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With the growing need for alternative energy sources, research into energy harvesting technologies has increased considerably in recent years. The particular case of energy harvesting on road pavements is a very recent area of research. This paper deals with the development of energy harvesting technologies for road pavements, identifies the technologies that are being studied and developed, examines how such technologies can be divided into different classes and gives a technical analysis and comparison of those technologies, using the results achieved with prototypes.

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. Environmental and economic assessment of pavement construction and management practices for enhancing pavement sustainability. Resources, Conservation and Recycling, Elsevier, 2017, 116, pp.15-31. 10.1016/j.resconrec.2016 WMA mixtures, reducing energy consumed and emissions generated in mixtures production, applying 7 in-place recycling techniques, and implementing preventive treatments. In this study, a comprehensive 8 and integrated pavement life cycle costing-life cycle assessment model was developed to investigate, 9 from a full life cycle perspective, the extent to which several pavement engineering solutions, namely 10 hot in-plant recycling mixtures, WMA, cold central plant recycling and preventive treatments, are 11 efficient in improving the environmental and economic dimensions of pavement infrastructure 12 sustainability, when applied either separately or in combination, in the construction and management 13 of a road pavement section located in Virginia, USA. Furthermore, in order to determine the preference 14 order of alternative scenarios, a multicriteria decision analysis method was applied. The results showed 15 that the implementation of a recycling-based maintenance and rehabilitation strategy where the asphalt 16 mixtures are of type hot-mix asphalt containing 30% RAP, best suits the multidimensional and 17 conflicting interests of decision-makers. This outcome was found to be robust even when different 18 design and performance scenarios of the mixtures and type of treatments are considered. 19 20

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SARS-CoV-2 emerged in late 2019. Since then, it has spread to several countries, becoming classified as a pandemic. So far, there is no definitive treatment or vaccine, so the best solution is to prevent transmission between individuals through social distancing. However, it is not easy to measure the effectiveness of these distance measures. Therefore, this study uses data from Google COVID-19 Community Mobility Reports to understand the Portuguese population’s mobility patterns during the COVID-19 pandemic. In this study, the Rt value was modeled for Portugal. In addition, the changepoint was calculated for the population mobility patterns. Thus, the mobility pattern change was used to understand the impact of social distance measures on the dissemination of COVID-19. As a result, it can be stated that the initial Rt value in Portugal was very close to 3, falling to values close to 1 after 25 days. Social isolation measures were adopted quickly. Furthermore, it was observed that public transport was avoided during the pandemic. Finally, until the emergence of a vaccine or an effective treatment, this is the new normal, and it must be understood that new patterns of mobility, social interaction, and hygiene must be adapted to this reality.

The pavement maintenance and rehabilitation (M&R) strategy selection problem is an exceedingly hard problem to solve optimally. In this paper, a novel Adaptive Hybrid Genetic Algorithm (AHGA) is proposed which incorporates Local Search (LS) techniques into Genetic Algorithms (GA) to improve the overall efficiency and effectiveness of the search. Specifically, it contains two dynamic learning mechanisms to guide and combine the exploration and exploitation search processes adaptively. The first learning mechanism aims to assess the worthiness of conducting an LS reactively and to control the computational resources allocated to the application of this search technique efficiently. The second learning mechanism uses instantaneously learned probabilities to select from a set of pre-defined LS operators which compete against each other for selection which is the most appropriate at any particular stage of the search to take over from the evolutionary-based search process. The new AHGA is compared to a non-hybridized version of the GA by applying the algorithms to several case studies in order to determine the best pavement M&R strategy that minimizes the present value of the total M&R costs. The results show that the proposed AHGA statistically outperforms the traditional GA in terms of efficiency.

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