Cette thèse dans le domaine du traitement des signaux non-stationnaires, appliqué aux bruits du cœur mesurés avec un stéthoscope numérique, vise à concevoir un outil automatisé et « intelligent », permettant aux médecins de disposer d’une source d’information supplémentaire à celle du stéthoscope traditionnel. Une première étape dans l’analyse des signaux du cœur, consiste à localiser le premier et le deuxième son cardiaque (S1 et S2) afin de le segmenter en quatre parties : S1, systole, S2 et diastole. Plusieurs méthodes de localisation des sons cardiaques existent déjà dans la littérature. Une étude comparative entre les méthodes les plus pertinentes est réalisée et deux nouvelles méthodes basées sur la transformation temps-fréquence de Stockwell sont proposées. La première méthode, nommée SRBF, utilise des descripteurs issus du domaine temps-fréquence comme vecteur d’entré au réseau de neurones RBF qui génère l’enveloppe d’amplitude du signal cardiaque, la deuxième méthode, nommée SSE, calcule l’énergie de Shannon du spectre local obtenu par la transformée en S. Ensuite, une phase de détection des extrémités (onset, ending) est nécessaire. Une méthode d’extraction des signaux S1 et S2, basée sur la transformée en S optimisée, est discutée et comparée avec les différentes approches qui existent dans la littérature. Concernant la classification des signaux cardiaques, les méthodes décrites dans la littérature pour classifier S1 et S2, se basent sur des critères temporels (durée de systole et diastole) qui ne seront plus valables dans plusieurs cas pathologiques comme par exemple la tachycardie sévère. Un nouveau descripteur issu du domaine temps-fréquence est évalué et validé pour discriminer S1 de S2. Ensuite, une nouvelle méthode de génération des attributs, basée sur la décomposition modale empirique (EMD) est proposée.Des descripteurs non-linéaires sont également testés, dans le but de classifier des sons cardiaques normaux et sons pathologiques en présence des souffles systoliques. Des outils de traitement et de reconnaissance des signaux non-stationnaires basés sur des caractéristiques morphologique, temps-fréquences et non linéaire du signal, ont été explorés au cours de ce projet de thèse afin de proposer un module d’aide au diagnostic, qui ne nécessite pas d’information à priori sur le sujet traité, robuste vis à vis du bruit et applicable dans des conditions cliniques. / This thesis in the field of biomedical signal processing, applied to the heart sounds, aims to develop an automated and intelligent module, allowing medical doctors to have an additional source of information than the traditional stethoscope. A first step in the analysis of heart sounds is the segmentation process. The heart sounds segmentation process segments the PCG (PhonoCardioGram) signal into four parts: S1 (first heart sound), systole, S2 (second heart sound) and diastole. It can be considered one of the most important phases in the auto-analysis of PCG signals. The proposed segmentation module in this thesis can be divided into three main blocks: localization of heart sounds, boundaries detection of the localized heart sounds and classification block to distinguish between S1and S2. Several methods of heart sound localization exist in the literature. A comparative study between the most relevant methods is performed and two new localization methods of heart sounds are proposed in this study. Both of them are based on the S-transform, the first method uses Radial Basis Functions (RBF) neural network to extract the envelope of the heart sound signal after a feature extraction process that operates on the S-matrix. The second method named SSE calculates the Shannon Energy of the local spectrum calculated by the S-transform for each sample of the heart sound signal. The second block contains a novel approach for the boundaries detection of S1 and S2 (onset & ending). The energy concentrations of the S-transform of localized sounds are optimized by using a window width optimization algorithm. Then the SSE envelope is recalculated and a local adaptive threshold is applied to refine the estimated boundaries. For the classification block, most of the existing methods in the literature use the systole and diastole duration (systole regularity) as a criterion to discriminate between S1 and S2. These methods do not perform well for all types of heart sounds, especially in the presence of high heart rate or in the presence of arrhythmic pathologies. To deal with this problem, two feature extraction methods based on Singular Value Decomposition (SVD) technique are examined. The first method uses the S-Transform and the second method uses the Intrinsic Mode Functions (IMF) calculated by the Empirical Mode Decomposition (EMD) technique. The features are applied to a KNN classifier to estimate the performance of each feature extraction method. Nonlinear features are also tested in order to classify the normal and pathological heart sounds in the presence of systolic murmurs. Processing and recognition signal processing tools based on morphological, time-frequency and nonlinear signal features, were explored in this thesis in order to propose an auto-diagnosis module, robust against noise and applicable in clinical conditions.

The aim of this study is to measure and analyze vibrations on a fast response brushless exciter (FRBE) at a real hydropower plant and identify vibration origins through frequency analysis. Moreover, the observed vibrations are evaluated in relation to generator vibration standards and estimated tangential eigenfrequencies of the studied FRBE. It is concluded that the pulsations in the air gap torque, originating from the rotating thyristor bridge rectifier, is the source of the strongest vibrations. Some additional vibration sources are also identified. The requirements of the generator vibration standards are mostly fulfilled and no tangential eigenfrequencies are triggered in the vibration recordings. For further studies it is recommended that alternative control strategies and optimization of the FRBE mechanical design, with respect to its ability to withstand vibrations, should be investigated.

<p>Bone formation and bone healing were studied in the mandible, tibia and skull bones in adult, healthy and estrogen deficient rabbits implanted with different bone substitutes. </p><p>In the first study an evaluation of the differences in bone regeneration in and around solid (Alveograf *) and porous hydroxyapatite (Interpore 200*) was undertaken. The implant material was placed into experimentally made bone defects and in half of the defects hydroxyapatite was mixed with a fibrin sealant (Tisseel *). The material alone or mixed with Tisseel was also placed subperiostally in the mandible. The observation time was six month. No difference in bone regeneration was found between solid or porous hydroxyapatite granulas and the addition of Tisseel* did not seem to disturb the bone healing process. The implant material placed subperiostally did not induce bone formation nor did it provoke any bone resorption. The addition of Tisseel made the implant material much easier to handle and retain in the tissue during surgery.</p><p>Bone healing around hydroxyapatite implants was also evaluated in the second study. Experimental cavities in the mandible and tibia were filled with hydroxyapatite in granules or blocks (Interpore 200*) but now with or without autolyzed, antigen-extracted, allogeneic bone (AAA). Also in this study Tisseel* was used to facilitate the handling of the material. All cavities implanted with AAA-bone, regardless of the combination with hydroxyapatite or Tisseel, demonstrated excessive bone formation resembling exostosis formation. Thus, hydroxyapatite, both as granules and blocks, can be successfully combined with AAA bone utilizing the bone inductive capacity of AAA bone.</p><p>The same model was used to study the healing in ovariectomized animals in the third study. Bone cavities were implanted with or without AAA bone and left to heal. The results indicate that the osteoinductive capacity of AAA bone is in operation also in animals deprived of a normal estrogen production.</p><p>The effect of using AAA bone prior to implant insertion was studied in paper four. The bone-implant contact was significant higher when AAA bone had been used. The implant stability did not seem to be affected.</p><p>In paper five defects were made in skull and tibial bone in estrogen deficient animals. The deficiency of estrogen was confirmed through blood analysis, the decrease in the weight of uterus and bone mineral density. The whole body scanning with DEXA showed that the ovariectomized animals developed osteopenia. Various degree of bone formation was seen in the defects due to the influence of the bone inductive substance AAA bone. </p><p>The studies indicate that a conductive material like hydroxyapatite in granules or blocks could be useful in oral reconstructive surgery. The combination with AAA bone enhanced the bone formation in calvarial and tibial bone in healthy and estrogen deficient animals. Tisseel* could be used to facilitate handling and retention of the material in the intended position during the healing process without negative effects. </p>

Die Arbeit beschreibt die Analyse von Beobachtungen zweier Sonnenflecken in zweidimensionaler Spektro-Polarimetrie. Die Daten wurden mit dem Fabry-Pérot-Interferometer der Universität Göttingen am Vakuum-Turm-Teleskop auf Teneriffa erfasst. Von der aktiven Region NOAA 9516 wurde der volle Stokes-Vektor des polarisierten Lichts in der Absorptionslinie bei 630,249 nm in Einzelaufnahmen beobachtet, und von der aktiven Region NOAA 9036 wurde bei 617,3 nm Wellenlänge eine 90-minütige Zeitserie des zirkular polarisierten Lichts aufgezeichnet. Aus den reduzierten Daten werden Ergebniswerte für Intensität, Geschwindigkeit in Beobachtungsrichtung, magnetische Feldstärke sowie verschiedene weitere Plasmaparameter abgeleitet. Mehrere Ansätze zur Inversion solarer Modellatmosphären werden angewendet und verglichen. Die teilweise erheblichen Fehlereinflüsse werden ausführlich diskutiert. Das Frequenzverhalten der Ergebnisse und Abhängigkeiten nach Ort und Zeit werden mit Hilfe der Fourier- und Wavelet-Transformation weiter analysiert. Als Resultat lässt sich die Existenz eines hochfrequenten Bandes für Geschwindigkeitsoszillationen mit einer zentralen Frequenz von 75 Sekunden (13 mHz) bestätigen. In größeren photosphärischen Höhen von etwa 500 km entstammt die Mehrheit der damit zusammenhängenden Schockwellen den dunklen Anteilen der Granulen, im Unterschied zu anderen Frequenzbereichen. Die 75-Sekunden-Oszillationen werden ebenfalls in der aktiven Region beobachtet, vor allem in der Lichtbrücke. In den identifizierten Bändern oszillatorischer Power der Geschwindigkeit sind in einer dunklen, penumbralen Struktur sowie in der Lichtbrücke ausgeprägte Strukturen erkennbar, die sich mit einer Horizontalgeschwindigkeit von 5-8 km/s in die ruhige Sonne bewegen. Diese zeigen einen deutlichen Anstieg der Power, vor allem im 5-Minuten-Band, und stehen möglicherweise in Zusammenhang mit dem Phänomen der „Evershed-clouds“. Eingeschränkt durch ein sehr geringes Signal-Rausch-Verhältnis und hohe Fehlereinflüsse werden auch Magnetfeldvariationen mit einer Periode von sechs Minuten am Übergang von Umbra zu Penumbra in der Nähe einer Lichtbrücke beobachtet. Um die beschriebenen Resultate zu erzielen, wurden bestehende Visualisierungsverfahren der Frequenzanalyse verbessert oder neu entwickelt, insbesondere für Ergebnisse der Wavelet-Transformation. / The publication describes the analysis of two sunspot observations in two-dimensional spectropolarimetry. The data was obtained with the Fabry-Pérot-interferometer of Göttingen University at the German Vacuum Tower Telescope on Tenerife. Of the active region NOAA 9516 the full Stokes vector of polarised light was observed in the absorption line at 630.249 nm in single scans. A ninety minute time series of circular polarised light of the active region NOAA 9036 was observed at 617.3 nm wavelength. From the reduced data results for intensity, line-of-sight velocity, magnetic field strength as well as several other plasma parameters are inferred. Different approaches to solar atmosphere model inversion are applied and compared. The significant influence of errors is discussed in detail. The frequency behaviour of the results and spatial and temporal dependencies are further analysed by Fourier and wavelet transformation. As a result the existence of a high frequency band of velocity oscillations with a central frequency of about 75-seconds (13 mHz) can be confirmed. In greater heights of about 500 km the majority of the corresponding shock waves are derived from darker parts of the granules in contrast to the dominant five-minute-oscillations. 75-second-oscillations can also be observed in the active region, especially in the light bridge. In the identified bands of oscillatory velocity power, distinct structures become visible in a penumbral dark structure as well as in the light bridge that move into the quiet sun with a horizontal speed of 5-8 km/s. They show an increase in power, mostly 5-minute-band, and may be related to the Evershed cloud phenomenon. Under the constraint of a very low signal-to-noise ratio and high error influence, magnetic field variations of a 6-minute period are also observed in an umbral-penumbral transition area close to a light bridge. To derive these results, existing visualisation methods for frequency analysis where improved or newly developed, especially so for wavelet transform results.

Flood design necessitates discharge estimates for large recurrence intervals. However, in a flood frequency analysis, the uncertainty of discharge estimates increases with higher recurrence intervals, particularly due to the small number of available flood data. Furthermore, traditional distribution functions increase unlimitedly without consideration of an upper bound discharge. Hence, additional information needs to be considered which is representative for high recurrence intervals. Envelope curves which bound the maximum observed discharges of a region are an adequate regionalisation method to provide additional spatial information for the upper tail of a distribution function. Probabilistic regional envelope curves (PRECs) are an extension of the traditional empirical envelope curve approach, in which a recurrence interval is estimated for a regional envelope curve (REC). The REC is constructed for a homogeneous pooling group of sites. The estimation of this recurrence interval is based on the effective sample years of data considering the intersite dependence among all sites of the pooling group. The core idea of this thesis was an improvement of discharge estimates for high recurrence intervals by integrating empirical and probabilistic regional envelope curves into the flood frequency analysis. Therefore, the method of probabilistic regional envelope curves was investigated in detail. Several pooling groups were derived by modifying candidate sets of catchment descriptors and settings of two different pooling methods. These were used to construct PRECs. A sensitivity analysis shows the variability of discharges and the recurrence intervals for a given site due to the different assumptions. The unit flood of record which governs the intercept of PREC was determined as the most influential aspect. By separating the catchments into nested and unnested pairs, the calculation algorithm for the effective sample years of data was refined. In this way, the estimation of the recurrence intervals was improved, and therefore the use of different parameter sets for nested and unnested pairs of catchments is recommended. In the second part of this thesis, PRECs were introduced into a distribution function. Whereas in the traditional approach only discharge values are used, PRECs provide a discharge and its corresponding recurrence interval. Hence, a novel approach was developed, which allows a combination of the PREC results with the traditional systematic flood series while taking the PREC recurrence interval into consideration. An adequate mixed bounded distribution function was presented, which in addition to the PREC results also uses an upper bound discharge derived by an empirical envelope curve. By doing so, two types of additional information which are representative for the upper tail of a distribution function were included in the flood frequency analysis. The integration of both types of additional information leads to an improved discharge estimation for recurrence intervals between 100 and 1000 years. / Abschätzungen von Abflüssen mit hohen Wiederkehrintervallen werden vor allem für die Bemessung von Extremhochwässern benötigt. In der Hochwasserstatistik bestehen insbesondere für hohe Wiederkehrintervalle große Unsicherheiten, da nur eine geringe Anzahl an Messwerten für Hochwasserereignisse verfügbar ist. Zudem werden zumeist Verteilungsfunktionen verwendet, die keine obere Grenze beinhalten. Daher müssen zusätzliche Informationen zu den lokalen Pegelmessungen berücksichtigt werden, die den Extrembereich einer Verteilungsfunktion abdecken. Hüllkurven ermitteln eine obere Grenze von Hochwasserabflüssen basierend auf beobachteten maximalen Abflusswerten. Daher sind sie eine geeignete Regionalisierungsmethode. Probabilistische regionale Hüllkurven sind eine Fortentwicklung des herkömmlichen Ansatzes der empirischen Hüllkurven. Hierbei wird einer Hüllkurve einer homogenen Region von Abflusspegeln ein Wiederkehrintervall zugeordnet. Die Berechnung dieses Wiederkehrintervalls basiert auf der effektiven Stichprobengröße und berücksichtigt die Korrelationsbeziehungen zwischen den Pegeln einer Region. Ziel dieser Arbeit ist eine Verbesserung der Abschätzung von Abflüssen mit großen Wiederkehrintervallen durch die Integration von empirischen und probabilistischen Hüllkurven in die Hochwasserstatistik. Hierzu wurden probabilistische Hüllkurven detailliert untersucht und für eine Vielzahl an homogenen Regionen konstruiert. Hierbei wurden verschiedene Kombinationen von Einzugsgebietsparametern und Variationen von zwei Gruppierungsmethoden verwendet. Eine Sensitivitätsanalyse zeigt die Variabilität von Abfluss und Wiederkehrintervall zwischen den Realisationen als Folge der unterschiedlichen Annahmen. Die einflussreichste Größe ist der maximale Abfluss, der die Höhe der Hüllkurve bestimmt. Eine Einteilung in genestete und ungenestete Einzugsgebiete führt zu einer genaueren Ermittlung der effektiven Stichprobe und damit zu einer verbesserten Abschätzung des Wiederkehrintervalls. Daher wird die Verwendung von zwei getrennten Parametersätzen für die Korrelationsfunktion zur Abschätzung des Wiederkehrintervalls empfohlen. In einem zweiten Schritt wurden die probabilistischen Hüllkurven in die Hochwasserstatistik integriert. Da in traditionellen Ansätzen nur Abflusswerte genutzt werden, wird eine neue Methode präsentiert, die zusätzlich zu den gemessenen Abflusswerten die Ergebnisse der probabilistischen Hüllkurve – Abfluss und zugehöriges Wiederkehrintervall - berücksichtigt. Die Wahl fiel auf eine gemischte begrenzte Verteilungsfunktion, die neben den probabilistischen Hüllkurven auch eine absolute obere Grenze, die mit einer empirischen Hüllkurve ermittelt wurde, beinhaltet. Damit werden zwei Arten von zusätzlichen Informationen verwendet, die den oberen Bereich einer Verteilungsfunktion beschreiben. Die Integration von beiden führt zu einer verbesserten Abschätzung von Abflüssen mit Wiederkehrintervallen zwischen 100 und 1000 Jahren.

Atrial fibrillation (AF) is the most common type of cardiac arrhythmia encountered in clinical practice and is associated with an increased mortality and morbidity. Identification of the sources of AF has been a goal of researchers for over 20 years. Current treatment procedures such as Cardio version, Radio Frequency Ablation, and multiple drugs have reduced the incidence of AF. Nevertheless, the success rate of these treatments is only 35-40% of the AF patients as they have limited effect in maintaining the patient in normal sinus rhythm. The problem stems from the fact that there are no methods developed to analyze the electrical activity generated by the cardiac cells during AF and to detect the aberrant atrial tissue that triggers it. In clinical practice, the sources triggering AF are generally expected to be at one of the four pulmonary veins in the left atrium. Classifying the signals originated from four pulmonary veins in left atrium has been the mainstay of signal analysis in this thesis which ultimately leads to correctly locating the source triggering AF. Unlike many of the current researchers where they use ECG signals for AF signal analysis, we collect intra cardiac signals along with ECG signals for AF analysis. AF Signal collected from catheters placed inside the heart gives us a better understanding of AF characteristics compared to the ECG. . In recent years, mechanisms leading to AF induction have begun to be explored but the current state of research and diagnosis of AF is mainly about the inspection of 12 lead ECG, QRS subtraction methods, spectral analysis to find the fibrillation rate and limited to establishment of its presence or absence. The main goal of this thesis research is to develop methodology and algorithm for finding the source of AF. Pattern recognition techniques were used to classify the AF signals originated from the four pulmonary veins. The classification of AF signals recorded by a stationary intra-cardiac catheter was done based on dominant frequency, frequency distribution and normalized power. Principal Component Analysis was used to reduce the dimensionality and further, Linear Discriminant Analysis was used as a classification technique. An algorithm has been developed and tested during recorded periods of AF with promising results.

Η επεξεργασία του εγκεφαλογραφικού σήματος με τη χρήση νέων υπολογιστικών τεχνικών δίνει τεράστια ώθηση στη μελέτη νευροφυσιολογικών ερωτημάτων. Η χρήση αυτών των μεθόδων από ερευνητές με ελάχιστες γνώσεις προγραμματισμού απαιτεί την ανάπτυξη ενός εύχρηστου γραφικού περιβάλλοντος που να περιλαμβάνει εργαλεία για την αυτοματοποιημένη εφαρμογή των υπολογιστικών τεχνικών. Στην παρούσα εργασία παρουσιάζεται το γραφικό περιβάλλον που αναπτύχθηκε στη Μονάδα Νευροφυσιολογίας στο Εργαστήριο Φυσιολογίας της Ιατρικής Σχολής του Πανεπιστημίου Πατρών για την υποστήριξη των εγκεφαλογραφικών μελετών. Επεξηγούνται οι δυσκολίες της επεξεργασίας εγκεφαλογραφικού σήματος, οι λόγοι που καθιστούν τη χρήση ήδη υπαρχόντων εργαλείων αδύνατη ή ασύμφορη και δικαιολογείται η επιλογή της πλατφόρμας του MATLAB για την ανάπτυξη του περιβάλλοντος. Δίνεται αναλυτικά η πορεία υλοποίησης του προγράμματος και οι οδηγίες χρήσης του. Το περιβάλλον περιλαμβάνει μεθόδους για εισαγωγή δεδομένων από το πρόγραμμα καταγραφής Neuroscan, επιλογή τμημάτων για επεξεργασία, απεικονίσεις στα πεδία του χρόνου, του χώρου και της συχνότητας, εφαρμογή φίλτρων, ανάλυση προκλητών δυναμικών με παρουσίαση μέσης κυματομορφής και μέσου φασματογραφήματος, δημιουργία εικονικών καναλιών και συνεργασία με άλλα προγράμματα όπως τη χρήση της μεθόδου ανάλυσης ανεξαρτήτων συνιστωσών του EEGLAB. Παρουσιάζονται τα αποτελέσματα από τη χρήση του προγράμματος σε δυο μελέτες του εργαστηρίου. Καταρχάς, σε φυσιολογικό ύπνο για τη μελέτη της σχέσης δυο κυματομορφών του δεύτερου σταδίου του ύπνου, των συμπλεγμάτων Κ και των ατράκτων του ύπνου, όπου διαπιστώθηκε ότι η εμφάνιση του συμπλέγματος Κ επηρεάζει τη συχνότητα των ατράκτων όταν συμπίπτουν χρονικά. Έπειτα, σε παθολογικό ύπνο για τη διερεύνηση μεταβολών του θαλαμοφλοιικού κυκλώματος και των ατράκτων του ύπνου σε ένα παιδί με ιστορικό επιληψίας αφαιρέσεων παιδικής ηλικίας. Σε αυτή την περίπτωση διαπιστώθηκε η ύπαρξη ενός ρυθμού με χαρακτηριστικά παρόμοια των ατράκτων του ύπνου, αλλά σε διαφορετική συχνότητα, ενώ παράλληλα, σημαντικά μειωμένη ήταν η εμφάνιση φυσιολογικών ατράκτων. Τέλος, αναδεικνύονται τα πλεονεκτήματα της χρήσης του περιβάλλοντος και συζητείται η εκπλήρωση των στόχων και αναγκών του εργαστηρίου μέσα από το πρόγραμμα καθώς και οι πιθανές μελλοντικές επεκτάσεις. / The use of novel computational techniques in the analysis of encephalographic signals has given a huge boost to the study of neurophysiological questions. The use of such methods by researchers who have little knowledge of computer programming requires the development of a user-friendly graphical interface that includes tools for the automated application of these computational techniques. The present work presents the graphical interface developed at the Neurophysiology Unit of the University of Patras' Medical School for the support of EEG studies. The difficulties of the processing of EEG signals and the reasons that render the use of existing tools impossible or unfit are explained and I justify the choice of the MATLAB platform for the development of the environment. The course of the realization of the program and directions for its use are given in detail. The environment includes methods that import data from the Neuroscan recording system, select portions for processing, plot data over time, space and frequency, apply filters, analyze event-related potentials using average waveform and average spectrogram views, create virtual channels and cooperate with other programs, like using EEGLAB's technique of independent component analysis. The results of using the program in two laboratory studies are presented. First, it helped analyze normal sleep data, for the study of the relationship between two graphoelements of the second NREM sleep stage, the K complex and the sleep spindle. It was shown that the occurrence of a K complex affects the frequency of a spindle when they coincide. Next, in abnormal sleep data, for the study of possible changes of the thalamocortical pathway and sleep spindles on a child with medical history of childhood absence. In this case, the appearance of a rhythmic wave with attributes similar of a sleep spindle but different frequency of oscillation was shown, while at the same time, the incidence of normal spindles was significantly lower. Finally, the advantages of using this environment are shown and the fulfillment of the lab's goals and needs by the program, as well as possible future expansions, are discussed.

This thesis is about the demography of the tunicate Styela clava, a species of some notoriety because of its invasiveness and impacts in many parts of the world. Species assemblages have continuously changed throughout evolutionary history, but the rate of today’s anthropogenically facilitated dispersal is unparalleled in history. Non-indigenous species (NIS) are now considered one of the most important risks to native biodiversity. NIS become invasive by becoming both widespread and locally dominant. This requires that a species becomes established, spreads locally, and increases in abundance. In the early stages of invasion, its demography and life history characteristics are of crucial importance. In New Zealand, Styela has established populations in several places, but none of these populations has yet reached the high densities found in other countries. In Lyttelton Port, where this study was located, Styela was first noticed in 2005. It therefore presented an ideal situation to study an invasive species in its early stages of establishment and provided a potentially good model for understanding how invasive species get local traction and spread from initial infestation points. Therefore, I set out to determine demographic features of Styela to understand the numbers game of population dynamics. This study used empirical data on growth rates, size-frequencies through time, and size and age to maturity to test several models, including von Bertalanffy, Logistic dose-response, Ricker and power models of individual growth. The most useful proved to be the von Bertalanffy model. Styela individuals shrink frequently, so average growth rates were often quite low, even though some individuals reached 160 mm or more in total length. Mortality was greatest in summer, presumably after reproduction, and lowest in winter. Fewer than 5% of individuals survived 12 months, and most or all of these died soon afterwards. Populations were, therefore, essentially annual. Recruitment was difficult to determine because of the cryptic nature of small juveniles. However, size-frequency, abundance and mortality data indicated that recruitment most likely occurred in early spring (late-October), and then again in late summer, with growth to maturity (at c. 50 mm total length) within < 5 months. Several manipulative experiments showed that Styela did not readily capitalise on provision of free space but the other non-native ascidian, Ciona intestinalis, rapidly recruited. Transplants of Styela were greatly affected by C. intestinalis, which overgrew them, similar to a localised replacement of Styela by Ciona seen overseas. Lefkovitch modelling was used to test whether Styela had an “Achilles heel” in its life history, whereby managed removal could impact future populations. This showed that under several scenarios intervention would most likely be ineffectual. Overall, this study showed that the original populations in Lyttelton Port are either static or in decline, somewhat contrary to original expectations. Nevertheless, it appears that these small populations may be acting as stepping stones for spread of this species outside of the port.

In this thesis, the restorative effects of exposure to nature are examined through the lens of existing restoration theories. Limitations of existing theories, such as Attention Restoration Theory and Psycho-evolutionary Restoration Theory, are highlighted. To address the limitations of existing theories, an expanded theoretical framework is proposed: The expanded framework introduces a newly proposed neural mechanism and theory of restoration that build on existing theories by proposing a link to recently discovered reward systems in the ventral visual pathway. Results from six experiments provide consistent evidence to suggest that positive and negative responses to visual scenes are related to the low-level visuospatial properties of the scenes. Specifically, a discovery is made to suggest that the power of a limited visual spatial frequency range can consistently predict responses to natural, urban, and abstract scenes on measures of restoration (blink-rates, number of fixations, self-reported stress and pleasantness). This provides the first evidence to suggest that low-level visual properties of scenes may play an important role in affective and physiological responses to scenes. Furthermore, this newly discovered relationship provides a new way to objectively predict the relative restorative value of any given scene.

The problem studied in this thesis, is the classification of the small-scale aircraft targets by using a natural resonance based electromagnetic feature extraction technique. The aircraft targets are modeled by perfectly conducting, thin wire structures. The electromagnetic back-scattered data used in the classification process, are numerically generated for five aircraft models. A contemporary signal processing tool, the Wigner-Ville distribution is employed in this study in addition to using the principal components analysis technique to extract target features mainly from late-time target responses. The Wigner-Ville distribution (WD) is applied to the electromagnetic back-scattered responses from different aspects. Then, feature vectors are extracted from suitably chosen late-time portions of the WD outputs, which include natural resonance related v information, for every target and aspect to decrease aspect dependency. The database of the classifier is constructed by the feature vectors extracted at only a few reference aspects. Principal components analysis is also used to fuse the feature vectors and/or late-time aircraft responses extracted from reference aspects of a given target into a single characteristic feature vector of that target to further reduce aspect dependency. Consequently, an almost aspect independent classifier is designed for small-scale aircraft targets reaching high correct classification rate.