cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4270149
title: Ultrasound-Guided Percutaneous Irrigation of Rotator Cuff Calcific Tendinopathy (US-PICT): Patient Experience

description: <strong>Purpose: </strong>To assess patients' experience of ultrasound-guided percutaneous irrigation of rotator cuff calcific tendinopathy (US-PICT). <strong>Methods: </strong>Ninety-one patients (58 females; mean age: 50.5 ± 8.3 years) treated by US-PICT (local anesthesia, single-needle lavage, and intrabursal steroid injection) answered to a list of questions regarding their experience of the procedure before treatment, immediately after treatment, and three months later. The Borg CR10 scale was used to evaluate perceived pain, discomfort during anesthetic injection, and anxiety. The Wilcoxon, Spearman's rho, linear regression, and chi-square statistics were used. <strong>Results: </strong>81/91 patients complained mild discomfort during the injection of anesthetics (2, 1-2). Pain scores during US-PICT were very low (0, 0-1), with 70% patients having not experienced pain. After treatment, we found a significant reduction of pain (before: 8, 7-8; 3-month: 3, 1-6; <em>p</em> &lt; .001) and anxiety (before: 5, 2-7; during treatment: 2, 1-7; <em>p</em> = 0.010), with high overall satisfaction (immediately after: 10, 9-10; 3-month: 9, 7-10) and confidence in the possibility of recovery (immediately after: 9, 8-10; 3-month: 10, 8-10), respectively. Treatments performed before US-PICT were not statistically associated with pain relief (<em>p</em> = 0.389) and clinical improvement (<em>p</em> = 0.937). We found a correlation between satisfaction immediately postprocedure and confidence in the possibility of recovery (<em>p</em> = 0.002) and between satisfaction three months after treatment and clinical improvement (<em>p</em> &lt; 0.001) and patients' reminds about the description of the procedure (<em>p</em> = 0.005) and of the potential complications (<em>p</em> = 0.035). <strong>Conclusions: </strong>US-PICT is a mildly painful, comfortable, and well-tolerated procedure, regardless of any previous treatments. Patients' satisfaction is correlated with clinical benefit and full explanation of the procedure and its complications.
DOI: 10.5281/zenodo.4270160
title: T2 mapping of the sacroiliac joints in patients with axial spondyloarthritis

description: <strong>Purpose: </strong>To test whether T2 mapping of the sacro-iliac joints (SIJs) might help identifying patients with spondyloarthritis. <strong>Method: </strong>This study included 20 biologic-naive patients with axial spondyloarthritis (10 females; mean age: 38 ± 9years; range, 19-47) and 27 controls (16 males; mean age = 39 ± 13years; range = 28-71) who prospectively underwent SIJs MRI at 1.5 T, including a multislice multiecho spin-echo sequence. Standard MRIs were reviewed to assess the SIJs according to the Assessment of SpondyloArthritis International Society (ASAS) criteria and SPondyloArthritis Research Consortium of Canada (SPARCC) MRI index. T2 maps obtained from multiecho sequences were used to draw regions of interests in the cartilaginous part of the SIJs. Disease activity was assessed using BASDAI questionnaire. Bland-Altman method, ROC curve analysis, Chi square, Mann-Whitney U, Pearson's and Spearman's correlation coefficient were used for data analysis. <strong>Results: </strong>According to ASAS criteria, MRI was positive for sacroiliitis in 5/20 patients (25 %). Inter-observer reproducibility of T2 values was 87 % (coefficient of repeatability = 7.0; bias = 0.49; p &lt; .001). Mean T2 values of patients (58.5 ± 4.4 ms, range: 52.6-68.2 ms) were significantly higher (p &lt; .001) than those of controls (44.1 ± 6.6 ms, range: 33.6-67.2 ms). A T2 value of 52.51 ms yielded 100 % sensitivity and 91.7 % specificity to differentiate patients from controls. No statistically significant association/correlation was found between T2 values and BASDAI (r=-.026, p = .827), disease duration (r = .024, p = .871), SPARCC (r=-.004, p = .981), ASAS criteria (p = .476), HLA-B27-positivity (p = .139), age (r=-.2.53, p = .891), and gender (p = .404). <strong>Conclusions: </strong>T2 relaxation times of the SIJs were significantly higher in patients than in healthy controls, making this tool potentially helpful to early identify patients with spondyloarthritis.
DOI: 10.5281/zenodo.4270159
title: T2 mapping of the sacroiliac joints in patients with axial spondyloarthritis

description: <strong>Purpose: </strong>To test whether T2 mapping of the sacro-iliac joints (SIJs) might help identifying patients with spondyloarthritis. <strong>Method: </strong>This study included 20 biologic-naive patients with axial spondyloarthritis (10 females; mean age: 38 ± 9years; range, 19-47) and 27 controls (16 males; mean age = 39 ± 13years; range = 28-71) who prospectively underwent SIJs MRI at 1.5 T, including a multislice multiecho spin-echo sequence. Standard MRIs were reviewed to assess the SIJs according to the Assessment of SpondyloArthritis International Society (ASAS) criteria and SPondyloArthritis Research Consortium of Canada (SPARCC) MRI index. T2 maps obtained from multiecho sequences were used to draw regions of interests in the cartilaginous part of the SIJs. Disease activity was assessed using BASDAI questionnaire. Bland-Altman method, ROC curve analysis, Chi square, Mann-Whitney U, Pearson's and Spearman's correlation coefficient were used for data analysis. <strong>Results: </strong>According to ASAS criteria, MRI was positive for sacroiliitis in 5/20 patients (25 %). Inter-observer reproducibility of T2 values was 87 % (coefficient of repeatability = 7.0; bias = 0.49; p &lt; .001). Mean T2 values of patients (58.5 ± 4.4 ms, range: 52.6-68.2 ms) were significantly higher (p &lt; .001) than those of controls (44.1 ± 6.6 ms, range: 33.6-67.2 ms). A T2 value of 52.51 ms yielded 100 % sensitivity and 91.7 % specificity to differentiate patients from controls. No statistically significant association/correlation was found between T2 values and BASDAI (r=-.026, p = .827), disease duration (r = .024, p = .871), SPARCC (r=-.004, p = .981), ASAS criteria (p = .476), HLA-B27-positivity (p = .139), age (r=-.2.53, p = .891), and gender (p = .404). <strong>Conclusions: </strong>T2 relaxation times of the SIJs were significantly higher in patients than in healthy controls, making this tool potentially helpful to early identify patients with spondyloarthritis.
DOI: 10.5281/zenodo.4268901
title: CURE-OR-Sampled: Challenging Unreal and Real Environments for Object Recognition

description: <strong>File descriptions</strong> <strong>train.zip </strong>- the training set <strong>test.zip </strong>- the test set <strong>train.csv</strong> - the ground truth for the training images with the following information: <em>imageID, class, background, perspective, challengeType, challengeLevel</em> <strong>sample_submission.csv</strong> - a sample submission file in the correct format with column headers of <em>imageID </em>and <em>class</em> <strong>Data fields</strong> <strong>imageID </strong>- an anonymous id unique to a given image <strong>class </strong>- the class of the object in the given image: 1-10 1: Canon camera 2: Training marker cone 3: Baseball 4: Pan 5: Toy 6: LG Cell phone 7: Hair brush 8: DYMO Label maker 9: Calcium bottle 10: Shoes <strong>background </strong>- the background of the object 1: 2D white 2: 2D living room 3: 2D kitchen <strong>perspective </strong>- the perspective/orientation of the object 1: Front 2: Left side - 90 degrees 3: Back - 180 degrees 4: Right side - 270 degrees 5: Top <strong>challengeType </strong>- the type of generated challenging conditions 01: No challenge 02: Resize 03: Underexposure 04: Overexposure 05: Gaussian blur 06: Contrast 07: Dirty lens 1 08: Dirty lens 2 09: Salt & pepper noise 10: Grayscale 11: Grayscale resize 12: Grayscale underexposure 13: Grayscale overexposure 14: Grayscale gaussian blur 15: Grayscale contrast 16: Grayscale dirty lens 1 17: Grayscale dirty lens 2 18: Grayscale salt & pepper noise <strong>challengeLevel </strong>- the level of generated challenging conditions 0: No challenge (01) and Grayscale (10) only - no challenge level 1 - 4: the degree of a challenge from least to most For more information about CURE-OR dataset, please refer to the webpage.
description: {"references": ["D. Temel*, J. Lee*, and G. AlRegib, \"CURE-OR: Challenging Unreal and Real Environments for Object Recognition,\" in IEEE International Conference on Machine Learning and Applications (ICMLA), Orlando, FL, Dec. 2018", "D. Temel*, J. Lee*, and G. AlRegib, \"Object Recognition Under Multifarious Conditions: A Reliability Analysis and a Feature Similarity-Based Performance Estimation,\" in IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan, Sep. 2019"]}
DOI: 10.5517/ccdc.csd.cc1zzd0c
title: CCDC 1846453: Experimental Crystal Structure Determination

description: Related Article: Jaclyn L. Lange, Patrick R. W. J. Davey, Michelle T. Ma, Jonathan M. White, Alfred Morgenstern, Frank Bruchertseifer, Philip J. Blower, Brett M. Paterson|2020|Dalton Trans.|49|14962|doi:10.1039/D0DT02673E
DOI: 10.5517/ccdc.csd.cc21y2ps
title: CCDC 1904785: Experimental Crystal Structure Determination

description: Related Article: Jie Liu, Yuhui Wei, Fenlin Bao, Guixiang Li, Huiyan Liu, Haiying Wang|2019|Polyhedron|169|58|doi:10.1016/j.poly.2019.05.003
DOI: 10.14278/rodare.532
title: BGM MLA data from grinding kinetics experiments

description: Datasource from two sets of grinding experiments: - from top size fraction -1600µm+1250µm - from top size fraction -425µm+315µm
DOI: 10.5517/ccdc.csd.cc2659sh
title: CCDC 2030896: Experimental Crystal Structure Determination

description: Related Article: Oliver P. E. Townrow, Cheuk Chung, Stuart A. Macgregor, Andrew S. Weller, Jose M. Goicoechea|2020|J.Am.Chem.Soc.|142|18330|doi:10.1021/jacs.0c09742
DOI: 10.14278/rodare.531
title: BGM MLA data from grinding kinetics experiments

description: Datasource from two sets of grinding experiments: - from top size fraction -1600µm+1250µm - from top size fraction -425µm+315µm
DOI: 10.5517/ccdc.csd.cc2659tj
title: CCDC 2030897: Experimental Crystal Structure Determination

description: Related Article: Oliver P. E. Townrow, Cheuk Chung, Stuart A. Macgregor, Andrew S. Weller, Jose M. Goicoechea|2020|J.Am.Chem.Soc.|142|18330|doi:10.1021/jacs.0c09742
DOI: 10.5517/ccdc.csd.cc2659vk
title: CCDC 2030898: Experimental Crystal Structure Determination

description: Related Article: Oliver P. E. Townrow, Cheuk Chung, Stuart A. Macgregor, Andrew S. Weller, Jose M. Goicoechea|2020|J.Am.Chem.Soc.|142|18330|doi:10.1021/jacs.0c09742
DOI: 10.5281/zenodo.4270123
title: Cartes d'affectations des terres en 2016 et 2019 dans le Sud-Est de la Côte d'Ivoire

description: Ce répertoire est constitué des cartes d'affectations des terres de 2016 et de 2019 dans le Sud-Est de la Côte d'Ivoire. En Côte d’Ivoire, plus de la moitié du couvert forestier (57%) a disparu en un quart de siècle (1990-2015) avec une perte importante de biodiversité. Pour appuyer les politiques de réduction de la déforestation et comprendre les dynamiques en cours, des cartographies fines et régulières des changements d’affectations des terres sont nécessaires. Cependant, ces études sont rarement disponibles sur de grands territoires ou sont parfois obsolètes compte tenu de la rapidité des processus anthropiques en cours. L’objectif de cette étude est de tester une méthodologie de traitement d’images satellitaires Sentinel-2 et d’analyse des changements récents des affectations des terres entre 2016 et 2019 dans trois régions du Sud-Est de la Côte d’Ivoire. Cette méthodologie est basée sur l’utilisation d’images Sentinel-2 à 10 mètres de résolution sur une zone couvrant 22 014 km<sup>2 </sup>avec seize catégories d’affectations des terres. Après prétraitements, les images Sentinel-2 ont été soumises à une analyse automatisée sous R en plusieurs étapes dont la classification supervisée avec l’algorithme <em>Random Forest</em> et l’évaluation de la qualité du modèle de classification. Les cartes présentant des précisions globales satisfaisantes (76% pour la carte de 2016 et 75% pour celle de 2019) ont ensuite servi à produire les cartes des mutations des diverses formations forestières. Ces dernières montrent que le développement des cultures de rente (cacao, hévéa, café et palmier à huile), des cultures et jachères non différenciées ainsi que des infrastructures (habitations et routes), ont conduit à un taux de déforestation de 4,95% par an. Cette étude fourni une compréhension fines et récente des changements d’affectations des terres et contribue aux réflexions sur la mise en place d’un système national de suivi de terres.
DOI: 10.5281/zenodo.4270152
title: Data Set htwddKogRob-TSDReal for Localization and Lifelong Mapping

description: This dataset represents a 4.7 km long tour (odometry path shown in htwddKogRob-TSDReal_path.png) in an environment whose representation (see map htwddKogRob-TSDReal.png | 1px \(\widehat{=}\) 0.1m) is now obsolete. Several static objects have been moved or removed, and there are varying numbers of dynamic obstacles (people walking around). The work was first presented in: A Fuzzy-based Adaptive Environment Model for Indoor Robot Localization Authors: Frank Bahrmann, Sven Hellbach, Hans-Joachim Böhme Date of Publication: 2016/10/6 Conference: Telehealth and Assistive Technology / 847: Intelligent Systems and Robotics Publisher: ACTA Press Additionally, we present a video with the proposed algorithm and an insight of this dataset under: youtube.com/AugustDerSmarte https://www.youtube.com/watch?v=26NBFN_XeQg <strong>Instructions for use</strong> The zip archive contains ascii files, which hold the log files of the robot observations and robot poses. Since this data set was recorded in a real environment, the logfiles hold only the odometry based robot poses. For further information, please refer to the header of the logfiles. To simplify the parsing of the files, you can use these two Java snippets: <strong>Laser Range Measurements:</strong> <pre><code class="language-java"> List&lt;Double&gt; ranges = new ArrayList&lt;&gt;(numOfLaserRays); List&lt;Error&gt; errors = new ArrayList&lt;&gt;(numOfLaserRays); String s = line.substring(4); String delimiter = "()"; StringTokenizer tokenizer = new StringTokenizer(s, delimiter); while(tokenizer.hasMoreElements()){ String[] arr = tokenizer.nextToken().split(";"); boolean usable = (arr[0].equals("0")?false:true); double range = Double.parseDouble(arr[1]); ranges.add(range); errors.add(usable?Error.OKAY:Error.INVALID_MEASUREMENT); }</code></pre> <strong>Poses:</strong> <pre><code class="language-java"> String poseString = line.split(":")[2]; String[] elements = poseString.substring(1, poseString.length()-1).split(";"); double x = Double.parseDouble(elements[0]); double y = Double.parseDouble(elements[1]); double phi = Double.parseDouble(elements[2]);</code></pre>
description: For further questions please contact frank.bahrmann@htw-dresden.de
DOI: 10.5281/zenodo.4270151
title: Data Set htwddKogRob-TSDReal for Localization and Lifelong Mapping

description: This dataset represents a 4.7 km long tour (odometry path shown in htwddKogRob-TSDReal_path.png) in an environment whose representation (see map htwddKogRob-TSDReal.png | 1px \(\widehat{=}\) 0.1m) is now obsolete. Several static objects have been moved or removed, and there are varying numbers of dynamic obstacles (people walking around). The work was first presented in: A Fuzzy-based Adaptive Environment Model for Indoor Robot Localization Authors: Frank Bahrmann, Sven Hellbach, Hans-Joachim Böhme Date of Publication: 2016/10/6 Conference: Telehealth and Assistive Technology / 847: Intelligent Systems and Robotics Publisher: ACTA Press Additionally, we present a video with the proposed algorithm and an insight of this dataset under: youtube.com/AugustDerSmarte https://www.youtube.com/watch?v=26NBFN_XeQg <strong>Instructions for use</strong> The zip archive contains ascii files, which hold the log files of the robot observations and robot poses. Since this data set was recorded in a real environment, the logfiles hold only the odometry based robot poses. For further information, please refer to the header of the logfiles. To simplify the parsing of the files, you can use these two Java snippets: <strong>Laser Range Measurements:</strong> <pre><code class="language-java"> List&lt;Double&gt; ranges = new ArrayList&lt;&gt;(numOfLaserRays); List&lt;Error&gt; errors = new ArrayList&lt;&gt;(numOfLaserRays); String s = line.substring(4); String delimiter = "()"; StringTokenizer tokenizer = new StringTokenizer(s, delimiter); while(tokenizer.hasMoreElements()){ String[] arr = tokenizer.nextToken().split(";"); boolean usable = (arr[0].equals("0")?false:true); double range = Double.parseDouble(arr[1]); ranges.add(range); errors.add(usable?Error.OKAY:Error.INVALID_MEASUREMENT); }</code></pre> <strong>Poses:</strong> <pre><code class="language-java"> String poseString = line.split(":")[2]; String[] elements = poseString.substring(1, poseString.length()-1).split(";"); double x = Double.parseDouble(elements[0]); double y = Double.parseDouble(elements[1]); double phi = Double.parseDouble(elements[2]);</code></pre>
description: For further questions please contact frank.bahrmann@htw-dresden.de
DOI: 10.7277/zmhx-hs63
title: Versatile Colloidal Syntheses of Metal Chalcogenide Nanoparticles from Elemental Precursors using Amine-Thiol Chemistry

description: Colloidal metal chalcogenide nanoparticles have emerged as a promising hydrazine-free route for the fabrication of solution processed electronic devices. While a wide variety of synthetic pathways have been developed for these nanomaterials, typical colloidal syntheses rely on the use of metal salts as precursors, which contain anionic impurities such as halides, nitrates, acetates, and so forth, that may incorporate and alter the electrical properties of the targeted nanoparticles. In this report, the recent advances in amine-thiol chemistry and its unique ability to dissolve pure metals, chalcogens, and metal chalcogenides is expanded upon for the fabrication of metal chalcogenide nanoparticles. Alkylammonium metal thiolate species are easily formed upon addition of monoamine and dithiol to elemental Cu, In, Ga, Sn, Zn, Se, or metal chalcogenides such as Cu2S and Ag2S. These species were then used directly for the synthesis of colloidal nanoparticles without the need for any additional purification. The thermal decomposition pathway of one such representative alkylammonium metal thiolate species was studied, verifying that only metal chalcogenides and volatile byproducts are formed, providing a flexible route to compositionally uniform, phase pure, and anionic impurity-free colloidal nanoparticles. Synthetic methods were developed from these precursors to yield pure phase colloidal nanoparticles of binary, ternary, and quaternary materials and their alloys including In2S3, (InxGa1–x)2S3, CuInS2, CuIn(SxSe1–x)2, Cu(InxGa1–x)S2, Cu2ZnSnS4, and AgInS2. Successful synthesis with various experimental methods such as heat up, hot injection, and microwave assisted solvothermal reactions were also demonstrated, showing the flexibility and greater scope for this new synthesis route.
DOI: 10.17632/n7p4m547hf.1
title: Data for: A 90-day drinking water study in mice to characterize early events in the cancer mode of action of 1,4-dioxane
DOI: 10.17632/gky22nh7xp.1
title: Source code for: A Negative Transfer Approach to Person Re-Identification via Domain Augmentation

description: We provide the source code of this paper for reproducibility.
DOI: 10.18112/openneuro.ds002152.v1.0.4
title: DMCC13benchmark
DOI: 10.6084/m9.figshare.13224587
title: Consistent effects of pesticides on community structure and ecosystem function in freshwater systems

description: Data associated with 'Consistent effects of pesticides on community structure and ecosystem function in freshwater systems" published in <i>Nature Communications</i><i><br></i>All pertinent information regarding experimental design is contained within the manuscript. <br>Data has been uploaded in an excel file. First tab include the data, and the second tab includes the metadata.
DOI: 10.6084/m9.figshare.13226906.v1
title: Data set used for clustering analysis in PAST

description: Campanian-Paleocene Chondrichthyans and Localities.
DOI: 10.6084/m9.figshare.13226906
title: K-Pg chondrichthyan assemblages from Maryland: Paleobiogeographical significance and conservation needs [Data set used for clustering analysis in PAST]

description: We downloaded all occurrences of Campanian-Paleocene chondrichthyans from The Paleobiology Database (&gt;3,000 records) and converted this to a presence-absence matrix consisting of 198 localities and 113 genera in Excel.We then added 24 localities from the literature representing chondrichthyan faunas from Campanian-Paleocene localities, particularly those relevant to the K-Pg (latest Maastrichtian, early Danian), and ensuring that the Severn Formation was represented by multiple localities, not just lumped into a single geological unit..We then added data from our site. The final matrix consisted of 223 localities x 113 genera.The data set was analyzed in PAST 4.03 (Hammer et al., 2001) using paired grouping and single linkage clustering analyses.
DOI: 10.6084/m9.figshare.13226906.v3
title: K-Pg chondrichthyan assemblages from Maryland: Paleobiogeographical significance and conservation needs [Data set used for clustering analysis in PAST]

description: We downloaded all occurrences of Campanian-Paleocene chondrichthyans from The Paleobiology Database (&gt;3,000 records) and converted this to a presence-absence matrix consisting of 198 localities and 113 genera in Excel.We then added 24 localities from the literature representing chondrichthyan faunas from Campanian-Paleocene localities, particularly those relevant to the K-Pg (latest Maastrichtian, early Danian), and ensuring that the Severn Formation was represented by multiple localities, not just lumped into a single geological unit..We then added data from our site. The final matrix consisted of 223 localities x 113 genera.The data set was analyzed in PAST 4.03 (Hammer et al., 2001) using paired grouping and single linkage clustering analyses.
DOI: 10.6084/m9.figshare.13226906.v2
title: K-Pg chondrichthyan assemblages from Maryland: Palebiogeographical significance and conservation needs [Data set used for clustering analysis in PAST]

description: We downloaded all occurrences of Campanian-Paleocene chondrichthyans from The Paleobiology Database (&gt;3,000 records) and converted this to a presence-absence matrix consisting of 198 localities and 113 genera in Excel.We then added 24 localities from the literature representing chondrichthyan faunas from Campanian-Paleocene localities, particularly those relevant to the K-Pg (latest Maastrichtian, early Danian), and ensuring that the Severn Formation was represented by multiple localities, not just lumped into a single geological unit..We then added data from our site. The final matrix consisted of 223 localities x 113 genera.The data set was analyzed in PAST 4.03 (Hammer et al., 2001) using paired grouping and single linkage clustering analyses.
DOI: 10.6084/m9.figshare.13225274
title: Supplem Table S1. correlations chrebp genenetwork..xls

description: Correlations chrebp genenetwork
DOI: 10.6084/m9.figshare.13225274.v1
title: Supplem Table S1. correlations chrebp genenetwork..xls

description: Correlations chrebp genenetwork
DOI: 10.5281/zenodo.4270214
title: Model Validation Framework Evaluation Result

description: CSV Files with the results of the Model Validation Framework Evaluation
DOI: 10.5281/zenodo.4270213
title: Model Validation Framework Evaluation Result

description: CSV Files with the results of the Model Validation Framework Evaluation
DOI: 10.34740/kaggle/dsv/1640348
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.6084/m9.figshare.13228997
title: COVID-19 vaccine acceptance Peru

description: Data base for COVID-19 vaccine acceptance in Peru
DOI: 10.21227/rssc-8g31
title: test mean

description: merge hui and lucile best sumbissions