L-serine, a non-essential amino acid, plays a role in the biosynthesis of the amino acids, proteins, purine and pyrimidine nucleotides. It is important for the proper functioning of the nervous system. It has been considered in the treatment of patients with schizophrenia, depression, chronic fatigue syndrome and psychomotor retardation, and of the seizures encountered in patients with rare inborn errors of L-serine biosynthesis. However, there are no reports in the literature of the direct cardiovascular effects of L-serine. Using normotensive Sprague-Dawley rats, Sprague-Dawley rats rendered hypertensive by chronic treatment with the nitric oxide (NO) synthase inhibitior NG nitro L-arginine methyl ester (L-NAME) and spontaneously hypertensive rats (SHR), the present study examined the in vitro and in vivo effects of L-serine. In vitro studies focused on L-serine induced changes in phenylephrine constricted third order branches of rat mesenteric arterioles while the in vivo studies examined the effects of intravenous infusion of L-serine on mean arterial pressure (MAP) and heart rate (HR) in intact anaesthetized rats. L-serine (10 to 200 µmol/L) evoked concentration-dependent vasodilatation in phenylephrine constricted endothelium-intact, but not in endothelium-denuded, rat mesenteric arterioles. The vasodilator responses to L-serine were absent in the combined presence of apamin, a calcium activated small conductance potassium (SKCa) channel inhibitor, and TRAM-34, a calcium activated intermediate conductance potassium (IKCa) channel inhibitor, or ouabain, a sodium pump inhibitor and barium (Ba2+), an inward rectifying potassium (Kir) channel inhibitor, or when the vessels were depolarized by potassium chloride. The maximal vasodilatation response (Emax) to L-serine was higher in vessels from L-NAME treated rats (40%) than from control rats (20%). In anesthetized rats, L-serine evoked a rapid, reversible, dose-dependent fall in MAP (without a significant change in HR), which was more pronounced in L-NAME treated rats (> 60 mmHg) than in normotensive control rats (25 mmHg). The fall in MAP was inhibited (p<0.01) by apamin plus charybdotoxin pretreatment. Charybdotoxin was used in place of Tram-34 in in vivo studies since Tram-34 is not soluble in water or saline. In age matched Sprague-Dawley, Wistar-Kyoto (WKY) and SHR strains, D-serine had the same effects on MAP and HR as L-serine; however, L-serine evoked a greater maximal fall in MAP in all strains, and the effect was more pronounced in hypertensive rats. In contrast, the infusion of glycine, a metabolite of L-serine led to a dose-dependent fall in MAP in normotensive rats but a dose-dependent increase in MAP in both SHR and L-NAME treated hypertensive WKY rats. Both the depressor and pressor responses to glycine were abolished by pretreatment with the N-methyl D-aspartate receptor antagonist, MK-801. Regional hemodynamic studies performed using the fluorescent tagged microsphere distribution technique revealed that the fall in MAP and profound decrease in total peripheral resistance (TPR) evoked by acute L-serine infusion is due to increased blood flow in the splanchnic region and more particularly in the small intestinal vascular beds. This effect is blocked by the combined treatment with the KCa channel inhibitors, apamin plus charybdotoxin. Although resting MAP and TPR are higher, and cardiac output (CO) is lower both in SHR and in WKY rats rendered hypertensive by L-NAME treatment compared to normotensive WKY rats, L-serine infusion leads to a rapid fall in TPR and MAP, and an increase in CO in all models. This effect was more profound in the hypertensive rats. These findings suggest that L-serine could be helpful in overcoming splanchnic organ failure observed in patients with cardiopulmonary bypass. In addition, L-serine, either alone or in combination with other antihypertensive medications, could be considered in the management of endothelial dysfunctional states with reduced NO bioavailability such as hypertension and diabetes.

This thesis has applied the theory of real options to study forestry investment decision-making under stochastic timber prices. Suitable models have been developed for the stochastic timber prices, after addressing major issues in characterisation of the price process. First, the assumption of stochastic timber price process was based on detailed unit root tests, incorporating structural breaks in time-series analysis. The series was found to be stationary around shifting mean, justifying the assumption of mean reversion model. Due to shift in the mean, long-run mean to which the prices tended to revert could not be assumed constant. Accordingly, it was varied in discreet steps as per the breaks identified in the tests. The timber price series failed the normality test implying fat tails in the data. To account for these fat tails, ‘jumps’ were incorporated in the mean reversion model. The results showed that the option values for the jump model were higher than the mean reversion model and threshold levels for investment implied different optimal paths. Ignoring jumps could provide sub-optimal results leading to erroneous decisions. Second, the long-run mean to which prices reverted was assumed to shift continuously in a random manner. This was modeled through the incorporation of stochastic level and slope in the trend of the prices. Since the stochastic level and slope were not observable in reality, a Kalman-filter approach was used for the estimation of model parameters. The price forecasts from the model were used to estimate option values for the harvest investment decisions. Third, investment in a carbon sequestration project from managed forests was evaluated using real options, under timber price stochasticity. The option values and threshold levels for investment were estimated, under baseline and mitigation scenarios. Results indicated that carbon sequestration from managed forests might not be a viable investment alternative due to existing bottlenecks. Overall, the research stressed upon the need for market information and adaptive management, with a pro-active approach, for efficient investment decisions in forestry.

No description available.

In this thesis, we solve a mean-variance portfolio optimization problem with portfolio constraints under a regime-switching model. Specifically, we seek a portfolio process which minimizes the variance of the terminal wealth, subject to a terminal wealth constraint and convex portfolio constraints. The regime-switching is modeled using a finite state space, continuous-time Markov chain and the market parameters are allowed to be random processes. The solution to this problem is of interest to investors in financial markets, such as pension funds, insurance companies and individuals. We establish the existence and characterization of the solution to the given problem using a convex duality method. We encode the constraints on the given problem as static penalty functions in order to derive the primal problem. Next, we synthesize the dual problem from the primal problem using convex conjugate functions. We show that the solution to the dual problem exists. From the construction of the dual problem, we find a set of necessary and sufficient conditions for the primal and dual problems to each have a solution. Using these conditions, we can show the existence of the solution to the given problem and characterize it in terms of the market parameters and the solution to the dual problem. The results of the thesis lay the foundation to find an actual solution to the given problem, by looking at specific examples. If we can find the solution to the dual problem for a specific example, then, using the characterization of the solution to the given problem, we may be able to find the actual solution to the specific example. In order to use the convex duality method, we have to prove a martingale representation theorem for processes which are locally square-integrable martingales with respect to the filtration generated by a Brownian motion and a finite state space, continuous-time Markov chain. This result may be of interest in problems involving regime-switching models which require a martingale representation theorem.

Several magnetic materials, in the first approximation, can be described by idealised theoretical models, such as classical Ising or Heisenberg spin systems, and, to some extent, such models are able to qualitatively expose many experimentally observed phenomena. But often, to account for complex behavior of magnetic matter, such models have to be refined by including more terms in Hamiltonian. The compound LiHo_xY_{1-x}F_4, by increasing concentration of nonmagnetic yttrium can be tuned from a diluted ferromagnet to a spin glass. LiHoF_4 is a good realisation of the transverse field Ising model, the simplest model exhibiting a quantum phase transition. In the pure case the magnetic behaviour of this material is well described by mean-field theory. It was believed that when diluted, LiHo_xY_{1-x}F_4 would also manifest itself as a diluted transverse field Ising model which continue to be well described by mean-field theory, and, at sufficient dilution, at zero temperature, exhibit a quantum spin-glass transition. The experimental data did not support such a scenario, and it was pointed out that, to explain physics of LiHo_xY_{1-x}F_4 in transverse magnetic field, the effect of a transverse-field-generated longitudinal random field has to be considered. We explore this idea further in local mean-field studies in which all three parameters: temperature, transverse field and concentration can be consistently surveyed, and where the transverse-field-generated longitudinal random field is explicitly present in the effective spin-1/2 Hamiltonian. We suggest other materials that are possible candidates for studying quantum criticality in the transverse field Ising model, and in the diluted case, for studying the effects of transverse and longitudinal random fields. The compounds we consider are RE(OH)_3, where RE are the rare earth ions Tb^{3+}, Dy^{3+} and Ho^{3+}. Using mean-field theory, we estimate the values of the transverse magnetic field that, at zero temperature, destroy ferromagnetic order to be B_x^c=4.35 T, B_x^c=5.03 T and B_x^c=54.81 T for Ho(OH)_3, Dy(OH)_3 and Tb(OH)_3, respectively. We confirm that Ho(OH)_3 and Tb(OH)_3, similarly to LiHoF_4, can be described by an effective spin-1/2 Hamiltonian. In the case of Dy(OH)_3 there is a possibility of a first order phase transition at transverse field close to B_x^c, and Dy(OH)_3 cannot be described by a spin-1/2 effective Hamiltonian. While diluted dipolar Ising spin glass has been studied experimentally in LiHo_xY_{1-x}F_4 and in numerical simulations, there are no studies of the Heisenberg case. Example materials that are likely candidates to be realisations of the diluted dipolar Heisenberg spin glass are (Gd_xY_{1-x})_2Ti_2O_7, (Gd_xY_{1-x})_2Sn_2O_7 and (Gd_xY_{1-x})_3Ga_5O_{12}. To stimulate interest in experimental studies of these systems we present results of Monte of Carlo simulations of the diluted dipolar Heisenberg spin glass. By performing finite-size scaling analysis of the spin-glass correlation length and the spin-glass susceptibility, we provide a compelling evidence of a thermodynamical spin-glass transition in the model. Frustrated pyrochlore magnets, depending on the character of single ion anisotropy and interplay of different types of interaction over a broad range of energy scales, exhibit a large spectrum of exotic phases and novel phenomena. The pyrochlore antiferromagnet Er_2Ti_2O_7 is characterised by a strong planar anisotropy. Experimental studies reveal that Er_2Ti_2O_7 undergoes a continuous phase transition to a long-range ordered phase with a spin configuration that, in this thesis, is referred to as the Champion-Holdsworth state. Such results are not in agreement with the theoretical prediction that the ground state of the pyrochlore easy-plane antiferromagnet with dipolar interactions complementing the nearest neighbour exchange interactions, is not the Champion-Holdsworth state but the so-called Palmer-Chalker state. On the other hand, Monte Carlo simulations of the easy-plane pyrochlore antiferromagnet indicate a thermal order-by-disorder selection of the Champion-Holdsworth state. To answer the question of whether order-by-disorder selection can be the mechanism at play in Er_2Ti_2O_7, we performed Monte Carlo simulations of the easy-plane pyrochlore antiferromagnet with weak dipolar interactions. We estimate the range strengths of the dipolar interaction such that order-by-disorder selection of the Champion-Holdsworth state is not suppressed. The estimated value of the allowed strength of the dipolar interactions indicates that the model studied is likely insufficient to explain the physics of Er_2Ti_2O_7 and other types of interactions or quantum effects should be considered.

Detta arbete utförs efter en förfrågan från Uddeholm Tooling om att försöka kartlägga riskerna på inköpsmarknaden för metallerna krom, molybden och vanadin. Då detta anses vara mycket svårt föreslås här istället en kartläggning av marknaden för respektive metall, detta för att ge en bild av hur marknaden ser ut och vilka aktörer som finns.Frågorna som behandlas är var bryts, förädlas, konsumeras respektive metall? Hur varierar priserna, beskrivs priserna bäst med en random walk eller med en mean reverting stokastisk process.Det visar sig relativt snart att det är mycket problematiskt att inhämta relevant data. Speciellt då dessa metaller inte handlas öppet utan där kontrakten mellan köpare och säljare är konfidentiella. Priserna som rapporteras baseras på månatliga intervjuer med köpare, säljare och traders som utförs av branschmagasin. Detta leder till att det rapporterade priset ofta är stationärt under långa tidsperioder, det kan emellertid antas att det reella priset är betydligt mer volatilt och förändras från dag till dag. Dessa metaller kan även handlas i olika typer av föreningar och med olika renhetsgrader vilket ytligare försvårar studierna. Då det inte finns en marknadsplats där metallerna kan handlas kan även antagas att priset kan skilja sig beroende på var och av vem man köper.Detta leder till att det statistiska test som genomfördes i denna studie fick ett ofullständigt resultat, med låg korrelation mellan modell och verklighet. Det gick därför inte att avgöra om priset kan beskrivas som mean reverting. Andra studier pekar dock på att mean reversion är en mer träffsäker stokastisk process för att beskriva priserna på dessa metaller än vad än random walk är.En kartläggning av marknaden för dessa metaller visar tydligt att Kina är en signifikant aktör i samtliga fall. Då alla tre metaller främst används som legeringsämne i konstruktions- och rostfrittstål har dessa marknader stor betydelse för marknaden för respektive metall. Kina är den största konsumenten och producenten av både rostfritt och konstruktionsstål, dessutom är Kina stora vid framställningen av respektive metall. Resultatet visar på tydliga kopplingar mellan priset på respektive metall och på Kinas ökande konsumtion av stål.

In this thesis, a new algorithm has been proposed to segment the foreground of the fingerprint from the image under consideration. The algorithm uses three features, mean, variance and coherence. Based on these features, a rule system is built to help the algorithm to efficiently segment the image. In addition, the proposed algorithm combine split and merge with modified Otsu. Both enhancements techniques such as Gaussian filter and histogram equalization are applied to enhance and improve the quality of the image. Finally, a post processing technique is implemented to counter the undesirable effect in the segmented image. Fingerprint recognition system is one of the oldest recognition systems in biometrics techniques. Everyone have a unique and unchangeable fingerprint. Based on this uniqueness and distinctness, fingerprint identification has been used in many applications for a long period. A fingerprint image is a pattern which consists of two regions, foreground and background. The foreground contains all important information needed in the automatic fingerprint recognition systems. However, the background is a noisy region that contributes to the extraction of false minutiae in the system. To avoid the extraction of false minutiae, there are many steps which should be followed such as preprocessing and enhancement. One of these steps is the transformation of the fingerprint image from gray-scale image to black and white image. This transformation is called segmentation or binarization. The aim for fingerprint segmentation is to separate the foreground from the background. Due to the nature of fingerprint image, the segmentation becomes an important and challenging task. The proposed algorithm is applied on FVC2000 database. Manual examinations from human experts show that the proposed algorithm provides an efficient segmentation results. These improved results are demonstrating in diverse experiments.

The purpose of this thesis is to evaluate five different volatility forecasting models that are used to calculate financial market risk. The models are used on both daily exchange rates and high-frequency intraday data from four different series. The results show that time series models fitted to high-frequency intraday data together with a critical value taken from the empirical distribution displayed the best forecasts overall.

Having an engine model that is accurate but not too complicated is desirable when working with on-board diagnosis or engine control. In this thesis a four state mean value model is introduced. To make the model usable in an on-line automotive application it is discrete and simulated with a fixed step size solver. Modelling is done with simplicity as main object. Some simple static models are also presented. To validate the model measuring is carried out in a Scania R124LB truck with a 12 liter six-cylinder turbo charged diesel engine. In general, for this relatively simple model, the mean errors must be considered low. The inlet manifold pressure mean error during highway driving is 3.4\%.

Over the last years, the emission and on board diagnostics legislations for heavy duty trucks are getting more and more strict. An accurate engine model that is possible to execute in the engine control system enables both better diagnosis and lowered emissions by better control strategies. The objective of this thesis is to extend an existing mean value diesel engine model, to include turbo compound. The model should be physical, accurate, modular and it should be possible to execute in real time. The calibration procedure should be systematic, with some degree of automatization. Four different turbo compound models have been evaluated and two models were selected for further evaluation by integration with the existing model. The extended model showed to be quite insensitive to small errors in the compound turbine speed and hence, the small difference in accuracy of the tested models did not affect the other output signals significantly. The extended models had better accuracy and could be executed with longer step length than the existing model, despite that more complexity were added to the model. For example, the mean error of the intake manifold pressure at mixed driving was approximately 3.0%, compared to 5.8% for the existing model. The reasons for the improvements are probably the good performance of the added submodels and the systematic and partly automatized calibration procedure including optimization.