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Waterborne transport contributes to around 14% of the overall greenhouse gas emissions of transport in the European Union and it is among the most efficient modes of transport. Nonetheless, considering the aim of making the European Union carbon-neutral by 2050 and the fundamental role of waterborne transport within the European economy, effort is needed to reduce its environmental impact. This paper provides an assessment of research and innovation measures aiming at decreasing waterborne transport’s CO2 emissions by assessing European projects based on the European Commission’s Transport Research and Innovation Monitoring and Information System (TRIMIS). Additionally, it provides an outlook of the evolution of scientific publications and intellectual property activity in the area. The review of project findings suggests that there is no single measure which can be considered as a problem solver in the area of the reduction of waterborne CO2 emissions, and only the combination of different innovations should enable reaching this goal. The highlighted potential innovations include further development of lightweight composite materials, innovative hull repair methods, wind assisted propulsion, engine efficiency, waste heat electrification, hydrogen and alternative fuels. The assessment shows prevalence of funding allocated to technological measures; however, non-technological ones, like improved vessel navigation and allocation systems, also show a great potential for the reduction of CO2 emissions and reduction of negative environmental impacts of waterborne transport.

Many concepts and innovations aim to improve transport and mobility, while helping to decrease the externalities that transport imposes on society. Research and innovation monitoring tools are important to assess the current state of development so that research funding and policy making efforts can be aligned optimally. This paper presents a comprehensive approach which links technological developments in the transport sector in Europe to the objectives of the most recent policy developments, in particular, the 2020 European Sustainable and Smart Mobility Strategy. It does so by identifying and evaluating technologies from European Union-funded projects between 2007 and 2020, by means of a technology taxonomy. Information is provided at an aggregated level on funding characteristics of both projects and the technologies, while at the same time, the level of maturity of researched technologies in the most recent projects is identified. This study can aid policy makers to support the future development of transport technologies as part of pertinent policy strategies and identify research gaps.

This paper presents an artificial neural network (ANN) model that simulates user’s choice of electric or internal combustion engine automotive vehicles based on basic vehicle attributes (purchase price, range, operating cost, taxes due to emissions, time to refuel/recharge and vehicle price depreciation), with the objective of analyzing user behavior and creating a model that can be used to support policymaking. The ANN was trained using stated preference data from a survey carried out in six European countries, taking into account petrol, diesel and battery electric automotive vehicle attributes. Model results show that the electric vehicle parameters (especially purchase cost, range and recharge times), as well as the purchase cost of internal combustion engine vehicles, have the most influence on consumers’ vehicle choices. A graphical interface was created for the model, to make it easier to understand the interactions between different attributes and their impacts on consumer choices and thus help policy decisions.

Strain gauges and strain measurements have been widely used in structural health monitoring (SHM) systems as a means of detecting and localizing damage, due to their higher sensitivity to local damage. These damage identification techniques normally use strain related measurements such as the mode curvature, strain frequency response function or strain energy as the main parameter to detect damage. However, damage detection techniques based on acceleration measurements have also been investigated in the past, using modal parameter comparison and other methodologies. In this paper, the use of vibration-based strain measurements for use in SHM systems will be evaluated, with the purpose of characterizing their higher sensitivity in damage detection, when compared to other vibration measurements, such as acceleration-based measurements. Since the choice and use of the most damage sensitive parameter can lead to a more sensitive and robust system, the assessment of the more suitable sensor and processing of information is very important. For this purpose, numerical and experimental examples will be discussed to evaluate the higher performance of the strain gauges.

The increasing pressure on fuel economy has brought car manufacturers to implement solutions that improve vehicle efficiency, such as downsized engines, cylinder deactivation and advanced torque lock-up strategies. However, these solutions have a major drawback in terms of noise and vibration comfort. Downsized engines and lock-up strategies lead to the use of the engine at lower RPMs, and the reduced number of cylinders generates higher torque irregularities. Since the torque generated by the engine is transferred through flexible elements (clutch, torsional damper, gearbox, transmission, tire), these also impact the energy that is transferred to the vehicle body and perceived by the driver. This phenomenon leads to low frequency behavior, for instance booming noise and vibration. This paper presents a combined test and CAE modelling approach (1D/3D) to reverse engineer a vehicle equipped with a CPVA (centrifugal pendulum vibration absorber). The objectives were to fully understand and predict vehicle behavior with respect to the drivetrain torsional oscillations and low frequency booming noise and vibration. For this purpose, the procedure was divided in two phases: testing and modelling. The testing phase was used to get insight into the vehicle behavior, noise sources and noise transfer paths, using operational measurements. Moreover, dedicated component tests were carried out to obtain parameters to be used in the modelling phase, with the CPVA being the most complex and important component. The modelling phase used the test results as input to build a full vehicle model and to validate the booming noise results. The final model was fit for sensitivity studies and was also used to evaluate the performance of the CPVA, which is dedicated to the reduction of lock-up booming noise. Such an approach is a first step which can accelerate the SDPD (system driven product development) into a consolidated MBSE (model based system engineering) framework.

The fungi have wide distribution in ecosystems and can be found colonizing various substrates,where they act as efficient decomposers,participating in cycling of nutrients.The present study aimed to assess the diversity,richness and composition of filamentous fungi in leaf litter and aerial litter in a semi-deciduous forest in the Chapada Diamantina,Bahia,Brazil.Samples of leaf litter and aerial litter were collected monthly from October/2009 to September/2010 in eight installments in the studied area.Those samples were washed,placed in moist chambers and incubated.47 taxa were identified,37 in leaf litter and 35 in aerial litter,with 25 species common to both.A similarity of 69 % according to Sorensen index.The similarity was considered low when the sample points were compared to the same litter.Most fungi showed sporadic intervals.

This study evaluated the species composition of sand flies and identified potential vectors of Leishmania Ross species in rural areas of Porto Velho, Rondônia State, Brazil. American cutaneous leishmaniasis (ACL) is one of the gravest threats to public health in this state. Sand flies were collected over the course of 2014 and 2015 using HP light traps. Polymerase chain reaction was performed by targeting the Leishmania mkDNA region. In total, 2,344 sand flies were collected, from which 45 species, nine subgenera, and five species group were identified. The most abundant species were Lutzomyia antunesi (Coutinho) (n = 597, 25.47%), Lutzomyia ubiquitalis (Mangabeira) (n = 496, 21.16%), and Lutzomyia octavioi (Vargas) (n = 199, 8.49%). The greatest diversity occurred in the forest environment where the most abundant species were L. antunesi (n = 588, 25.07%), L. ubiquitalis (n = 493, 21.02%), L. octavioi (n = 199, 8.49%), and Lutzomyia flaviscutellata (Mangabeira) (n = 132, 5.63%). Two pools of L. ubiquitalis were positive for Leishmania DNA, which suggests that L. ubiquitalis is a putative vector of leishmaniasis in the municipality of Porto Velho.

Background: Although it is possible to preserve the aerial part of cassava in the form of silage, as demonstrated in previous studies, its low dry matter content can result in undesirable fermentation and increased effluent losses during silage, leading to a reduction in the final quality of the silage. A possible way to get around this problem would consist in mixing this silage with dehydrated by-products from the agroindustry. Objective: To evaluate the addition of dehydrated grape marc (DGM) to a silage of aerial parts of cassava (Manihot esculenta, Crantz) on the chemical composition, degradability and in vitro gas production of silage. Methods: A completely randomized experimental design was used, with two treatments: (I) silage of the aerial part of cassava without additive; (II) silage of the aerial part of cassava added with 10% dehydrated grape marc (DGM) in the natural matter, as an additive. After 30 days of fermentation, silages were evaluated to estimate the contents of dry matter (DM), crude protein (CP), ether extract (EE), neutral detergent fiber (NDF), total digestible nutrients (TDN), as well as pH, in vitro degradability, and cumulative gas production by semi-automatic in vitro gas production. Results: Addition of DGM did not affect CP, EE, NDF, nor TDN levels in silage. The DGM, however, promoted an increase in DM content (32.61 vs 30.31%) and a reduction in pH (4.00 vs 4.75) of the silage. The silage that received DGM presented higher degradability coefficients of soluble and potentially degradable fractions, which led to higher values of potential and effective degradability. Similarly, DGM promoted a reduction in particle colonization time (6.74 vs 10.01 h) and increased cumulative gas production (62.03 vs 57.82 mL/g DM). Conclusion: Addition of 10% dehydrated grape marc in the silage of aerial parts of cassava can be useful to reduce pH and increase dry matter contents of the silage.

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Objective: The research aims to analyze the relevance of smart cities in addressing the impacts of climate change, highlighting the need for sustainable urban planning and the use of technologies for mitigation and adaptation to contemporary environmental challenges.   Methodology: The methodology adopted consisted of a bibliographic review, carried out by surveying scientific articles in the SciELO, Google Scholar and Scopus databases, using specific keywords related to the topic, as well as Boolean operators AND and OR to refine the results. The inclusion criteria were limited to Brazilian studies published in the last six years, ensuring the currentness and relevance of the data.   Results: The results indicate that smart cities play a fundamental role in building a resilient urban environment, since they integrate information and communication technologies (ICTs) in the efficient management of resources, such as energy, water and mobility. Urban models based on artificial intelligence, the Internet of Things (IoT) and big data enable real-time monitoring, allowing rapid responses to extreme weather events, such as floods and heat waves. Furthermore, public policies aimed at sustainable mobility, encouraging the use of renewable energy and expanding urban green areas are highlighted as essential strategies for reducing the carbon footprint of cities. Engineering, especially in the fields of environmental, civil and electrical engineering, is a key player in implementing these solutions, developing sustainable infrastructures, improving public transport systems and optimizing smart grids.   Conclusion: It is concluded that the transition to smart cities not only contributes to mitigating the effects of climate change, but also significantly improves the quality of life of the population, promoting more inclusive, efficient and environmentally responsible urban spaces. Thus, the need for strategic planning that integrates technological innovation and sustainability as essential pillars for urban development in Brazil is reinforced.