Abstract
Early detection of melanoma is crucial for preventing severe complications and increasing the chances of successful treatment. Existing deep learning approaches for melanoma skin lesion diagnosis are deemed black-box models, as they omit the rationale behind the model prediction, compromising the trustworthiness and acceptability of these diagnostic methods. Attempts to provide concept-based explanations are based on post-hoc approaches, which depend on an additional model to derive interpretations. In this paper, we propose an inherently interpretable framework to improve the interpretability of concept-based models by incorporating a hard attention mechanism and a coherence loss term to assure the visual coherence of concept activations by the concept encoder, without requiring the supervision of additional annotations. The proposed framework explains its decision in terms of human-interpretable concepts and their respective contribution to the final prediction, as well as a visual interpretation of the locations where the concept is present in the image. Experiments on skin image datasets demonstrate that our method outperforms existing black-box and concept-based models for skin lesion classification. © 2023 IEEE.

Abstract
Medical rescuers are the frontline for COVID-19 and their psychological experience and health are major concerns to our society and healthcare system. This study aims to understand how medical rescuers psychologically experienced this pandemic and explore the contributing variables to COVID-19 anxiety. Portuguese medical rescuers (n = 203) answered questions about their COVID-19 experience, the COVID-19 Anxiety Scale, Patient-Health Questionnaire, Perceived Stress Scale, Obsessive-Compulsive Inventory, and Well-Being Questionnaire. Rescuers presented low COVID-19 anxiety and low-moderate levels of fear. Most already faced or were facing changes in their job-related tasks, did not change household and did not feel stigma/discrimination. COVID-19 workplace security measures were considered moderately adequate and low anxiety, depression and obsessive-compulsive symptoms, low to moderate stress and moderate well-being were found. Only COVID-19 fear and security measures, anxiety, depression and obsessive-compulsive symptoms explained COVID-19 anxiety. Overall, findings showed these rescuers were psychologically well adjusted during the pandemic's initial stages. © 2023 Associacao Portuguesa de Psicologia. All rights reserved.

Abstract
The spectral response of a SPR (surface plasmon resonance) sensor depends on the engineering of the conducting layer. In this paper, we analyze theoretically the spectra of a D-shaped SPR PCF (photonic crystal fiber) refractive index sensor considering four different plasmonic materials: Ag, Au, Ga-doped zinc oxide (GZO) and an Ag-nanowire metamaterial. The sensing properties provided by each material and how they form the bases to design multiplasmonic resonance sensors are the focus of our discussion.

Abstract

Abstract
This article presents a framework to assist in the design of technology-based interactive services for active mobility, which allows the data collected from the sensors to be made available to citizens. The proposed framework was developed based on data collected in focus group sessions held with potential stakeholders and on related models and frameworks. It consists of 8 steps, namely: strategy, scope, structure, skeleton, aesthetics and execution. It will enable the presentation of relevant information that will help users of active modes of transport in decision making in choosing a safe and comfortable route, assist professionals involved in the elaboration of interactive projects and promote more collaborative urban planning. © 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)

Abstract
As the need for replacing fossil and other non-renewable energy sources with renewables becomes more critical and urgent, wind energy appears to be among the two or three best choices for the short and medium time frames. The dominance of wind energy as the first choice in many regions, leads to an increasing impact of wind power quality on the overall grid. Wind energy’s inherent intermittent nature, both in intensity and longevity, could be an impediment to its adoption unless utility operators have the tools to anticipate the impact and integrate wind resources seamlessly by increasing or reducing its contribution to the overall capacity of the grid. The wind forecasting science is well established and has been the subject of serious study in multiple fields such as fluid dynamics, statistical analysis and numerical simulation and modeling. With the renewed interest and dependence on wind as a major energy source, these efforts have increased exponentially. One of the areas that shows great promise in developing improved forecasting tools, is the category of “Biological Inspired Optimization Techniques. The study presented in this paper is the result of a study to survey and assess an array of forecasting models and algorithms. © MIR Labs, www.mirlabs.net/ijcisim/index.html