Dynamical behaviour of multi-particle large-scale systems

Collective behaviours can be observed in both natural and man-made systems composed of a large number of elemental subsystems. Typically, each elemental subsystem has its own dynamics but, whenever interaction between individuals occurs, the individual behaviours tend to be relaxed, and collective behaviours emerge. In this paper, the collective behaviour of a large-scale system composed of several coupled elemental particles is analysed. The dynamics of the particles are governed by the same type of equations but having different parameter values and initial conditions. Coupling between particles is based on statistical feedback, which means that each particle is affected by the average behaviour of its neighbours. It is shown that the global system may unveil several types of collective behaviours, corresponding to partial synchronisation, characterised by the existence of several clusters of synchronised subsystems, and global synchronisation between particles, where all the elemental particles synchronise completely.

Efficient aggregate computations in large-scale dense WSN

We focus on large-scale and dense deeply embedded systems where, due to the large amount of information generated by all nodes, even simple aggregate computations such as the minimum value (MIN) of the sensor readings become notoriously expensive to obtain. Recent research has exploited a dominance-based medium access control(MAC) protocol, the CAN bus, for computing aggregated quantities in wired systems. For example, MIN can be computed efficiently and an interpolation function which approximates sensor data in an area can be obtained efficiently as well. Dominance-based MAC protocols have recently been proposed for wireless channels and these protocols can be expected to be used for achieving highly scalable aggregate computations in wireless systems. But no experimental demonstration is currently available in the research literature. In this paper, we demonstrate that highly scalable aggregate computations in wireless networks are possible. We do so by (i) building a new wireless hardware platform with appropriate characteristics for making dominance-based MAC protocols efficient, (ii) implementing dominance-based MAC protocols on this platform, (iii) implementing distributed algorithms for aggregate computations (MIN, MAX, Interpolation) using the new implementation of the dominance-based MAC protocol and (iv) performing experiments to prove that such highly scalable aggregate computations in wireless networks are possible.

Localizing objects in large-scale cyber- physical systems

We use the term Cyber-Physical Systems to refer to large-scale distributed sensor systems. Locating the geographic coordinates of objects of interest is an important problemin such systems. We present a new distributed approach to localize objects and events of interest in time complexity independent of number of nodes.

Design and implementation of a behaviorally typed programming system for web services

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática.

Assessment of climate change statistical downscaling methods: Application and comparison of two statistical methods to a single site in Lisbon

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente

Optimizing the renewable generation mix in the portuguese power system based on temporal and spatial diversity

Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.

Design and implementation of an autonomous, proactive, and reactive software infrastructure to help improving the management level of projects

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

Decision Support Concerning Demand Response Programs Design and Use – A Conceptual Framework and Simulation Tool

Demand response can play a very relevant role in the context of power systems with an intensive use of distributed energy resources, from which renewable intermittent sources are a significant part. More active consumers participation can help improving the system reliability and decrease or defer the required investments. Demand response adequate use and management is even more important in competitive electricity markets. However, experience shows difficulties to make demand response be adequately used in this context, showing the need of research work in this area. The most important difficulties seem to be caused by inadequate business models and by inadequate demand response programs management. This paper contributes to developing methodologies and a computational infrastructure able to provide the involved players with adequate decision support on demand response programs and contracts design and use. The presented work uses DemSi, a demand response simulator that has been developed by the authors to simulate demand response actions and programs, which includes realistic power system simulation. It includes an optimization module for the application of demand response programs and contracts using deterministic and metaheuristic approaches. The proposed methodology is an important improvement in the simulator while providing adequate tools for demand response programs adoption by the involved players. A machine learning method based on clustering and classification techniques, resulting in a rule base concerning DR programs and contracts use, is also used. A case study concerning the use of demand response in an incident situation is presented.

Optimizing memory transactions for large-scale programs

Even though Software Transactional Memory (STM) is one of the most promising approaches to simplify concurrent programming, current STM implementations incur significant overheads that render them impractical for many real-sized programs. The key insight of this work is that we do not need to use the same costly barriers for all the memory managed by a real-sized application, if only a small fraction of the memory is under contention lightweight barriers may be used in this case. In this work, we propose a new solution based on an approach of adaptive object metadata (AOM) to promote the use of a fast path to access objects that are not under contention. We show that this approach is able to make the performance of an STM competitive with the best fine-grained lock-based approaches in some of the more challenging benchmarks. (C) 2015 Elsevier Inc. All rights reserved.

Implementation of an IoT-based Sensor Network Integrating IoT-based Sensor Networks with Large-Scale Message Distribution

As technology advances not only do new standards and programming styles appear but also some of the previously established ones gain relevance. In a new Internet paradigm where interconnection between small devices is key to the development of new businesses and scientific advancement there is the need to find simple solutions that anyone can implement in order to allow ideas to become more than that, ideas. Open-source software is still alive and well, especially in the area of the Internet of Things. This opens windows for many low capital entrepreneurs to experiment with their ideas and actually develop prototypes, which can help identify problems with a project or shine light on possible new features and interactions. As programming becomes more and more popular between people of fields not related to software there is the need for guidance in developing something other than basic algorithms, which is where this thesis comes in: A comprehensive document explaining the challenges and available choices of developing a sensor data and message delivery system, which scales well and implements the delivery of critical messages. Modularity and extensibility were also given much importance, making this an affordable tool for anyone that wants to build a sensor network of the kind.

The impact of large-scale mortgage backed security purchases

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Design and characterization of Chitin- Glucan polymeric structures for wound dressing materials

The main objective of this work was the development of polymeric structures, gel and films, generated from the dissolution of the Chitin-Glucan Complex (CGC) in biocompatible ionic liquids for biomedical applications. Similar as chitin, CGC is only soluble in some special solvents which are toxic and corrosive. Due to this fact and the urgent development of biomedical applications, the need to use biocompatible ionic liquids to dissolve the CGC is indispensable. For the dissolution of CGC, the biocompatible ionic liquid used was Choline acetate. Two different CGC’s, KiOnutrime from KitoZyme and biologically produced CGC from Faculdade de Ciencias e Tecnologia (FCT) - Universidade Nova de Lisboa, were characterized in order to develop biocompatible wound dressing materials. The similar result is shown in term of the ratio of chitin:glucan, which is 1:1.72 for CGC-FCT and 1:1.69 for CGC-Commercial. For the analysis of metal element content, water and inorganic salts content and protein content, both polymers showed some discrepancies, where the content in CGC-FCT is always higher compared to the commercial one. The different characterization results between CGC-FCT and CGC-Commercial could be addressed to differences in the purification method, and the difference of its original strain yeast, whereas CGC-FCT is derived from P.pastoris and the commercial CGC is from A.niger. This work also investigated the effect of biopolymers, temperature dissolution, non-solvent composition on the characteristics of generated polymeric structure with biocompatible ionic liquid. The films were prepared by casting a polymer mixture, immersion in a non-solvent, followed by drying at ambient temperature. Three different non-solvents were tested in phase inversion method, i.e. water, methanol, and glycerol. The results indicate that the composition of non-solvent in the coagulation bath has great influence in generated polymeric structure. Water was found to be the best coagulant for producing a CGC polymeric film structure. The characterizations that have been done include the analysis of viscosity and viscoelasticity measurement, as well as sugar composition in the membrane and total sugar that was released during the phase inversion method. The rheology test showed that both polymer mixtures exhibit a non- Newtonian shear thinning behaviour. Where the viscosity and viscoelasticity test reveal that CGCFCT mixture has a typical behaviour of a viscous solution with entangled polymer chains and CGCCommercial mixture has true gel behaviour. The experimental results show us that the generated CGC solution from choline acetate could be used to develop both polymeric film structure and gel. The generated structures are thermally stable at 100° C, and are hydrophilic. The produced films have dense structure and mechanical stabilities against puncture up to 60 kPa.

Design and development of a microfluidic platform for use with colorimetric gold nanoprobe assays

Due to the importance and wide applications of the DNA analysis, there is a need to make genetic analysis more available and more affordable. As such, the aim of this PhD thesis is to optimize a colorimetric DNA biosensor based on gold nanoprobes developed in CEMOP by reducing its price and the needed volume of solution without compromising the device sensitivity and reliability, towards the point of care use. Firstly, the price of the biosensor was decreased by replacing the silicon photodetector by a low cost, solution processed TiO2 photodetector. To further reduce the photodetector price, a novel fabrication method was developed: a cost-effective inkjet printing technology that enabled to increase TiO2 surface area. Secondly, the DNA biosensor was optimized by means of microfluidics that offer advantages of miniaturization, much lower sample/reagents consumption, enhanced system performance and functionality by integrating different components. In the developed microfluidic platform, the optical path length was extended by detecting along the channel and the light was transmitted by optical fibres enabling to guide the light very close to the analysed solution. Microfluidic chip of high aspect ratio (~13), smooth and nearly vertical sidewalls was fabricated in PDMS using a SU-8 mould for patterning. The platform coupled to the gold nanoprobe assay enabled detection of Mycobacterium tuberculosis using 3 8l on DNA solution, i.e. 20 times less than in the previous state-of-the-art. Subsequently, the bio-microfluidic platform was optimized in terms of cost, electrical signal processing and sensitivity to colour variation, yielding 160% improvement of colorimetric AuNPs analysis. Planar microlenses were incorporated to converge light into the sample and then to the output fibre core increasing 6 times the signal-to-losses ratio. The optimized platform enabled detection of single nucleotide polymorphism related with obesity risk (FTO) using target DNA concentration below the limit of detection of the conventionally used microplate reader (i.e. 15 ng/μl) with 10 times lower solution volume (3 μl). The combination of the unique optical properties of gold nanoprobes with microfluidic platform resulted in sensitive and accurate sensor for single nucleotide polymorphism detection operating using small volumes of solutions and without the need for substrate functionalization or sophisticated instrumentation. Simultaneously, to enable on chip reagents mixing, a PDMS micromixer was developed and optimized for the highest efficiency, low pressure drop and short mixing length. The optimized device shows 80% of mixing efficiency at Re = 0.1 in 2.5 mm long mixer with the pressure drop of 6 Pa, satisfying requirements for the application in the microfluidic platform for DNA analysis.

The design and development of heat extraction technologies for the utilisation of compost thermal energy

A composting Heat Extraction Unit (HEU) was designed to utilise waste heat from decaying organic matter for a variety of heating application The aim was to construct an insulated small scale, sealed, organic matter filled container. In this vessel a process fluid within embedded pipes would absorb thermal energy from the hot compost and transport it to an external heat exchanger. Experiments were conducted on the constituent parts and the final design comprised of a 2046 litre container insulated with polyurethane foam and kingspan with two arrays of qualpex piping embedded in the compost to extract heat. The thermal energy was used in horticultural trials by heating polytunnels using a radiator system during a winter/spring period. The compost derived energy was compared with conventional and renewable energy in the form of an electric fan heater and solar panel. The compost derived energy was able to raise polytunnel temperatures to 2-3°C above the control, with the solar panel contributing no thermal energy during the winter trial and the electric heater the most efficient maintaining temperature at its preset temperature of 10°C. Plants that were cultivated as performance indicators showed no significant difference in growth rates between the heat sources. A follow on experiment conducted using special growing mats for distributing compost thermal energy directly under the plants (Radish, Cabbage, Spinach and Lettuce) displayed more successful growth patterns than those in the control. The compost HEU was also used for more traditional space heating and hot water heating applications. A test space was successfully heated over two trials with varying insulation levels. Maximum internal temperature increases of 7°C and 13°C were recorded for building U-values of 1.6 and 0.53 W/m2K respectively using the HEU. The HEU successfully heated a 60 litre hot water cylinder for 32 days with maximum water temperature increases of 36.5°C recorded. Total energy recovered from the 435 Kg of compost within the HEU during the polytunnel growth trial was 76 kWh which is 3 kWh/day for the 25 days when the HEU was activated. With a mean coefficient of performance level of 6.8 calculated for the HEU the technology is energy efficient. Therefore the compost HEU developed here could be a useful renewable energy technology particularly for small scale rural dwellers and growers with access to significant quantities of organic matter

Large-scale imatinib dose-concentration-effect study in CML patients under routine care conditions.

This observational study analyzed imatinib pharmacokinetics and response in 2478 chronic myeloid leukemia (CML) patients. Data were obtained through centralized therapeutic drug monitoring (TDM) at median treatment duration of ≥2 years. First, individual initial trough concentrations under 400mg/day imatinib starting dose were estimated. Second, their correlation (C^min(400mg)) with reported treatment response was verified. Low imatinib levels were predicted in young male patients and those receiving P-gp/CYP3A4 inducers. These patients had also lower response rates (7% lower 18-months MMR in male, 17% lower 1-year CCyR in young patients, Kaplan-Meier estimates). Time-point independent multivariate regression confirmed a correlation of individual C^min(400mg) with response and adverse events. Possibly due to confounding factors (e.g. dose modifications, patient selection bias), the relationship seemed however flatter than previously reported from prospective controlled studies. Nonetheless, these observational results strongly suggest that a subgroup of patients could benefit from early dosage optimization assisted by TDM, because of lower imatinib concentrations and lower response rates.