Agent-based parking occupancy simulation

The existing parking simulations, as most simulations, are intended to gain insights of a system or to make predictions. The knowledge they have provided has built up over the years, and several research works have devised detailed parking system models. This thesis work describes the use of an agent-based parking simulation in the context of a bigger parking system development. It focuses more on flexibility than on fidelity, showing the case where it is relevant for a parking simulation to consume dynamically changing GIS data from external, online sources and how to address this case. The simulation generates the parking occupancy information that sensing technologies should eventually produce and supplies it to the bigger parking system. It is built as a Java application based on the MASON toolkit and consumes GIS data from an ArcGis Server. The application context of the implemented parking simulation is a university campus with free, on-street parking places.

An agent-based simulator to estimate domestic energy use

Throughout recent years, there has been an increase in the population size, as well as a fast economic growth, which has led to an increase of the energy demand that comes mainly from fossil fuels. In order to reduce the ecological footprint, governments have implemented sustainable measures and it is expected that by 2035 the energy produced from renewable energy sources, such as wind and solar would be responsible for one-third of the energy produced globally. However, since the energy produced from renewable sources is governed by the availability of the respective primary energy source there is often a mismatch between production and demand, which could be solved by adding flexibility on the demand side through demand response (DR). DR programs influence the end-user electricity usage by changing its cost along the time. Under this scenario the user needs to estimate the energy demand and on-site production in advance to plan its energy demand according to the energy price. This work focuses on the development of an agent-based electrical simulator, capable of: (a) estimating the energy demand and on-site generation with a 1-min time resolution for a 24-h period, (b) calculating the energy price for a given scenario, (c) making suggestions on how to maximize the usage of renewable energy produced on-site and to lower the electricity costs by rescheduling the use of certain appliances. The results show that this simulator allows reducing the energy bill by 11% and almost doubling the use of renewable energy produced on-site.

Relating the spatial component and users interests to improve applications based on questions, petitions and participatory processes

Nowadays, participatory processes attending the need for real democracy and transparency in governments and collectives are more needed than ever. Immediate participation through channels like social networks enable people to give their opinion and become pro-active citizens, seeking applications to interact with each other. The application described in this dissertation is a hybrid channel of communication of questions, petitions and participatory processes based on Public Participation Geographic Information System (PPGIS), Participation Geographic Information System (PGIS) and ‘soft’ (subjective data) Geographic Information System (SoftGIS) methodologies. To achieve a new approach to an application, its entire design is focused on the spatial component related with user interests. The spatial component is treated as main feature of the system to develop all others depending on it, enabling new features never seen before in social actions (questions, petitions and participatory processes). Results prove that it is possible to develop a working application mainly using open source software, with the possibility of spatial and subject filtering, visualizing and free download of actions within application. The resulting application empowers society by releasing soft data and defines a new breaking approach, unseen so far.

Engineered MRI nanoprobes based on superparamagnetic iron oxide nanoparticles

This project aimed to engineer new T2 MRI contrast agents for cell labeling based on formulations containing monodisperse iron oxide magnetic nanoparticles (MNP) coated with natural and synthetic polymers. Monodisperse MNP capped with hydrophobic ligands were synthesized by a thermal decomposition method, and further stabilized in aqueous media with citric acid or meso-2,3-dimercaptosuccinic acid (DMSA) through a ligand exchange reaction. Hydrophilic MNP-DMSA, with optimal hydrodynamic size distribution, colloidal stability and magnetic properties, were used for further functionalization with different coating materials. A covalent coupling strategy was devised to bind the biopolymer gum Arabic (GA) onto MNPDMSA and produce an efficient contrast agent, which enhanced cellular uptake in human colorectal carcinoma cells (HCT116 cell line) compared to uncoated MNP-DMSA. A similar protocol was employed to coat MNP-DMSA with a novel biopolymer produced by a biotechnological process, the exopolysaccharide (EPS) Fucopol. Similar to MNP-DMSA-GA, MNP-DMSA-EPS improved cellular uptake in HCT116 cells compared to MNP-DMSA. However, MNP-DMSA-EPS were particularly efficient towards the neural stem/progenitor cell line ReNcell VM, for which a better iron dose-dependent MRI contrast enhancement was obtained at low iron concentrations and short incubation times. A combination of synthetic and biological coating materials was also explored in this project, to design a dynamic tumortargeting nanoprobe activated by the acidic pH of tumors. The pH-dependent affinity pair neutravidin/iminobiotin, was combined in a multilayer architecture with the synthetic polymers poy-L-lysine and poly(ethylene glycol) and yielded an efficient MRI nanoprobe with ability to distinguish cells cultured in acidic pH conditions form cells cultured in physiological pH conditions.

Engineering bio-based polymers using alternative solvents and processes

The work presented in this thesis explores novel routes for the processing of bio-based polymers, developing a sustainable approach based on the use of alternative solvents such as supercritical carbon dioxide (scCO2), ionic liquids (ILs) and deep eutectic solvents (DES). The feasibility to produce polymeric foams via supercritical fluid (SCF) foaming, combined with these solvents was assessed, in order to replace conventional foaming techniques that use toxic and harmful solvents. A polymer processing methodology is presented, based on SCF foaming and using scCO2 as a foaming agent. The SCF foaming of different starch based polymeric blends was performed, namely starch/poly(lactic acid) (SPLA) and starch/poly(ε-caprolactone) (SPCL). The foaming process is based on the fact that CO2 molecules can dissolve in the polymer, changing their mechanical properties and after suitable depressurization, are able to create a foamed (porous) material. In these polymer blends, CO2 presents limited solubility and in order to enhance the foaming effect, two different imidazolium based ILs (IBILs) were combined with this process, by doping the blends with IL. The use of ILs proved useful and improved the foaming effect in these starch-based polymer blends. Infrared spectroscopy (FTIR-ATR) proved the existence of interactions between the polymer blend SPLA and ILs, which in turn diminish the forces that hold the polymeric structure. This is directly related with the ability of ILs to dissolve more CO2. This is also clear from the sorption experiments results, where the obtained apparent sorption coefficients in presence of IL are higher compared to the ones of the blend SPLA without IL. The doping of SPCL with ILs was also performed. The foaming of the blend was achieved and resulted in porous materials with conductivity values close to the ones of pure ILs. This can open doors to applications as self-supported conductive materials. A different type of solvents were also used in the previously presented processing method. If different applications of the bio-based polymers are envisaged, replacing ILs must be considered, especially due to the poor sustainability of some ILs and the fact that there is not a well-established toxicity profile. In this work natural DES – NADES – were the solvents of choice. They present some advantages relatively to ILs since they are easy to produce, cheaper, biodegradable and often biocompatible, mainly due to the fact that they are composed of primary metabolites such as sugars, carboxylic acids and amino-acids. NADES were prepared and their physicochemical properties were assessed, namely the thermal behavior, conductivity, density, viscosity and polarity. With this study, it became clear that these properties can vary with the composition of NADES, as well as with their initial water content. The use of NADES in the SCF foaming of SPCL, acting as foaming agent, was also performed and proved successful. The SPCL structure obtained after SCF foaming presented enhanced characteristics (such as porosity) when compared with the ones obtained using ILs as foaming enhancers. DES constituted by therapeutic compounds (THEDES) were also prepared. The combination of choline chloride-mandelic acid, and menthol-ibuprofen, resulted in THEDES with thermal behavior very distinct from the one of their components. The foaming of SPCL with THEDES was successful, and the impregnation of THEDES in SPCL matrices via SCF foaming was successful, and a controlled release system was obtained in the case of menthol-ibuprofen THEDES.