Abstract
The fourth industrial revolution is based on the production process’s digitisation to promote traceability, reduction of waste and decision support. This transition from the physical to the information domain requires, besides the process’s digital representation, sensors and transducers capable of capturing the system states. In the case of agricultural processes, due to the heterogeneity of production conditions, as well as the large area in which it takes place, physical characterisation often requires a large number of sensors spread over several hectares. This fact makes the economic costs associated with the digitisation of agriculture a very relevant aspect. In particular, if robust and precise sensors are to be deployed. Within this reference frame, this paper describes the approach taken to develop low-cost sensors capable of measuring soil moisture at three different depths. Robustness is achieved through the use of materials with high mechanical strength and corrosion resistance and both accuracy and repeatability are accomplished by using a signal conditioning strategy based on a programmable analogue front-end. Details about the methodology used are presented throughout the article. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

Abstract

Abstract
The excitation of two different electromagnetic surface waves-surface plasmon polaritons (SPPs) and Bloch surface waves (BSWs)-is demonstrated in a 1-D metal-dielectric photonic crystal with numerical and experimental studies. The discussed structure consists of an Ag-TiO2 thin-film stack forming a metal-insulator-metal-insulator device. The thickness of the TiO2 layer placed between the metals is tested for two different values (50 and 300 nm), which also allows the excitation of guided-mode resonances. It is observed that BSWs in this metal-dielectric structure behave similar to the case of all-dielectric photonic crystals, whereas the SPP modes display similar properties to those excited in metal-insulator-metal cavities. The sensitivity of these surface states to variations in the refractive index (RI) of the external dielectric is characterized. For the case of the plasmonic modes, a maximum sensitivity of (7.2 +/- 0.3) x 10(3) nm/RIU was measured, while for the BSW the maximum sensitivity was (1.20 +/- 0.05) x 10(2) nm/RIU. Due to the large field enhancement and penetration on external media, these surface states display exceptional properties for application in optical sensors, and the presented results provide interesting possibilities in the design of novel sensing structures with a flexible selection of surface states for interrogation.

Abstract
This work aims to identify teaching and learning practices in practical classes of Computer Network Technology courses, which promote the use of the Physical Laboratory (PL) as an epistemic tool to improve learning in epistemic terms. Content analysis of Multimodal Narrations (MN) of three classes by two teachers were used. An MN aggregates and organizes the data collected in the PL environment. Based on the results, we infer that the student and the teacher, under certain conditions, use the physical laboratory as an epistemic tool since the physical interactions prove its use and reuse. In addition, this study allows, in the context of work in the physical laboratory of networks, to identify that the orchestrations of mediation patterns adopted by the teacher influence the students' epistemic practices and the use of the laboratory as a tool to produce new knowledge. The following contributions are presented: (1) The quality of the students' epistemic practices is increased if, in the teacher's dynamics of mediation, the control of the students' action is reduced; (2) The orchestration of the teacher's mediation patterns is essential to achieve beneficial results in student learning with the use of artifacts from the physical laboratory of Computer Networks; (3) For the physical laboratory to become an epistemic tool, it is necessary that the mediation standards allow students to develop epistemic practices to a high or very high degree and there is a certain mediation orchestration.

Abstract
Imbalanced data are present in various business sectors and must be handled with the proper resampling methods and classification algorithms. To handle imbalanced data, there are numerous resampling and learning method combinations; nonetheless, their effective use necessitates specialised knowledge. In this paper, several approaches, ranging from more accessible to more advanced in the domain of data resampling techniques, will be considered to handle imbalanced data. The application developed delivers recommendations of the most suitable combinations of techniques for a specific dataset by extracting and comparing dataset meta-feature values recorded in a knowledge base. It facilitates effortless classification and automates part of the machine learning pipeline with comparable or better results than state-of-the-art solutions and with a much smaller execution time.

Abstract
The transportation industry focuses on reducing vehicle weight for fuel economy and emissions. This emphasis promotes the use of coaches, which raises concerns about passenger safety in frontal collisions. The proposal is to correlate the crashworthiness of coaches with the replacement of fibreglass composite materials by a state-of-the-art polymer (DCPD). Based on the ECE R29 standard, FEM models solved by Pamcrash (R) assess the vehicle's crashworthiness. Cross-referencing these results with the Eco-Design X technique, two models are evaluated in terms of environmental impact. The LeanDfX methodology involves multiple analyses for design domains, including model optimisation, manufacturing processes, and eco-design. On a performance scale of 0% to 100%, different 'X' domains are evaluated. The Eco-Design study allowed the assessing the environmental impacts of the proposed solution compared to the original models, is conducted using Simapro v9.2.0.2 and the ReCiPe 2016 methodology. The novel design proposed modifications to the models resulted in significant structural behaviour improvements for driver's physical integrity. The cross results of Design-for-Crashworthiness and Design-for-Eco-Design using the innovative LeanDfX framework provide a new perspective to be integrated into the automotive industry. The use of DCPD is expected to lead to a more crashworthy and environmentally friendly design, while ensuring passenger safety.