cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/gk7nnm9fxk.1
title: Ngauruhoe crystal geochemistry

description: Geochemical data set for the manuscript "A history of magma mixing and mingling microscopically recorded in monotonous appearing andesites from Ngauruhoe volcano." by Cocker et al.
DOI: 10.5281/zenodo.5647093
title: Reproduction package for paper "How far are we from reproducible research on code smell detection? A systematic literature review"

description: Checklist and data extracted from publications analyzed for "How far are we from reproducible research on code smell detection? A systematic literature review" paper, together with processing scripts and calculations of Cohen's Kappa. Paper that describes details of the data is available here: https://doi.org/10.1016/j.infsof.2021.106783
DOI: 10.5281/zenodo.6818051
title: Summary statistics for "Exome sequencing identifies rare damaging variants in ATP8B4 and ABCA1 as risk factors for Alzheimer's Disease"

description: These are the burden test results (summary statistics) for the publication: "Exome sequencing identifies rare damaging variants in ATP8B4 and ABCA1 as risk factors for Alzheimer’s Disease", Nature Genetics, 2022. <em>Format: tab-separated-value.</em> <em>Fields:</em> <em>gene_stable_id: Ensembl gene id</em> <em>gene_name: standard gene name</em> <em>pvalue: burden test significance (likelihood ratio test, population structure correction based on 6 PCA components)</em> <em>cmac_all: sum of minor allele dosages across all contributing samples and variants</em> <em>group: variant group (LOF, LOF+REVEL&gt;=75, LOF+REVEL&gt;=50, LOF+REVEL&gt;=25, see publication methods for further selection criteria).</em> <em>beta/se: beta/se of logistic ordinal regression (see publication methods). Positive = risk-increasing. Negative = risk-decreasing.</em>
DOI: 10.17632/g76knbxjxn.1
title: Observational data in 8 representative cities of Central-Eastern China

description: Archived here are the input data for MIR calculation in 8 representative cities of Central-Eastern China in the paper: Zhang, Y., Xue, L., Mu, J., Chen, T., Li, H., Gao, J., and Wang W.: Developing the maximum incremental reactivity for volatile organic compounds in major cities of Central-Eastern China, Journal of Geophysical Research, in review, 2022
DOI: 10.17632/tfp9k8cs6f.1
title: Summary of data for estimating regional background ozone in SD

description: The data in this file is for the manuscritpt entitled "Understanding regional background ozone by multiple methods: A case study in the Shandong region, China, 2018-2020" in  JGR-A journal.
DOI: 10.18739/a2x34ms0v
title: Conductivity, Temperature, Pressure (CTD) measurements from cast data taken in the Eurasian and Makarov basins, Arctic Ocean, 2018

description: This archive includes NABOS-II (Nansen and Amundsen Basins Observational System) 2018 summer CTD (conductivity, temperature, and pressure) survey data collected in the eastern Eurasian Basin and Laptev/East Siberian Sea. Each file contains the depth of the CTD cast, as well as the level of pressure, temperature, salinity and the amount of dissolved oxygen measured by the cast. "ctd_survey.zip" is a zipped directory containing all of the files, included for convinience.
DOI: 10.25910/4bsb-1754
title: Knowledge, skills and barriers to evidence-based practice and the impact of a flipped classroom training program for physical therapists: an observational study

description: Objective: To evaluate the knowledge, skills and barriers to evidence-based practice and the impact of evidence-based practice training for physical therapy clinicians. Methods: Physical therapists from a health district in Sydney, Australia were invited to participate. The primary outcome was the Assessing Competency in Evidence-based Medicine scale (range 0-15; 15 is high knowledge and skill) to quantify knowledge and skills. The secondary outcomes were the four subscales of the BARRIERS scale (range 1-4; 4 is high barrier) to quantify barriers. Outcomes were collected at baseline and post an evidence-based practice training program (flipped classroom approach that addressed the core competencies for teaching evidence-based practice) of 3 months duration. Registration: Australian and New Zealand Clinical Trial Register (ACTRN12619000038190). Results: 104 participants completed baseline data and 94 completed post-training data. The mean score for the Assessing Competency in Evidence-based Medicine scale for knowledge and skills at baseline was 9.5 (standard deviation 1.6). The mean BARRIERS subscale scores at baseline were: Healthcare Provider 1.9 (0.5); Research 2.2 (0.5); Setting 2.6 (0.5); and Presentation 2.6 (0.5). On average, training increased the Assessing Competency in Evidence-based Medicine scale score by 0.1 points (95% confidence interval -0.2 to 0.5) and reduced barriers by -0.1 (-0.2 to 0.0; Setting subscale) to -0.2 (-0.3 to -0.1; Healthcare Provider subscale). Conclusions: Physical therapists have knowledge and skill in evidence-based practice that is comparable to other allied health professionals, medical students and medical doctors, and encountered barriers to using high-quality clinical research to guide practice. Training did not change knowledge and skills but did reduce barriers.
DOI: 10.26167/xxwd-j920
title: Native arbuscular mycorrhizal fungi increased resistance of two plantain varieties  (Fhia 21 and Orishele), under water deficit conditions in Cote d’Ivoire

description: A pot experiment was conducted to assess the potential of arbuscular mycorrhizal fungi to improve plantain resistance to water deficit conditions. For this purpose, three sources of inoculants were used: (1) a strain of Glomus clavisporum isolated from plantain rhizosphere in Azaguié region; (2) a fungal complex isolated from plantain rhizosphere in Azaguié (5°38 'N, 4°05' W); (3) a fungal complex isolated from plantain rhizosphere in Bouaflé (6°59 'N, 5°45' W). These inoculants were tested, using the plantain varieties Fhia 21 and Orishele, using three levels of water supply (100, 60 and 30%). Plant growth and others physiological parameters were measured and compared for all the treatments, including the control. Comprehensively, root colonization decreased with the reduction of water supply. The mycorrhizal plants had widest leaves, highest leaf water and chlorophyll contents for any level of water supply. As same, arbuscular mycorrhizal fungi significantly increased soluble sugars and proline contents with water deficit. These results demonstrated that arbuscular mycorrhizal fungi increase plantain photosynthetic activity and thus impact plantain growth in any water supply condition. The proline and soluble sugars are were sensitive molecules to water stress conditions and their productions in the plantain are were improved in presence of mycorrhizal fungi.

description: Une expérience en pot a été réalisée pour évaluer le potentiel des champignons mycorhiziens à arbuscules (CMA) à améliorer la résistance du bananier plantain au déficit hydrique. Pour cela, trois inocula ont été utilisées : (1) une souche de Glomus clavisporum provenant d'Azaguié, (2) un complexe de spores isolé provenant d’Azaguié (5 ° 38 'N - 4 ° 05' O) et (3) un complexe de spores provenant de Bouaflé (6 ° 59 'N - 5 ° 45' O). Ces inocula ont été testés sur les variétés Fhia 21 et Orishele en considérant trois niveaux d’apport d’eau (100, 60 et 30%). La croissance des plants et d'autres paramètres physiologiques ont été mesurés et comparés pour tous les traitements. Il en ressort que la colonisation des racines a diminué avec la réduction de l’apport d’eau. Les plants mycorhizées avaient les feuilles les plus larges, la plus grande teneur en eau et en chlorophylle, quel que soit le niveau d’apport en eau. De même, les CMA ont augmenté de manière significative les sucres solubles et les teneurs en proline dans les situations de déficit hydrique. Ces résultats démontrent que les CMA augmentent l'activité photosynthétique du bananier plantain et ont un impact sur sa croissance dans toutes les conditions d’apport en eau. La proline et les sucres solubles sont des molécules sensibles aux conditions de stress hydrique et leur production dans le bananier plantain sont améliorées en présence de CMA.
DOI: 10.5281/zenodo.3515935
title: Written and spoken digits database for multimodal learning

description: <strong>Database description:</strong> The written and spoken digits database is not a new database but a constructed database from existing ones, in order to provide a ready-to-use database for multimodal fusion. The written digits database is the original MNIST handwritten digits database [1] with no additional processing. It consists of 70000 images (60000 for training and 10000 for test) of 28 x 28 = 784 dimensions. The spoken digits database was extracted from Google Speech Commands [2], an audio dataset of spoken words that was proposed to train and evaluate keyword spotting systems. It consists of 105829 utterances of 35 words, amongst which 38908 utterances of the ten digits (34801 for training and 4107 for test). A pre-processing was done via the extraction of the Mel Frequency Cepstral Coefficients (MFCC) with a framing window size of 50 ms and frame shift size of 25 ms. Since the speech samples are approximately 1 s long, we end up with 39 time slots. For each one, we extract 12 MFCC coefficients with an additional energy coefficient. Thus, we have a final vector of 39 x 13 = 507 dimensions. Standardization and normalization were applied on the MFCC features. To construct the multimodal digits dataset, we associated written and spoken digits of the same class respecting the initial partitioning in [1] and [2] for the training and test subsets. Since we have less samples for the spoken digits, we duplicated some random samples to match the number of written digits and have a multimodal digits database of 70000 samples (60000 for training and 10000 for test). The dataset is provided in six files as described below. Therefore, if a shuffle is performed on the training or test subsets, it must be performed in unison with the same order for the written digits, spoken digits and labels. <strong>Files:</strong> data_wr_train.npy: 60000 samples of 784-dimentional written digits for training; data_sp_train.npy: 60000 samples of 507-dimentional spoken digits for training; labels_train.npy: 60000 labels for the training subset; data_wr_test.npy: 10000 samples of 784-dimentional written digits for test; data_sp_test.npy: 10000 samples of 507-dimentional spoken digits for test; labels_test.npy: 10000 labels for the test subset. <strong>References:</strong> LeCun, Y. & Cortes, C. (1998), “MNIST handwritten digit database”. Warden, P. (2018), “Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition”.
description: {"references": ["LeCun, Y. & Cortes, C. (1998), \"MNIST handwritten digit database\".", "Warden, P. (2018), \"Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition\"."]}
DOI: 10.5281/zenodo.5647092
title: Reproduction package for paper "How far are we from reproducible research on code smell detection? A systematic literature review"

description: Checklist and data extracted from publications analyzed for "How far are we from reproducible research on code smell detection? A systematic literature review" paper, together with processing scripts and calculations of Cohen's Kappa. Paper that describes details of the data is available here: https://doi.org/10.1016/j.infsof.2021.106783
DOI: 10.5281/zenodo.3559480
title: VUDENC - python corpus for word2vec

description: Python corpus for training a word2vec model, and one trained model.
DOI: 10.15129/d7e03984-b43c-4557-b4e4-497f62cd19d4
title: Supplementary material for: "Spatial and temporal evolution of three-dimensional thermovibrational convection in a cubic cavity with various thermal boundary conditions”

description: The files appended with the .cfluid, xlsx and .csv can be visualized on Matlab or MS Excel, Many Figures were produced by visualizing the velocity field in Paraview. Simply click on the .foam files to visualise the data set. Note: Paraview must be installed.
DOI: 10.15139/s3/q10hby
title: Replication Data for: Conference Committee Structure and Majority Party Bias in U.S. States

description: How representative are conference delegations in state legislative chambers? I argue that differing conference rules across state legislative chambers influence majority party control over conference delegations. With an original data set encompassing all state-level conference committees from 2005 to 2016, I compare the observed policy preferences between conference delegation and majority party medians when the majority party unilaterally appoints and when the minority party has influence over conferee selection. My results show that in state legislative chambers where the minority can influence conference appointments, delegations are ideologically biased away from the majority party. These findings underscore how majority parties are limited when minorities have procedural rights.
DOI: 10.5281/zenodo.3228846
title: EMG and Video Dataset for sensor fusion based hand gestures recognition

description: This dataset contains data for hand gestures recognition recorded with 3 different sensors. 


	sEMG: recorded via the Myo armband that is composed of 8 equally spaced non-invasive sEMG sensors that can be placed approximately around the middle of the forearm. The sampling frequency of Myo is 200 Hz. The output of the Myo is a.u 
	DVS: Dynamic Video Sensor which is a very low power event based camera with 128x128 resolution
	DAVIS: Dynamic Video Sensor which is a very low power event based camera with 240x180 resolution that also acquires APS frames.


The dataset<strong> </strong>contains recordings of 10 subjects. Each subject performed 3 sessions, where each of the 5 hand gesture was recorded 5 times, each lasting for 2s. Between the gestures a relaxing phase of 1s is present where the muscles could go to the rest position, removing any residual muscular activation.

Note: We did not upload the raw data (*.aedat) for the DAVIS being those files very heavy. All the information for the sensor has been extracted and can be found in the two files *.npz and *.mat. In case the raw data was needed please contact


	enea.ceolini@ini.uzh.ch
	elisa@ini.uzh.ch


==== README ====

DATASET STRUCTURE:<br>
EMG and DVS recordings<br>
10 subjects<br>
3 sessions for each subject<br>
5 gestures in each session ('pinky', 'elle', 'yo', 'index', 'thumb')

Data name:<br>
subjectXX_sessionYY_ZZZ<br>
XX : [01, 02, 03, 04, 05, 06, 07, 08, 09, 10] <br>
YY : [01, 02, 03]<br>
ZZZ : [emg, ann, dvs, davis]

Data format:<br>
emg: .npy<br>
ann: .npy<br>
dvs: .aedat,.npy<br>
davis: .mat,.npz

DVS<br>
DVS recordings only contain DVS events<br>
- .aedat (raw data): can be imported in Matlab using (https://github.com/inivation/AedatTools/tree/master/Matlab) or in Python with function aedat2numpy in converter.py (https://github.com/Enny1991/hand_gestures_cc19/tree/master/jAER_utils)<br>
- .npy (exported data): numpy.ndarray (xpos, ypos, ts, pol), 2D numpy array containing data of all events, timestamps ts reset to the trigger event (synchronized with the myo), timestamps ts in seconds

 <br>
DAVIS<br>
DAVIS recordings contain DVS events and APS frames.<br>
- .mat (exported data): mat structure, name 'aedat', events are inside aedat.data.polarity (aedat.data.polarity.x,aedat.data.polarity.y,aedat.data.polarity.timeStamp,aedat.data.polarity.polarity), aps frames are inside aedat.data.frame.samples, timestamps are in aedat.data.frame.timeStampStart (start of frame collection) or aedat.data.frame.timeStampEnd (end of frame collection)<br>
- .npz (exported data): npz files: ['frames_time', 'dvs_events', 'frames'], 'dvs_events' is a numpy.ndarray (xpos, ypos, ts, pol), 2D numpy array containing data of all events, timestamps ts reset to the trigger event (synchronized with the myo), timestamps ts in seconds; 'frames' and 'frames_time' are aps data, 'frames' is a list of all the frames, reset at the triggered time, 'frames_time' is the time for each frame, we considered the start timeStamps for each frame.

<br>
DOI: 10.5281/zenodo.4682683
title: Dataset for "Deriving map images of generalised mountain roads with generativeadversarial networks."

description: This is the dataset used in the paper "Deriving map images of generalised mountain roads with generativeadversarial networks.". The data are derived from an extract of the database used to make the topographic maps at the 1:25,000 scale and 1:250,000 map scale at IGN. The base vector data are presented in shapefile_montain_road folder, while constructed images using manually paired data and a reasonable fixe size grid are in roads_images_manually_matched folder.
DOI: 10.5281/zenodo.4682682
title: Dataset for "Deriving map images of generalised mountain roads with generativeadversarial networks."

description: This is the dataset used in the paper "Deriving map images of generalised mountain roads with generativeadversarial networks.". The data are derived from an extract of the database used to make the topographic maps at the 1:25,000 scale and 1:250,000 map scale at IGN. The base vector data are presented in shapefile_montain_road folder, the vector manually matched data are in shapefile_manually_matched folder; finally constructed images using manually paired data and a reasonable fixe size grid are in roads_images_manually_matched folder.
DOI: 10.5281/zenodo.7346309
title: Dataset for "Deriving map images of generalised mountain roads with generativeadversarial networks."

description: This is the dataset used in the paper "Deriving map images of generalised mountain roads with generativeadversarial networks.". The data are derived from an extract of the database used to make the topographic maps at the 1:25,000 scale and 1:250,000 map scale at IGN. The base vector data are presented in shapefile_montain_road folder, the vector manually matched data are in shapefile_manually_matched folder; finally constructed images using manually paired data and a reasonable fixe size grid are in roads_images_manually_matched folder.
DOI: 10.6084/m9.figshare.21601575.v1
title: Supplementary Material for: Ultrathin Bronchoscopy for the Diagnosis of Peripheral Pulmonary Lesions: A Meta-Analysis

description: <b><i>Background:</i></b> Ultrathin bronchoscopy (external diameter, ≤3.5 mm) is useful for the diagnosis of peripheral pulmonary lesions because of its good accessibility. <b><i>Objectives:</i></b> We performed a meta-analysis to investigate the diagnostic yield of ultrathin bronchoscopy for peripheral pulmonary lesions. <b><i>Methods:</i></b> We performed a systematic search of MEDLINE and EMBASE (from inception to May 2021), and meta-analysis was performed using R software. The diagnostic yield was evaluated by dividing the number of successful diagnoses by the total number of lesions, and subgroup analysis was performed to identify related factors. <b><i>Results:</i></b> Nineteen studies with a total of 1,977 peripheral pulmonary lesions were included. The pooled diagnostic yield of ultrathin bronchoscopy was 0.65 (95% confidence interval, 0.60–0.70). Significant heterogeneity was observed among studies (χ<sup>2</sup>, 87.75; <i>p</i> &lt; 0.01; <i>I</i><sup>2</sup>, 79.5%). In a subgroup analysis, ultrathin bronchoscopy with 1.2 mm channel size showed a diagnostic yield of 0.61 (95% confidence interval, 0.53–0.68), whereas ultrathin bronchoscopy with 1.7 mm channel size showed 0.70 (95% confidence interval, 0.66–0.74) (χ<sup>2</sup>, 5.35; <i>p</i> = 0.02). In addition, there was a significant difference in diagnostic yield based on lesion size, histologic diagnosis (malignant vs. benign), bronchus sign, and lesion location from the hilum, whereas no significant difference was found based on lobar location. The overall complication rate of ultrathin bronchoscopy was 2.7% (pneumothorax, 1.1%). <b><i>Conclusions:</i></b> Ultrathin bronchoscopy is an excellent tool for peripheral pulmonary lesion diagnosis with a low complication rate. The diagnostic yield of ultrathin bronchoscopy was significantly higher with larger channel size, which might be attributed to the availability of radial endobronchial ultrasound.
DOI: 10.5281/zenodo.4783264
title: Dataset for "Code Smells Detection Using Artificial Intelligence Techniques: A Business-Driven Systematic Review"

description: Checklist and data extracted from publications analyzed for "Code Smells Detection Using Artificial Intelligence Techniques: A Business-Driven Systematic Review" paper Details regarding this data set can be found in the paper available under: https://doi.org/10.1007/978-3-030-77916-0_12
DOI: 10.5281/zenodo.4783254
title: Dataset for "Code Smells Detection Using Artificial Intelligence Techniques: A Business-Driven Systematic Review"

description: Checklist and data extracted from publications analyzed for "Code Smells Detection Using Artificial Intelligence Techniques: A Business-Driven Systematic Review" paper Details regarding this data set can be found in the paper available under: https://doi.org/10.1007/978-3-030-77916-0_12
DOI: 10.6084/m9.figshare.21601227.v1
title: Supplementary Material for: Systematic Review and Meta-Analysis of the Diagnostic Accuracy of the International Academy of Cytology Yokohama System for Reporting Breast Fine-Needle Aspiration Biopsy in Diagnosing Breast Cancer

description: <b><i>Objectives:</i></b> The primary objective is to determine the accuracy of fine-needle aspiration biopsy (FNAB) in breast lesions reported according to the International Academy of Cytology (IAC) Yokohama system for reporting breast FNAB. The participants include any patient presenting with any breast lesion found suitable for FNAB. The target condition was breast cancer. The secondary objective was to study the proportion of inadequate FNAB in the selected studies. <b><i>Methods:</i></b> PubMed/MEDLINE and Embase were searched for studies having all the following key search terms: Breast AND FNAB AND Diagnostic Accuracy published in the time frame of 2017 to May 16, 2022. The Cochrane and PROSPERO databases, citations of selected articles and articles citing the selected articles were also searched. Studies assessing the diagnostic accuracy of breast FNAB in diagnosing breast cancer, which had at least 75 subjects (and at least 20 subjects each in the benign and malignant FNAB groups), were selected. The reference standard was histopathology (or adequate clinical follow-up for benign disease). Studies were screened independently by two researchers, with a consensus reached among the authors in cases of conflict. The risk of bias and applicability were assessed using the QUADAS-2 tool. Sensitivity and specificity at each diagnostic cut-off were assessed by bivariate generalized linear mixed-model meta-analysis. The area under the receiver operating characteristics curve (AUC) and inadequacy rate were assessed by random-effects meta-analysis. The confidence intervals of sensitivity, specificity, and AUC were examined against a value of 0.95. <b><i>Results:</i></b> Twenty-two studies, all of which were cross-sectional single-gate studies, were selected with a total of 10,886 subjects with a primary breast lesion having concurrent FNAB and reference standard reports. Sensitivity and specificity, with 95% confidence intervals, were 0.978 [0.968, 0.985] and 0.832 [0.76, 0.886] for the diagnostic cut-off of “Atypical considered positive for malignancy,” 0.916 [0.892, 0.935] and 0.983 [0.97, 0.99] for the cut-off of “Suspicious of Malignancy considered positive,” and 0.763 [0.706, 0.812] and 0.999 [0.994, 1] for the cut-off of “Malignant considered positive.” The overall AUC was 0.975 [0.962, 0.984]. FNAB sampling without imaging guidance was associated with lower inadequacy. <b><i>Discussion:</i></b> There is strong evidence that the overall accuracy, sensitivity for “Atypical category considered positive” and specificity when “Suspicious or Malignant categories are considered positive” of FNAB are high when using the categories of the IAC Yokohama Reporting System, demonstrating the usefulness of FNAB in diagnosing breast cancer.