Dynamic combinatorial chemistry (DCC) is a powerful tool to identify new ligands for biological targets. In the technique, library synthesis and hit identification are neatly combined into a single step. A labile functionality between fragments allows the biological target to self-select binders from a dynamic combinatorial library (DCL) of interconverting building blocks. The scope of suitable reversible reactions that proceed under thermodynamic control in physiological conditions has been gradually expanded over the last decades, however DCC has thus far failed to gain traction as a technique appropriate for drug discovery in the pharmaceutical industry. The constraints placed on library size by validated analytical techniques, and the effort-intensive reality of this academically elegant concept have not allowed DCC to develop into a broad-platform technique to compete with the high-throughput screening campaigns favoured by medicinal chemists. This thesis seeks to develop DCL analysis techniques, in an effort to increase the library size and accelerate the analysis of DCC experiments. Using a 19F-labelled core scaffold, we constructed a DCL that could be monitored non-invasively by 19F NMR. Building on NMR techniques developed by fragment screening and non-biological DCC campaigns, the method was developed to circumvent the undesired equilibrium-perturbing side effects arising from sample-consuming analytical methods. The N-acylhydrazone (NAH) DCL equilibrated rapidly at pH 6.2 using 4-amino-L-phenylalanine (4-APA) as a novel, physiologically benign, nucleophilic catalyst. The DCL was designed to target b-ketoacyl-ACP synthase III (FabH), an essential bacterial enzyme and antibiotic target. From the 5-membered DCL, a single combination was identified as a privileged structure by our 19F NMR method. The result correlated well with an in vitro assay, validating 19F NMR as a tool for DCL screening. During the 19F NMR study we identified an established antimicrobial compound, 4,5- dichloro-1,2-dithiole-3-one (HR45), to have potential as a core scaffold from which to develop future DCLs targeting FabH. Despite the potentially tractable chemistry of HR45 for DCC, lack of knowledge around the inhibitory mechanism of the compound prevented us from proceeding. Thus, we used mass spectrometry, NMR and molecular modelling to show that HR45 acts by forming a covalent adduct with S. aureus FabH. The 5-chloro substituent directs attack from the nucleophilic thiol side chain of the essential active site cysteine-112 residue via a Michael-type addition elimination mechanism. Although interesting, this mechanism disfavoured the use of HR45 as a core scaffold for NAH exchange in a DCC campaign. Electrospray ionisation mass spectrometry (ESI-MS) is a powerful technique that allows for larger DCLs by eliminating the size-limitations imposed by the need for spectral or chromatographic resolution of DCL members. We developed a 4-APAcatalysed NAH library targeting the pyridoxal 5’-phosphate (PLP) dependent enzyme 7,8-diaminopelargonic acid synthase (BioA), an essential enzyme in the biotin biosynthesis pathway. We exploited the aldehyde moiety of PLP to form an NAH DCL with a panel of hydrazides, and used the BioA isozymes from M. tuberculosis (Mtb) and E. coli to template the library. A combination of buffer exchange and denaturing ESI-MS allowed us to conduct a DCC experiment with a 29-member DCL. Hits from the DCC experiment correlated well with differential scanning fluorimetry (DSF) results. Of these hits, 5 compounds were selected for further study. In vivo activity was displayed by 2 compounds against E. coli and the ESKAPE pathogen A. baumannii. The identification of compounds with antibacterial activity from a DCL further validates ESI-MS as a platform technology for drug discovery.

Cancer researchers and oncologists benefit greatly from text mining major knowledge sources in biomedicine such as PubMed. Fundamentally, text mining depends on accurate text classification. In conventional natural language processing (NLP), this requires experts to annotate scientific text, which is costly and time consuming, resulting in small labelled datasets. This leads to extensive feature engineering and handcrafting in order to fully utilise small labelled datasets, which is again time consuming, and not portable between tasks and domains. In this work, we explore emerging neural network methods to reduce the burden of feature engineering while outperforming the accuracy of conventional pipeline NLP techniques. We focus specifically on the cancer domain in terms of applications, where we introduce two NLP classification tasks and datasets: the first task is that of semantic text classification according to the Hallmarks of Cancer (HoC), which enables text mining of scientific literature assisted by a taxonomy that explains the processes by which cancer starts and spreads in the body. The second task is that of the exposure routes of chemicals into the body that may lead to exposure to carcinogens. We present several novel contributions. We introduce two new semantic classification tasks (the hallmarks, and exposure routes) at both sentence and document levels along with accompanying datasets, and implement and investigate a conventional pipeline NLP classification approach for both tasks, performing both intrinsic and extrinsic evaluation. We propose a new approach to classification using multilevel embeddings and apply this approach to several tasks; we subsequently apply deep learning methods to the task of hallmark classification and evaluate its outcome. Utilising our text classification methods, we develop and two novel text mining tools targeting real-world cancer researchers. The first tool is a cancer hallmark text mining tool that identifies association between a search query and cancer hallmarks; the second tool is a new literature-based discovery (LBD) system designed for the cancer domain. We evaluate both tools with end users (cancer researchers) and find they demonstrate good accuracy and promising potential for cancer research.

This diploma thesis briefly introduces the concept of inquiry based teaching mathematics. In inquiry based teaching, emphasis is placed primarily on the active activity of the pupil, the aim of which is to discover a certain reality. This activity mainly involves solving problems and finding the right paths to achieve the right goal. We can call this path to a goal as a research. The inquiry process involves observing, formulating questions, identifying information, designing possible processes, and verifying them. In this educational method, the role of the teacher is not to pass the facts to the pupils, but to target them and to supervise the correctness of their practices. We can understand the teacher here as a guide, adviser or assistant on the path to the goal (discovery). In the thesis a few examples of mathematics of elementary and secondary schools are given, in which the inquiry based approach is applied. Mathematics in the given examples is not complicated, emphasis is put on the practical use. In the examples interdisciplinary relationships are developed as well, which is an important part of the inquiry based teaching. In each example, additional questions are provided.

O crescimento do uso de sistemas de posicionamento global (GPS) e outros sistemas de localização espacial tornaram possível o rastreamento de objetos móveis, produzindo um grande volume de um novo tipo de dado, chamado trajetórias de objetos móveis. Existe, entretanto, uma forte lacuna entre a quantidade de dados extraídos destes dispositivos, dotados de sistemas GPS, e a descoberta de conhecimento que se pode inferir com estes dados. Um tipo de descoberta de conhecimento em dados de trajetórias de objetos móveis é a classificação. A classificação de trajetórias é um tema de pesquisa relativamente novo, e poucos métodos tem sido propostos até o presente momento. A maioria destes métodos foi desenvolvido para uma aplicação específica. Poucos propuseram um método mais geral, aplicável a vários domínios ou conjuntos de dados. Este trabalho apresenta um novo método de classificação que transforma as trajetórias em séries temporais, de forma a obter características mais discriminativas para a classificação. Experimentos com dados reais mostraram que o método proposto é melhor do que abordagens existentes. / The growing use of global positioning systems (GPS) and other location systems made the tracking of moving objects possible, producing a large volume of a new kind of data, called trajectories of moving objects. However, there is a large gap between the amount of data generated by these devices and the knowledge that can be inferred from these data. One type of knowledge discovery in trajectories of moving objects is classification. Trajectory classification is a relatively new research subject, and a few methods have been proposed so far. Most of these methods were developed for a specific application. Only a few have proposed a general method, applicable to multiple domains or datasets. This work presents a new classification method that transforms the trajectories into time series, in order to obtain more discriminative features for classification. Experiments with real trajectory data revealed that the proposed approach is more effective than existing approaches.

A presente tese analisa a maneira como a probabilidade influencia a formação da decisão sobre os fatos (contexto de descobrimento), bem como a motivação acerca dessas decisões (contexto justificativo). Mediante prévia análise da relevância da verdade no processo judicial, demonstra-se também que no terreno processual somente é possível falar em probabilidade, o que implica a ideia de um modelo probabilístico do juízo de fato, cujo núcleo é o módulo da escolha entre as alternativas possíveis. Portanto, são oferecidos critérios para a escolha das alternativas, os quais são denominados como diretrizes probatórias. De outro lado, a fim de que o convencimento do juiz a respeito dos fatos seja o mais racional possível, também é examinada a obrigatoriedade da motivação das decisões judiciais. Para tanto, é realizada abordagem à luz do Estado Constitucional e, ao final, demonstra-se que a probabilidade igualmente conforma o contexto justificativo, pois faz com que a motivação seja um discurso probatório racional. / This thesis examines how probability influences the fact-finding process (context of discovery) and the motivation about the trial of facts (context of justification). Considering the analysis of the relevance of truth in the judicial process, also in the procedural field only probability is taken into account, which implies the idea of a probabilistic model of factual judgment, whose core is the module of choice among the possible alternatives. Therefore, guidelines are offered for the choice of alternatives, which are called as evidentiary guidelines. On the other hand, in order to achieve the most rational conviction of the trier, mandatory legal motivation is also examined. The approach focuses on the Constitutional State and, in the end, is shown that the probability also conforms the context of justification, in order to make the legal motivation as a rational evidence speech.

This thesis consists of three essays examining the impact and consequences of the trading behaviour of a finely disaggregated category of investors in an electronic limit order book equity market, the Malta Stock Exchange (MSE). The three essays in market microstructure are closely related and examine how investor heterogeneity impacts the informational content of the limit order book, the informational content of individual trades, the price impact of investor trades, the aggressiveness of order submission strategies and the price discovery process within such a market. The first essay investigates the role of the financial intermediary in the price discovery process in a limit order market. We address this issue by analysing the trades of brokers within the Malta Stock Exchange by comparing the profitability of their individual trades and the impact of these trades on the price discovery process. The results of a Weighted Price Contribution methodology indicate that more active brokers that dominate the market in terms of volume and amount traded account for a significant portion of the price discovery process. We also find that the level of profitability of these brokers is directly proportional to the amount of volume traded and their relative share in the price discovery process. This appears to rule out the possibility of manipulative trades by these brokers in order to influence profitabilityThe second essay examines the price impact of the order flow emanating from finely disaggregated classes of investor with the aim of determining whether detectable differences exist in the extent to which orders emanating from particular groups of investors impact on the evolution of stock prices. On the aggregate stock level, results indicate price impact is inversely related to liquidity and as such the price impact of trades is of a higher magnitude and significance in stocks that are less liquid. Significantly, we find that stocks with higher liquidity and trading volume adjust quickly to price changes and the cumulative impact is realised earlier for these stocks. Similarly, for investor classes, our results show that the magnitude and significance of individual price impact increases as liquidity of the stocks declines, showing that as liquidity increases in the order book, the impact of information asymmetry begins to diminish. Institutional investors consistently have the highest significant impact on the evolution of prices across all the stocks. The final essay examines how investors structure their order submission choice in response to changes in the limit order book and market conditions (such as order depth, volatility, returns, and height of the limit order book). We identify 7 distinct investor classes who differ in their trading requirement and the information set available to them, and as such we expect that these investors will adopt different strategies to maximise their trades. The results show variability in the submission strategies adopted by investors as trade sides changes from buy to sell trades. It also indicate that investors have to balance between execution risk, the timely use of private information and the risk of being picked-off by other informed investors. In analysing the varied responses of these investors, we find that the order submission strategies adopted is most responsive to the risk of non-execution.

The Internet has evolved into a medium centered around content: people watch videos on YouTube, share their pictures via Flickr, and use Facebook to keep in touch with their friends. Yet, the only globally deployed service to discover content - i.e., Domain Name System (DNS) - does not discover content at all; it merely translates domain names into locations. The lack of persistent naming, in particular, makes content discovery, instead of domain discovery, challenging. Content Distribution Networks (CDNs), which augment DNSs with location-awareness, also suffer from the same problem of lack of persistent content names. Recently, several infrastructure- level solutions to this problem have emerged, but their fundamental limitation is that they fail to preserve the autonomy of network participants. Specifically, the storage requirements for resolution within each participant may not be proportional to their capacity. Furthermore, these solutions cannot be incrementally deployed. To the best of our knowledge, content discovery services based on peer-to-peer (P2P) networks are the only ones that support persistent content names. These services also come with the built-in advantage of scalability and deployability. However, P2P networks have been deployed in the real-world only recently, and their real-world characteristics are not well understood. It is important to understand these real-world characteristics in order to improve the performance and propose new designs by identifying the weaknesses of existing designs. In this dissertation, we first propose a novel, lightweight technique for capturing P2P traffic. Using our captured data, we characterize several aspects of P2P networks and draw conclusions about their weaknesses. Next, we create a botnet to demonstrate the lethality of the weaknesses of P2P networks. Finally, we address the weaknesses of P2P systems to design a P2P-based content discovery service, which resolves the drawbacks of existing content discovery systems and can operate at Internet-scale. This dissertation includes both previously published/unpublished and co-authored material.

As estrategias de passes têm sido sempre de interesse para a pesquisa de futebol. Desde os inícios do futebol, os técnicos tem usado olheiros, gravações de vídeo, exercícios de treinamento e feeds de dados para coletar informações sobre as táticas e desempenho dos jogadores. No entanto, a natureza dinâmica das estratégias de passes são bastante complexas para refletir o que está acontecendo dentro do campo e torna difícil o entendimento do jogo. Além disso, existe uma demanda crecente pela deteção de padrões e analise de estrategias de passes popularizado pelo tiki-taka utilizado pelo FC. Barcelona. Neste trabalho, propomos uma abordagem para abstrair as sequências de pases e agrupálas baseadas na geometria da trajetória da bola. Para analizar as estratégias de passes, apresentamos um esquema de visualização interátiva para explorar a frequência de uso, a localização espacial e ocorrência temporal das sequências. A visualização Frequency Stripes fornece uma visão geral da frequencia dos grupos achados em tres regiões do campo: defesa, meio e ataque. O heatmap de trajetórias coordenado com a timeline de passes permite a exploração das formas mais recorrentes no espaço e tempo. Os resultados demostram oito trajetórias comunes da bola para sequências de três pases as quais dependem da posição dos jogadores e os ângulos de passe. Demonstramos o potencial da nossa abordagem com utilizando dados de várias partidas do Campeonato Brasileiro sob diferentes casos de estudo, e reportamos os comentários de especialistas em futebol. / Passing strategies analysis has always been of interest for soccer research. Since the beginning of soccer, managers have used scouting, video footage, training drills and data feeds to collect information about tactics and player performance. However, the dynamic nature of passing strategies is complex enough to reflect what is happening in the game and makes it hard to understand its dynamics. Furthermore, there exists a growing demand for pattern detection and passing sequence analysis popularized by FC Barcelona’s tiki-taka. We propose an approach to abstract passing strategies and group them based on the geometry of the ball trajectory. To analyse passing sequences, we introduce a interactive visualization scheme to explore the frequency of usage, spatial location and time occurrence of the sequences. The frequency stripes visualization provide, an overview of passing groups frequency on three pitch regions: defense, middle, attack. A trajectory heatmap coordinated with a passing timeline allow, for the exploration of most recurrent passing shapes in temporal and spatial domains. Results show eight common ball trajectories for three-long passing sequences which depend on players positioning and on the angle of the pass. We demonstrate the potential of our approach with data from the Brazilian league under several case studies, and report feedback from a soccer expert.

Conselho Nacional de Desenvolvimento Científico e Tecnológico / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / A tese pretende estabelecer o que estaria o mais próximo possível de uma lógica da descoberta para as ciências sociais. A narrativa dessas disciplinas não seria neutra nem objetiva, mas procuraria produzir, retoricamente, os efeitos de neutralidade e objetividade, evitando a heroicização, a vilanização e a vitimização dos agentes. Isso decorreria da necessidade de o cientista social validar sua narrativa perante um auditório ideal ou potencialmente universal, abrigando, em princípio, todo o tipo de valores. Essa pluralidade de visões de mundo não permite que os agentes sejam ingenuamente tratados como heróis, vilões ou vítimas. Com isso, o autor do texto de ciências sociais procuraria simular um ponto de vista de Deus, como ironista supremo, que tudo vê, acima dos participantes imperceptivos de seu relato. Foi feito um estudo de caso a partir do debate sobre populismo no Brasil, no qual foram identificados quatro pontos básicos em torno dos quais girou a controvérsia: o das estruturas prototípicas, o da estruturação imaginária, o da estrutura intersubjetiva e a dinâmica da relação entre grande teoria e pesquisa empírica. / The aim of this thesis is to get as close as possible to a logic of discovery for the social sciences. Those disciplines do not have a neutral and objective narrative, but try to achieve, rhetorically, neutrality and objectivity effects, avoiding to portrait agents as heroes, villains or victims. It follows from the need to validate scientific narratives in face of an ideally or potentially universal auditory, withholding, in principle, all kinds of values. Such plurality of world visions makes it difficult to naively treat agents as heroes, villains, or victims. As a consequence, the social scientist simulates a Gods Eye view, placing himself in a Supreme Ironist perspective, who sees everything from above, whose vision reaches beyond what nonperceptive agents can see. To make my point, I took as case study the Brazilian controversy over populism. Based on it, four main topics of development were identified: one refered to the prototypical theoretic structures, other to its imaginary structuration, another to its intersubjective structure, and a last one to the relationship of empirical research to grand theory.

Aplicações cientes de contexto precisam de mecanismos para recuperar informações sobre o seu contexto de execução. Com base no contexto atual, tais aplicações são capazes de se autoadaptar para fornecer informações e serviços adequados aos seus usuários. A abordagem comum para infraestruturas de apoio às aplicações sensíveis ao contexto fornece serviços para a descoberta de recursos através da utilização de pares <chave-valor> e motores que executam apenas correspondência sintática. Esta abordagem não considera as possíveis relações semânticas entre as palavras-chave usadas. Portanto, a sua expressividade semântica limitada, leva a um serviço de descoberta que provê baixa taxa de recuperação e baixa acurácia. Este trabalho apresenta a utilização de uma outra abordagem para o serviço de contexto e descoberta, que utiliza ontologias para representar os recursos do contexto de execução e capturar a semântica da consulta do usuário, melhorando assim o processo de descoberta para a autoadaptação de sistemas sensíveis ao contexto. A abordagem proposta oferece também pontos de extensão para as aplicações clientes através da utilização de outras ontologias. Esta abordagem foi integrada à infraestrutura CDRF, de forma a adicionar semântica aos serviços desenvolvidos neste projeto. Exemplos de aplicações são também propostos para demonstrar a utilização dos novos serviços. / Context-aware applications demand ways of retrieving context information from the environment. Based on the current context, such applications are able to self-adapt to provide the correct information and services to its users. The usual approach for supporting infrastructures for context-aware applications provides facilities for resource discovery using <key-value> pairs and discovery engines that perform syntactic matching. This approach does not consider the possible semantic relations between the keywords used. So its limited semantic expressiveness often leads to poor discovery results. This paper presents the use of a different approach for service discovery that uses ontologies to represent resources and capture the semantics of the users query, improving the discovery process for self-adaptation of context-aware systems. The proposed approach also offers extension hooks to the client applications through the use of other ontologies. This approach is integrated into the CDRF framework and adds semantics to the services developed in that project. Example applications are also proposed to demonstrate the use of the new services.