Ibuprofen-loaded poly(trimethylene carbonate-co-ϵ- caprolactone) electrospun fibres for nerve regeneration

The development of scaffolds that combine the delivery of drugs with the physical support provided by electrospun fibres holds great potential in the field of nerve regeneration. Here it is proposed the incorporation of ibuprofen, a well-known non-steroidal anti-inflammatory drug, in electrospun fibres of the statistical copolymer poly(trimethylene carbonate-co-ε-caprolactone) [P(TMC-CL)] to serve as a drug delivery system to enhance axonal regeneration in the context of a spinal cord lesion, by limiting the inflammatory response. P(TMC-CL) fibres were electrospun from mixtures of dichloromethane (DCM) and dimethylformamide (DMF). The solvent mixture applied influenced fibre morphology, as well as mean fibre diameter, which decreased as the DMF content in solution increased. Ibuprofen-loaded fibres were prepared from P(TMC-CL) solutions containing 5% ibuprofen (w/w of polymer). Increasing drug content to 10% led to jet instability, resulting in the formation of a less homogeneous fibrous mesh. Under the optimized conditions, drug-loading efficiency was above 80%. Confocal Raman mapping showed no preferential distribution of ibuprofen in P(TMC-CL) fibres. Under physiological conditions ibuprofen was released in 24h. The release process being diffusion-dependent for fibres prepared from DCM solutions, in contrast to fibres prepared from DCM-DMF mixtures where burst release occurred. The biological activity of the drug released was demonstrated using human-derived macrophages. The release of prostaglandin E2 to the cell culture medium was reduced when cells were incubated with ibuprofen-loaded P(TMC-CL) fibres, confirming the biological significance of the drug delivery strategy presented. Overall, this study constitutes an important contribution to the design of a P(TMC-CL)-based nerve conduit with anti-inflammatory properties.

Two protocols without periodicity for the global and preemptive scheduling problem of multi-mode real-time systems upon multiprocessor Platforms

We consider the problem of scheduling a multi-mode real-time system upon identical multiprocessor platforms. Since it is a multi-mode system, the system can change from one mode to another such that the current task set is replaced with a new task set. Ensuring that deadlines are met requires not only that a schedulability test is performed on tasks in each mode but also that (i) a protocol for transitioning from one mode to another is specified and (ii) a schedulability test for each transition is performed. We propose two protocols which ensure that all the expected requirements are met during every transition between every pair of operating modes of the system. Moreover, we prove the correctness of our proposed algorithms by extending the theory about the makespan determination problem.

LLF schedulability analysis on multiprocessor platforms

LLF (Least Laxity First) scheduling, which assigns a higher priority to a task with smaller laxity, has been known as an optimal preemptive scheduling algorithm on a single processor platform. However, its characteristics upon multiprocessor platforms have been little studied until now. Orthogonally, it has remained open how to efficiently schedule general task systems, including constrained deadline task systems, upon multiprocessors. Recent studies have introduced zero laxity (ZL) policy, which assigns a higher priority to a task with zero laxity, as a promising scheduling approach for such systems (e.g., EDZL). Towards understanding the importance of laxity in multiprocessor scheduling, this paper investigates the characteristics of ZL policy and presents the first ZL schedulability test for any work-conserving scheduling algorithm that employs this policy. It then investigates the characteristics of LLF scheduling, which also employs the ZL policy, and derives the first LLF-specific schedulability test on multiprocessors. It is shown that the proposed LLF test dominates the ZL test as well as the state-of-art EDZL test.

Virtual Communities of Practice: Design and Development of Support Platforms and Participation Fostering

Mestrado em Engenharia Informática - Área de Especialização em Sistemas Gráficos e Multimédia

Energy-aware task mapping onto heterogeneous platforms using DVFS and sleep states

Heterogeneous multicore platforms are becoming an interesting alternative for embedded computing systems with limited power supply as they can execute specific tasks in an efficient manner. Nonetheless, one of the main challenges of such platforms consists of optimising the energy consumption in the presence of temporal constraints. This paper addresses the problem of task-to-core allocation onto heterogeneous multicore platforms such that the overall energy consumption of the system is minimised. To this end, we propose a two-phase approach that considers both dynamic and leakage energy consumption: (i) the first phase allocates tasks to the cores such that the dynamic energy consumption is reduced; (ii) the second phase refines the allocation performed in the first phase in order to achieve better sleep states by trading off the dynamic energy consumption with the reduction in leakage energy consumption. This hybrid approach considers core frequency set-points, tasks energy consumption and sleep states of the cores to reduce the energy consumption of the system. Major value has been placed on a realistic power model which increases the practical relevance of the proposed approach. Finally, extensive simulations have been carried out to demonstrate the effectiveness of the proposed algorithm. In the best-case, savings up to 18% of energy are reached over the first fit algorithm, which has shown, in previous works, to perform better than other bin-packing heuristics for the target heterogeneous multicore platform.

A framework for memory contention analysis in multi-core platforms

The last decade has witnessed a major shift towards the deployment of embedded applications on multi-core platforms. However, real-time applications have not been able to fully benefit from this transition, as the computational gains offered by multi-cores are often offset by performance degradation due to shared resources, such as main memory. To efficiently use multi-core platforms for real-time systems, it is hence essential to tightly bound the interference when accessing shared resources. Although there has been much recent work in this area, a remaining key problem is to address the diversity of memory arbiters in the analysis to make it applicable to a wide range of systems. This work handles diverse arbiters by proposing a general framework to compute the maximum interference caused by the shared memory bus and its impact on the execution time of the tasks running on the cores, considering different bus arbiters. Our novel approach clearly demarcates the arbiter-dependent and independent stages in the analysis of these upper bounds. The arbiter-dependent phase takes the arbiter and the task memory-traffic pattern as inputs and produces a model of the availability of the bus to a given task. Then, based on the availability of the bus, the arbiter-independent phase determines the worst-case request-release scenario that maximizes the interference experienced by the tasks due to the contention for the bus. We show that the framework addresses the diversity problem by applying it to a memory bus shared by a fixed-priority arbiter, a time-division multiplexing (TDM) arbiter, and an unspecified work-conserving arbiter using applications from the MediaBench test suite. We also experimentally evaluate the quality of the analysis by comparison with a state-of-the-art TDM analysis approach and consistently showing a considerable reduction in maximum interference.

Towards Certifiable Multicore-based Platforms for Avionics

Work in Progress Session, 21st IEEE Real-Time and Embedded Techonology and Applications Symposium (RTAS 2015). 13 to 16, Apr, 2015, pp 27-28. Seattle, U.S.A..

Towards the Certification of Multicore Platforms in the Avionics Domain

Poster presented in Work in Progress Session, The 28th GI/ITG International Conference on Architecture of Computing Systems (ARCS 2015). 24 to 27, Mar, 2015. Porto, Portugal.

Towards the Certification of Multicore Platforms in the Avionics Domain

Presented at Work in Progress Session, The 28th GI/ITG International Conference on Architecture of Computing Systems (ARCS 2015). 24 to 27, Mar, 2015. Porto, Portugal.

Ontologies for the interoperability of multiagent electricity markets simulation platforms

Electricity markets worldwide are complex and dynamic environments with very particular characteristics. These are the result of electricity markets’ restructuring and evolution into regional and continental scales, along with the constant changes brought by the increasing necessity for an adequate integration of renewable energy sources. The rising complexity and unpredictability in electricity markets has increased the need for the intervenient entities in foreseeing market behaviour. Market players and regulators are very interested in predicting the market’s behaviour. Market players need to understand the market behaviour and operation in order to maximize their profits, while market regulators need to test new rules and detect market inefficiencies before they are implemented. The growth of usage of simulation tools was driven by the need for understanding those mechanisms and how the involved players' interactions affect the markets' outcomes. Multi-agent based software is particularly well fitted to analyse dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. Several modelling tools directed to the study of restructured wholesale electricity markets have emerged. Still, they have a common limitation: the lack of interoperability between the various systems to allow the exchange of information and knowledge, to test different market models and to allow market players from different systems to interact in common market environments. This dissertation proposes the development and implementation of ontologies for semantic interoperability between multi-agent simulation platforms in the scope of electricity markets. The added value provided to these platforms is given by enabling them sharing their knowledge and market models with other agent societies, which provides the means for an actual improvement in current electricity markets studies and development. The proposed ontologies are implemented in MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) and tested through the interaction between MASCEM agents and agents from other multi-agent based simulators. The implementation of the proposed ontologies has also required a complete restructuring of MASCEM’s architecture and multi-agent model, which is also presented in this dissertation. The results achieved in the case studies allow identifying the advantages of the novel architecture of MASCEM, and most importantly, the added value of using the proposed ontologies. They facilitate the integration of independent multi-agent simulators, by providing a way for communications to be understood by heterogeneous agents from the various systems.