FCT1-Teses
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Percorrer FCT1-Teses por Objetivos de Desenvolvimento Sustentável (ODS) "07:Energias Renováveis e Acessíveis"
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- Mobility planning in edge assisted low power wide area networksPublication . Carvalho, Rodrigo Zuolo; Correia, Noélia Susana Costa; Al-Tam, FaroqEdge computing infrastructures are being integrated with Internet of Things (IoT) systems to facilitate time-critical applications. These systems often require data to be processed within a specific time window, so the edge becomes vital in developing reactive IoT applications with time restriction requirements. Although different architectural designs will always have advantages and disadvantages, mobile gateways are particularly relevant in enabling this integration with the edge, particularly in the context of wide-area networks with occasional data generation. In these scenarios, mobility planning is necessary, as aspects of the technology need to be aligned with the temporal needs of an application. This dissertation intersects machine learning techniques and mathematical models to establish a framework that solves the problem of mobility planning for LoRaWAN gateways when cooperating with edge system architectures. Throughout the pipeline for attaining this objective, some sideline contributions are yielded, such as machine learning agents to improve the Adaptive Data Rate (ADR) mechanism, mathematical models to estimate the gateways’ journey time, and machine learning agents that meet the constraints on valid data collection and delivery to edge systems. The nature of the problem at hand makes cutting-edge Deep Reinforcement Learning (DRL) techniques helpful in solving inherited issues, such as dealing with multiple dimensions in the action space while aiming for optimum system performance. This dissertation culminates in a novel scalable DRL model incorporating a pointer network (Ptr-Net) and an Actor-Critic (AC) algorithm to handle complex action spaces. The model synchronously determines the gateway location and visit time. Ultimately, the gateways can achieve a trajectory planning fulfilling all requirements while reducing latency and energy waste.
- Optimal light wavelength and intensity for algae cultivation in photobioreactorsPublication . Nogueira, Gustavo Filipe Magalhães; Schulze, Peter Simon Claus; Varela, João Carlos SerafimIn the present study, the growth response of Phaeodactylum tricornutum, Nannochloropsis oceanica, and Porphyra dioica cultures with different biomass concentrations to 22 combinations of red (620 nm), green (530 nm), and blue (450 nm) light at 3 different light intensities (200, 500, and 1000 μmol m-2 s-1) was investigated. Photosynthetic oxygen evolution rates as response variable were used to create predictive models with the optimal light conditions to improve growth at different algal growth stages. While P. dioica did not result in positive oxygen evolution rates and thus no model could be established, for P. tricornutum and N. oceanica, predictive models showed statistical significance and were used to develop light regimes, matching the needs of algae cultures at different growth stages (lag, exponential, and late exponential phase). The generated models predicted the least absorbed wavelength (620 nm) as optimal for both algae, suggesting that it penetrated the algal culture deeper and stimulated photosynthesis of more cells than more absorbed wavelengths (e.g., 450 nm) that do not penetrate deeper into the culture. An additional experiment was conducted to validate the obtained light regimes. For this purpose, a novel light system (AlgaeLum) was developed, 3D printed and assembled for testing different light quantities and qualities. Experiments showed no significant differences in growth rate and maximum biomass concentrations compared to the control warm white light for both algae. Less absorbed wavelengths showed to improve photosynthetic efficiency in both microalgal species, especially in highly dense cultures and low light paths, over highly absorbed wavelengths (450 nm). Based on this result, the use of red light (620 nm) LEDs is recommended for N. oceanica and P. tricornutum as it offers an optimal balance between cost-effectiveness in terms of both CAPEX and OPEX) and photosynthetic efficiency. The developed AlgaeLum system can be used in the future to conduct other trials (e.g., continuous cultivation systems), which was not tested in the present study to validate the present results.
- Unlocking cyanobacterial metabolic potential: ß-oxidation pathwayPublication . Gonçalves, Inês Oliveira; Figueiredo, Sandra; Varela, JoãoCyanobacteria are a very diverse phylum of photosynthetic prokaryotes. As the first known organisms to produce oxygen on Earth, these microorganisms were crucial to the development of the biosphere and early Earth life forms. Cyanobacteria still presents several undefined genomic and metabolic pathways, despite their relevance, namely as a promising biological alternative to overcome the increasing demand for sustainable fuels and plastics. One of the still unclear pathways in cyanobacteria is b-oxidation, the catabolic process of fatty acid (FA) degradation. This mechanism had been thought to be universal for all organisms; however, some studies have suggested that b-oxidation might be lacking in cyanobacteria, despite the scattered evidence to support this hypothesis. We have revealed unprecedented results that may help finally understand this fundamental metabolic pathway in cyanobacteria. Through the bioinformatic analysis performed, some cyanobacteria strains were shown to encode putative fatty acid degradation (fad) machinery. Genomic context analysis led to the identification of a previously uncharacterized gene, here called AMP-L, that completes the full set of fad genes required for fatty acid activation and subsequent entry into the b-oxidation pathway. With the protocol optimized in this work, cyanobacterial fatty acyl-CoA intermediates with different length chains were detected for the first time. Different in vivo FA supplementation assays support these findings, showing for the firsttime cyanobacteria strains that might be able to degrade FA. These results address several fundamental questions related to cyanobacteria evolution and FA metabolism. Furthermore, this study brings knowledge that would, ultimately, lead to more efficient metabolism engineering applied to biotechnological purposes.