Abstract
Recent studies have focused on forecasting power demand in buildings to enhance energy management. However, the literature still lacks comparative analyses of power demand forecasting algorithms. In addition, more case studies involving different building typologies are needed, as each building exhibits distinct behavior and load profiles. This paper aims to develop machine learning models to forecast the power demand of a large shopping center in the northern region of Portugal. The main objective is to compare the performance of several machine learning models. The results are promising, demonstrating adequate performance even during most holidays.

Abstract
The cost of transportation of raw materials is a significant part of the procurement costs in the forestry industry. As a result, routing and scheduling techniques were introduced to the transportation of raw materials from extraction sites to transformation mills. However, little to no attention has been given to date to the material reception process at the mill. Another factor that motivated this study was the formation of large waiting queues at the mill gates and docks. Queues increase the reception time and associated costs. This work presents the development of a scheduling and reception system for deliveries at a mill. The scheduling system is based on Trucking Appointment Systems (TAS), commonly used at maritime ports, and on revenue management concepts. The developed system allocates each delivery to a timeslot and to an unloading dock using revenue management concepts. Each delivery is segmented according to its priority. Higher-segment deliveries have priority when there are multiple candidates to be allocated for one timeslot. The developed scheduling system was tested on a set of 120 daily deliveries at a Portuguese paper pulp mill and led to a reduction of 66% in the daily reception cost when compared to a first-in, first-out (FIFO) allocation approach. The average waiting time was also significantly reduced, especially in the case of high-priority trucks.

Abstract
Magneto-optic surface plasmon resonances (MOSPRs) rely on the interaction of magnetic fields with surface plasmon polaritons (SPP) to modulate plasmonic bands with magnetic fields and enhance magneto-optical activity. In the present work, a study on the magnetoplasmonic behavior of Ag/Fe bilayers is carried out by VIS-NIR spectroscopy and backed with SQUID measurements, determining the thickness-dependent magnetization of thin-film samples. The MOSPR sensing properties of Ag/Fe planar bilayers are simulated using Berreman's matrix formalism, from which an optimized structure composed of 15 nm of Ag and 12.5 nm of Fe is obtained. The selected structure is fabricated and characterized for refractive index (RI) sensitivity, reaching 4946 RIU-1 and returning an effective enhancement of refractometric sensitivity after magneto-optical modulation. A new optimized and cobalt-free magnetoplasmonic Ag/Fe bilayer structure is studied, fabricated, and characterized for the first time towards refractometric sensing, to the best of our knowledge. This configuration exhibits potential for enhancing refractometric sensitivity via magneto-optical modulation, thus paving the way towards a simpler, more accessible, and safe type of RI sensor with potential applications in chemical sensors and biosensors.

Abstract
This research determines how to integrate factors related to evacuation in emergency preparedness using techniques for Multicriteria Decision-Making (MCDM). A distinctive MCDM technique that incorporates human behavior into evacuation models enhances decision-making and safety during emergencies, especially in vulnerable populations. For this purpose, a hybrid combination of MCDM methods-CRiteria Importance Through Intercriteria Correlation (CRITIC), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Weighted Aggregated Sum Product Assessment (WASPAS)-is used to rank the vulnerability of Chilean regions by considering various factors. First, the related factors are ranked by CRITIC, and the result is that the psychosocial problem factor has the highest priority and weight. Then, according to the hybrid methods and CRITIC, all regions of Chile are ranked first with TOPSIS, WASPAS, and a combination of them to determine which one has the highest priority. The results show that the Santiago Metropolitan Region has the highest priority for vulnerability in all three methods.

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
Engineering is considered important in solving unsustainability. However, it is a complex problem that must be viewed, analysed and studied from various perspectives and taking with the contribution of various areas of knowledge. This work studied the use of interdisciplinarity as a contribution to interconnect ethics and sustainability with technical-scientific contents of electrical engineering. The research intended to use interdisciplinarity to help engineering students recognise that engineering is not ethically neutral, and that, therefore, the problems (and solutions) must also be analysed from an ethical and sustainability perspective. A framework was developed, and a pedagogical activity using interdisciplinarity was applied. Results show that, after the activity, students recognise that ethical values influence calculations in the area of electrical installations; and move from a single view to identify different alternatives, perspectives, motivations and multiple objectives. This leads to studying more alternatives and hopefully better overall technical solutions.