Synthesis and computer-assisted design of mitochondrial electron transport-chain inhibitors as antimalarial agents

Tese de doutoramento, Farmácia (Química Farmacêutica e Terapêutica), Universidade de Lisboa, Faculdade de Farmácia, 2014

Partial volume correction using bimodal contrast agents in PET-MRI

Tese de mestrado integrado em Engenharia Biomédica e Biofísica, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2014

Identification of bacteria associated with Dinoflagellates (Dinophyceae) Alexandrium spp. using tyramide signal amplification fluorescent in situ hybridization and confocal microscopy

In the marine environment, phytoplankton and bacterioplankton can be physically associated. Such association has recently been hypothesized to be involved in the toxicity of the dinoflagellate genus Alexandrium. However, the methods, which have been used so far to identify, localize, and quantify bacteria associated with phytoplankton, are either destructive, time consuming, or lack precision. In the present study we combined tyramide signal amplification–fluorescent in situ hybridization (TSA-FISH) with confocal microscopy to determine the physical association of dinoflagellate cells with bacteria. Dinoflagellate attached microflora was successfully identified with TSA-FISH, whereas FISH using monolabeled probes failed to detect bacteria, because of the dinoflagellate autofluorescence. Bacteria attached to entire dinoflagellates were further localized and distinguished from those attached to empty theca, by using calcofluor and DAPI, two fluorochromes that stain dinoflagellate theca and DNA, respectively. The contribution of specific bacterial taxa of attached microflora was assessed by double hybridization. Endocytoplasmic and endonuclear bacteria were successfully identified in the nonthecate dinoflagellate Gyrodinium instriatum. In contrast, intracellular bacteria were not observed in either toxic or nontoxic strains of Alexandrium spp. Finally, the method was successfully tested on natural phytoplankton assemblages, suggesting that this combination of techniques could prove a useful tool for the simultaneous identification, localization, and quantification of bacteria physically associated with dinoflagellates and more generally with phytoplankton.

Essential oils as anti-nematode agents and their influence on in vitro nematode

Tese de doutoramento, Biologia (Biotecnologia), Universidade de Lisboa, Faculdade de Ciências, 2015

Avaliação do potencial clínico de novos ligandos para o receptor estrogénico em diagnóstico e terapia de tumores da mama

Tese de doutoramento, Química (Química Inorgânica), Universidade de Lisboa, Faculdade de Ciências, 2015

'It's Almost Like Talking to a Person': Student Discolsure to Pedagogical Agents in Sensitive Setting

Online chatbots (also known as pedagogical agents or virtual assistants) are becoming embedded into the fabric of technology, both in educational and commercial settings. Yet understanding of these technologies is inchoate and often untheorised, influenced by individuals’ willingness to trust technologies, aesthetic appearance of the chatbot and technical literacy, among other factors. This paper draws upon data from two research studies that evaluated students’ experiences of using pedagogical agents in education using responsive evaluation. The findings suggest that emotional connections with pedagogical agents were intrinsic to the user’s sense of trust and therefore likely to affect levels of truthfulness and engagement. They also indicate that the topic of the pedagogical agent-student interaction is key to the student’s experience. The implications of these studies are that truthfulness, personalisation and emotional engagement are all vital components in using pedagogical agents to enhance online learning.

Detection of Incipient Thermal Damage Of Carbon Fiber/Epoxy Composites Using Fluorescent Thermal Damage Probes

Thesis (Ph.D.)--University of Washington, 2013

Beyond Robotic Wastelands of Time: Abandoned Pedagogical Agents and New Pedalled Pedagogies

Chatbots, known as pedagogical agents in educational settings, have a long history of use, beginning with Alan Turing’s work. Since then online chatbots have become embedded into the fabric of technology. Yet understandings of these technologies are inchoate and often untheorised. Integration of chatbots into educational settings over the past five years suggests an increase in interest in the ways in which chatbots might be adopted and adapted for teaching and learning. This article draws on historical literature and theories that to date have largely been ignored in order to (re)contextualise two studies that used responsive evaluation to examine the use of pedagogical agents in education. Findings suggest that emotional interactions with pedagogical agents are intrinsic to a user’s sense of trust, and that truthfulness, personalisation and emotional engagement are vital when using pedagogical agents to enhance online learning. Such findings need to be considered in the light of ways in which notions of learning are being redefined in the academy and the extent to which new literacies and new technologies are being pedalled as pedagogies in ways that undermine what higher education is, is for, and what learning means.

Molecularly imprinted polymer based on MWCNTs-QDs as fluorescent biomimetic sensor for specific recognition of target protein

A novel molecularly imprinted optosensing material based on multi-walled carbon nanotube-quantum dots (MWCNT-QDs) has been designed and synthesized for its high selectivity, sensitivity and specificity in the recognition of a target protein bovine serum albumin (BSA). Molecularly imprinted polymer coated MWCNT-QDs using BSA as the template (BMIP-coated MWCNT-QDs) exhibits a fast mass-transfer speed with a response time of 25 min. It is found that the BSA as a target protein can significantly quench the luminescence of BMIP-coated MWCNT-QDs in a concentration-dependent manner that is best described by a Stem-Volmer equation. The K-SV for BSA is much higher than bovine hemoglobin and lysozyme, implying a highly selective recognition of the BMIP-coated MWCNT-QDs to BSA. Under optimal conditions, the relative fluorescence intensity of BMIP-coated MWCNT-QDs decreases linearly with the increasing target protein BSA in the concentration range of 5.0 x 10(-7)-35.0 x 10(-7) M with a detection limit of 80 nM.

Understanding citizen media as practice: agents, processes, publics

Much recent commentary on citizen media has focused on online platforms as means through which citizens may disseminate self-produced media content that challenges dominant discourses or makes visible hidden realities. This chapter goes beyond a concern with media content to explore the much broader range of socially situated practices that develop around citizen media. Drawing on Couldry’s proposal for a practice paradigm in media research, it suggests shifting the focus from ‘citizen media’ to ‘citizen media practices’ and demonstrates, through a case study of communication activism in the World Social Forum, how this framework can bring into view a broad range of citizen media practices (beyond those directly concerned with the production and circulation of media content), the different forms of agency that such practices make possible, and the social fabric they can help generate. I conclude by arguing that a practice framework necessitates a rethink of the way that the concept of (counter-) publics is used in the context of citizen media. Citizen media practices of the kind described here can be understood not only as practices of ‘making public’ previously unreported issues and perspectives, but as practices of public¬-making: practices that support the formation of publics.

MASCEM: electricity markets simulation with strategic agents

Electricity markets are complex environments, involving numerous entities trying to obtain the best advantages and profits while limited by power-network characteristics and constraints.1 The restructuring and consequent deregulation of electricity markets introduced a new economic dimension to the power industry. Some observers have criticized the restructuring process, however, because it has failed to improve market efficiency and has complicated the assurance of reliability and fairness of operations. To study and understand this type of market, we developed the Multiagent Simulator of Competitive Electricity Markets (MASCEM) platform based on multiagent simulation. The MASCEM multiagent model includes players with strategies for bid definition, acting in forward, day-ahead, and balancing markets and considering both simple and complex bids. Our goal with MASCEM was to simulate as many market models and player types as possible. This approach makes MASCEM both a short- and mediumterm simulation as well as a tool to support long-term decisions, such as those taken by regulators. This article proposes a new methodology integrated in MASCEM for bid definition in electricity markets. This methodology uses reinforcement learning algorithms to let players perceive changes in the environment, thus helping them react to the dynamic environment and adapt their bids accordingly.

Seller, buyer and VPP agents behavior on a simulated electricity market

Competitive electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is an electricity market simulator able to model market players and simulate their operation in the market. As market players are complex entities, having their characteristics and objectives, making their decisions and interacting with other players, a multi-agent architecture is used and proved to be adequate. MASCEM players have learning capabilities and different risk preferences. They are able to refine their strategies according to their past experience (both real and simulated) and considering other agents’ behavior. Agents’ behavior is also subject to its risk preferences.

MV producers and consumers agents characterization with DSM techniques

This paper consist in the establishment of a Virtual Producer/Consumer Agent (VPCA) in order to optimize the integrated management of distributed energy resources and to improve and control Demand Side Management DSM) and its aggregated loads. The paper presents the VPCA architecture and the proposed function-based organization to be used in order to coordinate the several generation technologies, the different load types and storage systems. This VPCA organization uses a frame work based on data mining techniques to characterize the costumers. The paper includes results of several experimental tests cases, using real data and taking into account electricity generation resources as well as consumption data.