>Animals: One hundred seventeen client‐owned dogs (normal = 60; B1 = 31; B2 = 26).</p> <p>Methods: Prospective observational study. Angiotensin peptides (AP) and aldosterone concentrations were measured using liquid chromatography and mass spectrometry. Angiotensin converting enzymes 1 and 2 (ACE, ACE2) and renin activity surrogates were calculated from AP concentrations. Equilibrium dialysis (ED) and immediate protease inhibition (PI) methods of AP quantification were compared in 14 healthy dogs.</p> <p>Results: Core RAS activity and aldosterone concentrations did not differ among the 3 groups. However, the balance between the alternative and classical RAS differed, with dogs with stage B2 MMVD having significantly higher ACE2 activity surrogate (ACE2surr) when compared to normal dogs (adjusted P = .02; ratio of medians for ACE2surr [B2:normal], 1.89; 95% confidence interval [CI]: 1.4‐2.6). The ED and PI methods of AP quantification were highly correlated (AngI, r = .9, P < .0001; AngII, r = .8, P = .001).</p> <p>Conclusions and Clinical Importance: Circulating alternative RAS activity, specifically the surrogate measure of ACE2 activity, was increased in dogs with stage B2 MMVD as compared to normal dogs. Equilibrium dialysis results are analogous to immediate protease inhibition in dogs.</p>
Interfacial bonding strength along normal and shear direction of FMLs
<p>Interfacial bonding strength along normal and shear direction - lap_shear_Sandblasted at 1,3,5 bar</p>
Reproduction Package for "Preventing Refactoring Attacks on Software Plagiarism Detection through Graph-Based Structural Normalization"
<p>This repository stores all data used in the evaluation of the master's thesis "Preventing Refactoring Attacks on Software Plagiarism Detection through Graph-Based Structural Normalization". It ensures the continuous reproducibility of the results of the thesis.</p> <p>Content:</p> <ul> <li>JPlag v5.1.0 including the Java CPG frontend <ul> <li>Code base</li> <li>Runnable JAR</li> </ul> </li> <li>Data sets used for evaluation</li> <li>Evaluation results</li> <li>R script used to process the results</li> <li>Graphics and tables generated from the results</li> </ul> <p>The data sets were generated by Nils Niehues and Moritz Brödel and were originally published here:</p> <ul> <li><a href="../records/10430322">Supplementary Material for "Detecting Automatic Software Plagiarism via Token Sequence Normalization" (zenodo.org)</a></li> <li><a href="../records/10149536">Reproduction package for: Intelligent Match Merging to Prevent Obfuscation Attacks on Software Plagiarism Detectors (zenodo.org)</a></li> </ul> <p>The data sets are based partly on PROGPedia, available here:</p> <ul> <li><a href="../records/7449056">PROGpedia (zenodo.org)</a></li> </ul> <p>Visit <a title="State-of-the-Art Software Plagiarism & Collusion Detection" href="jplag.github.io/JPlag/" target="_blank" rel="noopener">JPlag</a> on GitHub for the current version.<br>See the thesis document for more information.</p> <p>Read about similar publications about Plagiarism Detection <a title="JPlag" href="https://jplag.github.io/MinimalLandingPage/" target="_blank" rel="noopener">here</a>.</p>
HyperspectralBlueberries: a dataset of hyperspectral reflectance images of normal and defective blueberries
<p>The <strong>HyperspectralBluberries</strong> dataset consists of hyperspectral datacubes, which were acquired by an in-house assembled benchtop line scanning system, from 420 blueberries of two categories, including 210 sound fruit and 210 samples with various defects. The fruit samples were hand-picked from a commercial orchard. Each scanning event, which was done for an array of 42 samples, yields two files in image formats .bil (band-interleaved-by-line) and .hdr (header), which store the hyperspectral raw data and associated metadata, respectively, and are both necessary for loading hyperspectral data for processing. In addition to sample scanning, a white reference was also scanned, which can be used for standardizing spectral responses. As a result, there are 22 files in the dataset, totaling about 25 GB in file size. The sample file names are descriptive, indicating the blueberry category and number information. The dataset was used for developing machine learning models for differentiating between normal and defective blueberries, achieving an overall accuracy of 96.6%. Software programs for the modeling work are publicly available at: <a href="https://github.com/vicdxxx/Blueberry-Defect-Detection-by-Hyperspectral-Imaging">https://github.com/vicdxxx/Blueberry-Defect-Detection-by-Hyperspectral-Imaging.</a></p> <p>Details about the dataset curation and modeling experiments are described in the journal article: <a href="https://www.sciencedirect.com/science/article/pii/S2772375524000789">Deng, B., Lu, Y., Stafne, E. (2024). </a><a href="https://www.sciencedirect.com/science/article/pii/S2772375524000789">Fusing Spectral and Spatial Features of Hyperspectral Reflectance Imagery for Differentiating between Normal and Defective Blueberries. Smart Agricultural Technology</a>. <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.atech.2024.100473" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.atech.2024.100473</a>. If you use the dataset in published research, please consider citing the dataset or the <a href="https://doi.org/10.1016/j.ecoinf.2024.102546">journal article</a>. Hopefully, you find the dataset useful. </p>
Data products associated with "Probabilistic Forward Modeling of Galaxy Catalogs with Normalizing Flows"
<p>These are the data products associated with "Probabilistic Forward Modeling of Galaxy Catalogs with Normalizing Flows" by J. F. Crenshaw, et. al. This includes the input catalog and the outputs of the workflow described here https://github.com/jfcrenshaw/pzflow-paper, as well as a gzip of the github repo.</p>
AI classification of normal and malignant cells on the basis of their viscoelastic properties
Open the record for dataset details and reuse information.
The Efficacy of Daily versus Weekly Ferrous Sulfate in Maintaining Normal Serum Ferritin Levels During Pregnancy: A Randomized Controlled Trial
<p>Serum ferritin is the most reliable indication of stored iron in pregnancy, offering a<br>noninvasive way to detect iron deficiency anemia before it occurs. Therefore, this study aimed to<br>determine serum ferritin levels among women receiving daily versus weekly iron supplementation,<br>with a secondary focus on comparing the proportion developing iron deficiency anemia and compli-<br>ance rates between the two groups.<br>Methods: This non-blinded randomized control trial involved non-anaemic pregnant women attend-<br>ing antenatal clinics at two Teaching Hospitals in Osun State. One hundred twenty-five subjects were<br>recruited to receive 65mg in the control group, while another 125 subjects in the active group re-<br>ceived three tablets (195mg) of ferrous sulfate (Fesulf) once weekly for 17 weeks from the 20th to<br>37th weeks of gestation. The primary outcome measure was comparing mean serum ferritin levels in<br>both groups at 37 weeks.<br>Results: Among the 240 subjects analyzed, the 37-week serum ferritin level was higher in the daily<br>group (73.26±26.67µg/L) compared to the weekly group (63.04±30.71 µg/L), p value=0.006. Four<br>(3.36%) and 10 (8.26%) of our subjects had Iron deficiency anaemia. Nine subjects (3.75%) reported<br>dyspepsia as a side effect. Daily 65 mg of Felsulf proved more effective than weekly 195mg in main-<br>taining normal blood ferritin levels during pregnancy.<br>Conclusions: Daily iron supplementation with 65mg ferrous sulfate was more effective at main-<br>taining adequate maternal iron concentration in this group of non-anaemic pregnant women. This<br>dosage is recommended for routine iron supplementation in our environment.</p>
Dry ECG Dataset: Normal and Interference-Affected Records (NSIR Dataset)
<p><strong>The dataset consists of 149 ECG signals that were sampled at a frequency of 500 Hz using a single lead. </strong></p> <p><strong>The main objective</strong> is to identify and differentiate normal-recorded ECG signals from those affected by two common types of interference:</p> <ul> <li>50/60 Hz power line interference .</li> <li> electrode contact noise caused by unstable movement.</li> </ul> <p>The data was recorded at the LINS Laboratory within the University of USTHB in Algeria using <strong>the Orbital 90 dry electrode</strong>, which has a 25 mm conductive area diameter based on the three electrodes configurations to measure the potential difference between the two arms, with the right leg serving as the reference. In order to improve signal quality, a fourth-order Butterworth low-pass filter was utilized for its smooth frequency response and minimal phase distortion, followed by a notch filter to eliminate 50 Hz power line noise. These filtering processes significantly enhanced the ECG signal quality by reducing noise and interference while preserving important cardiac information. The recorded data was stored in <strong>CSV</strong> format using UART communication via a USB connected to a computer.</p> <ul> <li><strong>Dataset Summary</strong></li> </ul> <table> <tbody> <tr> <td><strong>Type of Record </strong></td> <td><strong>Number of Records</strong></td> </tr> <tr> <td>well-recorded ECG</td> <td>42</td> </tr> <tr> <td>50/60 Hz power line interference</td> <td>44</td> </tr> <tr> <td>electrode contact noise</td> <td>63</td> </tr> <tr> <td><strong>Total</strong></td> <td>149</td> </tr> </tbody> </table> <p> </p> <p><strong>Note :</strong></p> <ol> <li><strong>You can find in the attachment a set of scalogram representations of the data with different wavelets, converted using the CWT technique.</strong></li> <li><strong>These data were used in transfer learning and gave a remarkable result, highlighting the unnecessary need for a huge dataset to train a transfer learning algorithm when the data is well recorded and the classes are distinguished.</strong></li> </ol> <p> </p> <ul> <li>For more details please feel free to contact us :</li> </ul> <ol> <li>Kharziwisseme@hotmail.com</li> <li>kerdjidjoussama@gmail.com</li> <li>malikakedir@gmail.com</li> <li>nac.meziane@gmail.com</li> </ol>
Test set for Normalization of Historical English in CEEC
<p>The file contains three lists of normalizations of historical English forms that have been produced by hand. The file contains 3 lists of 100 historical-modern spelling pairs: a mixed century list, a 15th century list and an 18th century list. The historical forms originate from the CEEC corpus.</p>
Medical Concept Normalization in Social Media Posts with Recurrent Neural Networks
<p>Text mining of scientific libraries and social media has already proven itself as a reliable tool for<br> drug repurposing and hypothesis generation. The task of mapping a disease mention to a concept<br> in a controlled vocabulary, typically to the standard thesaurus in the Unified Medical Language<br> System (UMLS), is known as medical concept normalization. This task is challenging due to the<br> differences in medical terminology between health care professionals and social media texts coming<br> from the lay public. To bridge this gap, we use sequence learning with recurrent neural networks<br> and semantic representation of one- or multi-word expressions: we develop end-to-end architectures<br> directly tailored to the task, including bidirectional Long Short-Term Memory and Gated Recurrent<br> Units with an attention mechanism and additional semantic similarity features based on UMLS.<br> Our evaluation over a standard benchmark shows that recurrent neural networks improve results<br> over an effective baseline for classification based on convolutional neural networks. A qualitative<br> examination of mentions discovered in a dataset of user reviews collected from popular online health<br> information platforms as well as quantitative evaluation both show improvements in the semantic<br> representation of health-related expressions in social media.</p>
Dataset for: A graph-based algorithm for RNA-seq data normalization
<p>mRNA-seq assays on mouse tissues were downloaded from the ENCODE project and consolidated into matrices of expression</p>
Experimentally Measuring an Isolated Branch of Nonlinear Normal Modes
<p>Dataset for "Experimentally Measuring an Isolated Branch of Nonlinear Normal Modes", Journal of Sound and Vibration.</p> <p>See "readme.txt" for details</p>
Reasearch data for publication "On optimizing metaheuristics performance with different error normalization approaches"
<p>These are the results of experiments performed for publication "On optimizing metaheuristics performance with different error normalization approaches" using authors own software -- EvANN -- which is available on github.</p>
MOVIE S1. Normal clearance of murine respiratory tract is mediated by discontinuous Muc5b and Muc5ac mucus clouds
<p>Movie S1. Mucus transport in healthy WT mouse trachea. The mucus on the mounted trachea was submerged in a buffer containing Alcian blue, the tissue tilted, and the mucus movement recorded by video microscopy.</p>
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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.