O objetivo desta dissertação é estimar os impactos econômicos de cenários de políticas climáticas para o Brasil. Mais especificamente, pretende-se através de um modelo de equilíbrio geral computável verificar como algumas variáveis econômicas respondem à simulação de algumas políticas de mitigação de mudanças climáticas por parte do Brasil. Para tal propósito, utilizou-se o modelo Emissions Prediction and Policy Analysis EPPA do MIT, o qual é um modelo dinâmico-recursivo, multi-regional que representa a economia mundial. Os principais resultados revelaram que a introdução de metas de redução de emissões a partir de 2015, possibilita uma redução expressiva das emissões de GEEs do país, com destaque para a redução proveniente de desmatamento. Quanto ao nível de atividade econômica verificou-se que o sacrifício a ser realizado em termos de perdas do PIB não se mostrou expressivo, o que pode ser explicado por uma matriz energética intensiva em fontes de energia limpa. Em termos de bem-estar, observou-se que a inclusão de metas de redução do desmatamento, como as representadas pela política CP1 trouxeram perdas modestas em bem-estar para o Brasil, ou seja, o esforço no sentido de enquadramento com as metas de Copenhague é benéfico, pois as perdas de bem-estar serão relativamente pequenas, caso o país continue o ritmo de redução em emissões previsto para 2020. / The objective of this dissertation is to estimate the economic impacts of climate policy scenarios for Brazil. More specifically, it is intended through a computable general equilibrium model to see how some economic variables respond to the simulation of some policies to mitigate climate change by Brazil. For this purpose, it was used the Emissions Prediction and Policy Analysis model EPPA, from the MIT, which is a dynamic-recursive model, multi-regional that represents the world economy. The results reveal that the introduction of the targets for reducing emissions from 2015, allows an expressive reduction of GHG emissions in the country, notably the reduction from deforestation. Regarding the level of economic activity showed that the sacrifice being made in terms of GDP loss was not significant, which can be explained by an energy-intensive sources of clean energy. In terms of welfare, it was observed that the inclusion of the targets for reducing deforestation, such as those represented by the policy CP1 brought modest losses in welfare for Brazil, namely the effort to frame the goals of Copenhagen is beneficial, because the loss of welfare will be relatively small if the country can continue the pace of reduction in emissions in 2020.

Submitted in fulfillment of the requirements for the degree of Doctor of Philosophy: Biotechnology, Durban University of Technology, Durban, South Africa, 2017. / Fossil carbon dioxide emissions can be biologically fixed which could lead to the development of technologies that are both economically and environmentally friendly. Carbon dioxide, which is the basis for the formation of complex sugars by green plants and microalgae through photosynthesis, has been shown to significantly increase the growth rates of certain microalgal species. Microalgae possess a greater capacity to fix CO2 compared to terrestrial plants. Selection of appropriate microalgal strains is based on the CO2 fixation and tolerance capability, both of which are a function of biomass productivity. Microalgal biomass could thus represent a natural sink for carbon. Furthermore, such systems could minimise capital and operating costs, complexity, and energy required to transport CO2 to other places. Prior to the development of an effective CO2 mitigation process, an essential step should be to identify the most CO2-tolerant indigenous strains. The first phase of this study therefore focused on the isolation, identification and screening of carboxyphilic microalgal strains (indigenous to the KwaZulu-Natal province in South Africa). In order to identify a high carbon-sequestering microalgal strain, the physiological effect of different concentrations of carbon sources on microalgae growth was investigated. Five indigenous strains (I-1, I-2, I-3, I-4 and I-5) and a reference strain (I-0: Coccolithus pelagicus 913/3) were subjected to CO2 concentrations of 0.03 - 15% and NaHCO3 of 0.05 - 2 g/1. The logistic model was applied for data fitting, as well as for estimation of the maximum growth rate (µmax) and the biomass carrying capacity (Bmax). Amongst the five indigenous strains, I-3 was similar to the reference strain with regards to biomass production values. The Bmax of I-3 significantly increased from 0.214 to 0.828 g/l when the CO2 concentration was increased from 0.03 to 15% (r = 0.955, p = 0.012). Additionally, the Bmax of I-3 increased with increasing NaHCO3 concentrations (r = 0.885, p = 0.046) and was recorded at 0.153 g/l (at 0.05 g/l) and 0.774 g/l (at 2 g/l). Relative electron transport rate (rETR) and maximum quantum yield (Fv/Fm) were also applied to assess the impact of elevated carbon sources on the microalgal cells at the physiological level. Isolate I-3 displayed the highest rETR confirming its tolerance to higher quantities of carbon. Additionally, the decline in Fv/Fm with increasing carbon was similar for strains I-3 and the reference strain (I-0). Based on partial 28S ribosomal DNA gene sequencing, strain I-3 was found to be homologous to the ribosomal genes of Chlorella sp. The influence of abiotic parameters (light intensity and light:dark cycles) and varying nutrient concentrations on the growth of the highly CO2 tolerant Chlorella sp. was thereafter investigated. It was found that an increase in light intensity from 40 to 175 umol m2 s-1 resulted in an enhancement of Bmax from 0.594 to 1.762 g/l, respectively (r = 0.9921, p = 0.0079). Furthermore, the highest Bmax of 2.514 g/l was detected at a light:dark cycle of 16:8. Media components were optimised using fractional factorial experiments which eventually culminated in a central composite optimisation experiment. An eight-factor resolution IV fractional factorial had a biomass production of 2.99 g/l. The largest positive responses (favourable effects on biomass production) were observed for individual factors X2 (NaNO3), X3 (NaH2PO4) and X6 (Fe-EDTA). Thereafter, a three-factor (NaNO3, NaH2PO4 and Fe-EDTA) central composite experimental design predicted a maximum biomass production of 3.051 g/l, which was 134.65% higher when compared to cultivation using the original ASW medium (1.290 g/l). A pilot scale flat panel photobioreactor was designed and constructed to demonstrate the process viability of utilising a synthetic flue gas mixture for the growth of microalgae. The novelty of this aspect of the study lies in the fact that a very high CO2 concentration (30%) formed part of the synthetic flue gas mixture. Overall, results demonstrated that the Chlorella sp. was able to grow well in a closed flat panel reactor under conditions of flue gas aeration. Biomass yield, however, was greatly dependent on culture conditions and the mode of flue gas supply. In comparison to the other batch runs, run B yielded the highest biomass value (3.415 g/l) and CO2 uptake rate (0.7971 g/day). During this run, not only was the Chlorella strain grown under optimised nutrient and environmental conditions, but the culture was also intermittently exposed to the flue gas mixture. Results from this study demonstrate that flue gas from industrial sources could be directly introduced to the indigenous Chlorella strain to potentially produce algal biomass while efficiently capturing and utilising CO2 from the flue gas. / D

With the introduction of cloud computing the computation got distributed, virtualized and scalable. This also meant that customers of cloud computing gave away some of their control of their system. That led to a heighten importance of how to handle security in the cloud, for both provider and customer. Since security is such a big subject the focus of this thesis is on confidentiality and privacy, both closely related to how to handle personal data. With the help of a systematic literature review in this thesis, current challenges and possible mitigations are presented in some different areas and concerning both the cloud provider and the cloud customer. The conclusion of the thesis is that cloud computing in itself have matured a lot since the early 2000’s and all of the challenges provided have possible mitigations. However, the exact implementation of said mitigation will differ depending on cloud customer and the exact application developed as well as the exact service provided by the cloud provider. In the end it will all boil down to a process that involves technology, employees and policies and with that can any user secure its cloud application.

This thesis is a critical evaluation of the theory and practice of Sustainable Supply Chain Management (SSCM). It seeks to understand why SSCM theory has so little to say about environmental sustainability and to explore how SSCM practice is contributing towards the transition towards sustainable development. I conjecture that SSCM scholars have not engaged sufficiently with the broader sustainability literature and other constructions of sustainability, which has led to a lack of theory development within SSCM. The sustainability paradigms framework that forms the core of the thesis was developed in order to broaden the discussion around sustainability within SSCM. Specifically, it embraces the contested nature of the concept of sustainability and uses multiple sustainability paradigms to construct future directions for theory development. In order to put the concept of environmental sustainability at the centre of SSCM theory, the concept of ‘environmental effectiveness’ was developed which seeks to differentiate between environmentally sustainable strategies and those that merely seek to achieve reductions in unsustainability. In order to evaluate the practice of SSCM, a case study was conducted. The concept of ‘environmental effectiveness’ is operationalized through the use of non-perceptual measures related to carbon emissions and evaluates the extent to which SSCM practices contribute towards climate stabilization, a key sustainability objective. It is found that those SSCM practices that have been shown to improve ‘environmental performance’ within the extant SSCM literature did not deliver ‘environmentally effective performance’ within the case study. This raises the possibility that the literature has mistaken reductions in unsustainability for sustainability proper and that we may need to go back to basics. The findings are discussed with reference to the sustainability paradigms framework and multiple opportunities for theory development within SSCM are explored.

Large-scale, high-density Wi-Fi networks use hundreds of access points to serve thousands of closelypacked users within a large physical space (hundreds of thousands of square feet or more, such as in a stadium or arena). Because of their scale, these are complex and dynamic systems comprised of several layers and multiple components within each layer, and faults may be present in any one of these components. The problems that manifest from these faults are usually not network-wide and may be localized to a certain physical areas of the network. This makes these problems challenging to detect and diagnose; in most cases, only a small number of devices tend to be impacted by any given problem. However, many such problems may occur simultaneously in different areas of the network. Adding to the complexity is the dynamic nature of such networks, where the physical positions of radios (in end-user devices), human bodies, and other objects in the space are constantly changing, thereby creating a continually-changing RF environment. Taken together, these properties make problem diagnosis in large-scale, high-density Wi-Fi networks challenging. There are many existing techniques for diagnosing problems in Wi-Fi networks. Many of these approaches rely on data from only a single perspective of the network to diagnose problems, for example, either the client, the infrastructure (access points), or external Wi-Fi sensors that passively monitor the network. In addition, many of these approaches require the invasive modification of the network’s components in order to collect data, through techniques such as the installation of specialized software on clients, modifying the firmware on access points, or even physically installing specialized devices in the RF environment of the Wi-Fi network. Finally, many approaches rely on offline analysis of the collected instrumentation, in which case diagnosis cannot be done in real time (minutes or less). Many others require network connectivity for real-time diagnosis, in which case the device must be able to communicate using the Wi-Fi infrastructure (that may be experiencing a problem). As a result, many of these approaches are difficult to deploy in production networks (due to the high financial cost or maintenance effort required), and those that are deployed often fail to detect and diagnose problems that are localized to a small number of devices (10 or less) or problems that are only present for a short time (minutes or less). This dissertation takes a unique approach that contrasts with existing approaches in three key ways. First, we combine the Wi-Fi performance data from multiple layers of the Wi-Fi network and attempt to diagnose problems at all of these layers, rather than focusing on a single layer alone, and we introduce a fault model that includes faults that can occur across all layers of the system. Second, we require no invasive modification of the Wi-Fi network or its components in order collect data and perform problem diagnosis and mitigation. Third, we present an infrastructure-free approach to problem diagnosis that relies on Bluetooth communication with other devices nearby (peers) to perform diagnosis based on multiple perspectives of the Wi-Fi network. With this approach, our diagnosis algorithm is able to collect data from multiple network perspectives without relying on Wi-Fi infrastructure, which may be slow or unavailable. Our approach begins with the construction of an instrumentation and data-collection system to obtain Wi-Fi performance metrics from both the client and infrastructure perspectives of the network. We then build upon our instrumentation to determine when user-visible problems occur. We define a user-visible problem as a Wi-Fi-network-performance problem that causes users to disengage from using the network. Once we have detected a user-visible problem, we then proceed to diagnose the root cause of the problem as one of the faults in our fault model using an approach based on decision trees. Finally, based on the diagnosed fault, we apply an automated mitigation-strategy, which forces the device to associate with a different access point that will likely provide better performance. To validate our approach and demonstrate its real-world impact, we have conducted a number of studies to collect data in support of our approach from both a laboratory testbed and real-world production Wi-Fi networks. We used our instrumentation and data-collection system to obtain data from over 25 real-world, large-scale, high-density Wi-Fi networks located within collegiate and professional stadiums. Our diagnostic system was deployed in a real-world mobile video-streaming application used over the Wi-Fi networks in these stadiums. Using this data, we determined the thresholds for when a Wi-Fi performance problem becomes user visible, based on our study of when users disengage from using the video-streaming application in the face of buffering. In addition to obtaining real-world data, we have studied this phenomenon in a testbed for fault injection and diagnosis that has been deployed both in a lab environment and in an arena to collect data on the behavior of large-scale, high-density Wi-Fi networks and understand how best to diagnose problems. Using this testbed, we evaluated the performance of our problem-diagnosis approach in terms of its precision and recall on injected faults. We also evaluated the performance of our mitigation strategy on our testbed by injecting faults and verifying that the selected mitigation strategy successfully mitigated the problem caused by that fault. We found that our approach diagnoses the correct root cause of faults with high precision and recall (often above 90%) and can mitigate problems via alternative access-point selection in 100% of our test cases. While we have studied our approach in certain test environments and for video-streaming applications, we believe that our approach can be applied to any Wi-Fi network and many other applications outside of video streaming. Our work in this dissertation could be extended through the automated discovery of the parameters for our diagnosis and mitigation algorithms that provide the best performance in other Wi-Fi networks, along with further studies of how Wi-Fi performance problems manifest in other types of applications and under what conditions users disengage with those applications due to problems.

Urbanization and wetland mitigation are increasingly common in coastal watersheds with expanding populations. These mitigation wetlands are intended to offset the functional and structural losses experienced when natural systems are degraded or destroyed. In the Tampa Bay watershed, urbanization is both expanding into the upper reaches of the watershed and intensifying in previously-developed areas, resulting in the creations of hundreds of freshwater mitigation wetlands. This dissertation utilized an existing database of mitigation wetlands, publicly available data, and field surveys to investigate the relationship between constructed wetlands and their surroundings and also determine how design affects wetland condition over time. The overarching goals of this dissertation were to evaluate the geospatial distribution and areal extent of constructed freshwater mitigation wetlands in Hillsborough County and determine how they influence the landscape; evaluate design variables and environmental factors influencing constructed wetland trajectories; and determine how future changes to the landscape will likely affect constructed wetland systems. The goals of Chapter 2 were to evaluate the relationship between mitigation wetland construction and total freshwater wetland area; determine if forested and non-forested wetlands are being impacted/mitigated at similar rates; determine if wetland mitigation is offsetting impacts from increased urbanization at the landscape scale. This study concluded that since 1985, permitted impacts of non-forested wetlands have occurred at a significantly greater annual rate than forested systems, despite their smaller regional footprint. Interestingly, this increased impact frequency, combined with mitigation ratios greater than 1:1 (mitigation to impact area), have helped decrease proportional difference in area between forested and non-forested wetlands in the region. Over the period of the study, mean LDI scores for drainage basins across watershed have increased, with those containing mitigation projects significantly increasing compared to those without. Changes in drainage basin LDI were significantly correlated to the number of mitigation projects per basin, total impact area, and total mitigation area. Upward shifts in drainage basin LDI categories have been documented in 25 of Hillsborough County’s 184 basins, however no significant connection to permittee-responsible freshwater wetlands was established. These results imply that current mitigation practices are failing to ameliorate increasing development intensity at the landscape scale. The goals of Chapter 3 were to determine the current condition of created freshwater mitigation wetlands in Hillsborough County, Florida; determine if forested and non-forested wetlands maintain similar trajectories after release; and evaluate how design and changes in the landscape influence created wetland condition over time. Original wetland engineering plans and historical data were used to establish baseline conditions at the time of wetland “release” and track wetland changes over time. A chronosequence approach was utilized to determine wetland trajectories and analyze potential differences between forested and non-forested systems. This study found that surveyed freshwater wetlands had decreased in size from their intended area by a total of approximately 18%, but due to increased mitigation ratios, were likely still producing a net gain in total wetland area and meeting the goals of “no net loss”. On average, wetland condition (as determined by WRAP scores) decreased by 9% from the time of release to the time of survey. Few differences were observed between wetland types with the exception of canopy richness and wetland trajectory, although correlations between wetland condition and time were non-significant. From the regression optimization analyses, it appeared that wetland location (as measured in the design WRAP score) was one of the most important factors contributing to surveyed wetland condition. In Chapter 4, future land use data was used to determine predicted anthropogenic pressure on these urban wetland systems and evaluate changes to the overall landscape. GIS based analyses on landscape development intensity (LDI) determined that significant changes are not expected at the landscape scale by the year 2025, however drainage basins that possess mitigation wetlands are anticipated to increase in development intensity. Predicted LDI scores for constructed freshwater wetlands is predicted to increase significantly, which could have detrimental impacts on wetland condition. This dissertation highlights the significance of wetland design and location on wetland condition. From this research, it is apparent that consideration of site placement is the most important design variable for small (3 hectares or less) freshwater wetlands; and that understanding of future conditions may promote long-term success. Long-term studies such as this are valuable tools for understanding how specific ecosystems respond to changing landscapes and should be used to help shape policies that reflect these ecological advancements. Understanding the past and preparing for the future is the only way to foster restoration success.

Purpose: In the last decade, supply chains of many global firms have been exposed to severe and costly supply chain disruptions. Triggered by either a manmade or a natural disaster, these disruptions are often a result of the increased network complexity and interdependency. One of the many contributing factors to this increased network complexity is the conscious effort by organizations to over optimise their efficiency and performance. The field of supply chain resilience, robustness and vulnerability studies, a new and growing area of knowledge, is contributing towards discovering the causes leading to supply chain disasters and measures to tackle them. Criticized to be highly fragmented and fraught with conceptual ambiguity, the filed has been evolving by incorporating vulnerability and resilience research from other interdisciplinary domains. This present research aims at mapping the intellectual territory of the resilience, robustness and vulnerability domain by conducting a literature review. The review also aims to establish a conceptual clarity in the definition of terms and constructs relevant to the field and to discover conceptual and methodological gaps in the existing body of literature. Design/methodology/approach: This literature review is conducted using a systematic review approach which benefits from a clearly defined audit and decision trail. After filtering through 2077 titles, the review is taken up for 43 articles. Findings: The review demonstrates that the drivers of vulnerability and strategies to tackle it can be grouped into three themes, Structural, Operational and Strategic. The review also demonstrates that the field is still plagued with conceptual ambiguity. By the analysis of the findings, a number of research directions were identified. Research limitations/implications: Major limitations to this study were the associated personal bias in quality assessment of included and excluded articles. Also, due to blurred definitions of terms and constructs in the literature, the thematic classification of findings could be challenged. Lastly, it cannot be stated with conviction that the chosen 43 articles are sufficient. Practical implications: This research highlights the future conceptual and methodological prospects in the field of resilience, robustness and vulnerability. The direction of structural research proposed in the thesis has a very high potential to secure future supply chains. Originality/value: This review is first to address the issue of SCV, SCRel and SCRob. The review provides an extensive overview of the present extant of the vulnerability, robustness research and it proposes a thematic framework to further extend the knowledge in this filed.

Femtocells have been introduced as a solution to poor indoor coverage in cellular communication which has hugely attracted network operators and stakeholders. However, femtocells are designed to co-exist alongside macrocells providing improved spatial frequency reuse and higher spectrum efficiency to name a few. Therefore, when deployed in the two-tier architecture with macrocells, it is necessary to mitigate the inherent co-tier and cross-tier interference. The integration of cognitive radio (CR) in femtocells introduces the ability of femtocells to dynamically adapt to varying network conditions through learning and reasoning. This research work focuses on the exploitation of cognitive radio in femtocells to mitigate the mutual interference caused in the two-tier architecture. The research work presents original contributions in mitigating interference in femtocells by introducing practical approaches which comprises a power control scheme where femtocells adaptively controls its transmit power levels to reduce the interference it causes in a network. This is especially useful since femtocells are user deployed as this seeks to mitigate interference based on their blind placement in an indoor environment. Hybrid interference mitigation schemes which combine power control and resource/scheduling are also implemented. In a joint threshold power based admittance and contention free resource allocation scheme, the mutual interference between a Femtocell Access Point (FAP) and close-by User Equipments (UE) is mitigated based on admittance. Also, a hybrid scheme where FAPs opportunistically use Resource Blocks (RB) of Macrocell User Equipments (MUE) based on its traffic load use is also employed. Simulation analysis present improvements when these schemes are applied with emphasis in Long Term Evolution (LTE) networks especially in terms of Signal to Interference plus Noise Ratio (SINR).

法條有限而人事無窮，想要以有限的法條規範無窮的人事，殆矣，故刑法第五十九條：「犯罪之情狀顯可憫恕，認科以最低度刑仍嫌過重者，得酌量減輕其刑。」本意係因「有限的法條本就無法規範無窮的人事且為了衡平情輕法重的個案正義，然個案正義不能背離社會大眾之法律情感，否則就會被社會大眾批評恐龍判決或恐龍法官。 本文試圖透過酌減規範的歷史、理論與實踐來探討酌減制度的適用是否適當？還是淪為法官恣意審判的護身符？並且如果酌減制度仍有存在的價值時，希望法院能就法官援引酌減制度審判之相關案件建立起資料庫可供法官參考，不只可讓法官審判時相同案件不至於有不同的判決，也不致讓民眾感覺到審判的不公平而影響司法威信。

This thesis proposes a classification system of risk mitigation strategies based on literature search and industry interviews. Following that, a list of generic properties was generated to describe individual strategies. In parallel, populating the properties of a large number of identified strategies was attempted. The practical implications are discussed mainly focusing on knowledge management for risk mitigation strategies. / Applied Science, Faculty of / Civil Engineering, Department of / Graduate