Data, Volume 9, Issue 3 (March 2024) – 8 articles

In this article, a dataset is described which combines wind turbine supervisory control and data acquisition (SCADA), meteorological and acoustical data and thus gives a detailed description of a wind farm and its atmospheric and acoustic environment. The data were collected during different seasons for several weeks at a time, such that a multitude of environmental and operational conditions are covered. In five measurement campaigns, in total three different locations with similar surroundings were captured. The raw data were enhanced with derived values such as atmospheric stability or direction of sound propagation. Data of one month including all time series measurements as well as monophonic audio recordings are now published. The dataset also contains three exemplary use cases along with documents that describe the data pre-processing. Full article

Marine bioconstructions are complex habitats that represent a hotspot of biodiversity. Among Mediterranean bioconstructions, those thriving on mesophotic bottoms on southeastern Italian coasts are of particular interest due to their horizontal and vertical extension. In general, the communities that develop in the Mediterranean twilight zone encompassed within the first 30 m of depth are better known, while relatively few data are available on those at greater depths. By further investigating the diversity and structure of mesophotic bioconstructions in the southern Adriatic, we can improve our understanding of Mediterranean biodiversity while developing effective conservation strategies to preserve these habitats of particular interest. The dataset reported here comprises records of benthic marine taxa from algae and invertebrate mesophotic bioconstructions investigated at six sites along the southern Adriatic coast of Italy, at depths between approximately 25 and 65 m. The dataset contains a total of 1718 records, covering 11 phyla and 648 benthic taxa, of which 580 were recognized at the species level. These data could provide a reference point for further investigations with descriptive or management purposes, including the possible assessment of mesophotic bioconstructions as refuges for shallow-water species. Full article

This paper presents two datasets about college students’ subjective well-being and mental health in a developing country. The first data set of this report offers a diagnosis of the prevalence of self-reported symptoms associated with stress, anxiety, depression, and overall evaluation of subjective well-being. The study uses validated scales to measure self-reported symptoms related to mental health conditions. To measure stress, the study used the Perceived Stress Scale (PSS-10) and the 7-item Generalized Anxiety Disorder Scale (GAD-7) to measure symptoms associated with anxiety (GAD-7), and the 9-item Patient Health Questionnaire (PHQ-9) to measure symptoms associated with depression. This diagnosis was collected in a college student sample of 3052 undergrad students in 2022 at a medium-sized university in Colombia. The second dataset reports the evaluation of a positive education intervention implemented in the same university. The Colombian Minister of Science and Technology financed the intervention to promote strategies to mitigate the consequences on college students’ well-being and mental health after the pandemic. The program evaluation data cover two years (2020–2022) with 193 college students in the treatment group (students enrolled in a class teaching evidence-based interventions to promote well-being and mental health awareness) and 135 students in the control group. Data for evaluation include a broad array of variables of life satisfaction, happiness, negative emotions, COVID-19 effects, relationships valuations, and habits and the measurement of three scales: The Satisfaction with Life Scale (SWLS), a brief measurement of depressive symptomatology (CESD-7), and the Brief Strengths Scale (BSS). Full article

Evaluating hearing in newborns and uncooperative patients can pose a considerable challenge. One potential solution might be to employ the Pupil Dilation Response (PDR) as an objective physiological metric. In this dataset descriptor paper, we present a collection of data showing changes in pupil dimension and shape upon presentation of auditory stimuli. In particular, we collected pupil data from 16 subjects, with no known hearing loss, upon different lighting conditions, measured in response to a series of 60–100 audible tones, all of the same frequency and amplitude, which may serve to further investigate any relationship between hearing capabilities and PDRs. Full article

This paper presents a set of Ground Penetrating Radar (GPR) data obtained from in situ measurements conducted in four ornamental stone quarries located in Italy (Botticino quarry) and Romania (Ruschita, Carpinis, and Pietroasa quarries). The GPR is a Non-Destructive Testing (NDT) technique that enables the detection and localization of fractures without damage to the surface, among other capabilities. In this study, two instruments of ground-coupled GPR were used to detect and locate the fractures, discontinuities, or weakened zones. The GPR data contains radargrams for discontinuities and fracture detection, besides the geographic location of the measures. For each measurement site, a set of radargrams has been acquired in two orthogonal directions, allowing for a 3D reconstruction of the investigated site. Full article

The definition of a tourism data space (TDS) in the Balearic Islands is a complex process that involves identifying the types of questions to be addressed, including analytical tools, and determining the type of information to be incorporated. This study delves into the functional requirements of a Balearic Islands’ TDS based on the study of scientific research carried out in the field of tourism in the Balearic Islands and drawing comparisons with international scientific research in the field of tourism information. Utilizing a bibliometric analysis of the scientific literature, this study identifies the scientific requirements that should be met for the development of a robust, rigorous, and efficient TDS. The goal is to support excellent scientific research in tourism and facilitate the transfer of research results to the productive sector to maintain and improve the competitiveness of the Balearic Islands as a tourist destination. The results of the analysis provide a structured framework for the construction of the Balearic Islands’ TDS, outlining objectives, methods to be implemented, and information to be considered. Full article

The genome of Bacillus thuringiensis strain INTA 103-23 was sequenced, revealing a high-quality draft assembly comprising 243 contigs with a total size of 6.30 Mb and a completeness of 99%. Phylogenetic analysis classified INTA 103-23 within the Bacillus cereus sensu stricto cluster. Genome annotation identified 6993 genes, including 2476 hypothetical proteins. Screening for pesticidal proteins unveiled 10 coding sequences with significant similarity to known pesticidal proteins, showcasing a potential efficacy against various insect orders. AntiSMASH analysis predicted 13 biosynthetic gene clusters (BGCs), including clusters with 100% similarity to petrobactin and anabaenopeptin NZ857/nostamide A. Notably, fengycin exhibited a 40% similarity within the identified clusters. Further exploration involved a comparative genomic analysis with ten phylogenetically closest genomes. The ANI values, calculated using fastANI, confirmed the closest relationships with strains classified under Bacillus cereus sensu stricto. This comprehensive genomic analysis of B. thuringiensis INTA 103-23 provides valuable insights into its genetic makeup, potential pesticidal activity, and biosynthetic capabilities. The identified BGCs and pesticidal proteins contribute to our understanding of the strain’s biocontrol potential against diverse agricultural pests. Full article

The continuous developments in information technologies have resulted in a significant rise in security concerns, including cybercrimes, unauthorized access, and cyberattacks. Recently, researchers have increasingly turned to social media platforms like X to investigate cyberattacks. Analyzing and collecting news about cyberattacks from tweets can efficiently provide crucial insights into the attacks themselves, including their impacts, occurrence regions, and potential mitigation strategies. However, there is a shortage of labeled datasets related to cyberattacks. This paper describes CybAttT, a dataset of 36,071 English cyberattack-related tweets. These tweets are manually labeled into three classes: high-risk news, normal news, and not news. Our final overall Inner Annotation agreement was 0.99 (Fleiss kappa), which represents high agreement. To ensure dataset reliability and accuracy, we conducted rigorous experiments using different supervised machine learning algorithms and various fine-tuned language models to assess its quality and suitability for its intended purpose. A high F1-score of 87.6% achieved using the CybAttT dataset not only demonstrates the potential of our approach but also validates the high quality and thoroughness of its annotations. We have made our CybAttT dataset accessible to the public for research purposes. Full article