Abstract

Abstract
A sensor based on the fiber Bragg grating (FBG) and additive manufacturing for diameter variation measurement is proposed and experimentally demonstrated in this work. Two designs were proposed: a FBG alone and a FBG in series with a spring. Three tests were developed for each design, and at the end, the statistical treatment was performed. The designs were fabricated using a 3D printer, and the FBG sensor is embedded. The results demonstrated that the structures proposed in this work can be used to monitor diameter variation, among other applications. The sensors, with and without spring in series, presented sensitivities of 0.0671 nm/mm and 0.5116 nm/mm, respectively, with a good linear response greater than 0.99.

Abstract
Habitat loss, climate change, and pesticide use are key threats affecting beetle populations. This paper describes Scarabreed, a project that contributes to mitigate the beetle decline crisis. It was carried out by a team of six European students from different engineering fields and nationalities within the European Project Semester (EPS) at the Instituto Superior de Engenharia do Porto (ISEP), a project-based and teamwork learning framework. The designed solution - the Beetle Breeder Version 2 (BBV2) - consists of a smart modular vivarium created especially for beetle breeding. It monitors and controls relevant habitat parameters and offers two user-friendly interfaces (on-device and a Web application). The innovative modular structure of the vivarium allows easy scaling, customisation, and transportation. As a whole, the project offers significant environmental benefits: (i) facilitates the captive breeding of endangered beetle species, promoting population restoration efforts; (ii) fosters, as an educational tool, youth and general public awareness about the crucial role beetles play in ecosystems; and (iii) adopts eco-efficient and responsible business practices by following ethics and sustainability driven design and marketing.

Abstract
Adaptive protocols enable the construction of more efficient state preparation circuits in variational quantum algorithms (VQAs) by utilizing data obtained from the quantum processor during the execution of the algorithm. This idea originated with Adaptive Derivative-Assembled Problem-Tailored variational quantum eigensolver (ADAPT-VQE), an algorithm that iteratively grows the state preparation circuit operator by operator, with each new operator accompanied by a new variational parameter, and where all parameters acquired thus far are optimized in each iteration. In ADAPT-VQE and other adaptive VQAs that followed it, it has been shown that initializing parameters to their optimal values from the previous iteration speeds up convergence and avoids shallow local traps in the parameter landscape. However, no other data from the optimization performed at one iteration is carried over to the next. In this work, we propose an improved quasi-Newton optimization protocol specifically tailored to adaptive VQAs. The distinctive feature in our proposal is that approximate second derivatives of the cost function are recycled across iterations in addition to optimal parameter values. We implement a quasi-Newton optimizer where an approximation to the inverse Hessian matrix is continuously built and grown across the iterations of an adaptive VQA. The resulting algorithm has the flavor of a continuous optimization where the dimension of the search space is augmented when the gradient norm falls below a given threshold. We show that this inter-optimization exchange of second-order information leads the approximate Hessian in the state of the optimizer to be consistently closer to the exact Hessian. As a result, our method achieves a superlinear convergence rate even in situations where the typical implementation of a quasi-Newton optimizer converges only linearly. Our protocol decreases the measurement costs in implementing adaptive VQAs on quantum hardware as well as the runtime of their classical simulation.

Abstract

Abstract
The rehabilitation of burn patients is essential and is intrinsically linked to conventional rehabilitation; the motivational challenges faced by burn patients in maintaining engagement with these rehabilitation programs are well known. It is understood that the use of other resources, particularly technological ones, associated with conventional rehabilitation could overcome these constraints and thereby optimize the rehabilitation program and health outcomes. The objective of this study is to synthesize the available evidence on the use of exergames in rehabilitation programs for burn patients. This systematic review was developed following the guidelines of the Joanna Briggs Institute (JBI). The search was conducted in the following databases: Medline (R), CINAHL (R), Sports Discus (R), Cochrane (R), and Scopus (R) during May 2025. The PRISMA Checklist Model was used to organize the information from the selected studies. Seven RCTs were included, involving a total of 236 participants. Outcomes related to the use of exergames in the rehabilitation of burn patients were identified, including increased range of motion, functionality, strength, speed of movement, improved balance, reduced fear and pain, and satisfaction with the technological resource used. It is believed that the results of this review, which confirmed the advantage of using exergames, such as Nintendo Wii, PlayStation, Xbox Kinect, or Wii Fit, to optimize the functionality of burn patients, can support clinical decision-making and encourage the integration of exergames to improve rehabilitation programs for burn patients.