cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3670644
title: Mokilko.coma

description: <strong>Annotated original recordings with transcriptions and translations in German in the exb file format</strong> Corpus EXMARaLDA Corpus Manager data: Mokilko_18: daayi kanê-m-méegútu / Dayi and her father Mokilko_19: tááya kán daayi / The story of Dayi
DOI: 10.5281/zenodo.3670645
title: Mokilko.coma

description: <strong>Annotated original recordings with transcriptions and translations in German in the exb file format</strong> Corpus EXMARaLDA Corpus Manager data: Mokilko_18: daayi kanê-m-méegútu / Dayi and her father Mokilko_19: tááya kán daayi / The story of Dayi
DOI: 10.5281/zenodo.3673895
title: Daayi kanê-m-méegútu - Dayi and her father (Story 18)

description: Eleonore Adwiraah and Herrmann Jungraithmayr; <br> MOKILKO- Erzählungen II<br> Frankfurt am Main 1993 @language-used-1 moz<br> Story name: dayi kane m megutu<br> transcription-name Mokilko_18 <strong>Description for Speaker </strong> Sigle SPK001DNT<br> Sex male<br> Age at time of recording 19<br> Full name Djimé N'Gaba Tchéré<br> id SPK001DNT <strong>Location (type: ) </strong> City Mukulu/Guéra Country Chad<br> Description for Location Description for Communication
DOI: 10.5281/zenodo.3673894
title: Daayi kanê-m-méegútu - Dayi and her father (Story 18)

description: Eleonore Adwiraah and Herrmann Jungraithmayr; <br> MOKILKO- Erzählungen II<br> Frankfurt am Main 1993 @language-used-1 moz<br> Story name: dayi kane m megutu<br> transcription-name Mokilko_18 <strong>Description for Speaker </strong> Sigle SPK001DNT<br> Sex male<br> Age at time of recording 19<br> Full name Djimé N'Gaba Tchéré<br> id SPK001DNT <strong>Location (type: ) </strong> City Mukulu/Guéra Country Chad<br> Description for Location Description for Communication
DOI: 10.21227/c84p-7z84
title: Transfer Learning CNN American Sign Language

description: This dataset contains the images used in the paper "Fine-tuning a pre-trained Convolutional Neural Network Model to translate American Sign Language in Real-time". M. E. Morocho Cayamcela and W. Lim, "Fine-tuning a pre-trained Convolutional Neural Network Model to translate American Sign Language in Real-time," 2019 International Conference on Computing, Networking and Communications (ICNC), Honolulu, HI, USA, 2019, pp. 100-104.
DOI: 10.21227/4333-q252
title: Fake news data

description: This dataset provides a labeled fake news data, which can be used to have a deep study of fake news.
DOI: 10.3886/e117802
title: Australian Social Mobility Using Surnames

description: This is the data and estimations underlying the paper Frontiers of Mobility: Was Australia 1870-2017 a more Socially Mobile Society than England? (Explorations in Economic History)
DOI: 10.21227/qhe2-1z76
title: Singapore Whole sky Nighttime Image SEGmentation Database

description: The SWINSEG dataset contains 115 nighttime images of sky/cloud patches along with their corresponding binary ground truth maps The ground truth annotation was done in consultation with experts from Singapore Meteorological Services. All images were captured in Singapore using WAHRSIS, a calibrated ground-based whole sky imager, over a period of 12 months from January to December 2016. All image patches are 500x500 pixels in size, and were selected considering several factors such as time of the image capture, cloud coverage, and seasonal variations.S. Dev, F. M. Savoy, Y. H. Lee, S. Winkler. Nighttime sky/cloud image segmentation. Proc. IEEE International Conference on Image Processing (ICIP), Beijing, China, Sep. 17-20, 2017.Please cite the above paper if you use the SWINSEG dataset.
DOI: 10.5281/zenodo.3673915
title: Replication package of "Search-based Crash Reproduction using Behavioral Model Seeding"

description: Search-based crash reproduction approaches assist developers during debugging by generating a test case which reproduces a crash given its stack trace. One of the fundamental steps of this approach is creating objects needed to trigger the crash. One way to overcome this limitation is seeding: using information about the application during the search process. With seeding, the existing usages of classes can be used in the<br> search process to produce realistic sequences of method calls which create the required objects. In this study, we introduce behavioral model seeding: a new seeding method which learns class usages from both<br> the system under test and existing test cases. Learned usages are then synthesized in a behavioral model (state machine). Then, this model serves to guide the evolutionary process. To assess behavioral model-seeding, we evaluate it against test-seeding (the state-of-the-art technique for seeding realistic objects) and no-seeding (without seeding any class usage). For this evaluation, we use a benchmark of 122 hard-to-reproduce crashes stemming from six open-source projects. Our results indicate that behavioral model-seeding outperforms both test seeding and no-seeding by a minimum of 6% without any notable negative impact on efficiency.
description: {"references": ["https://arxiv.org/abs/1912.04606", "https://github.com/STAMP-project/Botsing-model-seeding-application"]}
DOI: 10.5281/zenodo.3673916
title: Replication package of "Search-based Crash Reproduction using Behavioral Model Seeding"

description: Search-based crash reproduction approaches assist developers during debugging by generating a test case which reproduces a crash given its stack trace. One of the fundamental steps of this approach is creating objects needed to trigger the crash. One way to overcome this limitation is seeding: using information about the application during the search process. With seeding, the existing usages of classes can be used in the<br> search process to produce realistic sequences of method calls which create the required objects. In this study, we introduce behavioral model seeding: a new seeding method which learns class usages from both<br> the system under test and existing test cases. Learned usages are then synthesized in a behavioral model (state machine). Then, this model serves to guide the evolutionary process. To assess behavioral model-seeding, we evaluate it against test-seeding (the state-of-the-art technique for seeding realistic objects) and no-seeding (without seeding any class usage). For this evaluation, we use a benchmark of 122 hard-to-reproduce crashes stemming from six open-source projects. Our results indicate that behavioral model-seeding outperforms both test seeding and no-seeding by a minimum of 6% without any notable negative impact on efficiency.
description: {"references": ["https://arxiv.org/abs/1912.04606", "https://github.com/STAMP-project/Botsing-model-seeding-application"]}
DOI: 10.5281/zenodo.3673924
title: 'MARSH' - respiratory signal repository

description: This dataset, 'MARSH', includes respiratory signals as part of the study "Fusion enhancement for tracking of respiratory rate through intrinsic mode functions in photoplethysmography."<br> It is meant to support academic research, particularly on algorithm development tools. Contents:<br> - Data.txt (age, gender, height, weight, systole, diastole, [respectively])<br> - ECG.mat (raw ECG data)<br> - ECG_annot.mat (annotations for the R peaks in ECG data)<br> - IP.mat (Raw IP data)<br> - IP_annot.mat (annotations for the local maxima of IP data [end of inspiration phase])<br> - NASAL.mat (Thermistor mask data)<br> - NASAL_annot.mat (annotations for the local maxima of thermistor mask data [end of inspiration phase])<br> - PPG.mat (Raw PPG signal data) When referring to this dataset, please consider including the following reference: Mikko Pirhonen and Vehkaoja Antti, Fusion enhancement for tracking of respiratory rate through intrinsic mode functions in photoplethysmography. Biomedical Signal Processing and Control. 2020
description: {"references": ["Mikko Pirhonen and Vehkaoja Antti, Fusion enhancement for tracking of respiratory rate through intrinsic mode functions in photoplethysmography. Biomedical Signal Processing and Control. 2020"]}
DOI: 10.5281/zenodo.3673923
title: 'MARSH' - respiratory signal repository

description: This dataset, 'MARSH', includes respiratory signals as part of the study "Fusion enhancement for tracking of respiratory rate through intrinsic mode functions in photoplethysmography."<br> It is meant to support academic research, particularly on algorithm development tools. Contents:<br> - Data.txt (age, gender, height, weight, systole, diastole, [respectively])<br> - ECG.mat (raw ECG data)<br> - ECG_annot.mat (annotations for the R peaks in ECG data)<br> - IP.mat (Raw IP data)<br> - IP_annot.mat (annotations for the local maxima of IP data [end of inspiration phase])<br> - NASAL.mat (Thermistor mask data)<br> - NASAL_annot.mat (annotations for the local maxima of thermistor mask data [end of inspiration phase])<br> - PPG.mat (Raw PPG signal data) When referring to this dataset, please consider including the following reference: Mikko Pirhonen and Vehkaoja Antti, Fusion enhancement for tracking of respiratory rate through intrinsic mode functions in photoplethysmography. Biomedical Signal Processing and Control. 2020
description: {"references": ["Mikko Pirhonen and Vehkaoja Antti, Fusion enhancement for tracking of respiratory rate through intrinsic mode functions in photoplethysmography. Biomedical Signal Processing and Control. 2020"]}
DOI: 10.5281/zenodo.3673960
title: PROLIFIC_790157_IRIS_WP2_MAE_protein

description: Technical data regarding the extraction of protein assisted by microwave.
DOI: 10.21227/65zq-mc13
title: modified CASIA

description: The modified CASIA dataset is created for research topics like: perceptual image hash, image tampering detection, user-device physical unclonable function and so on. The ground truth images are taken from the CASIA image tampering detection evaluation (ITDE) v1.0 database (J.Dong, et. al, CASIA image tampering detection evaluation database, ChinaSIP2013), which contains images from eight categories (animal, architecture, article, character, nature, plant, scene and texture) of size 384X256 or 256X384. Instead of directly using the tampered image set from CASIA ITDE v1.0, the tampered versions of those authentic images are selected from CASIA ITDE V2.0, which are more challenging and comprehensive since it considers post-processing like blurring or filtering over the tampered regions to make the tampered images appear realistic to human eyes. For one authentic image, there may be several tampered versions in the CASIA ITDE v2.0 dataset. To increase the diversity, only one tampered version is kept for each authentic image. As a result, the modified CASIA database contains 400 (8 categories X 50 per category) authentic images and their corresponding tampered versions.According to CASIA ITDE v2.0, the tampered images are generated using crop-and-paste operation under Adobe Photoshop on the authentic images, and the tampered regions may have random shapes and different sizes, rotations or distortions. In order to evaluate the proposed system performance over content-preserving manipulations, we enrich the modified CASIA dataset by adding content-preserving manipulations to the authentic images using Matlab and ImageJ. Common image processing techniques like rotation, scaling, filtering and JPEG compression, and unavoidable process/transmission noises like Gaussian, Salt&Pepper and speckle noise are considered. Furthermore, the abovementioned content-preserving manipulations are also applied to the tampered dataset to evaluate if their combination can evade detection. As a result, the modified CASIA database D contains:1) D_au: 400 authentic images in 8 categories, each with 50 images;2) D_tampered: 400 tampered images corresponding to the authentic ones from D_au;3) D_au_cp: 3600 (400x 9) images generated by adding a single content-preserving manipulation (9 types: Gaussian noise, salt&pepper noise, speckle noise, Gaussian filter, motion blur, JPEG compression, gamma correction, rotation and scaling) to every image of D_au;4) D_tampered_cp: 3600 (400x9) tampered images by applying those 9 content-preserving manipulations listed in 3) to the images of Dtampered.To use the dataset, please cite: [1] Y. Zheng, Y. Cao and C. Chang, "A PUF-Based Data-Device Hash for Tampered Image Detection and Source Camera Identification," in IEEE Transactions on Information Forensics and Security, vol. 15, pp. 620-634, 2020.[2]J. Dong, W. Wang and T. Tan, "CASIA Image Tampering Detection Evaluation Database," 2013 IEEE China Summit and International Conference on Signal and Information Processing, Beijing, 2013, pp. 422-426.
DOI: 10.21227/f8ww-jm82
title: Autonomous T-Junction Traffic Light Control System.

description: A Traffic Light Controller PETRI_NET (Finite State Machine) Implementation.An implementation of FSM approach can be followed in systems whose tasks constitute a well-structured list so all states can be easily enumerated. A Traffic light controller represents a relatively complex control function
DOI: 10.6073/pasta/454b258694d6790b2d97a4372f3b2b8c
title: Hubbard Brook Experimental Forest: microbial biomass and activity at Climate Change Across Seasons Experiment (CCASE) plots, 2015

description: This data set includes measurements of microbial biomass and activity measured on the Climate Change Across Seasons Experiment (CCASE) plots in May 2015. Reference (or control) plots are shared with the collaborating Northern Forest DroughtNet experiment. There are six plots total (each 11 x 14m). Two are warmed 5 degrees C throughout the growing season (Plots 3 and 4). Two others are warmed 5 degrees C in the growing season and have snow removed during winter to induce soil freeze/thaw cycles (Plots 5 and 6). Four kilometers (2.5 mi) of heating cable are buried in the soil to warm these four plots. Two additional plots serve as controls for our experiment (Plots 1 and 2). This data set includes measurements of microbial biomass and activity. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
DOI: 10.5281/zenodo.3673977
title: Cultural hitchhiking chapter (data and code)

description: Dataset and code to reproduce figures of the book chapter: <strong>Cultural hitchhiking in the context of the first agricultural groups of South-western Europe: a simulation study</strong>.
DOI: 10.5281/zenodo.3673978
title: Cultural hitchhiking chapter (data and code)

description: Dataset and code to reproduce figures of the book chapter: <strong>Cultural hitchhiking in the context of the first agricultural groups of South-western Europe: a simulation study</strong>.
DOI: 10.5281/zenodo.3673966
title: Comparing Transit Agency Peer Groups using Cluster Analysis-Data

description: This data is from a 2019 analysis of transit ridership in the United States. The purpose of the analysis was to codify US transit agencies into comparable groups using publicly available data. The data is split into dedicated right of way modes, and mixed right of way modes.
DOI: 10.25345/c5kd7k
title: MassIVE MSV000084970 - Chemical and Molecular Effects of Diffusion-Based Iodine Contrast-Enhancing Stains on Fluid-Preserved Avian Specimens
title: House sparrow specimens were stained with four different iodine-based stains to increase contrast in microCT. Proteomic characterization of muscle and bone was performed on contralateral samples (before and after staining). Iodination was detected for all stains. Analysis on samples from the Smithsonian National Museum of Natural History: USNM 657964, USNM 657968, USNM 657963, USNM 657967
DOI: 10.25387/g3.11663970.v2
title: Supplemental Material for Lin, Lin, and Lin, 2020

description: Figure S1 shows 10 linkage groups on genetic map of the F2 population derived from NH80-A x TA95. Figure S2 shows 10 linkage groups on genetic map of the BC1 population derived from NH80-A x WH606. Table S1 displays predicted genotypes of each line under multi-allelic and two-gene models, respectively. Tables S2, S3, and S4 display segregation ratios of male sterility in progeny tests A, B, and C, respectively. File S1 contains the physical positions of polymorphic tags and genotypic data of F<sub>2</sub> population derived from NH80-A × TA95. File S2 contains the physical positions of polymorphic tags and genotypic data of BC<sub>1</sub> population derived from NH80-A × WH606. File S3 contains four genomic DNA sequences of <i>BnRf </i>orthologs.
DOI: 10.25387/g3.11676441
title: Supplemental Material for Louha et al., 2020

description: Supplemental File S1 contains submission script for RepeatModeler. Supplemental File S2 contains primary configuration file used to run GMATA (default_cfg.txt). Supplemental File S3 contains submission script for MAKER. Supplemental File S4 contains MAKER executable file (maker_exe.ctl). Supplemental File S5 contains specifications for downstream filtering of BLAST and Exonerate alignments (maker_bopts.ctl). Supplemental File S6 contains primary configuration of MAKER specific options (maker_opts.ctl). Supplemental File S7 contains scripts for training SNAP. Supplemental File S8 contains scripts for training Augustus. Supplemental File S9 contains scripts for running BLASTP and InterProScan for functional annotation of predicted genes; and scripts for adding the functional annotations to gene annotation files. Supplemental File S10 contains submission script for BUSCO. Supplemental File S11 contains submission scripts for JupiterPlot pipeline. Supplemental File S12 contains submission script for tRNAscan-SE. Supplemental File S13 contains submission script for Infernal. Supplemental File S14 contains classification of predicted transposable elements. Supplemental File S15 contains annotation of microsatellites with their genomic locations. Supplemental File S16 contains percentage of different microsatellites present in the genome. Supplemental File S17 contains frequency of occurrence of microsatellites in each scaffold of the genome. Supplemental File S18 contains the distribution of the length of microsatellites. Supplemental File S19 contains predicted function of annotated genes by BLASTP. Supplemental File S20 contains prediction of protein domains, GO annotations and pathway annotations of predicted genes by InterProScan. Supplemental File S21 contains sequence and structure of tRNAs identified in the song sparrow genome. Supplemental File S22 contains classification of predicted tRNAs. Supplemental File S23 contains classification of different ncRNAs predicted in the genome with Infernal. Supplemental File S24 contains custom repeat library used to screen for repeats in the song sparrow genome. Supplemental Table S1 contains genome sizes of birds related to <i>M. melodia</i>. Supplemental Figure S1 contains the distribution of the percentage of annotated genes with their corresponding AED scores. Supplemental Figure S2 contains the distribution of the top base-pair composition of microsatellite motifs in the <i>M. melodia</i> genome. Supplemental Figure S3 contains comparison of <i>M. melodia</i> genome assembly with genome assemblies of related birds.
DOI: 10.17037/data.00001563
title: ACT and photograph scores dataset

description: An anonymised dataset of 53 children with clubfoot whose parents gave informed consent to participate in a cohort study in one hospital in Harare, Zimbabwe in 2017. The children had undergone Ponseti clubfoot treatment between 2011 and 2013. Dataset contains variables on ACT score and photographic scoring.
DOI: 10.18112/openneuro.ds000201.v1.0.3
title: The Stockholm Sleepy Brain Study: Effects of Sleep Deprivation on Cognitive and Emotional Processing in Young and Old
DOI: 10.21227/fxya-bd26
title: Random finite set based distributed multi-robot SLAM

description: These uploaded video files show the results of distributed multi-vehicle SLAM in three cases:1, simulated scenario;2, UTIAS dataset;3, Victoria park dataset.
DOI: 10.21227/ym20-r826
title: Random finite set based distributed multi-robot SLAM

description: These uploaded video files show the results of distributed multi-vehicle SLAM in three cases:1, simulated scenario;2, UTIAS dataset;3, Victoria park dataset.
DOI: 10.25345/c5fq2j
title: MassIVE MSV000084971 - Allosteric interactions in the parathyroid hormone class B GPCR arrestin complex formation
title: Peptide ligands of class B GPCRs act via a two step binding process, but many gaps remain in our understanding of the essential mechanisms that link the extracellular binding of peptide ligands to intracellular receptor arrestin interaction. Using NMR, crosslinking coupled to mass spectrometry, signaling experiments, and computational approaches on the parathyroid hormone (PTH) type 1 receptor (PTHR), we show that the initial binding of the PTH C terminal part to the receptor constrains the conformation of the flexible N terminal signaling epitope of the PTH before a second binding event takes place. A hot spot PTH residue, His9, that inserts into the transmembrane domain of the PTHR at this second step allosterically engages receptor and arrestin coupling. The mechanism appears to elicit a conformational change in the receptor intracellular loop 3 (ICL3) that permits favorable interactions with the b arrestin finger loop. These results unveil structural determinants for PTHR arrestin complex formation and reveal that the two step binding mechanism proceeds via cooperative fluctuations between the peptide ligand and the receptor, which may be extended to other class B GPCRs.
DOI: 10.15468/kaxo5s
title: On the genus Racekiela in Mexico: molecular and morphological description of Racekiela cresciscrystae n. sp.

description: This dataset contains the digitized treatments in Plazi based on the original journal article Patricia Gómez, José Luis Carballo, Cruz-Barraza, José Antonio, Camacho-Cancino, Mildred (2019): On the genus Racekiela in Mexico: molecular and morphological description of Racekiela cresciscrystae n. sp. JOURNAL OF NATURAL HISTORY 53 (21): 1351-1368, DOI: 10.1080/00222933.2019.1637475
DOI: 10.17632/cxy7s2b6y7.1
title: Data for: Corruption and equity market performance: International comparative evidence

description: The empirical analysis explores annual panel data for 23 developed economies vis-à-vis 21 developing ones, over the period 2002-2017. For each country, we collect the US-denominated price levels of both conventional and Islamic equity market indices, as well as the levels of corruption. Stock market index series are retrieved from the MSCI Barra database, whereas country corruption risk ratings are sourced from the widely adopted International Country Risk Guide (ICRG), which is produced by the Political Risk Services (PRS) Group.