Data | April 2021 - Browse Articles

11 pages, 955 KiB

Open AccessData Descriptor

BOOSTR: A Dataset for Accelerator Control Systems

by Diana Kafkes and Jason St. John

Data 2021, 6(4), 42; https://doi.org/10.3390/data6040042 - 16 Apr 2021

Cited by 3 | Viewed by 3387

The Booster Operation Optimization Sequential Time-series for Regression (BOOSTR) dataset was created to provide a cycle-by-cycle time series of readings and settings from instruments and controllable devices of the Booster, Fermilab’s Rapid-Cycling Synchrotron (RCS) operating at 15 Hz. BOOSTR provides a [...] Read more.

The Booster Operation Optimization Sequential Time-series for Regression (BOOSTR) dataset was created to provide a cycle-by-cycle time series of readings and settings from instruments and controllable devices of the Booster, Fermilab’s Rapid-Cycling Synchrotron (RCS) operating at 15 Hz. BOOSTR provides a time series from 55 device readings and settings that pertain most directly to the high-precision regulation of the Booster’s gradient magnet power supply (GMPS). To our knowledge, this is one of the first well-documented datasets of accelerator device parameters made publicly available. We are releasing it in the hopes that it can be used to demonstrate aspects of artificial intelligence for advanced control systems, such as reinforcement learning and autonomous anomaly detection. Full article

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30 pages, 6944 KiB

Open AccessArticle

AMAΛΘΕΙA: A Dish-Driven Ontology in the Food Domain

by Stella Markantonatou, Katerina Toraki, Panagiotis Minos, Anna Vacalopoulou, Vivian Stamou and George Pavlidis

Data 2021, 6(4), 41; https://doi.org/10.3390/data6040041 - 14 Apr 2021

Cited by 5 | Viewed by 4350

Abstract

We present AΜAΛΘΕΙA (AMALTHIA), an application ontology that models the domain of dishes as they are presented in 112 menus collected from restaurants/taverns/patisseries in East Macedonia and Thrace in Northern Greece. AΜAΛΘΕΙA supports a tourist mobile application offering multilingual translation of menus, dietary [...] Read more.

We present AΜAΛΘΕΙA (AMALTHIA), an application ontology that models the domain of dishes as they are presented in 112 menus collected from restaurants/taverns/patisseries in East Macedonia and Thrace in Northern Greece. AΜAΛΘΕΙA supports a tourist mobile application offering multilingual translation of menus, dietary and cultural information about the dishes and their ingredients, as well as information about the geographical dispersion of the dishes. In this document, we focus on the food/dish dimension that constitutes the ontology’s backbone. Its dish-oriented perspective differentiates AΜAΛΘΕΙA from other food ontologies and thesauri, such as Langual, enabling it to codify information about the dishes served, particularly considering the fact that they are subject to wide variation due to the inevitable evolution of recipes over time, to geographical and cultural dispersion, and to the chef’s creativity. We argue for the adopted design decisions by drawing on semantic information retrieved from the menus, as well as other social and commercial facts, and compare AMAΛΘΕΙA with other important taxonomies in the food field. To the best of our knowledge, AΜAΛΘΕΙA is the first ontology modeling (i) dish variation and (ii) Greek (commercial) cuisine (a component of the Mediterranean diet). Full article

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4 pages, 196 KiB

Open AccessData Descriptor

Isolation of Microsatellite Markers from De Novo Whole Genome Sequences of Coptotermes gestroi (Wasmann) (Blattodea: Rhinotermitidae)

by Li Yang Lim, Shawn Cheng and Abdul Hafiz Ab Majid

Data 2021, 6(4), 40; https://doi.org/10.3390/data6040040 - 10 Apr 2021

Cited by 2 | Viewed by 2350

Abstract

Coptotermes gestroi (Wasmann) (Blattodea: Rhinotermitidae) is a subterranean termite species from Southeast Asia which has been unintentionally introduced to many parts of the world through commerce and modern transportation. Known for causing extensive damage to timber used in the built environment, the termite [...] Read more.

Coptotermes gestroi (Wasmann) (Blattodea: Rhinotermitidae) is a subterranean termite species from Southeast Asia which has been unintentionally introduced to many parts of the world through commerce and modern transportation. Known for causing extensive damage to timber used in the built environment, the termite also has a habit of nesting in carton nests in wood and wooden structures in buildings. As so little is known of its breeding system, colony, and genetic structure, we initiated work to sequence its genome with an Illumina HiSeq™ 2000 sequencer. In this publication, we announce our paired-end sequencing data and report the isolation of 119,190 microsatellite markers from our DNA assembly. The microsatellite marker reported in this publication can be used to elucidate the mating system and genetic structure of this highly invasive termite species. Additionally, in this announcement the study authors make the Bio Project sequence accession number SRR13105492 accessible from the Sequence Read Archive database. Full article

13 pages, 496 KiB

Open AccessData Descriptor

Exploring Inner-City Residents’ and Foreigners’ Commitment to Improving Air Pollution: Evidence from a Field Survey in Hanoi, Vietnam

by Quan-Hoang Vuong, Tri Vu Phu, Tuyet-Anh T. Le and Quy Van Khuc

Data 2021, 6(4), 39; https://doi.org/10.3390/data6040039 - 10 Apr 2021

Cited by 9 | Viewed by 6513

Abstract

Solutions for mitigating and reducing environmental pollution are important priorities for many developed and developing countries. This study was conducted to better understand the degree to which inner-city citizens and foreigners perceive air pollution and respond to it, particularly how much they willingly [...] Read more.

Solutions for mitigating and reducing environmental pollution are important priorities for many developed and developing countries. This study was conducted to better understand the degree to which inner-city citizens and foreigners perceive air pollution and respond to it, particularly how much they willingly contribute to improving air quality in Vietnam, a lower-middle-income nation in Southeast Asia. During mid-December 2019, a stratified random sampling technique and a contingent valuation method (CVM) were employed to survey 199 inhabitants and 75 foreigners who reside and travel within the inner-city of Hanoi. The data comprises four major groups of information on: (1) perception of air pollution and its impacts, (2) preventive measures used to mitigate polluted air, (3) commitments on willingness-to-pay (WTP) for reducing air pollution alongside reasons for the yes-or-no-WTP decision, and (4) demographic information of interviewees. The findings and data of this study could offer many policy implications for better environmental management in the study area and beyond. Full article

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6 pages, 255 KiB

Open AccessEditor’s ChoiceData Descriptor

Hand-Washing Video Dataset Annotated According to the World Health Organization’s Hand-Washing Guidelines

by Martins Lulla, Aleksejs Rutkovskis, Andreta Slavinska, Aija Vilde, Anastasija Gromova, Maksims Ivanovs, Ansis Skadins, Roberts Kadikis and Atis Elsts

Data 2021, 6(4), 38; https://doi.org/10.3390/data6040038 - 7 Apr 2021

Cited by 10 | Viewed by 5379

Abstract

Washing hands is one of the most important ways to prevent infectious diseases, including COVID-19. The World Health Organization (WHO) has published hand-washing guidelines. This paper presents a large real-world dataset with videos recording medical staff washing their hands as part of their [...] Read more.

Washing hands is one of the most important ways to prevent infectious diseases, including COVID-19. The World Health Organization (WHO) has published hand-washing guidelines. This paper presents a large real-world dataset with videos recording medical staff washing their hands as part of their normal job duties in the Pauls Stradins Clinical University Hospital. There are 3185 hand-washing episodes in total, each of which is annotated by up to seven different persons. The annotations classify the washing movements according to the WHO guidelines by marking each frame in each video with a certain movement code. The intention of this “in-the-wild” dataset is two-fold: to serve as a basis for training machine-learning classifiers for automated hand-washing movement recognition and quality control, and to allow to investigation of the real-world quality of washing performed by working medical staff. We demonstrate how the data can be used to train a machine-learning classifier that achieves classification accuracy of 0.7511 on a test dataset. Full article

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8 pages, 3867 KiB

Open AccessData Descriptor

FastFix Albatross Data: Snapshots of Raw GPS L-1 Data from Southern Royal Albatross

by Timothy C. A. Molteno and Keith W. Payne

Data 2021, 6(4), 37; https://doi.org/10.3390/data6040037 - 7 Apr 2021

Viewed by 2614

Abstract

This dataset contains 4-millisecond snapshots of the GPS radio spectrum stored by wildlife tracking tags deployed on adult Southern Royal Albatross (Diomedea epomophora) in New Zealand. Approximately 60,000 snapshots were recovered from nine birds over two southern-hemisphere summers in 2012 and [...] Read more.

This dataset contains 4-millisecond snapshots of the GPS radio spectrum stored by wildlife tracking tags deployed on adult Southern Royal Albatross (Diomedea epomophora) in New Zealand. Approximately 60,000 snapshots were recovered from nine birds over two southern-hemisphere summers in 2012 and 2013. The data can be post-processed using snapshot positioning algorithms, and are made available as a test dataset for further development of these algorithms. Included are post-processed position estimates for reference, as well as test data from stationary tags positioned under various test conditions for the purposes of characterizing tag performance. Full article

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27 pages, 3118 KiB

Open AccessData Descriptor

Targeted Chemometrics Investigations of Source-, Age- and Gender-Dependencies of Oral Cavity Malodorous Volatile Sulphur Compounds

by Kerry L. Grootveld, Victor Ruiz-Rodado and Martin Grootveld

Data 2021, 6(4), 36; https://doi.org/10.3390/data6040036 - 6 Apr 2021

Viewed by 2358

Abstract

Halitosis is a highly distressing, socially unaesthetic condition, with a very high incidence amongst the adult population. It predominantly arises from excessive oral cavity volatile sulphur compound (VSC) concentrations, which have either oral or extra-oral etiologies (90–95% and 5–10% of cases, respectively). However, [...] Read more.

Halitosis is a highly distressing, socially unaesthetic condition, with a very high incidence amongst the adult population. It predominantly arises from excessive oral cavity volatile sulphur compound (VSC) concentrations, which have either oral or extra-oral etiologies (90–95% and 5–10% of cases, respectively). However, reports concerning age- and gender-related influences on the patterns and concentrations of these malodorous agents remain sparse; therefore, this study’s first objective was to explore the significance and impact of these potential predictor variables on the oral cavity levels of these malodorants. Moreover, because non-oral etiologies for halitosis may represent avatars of serious extra-oral diseases, the second objective was to distinguish between etiology- (source-) dependent patterns of oral cavity VSCs. Oral cavity VSC determinations were performed on 116 healthy human participants using a non-stationary gas chromatographic facility, and following a 4 h period of abstention from all non-respiratory oral activities. Participants were grouped according to ages or age bands, and gender. Statistical analyses of VSC level data acquired featured both univariate/correlation and multivariate (MV) approaches. Factorial analysis-of-variance and MV analyses revealed that the levels of all VSCs monitored were independent of both age and gender. Principal component analysis (PCA) and a range of further MV analysis techniques, together with an agglomerative hierarchal clustering strategy, demonstrated that VSC predictor variables were partitioned into two components, the first arising from orally-sourced H₂S and CH₃SH, the second from extra-orally-sourced (CH₃)₂S alone (about 55% and 30% of total variance respectively). In conclusion, oral cavity VSC concentrations appear not to be significantly influenced by age and gender. Furthermore, (CH₃)₂S may serve as a valuable biomarker for selected extra-oral conditions. Full article

(This article belongs to the Section Computational Biology, Bioinformatics, and Biomedical Data Science)

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16 pages, 31313 KiB

Open AccessData Descriptor

A Sentinel-2 Dataset for Uganda

by Jonas Ardö

Data 2021, 6(4), 35; https://doi.org/10.3390/data6040035 - 30 Mar 2021

Cited by 1 | Viewed by 4449

Abstract

Earth observation data provide useful information for the monitoring and management of vegetation- and land-related resources. The Framework for Operational Radiometric Correction for Environmental monitoring (FORCE) was used to download, process and composite Sentinel-2 data from 2018–2020 for Uganda. Over 16,500 Sentinel-2 data [...] Read more.

Earth observation data provide useful information for the monitoring and management of vegetation- and land-related resources. The Framework for Operational Radiometric Correction for Environmental monitoring (FORCE) was used to download, process and composite Sentinel-2 data from 2018–2020 for Uganda. Over 16,500 Sentinel-2 data granules were downloaded and processed from top of the atmosphere reflectance to bottom of the atmosphere reflectance and higher-level products, totalling > 9 TB of input data. The output data include the number of clear sky observations per year, the best available pixel composite per year and vegetation indices (mean of EVI and NDVI) per quarter. The study intention was to provide analysis-ready data for all of Uganda from Sentinel-2 at 10 m spatial resolution, allowing users to bypass some basic processing and, hence, facilitate environmental monitoring. Full article

(This article belongs to the Section Spatial Data Science and Digital Earth)

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Data, Volume 6, Issue 4 (April 2021) – 8 articles

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