cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3743347
title: Higher Education & Research in Africa – the stakeholders

description: <strong>List of stakeholders and research-related institutions in Africa and abroad. The list is continuously being updated and displayed at </strong><strong>https://info.africarxiv.org/stakeholders/</strong><strong>. </strong> Correspondence: (JH, JO, NK) info@africarxiv.org The list contains stakeholders and practitioners in Higher Education and [Open] Science on the African continent. We herewith want to encourage closer collaboration between African and non-African institutions and visualize existing ones to encourage more of that. Listed stakeholders include: African research institutions and academies Institutions that work towards research and HE capacity building in Africa Non-academic institutions that work closely with universities and research institutions in Africa Universities have not been added to the list. We are aware that several lists on African universities already exist and seek to collaborate to add those to future versions of this dataset. <strong>To suggest changes and additions to this dataset please enter directly to the Google Form at </strong><strong>https://forms.gle/97nzXuggTHodDimC6</strong>. An interactive map of the stakeholders in this list can be viewed at https://kumu.io/access2perspectives/he-research-in-africa <br> <br>
DOI: 10.5281/zenodo.3743348
title: Higher Education & Research in Africa – the stakeholders

description: <strong>List of stakeholders and research-related institutions in Africa and abroad. The list is continuously being updated and displayed at </strong><strong>https://info.africarxiv.org/stakeholders/</strong><strong>. </strong> Correspondence: (JH, JO, NK) info@africarxiv.org The list contains stakeholders and practitioners in Higher Education and [Open] Science on the African continent. We herewith want to encourage closer collaboration between African and non-African institutions and visualize existing ones to encourage more of that. Listed stakeholders include: African research institutions and academies Institutions that work towards research and HE capacity building in Africa Non-academic institutions that work closely with universities and research institutions in Africa Universities have not been added to the list. We are aware that several lists on African universities already exist and seek to collaborate to add those to future versions of this dataset. <strong>To suggest changes and additions to this dataset please enter directly to the Google Form at </strong><strong>https://forms.gle/97nzXuggTHodDimC6</strong>. An interactive map of the stakeholders in this list can be viewed at https://kumu.io/access2perspectives/he-research-in-africa <br> <br>
DOI: 10.5281/zenodo.3743360
title: Recurring Twitter trending topics in Italy between 2019 and 2020

description: This small dataset provides a list of 3695 hashtags which appeared to be trending topics in Italy on Twitter between 2019-01-01 and 2020-03-31 (459 days) at least 4 times. Moreover, a list of recurring trending topics naming a day of the week is provided, filterable by whether the hashtag is a "hashtag appointment" or just a non-Twitter event or work which happens to contain a name of the week. The list shows that Italian users appear to share some global celebrations like #MondayMotivation, but no equivalents for hashtags like #ThrowbackThursday although #buonsabato is popular and some users attempted to launch some like #SabatoArtistico.
DOI: 10.5281/zenodo.3743361
title: Recurring Twitter trending topics in Italy between 2019 and 2020

description: This small dataset provides a list of 3695 hashtags which appeared to be trending topics in Italy on Twitter between 2019-01-01 and 2020-03-31 (459 days) at least 4 times. Moreover, a list of recurring trending topics naming a day of the week is provided, filterable by whether the hashtag is a "hashtag appointment" or just a non-Twitter event or work which happens to contain a name of the week. The list shows that Italian users appear to share some global celebrations like #MondayMotivation, but no equivalents for hashtags like #ThrowbackThursday although #buonsabato is popular and some users attempted to launch some like #SabatoArtistico.
DOI: 10.18434/m31517
title: 25-Hydroxyvitamin D Isomerizes to Pre-25-hydroxyvitamin D in Solution: Considerations for Calibration in Clinical Measurements

description: Reference standards for the vitamin D metabolites 25-hydroxyvitamin D3, 25-hydroxyvitamin D2, and 3-epi-25-hydroxyvitamin D3 were evaluated using liquid chromatography (LC) with ultraviolet (UV) absorbance and mass spectrometric (MS) detection to assess purity. The chromatograms for solutions of all three 25(OH)D compounds, obtained using a pentafluorophenyl (PFP) stationary phase, revealed peaks that increased in area over time and had MS spectra that were nearly identical to the parent compound, indicating isomers had formed in solution that were unrelated to the reference standard purity. However, when the purity evaluations were completed with a cyanopropyl stationary phase, the isomeric products coeluted with the parent compounds and were not observable. The rates of formation of the isomeric products were found to increase when heated and were confirmed to be pre-25-hydroxyvitamin D compounds using spectral information from both MS detection and nuclear magnetic resonance (NMR) spectroscopy. The rates of conversion of 25(OH)D3 to pre-25(OH)D3 was studied in solutions of ethanol and bovine serum albumin (BSA) in phosphate-buffered saline (PBS). The solutions prepared with BSA/PBS were found to form twice as much pre-25(OH)D3 as the solutions in ethanol. The isomerization of 25(OH)D in solution has implications for calibration of 25(OH)D in clinical measurements, which are discussed.
DOI: 10.21227/78yt-m043
title: DeepWiPHY: Synthetic and real-world IEEE 802.11ax OFDM symbol dataset

description: This dataset is associated with the paper entitled "DeepWiPHY: Deep Learning-Based IEEE 802.11ax Receiver". It has synthetic and real-word IEEE 802.11ax OFDM symbols. The synthetic dataset has around 110 million OFDM symbols and the real-world dataset has more than 14 million OFDM symbols. Our comprehensive synthetic dataset has specifically considered typical indoor channel models and RF impairments. The real-world dataset was collected under a wide range of signal-to-noise ratio (SNR) levels and at various locations in a large office. To create this real-world dataset, we built a passive sniffing-based data collection testbed with a commercial AP, a Samsung mobile phone and two USRPs.
DOI: 10.5281/zenodo.3733196
title: Skin Self-Examination by Melanoma Survivors and Their Skin Check Partners

description: Melanoma survivors with localized disease and their skin check partners enrolled in two sequential randomized control trials of skin self-examination (SSE) training. In Phase 1, the pair read a workbook in the office, took it home and had quarterly total body skin examinations with a dermatologist for two years. In Phase 2, the materials were mailed to the pairs. SSE knowledge, self-efficacy (confidence), performance (frequency and extent), and appropriate identification of concerning moles were compared between the two phases.
DOI: 10.5281/zenodo.3733197
title: Skin Self-Examination by Melanoma Survivors and Their Skin Check Partners

description: Melanoma survivors with localized disease and their skin check partners enrolled in two sequential randomized control trials of skin self-examination (SSE) training. In Phase 1, the pair read a workbook in the office, took it home and had quarterly total body skin examinations with a dermatologist for two years. In Phase 2, the materials were mailed to the pairs. SSE knowledge, self-efficacy (confidence), performance (frequency and extent), and appropriate identification of concerning moles were compared between the two phases.
DOI: 10.15468/hwiezs
title: On some species of Apatetica WESTWOOD (Coleoptera: Staphylinidae: Apateticinae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Assing, Volker (2018): On some species of Apatetica WESTWOOD (Coleoptera: Staphylinidae: Apateticinae). Beiträge zur Entomologie = Contributions to Entomology 68 (2): 347-359, DOI: 10.21248/contrib.entomol.68.2.347-359
DOI: 10.3886/e100532v3-23567
title: The Influence of Cultural Factors on Trust in Automation

description: Human interaction with automation is a complex process that requires both skilled operators and complex system designs to effectively enhance overall performance. Although automation has successfully managed complex systems throughout the world for over half a century, inappropriate reliance on automation can still occur, such as the recent malfunction in Tesla autopilot mechanisms that resulted in a fatality. Research has shown that trust, as an intervening variable, is critical to the development of appropriate reliance on automated systems. Because automation inevitably involves uncertainty, trust in automation is related to a calibration between a user’s expectations and the capabilities of automation. Prior studies suggest that trust is dynamic and influenced by both endogenous (e.g., cultural diversity) and exogenous (e.g., system reliability) variables. While a large body of work on trust in automation has accumulated over the past two decades, a standard measure has remained elusive, with research relying on short, idiosyncratically worded questionnaires. These challenges are exacerbated for measuring trust in automation in non-Western cultures because most research has been limited to North America and Western Europe. <br><br>To determine how cultural factors affect various aspects of trust in and reliance on automation, the present research has developed a cross-cultural trust questionnaire and an air traffic control simulator that incorporates a variety of scenarios identified from a review of relevant literature. The measures and tasks have been validated by a crowdsourcing system (Amazon Mechanical Turk), as well as through experimental studies conducted in the U.S., Turkey, and Taiwan, with approximately 1000 participants. Over various phases of data collection and statistical evaluations, a final 18-item Universal Trust in Automation (UTA) instrument was identified that satisfies the stringent tests (including reliability and validity tests and measurement invariance analysis), indicating that the instrument is robust across national cultures and is effective in capturing both predispositions to trust and trust that evolves through use of a system. The findings reveal substantial cultural differences in human trust in automation, which have a significant impact on the design, implementation, and evaluation of automated systems to make them more trustworthy in determining the appropriate trust calibration for optimized reliance across cultures.
description: Presence of Common Scales: A Likert-type scale was used
description: cognitive assessment test; on-site questionnaire; self-enumerated questionnaire; web-based survey;
description: Smallest Geographic Unit: Country
description: Multistage, Corss-cultural data collection, Clustered sampling design
DOI: 10.3886/e118750
title: Ethiopia Industrial Park Skills Assessment

description: The SKY skills assessment is a state-of-the art employer-employee-trainer survey that collects information on how employees’ skills match with the skills that employers and trainers perceive to be important. This survey instrument is unique in that it allows several assessors to evaluate the garment production skills of workers and combine these assessment scores with individual workers’ self-reported history of skills development and attitudes towards work, as well as the characteristics of the factory. The study began in 2018 and included 588 individuals from 19 factories in the Hawassa and Bole Lemi industrial parks. <br>
DOI: 10.3886/e118750v1
title: Ethiopia Industrial Park Skills Assessment

description: The SKY skills assessment is a state-of-the art employer-employee-trainer survey that collects information on how employees’ skills match with the skills that employers and trainers perceive to be important. This survey instrument is unique in that it allows several assessors to evaluate the garment production skills of workers and combine these assessment scores with individual workers’ self-reported history of skills development and attitudes towards work, as well as the characteristics of the factory. The study began in 2018 and included 588 individuals from 19 factories in the Hawassa and Bole Lemi industrial parks. <br>
DOI: 10.5281/zenodo.3743287
title: Stem trichome mRNA-Seq from lycopersicum x habrochaites crosses (Parents and F1)

description: <strong>Stem trichome mRNA-Seq datasets from different crossing materials.</strong> Genetic material Obtained from ENZA Zaden. The pollen from <em>S. habrochaites</em> LA1777 or PI127826 was placed on the pistil of <em>S. lycopersicum to obtain </em>interspecific crosses. The pollen of <em>S. habrochaites</em> LA1777 was placed on the pistil of PI127826 to obtain <em>S. habrochaites</em> F1. <strong>Sample collection</strong> .... <strong>Total RNA isolation</strong> <strong>....</strong> <strong>Sequencing </strong> ... Sample table <pre><code class="language-markdown">| sample | species | cross | forward_read | reverse_read | comment | |-------------------|-----------------------------------|--------|----------------------------------------------------------|---------------------------------------------------------|-------------| | 14865_PI127826_F1 | S. lycopersicum x S. habrochaites | F1 | 14865_PI127826_F1_AGCGATAG-AGGCGAAG_L007_R1_001.fastq.gz | 14865_PI127826_F1_AGCGATAG-AGGCGAAG_L007_R2.fastq.gz | | | LA1777_4 | S. habrochaites | Parent | LA1777_4_TCTCGCGC-CAGGACGT_L005_R1_001.fastq.gz | LA1777_4_TCTCGCGC-CAGGACGT_L005_R2_001.fastq.gz | | | LA1777_F1_3 | S. lycopersicum x S. habrochaites | F1 | LA1777_F1_3_TCTCGCGC-TAATCTTA_L007_R1_001.fastq.gz | LA1777_F1_3_TCTCGCGC-TAATCTTA_L007_R2_001.fastq.gz | | | LA1777_P1_Cv_4 | S. lycopersicum | Parent | LA1777_P1_Cv_4_TCTCGCGC-AGGCGAAG_L007_R1_001.fastq.gz | LA1777_P1_Cv_4_TCTCGCGC-AGGCGAAG_L007_R2_001.fastq.gz | | | PI26_P1_cv_i | S. lycopersicum | Parent | PI26_P1_cv_i_AGCGATAG-CCTATCCT_L006_R1_001.fastq.gz | PI26_P1_cv_i_AGCGATAG-CCTATCCT_L006_R2_001.fastq.gz | | | PI26_P2_w_4 | S. habrochaites f. hirsutum | Parent | PI26_P2_w_4_AGCGATAG-TATAGCCT_L005_R1_001.fastq.gz | PI26_P2_w_4_AGCGATAG-TATAGCCT_L005_R2_001.fastq.gz | | | PI26xLA1777_F1_J | S. habrochaites | F1 | PI26xLA1777_F1_J_TCTCGCGC-GTACTGAC_L005_R1_001.fastq.gz | PI26xLA1777_F1_J_TCTCGCGC-GTACTGAC_L005_R2_001.fastq.gz | </code></pre>
DOI: 10.18434/m31728
title: SRM 3949 Folate Vitamers in Frozen Human Serum

description: Standard Reference Material 3949 Folate Vitamers in Frozen Human Serum
DOI: 10.5281/zenodo.3742271
title: Multivariate time series for testing -- RacketSports dataset

description: The original data was retrieved from http://www.timeseriesclassification.com/description.php?Dataset=RacketSports Original data description:<br> The data was created by university students plyaing badminton or squash whilst wearing a smart watch (Sony Smart watch 35). The watch relayed the x-y-z coordinates for<br> both the gyroscope and accelerometer to an android phone (One Plus 56). The phone<br> wrote these values to an Attribute-Relation File Format (arff) file using an app developed<br> by a UEA computer science masters student. The problem is to identify which sport and which stroke the players are making. The data was collected at a rate of 10 HZ over 3 seconds whilst the player played<br> either a forehand/backhand in squash or a clear/smash in badminton.<br> The data was collected as part of an undergraduate project by Phillip Perks in 2017/18. Pre-processing<br> Data processing was done as described in: https://github.com/NLeSC/mcfly-tutorial/blob/master/utils/tutorial_racketsports.py<br> The original data was split into train and test set. Here the data was loaded and further divided into train, test, validation sets.<br> To keep it simple we here simply divided the original test part into test and validation.<br> The resulting data was stored as numpy .npy files. The zip file contains three sets of time series data (X_train, X_test, X_valid) and the respective labels (y_train, y_test, y_valid). Reference:<br> http://www.timeseriesclassification.com/description.php?Dataset=RacketSports<br> (The data was collected as part of an undergraduate project by Phillip Perks in 2017/18.)
description: {"references": ["http://www.timeseriesclassification.com/description.php?Dataset=RacketSports"]}
DOI: 10.5281/zenodo.3742270
title: Multivariate time series for testing -- RacketSports dataset

description: The original data was retrieved from http://www.timeseriesclassification.com/description.php?Dataset=RacketSports Original data description:<br> The data was created by university students plyaing badminton or squash whilst wearing a smart watch (Sony Smart watch 35). The watch relayed the x-y-z coordinates for<br> both the gyroscope and accelerometer to an android phone (One Plus 56). The phone<br> wrote these values to an Attribute-Relation File Format (arff) file using an app developed<br> by a UEA computer science masters student. The problem is to identify which sport and which stroke the players are making. The data was collected at a rate of 10 HZ over 3 seconds whilst the player played<br> either a forehand/backhand in squash or a clear/smash in badminton.<br> The data was collected as part of an undergraduate project by Phillip Perks in 2017/18. Pre-processing<br> Data processing was done as described in: https://github.com/NLeSC/mcfly-tutorial/blob/master/utils/tutorial_racketsports.py<br> The original data was split into train and test set. Here the data was loaded and further divided into train, test, validation sets.<br> To keep it simple we here simply divided the original test part into test and validation.<br> The resulting data was stored as numpy .npy files. The zip file contains three sets of time series data (X_train, X_test, X_valid) and the respective labels (y_train, y_test, y_valid). Reference:<br> http://www.timeseriesclassification.com/description.php?Dataset=RacketSports<br> (The data was collected as part of an undergraduate project by Phillip Perks in 2017/18.)
description: Version 0.20. correctly stores numpy arrays of floats.
description: {"references": ["http://www.timeseriesclassification.com/description.php?Dataset=RacketSports"]}
DOI: 10.7910/dvn/ticzzh/u5dlgw
title: famben_1Apr2020.tab

description: :unav
DOI: 10.7910/dvn/ticzzh
title: PROSPERED Dataset: Family Cash Benefits

description: This database captures the existence of policies establishing family allowances that require the presence of children in the household as a condition for eligibility. The database focuses on cash payments only. Variables include whether benefits are subject to a means test, and whether they are available universally or only for targeted populations. Longitudinal data is available for every year between 2002 and 2012 for the 121 countries that have been surveyed by either the Demographic and Health Surveys (DHS) or the Multiple Indicator Cluster Surveys (MICS) at least once between 1999 and 2013.
DOI: 10.7910/dvn/ticzzh/ebjsqq
title: famben_1Apr2020-1.tab

description: :unav
DOI: 10.7910/dvn/ticzzh/psduwz
title: PROSPERED data dictionary- familybenefits 032020.pdf

description: :unav
DOI: 10.5281/zenodo.3743483
title: Supplemental Data S1

description: <strong>Supplemental Data S1.</strong> ScanFold output for all genomes. Raw output alongside files used to visualize data. Please see README for detailed descriptions of each file.
DOI: 10.5281/zenodo.3743484
title: Supplemental Data S1

description: <strong>Supplemental Data S1.</strong> ScanFold output for all genomes. Raw output alongside files used to visualize data. Please see README for detailed descriptions of each file.
DOI: 10.6084/m9.figshare.12093648.v1
title: KPOP DATA.xlsx

description: This excel sheet describes the data obtained through a survey conducted for a study on Social media and K-Pop.
DOI: 10.21227/1zv2-4h51
title: free dataset from news/message boards/blogs about CoronaVirus (4 month of data - 5.2M posts)

description: Free dataset from news/message boards/blogs about CoronaVirus (4 month of data - 5.2M posts). The time frame of the data is Dec/2019 - March/2020. The posts are in English mentioning at least one of the following: "Covid" OR CoronaVirus OR "Corona Virus".
DOI: 10.18434/m32176
title: PPdiffuse: Web-based (html and javascript) calculator for voltage-driven transport of polypeptides in nanopores

description: Web calculator for polypeptide motion through nanopores. The calculation is done in the framework of conditional first passage times based on the Smoluchowski transport equation. These calculations are quite complex in general, but this calculator allows the piecewise construction of an energy landscape that reflects the average forces on a polymer confined in a nanopore based on its primary sequence. The calculator is written in HTML and javascript.
DOI: 10.6075/j01v5cb9
title: Locus 100. In Kastrouli Mycenaean Excavations, Greece 2016

description: Cleaning looted tombs
DOI: 10.6075/j05m643g
title: Area A. In Kastrouli Mycenaean Excavations, Greece 2016

description: Area A at Kastrouli represents the exposed and disturbed tomb on the site’s surface, and an excavation square to the immediate east of the tomb (Squares 5/19, 6/19, and 7/19).
DOI: 10.6075/j0hx1b38
title: Locus 104. In Kastrouli Mycenaean Excavations, Greece 2016

description: Cleaning the north end of the lintel stone
DOI: 10.6075/j0np22v1
title: Locus 103. In Kastrouli Mycenaean Excavations, Greece 2016

description: Wall collapse in squares 5/21 and 5/22
DOI: 10.6075/j0sf2tkc
title: Locus 102. In Kastrouli Mycenaean Excavations, Greece 2016

description: Cleaning south end of lintel stone
DOI: 10.6075/j0x34vvx
title: Locus 101. In Kastrouli Mycenaean Excavations, Greece 2016

description: Cleaning and weeding square 5/19
DOI: 10.6075/j04m92x7
title: Locus 107. In Kastrouli Mycenaean Excavations, Greece 2016

description: Cleaning inside looter's hole
DOI: 10.6075/j08c9tnk
title: Locus 106. In Kastrouli Mycenaean Excavations, Greece 2016

description: Cleaning locus topsoil
DOI: 10.6075/j0d50kcv
title: Locus 105. In Kastrouli Mycenaean Excavations, Greece 2016

description: Wall
DOI: 10.6075/j00v8b6x
title: Locus 108. In Kastrouli Mycenaean Excavations, Greece 2016

description: Cleaning and excavating inside the dromos
DOI: 10.6075/j0rf5sf0
title: Locus 110. In Kastrouli Mycenaean Excavations, Greece 2016

description: Area under rock removed from dromos
DOI: 10.6075/j0w66j5q
title: Locus 109. In Kastrouli Mycenaean Excavations, Greece 2016

description: Topsoil of northeast corner of square 6/19
DOI: 10.15468/kkpbvu
title: Taxonomic revision of Strandesia s. s. (Crustacea, Ostracoda) from four Brazilian floodplains, with the description of three new species

description: This dataset contains the digitized treatments in Plazi based on the original journal article Ferreira, Vitor Góis, Higuti, Janet, Martens, Koen (2020): Taxonomic revision of Strandesia s. s. (Crustacea, Ostracoda) from four Brazilian floodplains, with the description of three new species. Zootaxa 4760 (1): 1-74, DOI: https://doi.org/10.11646/zootaxa.4760.1.1
DOI: 10.15468/vgppju
title: Megadiverse Ecuador: a review of Mysmenopsis (Araneae, Mysmenidae) of Ecuador, with the description of twenty-one new kleptoparasitic spider species

description: This dataset contains the digitized treatments in Plazi based on the original journal article Dupérré, Nadine, Tapia, Elicio (2020): Megadiverse Ecuador: a review of Mysmenopsis (Araneae, Mysmenidae) of Ecuador, with the description of twenty-one new kleptoparasitic spider species. Zootaxa 4761 (1): 1-81, DOI: https://doi.org/10.11646/zootaxa.4761.1.1
DOI: 10.6075/j0mp51p6
title: Locus 111. In Kastrouli Mycenaean Excavations, Greece 2016

description: Square 6/19, down in tomb