viii, 61 p. A print copy of this thesis is available through the UO Libraries. Search the library catalog for the location and call number. / Set in the turbulence of 1968, Uwe Timm's novel, Heißer Sommer, focuses on two themes: self-discovery and the exploration of boundaries. The protagonist in Timm's novel is Ullrich, a university student who embodies the unrest of his time. Timm intertwines Ullrich's inner private sphere with the outer political sphere, which allows him to understand himself through the frame of his political activism. Moreover, Ullrich is used as an instrument by Timm to critique and shed an ironical light on the glamorization of the West German student movement. Timm illuminates several political (as well as personal) contradictions and criticisms through his protagonist's exposure to the revolutionary movement. / Adviser: Alexander Mathas

Doctor en Ciencias, Mención Computación / Este trabajo de tesis presenta soluciones para al problema de detección de anomalı́as en flujo de datos multivariantes. Dado una subsequencia de serie temporal (una pequeña parte de la serie original) como entrada, uno quiere conocer si este corresponde a una observación normal o es una anomalı́a, con respecto a la información histórica. Pueden surgir dificultades debido principalmente a que los tipos de anomalı́a son desconocidos. Además, la detección se convierte en una tarea costosa debido a la gran cantidad de datos y a la existencia de variables de dominios heterogéneos. En este contexto, se propone un enfoque de detección de anomalı́as basado en Discord Discovery, que asocia la anomalı́a con la subsecuencia más inusual utilizando medidas de similitud. Tı́picamente, los métodos de reducción de la dimensionalidad y de indexación son elaborados para restringir el problema resolviéndolo eficientemente. Adicionalmente, se propone técnicas para generar modelos representativos y consisos a partir de los datos crudos con el fin de encontrar los patrones inusuales. Estas técnicas también mejoran la eficiencia en la búsqueda mediante la reducción de la dimensionalidad. Se aborda las series multivariantes usando técnicas de representación sobre subsequencias no- normalizadas, y se propone nuevas técnicas de discord discovery basados en ı́ndices métricos. El enfoque propuesto es comparado con técnicas del estado del arte. Los resultados ex- perimentales demuestran que aplicando la transformación de translación y representación de series temporales pueden contribuir a mejorar la eficacia en la detección. Además, los métodos de indexación métrica y las heurı́sticas de discord discovery pueden resolver eficien- temente la detección de anomalı́as en modo offline y online en flujos de series temporales multivariantes. / Este trabajo ha sido financiado por beca CONICYT - CHILE / Doctorado para Extranjeros, y apoyada parcialmente por el Proyecto FONDEF D09I1185 y el Programa de Becas de NIC Chile

Online social networks (OSNs) have become the most popular Internet application that attracts billions of users to share information, disseminate opinions and interact with others in the online society. The unprecedented growing popularity of OSNs naturally makes using social network services as a pervasive phenomenon in our daily life. The majority of OSNs service providers adopts a centralised architecture because of its management simplicity and content controllability. However, the centralised architecture for large-scale OSNs applications incurs costly deployment of computing infrastructures and suffers performance bottleneck. Moreover, the centralised architecture has two major shortcomings: the single point failure problem and the lack of privacy, which challenges the uninterrupted service provision and raises serious privacy concerns. This thesis proposes a decentralised approach based on peer-to-peer (P2P) networks as an alternative to the traditional centralised architecture. Firstly, a self-organised architecture with self-sustaining social network adaptation has been designed to support decentralised topology maintenance. This self-organised architecture exhibits small-world characteristics with short average path length and large average clustering coefficient to support efficient information exchange. Based on this self-organised architecture, a novel decentralised service discovery model has been developed to achieve a semantic-aware and interest-aware query routing in the P2P social network. The proposed model encompasses a service matchmaking module to capture the hidden semantic information for query-service matching and a homophily-based query processing module to characterise user’s common social status and interests for personalised query routing. Furthermore, in order to optimise the efficiency of service discovery, a swarm intelligence inspired algorithm has been designed to reduce the query routing overhead. This algorithm employs an adaptive forwarding strategy that can adapt to various social network structures and achieves promising search performance with low redundant query overhead in dynamic environments. Finally, a configurable software simulator is implemented to simulate complex networks and to evaluate the proposed service discovery model. Extensive experiments have been conducted through simulations, and the obtained results have demonstrated the efficiency and effectiveness of the proposed model.

abstract: Online health forums provide a convenient channel for patients, caregivers, and medical professionals to share their experience, support and encourage each other, and form health communities. The fast growing content in health forums provides a large repository for people to seek valuable information. A forum user can issue a keyword query to search health forums regarding to some specific questions, e.g., what treatments are effective for a disease symptom? A medical researcher can discover medical knowledge in a timely and large-scale fashion by automatically aggregating the latest evidences emerging in health forums. This dissertation studies how to effectively discover information in health forums. Several challenges have been identified. First, the existing work relies on the syntactic information unit, such as a sentence, a post, or a thread, to bind different pieces of information in a forum. However, most of information discovery tasks should be based on the semantic information unit, a patient. For instance, given a keyword query that involves the relationship between a treatment and side effects, it is expected that the matched keywords refer to the same patient. In this work, patient-centered mining is proposed to mine patient semantic information units. In a patient information unit, the health information, such as diseases, symptoms, treatments, effects, and etc., is connected by the corresponding patient. Second, the information published in health forums has varying degree of quality. Some information includes patient-reported personal health experience, while others can be hearsay. In this work, a context-aware experience extraction framework is proposed to mine patient-reported personal health experience, which can be used for evidence-based knowledge discovery or finding patients with similar experience. At last, the proposed patient-centered and experience-aware mining framework is used to build a patient health information database for effectively discovering adverse drug reactions (ADRs) from health forums. ADRs have become a serious health problem and even a leading cause of death in the United States. Health forums provide valuable evidences in a large scale and in a timely fashion through the active participation of patients, caregivers, and doctors. Empirical evaluation shows the effectiveness of the proposed approach. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2016

Many pathogenic microorganisms are believed to stochastically switch into low metabolic states that display resistance to supra-lethal levels of antibiotics. These so-called “persister” cells have been associated with recurrent infections and the development of antibiotic resistance. Whilst a compound that eliminates Staphylococcus aureus persister cells has been described, it is not active against Gram-negative bacteria. The aim of my PhD project was to develop a high-throughput assay for compounds that eradicate persister cells in the -proteobacterium Burkholderia thailandensis. Further to this, I aimed to develop “hit” compounds from screening into lead series through investigation of structure activity relationships and, use a chemical genetics approach to elucidate potential mechanisms of action. I developed a phenotypic assay to identify compounds that eradicate persister cells. The assay was based on the reduction of the resazurin based dye PrestoBlue. Optimization of the assay gave a Z’ prime of 0.41 when screened in high throughput at the DDU. Screening of the library of 61,250 compounds identified 2,127 compounds that gave a statistically significant reduction in persister cell numbers. Follow-up assays highlighted 29 compounds with a pIC50 greater than five. Detailed investigation allowed me to down select to six “best in class” compounds, which included the licensed drug chloroxine. A time dependent killing assay showed that chloroxine reduced levels of persister cells by three orders of magnitude over 72 hours (P = 0.01). Hit expansion around chloroxine using commercially available compounds did not identify any more potent compounds, but did highlight key features of the molecule for activity. Assay protocols were provided to collaborators at DSTL who were able to iv show that chloroxine is also active against persister cells formed by the tropical pathogen and Tier 1 biological agent Burkholderia pseudomallei. Investigations into the mechanism of action of chloroxine used Next Generation Sequencing of an over expression library, identifying two putative genes involved in inhibition of persister cells by chloroxine. My findings demonstrate a phenotypic assay against persister cells in Gram-negative bacteria, which has the power to identify potent anti-persister agents to assist in chemotherapy. Structural activity relationship and mechanism of action investigations have indicated lead series and genetic starting points for future development of this research. My PhD project has concluded with sufficient data for continuation of research following a number of leads and is at an ideal stage for instigation of a medicinal chemistry program for development of chloroxine as a clinical option for treatment of persistent melioidosis.

Made available in DSpace on 2014-06-12T15:57:37Z (GMT). No. of bitstreams: 2 arquivo3214_1.pdf: 3789743 bytes, checksum: 5121a8308f93d20405e932f1e9bab193 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2010 / Universidade Federal do Amazonas / Um breve exame do atual tráfego Internet mostra uma mistura de serviços conhecidos e desconhecidos, novas e antigas aplicações, tráfego legítimo e ilegítimo, dados solicitados e não solicitados, tráfego altamente relevante ou simplesmente indesejado. Entre esses, o tráfego Internet não desejado tem se tornado cada vez mais prejudicial para o desempenho e a disponibilidade de serviços, tornando escasso os recursos das redes. Tipicamente, este tipo de tráfego é representado por spam, phishing, ataques de negação de serviço (DoS e DDoS), vírus e worms, má configuração de recursos e serviços, entre outras fontes. Apesar dos diferentes esforços, isolados e/ou coordenados, o tráfego Internet não desejado continua a crescer. Primeiramente, porque representa uma vasta gama de aplicações de usuários, dados e informações com diferentes objetivos. Segundo, devido a ineficácia das atuais soluções em identificar e reduzir este tipo de tráfego. Por último, uma definição clara do que é não desejado tráfego precisa ser feita. A fim de solucionar estes problemas e motivado pelo nível atingido pelo tráfego não desejado, esta tese apresenta: 1. Um estudo sobre o universo do tráfego Internet não desejado, apresentado definições, discussões sobre contexto e classificação e uma série de existentes e potencias soluções. 2. Uma metodologia para identificar tráfego não desejado baseada em orquestração. OADS (Orchestration Anomaly Detection System) é uma plataforma única para a identificação de tráfego não desejado que permite um gerenciamento cooperativa e integrado de métodos, ferramentas e soluções voltadas a identificação de tráfego não desejado. 3. O projeto e implementação de soluções modulares integráveis a metodologia proposta. A primeira delas é um sistema de suporte a recuperação de informações na Web (WIRSS), chamado OADS Miner ou simplesmente ARAPONGA, cuja função é reunir informações de segurança sobre vulnerabilidades, ataques, intrusões e anomalias de tráfego disponíveis na Web, indexá-las eficientemente e fornecer uma máquina de busca focada neste tipo de informação. A segunda, chamada Alert Pre- Processor, é um esquema que utilize uma técnica de cluster para receber múltiplas fontes de alertas, agregá-los e extrair aqueles mais relevantes, permitindo correlações e possivelmente a percepção das estratégias usadas em ataques. A terceira e última é um mecanismo de correlação e fusão de alertas, FER Analyzer, que utilize a técnica de descoberta de episódios frequentes (FED) para encontrar sequências de alertas usadas para confirmar ataques e possivelmente predizer futuros eventos. De modo a avaliar a proposta e suas implementações, uma série de experimentos foram conduzidos com o objetivo de comprovar a eficácia e precisão das soluções

This Master's Thesis describes the design and development of an architecture for automated network node discovery and topology analysis, implemented as an extension to the network management and provisioning system NETadmin. The architecture includes functionality for flexible network model assessment, using a method for versatile comparison between off-line database models and real-world models. These models are populated by current node data collected by network sensors. The presented architecture supports (1) efficient creation and synchronization of network topology information (2) accurate recognition of new, replaced and upgraded nodes, including rogue nodes that may exhibit malicious behavior, and (3) provides an extension of an existing vendor-neutral enterprise network management and provisioning system. An evaluation of the implementation shows evidence of accurate discovery and classification of unmatched hosts in a live customer production network with over 400 nodes, and presents data on performance and scalability levels. The work was carried out at Netadmin System i Sverige AB, in Linköping, Sweden.

I denna uppsats undersöks creature design samt narrativ teori kring skräckfilmer för att ta reda på hur man kan skapa filmmonster vars utseende kan berätta och föra fram en fängslande historia. Ett väldesignat monster lever kvar i publikens minnen, och skapar ikoner för sin tidsperiod eller sin genre. Uppsatsen använder sig av en semiotisk metod för att analysera monstren i filmerna Alien, The Thing och Rovdjuret. För att designa monster till science fiction kan man kombinera zoologi, anatomiska studier samt mänsklig psykologi och fobier för att skapa ett visuellt fascinerande monster som skrämmer publiken och lever kvar i det allmänna medvetandet.

M.Ed. (Tertiary Didactics) / Please refer to full text to view abstract

Rapid development of antimicrobial resistance (AMR) among bacteria, combined with diminished new antibiotic discovery rates, is an increasing threat to human health. Bacterially derived antimicrobial peptides (AMP) hold excellent potential as potent novel therapeutics. This study embraces traditional natural AMP discovery methods and the newer in silico genome mining tool BAGEL 3 to facilitate identification of novel antimicrobial agents. The traditional screening efforts led to the discovery of two promising antimicrobial producer strains; Bacillus pumilus J1 producing two AMPs, peptides NI03 and NI04, and Klebsiella pneumoniae A7, which produced peptide NI05. In silico mining of the B. pumilus J1 and K. pneumoniae A7 genomes and those from under exploited anaerobic bacteria using BAGEL 3 yielded 18 putative bacteriocin structures that were associated with multiple known and relevant bacteriocin accessory genes and/or carried significant homologies to known bacteriocins. Peptide NI04 proved to be active against Gram positive species only, including meticillin resistant Staphylococcus aureus and vancomycin resistant enterococci and peptide NI03, in addition to these pathogens, showed activity against E. coli. Peptide NI05 was active against Gram-negative pathogens including extended spectrum β-lactamase producing E. coli. All isolated peptides were observed to be proteinaceous in nature and highly heat stable. Peptides were purified or partially purified using solid phase extraction followed by RP-HPLC. The mass of the peptides was determined using ESI or MALDI-TOF mass spectrometry. Tandem MS fragmentation of peptide NI04 generated several sequence tags. Draft genome sequences of the B. pumilus J1 and K. pneumoniae A7 producer strains were obtained using the Illumina MiSeq platform. This allowed identification of the genes encoding peptide NI04, which was confirmed to be novel and was named pumicin NI04. Further characterisation of pumicin NI04 demonstrated it was non-toxic to keratinocytes, Vero cells and non-haemolytic up to at least 18x the minimum inhibitory concentration. The discovery revealed that pumicin NI04 belongs to the WXG-100 peptide superfamily, having homology with the mycobacterial and staphylococcal virulence factor EsxA. This represents the first report of antimicrobial activity in a WXG-100 peptide and has intriguing evolutionary implications. Although it was not possible to fully characterise peptides NI03 and NI05, when BAGEL 3 was used to mine the B. pumilus J1 genome, a promising putative bacteriocin candidate was identified that was homologous to Enterocin AS-45, which also confers anti Gram-negative activity and may be related to the activity observed for NI03, however more evidence is required. Investigations of the K. pneumoniae A7 bacteriocin on the other hand helped establish that the K. pneumoniae microcin E492 pathway was present and highly conserved in strain A7, and is likely to be responsible for the activity observed indicating that NI05 was not a novel peptide.