Through the use of chronic experimental animal models, the majority of in vitro investigations of temporal lobe epilepsy have demonstrated enhanced network activity within the subdivisions of the hippocampal formation. However, clinical evidence in combination with in vivo and in vitro studies indicates that structures external to the hippocampus contribute to the genesis of seizure activity. To address the effects of limbic network excitation, I have utilized combined hippocampal---entorhinal cortex brain slices from pilocarpine-treated rats that display chronic seizures. / My investigations have focused upon three structures, the subiculum, entorhinal cortex and the insular cortex. The experiments in the pilocarpine-treated subiculum demonstrated increased network excitability that was attributed to a more positive GABAA receptor mediated inhibitory post-synaptic potential (IPSP) reversal point coupled with a reduced IPSP peak conductance. Utilizing RT-PCR analysis and immunohistochemical staining we observed a decline in K+-Cl- cotransporter mRNA expression and a reduced number of parvalbumin-positive, presumptive inhibitory interneurons. My second project assessed the network hyperexcitability in layer V of the lateral entorhinal cortex. This is the first study to report spontaneous bursting, in the absence of epileptogenic agents, in the epileptic entorhinal cortex. We attributed this level of network excitation to reduced GABAA receptor mediated inhibition and increased synaptic sprouting. In the final project, we extended our slice preparation to include the insular cortex, a structure external to the temporal lobe. Our investigations identified a mechanism of NMDA receptor dependent synaptic bursting that masked GABA A receptor mediated conductances.

The aim of this thesis was to examine the spatial and the temporal patterns of anxiety and chest pain resulting from the Canterbury, New Zealand earthquaeks. Three research objectives were identified: examine any spatial or termporal clusters of anxiety and chest pain; examine the associations between anxiety, chest pain and damage to neighbourhood; and determine any statistically significant difference in counts of anxiety and chest pain after each earthquake or aftershock which resulted in severe damage. Measures of the extent of liquefaction the location of CERA red-zones were used as proxy measures for earthquake damage. Cases of those who presented to Christchurch Public Hospital Emergency Department with either anxiety or chest pain between May 2010 and April 2012 were aggregated to census area unit (CAU) level for analysis. This thesis has taken a unique approach to examining the spatial and spatio-temporal variations of anxiety and chest pain after an earthquake and offers unique results. This is the first study of its kind to use a GIS approach when examining Canterbury specific earthquake damage and health variables at a CAU level after the earthquakes. Through the use of spatio-termporal scan modelling, negative and linear regression modelling and temporal linear modelling with dummy variables this research was able to conclude there are significant spatial and temporal variations in anxiety and chest pain resulting from the earthquakes. The spatio-termporal scan modelling identified a hot cluster of both anxiety and chest pain within Christchurch at the same time the earthquakes occurred. The negative binomial model found liquefaction to be a stronger predictor of anxiety than the Canterbury Earthquake Recovery Authority's (CERA) land zones. The linear regression model foun chest pain to be positively associated with all measures of earthquake damage with the exception of being in the red-zone. The temporal modelling identified a significant increase in anxiety cases one month after a major earthquake, and chest pain cases spiked two weeks after an earthquake and gradually decreased over the following five weeks. This research was limited by lack of control period data, limited measures of earthquake damage, ethical restrictions, and the need for population tracking data. The findings of this research will be useful in the planning and allocation of mental wellbeing resources should another similar event like the Canterbury Earthquakes occur in New Zealand.

Studies on data mining are being pursued in many different research areas, such as Machine Learning, Statistics, and Databases. The work presented in this thesis is based on the database perspective of data mining. The main focuses are on the temporal aspects of data mining problems, especially association rule discovery, and issues on the integration of data mining and database systems. Firstly, a theoretical framework for temporal data mining is proposed in this thesis. Within this framework, not only potential patterns but also temporal features associated with the patterns are expected to be discovered. Calendar time expressions are suggested to represent temporal features and the minimum frequency of patterns is introduced as a new threshold in the model of temporal data mining. The framework also emphasises the necessary components to support temporal data mining tasks. As a specialisation of the proposed framework, the problem of mining temporal association rules is investigated. The methodology adopted in this thesis is eventually discovering potential temporal rules by alternatively using special search techniques for various restricted problems in an interactive and iterative process. Three forms of interesting mining tasks for temporal association rules with certain constraints are identified. These tasks are the discovery of valid time periods of association rules, the discovery of periodicities of association rules, and the discovery of association rules with temporal features. The search techniques and algorithms for those individual tasks are developed and presented in this thesis. Finally, an integrated query and mining system (IQMS) is presented in this thesis, covering the description of an interactive query and mining interface (IQMI) supplied by the IQMS system, the presentation of an SQL-like temporal mining language (TML) with the ability to express various data mining tasks for temporal association rules, and the suggestion of an IQMI-based interactive data mining process. The implementation of this system demonstrates an alternative approach for the integration of the DBMS and data mining functions.

Pagrindinis šio darbo tikslas yra išnagrinėti judančių objektų indeksavimo duomenų bazėse problemas, siūlomus sprendimus bei palyginti keleto iš jų veiksmingumą. Įvairiais pjūviais buvo lyginami praeities duomenis indeksuojantys R ir iš jo išvesti STR bei TB medžiai. Eksperimentai atlikti naudojant sugeneruotus judančių objektų duomenis. Gauti rezultatai parodė, kad indeksų veiksmingas priklauso nuo tam tikrų sąlygų ir aplinkybių, kuriomis jie naudojami. / Over the past few years, there has been a continuous improvement in the wireless communications and the positioning technologies. As a result, tracking the changing positions of continuously moving objects is becoming increasingly feasible and necessary. Databases that deal with objects that change their location and/or shape over time are called spatio-temporal databases. Traditional database approaches for effective information retrieval cannot be used as the moving objects database is highly dynamic. A need for so called spatio-temporal indexing techniques comes to scene. Mainly, by the problem they are addressed to, indices are divided into two groups: a) indexing the past and b) indexing the current and predicted future positions. Also the have been proposed techniques covering both problems. This work is a survey for well known and used indices. Also there is a performance comparison between several past indexing methods. STR Tree, TB Tree and the predecessor of many indices, the R Tree are compared in various aspects using generated datasets of simulated objects movement.

Temporal Summarization (TS) is a new track introduced as part of the Text REtrieval Conference (TREC) in 2013. This track aims to develop systems which can return important updates related to an event over time. In TREC 2013, the TS track specifically used disaster related events such as earthquake, hurricane, bombing, etc. This thesis mainly focuses on building an effective TS system by using a combination of Information Retrieval techniques. The developed TS system returns updates related to disaster related events in a timely manner. By participating in TREC 2013 and with experiments conducted after TREC, we examine the effectiveness of techniques such as distributional similarity for term expansion, which can be employed in building TS systems. Also, this thesis describes the effectiveness of other techniques such as stemming, adaptive sentence selection over time and de-duplication in our system, by comparing it with other baseline systems. The second part of the thesis examines the current methodology used for evaluating TS systems. We propose a modified evaluation method which could reduce the manual effort of assessors, and also correlates well with the official track’s evaluation. We also propose a supervised learning based evaluation method, which correlates well with the official track’s evaluation of systems and could save the assessor’s time by as much as 80%.

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Thesis (PhD) -- University of South Australia, 1999