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Resveratrol is a naturally occurring phytoalexin of the stilbene family produced by various plants in response to stress, UV radiation, and fungal attack. It is primarily found in peanuts, berries, grape skin, and red wine. Resveratrol has been found to exhibit anti-cancer, anti-inflammatory, anti-aging, and anti-oxidant properties. Research indicates that diets enriched with resveratrol containing substances result in less incidence of cancer. Unfortunately, the low bioavailability and solubility has been a huge setback for its potential prospects. As a result, efforts have been made to synthesize derivatives of resveratrol with increased solubility and bioavailability. Three triester novel resveratrol derivatives 3, 4’, 5-tri (benzoyloxy) stilbene, 3, 4’, 5-tri (toluyloxy) stilbene and 3, 4’, 5-tri (2”-butenoyloxy) stilbene have been synthesized by esterification process that can further be subjected for biological evaluation. Structures and purities of all newly synthesized derivatives were confirmed by 1H, 13C NMR spectroscopy and infrared spectroscopy.

A population of financial derivatives can be compressed if a subset of derivatives yield a net cash flow that lies within a given tolerance level between the parties involved. To conduct a correct population compression, it is essential that all derivatives of the involved parties are present in the derivative set. The current state-of-the-art to ensure this is to have analysts with domain expertise analyzing the populations with the use of assisting tools. The purpose of this project was to automate this process through the use of machine learning classification. Different ways of using clustering for representing a collection of derivatives was implemented and evaluated. The first representation derives from a clustering of all derivatives across populations, describing the distribution of the derivatives across the clusters. A second representation uses the previously mentioned clustering to instead find the distance from a population to all the clusters to form a vector. These representations were compared to two naive representations, one where the mean derivative of a population is used as representation and one where a random clustering is used to find a distribution. The representations were evaluated through classification, using three different classification models (Support Vector Machine, Decision Tree, and a Naive Bayes' Classifier). Different models were tested to examine whether the representations generalize across models. Both the proposed representations were found to be comparable with the naive representations, indicating that the representations fail to capture the characteristics of missing derivatives. The cause of this was found to be that populations of derivatives vary too much for clustering to be consistent enough across populations. / En population av finansiella derivat kan komprimeras om en delmängd av derivat ger ett nettokassaflöde mellan de berörda parterna som ligger inom ett givet toleransintervall. För att göra en korrekt kompression är det viktigt att alla derivat med de involverade parterna finns närvarande i derivatuppsättningen. I nuläget används analytiker som med domänkompetens och erfarenhet kan analysera populationen med hjälp utav verktyg. Syftet med detta projekt var att undersöka om det är möjligt att automatisera denna process genom att använda maskininlärningsklassificering. Olika sätt att använda klustring för att representera en samling derivat implementerades och utvärderades. Den första representationen klustrar alla derivat över populationer och representerar en population med en vektor som beskriver fördelningen av derivaten över kluster. En andra representation använder den tidigare nämnda klustringen för att istället hitta avståndet från populationen som ska representeras till alla kluster för att bilda en vektor. Dessa representationer jämfördes med två naiva representationer, en där det genomsnittliga derivatet av en population används som representation och en där en slumpmässig klustring används för att hitta en distribution likt den först beskrivna representationen. Representationerna utvärderades genom klassificering med tre olika klassificeringsmodeller (stödvektormaskiner, beslutsträd och en naiv Bayesklassificierare). Olika modeller testades för att utvärdera hur representationerna generaliserar över modeller. Båda de föreslagna representationerna visade sig prestera i linje med de naiva representationerna, vilket indikerar att representationerna misslyckas med att fånga kännetecknen för saknade derivat. Orsaken till detta tycks vara att varje uppsättning av derivat är så unik att klustring av derivaten blir för olik baserat på vilken uppsättning man använder.

Open Source Hardware (OSHW) is a concept where hardware designs are shared for everyone to use, modify and build upon. This have become a widespread phenomenon in the microcontroller industry and created an ecosystem where users and companies produce various “derivatives” or alternative designs based on existing OSHW. This research explores this phenomenon of derivative development between users and producers and how this affects innovation, by exploring three case studies of user developed derivatives and interviews with producers and various people with OSHW background. This thesis found that this ecosystem to be dependent on Open Source and leverages the interest of users motivation to innovate and producer support. Furthermore, eight different factor were discovered that derivative development affecting innovation. (1) Openness & Transparency allows the user to innovate without fearing consequences of IP infringement and establishing trust. The transparency also increases the chances for the users to become innovators, as it facilitates the understanding of products, through the documentations and information sharing. (2) Support from producers facilitates users’ ability to design and innovate and was found crucial for the emergence of derivative designs. (3) Amplified Motivation through personal interest has a high impact in the innovation of open microcontrollers. (4) Market diffusion through low-cost ways of sharing and diffusing designs. (5) Market expansion increasing the number of derivative development can affect the resources used by producers in their development process. (6) Product improvements are affected, because of the vast feedback provided by the community, which can lead to through the discovery of usage in fields, product functionality. This increases the quality of the product and allows OSHW producers to stay competitive. (7) Collaboration can affect innovation by the collaborations with derivative projects and businesses. (8) Brand and Marketing is affecting by the number of users that use producers’ products for user-innovators development of derivative designs.

Nonsmoothness appears in various applications in chemical engineering, including multi-stream heat exchangers, nonsmooth flash calculation, process integration. In terms of numerical approaches, convex/concave relaxations of static and dynamic systems may also exhibit nonsmoothness. These relaxations are used in deterministic methods for global optimization. This thesis presents several new theoretical results for nonsmooth sensitivity analysis, with an emphasis on convex relaxations. Firstly, the "compass difference" and established ODE results by Pang and Stewart are used to describe a correct subgradient for a nonsmooth dynamic system with two parameters. This sensitivity information can be computed using standard ODE solvers. Next, this thesis also uses the compass difference to obtain a subgradient for the Tsoukalas-Mitsos convex relaxations of composite functions of two variables. Lastly, this thesis develops a new general subgradient result for Tsoukalas-Mitsos convex relaxations of composite functions. This result does not limit on the dimensions of input variables. It gives the whole subdifferential of Tsoukalas-Mitsos convex relaxations. Compare to Tsoukalas-Mitsos’ previous subdifferential results, it does not require additionally solving a dual optimization problem as well. The new subgradient results are extended to obtain directional derivatives for Tsoukalas-Mitsos convex relaxations. The new subgradient results and directional derivative results are computationally approachable: subgradients in this article can be calculated both by the vector forward AD mode and reverse AD mode. A proof-of-concept implementation in Matlab is discussed. / Thesis / Master of Applied Science (MASc)

<p> A series of derivatives of thiazolidine-4-carboxylic acid was prepared from two sulfur containing aminoacids, cysteine and D-penicillamine. Cysteine is very easily oxidized to a disulfide, while penicillamine is less susceptible to oxidation of the sulfhydryl group because of greater steric hindrance. Sulfhydryl aminoacids react readily with aldehydes and ketones to give thiazolidine rings with varying degrees of substitution.</p> <p> Many of the compounds prepared were studied in solution and in the solid state by means of nmr, vibrational spectroscopy, mass spectra and X-ray crystallographic data. Thiazolidine-4-carboxylic acids contain a free carboxyl group and a secondary amino group, both of which can be ionized. Infrared spectra and X-ray crystallography are useful in detecting ionization and hydrogen bonds. An example is given of a compound that can exist in both the zwitterion and the non ionized state depending on the solvent of recrystallization.</p> <p> From previous work in our group we were predicting that increasing steric crowding in the thiazolidine ring in close proximity to the ionizable groups would decrease the tendency of these molecules to ionize. No such simple relationship could be found.</p> / Thesis / Master of Science (MSc)

With the discontinuation of Interbank Offered Rates(IBOR), traders found some al-ternative reference rates to replace IBOR. Backward-looking rates are widely accepted new benchmark interest rates. In this thesis, we introduce and subsequently proceed to explore backward-looking rate model and continue doing some re-valuation of interest rate instruments under the backward-looking rates framework.

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