ABSTRACT Assessing the impact of herbivory on plant growth and reproduction is important to predict the success of biocontrol of invasive plants. Leaf area production is most important, as photosynthesis provides the foundation for all plant growth and fitness. High levels of defoliation generally reduce the productivity of plants. However, leaf area production fluctuates during the season and compensational growth may occur, which both complicate accurate estimations of defoliation impacts. Under field conditions the interaction with neighbouring species and the availability of soil nutrients need to be assessed in order to gauge long term effects of weed invasions on natural environments. In this thesis I have investigated seasonal leaf area dynamics in Buddleia davidii following repeated artificial defoliation, to quantify compensational leaf production and to understand the regulatory mechanisms involved. The impact of defoliation on photosynthesis, seed production, germination and nitrogen translocation patterns were analysed. Finally, possible facilitation between B. davidii and a native nitrogen fixer, Coriaria arborea, and the impact of B. davidii on soil nutrient availability were investigated. In defoliated B. davidii, increased node production (34%), leaf size (35%) and leaf longevity (12%) resulted in 52% greater total emergent leaf area in the short term. However, with time and diminishing tissue resources the compensation declined. No upregulation of photosynthesis was observed in pre-existing leaves. Compensational leaf area production occurred at the expense of reproduction but the germination capacity of individual seeds was unaffected. In B. davidii, nitrogen reserves are stored in old leaves. Thus, the defoliation-induced decline in tissue reserves led to changes in the remobilisation pattern and increased the importance of soil uptake but biomass production especially that of roots had declined significantly (39%). Slight facilitation effects from the neighbouring nitrogen fixer and VA-mycorrhizae were observed on B. davidii in the field, while its impact on soil chemistry during spring was negligible. Defoliation of B. davidii resulted in priority allocation of resources to compensational leaf growth and a concomitant reduction in flower and seed production. The compensational leaf production greatly increased the demand for nitrogen, while continued leaf removal decreased the pool of stored nitrogen. This led to changes in nitrogen remobilisation and an increased importance of root uptake. However, the significant decline in root growth will likely impair adequate nutrient uptake from the soil, which is especially important where B. davidii invades nutrient poor habitats and will increase the success of biocontrol of the species. While mycorrhizae increase nutrient accessibility for B. davidii, it is likely that the additional stress of defoliation will negate the small facilitative effects from nitrogen-fixing species like C. arborea. This research provides new insights into the mechanisms regulating leaf area dynamics at the shoot level and systemic physiological responses to defoliation in plants, such as nitrogen translocation. The compensation in leaf area production was considerable but only transitory and thus, the opportunity to alleviate effects of leaf loss though adjustment of light capture limited. However, to ascertain that photosynthesis at whole plant level does not increase after defoliation, more detailed measurements especially on new grown leaves are necessary. In general, defoliation had greatly reduced plant growth and performance so that an optimistic outlook for controlling this species can be given. Conclusions about the wider impacts of B. davidii on soil chemistry and community function will require further research.

V této práci se zabýváme metodami pro regresní analýzu výskytu opako- vaných událostí, při které je třeba se vypořádat se závislostí čas· do události v rámci jednoho subjektu. V první části práce se zabýváme možným rozšířením Coxova modelu proporcionálního rizika, který se využívá při analýze cenzoro- vaných dat, pro analýzu výskytu opakovaných událostí. Hlavní část práce je věnována odhadu parametr· v marginálních modelech a jejich asymptotickým vlastnostem. Následně se zabýváme i odhadem parametr· v marginálních mo- delech pro mnohorozměrná cenzorovaná data. Vhodnost použití marginálních model· je zkoumána pomocí simulací. 1

Survival analysis is an effective tool for conservation studies, since it measure the risk of an event that is important for the survival of populations and preservation of biodiversity. In this thesis three different models for survival analysis are used to estimate the age at breeding between two genetically different populations of brown trout. These populations are an evolutionary enigma, since they apparently coexist in direct competition with each other, which according to ecological theory should not happen. Thus it is of interest if differences between them can be identified. The data consists of brown trouts and has been collected over 20 years. The models are the Cox Proportional Hazards model, the Complementary Log-Log Link model and the Log Logistic Accelerated Failure-Time model. The Cox model were estimated in three different ways due to the nonproportional hazards in the estimates of time to breeding, which gave different interpretations of the same model. All of the models agree that the population B breed at younger ages than the population A, which suggests that the two populations have different reproductive strategies.

Change-point detection in hazard rate function is an important research topic in survival analysis. In this dissertation, we firstly review existing methods for single change-point detection in piecewise exponential hazard model. Then we consider the problem of estimating the change point in the presence of right censoring and long-term survivors while using Kaplan-Meier estimator for the susceptible proportion. The maximum likelihood estimators are shown to be consistent. Taking one step further, we propose an counting process based and least squares based change-point detection algorithm. For single change-point case, consistency results are obtained. We then consider the detection of multiple change-points in the presence of long-term survivors via maximum likelihood based and counting process based method. Last but not least, we use a weighted least squares based and counting process based method for detection of multiple change-points with long-term survivors and covariates. For multiple change-points detection, simulation studies show good performances of our estimators under various parameters settings for both methods. All methods are applied to real data analyses. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection

Les véhicules automobiles autonomes sont des systèmes critiques. En effet, suite à leurs défaillances, ils peuvent provoquer des dégâts catastrophiques sur l'humain et sur l'environnement dans lequel ils opèrent. Le contrôle des véhicules autonomes robotisés est une fonction complexe, qui comporte de très nombreux modes de défaillances potentiels. Dans le cas de plateformes expérimentales qui n'ont suivi ni les méthodes de développement ni le cycle de certification requis pour les systèmes industriels, les probabilités de défaillances sont beaucoup plus importantes. En effet, ces véhicules expérimentaux se heurtent à deux problèmes qui entravent leur sûreté de fonctionnement, c'est-à-dire la confiance justifiée que l'on peut avoir dans leur comportement correct. Tout d'abord, ils sont utilisés dans des environnements ouverts, au contexte d'exécution très large. Ceci rend leur validation très complexe, puisque de nombreuses heures de test seraient nécessaires, sans garantie que toutes les fautes du système soient détectées puis corrigées. De plus, leur comportement est souvent très difficile à prédire ou à modéliser. Cela peut être dû à l'utilisation des logiciels d'intelligence artificielle pour résoudre des problèmes complexes comme la navigation ou la perception, mais aussi à la multiplicité de systèmes ou composants interagissant et compliquant le comportement du système final, par exemple en générant des comportements émergents. Une technique permettant d'augmenter la sécurité-innocuité (safety) de ces systèmes autonomes est la mise en place d'un composant indépendant de sécurité, appelé « Safety-Bag ». Ce système est intégré entre l'application de contrôle-commande et les actionneurs du véhicule, ce qui lui permet de vérifier en ligne un ensemble de nécessités de sécurité, qui sont des propriétés nécessaires pour assurer la sécurité-innocuité du système. Chaque nécessité de sécurité est composée d'une condition de déclenchement et d'une intervention de sécurité appliquée quand la condition de déclenchement est violée. Cette intervention consiste soit en une inhibition de sécurité qui empêche le système d'évoluer vers un état à risques, soit en une action de sécurité afin de remettre le véhicule autonome dans un état sûr. La définition des nécessités de sécurité doit suivre une méthode rigoureuse pour être systématique. Pour ce faire, nous avons réalisé dans nos travaux une étude de sûreté de fonctionnement basée sur deux méthodes de prévision des fautes : AMDEC (Analyse des Modes de Défaillances, leurs Effets et leur Criticité) et HazOp-UML (Etude de dangers et d'opérabilité) qui mettent l'accent respectivement sur les composants internes matériels et logiciels du système et sur l'environnement routier et le processus de conduite. Le résultat de ces analyses de risques est un ensemble d'exigences de sécurité. Une partie de ces exigences de sécurité peut être traduite en nécessités de sécurité implémentables et vérifiables par le Safety-Bag. D'autres ne le peuvent pas pour que le système Safety-Bag reste un composant relativement simple et validable. Ensuite, nous avons effectué des expérimentations basées sur l'injection de fautes afin de valider certaines nécessités de sécurité et évaluer le comportement de notre Safety-Bag. Ces expériences ont été faites sur notre véhicule robotisé de type Fluence dans notre laboratoire dans deux cadres différents, sur la piste réelle SEVILLE dans un premier temps et ensuite sur la piste virtuelle simulée par le logiciel Scanner Studio sur le banc VILAD. Le Safety-Bag reste une solution prometteuse mais partielle pour des véhicules autonomes industriels. Par contre, il répond à l'essentiel des besoins pour assurer la sécurité-innocuité des véhicules autonomes expérimentaux. / Autonomous automotive vehicles are critical systems. Indeed, following their failures, they can cause catastrophic damage to the human and the environment in which they operate. The control of autonomous vehicles is a complex function, with many potential failure modes. In the case of experimental platforms that have not followed either the development methods or the certification cycle required for industrial systems, the probabilities of failure are much greater. Indeed, these experimental vehicles face two problems that impede their dependability, which is the justified confidence that can be had in their correct behavior. First, they are used in open environment, with a very wide execution context. This makes their validation very complex, since many hours of testing would be necessary, with no guarantee that all faults in the system are detected and corrected. In addition, their behavior is often very difficult to predict or model. This may be due to the use of artificial intelligence software to solve complex problems such as navigation or perception, but also to the multiplicity of systems or components interacting and complicating the behavior of the final system, for example by generating behaviors emerging. A technique to increase the safety of these autonomous systems is the establishment of an Independent Safety Component, called "Safety-Bag". This system is integrated between the control application and the actuators of the vehicle, which allows it to check online a set of safety necessities, which are necessary properties to ensure the safety of the system. Each safety necessity is composed of a safety trigger condition and a safety intervention applied when the safety trigger condition is violated. This intervention consists of either a safety inhibition that prevents the system from moving to a risk state, or a safety action to return the autonomous vehicle to a safe state. The definition of safety necessities must follow a rigorous method to be systematic. To do this, we carried out in our work a study of dependability based on two fault prevention methods: FMEA and HazOp-UML, that respectively focus on the internal hardware and software components of the system and on the road environment and driving process. The result of these risk analyzes is a set of safety requirements. Some of these safety requirements can be translated into safety necessities, implementable and verifiable by the Safety-Bag. Others cannot be implemented in the Safety-Bag. The latter must remain simple so that it is easy to be validated. Then, we carried out experiments based on the faults injection in order to validate some safety necessities and to evaluate the Safety-Bag's behavior. These experiments were done on our robotic vehicle type Fluence in our laboratory in two different settings, on the actual track SEVILLE at first and then on the virtual track simulated by the Scanner Studio software on the VILAD testbed. The Safety-Bag remains a promising but partial solution for autonomous industrial vehicles. On the other hand, it meets the essential needs for the safety of experimental autonomous vehicles.

在探討願付價格的條件評估法中一種常被使用的方法為“雙界二分選擇法”，並且一個隱含的假設是，所有研究對象皆願意支付一個合理的金額。然而對於某些商品，有些人也許願意支付任何金額；相對的，有些人可能不願意支付任何金額。分析願付價格時若不考慮這兩類極端反應者，則可能會得到一個偏誤的願付價格。本篇研究中，我們提出一個“混合模型”來處理此議題，其中以多元邏輯斯迴歸模型來描述不同反應者的比例，並以加速失敗時間模型來估計願意支付合理金額者其願付價格的分布。此外，我們以關於治療高血壓新藥之願付價格實例，作為實證分析。 / One commonly used method in contingent valuation (CV) survey for WTP (willingness-to-pay) is the “double-bound dichotomous choice approach” and an implicit assumption is that all study subjects are willing to pay a reasonable price. However, for certain goods, some subjects may be willing to pay any price for them, while some others may be unwilling to pay any price. Without considering these two types of the extreme respondents, a wrongly estimated WTP value will be obtained. We propose a “mixture model” to handle the issues in this study, in which a multinomial logistic model is taken to specify the proportions of different respondents and an accelerated failure time model is utilized to describe the distribution of WTP price for subjects who are willing to pay a reasonable price. In addition, an empirical example on WTP prices for a new hypertension treatment is provided to illustrate the proposed methods.

Made available in DSpace on 2014-12-17T15:26:38Z (GMT). No. of bitstreams: 1 Patricia Borchardt Santos.pdf: 378137 bytes, checksum: e27ccc5c056aa17d7bd2ca2c8b64458f (MD5) Previous issue date: 2009-12-01 / We presented in this work two methods of estimation for accelerated failure time models with random e_ects to process grouped survival data. The _rst method, which is implemented in software SAS, by NLMIXED procedure, uses an adapted Gauss-Hermite quadrature to determine marginalized likelihood. The second method, implemented in the free software R, is based on the method of penalized likelihood to estimate the parameters of the model. In the _rst case we describe the main theoretical aspects and, in the second, we briey presented the approach adopted with a simulation study to investigate the performance of the method. We realized implement the models using actual data on the time of operation of oil wells from the Potiguar Basin (RN / CE). / Apresentamos neste trabalho dois m?todos de estima??o para modelos de tempo de falha acelerado com efeito aleat?rio para tratar de dados de sobreviv?ncia correlacionados. O primeiro m?todo, que est? implementado no software SAS, atrav?s do procedimento NLMIXED, utiliza a quadratura Gauss-Hermite adaptada para obter a verossimilhan?a marginalizada. O segundo m?todo, implementado no software livre R, est? baseado no m?todo da verossimilhan?a penalizada para estimar os par?metros do modelo. No primeiro caso descrevemos os principais aspectos te?ricos e, no segundo, apresentamos brevemente a abordagem adotada juntamente com um estudo de simula??o para investigar a performance do m?todo. Realizamos uma aplica??o dos modelos usando dados reais sobre o tempo de funcionamento de po?os petrol?feros da Bacia Potiguar (RN/CE).

MSc (Statistics) / Department of Statistics / Selection of variables is vital in high dimensional statistical modelling as it aims to identify the right subset model. However, variable selection for discrete survival analysis poses many challenges due to a complicated data structure. Survival data might have unobserved heterogeneity leading to biased estimates when not taken into account. Conventional variable selection methods have stability problems. A simulation approach was used to assess and compare the performance of Least Absolute Shrinkage and Selection Operator (Lasso) and gradient boosting on discrete survival data. Parameter related mean squared errors (MSEs) and false positive rates suggest Lasso performs better than gradient boosting. Frailty models outperform discrete survival models that do not account for unobserved heterogeneity. The two methods were also applied on Zimbabwe Demographic Health Survey (ZDHS) 2016 data on age at first marriage and did not select exactly the same variables. Gradient boosting retained more variables into the model. Place of residence, highest educational level attained and age cohort are the major influential factors of age at first marriage in Zimbabwe based on Lasso. / NRF

Major disasters such as wildfire, tornado, hurricane, tropical storm, flooding cause disruptions in infrastructure systems such as power outage, disruption to water supply system, wastewater management, telecommunication failures, and transportation facilities. Disruptions in electricity infrastructures have negative impacts on sectors throughout a region, including education, medical services, financial, and recreation sectors. In this study, we introduce a novel approach to investigate the factors which can be associated with longer restoration time of power service after a hurricane. Considering restoration time as the dependent variable and utilizing a comprehensive set of county-level data, we have estimated a Generalized Accelerated Failure Time (GAFT) model that accounts for spatial dependence among observations for time to event data. The model fit improved by 12% after considering the effects of spatial correlation in time to event data. Using GAFT model and Hurricane Irma's impact on Florida as a case study, we examined: (1) differences in electric power outages and restoration rates among different types of power companies: investor-owned power companies, rural and municipal cooperatives; (2) the relationship between the duration of power outage and power system variables; (3) the relationship between the duration of power outage and socioeconomic attributes. The findings of this study indicate that counties with a higher percentage of customers served by investor-owned electric companies and lower median household income, faced power outage for a longer time. This paper identifies the key factors to predict restoration time of hurricane-induced power outages, allowing disaster management agencies to adopt strategies required for restoration process.

為了處理在願付價格的研究中，極端受訪者對於估計結果所造成的誤差。本文沿用Tsai(2005)所建議採用的三要素混合模型，將受訪者區分為價格再高都願意支付、願意支付合理價格以及價格再低都不願意支付等三種類型。在評估願付價格時，以加速失敗模型(accelerated failure time model，簡稱AFT model)針對願意支付合理價格的受訪者進行估計，並且在考慮不同起價點可能會造成不同程度的起價點偏誤(starting point bias)或是定錨效果(anchoring effect)的情形下，提出一個起價點偏誤調整模型來做探討。我們並以CVDFACTS中的高血壓之願付價格資料進行實證分析。分析結果發現，教育程度越高的男性對於能降低高血壓病患罹患心臟血管相關疾病之新藥願意付較高的金額。此外我們也發現在此筆資料中，不同起價點確實會造成不同程度的偏誤，經由偏誤調整後會得到較高的願付金額。 / A study of willingness-to-pay often suffers from the bias introduced by extreme respondents who are willing to or not willing to pay any price. To overcome the problem, a three-component model proposed by Tsai (2005) is adopted. Under such a circumstance, respondents are classified into three categories, i.e. respondents who are willing to pay any price, unwilling to pay any price, or willing to pay a reasonable price. The willingness-to-pay for those subjects who are willing to pay a reasonable price is again modeled by an accelerated failure time model (AFT model). In this study, we, however, propose an unified model that allows us to look into the issue related to starting point bias and anchoring effect, simultaneously. Willingness-to-pay for cardiovascular disease treatment from a longitudinal follow-up survey- CVDFACTS, is investigated using the new model. Through the use of the model, we are able to detect the effects of starting point biases, and make a proper adjustment accordingly. Our analysis indicates that male respondents with higher education level have an inclination to pay higher price for the new treatment. Besides, we also discover that starting point bias does exist in this dataset.