A company's need for an effective and suitable corporate strategy is higher than ever due tofierce and increasing competition in the current business landscape. In order for companies tofinance their chosen corporate strategy, as for instance conduct investments for growth, theyneed proper funding. Moreover, the capital structure defines and outlines a company’s availablemix of debt and equity. Financial theories and studies further conclude that it is paramount forcompanies to understand the relationship between the corporate strategy and the capital structurein order to remain competitive. However, the current amount of empirical studies that have beenconducted in this area is very limited. Therefore, this study has analysed and examined therelationship between the corporate strategy and the capital structure for small and medium-sizedenterprises (SMEs) in the Swedish manufacturing industry. Indeed, the purpose of the study is toexamine this relationship. The study has been executed by conducting five case studies where five different SMEs in theSwedish manufacturing industry have been analysed. The companies represent both familyownership as well as ownerships via external investors. The five case studies consisted of semistructuredinterviews with the CEO of each firm. A questionnaire was also provided to the fiverespondents, which enhanced the possibility to benchmark the results from the companies. The results of the study indicate that the relationship between the corporate strategy and thecapital structure differs depending on a company’s type of ownership. In conclusion, forexternally owned companies (e.g. owned by private equity companies), the corporate strategytends to drive the choice of capital structure. On the other hand, for companies owned by thefounding families, the relationship seems to be inverted where the capital structure rather drivesthe choice of corporate strategy. / Ett företags behov av en effektiv och passande företagsstrategi är högre än någonsin på grund avhård och ökande konkurrens på den nuvarande marknaden. För att ett företag skall kunnafinansiera sin valda företagsstrategi, som exempelvis att genomföra investeringar för tillväxt,krävs det en väl avvägd finansiering. Vidare definierar och beskriver kapitalstrukturen ettföretags tillgänglighet gällande dess mix av skulder och eget kapital. Samtidigt visar finansiellteori och studier på området att det är av största vikt för företag att de förstår sambandet mellandess företagsstrategi och kapitalstruktur för att de skall kunna förbli konkurrenskraftiga. Dock ärantalet studier som är gjorda på området mycket begränsade. Således har denna studie analyseratoch undersökt sambandet mellan företagsstrategin och kapitalstrukturen för små och medelstoraföretag (SMEs) inom den svenska tillverkningsindustrin. Studien har utförts genom att genomföra fem fallstudier där fem olika små och medelstoraföretag inom den svenska tillverkningsindustrin har analyserats. Företagen representerar bådefamiljeägda företag samt företag ägda av externa investerare. De fem fallstudierna bestod avsemistrukturerade intervjuer med VDn för respektive bolag. Ett frågeformulär distribueradesockså till de fem respondenterna för att kunna möjliggöra en jämförelse av resultaten från bolagen. Resultaten av studien indikerar att sambandet mellan företagsstrategin och kapitalstrukturenvarierar beroende på typ av ägarskap av ett bolag. Sammanfattningsvis så tenderar valet avföretagsstrategi att driva valet av kapitalstruktur för bolag ägda av externa investerare(exempelvis bolag ägda av private equity-företag). Å andra sidan tenderar förhållandet snararevara inverterat för företag ägda av sina grundarfamiljer, där kapitalstrukturen snarare driver valetav företagsstrategi.

In post-financial crisis times, new legislation in combination with banks’ changed risk aversion has to a great extent changed the proprietary trading to client driven trading, i.e. market making or client facilitation. This type of trading complicates the risk-return dynamics, as the goal is often to minimize risk and achieve profitable commission revenues. This thesis aims to disclose the risk-return tradeoff in a client driven trading environment. This is done by investigating the conditional relation between risk and realized return. As opposed from many studies which proxy the risk with beta or variance, I use a delta-gamma Value at Risk model as the risk proxy, which I also backtest. For the return proxy, I use three different measures; P&L, commission revenues and the sum of these two. A positive tradeoff exists if (i) the return is equally negatively dependent on the risk if the ex post return is negative, as it is positively dependent on the risk if the ex post return is positive and (ii) the average return is significantly positive. For three different client driven trading portfolios tested, I found a positive risk-return tradeoff in one portfolio, between the P&L plus commission revenues and the Value at Risk. However, since a symmetrical conditional relationship between risk and P&L plus commission revenues was found in all portfolios, and the average return was positive, the positive tradeoff would have existed if the average return would have been significantly positive. On the other hand, one could argue that the tradeoff exists, but is not significant. No relation between risk and commission revenues was found. A probable cause to this is the hedging strategies, which would be an interesting topic for further research. / I tiden efter finanskrisen har nya regelverk i kombination med bankers förändrade riskaptit till stor del förändrat den proprietära handeln till klientdriven handel, i.e. ”market making” eller förenklad handel för kund. Denna typ av handel komplicerar dynamiken mellan risk och avkastning, då målet ofta är att minimera risk och nå lönsamma kommissionsintäkter. Denna uppsats ämnar påvisa förhållandet mellan risk och avkastning i en klientdriven handelsmiljö. Detta görs genom att undersöka den betingade relationen mellan risk och realiserad avkastning. Till skillnad från andra studier som använder beta eller varians som riskmått, använder jag en delta-gamma Value at Risk-modell som jag också backtestar. Som avkastningsmått, använder jag tre olika mått; P&L, kommissionsintäkter samt summan av dessa två. En positiv belöning för att bära risk existerar om (i) avkastningen är lika negativt beroende av risken om den realiserade avkastningen är negativ, som den är positivt beroende av risken om den realiserade avkastningen är positiv och (ii) medelvärdet på avkastningen är signifikant positiv. För tre olika klientdrivna portföljer som testats, hittades en positiv belöning för att bära risk endast i en portfölj, mellan P&L plus kommissionsintäkter och Value at Risk. Emellertid, eftersom en symmetrisk systematisk betingad relation mellan risk och P&L plus kommissionsintäkter hittades i alla portföljer, och medelavkastningen var positiv, skulle den positiva belöningen ha funnits om medelavkastningen varit signifikant positiv. Å andra sidan skulle jag kunna hävda att den positiva belöningen finns, men inte är signifikant. Ingen relation mellan risk och kommissionsintäkter hittades. En trolig orsak till detta är hedgnings-strategierna, vilket vore ett intressant ämne för fortsatt forskning.

<p>The capacity of deep reinforcement learning policy networks has been found to affect the performance of trained agents. It has been observed that policy networks with more parameters have better training performance and generalization ability than smaller networks. In this work, we find cases where this does not hold true. We observe unimodal variance in the zero-shot test return of varying width policies, which accompanies a drop in both train and test return. Empirically, we demonstrate mostly monotonically increasing performance or mostly optimal performance as the width of deep policy networks increase, except near the variance mode. Finally, we find a scenario where larger networks have increasing performance up to a point, then decreasing performance. We hypothesize that these observations align with the theory of double descent in supervised learning, although with specific differences.</p>

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The distributed nature of Federated Learning (FL) creates security-related vulnerabilities including training-time attacks. Recently, it has been shown that well-known Byzantine-resilient aggregation schemes are indeed vulnerable to an informed adversary who has access to the aggregation scheme and updates sent by clients. Therefore, it is a significant challenge to establish successful defense mechanisms against such an adversary. To the best of our knowledge, most current aggregators are immune to single or partial attacks and none of them is expandable to defend against new attacks. We frame the robust distributed learning problem as a game between a server and an adversary that tailors training-time attacks. We introduce RobustTailor, a simulation-based algorithm that prevents the adversary from being omniscient. RobustTailor is a mixed strategy and has good expandability for any deterministic Byzantine-resilient algorithm. Under a challenging setting with information asymmetry between two players, we show that our method enjoys theoretical guarantees in terms of regret bounds. RobustTailor preserves almost the same privacy guarantees as standard FL and robust aggregation schemes. Simulation improves robustness to training-time attacks significantly. Empirical results under challenging attacks validate our theory and show that RobustTailor preforms similar to an upper bound which assumes the server has perfect knowledge of all honest clients over the course of training. / Den distribuerade karaktären hos federerade maskininlärnings-system gör dem sårbara för cyberattacker, speciellt under tiden då systemen tränas. Nyligen har det visats att många existerande Byzantine-resilienta aggregeringssystem är sårbara för attacker från en välinformerad motståndare som har tillgång till aggregeringssystemet och uppdateringarna som skickas av klienterna. Det är därför en stor utmaning att skapa framgångsrika försvarsmekanismer mot en sådan motståndare. Såvitt vi vet är de flesta nuvarande aggregatorer immuna mot enstaka eller partiella attacker och ingen av dem kan på ett enkelt sätt utvidgas för att försvara sig mot nya attacker. Vi utformar det robusta distribuerade inlärningsproblemet som ett spel mellan en server och en motståndare som skräddarsyr attacker under träningstiden. Vi introducerar RobustTailor, en simuleringsbaserad algoritm som förhindrar att motståndaren är allvetande. RobustTailor är en blandad strategi med god expanderbarhet för alla deterministiska Byzantine-resilienta algoritmer. I en utmanande miljö med informationsasymmetri mellan de två spelarna visar vi att vår metod har teoretiska garantier i form av gränser för ånger. RobustTailor har nästan samma integritetsgarantier som standardiserade federerade inlärnings- och robusta aggregeringssystem. Vi illustrerar även hur simulering förbättrar robustheten mot attacker under träningstiden avsevärt. Empiriska resultat vid utmanande attacker bekräftar vår teori och visar att RobustTailor presterar på samma sätt som en övre gräns som förutsätter att servern har perfekt kunskap om alla ärliga klienter under utbildningens gång.

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Stressful experiences in early life can have profound and lasting impacts on phenotypic development. In anthropogenic environments, organisms are increasingly exposed to evolutionarily novel stressors that may play a major role in shaping the phenotypic variation upon which natural selection acts. For instance, ionizing radiation persists in areas affected by nuclear reactor accidents, nuclear weapons testing, and the nuclear power production process. This thesis explored the dose-response effects of early life ionizing radiation exposure on life- history traits in the cricket (Acheta domesticus L.). Specifically, this work had two goals: (1) to examine the effects of early life radiation stress on the potential tradeoff between growth and self-maintenance, and (2) to explore the dose-dependent effects of juvenile radiation exposure on adult trait expression (particularly fecundity, offspring investment, and offspring fitness). It was found that exposure to moderate doses of radiation in early development resulted in a slower juvenile growth rate but increased survival in early adulthood, suggesting that self- maintenance was prioritized over growth. Despite the strong inhibitory effects of early life radiation on adult female body mass, age-specific fecundity was negatively impacted only at relatively high radiation doses. Crickets exposed to moderate radiation doses in early development laid larger eggs in adulthood relative to controls and these eggs had a greater hatching success, suggesting that radiation exposure had transgenerational effects on offspring performance. No noticeable effects of early life radiation exposure were detected on total and non-enzymatic antioxidant capacity or hydrogen peroxide levels in adult females. Together, this research indicates that a single, acute exposure to ionizing radiation in early life can affect phenotypic development in a complex, dose-dependent manner and that rather than being purely negative, phenotypic responses can be sustained or even enhanced. / Thesis / Master of Science (MSc) / Stressful experiences in early life can have lasting impacts on organismal development, but the extent to which early life stress is harmful is unclear. In human-dominated environments, pollutants such as ionizing radiation can be a significant form of developmental stress. This thesis explores the fitness-related effects of early life ionizing radiation exposure in the cricket, Acheta domesticus. Impacts on growth, longevity, fecundity, and offspring fitness are explored. This research indicates that early life stress can affect phenotypic development in a complex, dose-dependent manner and that rather than being purely negative, responses can be sustained or even enhanced.

Syfte: Undersökningen syftar till att utifrån teorier kring kapitalstruktur och empiriska samband mellan skuldsättning och lönsamhet diskutera hur skuldsättning kan användas i ekonomistyrning. Metod: Undersökningen är gjord enligt kvantitativ forskningsmetod. Sekundärdata hämtas och analyseras med statistiska metoder. Resultaten diskuteras med teoretisk referensram. Slutsats :Studiens empiriska resultat visar på ett signifikant negativt samband mellan skuldsättning (​TSK ​ ) och lönsamhet (​ROA ​ ), samt ett signifikant positivt samband mellan skuldsättning (​TSK ​ ) och lönsamhet (​ROE ​ ). De empiriska resultaten tyder på att hur skuldsättning kan användas i ekonomistyrning beror på hur lönsamhet mäts. / Purpose: This study aims to; from theories of capital structure and empirical relations between debt and profitability discuss how debt can be used in management control. Method: This study follow quantitative research method. Secondary data is retrieved and analyzed by statistical methods. The results are discussed with the theoretical framework. Conclusion: Empirical results indicate a significant negative relationship between debt (​TSK ​ ) and profitability (​ROA ​ ), followed by a significant positive relationship between debt (​TSK ​ ) and profitability (​ROE ​ ). Empirical results further suggest that the measure of profitability is crucial for how debt can be used in management control.

In this work, new methods of feature extraction, feature selection, stochastic data characterization/modeling, variance reduction and measures for parametric discrimination are proposed. These methods have implications for data mining, machine learning, and information theory. A novel decision-support system is developed in order to guide intervention during cardiac arrest. The models are built upon knowledge extracted with signal-processing, non-linear dynamic and machine-learning methods. The proposed ECG characterization, combined with information extracted from PetCO2 signals, shows viability for decision-support in clinical settings. The approach, which focuses on integration of multiple features through machine learning techniques, suits well to inclusion of multiple physiologic signals. Ventricular Fibrillation (VF) is a common presenting dysrhythmia in the setting of cardiac arrest whose main treatment is defibrillation through direct current countershock to achieve return of spontaneous circulation. However, often defibrillation is unsuccessful and may even lead to the transition of VF to more nefarious rhythms such as asystole or pulseless electrical activity. Multiple methods have been proposed for predicting defibrillation success based on examination of the VF waveform. To date, however, no analytical technique has been widely accepted. For a given desired sensitivity, the proposed model provides a significantly higher accuracy and specificity as compared to the state-of-the-art. Notably, within the range of 80-90% of sensitivity, the method provides about 40% higher specificity. This means that when trained to have the same level of sensitivity, the model will yield far fewer false positives (unnecessary shocks). Also introduced is a new model that predicts recurrence of arrest after a successful countershock is delivered. To date, no other work has sought to build such a model. I validate the method by reporting multiple performance metrics calculated on (blind) test sets.