Epidermis recreation in spongy-like hydrogels: New opportunities to explore epidermis-like analogues

[Excerpt] On the road to successfully achieving skin regeneration, 3D matrices/scaffolds that provide the adequate physico-chemical and biological cues to recreate the ideal healing environment are believed to be a key element [1], [2] and [3]. Numerous polymeric matrices derived from both natural [4] and [5] and synthetic [6], [7] and [8] sources have been used as cellular supports; nowadays, fewer matrices are simple carriers, and more and more are ECM analogues that can actively participate in the healing process. Therefore, the attractive characteristics of hydrogels, such as high water content, tunable elasticity and facilitated mass transportation, have made them excellent materials to mimic cells’ native environment [9]. Moreover, their hygroscopic nature [10] and possibility of attaining soft tissues-like mechanical properties mean they have potential for exploitation as wound healing promoters [11], [12], [13] and [14]. Nonetheless, hydrogels lack natural cell adhesion sites [15], which limits the maximization of their potential in the recreation of the cell niche. This issue has been tackled through the use of a range of sophisticated approaches to decorate the hydrogels with adhesion sequences such as arginine-glycine-aspartic acid (RGD) derived from fibronectin [16], [17] and [18], and tyrosine-isoleucine-glycine-serine-arginine (YIGSR) derived from laminin [18] and [19], which not only aim to modulate cell adhesion, but also influencing cell fate and survival [18]. Nonetheless, its widespread use is still limited by significant costs associated with the use of recombinant bioactive molecules.

Detection of road accident accumulation zones with a visual analytics approach

Nowadays, road accidents are a major public health problem, which increase is forecasted if road safety is not treated properly, dying about 1.2 million people every year around the globe. In 2012, Portugal recorded 573 fatalities in road accidents, on site, revealing the largest decreasing of the European Union for 2011, along with Denmark. Beyond the impact caused by fatalities, it was calculated that the economic and social costs of road accidents weighted about 1.17% of the Portuguese gross domestic product in 2010. Visual Analytics allows the combination of data analysis techniques with interactive visualizations, which facilitates the process of knowledge discovery in sets of large and complex data, while the Geovisual Analytics facilitates the exploration of space-time data through maps with different variables and parameters that are under analysis. In Portugal, the identification of road accident accumulation zones, in this work named black spots, has been restricted to annual fixed windows. In this work, it is presented a dynamic approach based on Visual Analytics techniques that is able to identify the displacement of black spots on sliding windows of 12 months. Moreover, with the use of different parameterizations in the formula usually used to detect black spots, it is possible to identify zones that are almost becoming black spots. Through the proposed visualizations, the study and identification of countermeasures to this social and economic problem can gain new grounds and thus the decision- making process is supported and improved.

Safety classification using GIS in decision-making process to define priority road interventions

Given the current economic situation of the Portuguese municipalities, it is necessary to identify the priority investments in order to achieve a more efficient financial management. The classification of the road network of the municipality according to the occurrence of traffic accidents is fundamental to set priorities for road interventions. This paper presents a model for road network classification based on traffic accidents integrated in a geographic information system. Its practical application was developed through a case study in the municipality of Barcelos. An equation was defined to obtain a road safety index through the combination of the following indicators: severity, property damage only and accident costs. In addition to the road network classification, the application of the model allows to analyze the spatial coverage of accidents in order to determine the centrality and dispersion of the locations with the highest incidence of road accidents. This analysis can be further refined according to the nature of the accidents namely in collision, runoff and pedestrian crashes.

Recycled asphalt mixtures with foamed bitumen: an alternative to build ecofriendly road pavements

Nowadays, recycling has become a very important objective for the society in the scope of a closed loop product life cycle. In recent years, new recycling techniques have been developed in the area of road pavements that allow the incorporation of high percentages of reclaimed asphalt (RA) materials in recycled asphalt mixtures. The use of foamed bitumen for production of recycled asphalt mixtures is one of those techniques, which also allows the reduction of the mixing temperatures (warm mix technology). However, it is important to evaluate if this solution can maintain or improve the performance of the resulting mixtures. Thus, the main aim of the present study is to assess the performance of warm recycled asphalt mixtures incorporating foamed bitumen as the new binder and 50% RA, in comparison with a control mixture using conventional bitumen. Four mixtures have been produced with 50% RA, one of them at typical high mixing temperatures with a conventional bitumen (control mixture) and the other three with foamed bitumen at different production temperatures. These four mixtures were tested to evaluate their compactability and water sensitivity. The laboratory test results showed that the production of recycled mixtures with foamed bitumen can be reduced by 40ºC without changing the performance of the resulting mixtures.

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

Assessment of distinctive road runoff quality in coastal areas, based on a monitoring case study

High levels of marine salt deposition present in coastal areas have a relevant effect on road runoff characteristics. This study assesses this effect with the purpose of identifying the relationships between monitored water quality parameters and intrinsic site variables. To achieve this objective, an extensive monitoring program was conducted on a Portuguese coastal highway. The study included 30 rainfall events, in different weather, traffic, and salt deposition conditions. The evaluations of various water quality parameters were carried out in over 200 samples. In addition, the meteorological, hydrological, and traffic parameters were continuously measured. The salt deposition rates were determined by means of a wet candle device, which is an innovative feature of the monitoring program. The relation between road runoff pollutants and independent variables associated with weather, traffic, and salt deposition conditions was assessed. Significant correlations among pollutants were observed. A high salinity concentration and its influence on the road runoff were confirmed. Furthermore, the concentrations of the most relevant pollutants seemed to be very dependent on some meteorological variables, particularly the duration of the antecedent dry period prior to each rainfall event and the average wind speed.

Modelling tyre-road noise with data mining techniques

The research aimed to establish tyre-road noise models by using a Data Mining approach that allowed to build a predictive model and assess the importance of the tested input variables. The data modelling took into account three learning algorithms and three metrics to define the best predictive model. The variables tested included basic properties of pavement surfaces, macrotexture, megatexture, and uneven- ness and, for the first time, damping. Also, the importance of those variables was measured by using a sensitivity analysis procedure. Two types of models were set: one with basic variables and another with complex variables, such as megatexture and damping, all as a function of vehicles speed. More detailed models were additionally set by the speed level. As a result, several models with very good tyre-road noise predictive capacity were achieved. The most relevant variables were Speed, Temperature, Aggregate size, Mean Profile Depth, and Damping, which had the highest importance, even though influenced by speed. Megatexture and IRI had the lowest importance. The applicability of the models developed in this work is relevant for trucks tyre-noise prediction, represented by the AVON V4 test tyre, at the early stage of road pavements use. Therefore, the obtained models are highly useful for the design of pavements and for noise prediction by road authorities and contractors.

Geotechnical engineering for sustainable transportation infrastructure

This paper highlights how transportation geotechnics can interact with transportation infrastructures and how through the planning, design, construction and maintenance can contribute to ensure solutions more safe, reliable and resilient in the future. In this context sustainable concepts are discussed and applied as best practices to preserve natural resources and assuring socio-economic and environment benefits for the society

Development of an intelligent earthwork optimization system

Tese de Doutoramento em Engenharia Civil.

Avaliação do risco para peões em ambiente urbano

Dissertação de mestrado integrado em Engenharia Civil

A new page on the road book of inorganic mercury in fish body - tissue distribution and elimination following waterborne exposure and post-exposure periods

prova tipográfica / uncorrected proof

O papel do transporte público nos padrões de mobilidade no acesso a um campus universitário

Dissertação de mestrado integrado em Engenharia Civil