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13,017 results for “Positionning”
False Positives Dataset
<p>This dataset contains false positives identified in our study on evaluating SQL queries through Online Judge Systems (OJSs). False positives refer to incorrect queries that were mistakenly judged as correct by the OJS. These false positives reflect the types of errors students may encounter when submitting SQL queries in OJSs, particularly logical errors. The dataset includes various classifications of these logical errors and also provides code for statistical analysis of these classifications. Notably, a single query may exhibit multiple error types, meaning it can fall into several error categories simultaneously.</p>
Fig. 1 in Fig. 1 in Positive association between PTN polymorphisms and schizophrenia in Northeast Chinese Han population.
Fig. 1. Vertigo lilljeborgi distribution map.
Fig. 2 in Fig. 1 in Positive association between PTN polymorphisms and schizophrenia in Northeast Chinese Han population.
Fig. 2. Vertigo genesii distribution map.
Fig. 4 in Fig. 1 in Positive association between PTN polymorphisms and schizophrenia in Northeast Chinese Han population.
Fig. 4. Histograms showing frequency of all assembled records over time.
Fig. 3 in Fig. 1 in Positive association between PTN polymorphisms and schizophrenia in Northeast Chinese Han population.
Fig. 3. Vertigo geyeri distribution map.
Fig. 2 in Fig. 3 in Positive association between PTN polymorphisms and schizophrenia in Northeast Chinese Han population.
Fig. 2. Distribution of suitable habitat reconstructed with MaxEnt, a: LIG, and b: LGM.
Fig. 4 in Fig. 3 in Positive association between PTN polymorphisms and schizophrenia in Northeast Chinese Han population.
Fig. 4. Periodical suitable habitat changes of the macaques from LIG to the 2050s.
Fig. 1 in Positive association between PTN polymorphisms and schizophrenia in Northeast Chinese Han population.
Fig. 1. Map showing the current known global distribution of Scyllaea fulva and Scyllaea pelagica.
Fig. 1 in Positive association between PTN polymorphisms and schizophrenia in Northeast Chinese Han population.
Fig. 1. The study area with the point-count locations (black dots) on Tenerife Island.
DATASET FOR: A multimodal spectroscopic approach combining mid-infrared and near-infrared for discriminating Gram-positive and Gram-negative bacteria
<h4>Description:</h4> <p>This dataset comprises a comprehensive set of files designed for the analysis and 2D correlation of spectral data, specifically focusing on ATR and NIR spectra. It includes MATLAB scripts and supporting functions necessary to replicate the analysis, as well as the raw datasets used in the study. Below is a detailed description of the included files:</p> <ol> <li> <p><strong>Data Analysis</strong>:</p> <ul> <li><strong>File Name</strong>: <code>Data_Analysis.mlx</code></li> <li><strong>Description</strong>: This MATLAB Live Script file contains the main script used for the classification analysis of the spectral data. It includes steps for preprocessing, analysis, and visualization of the ATR and NIR spectra.</li> </ul> </li> <li> <p><strong>2D Correlation Data Analysis</strong>:</p> <ul> <li><strong>File Name</strong>: <code>Data_Analysis_2Dcorr.mlx</code></li> <li><strong>Description</strong>: This MATLAB Live Script file is similar to the primary analysis script but is specifically tailored for performing 2D correlation analysis on the spectral data. It includes detailed steps and code for executing the 2D correlation.</li> </ul> </li> <li> <p><strong>Functions</strong>:</p> <ul> <li><strong>Folder Name</strong>: <code>Functions</code></li> <li><strong>Description</strong>: This folder contains all the necessary MATLAB function files required to replicate the analyses presented in the scripts. These functions handle various preprocessing steps, calculations, and visualizations.</li> </ul> </li> <li> <p><strong>Datasets</strong>:</p> <ul> <li><strong>File Names</strong>: <code>ATR_dataset.xlsx</code>, <code>NIR_dataset.xlsx</code>, <code>Reference_data.csv</code></li> <li><strong>Description</strong>: These Excel files contain the raw spectral data for ATR and NIR analyses, as well as reference datasets. Each file includes multiple sheets with detailed measurements and metadata.</li> </ul> </li> </ol> <h4>Usage Notes:</h4> <ul> <li><strong>Software Requirements</strong>: <ul> <li>MATLAB is required to run the .mlx files and utilize the functions.</li> <li><strong>PLS_Toolbox</strong>: Necessary for certain preprocessing and analysis steps.</li> <li><strong>MIDAS 2010</strong>: Available at <a href="https://www.mathworks.com/matlabcentral/fileexchange/32384-midas-2010" target="_new" rel="noreferrer">MIDAS 2010</a>, required for the 2D correlation analysis.</li> </ul> </li> <li><strong>Replication</strong>: Users can replicate the analyses by running the <code>Data_Analysis.mlx</code> and <code>Data_Analysis_2Dcorr.mlx</code> scripts in MATLAB, ensuring that the <code>Functions</code> folder is in the MATLAB path.</li> <li><strong>Data Handling</strong>: The datasets are provided in .xlsx format, which can be easily imported into MATLAB or other data analysis software.</li> </ul>
In-Car McVAMPIRE – In-Car Multichannel Varying Mouth Position Impulse Response Dataset
<p>This dataset contains impulse responses (IRs) that were recorded in a minivan with eight seats arranged in three seat rows. The IRs were captured with 14 distributed overhead microphones using a mouth simulator at eight passenger seat positions with eleven orientations each. In addition, the dataset contains IRs measured with six built-in car loudspeakers as well as driving noise recordings at various speeds.</p> <p>This dataset supplements the <a href="https://doi.org/10.5281/zenodo.12818781">Anechoic McVAMPIRE</a> dataset which was captured with an identical microphone setup in an anechoic chamber. Both datasets can be used to simulate speech in a car from different seats with different speaker orientations including the loudspeaker-enclosure-microphone (LEM) system under anechoic or realistic, reverberant conditions.</p>
Data from: Spatial variation of soil CO2, CH4 and N2O fluxes across topographical positions in tropical forests of the Guiana Shield in Ecosystems
<p>Data from: Spatial variation of soil CO2, CH4 and N2O fluxes across topographical positions in tropical forests of the Guiana Shield in Ecosystems</p>
Dataset for Interspeech 2018 submission: Singing voice phoneme segmentation by hierarchically inferring syllable and phoneme onset positions
<p>This dataset contains the materials for training, testing the joint and HSMM models mentioned in the paper "<em>Singing voice phoneme segmentation by hierarchically inferring syllable and phoneme onset positions"</em>.</p> <p>The filename list of this dataset can be found in the function <em>get_train_test_recordings_joint()</em> of <em>./general/trainTestSeparation.py</em> file. The dataset contains the Praat TextGrids and .wavs of the variables: <em>train_primary_school, val_primary_school</em> and <em>test_primary_school</em>. For accessing other datasets such as <em>train_nacta_2017, train_nacta</em> and <em>train_sepa</em>, please download them from the links:</p> <p>jingju dataset part1: <a href="https://zenodo.org/record/1185154">https://zenodo.org/record/1185154</a></p> <p>jingju dataset part2: <a href="https://doi.org/10.5281/zenodo.842229">https://doi.org/10.5281/zenodo.842229</a></p> <p>Once you have downloaded these three datasets, you need to set the paths in <em>./general/filePathShared.py</em>.</p> <p>Set <em>path_jingju_dataset</em> to the parent path of these three datasets.</p> <p>Set <em>primarySchool_dataset_root_path</em> to the path of the interspeech2018 dataset (the current dataset).</p> <p>Set <em>nacta_dataset_root_path</em> to the path of the jingju dataset part1.</p> <p>Set <em>nacta2017_dataset_root_path</em> to the path the jingju dataset part2.</p> <p>For more information on this paper, please refer to the Github page: <a href="https://github.com/ronggong/interspeech2018_submission01">https://github.com/ronggong/interspeech2018_submission01</a></p> <p> </p>
Single-particle tracking data for "CTCF sites display cell cycle dependent dynamics in factor binding and nucleosome positioning"
<p>This dataset contains all the raw SPT data reported in "­­­­CTCF sites display cell cycle dependent dynamics in factor binding and nucleosome positioning" in the form of SPT trajectories. The SPT trajectories are provided in two different formats for convenience: a CSV format and a Matlab format. Both formats are readable by Spot-On: https://spoton.berkeley.edu/</p> <p>The SPT data contains "fast tracking" spaSPT data and this data was analyzed using the Matlab version of Spot-On which can be found and downloaded at: https://gitlab.com/tjian-darzacq-lab/spot-on-matlab</p> <p> </p> <p>Full details about the Matlab and CSV formats are provided in the ReadMe files in the associated zip files.</p> <p>Please see the associated manuscript for a detailed description of how the data was acquired and analyzed.</p>
DataSet: Framing side effects positively: a way to enhance analgesia?
<p>Side effects are frequent in pharmacological pain management, potentially preceding analgesia and limiting drug tolerability. Discussing side effects is part of informed consent, yet can favor nocebo effects. This study aimed to test whether a positive suggestion regarding side effects, which could act as reminders of the medication having been absorbed, might favor analgesia in a clinical interaction model.</p> <p> </p> <p>Sixty-six healthy males participated in a study “to validate pupillometry as an objective measure of analgesia”. Participants were unknowingly randomized double-blind to positive vs control information about side effects embedded in a video regarding the study drugs. Sequences of moderately painful heat stimuli applied before and after treatment with diclofenac and atropine served to evaluate analgesia. Atropine was deceptively presented as a co-analgesic, but used to induce side effects. Adverse events (AE) were collected with the General Assessment of Side Effects (GASE) questionnaire prior to the second induced pain sequence. Debriefing fully informed participants regarding the purpose of the study and showed them the two videos.</p> <p> </p> <p>The combination of medication led to significant analgesia, without a between-group difference. Positive information about side effects increased the attribution of AE to the treatment compared to the control information. The total GASE score was correlated with analgesia, i.e., the more AEs reported, the stronger the analgesia. Interestingly, there was a significant between-groups difference on this correlation: the GASE score and analgesia correlated only in the positive information group. This provides evidence for a selective link between AEs and pain relief in the group who received the suggestion that AEs could be taken as a sign “that help was on the way”. During debriefing, 65% of participants said they would prefer to receive the positive message in a clinical context. These results suggest feasibility and validity to investigate such a framing of side effects in a clinical context, for example in patients with chronic pain.</p>
Associated raw data to the PhD thesis: Design and evaluation of a camera-based indoor positioning system for forklift trucks
<p>This is a test data set for marker-based augmented reality algorithms used to locate ground conveyors in an industrial environment. It was recorded in the testing area of the chair fml at TUM to develop and evaluate algorithms for locating forklift trucks in my PhD thesis "Entwicklung und Evaluierung einer kamerabasierten Lokalisierungsmethode für Flurförderzeuge" (see https://mediatum.ub.tum.de/?id=1395267 available in German only).</p>
Associated raw data to the publication: An accurate and efficient camera-based indoor positioning approach for intralogistic environments (MHCL 2015)
<p>This is a test data set for marker-based augmented reality algorithms used to locate ground conveyors in an industrial environment. It was recorded in the testing area of the chair fml at TUM to develop and evaluate algorithms for locating forklift trucks in the publication "An accurate and efficient camera-based indoor positioning approach for intralogistic environments" at MHCL 2015 conference (see https://mediatum.ub.tum.de/1286589 and http://www.fml.mw.tum.de/fml/images/Publikationen/MHCL_2015_jung_submitted.pdf). Originally these files were recorded and used as uncompressed 8-bit grayscale bitmaps. The images were losslessly compressed to png files in order to reduce the test set file size (by approx. factor 3.5)</p>
Substituent position effects on sunscreen photodynamics: a closer look at methyl anthranilate
<p>Towards the development of a <em>bottom-up</em> rationale for sunscreen design, the effects of substituent position on the ultrafast photodynamics of the sunscreen precursor methyl anthranilate (MA, an <em>ortho</em> compound) were evaluated by studying <em>para-</em> and <em>meta-</em>MA in vacuum. Time-resolved ion yield (TR-IY) measurements reveal a long-lived S<sub>1</sub> excited state (≫ 1.2 ns) for <em>para-</em>MA, proposed to be the result of a weakly fluorescent, bound excited state. In the case of <em>meta-</em>MA, TR-IY transients reveal a much faster (~2 ns) excited state relaxation, possibly due to multiple low-lying S<sub>1</sub>/S<sub>0</sub> conical intersections of prefulvenic character. While <em>meta-</em>MA may not be an ideal sunscreen ingredient due to a low ultraviolet absorbance, its comparatively efficient relaxation mechanism may constitute an alternative to common sunscreen relaxation pathways.</p> <p>This archive contains example computational input and output files for both species, including:</p> <ol> <li>TD-DFT files for use with NWChem</li> <li>SA-CASSCF conical intersection search files for use with Gaussian 03</li> <li>CASPT2 files for use with Gaussian 03</li> <li>DFT relaxed geometries for <em>para</em>-MA and <em>meta-</em>MA (<em>e.g</em>. para_0_opt.xyz)</li> <li>SA-CASSCF conical intersection geometries from both molecules as (<em>e.g</em>. p1.xyz)</li> </ol>
Positive and Negative Affect Schedule (PANAS): psychometric properties for the online version in a clinical sample with emotional disorders
<p>This dataset contains sociodemographic and clinical data about 595 patients with emotional disorders that participated in a study with the objective of examining the psychometric properties of the online version of the Positive and Negative Affect Schedule (PANAS) in Spanish clinical sample.</p> <p> </p> <p> </p>
Influence of Dust Particles on Spatial Distributions of Particles and Fluxes in Positive Column of Glow Discharge.
<p><strong>Figures obtained from numerical simulation and discribe the influence of dust particles on spatial distributions of particles and fluxes in positive column of glow discharge. Table contain a list of reactions used in model. Dataset will be published in the article "Influence of Dust Particles on Spatial Distributions of Particles and Fluxes in Positive Column of Glow Discharge" </strong>C. Yuan, R. Tian, D. V. Bogdanov, E. A. Bogdanov, A. A. Kudryavtsev and Z. Zhou</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.