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540 results for “Data Normalization”
Supplementary data frames, AlphaFold models, Normal Mode Analysis (NMA) Data, and NMA of Corresponding NMR Ensembles in the S2RCI, MD, and S2 Datasets for "Gradations in protein dynamics captured by experimental NMR are not well represented by AlphaFold2 models and other computational metrics"
<h1><strong>Changes applied to V2</strong></h1> <p>In addition to the supplementary dataframes and AlphaFold models from each dataset in V1, V2 includes the additional data outlined below.</p> <p>The <strong>S2RCI</strong> and <strong>MD</strong> datasets include comprehensive analyses of AlphaFold2 models (both before and after truncation). These datasets feature: </p> <ul> <li><strong>AlphaFold2 Models</strong>: Both original and truncated structures. </li> <li><strong>WEBnma Modes</strong>: `modes.txt` files generated from WEBnma analysis, available for both non-truncated and truncated AF2 models. </li> <li><strong>Root-Mean-Square-Fluctuations (RMSF)</strong>: Profiles calculated before and after truncation of AF2 models. </li> <li><strong>NMR Data: Normal Mode Analysis (NMA)</strong>: Performed on corresponding NMR ensembles (see below). </li> </ul> <p> </p> <p>The <strong>NMR Data</strong> of NMA in these datasets includes: </p> <ul> <li>NMR ensembles </li> <li>Individual NMR models extracted from each ensemble </li> <li>STRIDE secondary structure calculations per-individual NMR models</li> <li>RMSF profiles per-individual NMR models</li> </ul> <p>For detailed information, please refer to the `Readme.txt` file within each corresponding folder. </p> <p>The <strong>S2 dataset</strong> includes all the features listed above, except for the NMR analysis.</p>
Data for bulk ATAC-seq normalization paper
<p>This zipped file contains all public datasets used in our benchmark of bulk ATAC-seq normalization methods.</p>
Fig. 16. A. Vertebral line normally separated from the parietal region. B in Phylogenetic relationships based on morphological data and taxonomy of the genus Salvadora Baird & Girard, 1853 (Reptilia, Colubridae)
Fig. 16. A. Vertebral line normally separated from the parietal region. B. Vertebral line reaching the parietal region.
Normalized Difference Vegetation Index (NDVI) data
<p> </p> <p>The raster data 'viCH_Landsat_NAfill.tif' represents Normalized Difference Vegetation Index (NDVI) data of Switzerland. Raster pixels have 250x250 m resolution and contain median values of the years 2013 to 2017. Data was collected by the Landsat satellite and was downloaded via Google Earth Engine. Missing values were closed with a local neighborhood average.</p> <p>The raster data 'viNE_Modis2018_NAfill.tif' represents NDVI data of North Eurasia, at 1x1 km resolution, and averaged over the growing season 2018. Data was collected by the Modis sensor and was downloaded via Google Earth Engine. Missing values were closed with a local neighborhood average.</p>
Normalized daily average Schumann resonance (SR) intensity data from 13 to 31 January, 2019
<p>Data are provided for the whole globe (T), South America (SA), Africa (AF) and Asia (AS).</p> <p>File prepared by Tamás Bozóki (20 January, 2023)<br> Contact: bozoki.tamas@epss.hu</p>
Gyroscope sensor data of shank motion during normal and barefoot walking
<p>The measurements were performed in closed and disturbance free space, where an unobstructed 10 m walkway was arranged. All tests were performed on a hard floor surface first with shoes that were adapt for walking (indoor sports shoes, sneakers etc.) and afterwards walking barefooted the same protocol. The subjects had clothing which did not restrict lower limb movement. In each test, the 10 m walking was repeated three times. Prior to testing, the procedure was demonstrated, and the sensors were carefully positioned to correct locations. The subjects were instructed to walk with their own natural walking velocity and to begin each 10 m walk from a completely stationary position.</p>
Data from: Evidence for normal novel object recognition abilities in developmental prosopagnosia
<p>The issue of the face specificity of recognition deficits in developmental prosopagnosia (DP) is fundamental to the organisation of high-level visual memory and has been increasingly debated in recent years. Previous DP investigations have found some evidence of object recognition impairments, but have almost exclusively used familiar objects (e.g., cars), where performance may depend on acquired object-specific experience and related visual expertise. An object recognition test not influenced by experience could provide a better, less contaminated measure of DPs' object recognition abilities. To investigate this, in the current study we tested 30 DPs and 30 matched controls on a novel object memory test (NOMT Ziggerins) and the Cambridge Face Memory Test (CFMT). DPs were impaired on the CFMT but showed no differences in accuracy or reaction times to controls on the NOMT. We found similar results when comparing DPs to a larger sample of 274 web-based controls. Additional individual analyses demonstrated that the rates of object recognition impairment in DPs did not differ from the rate of impairment in either control group. Together, these results demonstrate unimpaired object recognition in DPs for a class of novel objects that serves as a powerful index for broader novel object recognition capacity.</p>
Data of normal spectral emissivity measurements for Ta, Mo, W and Nb
<p>Data aquired during my master thesis about the normal spectral emissivty of Ta, Mo, W and Nb measured with an ohmic pulse heating apparatus and a us-DOAP</p>
Data from: Characterization of gut microbiota composition in hemodialysis patients with normal weight obesity
<p><b>Background:</b> Normal weight obesity (NWO), defined by a normal body mass index (BMI) but increased body fat percentage (BF%), is associated with an increased risk of cardiovascular disease and mortality. NWO is characterized by inflammation and muscle wasting in chronic kidney disease (CKD), but the underlying mechanisms remain largely unknown. Gut microbiota has been implicated in the regulation of host metabolism and may play important roles in the development of NWO in CKD.</p> <p><b>Methods:</b> In this case-control study, we examined the gut microbial diversity and taxonomy in 96 hemodialysis patients with normal weight (BMI <25 kg/m<sup>2</sup> and BF% ≤25% for men or ≤35% for women, n = 32), NWO (BMI <25 kg/m<sup>2</sup> and BF% >25% for men or >35% for women, n = 32), and overweight/obesity (BMI ≥25 kg/m<sup>2</sup>, n = 32), matched for age, gender, and diabetes. BF% was measured using bioimpedance spectroscopy device. Gut microbiota was determined by 16S rRNA sequencing.</p> <p><b>Results:</b> We found that α-diversity was significantly different among the 3 adiposity phenotypes, with NWO being the least diverse. α-diversity was positively correlated with BMI, subjective global assessment score, and physical activity, but negatively correlated with interleukin-6 and tumor necrosis factor-α. Patients with or without NWO were distinguished with respect to principal coordinate analysis of β-diversity. Notably, the relative abundance of butyrate-producing bacteria, such as <i>Faecalibacterium </i><i>prausnitzii</i> and<i> Coprococcus</i>, was markedly reduced in patients with NWO.</p> <p><b>Conclusion:</b> Our findings support associations between gut dysbiosis and a proinflammatory and catabolic state in hemodialysis patients with NWO.</p>
Data from: The Chord-Normalized Expected Species Shared (CNESS)-distance represents a superior measure of species turnover patterns
<p>1. Measures of β-diversity characterizing the difference in species composition between samples are commonly used in ecological studies. Nonetheless, commonly used dissimilarity measures require high sample completeness, or at least similar sample sizes between samples. In contrast, the Chord-Normalized Expected Species Shared (CNESS) dissimilarity measure calculates the probability of collecting the same set of species in random samples of a standardized size, and hence is not sensitive to completeness or size of compared samples. To date, this index has enjoyed limited use due to difficulties in its calculation and scarcity of studies systematically comparing it with other measures.</p> <p>2. Here, we developed a novel R function that enables users to calculate ESS (Expected Species Shared)-associated measures. We evaluate the performance of the CNESS index based on simulated datasets of known species distribution structure, and compared CNESS with more widespread dissimilarity measures (Bray-Curtis index, Chao-Sørensen index, and proportionality based Euclidean distances) for varying sample completeness and sample sizes.</p> <p>3. Simulation results indicated that for small sample size (m) values, CNESS chiefly reflects similarities in dominant species, while selecting large m values emphasizes differences in the overall species assemblages. Permutation tests revealed that CNESS has a consistently low CV (coefficient of variation) even where sample completeness varies, while the Chao-Sørensen index has a high CV particularly for low sampling completeness. CNESS distances are also more robust than other indices with regards to undersampling, particularly when chiefly rare species are shared between two assemblages.</p> <p>4. Our results emphasize the superiority of CNESS for comparisons of samples diverging in sample completeness and size, which is particularly important in studies of highly mobile and species-rich taxa where sample completeness is often low. Via changes in the sample size parameter m, CNESS furthermore cannot only provide insights into the similarity of the overall distribution structure of shared species, but also into the differences in dominant and rare species, hence allowing additional, valuable insights beyond the capability of more widespread measures.<br> </p>
Data from: Rethinking 'normal': the role of stochasticity in the phenology of a synchronously breeding seabird
1. Phenological changes have been observed in a variety of systems over the past century. There is concern that, as a consequence, ecological interactions are becoming increasingly mismatched in time, with negative consequences for ecological function. 2. Significant spatial heterogeneity (inter-site) and temporal variability (inter-annual) can make it difficult to separate intrinsic, extrinsic, and stochastic drivers of phenological variability. The goal of this study was to understand the timing and variability of breeding phenology of Adélie penguins under fixed environmental conditions, and to use those data to identify a 'null model' appropriate for disentangling the sources of variation in wild populations. 3. Data on clutch initiation were collected from both wild and captive populations of Adélie penguins. Clutch initiation in the captive population was modeled as a function of year, individual, and age to better understand phenological patterns observed in the wild population. 4. Captive populations displayed as much inter-annual variability in breeding phenology as wild populations, suggesting that variability in breeding phenology is the norm and thus may be an unreliable indicator of environmental forcing. The distribution of clutch initiation dates was found to be moderately asymmetric (right skewed) both in the wild and in captivity, consistent with the pattern expected under social facilitation. 5. The role of stochasticity in phenological processes has heretofore been largely ignored. However, these results suggest that inter-annual variability in breeding phenology can arise independent of any environmental or demographic drivers and that synchronous breeding can enhance inherent stochasticity. This complicates efforts to relate phenological variation to environmental variability in the wild. Accordingly, we must be careful to consider random forcing in phenological processes, lest we fit models to data dominated by random noise. This is particularly true for colonial species where breeding synchrony may outweigh each individual's effort to time breeding with optimal environmental conditions. Our study highlights the importance of identifying appropriate null models for studying phenology.
An MRI DICOM data set of the head of a normal male human aged 52
<p>This zip file contains a DICOM data set of magnetic resonance images a normal male mathematics professor aged 52. The experimental subject is the author. The MRI scans are T2 weighted turbo-spin-echo (T2W TSE) and T1 weighted Fast Field Echo (T1W FFE).</p> <p>The subject suffers from a small vertical strabismus (hypertropia), a misalignment of the eyes, which is visible in this data set.</p> <p>The author would like to thank the Radiology Department at the Macclesfield General Hospital for performing the scan.</p> <p> </p>
Data used to evaluate normalization approaces
<p>Data used in "Normalization of direct citations in publication-level networks: Evaluation of six approaches". </p> <p>Related code found in https://github.com/petersjogarde/papers/tree/main/normalization_dc_evaluation. </p>
Normalized subject indexing data of K10plus library union catalog
<p>This dataset contains <strong>normalized subject indexing data of K10plus library union catalog</strong>. It includes links between bibliographic records in K10plus and concepts (subjects or classes) from controlled vocabularies:</p> <ul> <li>kxp-subjects.tsv.gz: TSV format</li> <li>kxp-subjects.nt.gz: RDF format (in form of NTriples)</li> <li>vocabularies.json: information about vocabularies</li> <li>stats.json: statistics (number of records, subjects per vocabulary etc.)</li> </ul> <p>The dataset is based on a K10plus database dump at 2024-12-02.</p> <p><strong>K10plus</strong></p> <p>K10plus is a union catalog of German libraries, run by library service centers BSZ and VZG since 2019. The catalog contains bibliographic data of the majority of academic libraries in Germany. Bibliographic records in K10plus are uniquely identified by a PPN identifier.</p> <p>Several APIs exist to retrieve more data for a record via its PPN, e.g. link into K10plus OPAC:</p> <p>https://opac.k10plus.de/PPNSET?PPN={PPN}</p> <p>Retrieve full record in MARC/XML format:</p> <p>https://unapi.k10plus.de/?format=marcxml&id=opac-de-627:ppn:{PPN}</p> <p>Get formatted citation for display:</p> <p>https://ws.gbv.de/suggest/csl2?citationstyle=ieee&language=en&database=opac-de-627&query=pica.ppn=${PPN}</p> <p>APIs to look up more data from a notation or identifier of a vocabulary can be found in <a href="https://bartoc.org/">https://bartoc.org/</a>. For instance BK class 58.55 can be retrieved via DANTE API:</p> <p>https://api.dante.gbv.de/data?uri=http%3A%2F%2Furi.gbv.de%2Fterminology%2Fbk%2F58.55</p> <p>See vocabularies.json for mapping of vocabulary symbol to BARTOC URI and additional information.</p> <p><strong>Statistics</strong><br>See stats.json for number of records, links, triples and subjects per vocabulary.</p> <p><strong>TSV</strong></p> <p>The .tsv file contains three tab-separated columns:</p> <ol> <li>Bibliographic record identifier (PPN)</li> <li>Vocabulary symbol</li> <li>Notation or identifier in the vocabulary</li> </ol> <p>An example:</p> <p>010000011 bk 58.55<br>010000011 gnd 4036582-7</p> <p>Record 010000011 is indexed with class 58.55 from Basic Classification and with authority record 4036582-7 from Integrated authority file.</p> <p><strong>RDF</strong></p> <p>The NTriples file contains the same information as given in TSV file but identifiers are mapped to URIs. An example:</p> <p><http://uri.gbv.de/document/opac-de-627:ppn:010000011> <http://purl.org/dc/terms/subject> <http://d-nb.info/gnd/4036582-7> .<br><http://uri.gbv.de/document/opac-de-627:ppn:010000011> <http://purl.org/dc/terms/subject> <http://uri.gbv.de/terminology/bk/58.55> .</p> <p><strong>Changelog</strong></p> <ul> <li>2024-12-11: new dump based on K10plus title records extracted by a slightly different workflow.</li> <li>2024-04-05: new dump from end of February 2024. Total number of records decreased by merging of duplicates.</li> <li>2024-01-11: New dump from end of 2023. Added fivs and fivr classification</li> <li>2023-11-01: New dump from end of September.</li> <li>2023-05-07: New dump. Number of records slightly reduced because K10plus cleaned up duplicate records.</li> <li>2023-04-13: New dump, added stats.json</li> <li>2023-01-20: New dump</li> <li>2022-09-11: New dump, fixed PPN URIs and broken UTF-8 encoding</li> <li>2022-08-24: Fixed GND URIs, added LCC and KAB (<a href="https://doi.org/10.5281/zenodo.7018350">https://doi.org/10.5281/zenodo.7018350</a>)</li> <li>2022-08-24: First version (<a href="https://doi.org/10.5281/zenodo.7016626">https://doi.org/10.5281/zenodo.7016626</a>)</li> </ul> <p><strong>License and provenance</strong></p> <p>All data is public domain but references are welcome. See <a href="https://coli-conc.gbv.de/">https://coli-conc.gbv.de/</a> for related projects and documentation.</p> <p>This dataset has been created with public scripts from git repository <a href="https://github.com/gbv/k10plus-subjects">https://github.com/gbv/k10plus-subjects</a>.</p>
Data for 'Normalization procedure for obtaining the local density of states from high-bias scanning tunneling spectroscopy'
<p>This folder contains all the raw data needed to generate the figures in the paper '<em>Normalization procedure for obtaining the local density of states from high-bias scanning tunneling spectroscopy.</em>' The data are seperated by the figures in which they appear, with a text folder in each folder that contains any relevant additional information. </p>
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>
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>
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>
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>
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>
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OpenNeuro
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