Abstract
In the study, a new method for analyzing Electrocardiogram (ECG) signals is suggested, which is vital for detecting and treating heart diseases. The technique focuses on improving ECG signal classification, particularly in identifying different heart conditions like arrhythmias and myocardial infarctions. An enhanced version of the differential evolution (DE) algorithm integrated with neural networks is leveraged to classify these signals effectively. The process starts with preprocessing and extracting key features from ECG signals. These features are then processed by a multi-layer perceptron (MLP), a common neural network for ECG analysis. However, traditional MLP training methods have limitations, such as getting trapped in suboptimal solutions. To overcome this, an advanced DE algorithm is used, incorporating a partition-based strategy, opposition-based learning, and local search mechanisms. This improved DE algorithm optimizes the MLP by fine-tuning its weights and biases, using them as starting points for further refinement by the Gradient Descent with Momentum (GDM) local search algorithm. Extensive experiments demonstrate that this novel training approach yields better results than the traditional method. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Abstract
This paper compares the performance of Simulated Annealing and Tabu Search meta-heuristics in addressing a parallel machine scheduling problem aimed at minimizing weighted earliness, tardiness, total flowtime, and machine deterioration costs-a multi-objective optimization problem. The problem is transformed into a single-objective problem using weighting and weighting relative distance methods. Four scenarios, varying in the number of jobs and machines, are created to evaluate these metaheuristics. Computational experiments indicate that Simulated Annealing consistently yields superior solutions compared to Tabu Search in scenarios with lower dimensions despite longer run times. Conversely, Tabu Search performs better in higher-dimensional scenarios. Furthermore, it is observed that solutions generated by different weighting methods exhibit similar performance. © 2025 The Author(s).

Abstract
The broadband absorption coefficient spectrum of the rabbit lung presents some particular characteristics that allow the identification of the chromophores in this tissue. By performing a weighted combination of the absorption spectra of water, hemoglobin, DNA, proteins and the pigments melanin and lipofuscin, it was possible to obtain a good match to the experimental absorption spectrum of the lung. Such reconstruction provided reasonable information about the contents of the tissue components in the lung tissue, and allowed to identify a similar accumulation of melanin and lipofuscin. The broadband absorption coefficient spectrum of the rabbit lung was reconstructed from the absorption spectra of tissue components. The similar accumulation of melanin and lipofuscin was retrieved from the broadband baseline in the absorption coefficient spectrum, and the calculation of the absorption fold ratios for proteins, DNA and hemoglobin provided good results. The method used is innovative and can be improved to allow the quantification of tissue components concentrations directly. image

Abstract
Background: Students with Autism Spectrum Disorder (ASD) often face significant challenges in traditional educational environments, including difficulties in social interaction, engagement, and adapting to standard learning methods. These barriers can hinder their academic and personal development, highlighting the need for more inclusive and adaptive educational solutions. Objective: This study investigated whether immersive VR-based STEM learning environments can support the cognitive, social and behavioural development of pupils with ASD. We evaluated usability and accessibility needs, validated the artefact through expert consensus, and measured pre-post changes using established standardised instruments. Methodology: The research followed the Design Science Research (DSR) approach within STEM (Science, Technology, Engineering, and Mathematics) to develop VR-based learning experiences adapted to the needs of students with ASD. The Delphi method involved experts in defining best practices and educational strategies, helping to ensure that the proposed solutions were appropriate and aligned with student characteristics. The study included a control and an experimental group, both composed of students with ASD and typically developing students, assessing the impact of VR on learning and socialisation. Results: The findings suggest that VR-based learning environments may support improvements in cognitive, behavioural and social skills, although causal inference is limited by the small sample size and absence of randomisation. Conclusions: This study provides preliminary evidence that VR-based learning environments may help address educational barriers for students with ASD by offering structured, engaging and adaptable environments that could support inclusion and development.

Abstract
Abstract Companies adopt agile methodologies for various reasons, primarily due to their adaptability to change and evolving business demands. In this context, addressing non-functional requirements (NFRs) may not always be a priority and can present challenges for agile teams. The focus on User Stories present in agile methods and tools often does not offer explicit alternatives for documenting NFRs. In this research, we perform a survey to explore five different strategies for documenting NFRs, to identify which fits better for different types of quality attributes and to understand the strengths and drawbacks of each one. As a result, the participants considered certain strategies as being more or less suitable for specifying different types of quality attributes. For instance, while Story Labeling was rarely recommended for security requirements, using Story Sub-sections or Verification Rules were highly recommended for this kind of quality attribute. Our results also evaluated the strategies considering several factors, such as the level of detail and requirement duplication. As a practical implication, the results of this work can provide guidance to agile development teams in choosing the most suitable alternative for each NFR documentation.

Abstract