In this dissertation, we are interested in studying processes which generate events repeatedly over the follow-up time of a given subject. Such processes are called recurrent event processes and the data they provide are referred to as recurrent event data. Examples include the cancer recurrences, recurrent infections or disease episodes, hospital readmissions, the filing of warranty claims, and insurance claims for policy holders. In particular, we focus on the multi-type recurrent event times which usually arise when two or more different kinds of events may occur repeatedly over a period of observation. Our main objectives are to describe features of each marginal process simultaneously and study the dependence among different types of events. We present applications to a real dataset collected from the Nutritional Prevention of Cancer Trial. The objective of the clinical trial was to evaluate the efficacy of Selenium in preventing the recurrence of several types of skin cancer among 1312 residents of the Eastern United States. Four chapters are involved in this dissertation. Chapter 1 introduces a brief background to the statistical techniques used to develop the proposed methodology. We cover some concepts and useful functions related to survival data analysis and present a short introduction to frailty distributions. The Monte Carlo expectation maximization (MCEM) algorithm and copula functions for the multivariate variables are also presented in this chapter. Chapter 2 develops a multi-type recurrent events model with multivariate Gaussian random effects (frailties) for the intensity functions. In this chapter, we present nonparametric baseline intensity functions and a multivariate Gaussian distribution for the multivariate correlated random effects. An MCEM algorithm with MCMC routines in the E-step is adopted for the partial likelihood to estimate model parameters. Equations for the variances of the estimates are derived and variances of estimates are computed by Louis' formula. Predictions of the individual random effects are obtained because in some applications the magnitude of the random effects is of interest for a better understanding and interpretation of the variability in the data. The performance of the proposed methodology is evaluated by simulation studies, and the developed model is applied to the skin cancer dataset. Chapter 3 presents copula-based semiparametric multivariate frailty models for multi-type recurrent event data with applications to the skin cancer data. In this chapter, we generalize the multivariate Gaussian assumption of the frailty terms and allow the frailty distributions to have more features than the symmetric, unimodal properties of the Gaussian density. More flexible approaches to modeling the correlated frailty, referred to as copula functions, are introduced. Copula functions provide tremendous flexibility especially in allowing taking the advantages of a variety of choices for the marginal distributions and correlation structures. Semiparametric intensity models for multi-type recurrent events based on a combination of the MCEM with MCMC sampling methods and copula functions are introduced. The combination of the MCEM approach and copula function is flexible and is a generally applicable approach for obtaining inferences of the unknown parameters for high dimension frailty models. Estimation procedures for fixed effects, nonparametric baseline intensity functions, copula parameters, and predictions for the subject-specific multivariate frailties and random effects are obtained. Louis' formula for variance estimates are derived and calculated. We investigate the impact of the specification of the frailty and random effect models on the inference of covariate effects, cumulative baseline intensity functions, prediction of random effects and frailties, and the estimation of the variance-covariance components. Performances of proposed models are evaluated by simulation studies. Applications are illustrated through the dataset collected from the clinical trial of patients with skin cancer. Conclusions and some remarks for future work are presented in Chapter 4. / Ph. D.

The electrification of societies and the decarbonisation of electricity production are changing energy systems worldwide. A fast transition towards the replacement of fossil fuels by intermittent renewable energy sources is expected in the next decades to combat climate change. A significant share of the produced electricity is likely to be generated from offshore wind farms, due to the abundant wind resources in the offshore regions and the lack of available onshore sites. However, increased electricity dependence in combination with expanded offshore wind power generation introduce new vulnerabilities to the society. Specifically, the effects of high impact low probability (HILP) events are considered as potential threats to the power system, not least because of the increasing number of extreme weather events. Therefore, research on power grid vulnerability and power system resilience to HILP events are of significant interest. This thesis presents results of studies investigating power grid vulnerability from a topological perspective, and resilience to storm conditions of power systems with varying dependencies on offshore wind. To achieve this, methods based on complex network theory and AC power flow analysis have been developed, tested, and evaluated. Further, geospatial wind data from historical extreme storm events have been used to generate realistic power production profiles from hypothetical offshore wind farms. The results strengthen that complex network concepts can be used successfully in the context of power grid vulnerability analysis. Further, the results show that the resilience of power systems with large dependencies on offshore wind differ vastly depending on the grid properties and control strategies, which are further discussed in this thesis.

A review of the literature on adjustment to widowhood and survivorship reveals gaps in qualitative and quantitative studies which explore anticipatory processes for this expectable life event. Studies focusing on men anticipating this time of life are rare to non-existent. This is a qualitative study on the anticipatory processes (cognitive, emotional and behavioral) of individuals and couples. The theoretical underpinnings for the study are drawn from symbolic interactionist ideas of how individuals settle on a personal and functional reality and from the ideas of Peter Berger and his associates on how the marital conversation stabilizes the individual's sense of the world. Fourteen long-married couples ages 50 to 80 were interviewed. They are Caucasian, middle and upper-middle class people, married from 29 to 49 years. The first part of the study examines the following: whether people have a prediction relative to which of the couple will probably die first; whether members of the couple hold the same prediction; what factors inform such a prediction, and how much discussion there is of this topic. It was found that about one-half of the informants have a stable prediction and that three couples held the same view. Three typologies, the CLEARS, those IN PROCESS and the VAGUES, were used to describe the prediction behavior of the 28 participants. Among the seven factors highlighted were the sense of one's genetic inheritance, belief in the “common wisdom" that husbands pre-decease their wives, and observations of one's own energy level relative to one's partner. The second part of the study explores the worries and concerns of men and women as they look forward to a time without the life partner. The study uncovers the actions they take at present and actions they believe they would take in the future to best perform daily routines and to deal with emotional and relationship needs. It was found that the men and women envision their futures differently, that men anticipate the likelihood of remarriage and tend to see remarriage as a pleasant coping strategy. Women show a disinclination to remarry emphasizing the trade-offs of marriage. Their strategies are more varied, and are more likely to be based on observations of widowed women throughout their lives. Finally, the participants' religious and philosophical attitudes, broad enough to encompass death and loneliness, are noted. / Ph. D.

No / Despite advances in technology and medicine, death itself remains an immutable certainty. Indeed, the acceptance and understanding of our mortality are among the enduring metaphysical challenges that have confronted human beings from the beginning of time. How have we sought to cope with the inevitability of our mortality? How do various cultural and social representations of mortality shape and influence the way in which we understand and approach death? To what extent do personal beliefs and convictions about the meaning of life or the notion of an afterlife affect how we perceive and experience the process of death and dying? Steve Paulson, executive producer and host of To the Best of Our Knowledge, moderated a discussion on death, dying, and what lies beyond that included psychologist Lani Leary, professor of philosophy and religion Jeffrey J. Kripal, and sociologist Allan Kellehear. The following is an edited transcript of the discussion that occurred February 5, 7:00-8:30 pm, at the New York Academy of Sciences in New York City.

Denna studie syftar till att undersöka hur svenska destinationsbolag arbetar med strategier för att hantera säsongsvariationer. Studien grundar sig i tre olika strategier; evenemangsstrategier, samarbetsstrategier och marknadsföringsstrategier. Dessa strategier har setts som kompletterande till varandra och en egen modell har utformats med dessa som utgångspunkt. Materialet har samlats in genom sju semistrukturerade intervjuer med svenska destinationsbolag i södra och norra Sverige. Informanterna behövde erhålla kunskaper inom deras arbete med strategier inom exempelvis destinationsutveckling, evenemang, säsongsvariationer eller marknadsföring. Studiens modell har därefter tillämpats som ett instrument för att analysera resultatet. Resultatet visar att svenska destinationsbolag arbetar med evenemangsstrategier, samarbetsstrategier och marknadsföringsstrategier. Denna studie lyfter att evenemangs- och marknadsföringsstrategier är de mest framträdande strategierna under lågsäsong. Denna studie är skriven på svenska. / This study aims to investigate how Swedish destination companies work with strategies to manage seasonal variations. The study is based on three different strategies; event strategies, collaboration strategies and marketing strategies. These strategies have been seen as complementary to each other and a separate model has been designed with these as a starting point. The material has been collected through seven semi-structured interviews with Swedish destination companies in southern and northern Sweden. The informants needed to acquire knowledge in their work with strategies in areas such as destination development, events, seasonal variations or marketing. The study’s model has then been applied as an instrument to analyze the results. The result shows that Swedish destination companies work with event strategies, cooperation strategies and marketing strategies. This study highlights that event and marketing strategies are the most prominent strategies during the off-season. This study is written in Swedish

This thesis investigates the circumstances under which parties change their positions, with Swedish nuclear power policy as a case to adress the purpose. The thesis employed qualitative text analysis and the theoretical framework Advocacy Coalition Framework (ACF) to examine and adress the the thesis's research questions and purpose. ACF was used to formulate the research questions, focusing on wether there had been changes in the Swedish parliamentary parties' policy core belifes regardning nuclear power policy and, if so, wether external subsystem events and or\changes in coalition formation could explain these changes. The study found that three out of eight Swedish parliamentary parties had changed their policy core belifes regarding the nuclear power issue:the Social Democrats, the Green Party, and the Center party.  At least one of the examined external subsystem events could either explain the changes or reinforce previous changes. Furthermore, the sudy showed that changes in coalition formation could potentially explain the Social Democrats' and the Green Party's altered policy core belifes. Other potential explanations included the influence of the Janaury Agreement, where the Liberals, as a strongly pro-nuclear party, may have influenced the Green party and the Social Democrats to become more positive towards nuclear power. In summary, the sudy demonstrated that changes in coalition formation and\or external subsystem evenets are circumstances that can explain why parties change their positions. Additionally, the thesis suggested that ACF should include two additional external subsystem events, which this sudy has shown to have an impact on parties' changed policy core belifes:war and economic changes.

The case of the National Liberation Army (NLA) in Macedonia, taking up arms against the state in 2001, is a largely underrepresented in the literature. Thus, basing this study on the theory of contingent events and a relational perspective, the purpose of this study is to examine the processes and motives behind individuals joining the National Liberation Army in Macedonia. This was done by conducting semi-structured interviews with former rebels and combatants from Macedonia and analysing the material qualitatively, using the constant comparative method through the lens of the theory. The study of civil wars and rebel participation and mobilisation have long been dominated by quantitative studies and rational choice theory, which is why this study instead is qualitative in nature and based on the personal and individual perspectives of former combatants. I found that the main reasoning behind joining the NLA was to increase the rights for Albanians in Macedonia. Further, rebel participation, as well as the development of the motives behind it, were the result of a process of experiencing discrimination and contingent events. The eruption of violence can be contributed to the relationship and interactions between the Albanians experiencing discrimination and the Macedonian state, having acted as an oppressor. Thus, the results include not only understanding why individuals joined the NLA, but also how.

The intensity and frequency of precipitation events have increased because of global warming and its direct impact on the hydrological cycle. This poses a significant challenge for various locations around the globe where in recent years more unpredicted flooding has been observed. The utilization of hydrological models for accurate prediction of urban floods under heavy rainfall events is crucial to deal with such global problems. The purpose of this study is to develop a model based on the Spatial Distributed Travel Time (SDTT) approach that estimates the response of watersheds to a short and intense rainfall event in urban settings. The model is developed in Python and uses the ArcPy package, which allows access to all the geoprocessing tools available at ArcGIS, along with the Numpy package that supports matrices which makes mathematical calculation efficient.   One of the important factors affecting the response of watersheds is the contribution of upstream flow. The current study used Dynamic Upstream Contribution (DUC) to estimate the unit hydrograph and consider the effect of upstream runoff contributing to travel time equations using physical characteristics and the dynamic of rainfall events. The SDTT model was validated with a fully distributed model, MIKE 21, and showed that when the infiltration module estimates the total runoff volume accurately, the unit hydrograph of the DUC method can predict the peak almost as accurately as MIKE 21. Before validation, the excess rainfall estimated in the SDTT model is multiplied by a constant coefficient to align the total water volume of the model with that of the MIKE 21 model.  The peak flow is the most important component of a discharge hydrograph since its accurate prediction helps in assessing the severity of flooding and the capacity of drainage systems to handle the excess water. Another component of a discharge hydrograph is time to peak which the SDTT model predicts with a delay compared to MIKE 21. The sensitivity analysis showed the simplification regarding the dynamic of rainfall intensity used in travel time equations contributes to this delayed peak. The other simplification that might impact the watershed response is the approach the model used to handle depression volume which is too general. A conceptual method proposed in this report can be used in future studies to improve this part of the model by capturing the spatial distribution of depression locations as well as the temporal dynamics of charging the depressions.   After the model was validated in the first study area, it was implemented in another study area to evaluate the effect of urban development on the hydrological response of urban catchments to a short and intense rainfall event. This scenario-based analysis showed that by further development of the model, it can be used as a tool for the initial phase of hydrologic investigation of urban areas in response to heavy rainfall events. By conducting the screening phase of hydrological investigation and filtering the risky location, the SDTT model can be used as a complementary model for more advanced fully distributed models that are more computationally extensive.   The recorded simulation time demonstrated that the SDTT model is quick when it comes to small-sized watersheds, but it is less time-efficient for large catchments. An approach proposed in this report can be utilized to optimize the model's processing time for larger catchments. By making the model time efficient and addressing the issues mentioned in the report, the developed SDTT model can facilitate the hydrological investigation by reducing the initial data gathering burden and simulation time, and making the assessments of urban watersheds more efficient can facilitate informed decision-making in urban flood risk management. / Till följd av den globala uppvärmningen har intensiteten och frekvensen av nederbördshändelser ökat, en direkt inverkan på den hydrologiska cykeln som utgör en betydande utmaning för olika platser runt om i världen där oförutsedda översvämningar observerats under de senaste åren. Användningen av hydrologiska modeller för att med noggrannhet förutseurbana översvämningar under kraftiga nederbördshändelser är avgörande för att hantera detta globala problem. Syftet med denna studie är att utveckla en modell baserad på Spatial Distributed Travel Time (SDTT) metodiken. SDTT-metodiken beskriver responsen från ett avrinningsområde för en kort och intensiv nederbördshändelse i urban miljö. Modellen är utvecklad i Python och inkluderar ArcPy-paketet som ger tillgång till alla geoprocesseringsverktyg som finns i ArcGIS tillsammans med Numpy-paketet som stödjer matriser som effektiviserar matematiska beräkningar.  En av de avgörande faktorerna som visade sig påverka reaktionen från ett avrinningsområde var flödet från uppströmsområdet. Den aktuella studien använde Dynamic Upstream Contribution (DUC) för att uppskatta enhetshydrografen med hänsyn till effekten avrinningen uppströms har på avrinningshastigheten med hjälp av fysiska egenskaper och nederbördsdynamik. SDTT-modellen validerades med en fullt distribuerad modell, MIKE 21, och visade att när infiltrationsmodulen uppskattar den totala avrinningsvolymen exakt, kan enhetshydrografen för DUC-metoden förutsäga toppflödet exakt. Innan validering multipliceras överskottsnederbörden uppskattad i SDTT-modellen med en konstant koefficient för att justera modellens totala vattenvolym med den i MIKE 21-modellen. Toppflödet är den viktigaste komponenten i en flödeshydrograf eftersom dess noggranna förutsägelse hjälper till att bedöma allvarsgraden av översvämningar samt dräneringssystemens kapacitet att hantera överskottsvatten. En annan komponent i en flödeshydrograf är den tid det tar tills toppflödet uppstår, något som SDTT-modellen förutsäger med en fördröjning jämfört med MIKE 21. Känslighetsanalysen visade att förenklingen gällande dynamiken för nederbördsintensitet som används i ekvationerna för avrinningshastighet bidrar till denna fördröjda topp. Den andra förenklingen som kan påverka responsen från avrinningsområdet är metoden som modellen använde för att hantera volymen vatten som lagras i sänkor, som är förgenerell. En konceptuell metod föreslås i denna rapport och kan användas i framtida studier för att förbättra denna del av modellen genom att fånga den rumsliga fördelningen av sänkor samt tidsaspekten i att fylla upp sänkvolymerna.   Efter att modellen validerats i det första studieområdet, implementerades den i ett annat studieområde för att utvärdera kopplingen mellan stadsutveckling och hydrologisk respons i urbana avrinningsområden i kontexten av en kort och intensiv nederbördshändelse. Denna scenariobaserade analys visade att modellen efter vidareutveckling kan användas som ett verktyg för den inledande fasen av hydrologisk undersökning av stadsområden, i syfte att utreda möjliga konsekvenser av kraftiga nederbördshändelser. Genom att genomföra screeningfasen av hydrologisk undersökning och filtrera den mest riskfyllda platsen kan SDTT-modellen användas som en kompletterande modell för mer avancerade fullt distribuerade modeller som är mer beräkningsmässigt omfattande.   Den registrerade simuleringstiden visade att SDTT-modellen är snabb när det kommer till ett litet avrinningsområde, men modellen är mindre tidseffektiv för stora avrinningsområden. Ett tillvägagångssätt som föreslås i denna rapport kan användas för att optimera modellens handläggningstid för större avrinningsområden. Genom att göra modellen tidseffektiv och åtgärda frågorna som nämns i rapporten, kan den utvecklade SDTT-modellen underlätta den hydrologiska undersökningen genom att minska den inledande datainsamlingsbördan, minskasimuleringstiden, och dessutom göra utvärderingarna av urbana avrinningsområden mer effektiva. Slutligen kan modellens resultat användas för att underlätta informerat beslutsfattande kopplat till hantering av översvämningsrisker i städer.

<p dir="ltr">The escalating threat of flooding due to climate change, urbanization, and population growth calls for accurate flood estimation, especially as annual flood losses are projected to reach up to $52 billion by 2050. However, factors like changing precipitation patterns, watershed changes, and model uncertainties complicate future flood estimation. Rising global temperatures not only intensify extreme storms but also alter their spatial and temporal characteristics, yet these changes remain poorly understood across different climate regions, hindering effective hydrological response planning. This study investigates how climate change affects storm spatio-temporal patterns and probable maximum precipitation (PMP) estimates, pinpointing regions most vulnerable to these shifts. The specific three objectives of this study are 1) to understand how the spatial extent of short duration precipitation extreme changes across the globe particularly in response to climate variables like temperature 2) to understand and quantify the changes in combined spatio-temporal characteristics of extreme storms in response to rising temperatures; and 3) to evaluate changes in probable maximum precipitation (PMP) estimates in response to climate change, specifically identifying critical infrastructure—such as dams and nuclear facilities—that may be at increased risk.</p><p dir="ltr">In the first objective, a novel grid-based metric called the Spatial Homogeneity (SH) metric is developed to assess the changes in spatial extent of extreme storms of different intensity and across different regions. The study finds that rising temperature results in smaller size extreme storms in the tropics, but larger size storms in the arid regions. It is also found that more intense precipitation events have a smaller spatial extent. Furthermore, larger spatial extent storms were found to be associated with higher total precipitable water, while overall cold vs warm year or overall year around wetness vs dryness of a region had limited impact on the spatial extent of these extreme storms. The results of this study imply that rising temperatures will result in spatially smaller and more intense extreme precipitation storms in the tropics.</p><p dir="ltr">Adding a temporal dimension to the Spatial Homogeneity metric, the second objective introduces the Spatio-Temporal Homogeneity (STH) metric to analyze global patterns in the combined spatio-temporal characteristics of short-duration extreme storms. Findings reveal that extreme storms contract in both space and time in the tropics, while expanding in temperate zones as temperatures rise. Additionally, storms in the tropics and southern temperate regions exhibit increased front-loading, whereas northern temperate storms become slightly more rear-loaded. Short-duration (6–12 hours) storms show heightened sensitivity to temperature increases, underscoring the need for region-specific flood management and adaptation strategies.</p><p dir="ltr">Finally, the third objective assesses how climate change impacts global PMP estimates, focusing on changes in precipitation efficiency and maximum precipitable water<i> </i>𝑃𝑊_𝑚𝑎𝑥. While precipitation efficiency remains relatively unchanged, 𝑃𝑊_𝑚𝑎𝑥 has increased up to 40% in certain regions since the 1960s, establishing a conservative baseline for PMP rises. Future climate projections highlight that PMP estimates are expected to continue increasing even further. Furthermore, longer-duration PMPs show the most significant increases, stressing the need to reassess safety standards for large dams in high-risk areas. The study identifies the regions most at risk and highlights the necessity for updated PMP standards and targeted infrastructure adaptation in vulnerable regions.</p><p dir="ltr">This dissertation advances our understanding of how climate change is reshaping extreme precipitation characteristics, particularly from a hydrologic flood-generation perspective. By providing refined, climate-adjusted representations of future precipitation patterns, it marks a step toward improved accuracy in future flood and hydrologic response estimation. These insights lay a foundation for more informed flood risk assessments and support the development of targeted, resilient water management strategies essential for adapting to a changing climate.</p>

The structure of the master's thesis includes an introduction, three chapters, a conclusion, a list of references and appendices. The first chapter examines the concept, economic essence, structure of the company's working capital, sources of its formation and methods of managing it. The second chapter examines a brief description of the company, assesses the main financial and economic indicators, analyzes the dynamics, structure and efficiency of using working capital over the past three years. The third chapter examines the main problems identified in the analysis, develops measures to improve the management of the company's working capital, and calculates the impact of these measures on overall financial indicators. The conclusion forms the main findings. / Структура магистерской диссертации включает в себя введение, три главы, заключение, список использованных источников и приложения. В первой главе рассматривается понятие, экономическая сущность, структура оборотного капитала компании, источники его формирования и методы управления им. Во второй главе рассматривается краткая характеристика компании, проводится оценка основных финансово-экономических показателей, анализ динамики, структуры и эффективности использования оборотного капитала за последние три года. В третьей главе рассмотрены основные проблемы, выявленные в рамках анализа, разработаны мероприятия по совершенствованию управления оборотным капиталом компании, произведены расчеты влияния этих мероприятий на общие финансовые показатели. В заключении сформированы основные выводы.