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Abstract
Abstract Inductively coupled plasma-mass spectrometry analysis was conducted to examine the geochemical composition of K-feldspars from various aplite-pegmatites in the Barroso-Alvão field, focusing on the differences between Li-rich and Li-barren aplite-pegmatites. The study revealed significant variations in the concentrations of minor and trace elements (Rb, Tl, Li, Ga, Pb, Cs, Ba, Be, Ta, and Sn) present in the K-feldspars of Li-barren, spodumene-rich, and petalite-rich aplite-pegmatites. The data also indicate a geographical trend in both mineralogy and geochemistry across the aplite-pegmatites of the Barroso-Alvão field. Li-barren aplite-pegmatites are more concentrated in the southeast, spodumene-rich dominate the center, and petalite-rich varieties are more common in the northwest. Additionally, portable X-ray fluorescence analysis was performed on the crystals of the same samples to evaluate the feasibility of in situ geochemical analysis of K-feldspars, aiming to determine whether an aplite-pegmatite can be quickly identified as Li-rich. This approach seeks to provide a rapid field assessment of whether an aplite-pegmatite justifies further exploration for Li mining. Notably, the trace amounts of Li, Sn, P, and Ta found in K-feldspars are likely due to mineral inclusions of spodumene, cassiterite, apatite, and columbite–tantalite minerals, as observed petrographically in one of these Li-rich aplite-pegmatites.

Abstract
Hypertension (HT) is the leading risk factor for cerebral small vessel disease (CSVD). White matter lesions (WML) linked to CSVD are visible on conventional neuroimaging, likely reflecting late irreversible stages of the CSVD pathological cascade. Despite the prevalence of this disease, the mechanistic link between CSVD, hypertension and WML remains poorly understood. In this prospective, cross-sectional study, 44 hypertensive patients asymptomatic of CSVD underwent diffusion-weighted magnetic resonance imaging (dMRI) and transcranial Doppler (TCD) monitoring of the right middle and left posterior cerebral arteries (MCA and PCA, respectively) to assess dynamic cerebral autoregulation (dCA) and vasomotor reactivity to CO2 (VRCO2). Diffusion measures from two dMRI models quantified the WM structural integrity: fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity from diffusion tensor imaging (DTI), and quantitative anisotropy (QA) and isotropy from q-space diffeomorphic reconstruction (QSDR). We examined the association of dMRI measures with dCA and VRCO2 through correlational tractography. We observed that impaired VRCO2 was associated with decreased WM structural integrity, indicated by the associations of reduced QA and increased MD and RD with lower VRCO2. Regarding dCA, we found a negative association between QA and the phase parameter, indicating an increased dCA in association with reduced WM structural integrity. Our results suggest that HT-induced remodeling of the cerebrovasculature, with enhanced dCA and impaired VRCO2, may contribute to impaired brain function and lead to CSVD, and highlight the potential of integrating TCD studies and dMRI, including QSDR-derived metrics, to investigate the natural progression of CSVD from its early, asymptomatic stages.

Abstract
In many e-commerce platforms user communities share product information in the form of reviews and ratings to help other consumers to make their choices. This study develops a new theoretical framework generating a bipartite network of products sold by Amazon.com in the category musical instruments, by linking products through the reviews. We analyze product rating and perceived helpfulness of online customer reviews and the relationship between the centrality of reviews, product rating and the helpfulness of reviews using Clustering, regression trees, and random forests algorithms to, respectively, classify and find patterns in 2214 reviews. Results demonstrate: (1) that a high number of reviews do not imply a high product rating; (2) when reviews are helpful for consumer decision-making we observe an increase on the number of reviews; (3) a clear positive relationship between product rating and helpfulness of the reviews; and (4) a weak relationship between the centrality measures (betweenness and eigenvector) giving the importance of the product in the network, and the quality measures (product rating and helpfulness of reviews) regarding musical instruments. These results suggest that products may be central to the network, although with low ratings and with reviews providing little helpfulness to consumers. The findings in this study provide several important contributions for e-commerce businesses' improvement of the review service management to support customers' experiences and online customers' decision-making.

Abstract
Monodic folk music has traditionally been preserved in physical documents. It constitutes a vast archive that needs to be digitized to facilitate comprehensive analysis using AI techniques. A critical component of music score digitization is the transcription of lyrics, an extensively researched process in Optical Character Recognition (OCR) and document layout analysis. These fields typically require the development of specific models that operate in several stages: first, to detect the bounding boxes of specific texts, then to identify the language, and finally, to recognize the characters. Recent advances in vision language models (VLMs) have introduced multimodal capabilities, such as processing images and text, which are competitive with traditional OCR methods. This paper proposes an end-to-end system for extracting lyrics from images of handwritten musical scores. We aim to evaluate the performance of two state-of-the-art VLMs to determine whether they can eliminate the need to develop specialized text recognition and OCR models for this task. The results of the study, obtained from a dataset in a real-world application environment, are presented along with promising new research directions in the field. This progress contributes to preserving cultural heritage and opens up new possibilities for global analysis and research in folk music.

Abstract