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This research explored different catalytic cracking zeolite additives to improve propylene selectivity and minimize dry gas yield. A comprehensive study of the effect of zeolite structure, pore system and crystal size on maximizing propylene production in FCC unit and the effect of post synthetic modifications on the physicochemical properties and cracking activity of ZSM-5 was investigated using X-ray diffraction (XRD), pyridine adsorption fourier transform infra-red (FTIR), 27Al and 29Si magic-angle spinning nuclear magnetic resonance (MAS NMR) and the catalytic cracking using n-heptane, as a model compound for heavy naphtha. The catalytic performances of these additives were evaluated in a fixed-bed reactor unit using n-heptane as a model compound for naphtha at temperatures 450 - 500 oC and W/F 38 - 92 gcat.h/mol. A range of zeolites were tested with ZSM-5 showing the optimum results at high feed conversion. Further studies on ZSM-5 crystal size illustrated that nano ZSM-5 (300 nm) was superior compared to the regular ZSM-5 (2000 - 4000 nm) in achieved conversion level and propylene selectivity. These improvements were attributed to the shorter path lengths for the reactant reducing diffusion constraints significantly. Modifying nano ZSM-5 acidity using steaming, acid leaching and silanation showed significant improvement over nano ZSM-5 parent. Mild steaming of nano ZSM-5 improved both n-heptane conversion and propylene selectivity whilst severe steaming only improved propylene selectivity. This work attempted to address the often discussed catalytic activity enhancement from mild steaming and identified newly created moderate acid sites as the source of increased activity. Dealumination by acid leaching decreased the total aluminium content of nano ZSM-5 and changed the Brønsted/Lewis ratio. Increasing the B/L ratio, increased the conversion and propylene selectivity. In addition, this research focussed for the first time on the silanation of nano ZSM-5 and its effect on n-heptane cracking, in particular, propylene and dry gas selectivity. Silica was deposited on the external surface of nano ZSM-5 neutralising the acidic sites and as a result, dry gas yield was significantly decreased due to the elimination of non-selective cracking. However, the trade off with conversion was high.

Human enhancement (HE) is the field of research aiming to improve and overcome the biological limitations of the physical and mental performance of humans. The implications of HE might especially prove relevant within high-intensity environments, such as the working environment of police and fire and rescue services. The aim of this thesis is to identify the needs of personnel within these domains and to highlight potential HE solutions that could aid to improve responder performance in the setting of an active emergency. Interviews conducted with representatives for the Swedish police and fire and rescue service highlighted the need for support of mental performance in the form of destressing during highintensity situations as well as an improvement of creating situational awareness and making adequate decisions in a short amount of time. The results imply a potential of implementing HE solutions that aid emergency responders by keeping them alert and open for information gathering or minimizing the experienced level of stress while providing vital information for a proper response. The thesis alsoconcluded a generally positive attitude towards implementation of HE solutions.

<p dir="ltr">Traffic safety and congestion are global concerns. Autonomous vehicles (AVs) are expected to enhance transportation safety and reduce congestion. However, achieving their full potential requires 100% market penetration, a challenging task. This study addresses key issues in mixed traffic environments, where human-driven vehicles (HDVs) and connected autonomous vehicles (CAVs) coexist. A number of critical questions persist: 1) inadequate exploration of human errors (errors originating from non-CAV sources) in mixed traffic; 2): limited focus on information selection and learning efficiency in network-level rerouting, particularly in highly dynamic environments; 3) inadequacy of personalized element driver inputs in motion-planning frameworks; 4) lack of consideration of user privacy concerns.</p><p dir="ltr">With the goal of advancing the existing knowledge in this field and shedding light on these matters, this dissertation introduces multiple frameworks. These frameworks leverage connectivity and automation to improve safety and mobility in mixed traffic, addressing various research levels, including local-level and network-level safety enhancement, as well as network-level and global-level mobility enhancement. With optimization- and learning-based methods implemented (Model Predictive Control, Deep Neural Network, Deep Reinforcement Learning, Transformer model and Federated Learning), frameworks introduced in this dissertation are expected to help highway agencies and vehicle manufacturers improve the safety and efficiency of traffic flow in the mixed-traffic era. Our research findings revealed increased crash-avoidance rates in critical situations, enhanced accuracy in predicting lane changes, improved dynamic rerouting within urban areas, and the implementation of effective data-sharing mechanisms with a focus on user privacy. This research underscores the potential of connectivity and automation to significantly enhance mixed-traffic safety and mobility.</p>

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【第一篇論文中文摘要】 集中度風險於結構式商品的量化與分析：以房屋抵押貸款證券為例 "Martin and Wilde (2002)與Gordy (2003)" 針對巴塞爾協定(Basel Accords)中金融機構之投資組合所內藴之集中度風險提出了相對應的微粒化調整(Granularity Adjustment)風險量化準則，然而該模型僅止於單因子架構下探究單一信用標的集中度風險之量化。本文將其架構延用至結構式商品中，允許債權群組內之信用標的具不同區域別，我們採用Hull and White(2010)之跨池違約相關性描述，並結合Pykhtin (2004)中延拓單因子聯繫模型至多因子之方式，進而求取債權群組之單一資產集中度(Name Concentration)與區域類別集中度(Sector Concentration)風險的量化。本文以房屋抵押貸款證券(Mortgage Backed Securities, MBSs)為例，於集中度風險的考量下，藉由檢視不同風險情境下分券之損失起賠點，重新評估房屋抵押貸款證券AAA投資級分券信用評級之合理性。研究結果顯示，AAA評等之分券高度曝險於系統性風險，且於高風險情境下，標的房貸之區域集中現象擴大了違約相關性對債權群組損失分配的影響，致使AAA分券之損失起賠點得以超過其實際擔保額度(subordination)範圍。 【第二篇論文中文摘要】 美國銀行放款多角化對其報酬與風險之影響：相關性與傳染的觀點 本文目的在於分析銀行放款的多角化行為對其報酬與風險之影響。研究發現納入銀行放款投資組合相關性之考量，亦即標的資產之相關性結構以及資產間因契約關係所隱含跨投資組合之傳染途徑，將降低多角化之成效。文中透過因子模型(factor model)建構資產之報酬，同時決定其相關性結構，其中將資產間殘差項相關性作為傳染指標，進一步分析投資組合內標的資產間的平均相關係數、傳染與多角化程度間的關聯性。我們以美國銀行作為研究樣本，分別以赫芬達-赫希曼指數估算投資組合權重分配之集中度、使用組合內標的產業股票報酬資訊來計算投資組合內相關程度，接著利用標的產業與投資組合外產業間的殘差相關性來捕捉產業傳染效果，將此三項指標作為衡量多角化指標，分析其在1987年至2014年間聯貸投資組合多角化情形並試圖分析放款多角化對銀行績效之影響。透過契約關係的界定進而探討顧客傳染如何影響銀行績效。 研究發現於市場處於平穩期間(tranquil period)，所有多角化指標銀行放款均呈現放款多角化程度越高越有助於提高銀行的報酬並降低其風險。然而於危機期間(turmoil period)，銀行應將放款權重集中於部分產業、建構相關性較低之組合或選擇較低之傳染效果之產業作為放款的對象，用以提高銀行績效。隱含在危機期間銀行應該選擇適度之多角化策略，若僅以赫芬達-赫希曼指數作為多角化之衡量將顯示危機期間越集中越有助於銀行的表現，此舉將造成解釋上的偏誤。說明於投資組合多角化的衡量上，不該忽略由相關性結構所引發之集中度風險。 / 【Essay I】 Quantification and Analysis of Concentration Risk in Structured Products: the Case of Mortgage Backed Securities Granularity adjustments, introduced by Martin and While (2002) and Gordy (2003), allow one to quantify the concentration exposures of credit portfolios due to imperfect diversification. However, they focus solely on name concentrations under an Asymptotic Single Risk Factor (ASRF) framework. In this study, by adapting the multi-pool correlation structure of Hull and White (2010) under the multi-factor setting of Pykhtin (2004), we derive quantitative measures of name and sector concentration that facilitate subsequent analysis of the risk profiles embedded in Mortgage Backed Securities (MBSs). Under different stress scenarios, we examine the impacts of concentration exposures on the internal credit enhancements, in particular, the AAA tranche attachment points. We show that, under severe market conditions, the presence of sector concentrations in the underlying mortgage pools can further amplify the effects of default correlation on the portfolio loss distributions. As a direct consequence, the predetermined subordination level determined by the assignment of tranche attachment points can be exceeded. 【Essay II】 How Loan Portfolio Diversification Affects U.S. Banks’ Return and Risk: Correlation and Contagion Perspectives. In this paper we investigate how loan portfolio diversification affects the banks’ return and risk. We argue that, the dependence structure of bank loan portfolios, namely, the correlation structure among loan assets and the presence of contagion channels due to contractual relationships across the border of portfolio, contributes to the costs of diversification. Under the factor model framework, we derive a theoretical model to depict the asset returns and their dependence structure. Based on data of US bank loans collected from 1987-2014, our empirical study employs HHI, intra-portfolio correlation, and contagion as proxies for diversification to examine how loan portfolio diversification affects the banks’ profitability and riskiness. In addition, contractual relationships are identified and we investigate how customer contagion affects the bank’s performance. We find that all diversification measures exhibit a positive effect on the performance of U.S. banks during tranquil periods. However, for turmoil periods, banks with loan portfolios of more concentrated weight distributions, lower intra-portfolio correlation, or lower consumer contagion effects would have improved returns and reduced risk. In other words, during crisis, banks should choose an appropriate concentration strategy rather than focus on selected industries as determined solely by the HHI.