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This paper defines a conversion factor included in the European technical specification for the design of fibre–polymer composite structures that considers the effects of moisture on the mechanical properties of fiber-reinforced polymer (FRP) composites exposed to natural weathering. The first part of the paper presents a field investigation about the durability of four pultruded glass fiber–reinforced polymer (GFRP) structures in service for 11–22 years in a Mediterranean climate. Their performance was evaluated by dynamic mechanical analysis and mechanical tests on small-scale coupons. The changes of thermophysical and mechanical properties showed low-to-moderate degradation. The second part of the paper presents the design-oriented methodology to define the moisture conversion factor. The results from the experimental study and those gathered from a literature data survey on the retention of mechanical properties of FRP materials after long-term exposure to natural weathering were analyzed. Based on these data and statistical considerations, a value of 0.85 was adopted for the natural weathering moisture conversion factor. [ABSTRACT FROM AUTHOR]

This paper proposes a novel approach to the fuzzy newsvendor problem for inventory management applications. The main contributions of the paper are the following: a new credibility estimation is proposed, to explore the neighborhood around the most impactful demand scenarios; a simulation procedure was designed for the different demand scenarios, which allows comparison of the proposed approach with classical and fuzzy multi-item newsvendor problems; a modified genetic algorithm (GA) is introduced to ameliorate previous genetic algorithms in both the generation and evaluation of solutions. The new formulation of the fuzzy newsvendor problem, together with the modified GA, were shown to improve the average profit by up to 55% in problems with low-budget scenarios. [ABSTRACT FROM AUTHOR]

As it becomes increasingly necessary to reduce aviation-related emissions, condensation trails present an additional challenge. These are arguably responsible for the largest contribution to radiative forcing in the sector, but the phenomenon is still not as well understood as those involving other agents. The present study employs a large eddy simulation (LES) parametrization to validate a previously developed contrail model in order to assess the feasibility of a multi-model approach to increase confidence in simulations of contrail cirrus formation. Subsequently, the computational model was used to analyze the impact of e-fuels in contrail dynamics, resulting in reductions of over 7% and 14%, respectively, in average contrail lifetime and optical depth, with such improvements increasing if higher blending limits are utilized. This confirmed the potential for e-fuels as the most viable option for near-future large-scale implementations among all sustainable aviation fuel alternatives. [ABSTRACT FROM AUTHOR]

Robotic systems are increasingly present in dynamic environments. This paper proposes a hierarchical control structure wherein a behavior tree (BT) is used to improve the flexibility and adaptability of an omni-directional mobile robot for point stabilization. Flexibility and adaptability are crucial at each level of the sense–plan–act loop to implement robust and effective robotic solutions in dynamic environments. The proposed BT combines high-level decision making and continuous execution monitoring while applying non-linear model predictive control (NMPC) for the point stabilization of an omni-directional mobile robot. The proposed control architecture can guide the mobile robot to any configuration within the workspace while satisfying state constraints (e.g., obstacle avoidance) and input constraints (e.g., motor limits). The effectiveness of the controller was validated through a set of realistic simulation scenarios and experiments in a real environment, where an industrial omni-directional mobile robot performed a point stabilization task with obstacle avoidance in a workspace. [ABSTRACT FROM AUTHOR]

In order to achieve a more efficient allocation of healthcare resources in the near future, it is crucial to understand the patterns and causes of excess mortality and hospitalizations. Neonatal mortality still poses a significant challenge, particularly in developed nations where the mortality rates are already low and healthcare resources are generally available to most of the population. Furthermore, the low mortality rates mean that the data available for modeling are often very limited, restricting the modeling methods that can be used. It is also important that the chosen methods allow for explainable, non-black-box models that can be interpreted by healthcare professionals. Considering these challenges, the work hereby presented thoroughly analyzed the time series of the neonatal mortality rates in Portugal between 2014 and 2019 in terms of trend and seasonal patterns. The applicability and performance of different data-based methods were also analyzed. Furthermore, the mortality rates were studied in terms of their relation to environmental variables, such as temperature and air pollution indicators, with the goal of establishing causal relations between such variables and excess mortality. The preliminary results show that ARMA, neural and fuzzzy models are able to forecast the studied mortality rates with good performance. In particular, neural models have the best predictive performance, while fuzzy models are well suited to obtain interpretable models with acceptable performance. [ABSTRACT FROM AUTHOR]

Airborne wind energy (AWE) has received increasing attention during the last decade, with the goal of achieving electricity generation solutions that may be used as a complement or even an alternative to conventional wind turbines. Despite that several concepts have already been proposed and investigated by several companies and research institutions, no mature technology exists as yet. The mode of energy generation, the type of wing, the take-off and landing approaches, and the control mechanisms, to name a few, may vary among AWE crosswind systems. Given the diversity of possibilities, it is necessary to determine the most relevant factors that drive AWE exploration. This paper presents a review on the characteristics of currently existing AWE technological solutions, focusing on the hardware architecture of crosswind systems, with the purpose of providing the information required to identify and assess key factors to be considered in the choice of such systems. The identified factors are categorized into four distinct classes: technical design factors (aerodynamic performance, mass-to-area ratio, durability, survivability); operational factors (continuity of power production, controllability, take-off and landing feasibility); fabrication and logistical factors (manufacturability, logistics); and social acceptability factors (visual impact, noise impact, ecological impact, safety). [ABSTRACT FROM AUTHOR]

As the push for carbon-neutral transport continues, the aviation sector is facing increasing pressure to reduce its carbon footprint. Furthermore, commercial air traffic is expected to resume the continuous growth experienced until the pandemic, highlighting the need for reduced emissions. The use of alternative fuels plays a key role in achieving future emission goals, while also lowering the dependency on fossil fuels. The so-called sustainable aviation fuels (SAF), which encompass bio and synthetic fuels, are currently the most viable option, but hydrogen is also being considered as a long-term solution. The present paper reviews the production methods, logistical and technological barriers, and potential for future mass implementation of these alternative fuels. In general, biofuels currently present higher technological readiness levels than other alternatives. Sustainable mass production faces critical feedstock-related challenges that synthetic fuels, together with other solutions, can overcome. All conventional fuel replacements, though with different scopes, will be important in meeting long-term goals. Government support will play an important role in accelerating and facilitating the transition towards sustainable aviation. [ABSTRACT FROM AUTHOR]

In the last few decades, there has been a growing necessity for systems that handle market changes and personalized customer needs with near mass production efficiency, defined as the new mass customization paradigm. The Industry 5.0 vision further enhances the human-centricity aspect, in the necessity for manufacturing systems to cooperate with workers, taking advantage of their problem-solving capabilities, creativity, and expertise of the manufacturing process. A solution is to develop a flexible manufacturing system capable of handling different customer requests and real-time decisions from operators. This paper tackles these aspects by proposing a digital twin of a robotic system for solution preparation capable of making real-time scheduling decisions and forecasts using a simulation model while allowing human interventions. A discrete event simulation model was used to forecast possible system improvements. The simulation handles real-time scheduling considering the possibility of adding identical parallel machines. Results show that processing multiple jobs simultaneously with more than one machine on critical processes, increasing the robot speed, and using heuristics that emphasize the shortest transportation time can reduce the overall completion time by 82%. The simulation model has an animated visualization window for a deeper understanding of the system. [ABSTRACT FROM AUTHOR]

This paper presents an experimental study about the effects of hygrothermal and outdoor ageing on a polyurethane (PUR) adhesive used in civil engineering applications. Small-scale adhesive coupons were exposed to different types of ageing environments for up to two years: (i) immersion in demineralised water at 20 and 40 °C, (ii) immersion in salt water at 20 and 40 °C, (iii) continuous condensation environment at 40 °C, and (iv) outdoor ageing in Lisbon, Portugal. At predetermined times, after a desorption period until constant mass, the effects of such exposure on the physical and mechanical responses of the PUR adhesive was investigated using the following techniques: (i) water sorption, (ii) dynamic mechanical analyses (DMA); (iii) flexural; and (iv) in-plane shear tests. The diffusion mechanisms observed were not purely Fickian; a long relaxation period was noticed, with water molecules being continuously incorporated in the adhesive until the end of the experiments; two alternative analytical modelling approaches were successfully used to simulate the diffusion processes. After immersion in water and salt water for two years, the viscoelastic behaviour of the adhesive showed signs of post-curing phenomena, and some of the physical degradation was found to be reversible due to drying, although it was not explicitly quantified; accordingly, the T g showed increasing trends (11-14%). The mechanical properties of the adhesive showed signs of irreversible degradation mechanisms, more relevant on the in-plane shear properties, with reductions up to 26% in strength and 44% in modulus under the harsher conditions. Flexural properties also exhibited irreversible degradation, with maximum reductions up to 30% in strength and 36% in modulus. Increased temperature did not have a significant effect in the flexural and shear strength, but caused higher degradation in the corresponding moduli. The degradation caused by salt water immersion and continuous condensation was comparable to that in demineralized water immersion (at the same temperature). [ABSTRACT FROM AUTHOR]

The growing environmental concerns and liberalization of energy markets have resulted in an increased competition between utilities and a strong focus on efficiency. To develop new energy efficiency measures and optimize operations, utilities seek new market-related insights and customer engagement strategies. This paper proposes a clustering-based methodology to define the segmentation of residential gas consumers. The segments of gas consumers are obtained through a detailed clustering analysis using smart metering data. Insights are derived from the segmentation, where the segments result from the clustering process and are characterized based on the consumption profiles, as well as according to information regarding consumers' socio-economic and household key features. The study is based on a sample of approximately one thousand households over one year. The representative load profiles of consumers are essentially characterized by two evident consumption peaks, one in the morning and the other in the evening, and an off-peak consumption. Significant insights can be derived from this methodology regarding typical consumption curves of the different segments of consumers in the population. This knowledge can assist energy utilities and policy makers in the development of consumer engagement strategies, demand forecasting tools and in the design of more sophisticated tariff systems. [ABSTRACT FROM AUTHOR]

Left ventricular ejection fraction (LVEF) constitutes an important physiological parameter for the assessment of cardiac function, particularly in the settings of coronary artery disease and heart failure. This study explores the use of routinely and easily acquired variables in the intensive care unit (ICU) to predict severely depressed LVEF following ICU admission. A retrospective study was conducted. We extracted clinical physiological variables derived from ICU monitoring and available within the MIMIC II database and developed a fuzzy model using sequential feature selection and compared it with the conventional logistic regression (LR) model. Maximum predictive performance was observed using easily acquired ICU variables within 6 hours after admission and satisfactory predictive performance was achieved using variables acquired as early as one hour after admission. The fuzzy model is able to predict LVEF ≤ 25% with an AUC of 0.71 ± 0.07, outperforming the LR model, with an AUC of 0.67 ± 0.07. To the best of the authors’ knowledge, this is the first study predicting severely impaired LVEF using multivariate analysis of routinely collected data in the ICU. We recommend inclusion of these findings into triaged management plans that balance urgency with resources and clinical status, particularly for reducing the time of echocardiographic examination. [ABSTRACT FROM AUTHOR]