| 1. |
- Asif, M., et al.
(author)
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A dataset about anthropometric measurements of the Pakistani children and adolescents using a cross-sectional multi-ethnic anthropometric survey
- 2021
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In: Data in Brief. - : Elsevier. - 2352-3409. ; 34
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Journal article (peer-reviewed)abstract
- Evaluation of nutritional status is necessary during childhood and the juvenile years when the level of hydration and the adipose tissues experience significant changes. Anthropometric measurements and their derived indices are valid proxies to predict body fat, obesity (general or central) and their associated cardiovascular risks. The dataset under consideration also provides the socio-demographic related information and anthropometric measurement values related to height, weight, body mass index (BMI), waist circumference (WC), hip circumference (HpC), waist-to-hip ratio (WHpR), waist-to-height ratio (WHtR), mid-upper arm circumference (MUAC), neck circumference (NC), and wrist circumference (WrC). Standard procedure was adopted for quantifying the body measurements. The data were consisting of 10,782 children and adolescents aged 2–19 years, belonging four major cities of Pakistan viz. Multan, Lahore, Rawalpindi and Islamabad. This dataset is beneficial to develop anthropometric growth charts which will provide the essential knowledge of growth and nutritional disorders (e.g., stunted, overweight and obesity) of Pakistani children and adolescents. The dataset can also be used by researchers to calculate body surface area (BSA), body frame size (BFS), body shape index (BSI), and tri-ponderal mass index (TMI) of children and adolescents that are also some other reliable indicators of obesity and insulin resistance as well as cardiometabolic risk in children and adults.
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| 2. |
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| 3. |
- Bezerra Lima Verde, Isabel
(author)
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Characterization of a new multidrug-resistant Brazilian K. pneumoniae isolate and 172 Klebsiella spp. sequenced strains: Genomic island, multilocus sequence typing and capsule locus dataset
- 2021
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In: Data in Brief. - : Elsevier BV. - 2352-3409. ; 34
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Journal article (peer-reviewed)abstract
- The genus Klebsiella comprises species that cause nosocomial and community-acquired infections. A dataset was created to compile the sequence type (ST) and capsule type (K-locus) information predicted for 172 worldwide isolates of Klebsiella spp. whose complete genomes could be retrieved from the GenBank (NCBI) repository. The dataset also includes information related to one multidrug-resistant strain (B31) isolated from a patient who was admitted to an intensive care unit in the Northeast region of Brazil. This strain was phenotypically characterized and submitted to whole-genome sequencing and comparative genomics analysis as we recently reported [1]. The dataset also compiles information on Pathogenicity Islands (PIs), Resistance Islands (RIs) and Miscellaneous Islands (MIS) present in the genome of strain B31. The information provided here may support outbreak prevention policies and future epidemiological studies involving Klebsiella spp. (c) 2021 Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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| 4. |
- Chimamiwa, Gibson, 1977-, et al.
(author)
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Multi-sensor dataset of human activities in a smart home environment
- 2021
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In: Data in Brief. - : Elsevier. - 2352-3409. ; 34
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Journal article (peer-reviewed)abstract
- Time series data acquired from sensors deployed in smart homes present valuable information for intelligent systems to learn activity patterns of occupants. With the increasing need to enable people to age in place independently, the availability of such data is key to the development of home monitoring solutions. In this article we describe an unlabelled dataset of measurements collected from multiple environmental sensors placed in a smart home to capture human activities of daily living. Various sensors were used including passive infrared, force sensing resistors, reed switches, mini photocell light sensors, temperature and humidity, and smart plugs. The sensors record data from the user's interactions with the environment, such as indoor movements, pressure applied on the bed, or current consumption when using electrical appliances. Millions of raw sensor data samples were collected continuously at a frequency of 1 Hz over a period of six months between 26 February 2020 and 26 August 2020. The dataset can be useful in the analysis of different methods, including data-driven algorithms for activity or habit recognition. In particular, the research community might be interested in investigating the performance of algorithms when applied on unlabelled datasets and not necessarily on annotated datasets. Furthermore, by applying artificial intelligence (AI) algorithms on such data collected over long periods, it is possible to extract patterns that reveal the user's habits as well as detect changes in the habits. This can benefit in detecting deviations in order to provide timely interventions for patients, e.g., people with dementia.
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| 5. |
- Dellmuth, Lisa M., et al.
(author)
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Dataset on non-state actor participation in regional fisheries management organizations
- 2021
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In: Data in Brief. - : Elsevier BV. - 2352-3409. ; 34
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Research review (peer-reviewed)abstract
- In this article, we present and describe a new dataset of non-state actor participation in seven regional fisheries management organizations (RFMOs). The dataset contains institutional, economic and ecological variables relevant for non-state actor participation in RFMOs and for RFMO effectiveness. To code non-state actor participation and institutional factors, we quantify information from publicly available RFMO reports as well as data from the Policy IV dataset. We pair these data with existing datasets on ecological and economic factors from the RAM Legacy and the Sea Around Us databases. This article describes the data collection process and the coded variables in detail.
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| 6. |
- Elfversson, Emma, 1983-
(author)
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Cities and armed conflict : A systematic urban-rural coding of UCDP conflict events data
- 2021
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In: Data in Brief. - : Elsevier. - 2352-3409. ; 39
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Journal article (peer-reviewed)abstract
- This data article provides a descriptive overview of the Cities and Armed Conflict Events (CACE) dataset and the data collection methods. The dataset provides a systematic coding of armed conflict events taking place in cities and outside cities across the globe. It constitutes an extension of the Uppsala Conflict Data Program (UCDP) Georeferenced Events Dataset (GED) version 18.1 and covers 1989–2017. To identify which events of armed conflict took place in cities, the data was manually matched to to data from the United Nations Statistics Division (UNSD). The dataset enables systematic analysis of urban-rural patterns in armed conflict, as illustrated by Elfversson & Höglund [1]. While existing methods for analysing such patterns frequently rely on matching conflict data to spatial grids combined with population density, the data presented here with higher validity captures whether violent events take place in cities.
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| 7. |
- Eriksson, Mattias, et al.
(author)
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Guest attendance data from 34 Swedish pre-schools and primary schools
- 2021
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In: Data in Brief. - : Elsevier BV. - 2352-3409. ; 36
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Journal article (peer-reviewed)abstract
- This data article describes 34 datasets, compiled into one table, describing guest attendance at lunch meal servings in Swedish public schools and preschools. Fifteen of the schools and all 16 of the preschools covered belong to one municipality, while the remaining three schools belong to two other municipalities, all located in central Sweden. Data on number of plates was used as a proxy of the number of guests eating lunch. Number of used plates was recorded from late August 2010 to early June 2020, i.e. covering the period both before and during the initial phase of the Covid-19 pandemic, so that making possible to evaluate changes in guest attendance during the pandemic. Since these were real data, all data elements pertaining to exact canteens or staff identity have been removed. There is a scarcity of real business data for scientific and educational purposes, so these datasets can play an important role in research and education within catering management, consumption pattern analysis, machine learning, data mining and other fields.
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| 8. |
- Fauvelle, Mikael, et al.
(author)
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Surf and turf : A dataset of stable isotope values of plants and animals from southern California
- 2021
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In: Data in Brief. - : Elsevier BV. - 2352-3409. ; 38
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Journal article (peer-reviewed)abstract
- This article presents baseline isotope values for plant and animal samples collected from across southern California. A total of 80 samples representing 50 species were collected and analyzed for this project. This original dataset includes 31 plant species, 13 finfish species, 3 mollusk species, 2 crustacean species, and 1 echinoderm. Plant samples were collected by the authors and an undergraduate research assistant in San Diego and Santa Barbara counties. Animal samples were procured from local fishers in San Diego and Santa Barbara. All samples were subjected to stable isotope analysis at the University of California, San Diego (UCSD). In this paper we present our new δ13C and δ15N data alongside previously published values from three other studies [1–3]. The previously published values reproduced here were derived from a mix of modern and archaeological samples. Together, these data represent the most complete dataset currently available for southern California baseline stable isotope values. The full combined dataset can be found in the Supplemental Data included with this paper, while Table 1 presents a comparison of defatted and untreated faunal specimens. These data will be of use to archaeologists and ecologists conducting future isotope studies on the Pacific Coast of North America.
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| 9. |
- Hartvigsson, Elias, 1986, et al.
(author)
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Dataset for generating synthetic residential low-voltage grids in Sweden, Germany and the UK
- 2021
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In: Data in Brief. - : Elsevier BV. - 2352-3409. ; 36
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Journal article (peer-reviewed)abstract
- Assessing grid capacity on national and local levels is important in order to formulate renewable energy targets, calculate integration costs of distributed generation (such as residential solar PV and electric vehicles). Currently, 70–96% of the residential solar PV installations in Germany and Italy are found in the low-voltage grid. Previous grid assessments have relied on grid data from individual low-voltage grids, making them limited to a few cases. This article presents synthetic low-voltage grid data from a reference network model. The reference network model generates synthetic low-voltage grids using publicly available data and national regulations and standards. In addition, the article presents data of residential solar photovoltaic hosting capacity in low-voltage grids. The datasets are high-resolution (1 × 1 km) and contains data on electricity peak demand, share of population living in apartments and important grid metrics such as transformer capacity, maximum feeder length and estimations of residential solar photovoltaic hosting capacity. Datasets on grid components are rare and the dataset can be used to assess grid impacts from other residential end-use technologies, and function as baseline for other reference network models.
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| 10. |
- Karlson, Agnes M. L., et al.
(author)
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Polycyclic aromatic hydrocarbons and stable isotopes of carbon and nitrogen in Baltic Sea blue mussels : Time series data 1981-2016
- 2021
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In: Data in Brief. - : Elsevier BV. - 2352-3409. ; 35
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Journal article (peer-reviewed)abstract
- Blue mussels are a target species in contaminant monitoring regarding Polycyclic Aromatic Hydrocarbons (PAHs) in biota, and also used as an isotope baseline for trophic position assessment in other biota. The latter is crucial for calculating biomagnification potential of environmental contaminants. This data set comprises long-term time series of PAHs (15 individual substances) in Baltic Sea blue mussels (Mytilus trossulus edulis) from Kvadofjarden (collected from a depth of 5-10 m), a reference area along the Swedish coast in the Baltic Proper from 25 years during 1987-2016, and of stable isotopes in five individuals (2 cm mussels) per year during the time period 1981-2017. The data has been co-analysed with environmental (oceanographic) data in The importance of adjusting contaminant concentrations using environmental data: a retrospective study of 25 years data in Baltic blue mussels published in: Science of the Total Environment (https://doi.org/10.1016/j.scitotenv.2020.143913).
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| 11. |
- Landström, Anton, et al.
(author)
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Electron spectroscopies of 3-hydroxyflavone and 7-hydroxyflavone in MCM-41 silica nanoparticles and in acetonitrile solutions. Experimental data and DFT/TD-DFT calculations
- 2021
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In: Data in Brief. - : Elsevier. - 2352-3409. ; 34
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Journal article (peer-reviewed)abstract
- The data presented here concern the photophysical characterization of luminescent MCM-41 nanoparticles doped with 3-hydroxyflavone and 7-hydroxyflavone, two fluorescent flavonoids. UV-Vis and fluorescence spectra obtained on freshly-prepared samples and aged (2 months exposed to air) samples are shown. The effect of light exposure is also studied. In parallel, experiments have been carried out in acetonitrile solutions of the two flavonoids as a term of comparison. Time-dependent density functional theory calculations have also been used to simulate UV-Vis and emission spectra of different species for both flavonoids (neutral molecule, tautomers, cationic and anionic forms), taking into account the effect of the surrounding medium (solvent). Density functional theory calculations of vibrational spectra (IR, Raman) of neutral and tautomeric species of 3HF and 7HF are also provided.
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| 12. |
- Li, Xia, et al.
(author)
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Dataset of whole-brain resting-state fMRI of 227 young and elderly adults acquired at 3T
- 2021
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In: Data in Brief. - : Elsevier BV. - 2352-3409. ; 38
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Journal article (peer-reviewed)abstract
- To investigate the impact of adult age on the brain functional connectivity, whole-brain resting-state functional magnetic resonance imaging (R-fMRI) data were acquired on a 3T clinical MRI scanner in a cohort of 227, right-handed, native Swedish-speaking, healthy adult volunteers (N=227, aged 18-74 years old, male/female=99/128). The dataset is mainly consisted of a younger (18-30 years old n=124, males/females=51/73) and elderly adult (n=76, 60-76 years old, males/females=35/41) subgroups. The dataset was analyzed using a new data-driven analysis (QDA) framework. With QDA two types of threshold-free voxel-wise resting-state functional connectivity (RFC) metrics were derived: the connectivity strength index (CSI) and connectivity density index (CDI), which can be utilized to assess the brain changes in functional connectivity associated with adult age. The dataset can also be useful as a reference to identify abnormal changes in brain functional connectivity resulted from neurodegenerative or neuropsychiatric disorders.
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| 13. |
- Mohamedin, Esraa Hamdy, 1991, et al.
(author)
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Additional data and experimental setups, for a comparative study of alloys in contact to eutectic melts for thermal storage
- 2021
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In: Data in Brief. - : Elsevier BV. - 2352-3409. ; 38
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Journal article (peer-reviewed)abstract
- Three different eutectic salt mixtures have been brought into contact with three different high temperature alloys to assess corrosion damages for next-generation CSPs. This article contains additional material to support findings and assessments reported on our main article in the Solar Energy Journal [https://doi.org/10.1016/j.solener.2021.06.069]. Five sections, A-E, provide data to ensure reproducibility and confidence in our claims in the main article. A newly designed experimental setup for high temperature exposures is described as well as impurities within used chemicals. Material thickness measurements document alloy consumption by eutectic salts. Reaction enthalpies are listed illustrating individual metal species in contact with salt species at relevant temperatures. Thermodynamic single point equilibrium calculations have extended environmentally induced Laves phase precipitation found for alloy Kanthal APMT in contact with molten chlorides.
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| 14. |
- Pakpour, Amir H., et al.
(author)
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A population-based dataset concerning predictors of willingness to get a COVID-19 vaccine in Iran
- 2021
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In: Data in Brief. - : Elsevier. - 2352-3409. ; 39
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Journal article (peer-reviewed)abstract
- The global issue of preventing the spread of COVID-19 is challenging. One of the most efficient ways to control the pandemic is to have a full coverage of COVID-19 vaccination. Therefore, this paper collected survey data to understand the intention and willingness of COVID-19 vaccination uptake in Qazvin, Iran. With the use of a paper-and-pencil method and multistage stratified cluster sampling, research personnel approached and interviewed a representative sample of adults in Qazvin (n = 10843) between February 19 and April 9, 2021. The survey asked questions regarding sociodemographic information, fear of COVID-19, perceived COVID-19 infectability, perceived behavioral control over COVID-19 vaccination, subjective norm of COVID-19 vaccination, attitude towards COVID-19 vaccination, and intention to get COVID-19 vaccinated. The data collected from this survey were analyzed using descriptive statistics, which were carried out using the IBM SPSS version 17.0.
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| 15. |
- Perret, E., et al.
(author)
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WAXD, polarized ATR-FTIR and DSC data of stress-annealed poly(3-hydroxybutyrate) fibers
- 2021
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In: Data in Brief. - : Elsevier BV. - 2352-3409. ; 39, s. 107523-
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Journal article (peer-reviewed)abstract
- This article summarizes synchrotron wide-angle x-ray diffraction (WAXD) patterns, polarized attenuated Fourier transform infrared spectroscopy (ATR-FTIR) data and differential scanning calorimetry (DSC) data of differently stress-annealed poly(3-hydroxybutyrate) (P3HB) fibers. Additionally, in-situ polarized ATR-FTIR data has been measured under tensile drawing of pre-annealed P3HB fibers under low annealing stress. Modifications to the ATR-FTIR setup and sample holders for performing measurements on P3HB fibers are explained in the experimental section. For more information see 'Reversible mesophase in stress-annealed poly(3-hydroxybutyrate) fibers: A synchrotron x-ray and polarized ATR-FTIR study' [1] .
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| 16. |
- Sharma, Kamendra, et al.
(author)
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2D Raman, ATR-FTIR, WAXD, SAXS and DSC data of PET mono- and PET/PA6 bicomponent filaments
- 2021
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In: Data in Brief. - : Elsevier BV. - 2352-3409. ; 38
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Journal article (peer-reviewed)abstract
- This data in brief article summarizes structural data obtained from monocomponent melt-spun and offline drawn poly(ethylene terephthalate) (PET) monofilaments, as well as from melt-spun bicomponent core-sheath PET-polyamide 6 (PA6) filaments. The diameters of the single filaments range from 27 mu m to 79 mu m. Presented analysis techniques and results thereof are (i) Raman mapping of filament crosssections: 2D maps of peak positions, widths, peak area ratios; (ii) attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR): ATR-FTIR spectra and extraction of surface crystallinity; (iii) wide-angle x-ray diffraction (WAXD): WAXD patterns and extraction of average crystallinity; (iv) small-angle x-ray scattering (SAXS): SAXS patterns and determined crystallite sizes and long-spacings; (v) differential scanning calorimetry (DSC): thermograms and extracted average crystallinity as well as thermal properties; (vi) atomic force microscopy (AFM): AFM image of the surface of an embedded fiber cross-section. For more information, see the publication by E. Perret et al. 'High-resolution 2D Raman mapping of mono-and bicomponent filament cross-sections' [1] .
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| 17. |
- Stefánsson, Bergur V., et al.
(author)
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Data from a pooled post hoc analysis of 14 placebo-controlled, dapagliflozin treatment studies in patients with type 2 diabetes with and without anemia at baseline
- 2021
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In: Data in Brief. - : Elsevier. - 2352-3409. ; 37, s. 1-11
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Journal article (peer-reviewed)abstract
- Dapagliflozin is a highly selective sodium-glucose cotransporter 2 inhibitor associated with stabilization of estimated glomerular filtration rate (eGFR); reductions in glycated hemoglobin (HbA1c), systolic blood pressure, body weight, and albuminuria; and a small and consistent increase in hematocrit [1–4]. This data set is based on the associated article [5] analyzing data from 5325 patients with type 2 diabetes from 14 placebo-controlled, phase 3 (one phase 2/3), double-blind dapagliflozin treatment studies of 24–104 weeks’ duration. Data on dapagliflozin's effects (vs. placebo) on hemoglobin (Hb), hematocrit, serum albumin, serum total protein concentrations, urine albumin/creatinine ratio, eGFR, heart rate, blood pressure, body weight, and safety in patients with type 2 diabetes with and without anemia were pooled and analyzed. Patients were divided into two groups according to baseline Hb levels: anemia (Hb <13 g/dL in men and <12 g/dL in women) and no anemia. Some biomarkers associated with erythropoiesis and the presence of anemia, such as iron, transferrin, ferritin, reticulocytes, and hepcidin, were not included in the original studies and therefore data for these biomarkers were not available. Descriptive statistics were used for baseline characteristics and safety data and a longitudinal repeated-measures mixed model for efficacy data. Changes in Hb concentrations were evaluated, and the proportion of patients with baseline anemia who were no longer anemic at week 24 was determined, as was the occurrence of polycythemia (Hb >16.5 g/dL in men and >16.0 g/dL in women). Because anemia commonly occurs in patients with diabetes and chronic kidney disease [6], the data can be of value to further analyze trends in relevant physiological and pathophysiological parameters.
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| 18. |
- Svanström, Fredrik, et al.
(author)
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A dataset for multi-sensor drone detection
- 2021
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In: Data in Brief. - Amsterdam : Elsevier Inc.. - 2352-3409. ; 39
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Journal article (peer-reviewed)abstract
- The use of small and remotely controlled unmanned aerial vehicles (UAVs), referred to as drones, has increased dramatically in recent years, both for professional and recreative purposes. This goes in parallel with (intentional or unintentional) misuse episodes, with an evident threat to the safety of people or facilities [1]. As a result, the detection of UAV has also emerged as a research topic [2]. Most of the existing studies on drone detection fail to specify the type of acquisition device, the drone type, the detection range, or the employed dataset. The lack of proper UAV detection studies employing thermal infrared cameras is also acknowledged as an issue, despite its success in detecting other types of targets [2]. Beside, we have not found any previous study that addresses the detection task as a function of distance to the target. Sensor fusion is indicated as an open research issue as well to achieve better detection results in comparison to a single sensor, although research in this direction is scarce too [3–6]. To help in counteracting the mentioned issues and allow fundamental studies with a common public benchmark, we contribute with an annotated multi-sensor database for drone detection that includes infrared and visible videos and audio files. The database includes three different drones, a small-sized model (Hubsan H107D+), a medium-sized drone (DJI Flame Wheel in quadcopter configuration), and a performance-grade model (DJI Phantom 4 Pro). It also includes other flying objects that can be mistakenly detected as drones, such as birds, airplanes or helicopters. In addition to using several different sensors, the number of classes is higher than in previous studies [4]. The video part contains 650 infrared and visible videos (365 IR and 285 visible) of drones, birds, airplanes and helicopters. Each clip is of ten seconds, resulting in a total of 203,328 annotated frames. The database is complemented with 90 audio files of the classes drones, helicopters and background noise. To allow studies as a function of the sensor-to-target distance, the dataset is divided into three categories (Close, Medium, Distant) according to the industry-standard Detect, Recognize and Identify (DRI) requirements [7], built on the Johnson criteria [8]. Given that the drones must be flown within visual range due to regulations, the largest sensor-to-target distance for a drone in the dataset is 200 m, and acquisitions are made in daylight. The data has been obtained at three airports in Sweden: Halmstad Airport (IATA code: HAD/ICAO code: ESMT), Gothenburg City Airport (GSE/ESGP) and Malmö Airport (MMX/ESMS). The acquisition sensors are mounted on a pan-tilt platform that steers the cameras to the objects of interest. All sensors and the platform are controlled with a standard laptop vis a USB hub.
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