Gröna obligationer, ett obligationslån där lånet måste knytas till ett hållbart projekt, är ettväxande begrepp i världen. Sverige är ett av de länder i framkant vad gäller användandet avdenna typ av obligationer. Allt fler investerare är måna om att investera i hållbara alternativ,där just gröna obligationer dykt upp som ett möjligt val. Men vilka motivationsfaktorer finnsdet som får företagen att vilja emittera dessa? Denna studie syftar till att besvara frågan om detråder några skillnader i lönsamhet för bolag som har emitterat gröna obligationer gentemot desom inte har.Utifrån författarnas kännedom finns det ingen liknande studie genomförd på den svenskamarknaden för tillfället. En tidigare studie har dock genomförts på den kinesiska marknadenmed ett resultat som påvisar en positiv relation mellan lönsamhet och gröna obligationer tillföljd av bolagets möjlighet att sänka sin kapitalkostnad.Studien genomfördes utifrån data mellan 2019-2021 på den svenska Large Cap marknaden.Både för hela men också specifikt för sektorer där gröna obligationer har tillämpats merfrekvent. Avkastning på totalt kapital (ROA) har använts som lönsamhetsmått medan grönaobligationer utgjorts av en binär variabel där de olika bolagen tilldelats en etta eller nollaberoende på om de haft gröna obligationer under hela det mätta året respektive inte. Studienhar tagit avstamp från trade-off och pecking-order theory som har sina synsätt på hur bolag börhantera sin skuldsättningsgrad och prioritera sina valmöjligheter att ta in ny finansiering.Studien har även använt sig av aktieägarteorin och intressentteorin för att återkoppla tillbolagens bakomliggande motiveringar att fatta de beslut de tar.Resultatet från studien visade inget signifikant samband mellan lönsamhet och grönaobligationer för svenska Large Cap eller för de branscherna som testades enskilt. Denna studiehar trots det bidragit med ny kunskap om hur relationen mellan gröna obligationer ochlönsamhet ser ut på en marknad där det inte testats förut.

Neural Network models got the attention of the scientific community for their increasing accuracy in predictions and good emulation of some human tasks. This led to extensive enhancements in their architecture, resulting in models with fast-growing memory and computation requirements. Due to hardware constraints such as memory and computing capabilities, the inference of a large neural network model can be distributed across multiple devices by a partitioning algorithm. The proposed framework finds the optimal model splits and chooses which device shall compute a corresponding split to minimize inference time and energy. The framework is based on PipeEdge algorithm and extends it by not only increasing inference throughput but also simultaneously minimizing inference energy consumption. Another thesis contribution is the augmentation of the emerging technology Compute-in-memory (CIM) devices to the system. To the best of my knowledge, no one studied the effect of including CIM, specifically DNN+NeuroSim simulator, devices in a distributed inference. My proposed framework could partition VGG8 and ResNet152 on ImageNet and achieve a comparable trade-off between inference slowest stage increase and energy reduction when it tried to decrease inference energy (e.g. 19% energy reduction with 34% time increase) and when CIM devices were augmenting the system (e.g. 34% energy reduction with 45% time increase).

Sustainability is a subject that seems to continuously gain popularity and importance in society.Hence, many aspects of the business world also revolve around the matter. One view onsustainability is that the current generation should act in a manner that allows the next generationto have similar foundations to prosper. An important factor in this involves the investment effortsfrom the companies, in particular the industrial companies. Therefore, this thesis aims toinvestigate the potential influence that recently increased interest rates have on sustainabilityefforts within Swedish manufacturing businesses. The responses to this phenomenon have beendiverse, with arguments that sustainability initiatives will remain unaffected, others suggestingadverse effects, and a few proposing that only a reduced demand following increased rates willbe impacted. Consequently, the purpose of this research was to gain valuable insights into theimplications of changing business climates on sustainability work and investments with theresearch question being what insights can be gained regarding sustainability efforts by exploringthe experiences of companies facing increased interest rates? We interviewed six listed Swedishcompanies with a production line to gain a deeper understanding from their experiences on howthey face increased interest rates and balance their sustainability efforts. This thesis draws uponseveral theoretical frameworks, including the stakeholder theory, legitimacy theory, trade-offtheory and corporate social responsibility (CSR). These theoretical perspectives provide acomprehensive foundation for understanding the complexities and dynamics surroundingsustainability efforts in the context of changing interest rates.To gather the necessary insights, this research employed a qualitative approach in theinterpretivist paradigm, conducting semi-structured interviews with a purposive non-probabilitysample of six participants. By capturing the experiences and perspectives of the participants, thestudy aims to generate rich and nuanced data that can improve our understanding of the impactof increased interest rates on sustainability efforts. Our analysis of the empirical results revealedthat these companies, despite potential challenges, remain committed to their sustainability goalsand efforts. They have not perceived any immediate threats to their goals due to increased interestrates.Thus, sustainable investments remain a critical aspect of companies’ strategies to meet globalsustainability goals. Motivated by legitimacy, stakeholder expectations and CSR commitments,companies integrate sustainability into their operations and influence stakeholders to participatein sustainable value creation. While the effects of interest rate hikes are diverse, companiesmaintain their sustainability efforts and strive to achieve their goals although potential risks andchallenges may arise in the future.

In this study, we evaluated the development of stress response in (1) two different species of quail, one species that is relatively fast-growing (Japanese quail, Coturnix japonica) and one that is relatively slow-growing (Gambel’s quail, Callipepla gambelii) and (2) two strains of a single species, the Japanese quail (wild-type and domesticated), that differ considerably in final size. Our data indicate that wild-type Japanese quail and Gambel’s quail have experienced trade-offs between growth and the stress response (e.g. Gambel’s quail have slower growth rates, but greater levels of CORT). However, the domesticated strain of Japanese quail used in this study seem to violate some predictions based on the life history theory (e.g. the domestic strain has faster growth rates and greater levels of CORT). The data in this study contribute to the understanding of differences in the stress response between species that exhibit different life history strategies.

Covid-19-pandemin ändrade snabbt förutsättningarna på kapitalmarknaden och företagen tvingades fort att anpassa sig efter rådande restriktioner och rekommendationer. Denna studie undersöker hur kapitalstrukturen i bolag noterade på Stockholmsbörsen förändrades under pandemiåren 2020–2021 jämfört med före pandemin (2016–2019). Med hjälp av teorier för kapitalstruktur och tidigare studier identifierades fem centrala mått som hjälper till att förklara skuldsättningsgraden. Genom multivariat analys studeras och analyseras vilka variabler och samband som har påverkat kapitalstrukturen under perioden. Studiens resultat visar, i likhet med tidigare studier kring agerande under krissituationer, att företagens skuldsättningsgrad minskade under jämfört med före pandemin.

Field surveys of Strongylocentrotus purpuratus demonstrated that concentrations of natural sunscreens, mycosporine-like amino acids (MAAs), were higher in females than males for both gonadal and epidermal tissues, increased in ovaries as spawning season approached, and were influenced by the sea urchins’ microhabitat. Sea urchins occupying burrows, or “pits”, had lower concentrations of MAAs than those outside pits, suggesting a trade-off between physical and UV protection. Overall, UV irradiance did not influence MAA accumulation in gonadal tissues. However, males increased their allocation of MAAs to epidermal tissues in the microhabitat with the highest irradiance. Relative concentrations of individual MAAs were similar for epidermal tissues from both sexes and ovaries, providing broadband UVA/UVB absorbance, but testes contained principally one MAA, palythine. This is the first study to demonstrate that S. purpuratus and eight species of macroalgae in California have MAAs, and that the concentrations can be influenced by microhabitat.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第24569号 / 工博第5075号 / 新制||工||1972(附属図書館) / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 須崎 純一, 教授 宇野 伸宏, 准教授 松島 格也 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Long-term ecological research in deep lakes offers valuable insights into understanding changes in trophic states and organization of phytoplankton assemblages. Utilizing five decades of phytoplankton taxonomic trait data from pre-alpine Lake Constance, a confirmed negative relationship was found between phosphate and light affinity at the annual community trait level. Drawing inspiration from the stronger community-level tradeoff observed between the affinity for phosphate and light among phytoplankton species in Lake Constance, I hypothesized that resource acquisition traits, characterized by the half-saturation constants for nutrient-limited growth (Mi) and light-limited growth (Hi), should exhibit a negative trade-off mechanism at the community mean trait level, derived from the traits of the species in Lake Constance. The developed model was parametrized using empirical data from the lake. Intra- and inter-annual variation in environmental conditions were incorporated in the model by considering seasonal changes in temperature, light intensity, temperature-influenced exchange rates of the vertical water column, and decadal changes in nutrients in Lake Constance. Simulations reflected observed seasonal dominance patterns of phytoplankton species and predicted differences in relative abundance under varying nutrient supplies, aligning with resource limitation trends. Consistent with empirical observations, a negative relationship between light and phosphorous affinity is observed in the 60-year simulation of Lake Constance. The elucidation of such a trade-off mechanism is expected to facilitate the understanding of the coexistence of phytoplankton species in Lake Constance amidst the decadal changes in phosphorus loading by selecting for higher light affinity during eutrophic phases and higher phosphorus affinity during oligotrophic phases.

Performance modelling and evaluation has long been considered of paramount importance to computer networks from design through development, tuning and upgrading. These networks, however, have evolved significantly since their first introduction a few decades ago. The Ubiquitous Web in particular with fast-emerging unprecedented services has become an integral part of everyday life. However, this all is coming at the cost of substantially increased security risks. Hence cybercrime is now a pervasive threat for today’s internet-dependent societies. Given the frequency and variety of attacks as well as the threat of new, more sophisticated and destructive future attacks, security has become more prevalent and mounting concern in the design and management of computer networks. Therefore equally important if not more so is security. Unfortunately, there is no one-size-fits-all solution to security challenges. One security defence system can only help to battle against a certain class of security threats. For overall security, a holistic approach including both reactive and proactive security measures is commonly suggested. As such, network security may have to combine multiple layers of defence at the edge and in the network and in its constituent individual nodes. Performance and security, however, are inextricably intertwined as security measures require considerable amounts of computational resources to execute. Moreover, in the absence of appropriate security measures, frequent security failures are likely to occur, which may catastrophically affect network performance, not to mention serious data breaches among many other security related risks. In this thesis, we study optimisation problems for the trade-offs between performance and security as they exist between performance and dependability. While performance metrics are widely studied and well-established, those of security are rarely defined in a strict mathematical sense. We therefore aim to conceptualise and formulate security by analogy with dependability so that, like performance, it can be modelled and quantified. Having employed a stochastic modelling formalism, we propose a new model for a single node of a generic computer network that is subject to various security threats. We believe this nodal model captures both performance and security aspects of a computer node more realistically, in particular the intertwinements between them. We adopt a simulation-based modelling approach in order to identify, on the basis of combined metrics, optimal trade-offs between performance and security and facilitate more sophisticated trade-off optimisation studies in the field. We realise that system parameters can be found that optimise these abstract combined metrics, while they are optimal neither for performance nor for security individually. Based on the proposed simulation modelling framework, credible numerical experiments are carried out, indicating the scope for further work extensions for a systematic performance vs security tuning of computer networks.

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