cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5155269
title: RPH analysis

description: None
DOI: 10.5281/zenodo.5144802
title: Dataset: Mask R-CNN Based C. Elegans Detection with a DIY Microscope

description: The dataset consists of images of C. elegans in Petri Dish that were captured at a frequency of 1 Hz at 3280 × 2464 pixels via a Raspberry Pi based DIY Microscope. Further details of the recording setup and the dataset can be found in the corresponding article. Up on use, please cite the following article https://doi.org/10.3390/bios11080257 such as: Fudickar, S.; Nustede, E.J.; Dreyer, E.; Bornhorst, J. Mask R-CNN Based C. Elegans Detection with a DIY Microscope. <em>Biosensors</em> <strong>2021</strong>, <em>11</em>, 257. https://doi.org/10.3390/bios11080257 <br>
description: Usage: To train the neural network, the specified folder for the RGB images is checked first with the os library and the paths of all contained jpg files are stored as strings in a list. This list is then iterated and the first image is loaded via the openCV library. The filename of each RGB image contains a number and an ID as unique identifier. This is used to identify the associated labels. For example, image with Filename "img_038_id2.jpg" has the ID 2. In the associated masks folder, all image files are loaded that also have the 038_id2 in the file name, such as "m5_img_038_id2.jpg". So for each RGB image a list of mask images, also loaded with openCV, is kept in temporary memory. All images then run through the sliding window algorithm and are presented to the network in individual parts one after the other.
DOI: 10.5281/zenodo.5144801
title: Dataset: Mask R-CNN Based C. Elegans Detection with a DIY Microscope

description: The dataset consists of images of C. elegans in Petri Dish that were captured at a frequency of 1 Hz at 3280 × 2464 pixels via a Raspberry Pi based DIY Microscope. Further details of the recording setup and the dataset can be found in the corresponding article. Up on use, please cite the following article https://doi.org/10.3390/bios11080257 such as: Fudickar, S.; Nustede, E.J.; Dreyer, E.; Bornhorst, J. Mask R-CNN Based C. Elegans Detection with a DIY Microscope. <em>Biosensors</em> <strong>2021</strong>, <em>11</em>, 257. https://doi.org/10.3390/bios11080257 <br>
description: Usage: To train the neural network, the specified folder for the RGB images is checked first with the os library and the paths of all contained jpg files are stored as strings in a list. This list is then iterated and the first image is loaded via the openCV library. The filename of each RGB image contains a number and an ID as unique identifier. This is used to identify the associated labels. For example, image with Filename "img_038_id2.jpg" has the ID 2. In the associated masks folder, all image files are loaded that also have the 038_id2 in the file name, such as "m5_img_038_id2.jpg". So for each RGB image a list of mask images, also loaded with openCV, is kept in temporary memory. All images then run through the sliding window algorithm and are presented to the network in individual parts one after the other.
DOI: 10.15468/mrc3gs
title: New species of the genus Inversidens Haas, 1911 (Unionoida, Unionidae, Gonideinae) from Jiangxi Province, China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Wu, Ruiwen, Liu, Xiongjun, Kondo, Takaki, Ouyang, Shan, Wu, Xiaoping (2021): New species of the genus Inversidens Haas, 1911 (Unionoida, Unionidae, Gonideinae) from Jiangxi Province, China. ZooKeys 1054: 85-93, DOI: http://dx.doi.org/10.3897/zookeys.1054.69075, URL: http://dx.doi.org/10.3897/zookeys.1054.69075
DOI: 10.6084/m9.figshare.15074544.v3
title: Datasets

description: <b>The effect of ingestion of Red dragon fruit extract on levels of malondialdehyde and superoxide dismutase after strenuous exercise in rats (<i>Rattus norvegicus</i>)</b> Gusbakti R<sup>1</sup>, Syafrudin Ilyas<sup>2</sup>, I Nyoman Ehrich Lister<sup>3</sup>, Chrismis N Ginting<sup>4</sup><b><br></b><b>Background: </b>Prolonged activation of skeletal muscles causes a decrease in the production of force known as fatigue. Exercise with strenuous intensity causes an increase in Reactive Oxygen Species (ROS). An increase in free radicals causes oxidative stress resulting in damage to cell function to mitochondrial dysfunction, and fatigue. This study aimed to determine the antioxidant potential of red dragon fruit (RDF) to delay fatigue due to oxidative stress, which improves cell function in mitochondria. <b>Methodology: </b>The subjects of this study consisted of twenty-five male rats <i>(Rattus norvegicus)</i> aged three months with an average weight of 200 grams. The subjects were further divided into 5 groups consist of group K1 was N.A. (No Activity) but drinking and eating. Group K2 performed strenuous exercise without Red Dragon Fruit (NRDF) treatment. Groups 3, 4, and 5 performed strenuous exercise and were treated with 75 mg kg<sup>-1</sup>.bw, 150 mg kg<sup>-1</sup>.bw, and 300 mg kg<sup>-1</sup>.bw of RDF extract, respectively. The exercise for the rats involved intense swimming for 20 minutes every day, four days a week for 31 days. Malondialdehyde (MDA) was measured with the ELISA method and histopathology (H&E staining) for muscle soleus and lung tissue. <b>Results: </b>Strenuous exercise followed by RDF extract ingestion was compared for fatigue in terms of duration and time; before (24.55±1.38 minute) and after (95.31±7.82 minute) and led to a significant difference of 39% (p&lt;0.01). The study also compared MDA before and after RDF extract ingestion in the K2 vs. the P1 group (p&lt;0.05). At the same time, P2 differed more significantly (p&lt;0.01). This indicated a spread of free radicals and featured histopathological damage of muscle cells. However, ingestion of RDF extract leads to improvement of soleus muscle cells; thus, repairs cell function, delaying fatigue. <b>Conclusion</b><b>: </b>This study confirmed that strenuous exercise which causes an increase in ROS intensifies free radicals with RDF extract ingestion and declines oxidative stress , repairing cell function and delaying fatigue. Keywords: Red Dragon Fruit (RDF), Strenuous exercise, MDA, Improved cell function, Fatigue
DOI: 10.18112/openneuro.ds003743.v1.0.1
title: AutomatedZShimSpinalCord
DOI: 10.48370/ofd/mxxdha/mxd8st
title: HMW_Asplenium_trichomanes_L._H_6265.jpg

description: :unav
DOI: 10.48370/ofd/mxxdha
title: Zanokcica skalna (Asplenium trichomanes L.), 6265

description: Herbarium
DOI: 10.48370/ofd/22tj40/jnjyuw
title: HMW_Asplenium_trichomanes_L._H_6027.jpg

description: :unav
DOI: 10.48370/ofd/22tj40
title: Zanokcica skalna (Asplenium trichomanes L.), 6027

description: Herbarium
DOI: 10.48370/ofd/t8lnaf/4flsyp
title: HMW_Asplenium_trichomanes_L._H_3827.jpg

description: :unav
DOI: 10.48370/ofd/t8lnaf
title: Zanokcica skalna (Asplenium trichomanes L.), 3827

description: Herbarium
DOI: 10.48370/ofd/s7lyvh/r8t7nl
title: HMW_Asplenium_trichomanes_L._H_3648.jpg

description: :unav
DOI: 10.48370/ofd/s7lyvh
title: Zanokcica skalna (Asplenium trichomanes L.), 3648

description: Herbarium
DOI: 10.48370/ofd/7hwo3r/osom9g
title: HMW_Asplenium_ruta-muraria_L._H_0097.jpg

description: :unav
DOI: 10.48370/ofd/7hwo3r
title: Zanokcica murowa (Asplenium ruta-muraria L.), 97

description: Herbarium
DOI: 10.48370/ofd/f9mc2n/qdhbnp
title: HMW_Asplenium_ruta-muraria_L._H_6565.jpg

description: :unav
DOI: 10.48370/ofd/f9mc2n
title: Zanokcica murowa (Asplenium ruta-muraria L.), 6565

description: Herbarium
DOI: 10.48370/ofd/xr2ihi/mjh7w7
title: HMW_Asplenium_ruta-muraria_L._H_6028.jpg

description: :unav
DOI: 10.48370/ofd/xr2ihi
title: Zanokcica murowa (Asplenium ruta-muraria L.), 6028

description: Herbarium
DOI: 10.48370/ofd/gtwuup/clxduz
title: HMW_Asplenium_ruta-muraria_L._H_3938.jpg

description: :unav
DOI: 10.48370/ofd/gtwuup
title: Zanokcica murowa (Asplenium ruta-muraria L.), 3938

description: Herbarium
DOI: 10.48370/ofd/69xtoh/fw8ig7
title: HMW_Asplenium_ruta-muraria_L._H_3682.jpg

description: :unav
DOI: 10.48370/ofd/69xtoh
title: Zanokcica murowa (Asplenium ruta-muraria L.), 3682

description: Herbarium
DOI: 10.48370/ofd/un6mxe/1wncch
title: HMW_Asplenium_ruta-muraria_L._H_3517.jpg

description: :unav
DOI: 10.48370/ofd/un6mxe
title: Zanokcica murowa (Asplenium ruta-muraria L.), 3517

description: Herbarium
DOI: 10.14284/325
title: The COHERENS-SWAN coupled set for wave-current interaction study in the coastal area - code modifications. Internal report

description: This data is the core script of COHERENS-SWAN coupled set. It contains the scripts needed to create the COHERENS-SWAN set. The resulting set can be used to study wave-current interaction in coastal area. The code changes are made to the original code of SWAN version 40.91 and COHERENS version 2.4.1. Therefore, the code changes are ONLY compatible with the SWAN version 40.91 and the COHERENS version 2.4.1. SWAN is a program to simulate spectral wave in nearshore areas. The COHERENS is a program to simulate hydrodynamic system. The resulting coupled set is intended for academic use only.
description: This data contains only the new subroutines and the subroutines which need to be modified. However, in order to obtain a functioning coupled set, the original subroutines of each program (COHERENS and SWAN) should be included in the right order. Each of the above mentioned programs fall under different license terms which can be subject to change by the distributor. To obtain the full code of SWAN visit: http://swanmodel.sourceforge.net/download/download.htm and to obtain the COHERENS full code visit: http://odnature.naturalsciences.be/coherens For further details and instructions refer to the HW_manual.doc.
DOI: 10.48370/ofd/lrdb98/2uegd7
title: HMW_Batrachium_peltatum_Schrank_H_6870.jpg

description: :unav
DOI: 10.48370/ofd/lrdb98
title: Włosienicznik tarczowaty (Batrachium peltatum Schrank), 6870

description: Herbarium
DOI: 10.5281/zenodo.5145656
title: VivesDebate: A New Annotated Multilingual Corpus of Argumentation in a Debate Tournament

description: The application of the latest Natural Language Processing breakthroughs in computational argumentation has shown promising results which have raised the interest in this area of research. However, the available corpora with argumentative annotations are often limited to a very specific purpose or are not of adequate size to take advantage of state-of-the-art deep learning techniques (e.g., deep neural networks). In this paper, we present VivesDebate, a large, richly annotated, and versatile professional debate corpus for computational argumentation research. The corpus has been created from 29 transcripts of a debate tournament in Catalan and has been machine-translated into Spanish and English. The annotation contains argumentative propositions, argumentative relations, debate interactions, and professional evaluations of the arguments and argumentation. The presented corpus can be useful for research on a heterogeneous set of computational argumentation underlying tasks such as argument mining, argument analysis, argument evaluation, or argument generation among others. All this makes VivesDebate a valuable resource for computational argumentation research within the context of massive corpora aimed at Natural Language Processing tasks.
DOI: 10.5517/ccdc.csd.cc24cvn1
title: CCDC 1977603: Experimental Crystal Structure Determination

description: Related Article: Qingjiang Li, Peng-Peng Lin, Long-Ling Huang, Si-Xin Feng, Shuang Yang, Honggen Wang, Zhi-Shu Huang|2021|CSD Communication|||
description: Related Article: Peng-Peng Lin, Long-Ling Huang, Si-Xin Feng, Shuang Yang, Honggen Wang, Zhi-Shu Huang, Qingjiang Li|2021|Org.Lett.|23|3088|doi:10.1021/acs.orglett.1c00767
DOI: 10.5517/ccdc.csd.cc24ls7s
title: CCDC 1984255: Experimental Crystal Structure Determination

description: Related Article: Ahmed H. Tantawy, Xiang-Gao Meng, Adel A. Marzouk, Ali Fouad, Ahmed H. Abdelazeem, Bahaa G. M. Youssif, Hong Jiang, Man-Qun Wang|2021|RSC Advances|11|25738|doi:10.1039/D1RA04061H
DOI: 10.5517/ccdc.csd.cc27n0lj
title: CCDC 2074817: Experimental Crystal Structure Determination

description: Related Article: A.M.Mills, A.L.Spek, R.W.J.M.Hanssen, D.Vogt|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc27nhw9
title: CCDC 2075291: Experimental Crystal Structure Determination

description: Related Article: Fen Wang, Jierui Jing, Yanliang Zhao, Xiaohan Zhu, Xue-Peng Zhang, Liujie Zhao, Panjie Hu, Wei-Qiao Deng, Xingwei Li|2021|Angew.Chem.,Int.Ed.|60|16628|doi:10.1002/anie.202105093
description: Related Article: fen wang|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc27mc8j
title: CCDC 2074187: Experimental Crystal Structure Determination

description: Related Article: Rahul Suresh, Itai Massad, Ilan Marek|2021|Chemical Science|12|9328|doi:10.1039/D1SC02575A
description: Related Article: Rahul Suresh, Itai Massad, Ilan Marek|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc27ntzq
title: CCDC 2075604: Experimental Crystal Structure Determination

description: Related Article: Jiang wenlin|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc27nv2v
title: CCDC 2075607: Experimental Crystal Structure Determination

description: Related Article: Jiang wenlin|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc27lmhz
title: CCDC 2073481: Experimental Crystal Structure Determination

description: Related Article: Eric W. Reinheimer, Marc Fourmigue, Kim R.Dunbar|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc27pcy8
title: CCDC 2076130: Experimental Crystal Structure Determination

description: Related Article: Lin Yang, Bruce M. Foxman|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28dfz3
title: CCDC 2097335: Experimental Crystal Structure Determination

description: Related Article: Brian W. Skelton, Effendy, Allan H. White|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28dmy8
title: CCDC 2097520: Experimental Crystal Structure Determination

description: Related Article: W. Clegg, K. Guille|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28dz2r
title: CCDC 2097834: Experimental Crystal Structure Determination

description: Related Article: Brian W. Skelton, Effendy, Allan H. White|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28fv8v
title: CCDC 2098677: Experimental Crystal Structure Determination

description: Related Article: Arnold L. Rheingold, Linda H. Doerrer and Alice Fan|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28fzyn
title: CCDC 2098822: Experimental Crystal Structure Determination

description: Related Article: Brian W. Skelton, Dieter Wege, Colette G. Sims, David C.R. Hockless|2021|CSD Communication|||
DOI: 10.5061/dryad.jj4g11s/40
title: KRAS_10-5_144145_filtered.csv

description: A gzipped csv documenting the tag, read sequence, and associated qualities of all reads matching the majority read length (documented in read lengths csv) of gDNA 10^-5 sample, replicate1. The header information is in the README.txt file.
DOI: 10.5061/dryad.jj4g11s/41
title: KRAS_10-5_145146_filtered.csv

description: A gzipped csv documenting the tag, read sequence, and associated qualities of all reads matching the majority read length (documented in read lengths csv) of gDNA 10^-5 sample, replicate2. The header information is in the README.txt file.
DOI: 10.5061/dryad.jj4g11s/42
title: KRAS_10-4_144146_filtered.csv

description: A gzipped csv documenting the tag, read sequence, and associated qualities of all reads matching the majority read length (documented in read lengths csv) of gDNA 10^-4 sample, replicate1. The header information is in the README.txt file.
DOI: 10.5061/dryad.jj4g11s/43
title: KRAS_10-4_145147_filtered.csv

description: A gzipped csv documenting the tag, read sequence, and associated qualities of all reads matching the majority read length (documented in read lengths csv) of gDNA 10^-4 sample, replicate2. The header information is in the README.txt file.
DOI: 10.5061/dryad.jj4g11s/44
title: KRAS_10-3_144147_filtered.csv

description: A gzipped csv documenting the tag, read sequence, and associated qualities of all reads matching the majority read length (documented in read lengths csv) of gDNA 10^-3 sample, replicate1. The header information is in the README.txt file.
DOI: 10.5061/dryad.jj4g11s/45
title: KRAS_10-3_145148_filtered.csv

description: A gzipped csv documenting the tag, read sequence, and associated qualities of all reads matching the majority read length (documented in read lengths csv) of gDNA 10^-3 sample, replicate2. The header information is in the README.txt file.
DOI: 10.5061/dryad.jj4g11s/46
title: KRAS_10-2_144148_filtered.csv

description: A gzipped csv documenting the tag, read sequence, and associated qualities of all reads matching the majority read length (documented in read lengths csv) of gDNA 10^-2 sample, replicate1. The header information is in the README.txt file.
DOI: 10.5061/dryad.jj4g11s/47
title: KRAS_10-2_145149_filtered.csv

description: A gzipped csv documenting the tag, read sequence, and associated qualities of all reads matching the majority read length (documented in read lengths csv) of gDNA 10^-2 sample, replicate2. The header information is in the README.txt file.
DOI: 10.5061/dryad.k81584t.1
title: Data from: Sharing of clinical trial data and results reporting practices among large pharmaceutical companies: cross sectional descriptive study and pilot of a tool to improve company practices
DOI: 10.5061/dryad.k81584t.1/1.1
title: GPS Dataset for dryad and BEI Final

description: This is the analyzable dataset for our BMJ paper evaluating data sharing and clinical trial transparency practices of large pharma companies with drugs approved by the FDA in 2015. Data sources include Drugs@FDA, Clinicaltrials.gov (and other trial registries), the medical literature and others (see methods section of published paper for data sources). Variables include the name of the drug, active ingredient, NDA sponsor, FDA approval date, Trial phase, Condition studied, NCT number, etc (see paper methods section for longer variable list).
DOI: 10.5061/dryad.k81584t.2
title: Data from: Sharing of clinical trial data and results reporting practices among large pharmaceutical companies: cross sectional descriptive study and pilot of a tool to improve company practices
DOI: 10.5061/dryad.k81584t.2/1.2
title: GPS Dataset for dryad and BEI Final

description: This is the analyzable dataset for our BMJ paper evaluating data sharing and clinical trial transparency practices of large pharma companies with drugs approved by the FDA in 2015. Data sources include Drugs@FDA, Clinicaltrials.gov (and other trial registries), the medical literature and others (see methods section of published paper for data sources). Variables include the name of the drug, active ingredient, NDA sponsor, FDA approval date, Trial phase, Condition studied, NCT number, etc (see paper methods section for longer variable list).
DOI: 10.5061/dryad.ts45225/10
title: PalmTraits_1.0

description: Dataset with palm traits, i.e. a tab-delimited text file containing taxonomic information (species, genus, tribe, subfamily) together with all trait data
DOI: 10.5061/dryad.ts45225/2
title: ReferenceToSpecies_PalmTraits_1.0

description: References per species, i.e. a tab-delimited text file containing all references that have been used for each species
DOI: 10.5061/dryad.ts45225/6
title: palms_in_tdwg3

description: Presence-absence data of palms at the resolution of botanical countries, data to be used with R script
DOI: 10.5061/dryad.ts45225/8
title: AllReferences_PalmTraits_1.0

description: Full list of references used to compile the data
DOI: 10.5061/dryad.ts45225/9
title: PalmTraitsDemo

description: An R script containing code that allows to combine the PalmTraits 1.0 database with species distribution and phylogenetic information
DOI: 10.17632/2z94cgd34d.1
title: Data for: Expressivist to the Core: Metaaesthetic Subjectivism is Stable and Robust
DOI: 10.17632/77m8fd3382.1
title: Data for: Evaluation of PD-L1 biomarker for immune checkpoint inhibitor (PD-1/PD-L1 inhibitors) treatments for urothelial carcinoma patients: A meta-analysis

description: raw extracted data from all clinical trials
DOI: 10.17632/ktr99fc826.2
title: Loay & Maha Stamps Dataset

description: Recently, with the continuous evolution of new technology the world has faced unusual growth of multimedia data especially in document images. Huge quantities of documents are created and used in many important official organizations. The stamps assure the authenticity of the documents contents. The general objective of this dataset is enabling researchers in the field of pattern recognition to analyze, detect, localize and recognize different types of stamps. The size of the dataset is 48.9 MB. It contains a total of 1557 color stamps samples which are stored as BMP image format. The images of stamps were acquired from documents using a scanner and mobile camera. The cropping process was applied to capture only the stamp area of the whole document, using three applications which are paint, snip and sketch software. For each cropped stamp, eight stamp images are produced from rotating the original one at different angles clockwise. Rotation starts from 5 degrees and increases by 5 degrees until it reaches to 40 degrees. Note the orientation of the original stamp image is with the horizon line, which means that it is at an angle of zero. The stamps have different size, shape, complexity, position, directions and colors. For example, there are six categories of stamp shapes arranged as circle, oval, square, rectangular, triangular and some other irregular shapes. Its worth to mention that the collected dataset may be degraded in quality and resolution and the stamp can be located on a relatively complex background. The dataset was collected from various sources, including official documents from Iraqi educational institutions, documents from syndicates such as teachers, engineers, doctors, pharmacists, Iraqi hospitals, provincial councils, and most Iraqi institutions. The dataset also contains some stamps from other Arab countries.
DOI: 10.17632/vx9n7ckvz9.1
title: Data for: Expression of the autophagy-related protein LC3B in granulosa cells, cumulus cells, and oocyte during atresia of pig antral follicles

description: For a long time, in mammals apoptosis was accepted as the type of programmed cell death (PCD) occurring in ovarian follicles undergoing atresia. However, recent studies have suggested that autophagy may be an alternative mechanism involved in follicle depletion, working independently or in tandem with apoptosis. This research investigated by western blot and immunofluorescence the expression of LC3B protein in freshly collected granulosa cells (GC), cumulus cells (CC), and oocytes to evaluate the involvement of autophagy in the process of antral follicle atresia in sexually mature sows. Moreover, apoptosis was analysed by Annexin V and TUNEL assays in the same cellular cohorts to evaluate the correlation between the two processes. Our immunostaining results show that the autophagy is induced in the majority of GC, CC, and oocytes collected from early and advanced atretic follicles. The quantitative results of western blot analysis demonstrate that a significant (P &lt; 0.05) and progressive increase of expression of the autophagy-related form of the protein (LC3B-II) takes places in these cells compared to healthy ones. Moreover, our data confirm that apoptosis occurs in GC of atretic follicles, thus showing that in pigs, like in rats and humans, apoptosis and autophagy work in GC as combined processes of PCD for antral follicle depletion. Finally, we did not detect apoptosis whereas we detected an overexpression of LC3B-II in CC and oocytes of atretic follicles, thus we suggest that in these cells the two processes work independently, with autophagy acting like a cytoprotective rather than a PCD mechanism.