Abstract
A paracetamol concentration-sensing scheme based on a linear cavity fiber laser configuration is demonstrated experimentally. The laser cavity has a fiber sensor at one end, that allows refractive index measurements. The refractometer consists of a cleaved fiber tip combined with an FBG functioning as a reflecting mirror. The combination of a fiber loop mirror at the other end allows to reflect all the light from the FBG and refractometer, forming a linear cavity. By measuring the intensity variation of the Fresnel reflection at the fiber-to-liquid interface, the measured concentration is linear and have a concentration sensitivity of [( - 8.74 & PLUSMN; 0.34) x 10-5 ] & mu;W/(g/kg), over a range of 52.61 to 219.25 g/kg, and with a resolution of 2.77 g/kg. The results obtained present high stability and prove the potential of the fiber laser system to performed realtime measurements of concentration, in a non-invasive way.

Abstract
Purpose The purpose of this study is to explore the potential and growth of big data across several industries between 2016 and 2020. This study aims to analyze the behavior of interest in big data within the community and to identify areas with the greatest potential for future big data adoption. Design/methodology/approach This research uses Google Trends to characterize the community's interest in big data. Community interest is measured on a scale of 0-100 from weekly observations over the past five years. A total of 16 industries were considered to explore the relative interest in big data for each industry. Findings The findings revealed that big data has been of high interest to the community over the past five years, particularly in the manufacturing, computers and electronics industries. However, over the 2020s the interest in the theme decreased by more than 15%, especially in the areas where big data typically had the greatest potential interest. In contrast, areas with less potential interest in big data such as real estate, sport and travel have registered an average growth of less than 10%. Originality/value To the best of the author's knowledge, this study is original in complementing the traditional survey approaches launched among the business communities to discover the potential of big data in specific industries. The knowledge of big data growth potential is relevant for players in the field to identify saturation and emerging opportunities for big data adoption.

Abstract
The human-environment-vehicle triad and how it relates to crashes has long been a topic of discussion, in which the human factor is consistently seen as the leading cause. Recently, more sophisticated approaches to Road Safety have advocated for a road-driver interaction view, in which human characteristics influence road perception and road environment affects driver behavior. This study focuses on road-driver interaction by using a driving simulator. The objective is to investigate how the driver profile influences driving performance and the effects of three countermeasures (peripheral transverse lines before and after the beginning of the curves and roadside poles in the curves). Fifty-six middle-aged male participants drove a non-challenging rural highway simulated scenario based on a real road where many single-vehicle crashes occurred. The drivers' profiles were assessed through their behavioral history measured by a validated version of the Driver Behavior Questionnaire (DBQ) comprising three dimensions: Errors (E), Ordinary Violations (OV), and Aggressive Violations (AV). The relationship between speed and trajectory measures and drivers' profiles was investigated using randomparameter models with heterogeneity in the means. The models' results showed that the DBQ subscale scores in OV explained a considerable part of the heterogeneity found in drivers' performance. Furthermore, the heterogeneity in the means caused by the DBQ subscale scores in OV and E in the presence of peripheral transverse lines indicates a difference in how drivers react to the countermeasures. The peripheral lines were more efficient than roadside poles to moderate speed but did not positively influence all drivers' trajectories. Although the peripheral lines could be seen as an alternative to change driver behavior in a non-challenging or monotonous road environment, the design used in this study should be reviewed.

Abstract
An isolation effort focused on sporogenous Actinomycetota from the Tagus estuary in Alcochete, Portugal, yielded a novel actinomycetal strain, designated MTZ3.1T, which was subjected to a polyphasic taxonomic study. MTZ3.1T is characterised by morphology typical of members of the genus Streptomyces, with light beige coloured substrate mycelium, which does not release pigments to the culture medium and with helicoidal aerial hyphae that differentiate into spores with a light- grey colour. The phylogeny of MTZ3.1T, based on the full 16S rRNA gene sequence, indicated that its closest relatives were Streptomyces alkaliterrae OF1T (98.48 %), Streptomyces chumphonensis KK1-2T (98.41 %), Streptomyces albofaciens JCM 4342T (98.34 %), Streoptomyces paromomycinus NBRC 15454T (98.34 %) and Streptomyces chrestomyceticus NRBC 13444T (98.34 %). Moreover, average nucleotide identity (ANI), average amino acid identity (AAI) and digital DNA-DNA hybridisation (dDDH) are below the species cutoff values (ANI 67.70 and 68.35 %, AAI 77.06 and 76.71 % and dDDH 22.10 and 21.50 % for S. alkaliterrae OF1T and S. chumphonensis KK1-2T, respectively). Whole genome sequencing revealed that MTZ3.1T has a genome of 5 644 485 bp with a DNA G+C content of 71.29 mol% and 5044 coding sequences. Physiologically, MTZ3.1T is strictly aerobic, able to grow at 15-37 & DEG;C, optimally at 25 & DEG;C and between pH5 and 8 and showed high salinity tolerance, growing with 0-10 %(w/v) NaCl. Major cellular fatty acids are C15:0, iso-C15:0, anteiso-C15: 0 and iso- C16:0. Furthermore, it was able to utilise a variety of nitrogen and carbon sources. Antimicrobial screening indicated that MTZ3.1T has potent anti- Staphylococcus aureus activity. On the basis of the polyphasic data, MTZ3.1T is proposed to represent a novel species, Streptomyces meridianus sp. nov. (= CECT 30416T = DSM 114037T=LMG 32463T).

Abstract
The grapevine variety identification is important in the wine's production chain since it is related to its quality, authenticity and singularity. In this study, we addressed the data augmentation approach to identify grape varieties with images acquired in-field. We tested the static transformations, RandAugment, and Cutmix methods. Our results showed that the best result was achieved by the Static method generating 5 images per sample (F1 = 0.89), however without a significative difference if compared with RandAugment generating 2 images. The worst performance was achieved by CutMix (F1 = 0.86).

Abstract