Abstract
Districting can reduce the complexities of delivery problems by segmenting its dimensions while facilitating drivers' familiarity with their work areas, fostering personal connections with customers, and enhancing satisfaction. This paper introduces and evaluates multiple heuristic approaches for route creation, to identify the most efficient method for intra and inter-districting routing. Out of 18 tested variants, the best-performing developed approach used a Lin-Khernigan-based heuristic, later converting it to a Shortest Hamiltonian Path in each district, creating inter-district connections to a hypothetical medoid in the next district to visit and utilizing asymmetric road distances. Although sub-optimal, the results obtained were satisfactory and the best components for route creation were identified. The models were developed and tested using real-world data from a parcel delivery company operating in the Porto metropolitan area of Portugal.

Abstract
The use of 3D modelling in medical education is a revolutionary tool during the learning process. In fact, this type of technology enables a more interactive teaching approach, making information retention more effective and enhancing students’ understanding. 3D modelling allows for the creation of precise representations of the human body, as well as interaction with three-dimensional models, giving students a better spatial understanding of the different organs and systems and enabling simulations of surgical and technical procedures. This way, medical education is enriched with a more realistic and safe educational experience. The goal is to understand whether, when students and schools are challenged, they play an important role in addressing health issues in their community. School-led projects are directed towards educational scenarios that emphasize STEM education, tackling relevant public health problems through open-school initiatives. By implementing an educational scenario focused on 3D modelling and leveraging technology, we aim to raise community awareness on public health issues. © 2025 Elsevier B.V., All rights reserved.

Abstract
The telecommunications sector faces a major challenge of high customer churn. Despite this, there is still a lack of research that explores the switching intention for telecommunication services, particularly with bundle services that currently dominate the market. This study aims to provide insight into consumer behaviour regarding bundle telecommunication services by examining the factors that impact satisfaction and switching intention, both directly and indirectly. Eighteen hypotheses were defined based on the literature, and were tested through a quantitative study with 910 bundle service customers using structural equation modelling with Smart-PLS. The results show that internet and television services have the strongest indirect impact on switching intention, mediated by overall satisfaction and loyalty. Additionally, the results indicate that switching costs and barriers do not significantly affect switching intention, and surprisingly, perceived contractual lock-in positively influences switching intention. This study provides a comprehensive understanding of the customer experience with bundled telecommunications services and offers relevant insights for telecommunication managers to prevent customer loss to competitors.

Abstract
Wireless communications in the THz frequency band is an envisioned revolutionary technology for sixth Generation (6G) networks. However, such frequencies impose certain coverage and device design challenges that need to be efficiently overcome. To this end, the development of cost- and energy-efficient approaches for scaling these networks to realistic scenarios constitute a necessity. Among the recent research trends contributing to these objectives belongs the technology of Reconfigurable Intelligent Surfaces (RISs). In fact, several high-level descriptions of THz systems based on RISs have been populating the literature. Nevertheless, hardware implementations of those systems are still very scarce, and not at the scale intended for most envisioned THz scenarios. In this paper, we overview some of the most significant hardware design and signal processing challenges with THz RISs, and present a preliminary analysis of their impact on the overall link budget and system performance, conducted in the framework of the ongoing TERRAMETA project.

Abstract
This paper presents pyZtrategic: a library that embeds strategic term rewriting and attribute grammars in the Python programming language. Strategic term rewriting and attribute grammars are two powerful programming techniques widely used in language engineering: The former relies on strategies to apply term rewrite rules in defining large-scale language transformations, while the latter is suitable to express context-dependent language processing algorithms. Thus, pyZtrategic offers Python programmers recursion schemes (strategies) which apply term rewrite rules in defining large scale language transformations. It also offers attribute grammars to express context-dependent language processing algorithms. PyZtrategic offers the best of those two worlds, thus providing powerful abstractions to express software maintenance and evolution tasks. Moreover, we developed several language engineering problems in pyZtrategic, and we compare it to well established strategic programming and attribute grammar systems. Our preliminary results show that our library offers similar expressiveness as such systems, but, unfortunately, it does suffer from the current poor runtime performance of the Python language. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

Abstract
MotivationAccurate determination and quantification of the taxonomic composition of microbial communities, especially at the species level, is one of the major issues in metagenomics. This is primarily due to the limitations of commonly used 16S rRNA reference databases, which either contain a lot of redundancy or a high percentage of sequences with missing taxonomic information. This may lead to erroneous identifications and, thus, to inaccurate conclusions regarding the ecological role and importance of those microorganisms in the ecosystem.ResultsThe current study presents MIMt, a new 16S rRNA database for archaea and bacteria's identification, encompassing 47 001 sequences, all precisely identified at species level. In addition, a MIMt2.0 version was created with only curated sequences from RefSeq Targeted loci with 32 086 sequences. MIMt aims to be updated twice a year to include all newly sequenced species. We evaluated MIMt against Greengenes, RDP, GTDB and SILVA in terms of sequence distribution and taxonomic assignments accuracy. Our results showed that MIMt contains less redundancy, and despite being 20 to 500 times smaller than existing databases, outperforms them in completeness and taxonomic accuracy, enabling more precise assignments at lower taxonomic ranks and thus, significantly improving species-level identification.