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6,467 results for “process”
Data of "Effects of core electron temperature on the competing processes of whistler and electrostatic instabilities in a beam plasma"
<p>Data of simulation output for "Effects of core electron temperature on the competing processes of whistler and electrostatic instabilities in a beam plasma", including wave field, energy, temperature and particle phase density.</p>
Recycling process (mechanical and hydrometallurgical) adapted to SIBs
Open the record for dataset details and reuse information.
EBD raw and processed Drugs data, generated samples.
Open the record for dataset details and reuse information.
Processed data and model for change detection
Open the record for dataset details and reuse information.
Problem instances for "An Iterated Greedy Matheuristic for Scheduling in Steelmaking-Continuous Casting Process"
<p>A test upload for archiving</p>
Processed gravity data for Evolution of enhanced magmatism at the ultraslow spreading Southwest Indian Ridge between 46°E and 53°E
<p>Mantle Bouguer gravity Anomaly (masked) in Figure 2d. Crustal thickness anomaly (masked) in Figure S2d. Crustal thickness anomaly (combined) in Figure S6.</p>
Processed grid of bathymetry and backscatter data at the Southwest Indian Ridge 50°28'E (AUV, DY40 cruise in 2016)
<p>Bathymetry and backscatter data used for this dataset were recorded during the DY40 cruise aboard R/V Xiangyanghong-10, using High-Resolution Bathymetric Sidescan Sonar System equipped by AUV QianLong-Ⅱ. The cruise took place in 2016 in the Southwest Indian Ridge 50°28'E. The sonar system was operated at 150 Hz with a swath width of 250 m, and the AUV was surveyed at an altitude of ~100 m above the seafloor at a speed of 1-2 kt with a track spacing of 400 m.</p>
Monitorization of chromium sputtering (PVD) process on plastic
<p>The file collets the evolution of process parameters during the deposition of a chromium coating by magnetron sputtering (PVD) on a polycarbonate substrate. The process was carried out at Tekniker research center. The monitorized process parameters are: time, gas flow, chamber pressure, substrate temperature, power, current and voltage of the evaporator.</p>
Processed data for the sRNA landscape chapter
<p><strong>Processed data to be used in analyses related to the sRNA landscape. </strong></p> <p><strong>1) small RNA processed data from stem trichomes</strong>: <a href="https://zenodo.org/api/files/88937ea4-8f58-4970-a931-6f8c8388db87/2020-12-17_11-23_results_stem_trichomes.tar.gz">2020-12-17_11-23_results_stem_trichomes.tar.gz </a></p> <ul> <li>Original small RNA-seq fastq files: available at <a href="https://doi.org/10.5281/zenodo.4105911">https://doi.org/10.5281/zenodo.4105911</a></li> <li>Software: small-rna-seq-pipeline v0.4.4 available at <a href="https://zenodo.org/record/4333786">https://zenodo.org/record/4333786</a></li> </ul> <p> </p> <p><strong>2) small RNA processed data from bald stem, leaf primordium and leaf: </strong></p> <p>xxxx === to be added === xxx</p> <p> </p> <p><strong>3) mRNA-seq processed data (raw and scaled counts) from different tissues (stem trichomes, bald stem, leaf, leaf primordium): </strong> <a href="https://zenodo.org/api/files/1c5ca622-83cf-4ab6-8fc5-7c2f54dc84bb/20201117_snakemake_messenger_rnaseq_trichomes_and_other_tissues.tar.gz">20201117_snakemake_messenger_rnaseq_trichomes_and_other_tissues.tar.gz</a></p> <p>This file was obtained from the following original mRNA-seq fastq files:</p> <ul> <li>Stem trichomes of Moneymaker: <a href="https://doi.org/10.5281/zenodo.3569304">dataset available here</a></li> <li>Stem trichomes of LA0716: <a href="https://doi.org/10.5281/zenodo.3569304">dataset available here</a></li> <li>Stem trichomes of PI127826: <a href="https://doi.org/10.5281/zenodo.3611143">dataset available here</a></li> <li>Bald stems, leaf primordia and leaves of Moneymaker, LA0716 and PI127826: <a href="https://doi.org/10.5281/zenodo.3954272">datasets are available here</a>. Samples S28 to S48 were used. </li> </ul> <p>The pipeline used was <a href="https://github.com/BleekerLab/snakemake_rnaseq/releases/tag/v0.3.4)">Snakemake RNA-seq release 0.3.4</a></p> <p>The file contains:</p> <ul> <li><a href="https://zenodo.org/api/files/10c9d73a-f52b-4923-a793-2fe3326d5587/raw_counts.parsed.tsv?versionId=475a35bb-424d-48f0-bdf8-6ede0455c26e">raw_counts.parsed.tsv</a>: contains the raw counts that can be used for differential expression analysis (e.g. with DESeq2).</li> <li><a href="https://zenodo.org/api/files/10c9d73a-f52b-4923-a793-2fe3326d5587/scaled_counts.tsv?versionId=c1ae1e86-c797-42c8-ac88-f250b97d09b1">scaled_counts.tsv</a>: contains counts that are scaled between samples. This can be used for heatmap creation or PCA analysis for instance. NOT for differential analysis. </li> <li><a href="https://zenodo.org/api/files/10c9d73a-f52b-4923-a793-2fe3326d5587/samples.tsv?versionId=ebefd1b7-50cd-4408-88f6-0770d8540191">samples.tsv</a>.: a file listing the fastq files analysed. </li> <li><a href="https://zenodo.org/api/files/10c9d73a-f52b-4923-a793-2fe3326d5587/config.yaml?versionId=7e47dc9f-7a47-4fbd-9774-7dfa1a46abc1">config.yaml</a>: a file that contains the parameters used when running the pipeline. </li> </ul> <p> </p>
Dataset related to article "Artificial intelligence processing electronic health records to identify commonalities and comorbidities cluster at Immuno Center Humanitas"
<p>This record contains raw data related to article “Artificial intelligence processing electronic health records to identify commonalities and comorbidities cluster at Immuno Center Humanitas”.</p> <p> </p> <p><strong>Background: </strong>Comorbidities are common in chronic inflammatory conditions, requiring multidisciplinary treatment approach. Understanding the link between a single disease and its comorbidities is important for appropriate treatment and management. We evaluate the ability of an NLP-based process for knowledge discovery to detect information about pathologies, patients' phenotype, doctors' prescriptions and commonalities in electronic medical records, by extracting information from free narrative text written by clinicians during medical visits, resulting in the extraction of valuable information and enriching real world evidence data from a multidisciplinary setting.</p> <p><strong>Methods: </strong>We collected clinical notes from the Allergy Department of Humanitas Research Hospital written in the last 3 years and used it to look for diseases that cluster together as comorbidities associated to the main pathology of our patients, and for the extent of prescription of systemic corticosteroids, thus evaluating the ability of NLP-based tools for knowledge discovery to extract structured information from free text.</p> <p><strong>Results: </strong>We found that the 3 most frequent comorbidities to appear in our clusters were asthma, rhinitis, and urticaria, and that 991 (of 2057) patients suffered from at least one of these comorbidities. The clusters which co-occur particularly often are oral allergy syndrome and urticaria (131 patients), angioedema and urticaria (105 patients), rhinitis and asthma (227 patients). With regards to systemic corticosteroid prescription volume by our clinicians, we found it was lower when compared to the therapy the patients followed before coming to our attention, with the exception of two diseases: Chronic obstructive pulmonary disease and Angioedema.</p> <p><strong>Conclusions: </strong>This analysis seems to be valid and is confirmed by the data from the literature. This means that NLP tools could have significant role in many other research fields of medicine, as it may help identify other important, and possibly previously neglected clusters of patients with comorbidities and commonalities. Another potential benefit of this approach lies in its potential ability to foster a multidisciplinary approach, using the same drugs to treat pathologies normally treated by physicians in different branches of medicine, thus saving resources and improving the pharmacological management of patients.</p>
Supplementary processed data for Chandler et al. Single-cell transcriptomics identifies aberrant glomerular angiogenic signalling in the early stages of a murine model of WT1 kidney disease
<p><strong><em>Summary datafiles for Chandler et al.</em></strong></p> <ul> <li>Processed single-cell RNA sequencing data, derived from murine glomeruli (isolated using the dynabead technique) from <em>n = 2</em> wild-type <em>Wt1<sup>+/+</sup></em> (Ctrl) and <em>n = 2</em> mutant <em>Wt1<sup>R394W/+</sup></em> (Mut) littermates of WT1 glomerulopathy, followed by 10x Genomics Chromium v3 platform.</li> <li>Please refer to associated scripts for analysis of the data: <a href="https://github.com/daniyal-jafree1995/collaborations/blob/main/Chandleretal_2022_WT1glomerulopathyscRNAseq.R">https://github.com/daniyal-jafree1995/collaborations/blob/main/Chandleretal_2022_WT1glomerulopathyscRNAseq.R</a> </li> <li>File descriptions as below: <ul> <li>barcodes.tsv.gz - barcodes file required for input to Read10X function in Seurat</li> <li>features.tsv.gz - features file required for input to Read10X function in Seurat</li> <li>matrix.mtx.gz - matrix file required for input to Read10X function in Seurat</li> <li>WT1_scRNAseq.rds - RDS file containing processed and annotated Seurat object for downstream analysis</li> </ul> </li> </ul>
Improvement of Sympathovagal Balance by Regular Exercise May Counteract the Ageing Process. A Study by the Analysis of QT Variability
<p>De Maria B, Lucini D, Gois MO, Catai AM, Perego F, Malacarne M, Pagani M, Porta A, Dalla Vecchia LA. Improvement of Sympathovagal Balance by Regular Exercise May Counteract the Ageing Process. A Study by the Analysis of QT Variability. Front Physiol. 2022 Apr 20;13:880250. doi: 10.3389/fphys.2022.880250. PMID: 35514344; PMCID: PMC9065681.</p> <p>Abstract</p> <p>QT interval (QT) variability analysis provides pathophysiological and prognostic information utilized in cardiac and non-cardiac diseases, complementary to those obtained from the analysis of heart period (HP) variability. An increased QT variability has been associated to a higher risk for cardiac events and poorest prognosis. Autonomic cardiovascular adaptation to internal and external challenges, such those occurring in athletes exposed to high levels of physical stress and in ageing could also be deepen by analyzing QT variability, searching for early prognostic signatures. The aim of the study was to analyze the QT variability and cardiac control complexity in a group of middle-aged half-marathon runners at baseline (B) and at a 10-year follow-up (FU). We found that the overall QT variability decreased at FU, despite the inescapable increase in age (52.3 ± 8.0 years at FU). This change was accompanied by an increase of the HP variability complexity without changes of the QT variability complexity. Of notice, over the years, the group of athletes maintained their regular physical activity by switching to a moderate intensity rather than strenuous. In conclusion, regular and moderate exercise over the years was beneficial for this group of athletes, as reflected by the decreased overall QT variability that is known to be associated to lower cardiovascular risk. The concomitant enhanced cardiac control complexity also suggests a trend opposite to what usually occurs with ageing, resulting in a more flexible cardiac control, typical of younger people.</p>
: The second research task in the project entitled "Tunable liquid metal complexes as catalysts for the model chemical and electrochemical processes" - NCN project OPUS (grant no. 2020/37/B/ST8/00693).
<p>The second research task carried out under the project concerns the synthesis of metallate ionic liquids and the physical and chemical properties characterization. The information relates to study performed for the NCN project OPUS, grant no. 2020/37/B/ST8/00693.</p>
unarXive: All arXiv Publications Pre-Processed for NLP, Including Structured Full-Text and Citation Network (full)
<h2><strong>Description</strong></h2><p>unarXive is a scholarly data set containing publications' structured full-text, annotated in-text citations, linked non-text content (mathematical notation, figure/table captions) and a citation network.</p><p>The data is generated from all LaTeX sources on <a href="https://arxiv.org/">arXiv</a> and therefore of higher quality than data generated from PDF files.</p><p>Typical uses are</p><ul><li>Training of ML models (citation recommendation, summarization, LLMs)</li><li>Citation context analysis</li><li>Bibliographic analyses</li></ul><h2><strong>Access</strong></h2><p>┏━━━━━━━━━━━━━━━━━━━━━━━━━━┓<br>┃ <a href="https://github.com/IllDepence/unarXive/raw/master/doc/unarXive_data_sample.tar.gz"><strong>D O W N L O A D S A M P L E</strong></a> ┃<br>┗━━━━━━━━━━━━━━━━━━━━━━━━━━┛</p><p>To download the whole data set send an access request and note the following:</p><blockquote><p><strong>Note</strong>: this Zenodo record is the "full" version of unarXive, which was generated from all of arXiv.org <i>including non-permissively licensed papers</i>. Make sure that your use of the data is compliant with the paper's licensing terms.¹<br>Alternatively you can use the <a href="https://doi.org/10.5281/zenodo.7752615">unarXive open subset</a>.</p><p>¹ For information on papers' licenses use <a href="https://info.arxiv.org/help/bulk_data/index.html">arXiv's bulk metadata access</a>.</p></blockquote><p>The code for generating the data set is <a href="https://github.com/IllDepence/unarXive">publicly available</a>.</p>
Dataset related to article "Multicentric evaluation of a machine learning model to streamline the radiotherapy patient specific quality assurance process"
<p> This record contains raw data related to article “Multicentric evaluation of a machine learning model to streamline the radiotherapy patient specific quality assurance process"</p> <p><em>Purpose:</em> Patient-specific quality assurance (PSQA) is performed to ensure that modulated treatment plans can be delivered as intended, but constitutes a substantial workload that could slow down the radiotherapy process and delay the start of clinical treatments. In this study, we investigated a machine learning (ML) tree-based ensemble model to predict the gamma passing rate (GPR) for volumetric modulated arc therapy (VMAT) plans.</p> <p><em>Materials and Methods:</em> 5622 VMAT plans from multiple treatment sites were selected from a database of Institution 1 and the ML model trained using 19 metrics. PSQA analyses were performed automatically using criteria 3%/1 mm (global normalization, absolute dose, 10% threshold) and 95% action limit. Model’s performance was evaluated on an out-of-sample test set of Institution 1 and on two independent sets of measurements collected at Institution 2 and Institution 3. Mean absolute error (MAE), as well as the model’s sensitivity and specificity, were computed.</p> <p><em>Results:</em> The model obtained a MAE of 2.33%, 2.54% and 3.91% for the three Institutions, with a specificity of 0.90, 0.90 and 0.68, and a sensitivity of 0.61, 0.25, and 0.55, respectively. Small positive median values of the residuals (i.e., the difference between measurements and predictions) were observed for each Institution (0.95%, 1.66%, and 3.42%). Thus, the model’s predictions were, on average, close to the real values and provided a conservative estimation of the GPR.</p> <p><em>Conclusions</em>: ML models can be integrated into clinical practice to streamline the radiotherapy workflow, but they should be center-specific or thoroughly verified within centers before clinical use.</p> <p> </p>
Unveiling the Sentiments and Opinions of Football Fans towards Video Assistant Referee (VAR) Technology: A Natural Language Processing Analysis
<p>The dataset has been used for the titled "Unveiling the Sentiments and Opinions of Football Fans towards Video Assistant Referee (VAR) Technology: A Natural Language Processing Analysis" provides valuable insights into the attitudes and opinions of football fans towards VAR technology. The dataset is the result of a natural language processing analysis of social media posts and online discussions related to VAR technology. It includes a comprehensive collection of sentiments, opinions, and attitudes expressed by football fans towards VAR technology, and provides researchers and analysts with a wealth of data to help them understand the public perception of this emerging technology in football. It can be used for further analysis in text analytics. </p>
Shadow mask assisted 193 nm Excimer laser processing of commercial Cyclo-Olefin-Copolymer (COC) substrates for low-cost micro-fluidic biosensing devices.
<p>An Abstract submitted to The 24th International Symposium on Laser Precision Microfabrication (LPM2023)</p>
Data about architectural experience influence on other's body expression processing
<p>The folder contains subjective arousal ratings, eye-tracking data (fixation times) and EEG data relative to the processing of emotional body expressions presented at the end of a virtual promenade within different architectural forms.</p> <p>Scripts are also provided for the reproducibility of statistical data analysis.</p> <p>Please refer to the "Readme.txt" file for more detailed information</p>
Process Metrics Collected using Commit Guru
<p>This data contains file-level process metrics collected using the commit guru tool.</p>
MAPK1 mediates C/EBPβ phosphorylation to promote maturation and inhibit EMT process in hESC-derived hepatocytes [CUT&Tag]
GEO Series GSE304638. Homo sapiens. 3 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
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.