Establishing guidelines for obtaining optimal cell sources to use in tendon tissue engineering strategies

Cell-based approaches in tissue engineering (TE) have been barely explored for the treatment of tendon and ligament (T/L) tissues, requiring the establishment of a widely available cell source with tenogenic potential. As T/L cells are scarce, stem cells may provide a good alternative. Understanding how resident cells behave in vitro, might be useful for recapitulating the tenogenic potential of stem cells for tendon TE applications. Therefore, we propose to isolate and characterize human T/L-derived cells (hTDCs and hLDCs) and compare their regenerative potential with stem cells from adipose tissue (hASCs) and amniotic fluid (hAFSCs)(1). T/L cells were isolated using different procedures and stem cells isolated as described elsewhere(1). Moreover, T/L cells were stimu- lated into the three mesenchymal lineages, using standard differentia- tion media. Cells were characterized for the typical stem cell markers as well as T/L related markers, namely tenascin-C, collagen I and III, decorin and scleraxis, using different complementary techniques such as real time RT-PCR, immunocytochemistry and flow cytometry. No differences were observed between T/L in gene expression and protein deposition. T/L cells were mostly positive for stem ness markers (CD73/CD90/CD105), and have the potential to differentiate towards osteogenesis, chondrogenesis and adipogenesis, demonstrated by the positive staining for AlizarinRed, SafraninO, ToluidineBlue and OilRed. hASCs and hAFSCs exhibit positive expression of all tenogenic mark- ers, although at lower levels than hTDCs and hLDCs. Nevertheless, stem cells availability is key factor in TE strategies, despite that it’s still required optimization to direct their tenogenic phenotype.

An evolutionary multi-objective optimization system for earthworks

Earthworks involve the levelling or shaping of a target area through the moving or processing of the ground surface. Most construction projects require earthworks, which are heavily dependent on mechanical equipment (e.g., excavators, trucks and compactors). Often, earthworks are the most costly and time-consuming component of infrastructure constructions (e.g., road, railway and airports) and current pressure for higher productivity and safety highlights the need to optimize earthworks, which is a nontrivial task. Most previous attempts at tackling this problem focus on single-objective optimization of partial processes or aspects of earthworks, overlooking the advantages of a multi-objective and global optimization. This work describes a novel optimization system based on an evolutionary multi-objective approach, capable of globally optimizing several objectives simultaneously and dynamically. The proposed system views an earthwork construction as a production line, where the goal is to optimize resources under two crucial criteria (costs and duration) and focus the evolutionary search (non-dominated sorting genetic algorithm-II) on compaction allocation, using linear programming to distribute the remaining equipment (e.g., excavators). Several experiments were held using real-world data from a Portuguese construction site, showing that the proposed system is quite competitive when compared with current manual earthwork equipment allocation.

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.

A proactive intelligent decision support system for predicting the popularity of online news

"Lecture notes in computer science series, ISSN 0302-9743, vol. 9273"

Modern optimization in earthwork construction

Earthworks tasks are often regarded in transportation projects as some of the most demanding processes. In fact, sequential tasks such as excavation, transportation, spreading and compaction are strongly based on heavy mechanical equipment and repetitive processes, thus becoming as economically demanding as they are time-consuming. Moreover, actual construction requirements originate higher demands for productivity and safety in earthwork constructions. Given the percentual weight of costs and duration of earthworks in infrastructure construction, the optimal usage of every resource in these tasks is paramount. Considering the characteristics of an earthwork construction, it can be looked at as a production line based on resources (mechanical equipment) and dependency relations between sequential tasks, hence being susceptible to optimization. Up to the present, the steady development of Information Technology areas, such as databases, artificial intelligence and operations research, has resulted in the emergence of several technologies with potential application bearing that purpose in mind. Among these, modern optimization methods (also known as metaheuristics), such as evolutionary computation, have the potential to find high quality optimal solutions with a reasonable use of computational resources. In this context, this work describes an optimization algorithm for earthworks equipment allocation based on a modern optimization approach, which takes advantage of the concept that an earthwork construction can be regarded as a production line.

Earthwork optimization system for sustainable highway construction

In highway construction, earthworks refer to the tasks of excavation, transportation, spreading and compaction of geomaterial (e.g. soil, rockfill and soil-rockfill mixture). Whereas relying heavily on machinery and repetitive processes, these tasks are highly susceptible to optimization. In this context Artificial Intelligent techniques, such as Data Mining and modern optimization can be applied for earthworks. A survey of these applications shows that they focus on the optimization of specific objectives and/or construction phases being possible to identify the capabilities and limitations of the analyzed techniques. Thus, according to the pinpointed drawbacks of these techniques, this paper describes a novel intelligent earthwork optimization system, capable of integrating DM, modern optimization and GIS technologies in order to optimize the earthwork processes throughout all phases of design and construction work. This integration system allows significant savings in time, cost and gas emissions contributing for a more sustainable construction.

Literacia, media e cidadania - Livro de atas do 3.º Congresso

(Excerto) A terceira edição do Congresso sobre Literacia, Media e Cidadania (LMC) teve lugar nos dias 17 e 18 de abril de 2015, em Lisboa, no Pavilhão do Conhecimento. Organizado pelo GILM – Grupo Informal sobre Literacia para os Media, o evento, que contou com a participação de cerca de 250 profissionais, teve como eixo central a temática “Literacia Mediática e Leituras Críticas do Mundo”. Durante dois dias de trabalho, procurou-se pro-mover uma reflexão crítica sobre a atualidade e o mundo, e o modo como os media a representam, com o objetivo de aprender a olhar e a ler criticamente os ecrãs e as mensagens e textos que produzem, o modo como os cidadãos os usam, como se apropriam deles e como produzem e partilham informação. Estes e outros tópicos relacionados foram apresentados e debatidos em 4 sessões plenárias, 16 sessões de comunicações livres e 4 workshops, acompanhados de uma mostra de projetos, produtos e serviços patentes no átrio do Pavilhão.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational in- telligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two il- lustrative Traffic Engineering methods are described, allowing to attain routing con- figurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Quantitative image analysis as a tool for Yarrowia lipolytica dimorphic growth evaluation in different culture media

Yarrowia lipolytica, a yeast strain with a huge biotechnological potential, capable to produce metabolites such as γ-decalactone, citric acid, intracellular lipids and enzymes, possesses the ability to change its morphology in response to environmental conditions. In the present study, a quantitative image analysis (QIA) procedure was developed for the identification and quantification of Y. lipolytica W29 and MTLY40-2P strains dimorphic growth, cultivated in batch cultures on hydrophilic (glucose and N-acetylglucosamine (GlcNAc) and hydrophobic (olive oil and castor oil) media. The morphological characterization of yeast cells by QIA techniques revealed that hydrophobic carbon sources, namely castor oil, should be preferred for both strains growth in the yeast single cell morphotype. On the other hand, hydrophilic sugars, namely glucose and GlcNAc caused a dimorphic transition growth towards the hyphae morphotype. Experiments for γ-decalactone production with MTLY40-2P strain in two distinct morphotypes (yeast single cells and hyphae cells) were also performed. The obtained results showed the adequacy of the proposed morphology monitoring tool in relation to each morphotype on the aroma production ability. The present work allowed establishing that QIA techniques can be a valuable tool for the identification of the best culture conditions for industrial processes implementation.

Design and optimization of an extrusion die for the production of wood–plastic composite profiles

In this work, the optimization of an extrusion die designed for the production of a wood–plastic composite (WPC) decking profile is investigated. The optimization was performed with the help of numerical tools, more precisely, by solving the continuity and momentum conservation equations that govern such flow, and aiming to balance properly the flow distribution at the extrusion die flow channel outlet. To capture the rheological behavior of the material, we used a Bird-Carreau model with parameters obtained from a fit to the (shear viscosity versus shearrate) experimental data, collected from rheological tests. To yield a balanced output flow, several numerical runs were performed by adjusting the flow restriction at different regions of the flow-channel parallel zone crosssection. The simulations were compared with the experimental results and an excellent qualitative agreement was obtained, allowing, in this way, to attain a good balancing of the output flow and emphasizing the advantages of using numerical tools to aid the design of profile extrusion dies.

In silico constraint-based strain optimization methods: the quest for optimal cell factories

Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed.

Cost-effective energy and carbon emission optimization in building renovation – A case-study in a low income neighbourhood

Construction sector is one of the major responsible for energy consumption and carbon emissions and renovation of existing buildings plays an important role in the actions to mitigate climate changes. Present work is based on the methodology developed in IEA Annex 56, allowing identifying cost optimal and cost effective renovation scenarios improving the energy performance. The analysed case study is a residential neighbourhood of the municipality of Gaia in Portugal. The analysis compares a reference renovation scenario (without improving the energy performance of the building) with a series of alternative renovation scenarios, including the one that is being implemented.

IEA EBC Annex56 vision for cost effective energy and carbon emissions optimization in building renovation

Building sector has become an important target for carbon emissions reduction, energy consumption and resources depletion. Due to low rates of replacement of the existing buildings, their low energy performances are a major concern. Most of the current regulations are focused on new buildings and do not account with the several technical, functional and economic constraints that have to be faced in the renovation of existing buildings. Thus, a new methodology is proposed to be used in the decision making process for energy related building renovation, allowing finding a cost-effective balance between energy consumption, carbon emissions and overall added value.

Literacia, media e cidadania: actas do 1º congresso nacional

[Excerto] Este livro de atas reúne um conjunto de comunicações apresentadas no 1º Congresso de Literacia, Média, Cidadania, realizado na Universidade do Minho, em 2011.

User expectations for media sharing practices in open display networks

Open Display Networks have the potential to allow many content creators to publish their media to an open-ended set of screen displays. However, this raises the issue of how to match that content to the right displays. In this study, we aim to understand how the perceived utility of particular media sharing scenarios is affected by three independent variables, more specifically: (a) the locativeness of the content being shared; (b) how personal that content is and (c) the scope in which it is being shared. To assess these effects, we composed a set of 24 media sharing scenarios embedded with different treatments of our three independent variables. We then asked 100 participants to express their perception of the relevance of those scenarios. The results suggest a clear preference for scenarios where content is both local and directly related to the person that is publishing it. This is in stark contrast to the types of content that are commonly found in public displays, and confirms the opportunity that open displays networks may represent a new media for self-expression. This novel understanding may inform the design of new publication paradigms that will enable people to share media across the display networks.