The growing popularity of various Web 2.0 media has created massive amounts of user-generated content such as online reviews, blog articles, shared videos, forums threads, and wiki pages. Such content provides insights into web users' preferences and opinions, online communities, knowledge generation, etc., and presents opportunities for many knowledge discovery problems. However, several challenges need to be addressed: data collection procedure has to deal with unique characteristics and structures of various Web 2.0 media; advanced data selection methods are required to identify data relevant to specific knowledge discovery problems; interactions between Web 2.0 users which are often embedded in user-generated content also need effective methods to identify, model, and analyze. In this dissertation, I intend to address the above challenges and aim at three types of knowledge discovery tasks: (data) collection, selection, and investigation. Organized in this "CSI" framework, five studies which explore and propose solutions to these tasks for particular Web 2.0 media are presented. In Chapter 2, I study focused and hidden Web crawlers and propose a novel crawling system for Dark Web forums by addressing several unique issues to hidden web data collection. In Chapter 3 I explore the usage of both topical and sentiment information in web crawling. This information is also used to label nodes in web graphs that are employed by a graph-based tunneling mechanism to improve collection recall. Chapter 4 further extends the work in Chapter 3 by exploring the possibilities for other graph comparison techniques to be used in tunneling for focused crawlers. A subtree-based tunneling method which can scale up to large graphs is proposed and evaluated. Chapter 5 examines the usefulness of user-generated content in online video classification. Three types of text features are extracted from the collected user-generated content and utilized by several feature-based classification techniques to demonstrate the effectiveness of the proposed text-based video classification framework. Chapter 6 presents an algorithm to identify forum user interactions and shows how they can be used for knowledge discovery. The algorithm utilizes a bevy of system and linguistic features and adopts several similarity-based methods to account for interactional idiosyncrasies.

Fragment based drug discovery (FBDD) has been applied to two protease drug targets, MMP-12 and HIV-1 protease. The primary screening and characterization of hit fragments were performed with surface plasmon resonance -technology. Further evaluation of the interaction was done by inhibition studies and in one case with X-ray crystallography. The focus of the two projects was different. Many MMP inhibitors contain a strong zinc chelating group, hydroxamate, interacting with the catalytic zinc atom. This strategy may be the cause for the low specificity of MMP inhibitors. Using FBDD we found a fragment with an unusual strong affinity for MMP-12. An inhibition assay confirmed that it was an inhibitor but indicated a stoichiometry of 2:1. Crystallography data revealed that an adduct of the fragment was bound in the active site, with interactions both with the catalytic zinc and the S1’ pocket. This may present a new scaffold for MMP-12 inhibitors. For HIV-1 protease the focus was on identifying inhibitors not sensitive to current resistance mutations. A fragment library for screening with SPR-technology was designed and used for screening against wild type enzyme and three variants with resistance mutations. Many of the hits were promiscuous but a number of fragments with possible allosteric inhibition mechanism were identified. The temperature dependency of the dissociation rate and reported resistance mutations was studied with thermodynamics. A good, but not perfect correlation was found between resistance and both the dissociation data and the free energy for dissociation compared to data from wild type enzyme. However, the type of mutation also influenced the results. The flap mutation G48V displayed thermodynamic profiles not completely correlating with resistance. It was found that dissociation rate and thermodynamics may complement each other when studying resistance, but only one of them may not be enough.

Formal learning contexts often present information to learners in an inert and highly abstract form, making it unlikely that learners would ever use this information in their every-da y lives. Learners do, however, show a greater propensity for retaining information that is seen as having relevance in their lives . Constructivism is an educational paradigm that has gained popularity amongst educationists. The core tenet of this paradigm is that learners learn through interaction with their environment and that all knowledge construction is based on previous life experience. Information that is presented to learners in a contextualised form not only has a better chance of being retained in long-term memory, but also has a greater likelihood of being applied in relevant life situations. This publication deals with the research, design and delivery of important information concerning diseases that have a major impact in Southern Africa. Firstly, learners at the University of Natal, Durban were polled for their existing knowledge concerning four widespread diseases, namely HIV/AIDS , tuberculosis, malaria and cancer. Aspects of these diseases where learners demonstrated a low level of awareness were defined as the primary learning object ives for an educational 3D- immersive microworld. Areas of knowledge concerning the transmission, symptomatic expression, biology and prevention of these diseases were generally not well represented in the learner sample. Hence, information regarding these aspects is presented to learners in a contextualised form within the microworld. Motivation for learners to play in this microworld is provided by a storyline that was researched and written for the portal. In addition, the model used in the storyline design was evaluated for its effectiveness as a tool to be used in the planning of future educational games. A model, the Puzzle Process model, was proposed to inform the design of puzzle interfaces for these types of interactive learning environments, and puzzle interfaces were designed for the virtual environment according to the model guidelines. The learning environment was tested as part of the formative evaluation with a small sample of learners . The testing process made use of both quantitative and qualitative methodologies to evaluate the effectiveness of the learning environment as a possible learning tool. Comparison of pre- and post-gameplay questionnaires showed that learners gained a more indepth and richer understanding of the topics being dealt with in the portal. In particular, the puzzle objects situated in the environment stimulated learners to negotiate meanings for the puzzle interfaces and, in the process, encouraged learners to discuss the topic being dealt with. Results from this study also show that the longer learners discussed and negotiated a certain knowledge domain, the greater their increase in richness of information was for that knowledge domain after gameplay. These results highlight the importance of social dialogue in the knowledge construction process and suggest that environments like these have great potential based on their ability to encourage learners to talk to one another and their facilitators while negotiating mutually acceptable knowledge. The original Puzzle Process model, as well as the Game Achievement model and the Game Object model were modified to account for the need for social dialogue and content. These more comprehensive models are instrumental for use in future virtual world environment design. / Thesis (Ph.D.)-University of KwaZulu- Natal, Durban, 2004

This thesis presents a framework for semantic Web Service discovery using descriptive (non-functional) service characteristics in a large-scale, multi-domain setting. The framework uses Web Ontology Language for Services (OWL-S) to design a template for describing non-functional service parameters in a way that facilitates service discovery, and presents a layered scheme for organizing ontologies used in service description. This service description scheme serves as a core for desigining the four main functions of a service directory: a template-based user interface, semantic query expansion algorithms, a two-level indexing scheme that combines Bloom filters with a Distributed Hash Table, and a distributed approach for storing service description. The service directory is, in turn, implemented as an extension of the Open Service Discovery Architecture. <br /><br /> The search algorithms presented in this thesis are designed to maximize precision and completeness of service discovery, while the distributed design of the directory allows individual administrative domains to retain a high degree of independence and maintain access control to information about their services.

We explore the possibility of automating <i>NP</i>-hardness reductions. We motivate the problem from an artificial intelligence perspective, then propose the use of second-order existential (<i>SO</i>&#8707;) logic as representation language for decision problems. Building upon the theoretical framework of J. Antonio Medina, we explore the possibility of implementing seven syntactic operators. Each operator transforms <i>SO</i>&#8707; sentences in a way that preserves <i>NP</i>-completeness. We subsequently propose a program which implements these operators. We discuss a number of theoretical and practical barriers to this task. We prove that determining whether two <i>SO</i>&#8707; sentences are equivalent is as hard as GRAPH ISOMORPHISM, and prove that determining whether an arbitrary <i>SO</i>&#8707; sentence represents an <i>NP</i>-complete problem is undecidable.

Viral proteases are important targets for anti-viral drugs. Discovery of protease inhibitors as anti-viral drugs is aided by an understanding of the interactions between viral protease and inhibitors. This thesis addresses the characterization of protease-inhibitor interactions for application to drug discovery and model system development. The choice of a relevant target is essential to molecular interaction studies. Therefore, full-length NS3 protein of hepatitis C virus (HCV) was obtained, providing a more relevant target and a better model for the development of HCV protease inhibitors. In addition, resistance to anti-viral drugs, a serious problem in the treatment of AIDS, prompted the investigation of resistant variants of human immunodeficiency virus (HIV) protease. Drug resistance was initially explored by characterization of the interactions between a series of closely related inhibitors and resistant variants of HIV protease, using an inhibition assay to determine the inhibition dissociation constants (Ki). The relationship between structure, activity and resistance profiles was not clarified, indicating that the effect of structural changes in the inhibitors and the protease are not predictable and must be analyzed case wise. It was proposed that additional kinetic characterization of the interactions was required and a biosensor-based method allowing for determination of affinity, KD, and interaction rate constants, kon and koff, was adopted. The increased physiological relevance of this method was confirmed, and the affinity data have better correlation with cell culture data. In addition, interactions between clinical inhibitors of HIV protease and enzyme variants indicate that increased dissociation rates (koff) are associated with the development of resistance. Thermodynamic characterization of the interactions between HIV-1 protease and clinically relevant inhibitors revealed distinct energetic characteristics for inhibitors. The resolution of the energetics of association and dissociation identified an inhibitor with unique interaction characteristics and confirmed the validity of using this method for further characterization of molecular interactions. This work resulted in the development of model systems for the analysis of kinetics, resistance and thermodynamic characteristics of protein-inhibitor interactions. The results give increased understanding of the biomolecular interactions and can be applied to drug discovery.

A variety of HIV-1 protease inhibitors and their interactions with the enzyme have been characterized in order to identify novel and improved drugs against AIDS. The investigated inhibitors were represented by clinical and non-clinical inhibitors, active site and allosteric inhibitors, transition-state analogues and metal-ions. In addition, different enzyme variants were used to investigate the contribution of different amino acid residues to the interaction with different ligands. The problem of resistance has been addressed by exploring novel types of inhibitors, and resistant mutants of HIV-1 protease. A study resolving the inhibition of HIV-1 protease by Cu2+ showed that the enzyme can be allosterically inhibited and that copper inhibition is a result of an interaction with His-69 and a subsequent conformational change. Several types of transition-state analogues were analyzed with respect to their inhibition of wild-type and resistant mutants of HIV-1 protease. Unfortunately cyclic compounds were not found to be better than linear compounds. Moreover, it was not possible to identify structure-activity relationships that clearly correlated with efficacy towards mutants and a biosensor based method for more detailed kinetic studies was therefore adopted. By cross-linking the immobilized enzyme on the biosensor matrix, a stable surface was obtained and kinetic rate constants could be determined for the interaction between the enzyme and inhibitors. Additional improvements in the methodology involved identification of a more representative interaction model, allowing more detailed studies of interactions with resistant mutants and varying conditions. Finally, absorption to lipid membranes and interaction with human serum albumin and α1-glycoprotein by clinical drugs were studied in a simplified ADME model system for improvement of the earlier stages of drug development. These studies have revealed important characteristics of these drugs that can potentially be modeled into new compounds that have improved efficacy of both wild-type and resistant mutants of HIV-1 protease.

The present study has focused on characterising protease-ligand interactions in the context of drug discovery. The proteases that have been studied are human matrix metallopeptidase 12 (MMP-12), HIV-protease and Hepatitis C virus (HCV) NS3/NS4A protease. These studies have involved kinetic characterisation of protease-inhibitor interactions using biosensor technology, as well as determination of inhibition and activity regulation by using activity assays. The regulation of MMP-12 activity by calcium was proposed, based on the study of the calcium dependence of MMP-12 activity. Furthermore, it was shown that the high affinity of hydroxamate-based inhibitors of MMP-12 were due to slow dissociation of the enzyme-inhibitor complex by using a new biosensor assay for the study of interactions between MMP-12 and ligands. A study of the pH-dependency of protease-inhibitor interactions revealed that the interaction kinetics of HIV-protease inhibitors differed with pH in a way that could be related to the inhibitor structures. This suggested that the forces of interaction are different in the association and dissociation phases of an interaction. Furthermore, it demonstrated the usefulness of pH as a variable in characterising protein-ligand interactions. Results applicable in the discovery of drugs against Hepatitis C were obtained, with the analysis of structure-activity relationships of novel inhibitors. Furthermore, the mode of binding imposed by key functional groups of the inhibitors was explored by investigating the effect of pH on the interactions with NS3. The results show the importance of using appropriate model systems for drug discovery by selecting relevant targets and assay conditions. Furthermore, the usefulness of kinetic rate information in drug discovery is demonstrated. Thus, by contributing to the knowledge of protease-ligand interactions, applicable to both protease inhibitor interactions and protease activity regulation, this thesis is expected to have an impact on the field of protease inhibitor development and drug discovery in general.

Presented at the University of Arizona 2016 IT Summit / The past several years has seen an increasing emphasis on providing access to the results of research, both publications and data. The majority of federal grant funding agencies require that researchers include a data management plan as part of their grant proposal. In response, the University of Arizona Libraries, in collaboration with the Office of Research and Discovery and the University Information Technology Services, has been providing data management services and resources to the campus for the past several years. In 2014, we conducted a research data management survey to find out how UA researchers manage their research data, determine the demand for existing services and identify new services that UA researchers need. In the fall of 2015, the Data Management and Data Publication and Curation (DMDC) Pilot was started to determine what specific services and tools, including training and support and the needed technology infrastructure, researchers need to effectively and efficiently manage and curate their research data. This presentation will present what data management services we currently are offering, discuss findings from the 2014 survey, and present initial results from the DMDC pilot.

Rule 31.22 of the Civil Procedure Rules 1998 provides, as a general rule, that those who receive documents through disclosure during civil proceedings may use them only for the purpose of the proceedings at hand. The general rule is subject to three exceptions, and judges have discretion to authorise subsequent use for other purposes. However, the foundational presupposition underpinning CPR 31.22 is that subsequent use, generally speaking, is improper. The thesis has two primary aims: (1) to demonstrate that the rule governing subsequent use (as developed in the case law) is theoretically and practically flawed, and that maintaining a blanket, general rule against subsequent use is unsound in principle, unjust, and procedurally inefficient; and (2) to generate a normative and procedural framework suitable for reform. Part I outlines the content, origins and operation of CPR 31.22. Through historical analysis, it suggests that presumptively categorising as improper all forms of subsequent use beyond the original litigation contradicts traditional authority. By identifying and examining the three principal rationales said to justify the modern rule, it argues that none affords sound justification. By analysing the exceptions to the rule, including judicial discretion, it seeks to show that such measures are incapable of remedying the defects in the underlying rule. Part II attempts to formulate a theoretically defensible, procedurally viable model for reforming CPR 31.22. It suggests that the presumption against subsequent use should be abolished, and the law reoriented around two central norms: the harm principle and a balancing approach. It tests this theoretical model by applying it to seven paradigmatic categories of subsequent use. Finally, it outlines a possible structure for procedural reform.