cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/b4n3h3xm3y.1
title: Stress Corrosion Cracking in Ex-service Gas Pipelines; A Comprehensive Study

description: The data presented was developed through analysis of EBSD datasets of SCC cracks taken from active low carbon steel pipelines. Samples were analysed on an FEI Inspect F50 SEM with an EDAX Hikari EBSD detector using OIM Data Collection 7 and analysed using OIM Analysis 7. Samples were obtained from the ND-TD plane to capture the morphology of the cracks and the resulting dataset rotated in software by 90 degrees about the TD direction to align the orientation of the sample to that of the system. The data contains information of grain boundary characteristics exported from standard OIM Analysis functions as well as some mechanical properties conducted on the sectioned steel samples.
DOI: 10.17632/ngfgss3zv2.1
title: Omnibus Survey Results_Arts and Medicine_Group 15

description: Background: We surveyed medical students on various health related questions such as sleep, consumption of energy drinks and fitness as well as their art involvement and interest in art-based therapies. We also surveyed if students were members of MusiCare (local music therapy organization). Our preliminary analysis compares arts participation before and after entering medical school, students’ self-reported stress levels, sleep hygiene and consumption of energy drinks. We hypothesize that students who participated in arts prior and during medical school will have lower self-reported stress levels and healthier stress-coping behaviors. Demographics: Medical and graduate students at the Texas Tech University Health Sciences Center School of Medicine, Lubbock, TX. Respondents include 133 MS1, 61 MS2, 44 MS3, 29 MS4, and 9 graduate students; 183 respondents aged 21-25, 72 26-30, 10 31-35 and 8 36-40; 129 males and 146 females. Data collection: This project used the TTUHSC School of Medicine P3-1 Honors Project Omnibus Survey, an online survey instrument sent to all TTUHSC School of Medicine medical students as well as medical residents, graduate students and faculty members. The survey, which included 26 question sets that branched according to respondent groups, received a total of 329 responses. The questions that our group submitted received 276 responses, a survey response rate of 83.9%. Results: Most students reported a moderate amount of stress on a typical week and acknowledge a high level of stress on a testing wee. About 75% of the students report an increase in stress during exam week. The majority of respondents get 5-9 hours of sleep per night. Approximately a third of the students were involved in arts prior to entering medical school. Students that were involved in arts reported a decrease in their activities during medical school. Factors most cited included lack of a dedicated students organization, colleagues to work with, dedicated space, and time limitation. Only 21 students reported being a member of MusiCare. A quarter of the medical students reported being interested in bedside art-based therapies. Art involvement most cited included activities playing a musical instrument and singing. Others included painting/drawing, dance, photography and writing. Students reported that they would participate in arts if there were organizations or devoted locations to encourage them to do so. Energy drinks consumption by medical student is a rare habit. Less than 10% of the population declares consuming them for studying or the night prior to an exam. Conclusions: We find a gap between the number of musically-oriented medical students and participation in MusiCare. Major contributing factors limiting students’ arts participation are organizational opportunity (e.g. creative writing/improvisation/photography club, etc.) and allocation of spaces. A large proportion of student have an interest in art-based healthcare.
DOI: 10.6073/pasta/d0efa5796fbe2eada016f95889f202fd
title: Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating and Drying Research (DryPEHR): Growing season, chamber-based, CO2 flux data, 2009-2018

description: This drying and warming experiment addresses the following questions: 1) Does ecosystem drying, warming and permafrost thaw cause a net release or uptake of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C that comprises the bulk of the soil C pool influence ecosystem C loss? 3) How do drying and warming affect plant communities and ecosystem properties? We are answering these questions using a combined warming and drying experiment (DryPEHR), which is situated with the Carbon in Permafrost Experimental Heating Research (CiPEHR) project and located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range. Warming treatment here refers to growing season air temperature warming (~1C) using open top chambers (OTC) combined with soil 'warming' using snow fences during the snow covered months. Drying is achieved using an automated pumping system that lowers the water table in the dry plots. Soil warming began in 2008; OTCs and drying in 2011. This data set includes measured values of CO2 fluxes during the growing season.
DOI: 10.17632/2xhxw55wny.1
title: DB Environmental DNA Navarra

description: Raw database with the main information used for an epidemiology study in Navarra region, Spain
DOI: 10.17632/wntw75msnf.1
title: High-throughput sequencing of Epidermolysis Bullosa- and Epidermolytic Ichhyosis-associated genomic regions in immortalised keratinocytes (Ion Torrent amplicon panel)

description: We developed a comprehensive AmpliSeq panel for NGS analysis of EB and EI-asociated genomic loci. These included mutation hotspots and predicted off-target sites for gene editing agents. Some of the data generated was used to analyse the off-target and on-target capabilities of a KRT10-specific TALEN (6.21) in the development of a gene editing therapeutic option for Epidermolytic Ichthyosis. In this study, the KRT10 on-target 17q21.2 (KRT10 exon 6) and 8 in silico predicted off-targets 4q12 (non-coding), 6q21 (non-coding), 6p22.1 (non-coding), 4q31.3 (FHDC1 intron 6), 1p21 (non-coding), 2p25 (non-coding), 5q15 (non-coding), 1p36.3 (non-coding) were analysed. Other genomic loci were included on the amplicon panel. Although these were not analysed in this study, they are included in the provided metadata. NGS data was assessed in immortalised patient keratinocytes (EH31_Unmodified), TALEN-treated immortalised patient keratinocytes (EH31_T6.21) and a single cell clone derived from TALEN-treated immortalised patient keratinocytes (EH31_T6.21_AH2). Other samples were included on the amplicon panel, but are not in the provided metadata. Despite high on-target activity, TALEN 6.21 activity was not observed at off-target sites.
DOI: 10.17632/79gx2sczhb.1
title: High-throughput sequencing of Epidermolysis Bullosa- and Epidermolytic Ichhyosis-associated genomic regions in primary keratinocytes (Ion Torrent amplicon panel)

description: We developed a comprehensive AmpliSeq panel for NGS analysis of EB and EI-asociated genomic loci. These included mutation hotspots and predicted off-target sites for gene editing agents. Some of the data generated was used to analyse the off-target and on-target capabilities of a KRT10-specific TALEN (6.21) in the development of a gene editing therapeutic option for Epidermolytic Ichthyosis. In this study, the KRT10 on-target (17q21.2 (KRT10 exon 6)) and 8 in silico predicted off-targets 4q12 (non-coding), 6q21 (non-coding), 6p22.1 (non-coding), 4q31.3 (FHDC1 intron 6), 1p21 (non-coding), 2p25 (non-coding), 5q15 (non-coding), 1p36.3 (non-coding) were analysed. Other genomic loci were included on the amplicon panel. Although these were not analysed in this study, they are included in the provided metadata. NGS data was assessed in primary patient keratinocytes (Prim_EI_Unmodified) and TALEN-treated primary patient keratinocytes (Prim_EI_T6.21). Other samples were included on the amplicon panel, but are not in the provided metadata. Despite high on-target activity, TALEN 6.21 activity was not observed at off-target sites.
DOI: 10.17632/7gh4f22mmz.1
title: Single Particle Impact Data

description: Raw data for volume loss, velocity calibration, and force calculations for manuscript on erosion and toughening mechanisms of electroless ni-p-nano-NiTi composite coatings
DOI: 10.17632/k498ggvffd.5
title: JOES - Judd Ofelt from Emission Spectra Application Software

description: By using this app please cite article: https://doi.org/10.1016/j.jlumin.2018.09.048 https://www.sciencedirect.com/science/article/pii/S0022231318313292 What is Judd-Ofelt theory? Judd-Ofelt theory has the ability to predict oscillator strengths in both absorption and luminescence, luminescence branching rations, excited state radiative lifetimes, energy-transfer probabilities and estimates of quantum efficiencies by using only three parameters. Its predictive qualities are responsible for its widespread use in all fields regarding luminescence of rare earths. Rapid increase of the importance of the field of lanthanide materials is followed by an increasing trend of number of research papers mentioning the theory. Why only europium? Europium has unique quality that Judd-Ofelt analysis can be done solely from the emission spectrum. For Judd-Ofelt of other elements from the absorption spectrum, look for the application software named RELIC. How to use it? All you need is the output file from the spectrofluorometer or a Origin file containing the spectrum intensity vs wavelength. The help file is contained within the application. Application software JOES is written in Java, and thus works on Windows, Linux or Mac OS. It is licensed under GPLv3. The application does not require installation. For Windows there are binaries available, for other platforms there are jar files. What is the app capable for? Calculate Branching ratios, Calculate Radiative transition probabilities, Calculate Cross-sections, Calculate Barycenters, Calculate Judd-Ofelt parameters Calculate CIE color space coordinates Estimate quantum efficiencies Draw CIE diagram Find Eu site symmetry Contains Refractive index database of 150 materials
DOI: 10.17632/v6ztmhd93c.1
title: Precipitation Clustering MATLAB code

description: Complete MATLAB code for reproducing the clustering methodology from "Informing future risks of record-level rainfall in the United States"
DOI: 10.21227/rcsd-h160
title: MaliciousML: MovieLens dataset attacked with diverse profile injection attacks

description: The MovieLens 1M dataset has been extended introducing diverse shilling profiles to push or nuke a target item. Shilling profiles has been generated using different shilling attack methods: random, average, bandwagon, reverse-bandwagon, love-hate and perfect-knowledge. Each file contains the 1M original MovieLens ratings plus the added votes for the shilling profiles. Each shilling profile rates as many items as the mean number of ratings from each user in the original dataset. The dataset is divided in four quartiles based on the number of rating for the target item.
DOI: 10.3886/e108625v1
title: Unionization rates by Commuting Zone in the United States

description: This is a computation of predicted unionization rates by 1990 Commuting Zones in the United States. The predictions are for the year 2000.<br><br>



















Issue: union status is available in the Current Population Survey
(Outgoing Rotation Groups), but the CPS does not have county identifiers for
the whole population, which are necessary to assign the CZ a CPS respondent
lives in. Moreover, even with access to restricted CPS data files, the CPS is
meant to be representative at the state level, so estimates at the CZ level may
not be accurate. <br><br>

Solution: use the CPS Merged Outgoing Rotation Groups (CPS
MORG) from 2000 to estimate the probability of being unionized by state, sex,
age group and 3-digit industry. Then, use the Quarterly Workforce Indicators (QWI)
to get employment figures by county, sex, age group and 3-digit industry.
Impute the estimated probability from the CPS MORG at the state, sex, age group
and 3-digit industry. Assign each county to its CZ. Then compute weighted
average of probability of being unionized by CZ, where employment counts are
used as weights. <br>
description: Employed individuals in the United States from the private or government sector (excluding self-employed or without pay).<br>
DOI: 10.5518/557
title: Data to support study of Rigidification of a Macrocyclic Tris-Catecholate Scaffold Leads to Electronic Localisation of its Mixed Valent Redox Product

description: The mixed valent radical obtained by oxidation of the platinum complex of a new tris-catecholate macrocycle has a class I, electronically localised structure.
DOI: 10.21227/w13n-ks56
title: MaliciousML: MovieLens dataset attacked with diverse profile injection attacks

description: The MovieLens 1M dataset has been extended introducing diverse shilling profiles to push or nuke a target item. Shilling profiles has been generated using different shilling attack methods: random, average, bandwagon, reverse-bandwagon, love-hate and perfect-knowledge. Each file contains the 1M original MovieLens ratings plus the added votes for the shilling profiles. Each shilling profile rates as many items as the mean number of ratings from each user in the original dataset. The dataset is divided in four quartiles based on the number of rating for the target item.
DOI: 10.5281/zenodo.2579347
title: ConceptNet 5.x Raw Data

description: This archive contains the raw data that ConceptNet 5 is built from. More information about ConceptNet is available at http://conceptnet.io. If you use ConceptNet as part of another work, you must attribute ConceptNet and you must not restrict its license terms. For more license information: https://creativecommons.org/licenses/by-sa/4.0/ ConceptNet has been developed by: * The MIT Media Lab, through various groups at different times: - Commonsense Computing<br> - Software Agents<br> - Digital Intuition * The Commonsense Computing Initiative, a worldwide collaboration with<br> contributions from: - National Taiwan University<br> - Universidade Federal de São Carlos<br> - Hokkaido University<br> - Tilburg University<br> - Nihon Unisys Labs<br> - Dentsu Inc.<br> - Kyoto University<br> - Yahoo Research Japan * Luminoso Technologies, Inc. Significant amounts of data were imported from: * WordNet, a project of Princeton University<br> * Wikipedia and Wiktionary, collaborative projects of the Wikimedia Foundation<br> * Luis von Ahn's "Games with a Purpose"<br> * DBPedia<br> * OpenCyc<br> * JMDict, by Jim Breen ConceptNet also takes input from these sources of distributional word embeddings: ConceptNet takes input from these sources of pre-computed distributional word embeddings: - GloVe: Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014. GloVe: Global Vectors for Word Representation.<br> https://nlp.stanford.edu/projects/glove/ - word2vec: Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Efficient Estimation of Word Representations in Vector Space. In Computing Research Repository. http://dblp.org/rec/bib/journals/corr/abs-1301-3781 - fastText: Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2016. Enriching Word Vectors with Subword Information. http://fasttext.cc<br> Here is a short, incomplete list of people who have made significant<br> contributions to the development of ConceptNet as a data resource, roughly in<br> order of appearance: * Push Singh<br> * Catherine Havasi<br> * Hugo Liu<br> * Hyemin Chung<br> * Robyn Speer<br> * Ken Arnold<br> * Yen-Ling Kuo<br> * Naoki Otani<br>
DOI: 10.5061/dryad.23nt63c/1
title: GPS movement data of Mongolian gazelle

description: GPS tracking data of 22 individuals of Mongolian gazelle monitored between 2014-2017
DOI: 10.5061/dryad.qj76320/1
title: Dryad Item 10.5061/DRYAD.QJ76320/1

description: (:tba)
DOI: 10.5061/dryad.qj76320/2
title: Dryad Item 10.5061/DRYAD.QJ76320/2

description: (:tba)
DOI: 10.5281/zenodo.2579118
title: Segmentation of Nuclei in Histopathology Images by deep regression of the distance map

description: This dataset has been annonced in our accepted paper "Segmentation of Nuclei in Histopathology Images by deep regression of the distance map" in Transcation on Medical Imaging on the 13th of August.<br>
This dataset consists of 50 annotated images, divided into 11 patients.

 

v1.1 (27/02/19): Small corrections to a few pixel that were labelled nuclei but weren't.
description: We would like to thank Ligue Nationnal contre le Cancer for funding my PhD.
DOI: 10.5281/zenodo.2579363
title: Dispersoid Composition in Zirconium Containing Al-Zn-Mg-Cu (AA7010) Aluminium Alloy - Supporting Data

description: Data related to measured dispersoid compositions and calculated dispersoid volume fractions:

Dispersoid Composition in Zirconium Containing Al-Zn-Mg-Cu (AA7010) Aluminium Alloy<br>
A.M. Cassell, J. D. Robson, C. P. Race, A. Eggeman, T. Hashimoto, M. Besel.

Submitted to Acta Materialia.

Datafile of compositions to reproduce Fig.8 in paper (.mat Matlab format)

Datafile of predicted dispersoid volume fractions on which calculations were performed to produce Fig. 10 in paper (comment in datafile provides further details)
description: Otto Fuchs KG are thanked for provision of the materials used in this study and financial support. The EPSRC are thanked for financial support through the associated programme grant LightFORM (EP/R001715/1).  CPR was funded by a University Research Fellowship of the Royal Society. Density functional theory calculations were performed on the Computational Shared Facility of the University of Manchester. The DFT data presented in the paper are available on Zenodo (zenodo.org) doi:10.5281/zenodo.2579165
DOI: 10.5281/zenodo.2579364
title: Dispersoid Composition in Zirconium Containing Al-Zn-Mg-Cu (AA7010) Aluminium Alloy - Supporting Data

description: Data related to measured dispersoid compositions and calculated dispersoid volume fractions:

Dispersoid Composition in Zirconium Containing Al-Zn-Mg-Cu (AA7010) Aluminium Alloy<br>
A.M. Cassell, J. D. Robson, C. P. Race, A. Eggeman, T. Hashimoto, M. Besel.

Submitted to Acta Materialia.

Datafile of compositions to reproduce Fig.8 in paper (.mat Matlab format)

Datafile of predicted dispersoid volume fractions on which calculations were performed to produce Fig. 10 in paper (comment in datafile provides further details)
description: Otto Fuchs KG are thanked for provision of the materials used in this study and financial support. The EPSRC are thanked for financial support through the associated programme grant LightFORM (EP/R001715/1).  CPR was funded by a University Research Fellowship of the Royal Society. Density functional theory calculations were performed on the Computational Shared Facility of the University of Manchester. The DFT data presented in the paper are available on Zenodo (zenodo.org) doi:10.5281/zenodo.2579165
DOI: 10.5517/ccdc.csd.cc14dg66
title: CCDC 1054657: Experimental Crystal Structure Determination

description: Related Article: S. Balachandar, M. Sethuram, P. Muthuraja, M. Dhandapani|2019|Tox.Res.|8|421|doi:10.1039/C8TX00258D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc14kjrz
title: CCDC 1059541: Experimental Crystal Structure Determination

description: Related Article: N. Latha Rani, Shivaprasad Sheety, N. V. Anil Kumar, M. A Sridhar|2018|J.Applic.Chem.|7|59|
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc1kkpqj
title: CCDC 1446978: Experimental Crystal Structure Determination

description: Related Article: N. Latha Rani, Shivaprasad Sheety, N. V. Anil Kumar, M. A Sridhar|2018|J.Applic.Chem.|7|59|
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.14457/tu.the.2014.487
title: แนวทางการบริหารจัดการทรัพยากรกายภาพของชุมชนชาวญี่ปุ่น: กรณีศึกษา สุขุมวิท 33/1

description: ในปัจจุบันกรุงเทพมหานครมีชาวญี่ปุ่นเข้ามาทำงานในประเทศไทยมีสัดส่วนมากในอันดับต้น ๆ ของชาวต่างชาติที่เข้ามาทำงานในประเทศไทย โดยคิดเป็นร้อยละ 23 จากทั้งหมด และมีแนวโน้มเพิ่มขึ้นทุกปี เนื่องด้วยอุปนิสัยของชาวญี่ปุ่นที่มีวัฒนธรรมการอยู่อาศัยแบบรวมกลุ่มกับคนชาติเดียวกัน จึงเกิดการรวมกลุ่มกันของชาวญี่ปุ่นในประเทศไทยขึ้นแห่งแรกในกรุงเทพมหานครในบริเวณซอยสุขุมวิท 33/1 อันเป็นที่รวมของร้านค้าและบริการสำหรับชาวญี่ปุ่น แต่ในปัจจุบันพบว่ามีคนเข้ามาใช้งานน้อยกว่าในอดีต อันเป็นผลมาจากพื้นที่ขาดการบริหารจัดการที่เหมาะสมและเกิดชุมชนใหม่ขึ้นในบริเวณอื่นของกรุงเทพมหานคร จึงสมควรได้รับการปรับปรุงโดย ใช้องค์ความรู้ทางด้านการบริหารจัดการทรัพยากรกายภาพสำหรับพื้นที่ระดับชุมชนโดยงานวิจัยนี้มีวัตถุประสงค์ คือ 1) ศึกษาพฤติกรรมการใช้ชีวิตของคนญี่ปุ่น โดยเฉพาะอย่างยิ่งในกรุงเทพมหานคร ซึ่งมีลักษณะการอยู่อาศัยแบบรวมกลุ่มกันอันเป็นวัฒนธรรมที่มีเอกลักษณ์ 2) ทราบถึงแนวทางการพัฒนาและบริหารจัดการพื้นที่ย่านการค้าตามแนวคิดการบริหารจัดการทรัพยากรกายภาพในระดับของชุมชนขนาดเล็ก 3) เพื่อศึกษาหาแนวทางในการบริหารจัดการพื้นที่ชุมชนญี่ปุ่นบริเวณซอยสุขุมวิท 33/1 ให้เกิดประสิทธิภาพยิ่งขึ้น โดยมีวิธีการศึกษาวิจัยด้วยวิธี 1) สำรวจและศึกษาลักษณะทางกายภาพโดยรวมของโครงการในปัจจุบัน 2) สำรวจความคิดเห็นและพฤติกรรมการใช้พื้นที่ชุมชนของคนญี่ปุ่นโดยใช้แบบสอบถาม 3) ออกแบบลักษณะทางกายภาพของชุมชนใหม่โดยใช้ข้อมูลที่ได้จากการวิจัย และนำไปประเมินผลโดยผู้ใช้งานจริงผลจากการศึกษาสามารถสรุปได้ว่าการออกแบบทรัพยากรกายภาพภายในพื้นที่ย่านการค้าอย่างเหมาะสมกับพฤติกรรมการใช้งานและลักษณะนิสัยของกลุ่มผู้ใช้งาน สามารถช่วยส่งเสริมให้เกิดการใช้งานภายในพื้นที่เพิ่มมากขึ้น ซึ่งสามารถนำข้อมูลที่ได้จากการวิจัยไปประยุกต์ใช้กับชุมชนอื่นๆ เพื่อการพัฒนาปรับปรุงทรัพยากรทางกายภาพให้ดีขึ้นต่อไป