Ion exchange dependent electroactive phase content and electrical properties of poly(vinylidene fluoride)/Na(M)Y composites

Different metal-ion exchanged NaY zeolite, Na(M)Y, were used to prepare poly(vinylidene fluoride) based composites by solvent casting and melting crystallization. The effect of different metal ion-exchanged zeolites on polymer crystallization and electrical properties was reported. Cation-framework interactions and hydration energy of the cations determined that K+ is the most efficient exchanged ion in NaY zeolite, followed by Cs+ and Li+. The electroactive phase crystallization strongly depends on the ions present in the zeolite, leading to variations of the surface energy characteristics of the Na(M)Y zeolites and the polymer chain ability of penetration in the zeolite. Thus, Na(Li)Y and NaY induces the complete electroactive -phase crystallization of the crystalline phase of PVDF, while Na(K)Y only induces it partly and Na(Cs)Y is not able to promote the crystallization of the electroactive phase. Furthermore, different ion size/weigh and different interaction with the zeolite framework results in significant variations in the electrical response of the composite. In this way, iinterfacial polarization effects in the zeolite cavities and zeolite-polymer interface, leads to strong increases of the dielectric constant on the composites with lightest ions weakly bound to the zeolite framework. Polymer composite with Na(Li)Y show the highest dielectric response, followed by NaY and Na(K)Y. Zeolite Na(Cs)Y contribute to a decrease of the dielectric constant of the composite. The results show the relevance of the materials for sensor development.

Effect of butadiene/styrene ratio, block structure and carbon nanotube content on the mechanical and electrical properties of thermoplastic elastomers after UV ageing

Thermoplastic elastomers based on a triblock copolymer styrene-butadiene-styrene (SBS) with different butadiene/styrene ratios, block structure and carbon nanotube (CNT) content were submitted to accelerated weathering in a Xenontest set up, in order to evaluate their stability to UV ageing. It was concluded that ageing mainly depends on butadiene/styrene ratio and block structure, with radial block structures exhibiting a faster ageing than linear block structures. Moreover, the presence of carbon nanotubes in the SBS copolymer slows down the ageing of the copolymer. The evaluation of the influence of ageing on the mechanical and electrical properties demonstrates that the mechanical degradation is higher for the C401 sample, which is the SBS sample with the largest butadiene content and a radial block structure. On the other hand, a copolymer derivate from SBS, the styrene-ethylene/butadiene-styrene (SEBS) sample, retains a maximum deformation of ~1000% after 80 h of accelerated ageing. The hydrophobicity of the samples decreases with increasing ageing time, the effect being larger for the samples with higher butadiene content. It is also verified that cytotoxicity increases with increasing UV ageing with the exception of SEBS, which remains not cytotoxic up to 80 h of accelerated ageing time, demonstrating its potential for applications involving exposition to environmental conditions.

Towards high performance and multi-functional structural membranes using advanced fibrous and textile materials

Scientific and technological advancements in the area of fibrous and textile materials have greatly enhanced their application potential in several high-end technical and industrial sectors including construction, transportation, medical, sports, aerospace engineering, electronics and so on. Excellent performance accompanied by light-weight, mechanical flexibility, tailor-ability, design flexibility, easy fabrication and relatively lower cost are the driving forces towards wide applications of these materials. Cost-effective fabrication of various advanced and functional materials for structural parts, medical devices, sensors, energy harvesting devices, capacitors, batteries, and many others has been possible using fibrous and textile materials. Structural membranes are one of the innovative applications of textile structures and these novel building skins are becoming very popular due to flexible design aesthetics, durability, lightweight and cost benefits. Current demand on high performance and multi-functional materials in structural applications has motivated to go beyond the basic textile structures used for structural membranes and to use innovative textile materials. Structural membranes with self-cleaning, thermoregulation and energy harvesting capability (using solar cells) are examples of such recently developed multi-functional membranes. Besides these, there exist enormous opportunities to develop wide varieties of multi-functional membranes using functional textile materials. Additionally, it is also possible to further enhance the performance and functionalities of structural membranes using advanced fibrous architectures such as 2D, 3D, hybrid, multi-layer and so on. In this context, the present paper gives an overview of various advanced and functional fibrous and textile materials which have enormous application potential in structural membranes.

RoboCup Soccer Leagues

RoboCup was created in 1996 by a group of Japanese, American, and European Artificial Intelligence and Robotics researchers with a formidable, visionary long-term challenge: “By 2050 a team of robot soccer players will beat the human World Cup champion team.” At that time, in the mid 90s, when there were very few effective mobile robots and the Honda P2 humanoid robot was presented to a stunning public for the first time also in 1996, the RoboCup challenge, set as an adversarial game between teams of autonomous robots, was fascinating and exciting. RoboCup enthusiastically and concretely introduced three robot soccer leagues, namely “Simulation,” “Small-Size,” and “Middle-Size,” as we explain below, and organized its first competitions at IJCAI’97 in Nagoya with a surprising number of 100 participants [RC97]. It was the beginning of what became a continously growing research community. RoboCup established itself as a structured organization (the RoboCup Federation www.RoboCup.org). RoboCup fosters annual competition events, where the scientific challenges faced by the researchers are addressed in a setting that is attractive also to the general public. and the RoboCup events are the ones most popular and attended in the research fields of AI and Robotics.RoboCup further includes a technical symposium with contributions relevant to the RoboCup competitions and beyond to the general AI and robotics.

Comparison of single and multi-objective evolutionary algorithms for robust link-state routing

Traffic Engineering (TE) approaches are increasingly impor- tant in network management to allow an optimized configuration and resource allocation. In link-state routing, the task of setting appropriate weights to the links is both an important and a challenging optimization task. A number of different approaches has been put forward towards this aim, including the successful use of Evolutionary Algorithms (EAs). In this context, this work addresses the evaluation of three distinct EAs, a single and two multi-objective EAs, in two tasks related to weight setting optimization towards optimal intra-domain routing, knowing the network topology and aggregated traffic demands and seeking to mini- mize network congestion. In both tasks, the optimization considers sce- narios where there is a dynamic alteration in the state of the system, in the first considering changes in the traffic demand matrices and in the latter considering the possibility of link failures. The methods will, thus, need to simultaneously optimize for both conditions, the normal and the altered one, following a preventive TE approach towards robust configurations. Since this can be formulated as a bi-objective function, the use of multi-objective EAs, such as SPEA2 and NSGA-II, came nat- urally, being those compared to a single-objective EA. The results show a remarkable behavior of NSGA-II in all proposed tasks scaling well for harder instances, and thus presenting itself as the most promising option for TE in these scenarios.

Logic programming and artificial neural networks in breast cancer detection

About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.

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.

Mechanical vs. electrical hysteresis of carbon nanotube/styrene-butadiene-styrene composites and their influence in the electromechanical response

The interesting properties of thermoplastics elastomers can be combined with carbon nanotubes (CNT) for the development of large strain piezoresistive composites for sensor applications. Piezoresistive properties of the composites depend on CNT content, with the gauge factor increasing for concentrations around the percolation threshold, mechanical and electrical hysteresis. The SBS copolymer composition (butadiene/styrene ratio) influences the mechanical and electrical hysteresis of composites and, therefore, the piezoresistive response. This work reports on the electrical and mechanical response of CNT/SBS composites with 4%wt nanofiller content, due to the larger electromechanical response. C401 and C540 SBS copolymers with 80% and 60% butadiene content, respectively have been selected. The copolymer with larger amount of soft phase (C401) shows a rubber-like mechanical behavior, with mechanical hysteresis increasing linearly with strain until 100% strain. The copolymer with the larger amount of hard phase (C540) just shows rubber-like behavior for low strains. The piezoresistive sensibility is similar for both composites for low strains, with a GF≈ 5 for 5% strain. The electrical hysteresis shows opposite behavior than the mechanical hysteresis, increasing with strain for both composites, but with higher increase for softer copolymer, C401. The GF increases with increasing strain, but this increase is larger for composites with lower amounts of soft phase due to the distinct initial modulus and deformation of the soft and hard phases of the copolymer. The soft phase shows larger strain under a given stress than the harder phase and the conductive pathway rearrangements in the composites are different for both phases, the harder copolymer (C540) showing higher piezoresistive sensibility, GF≈ 18, for 20% strain.

Thrombophilia screening: An artificial neural network approach

Thrombotic disorders have severe consequences for the patients and for the society in general, being one of the main causes of death. These facts reveal that it is extremely important to be preventive; being aware of how probable is to have that kind of syndrome. Indeed, this work will focus on the development of a decision support system that will cater for an individual risk evaluation with respect to the surge of thrombotic complaints. The Knowledge Representation and Reasoning procedures used will be based on an extension to the Logic Programming language, allowing the handling of incomplete and/or default data. The computational framework in place will be centered on Artificial Neural Networks.

Artificial neural networks in diagnosis of liver diseases

Liver diseases have severe patients’ consequences, being one of the main causes of premature death. These facts reveal the centrality of one`s daily habits, and how important it is the early diagnosis of these kind of illnesses, not only to the patients themselves, but also to the society in general. Therefore, this work will focus on the development of a diagnosis support system to these kind of maladies, built under a formal framework based on Logic Programming, in terms of its knowledge representation and reasoning procedures, complemented with an approach to computing grounded on Artificial Neural Networks.

Proving the suitability of magnetoelectric stimuli for tissue engineering applications

A novel approach for tissue engineering applications based on the use of magnetoelectric materials is presented. This work proves that magnetoelectric Terfenol-D/poly(vinylidene fluoride-co-trifluoroethylene) composites are able to provide mechanical and electrical stimuli to MC3T3-E1 pre-osteoblast cells and that those stimuli can be remotely triggered by an applied magnetic field. Cell proliferation is enhanced up to 25% when cells are cultured under mechanical (up to 110 ppm) and electrical stimulation (up to 0.115 mV), showing that magnetoelectric cell stimulation is a novel and suitable approach for tissue engineering allowing magnetic, mechanical and electrical stimuli.

Biomaterials for cartilage tissue engineering under mechanical stimulus

Tese de Doutoramento em Ciências (Especialidade de Física)

Modelling and verifying smell-free architectures with the Archery language

Architectural (bad) smells are design decisions found in software architectures that degrade the ability of systems to evolve. This paper presents an approach to verify that a software architecture is smellfree using the Archery architectural description language. The language provides a core for modelling software architectures and an extension for specifying constraints. The approach consists in precisely specifying architectural smells as constraints, and then verifying that software architectures do not satisfy any of them. The constraint language is based on a propositional modal logic with recursion that includes: a converse operator for relations among architectural concepts, graded modalities for describing the cardinality in such relations, and nominals referencing architectural elements. Four architectural smells illustrate the approach.