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<p>High-spin states in the oblate deformed odd-odd thallium nucleus ( ) 109 190 81 Tl have been investigated through the reaction 175Lu(20Ne, 5n)190Tl at a beam energy of 115 MeV. The gamma rays emitted from 190Tl nucleus were detected with Ge detectors using the AFRODITE array at iThemba LABS, South Africa. Gamma-gamma coincidence data were obtained and used to construct the level scheme. In this work, Directional Correlations from Oriented (DCO) state ratios and linear polarization anisotropies were measured in order to deduce spin and parity of energy levels in the decay scheme. It was possible to determine the spin and parity of two additional signature-partner bands which decay to the ground-state band.</p>

No description available.

In financial risk management it is essential to be able to model dependence in markets and portfolios in an accurate and efficient way. A high positive dependence between assets in a portfolio can be devastating, especially in times of crises, since losses will most likely occur at the same time in all assets for such a portfolio. The dependence is therefore directly linked to the risk of the portfolio. The risk can be estimated by several different risk measures, for example Value-at-Risk and Expected shortfall. This paper studies some different ways to measure risk and model dependence, both in a theoretical and empirical way. The main focus is on copulas, which is a way to model and construct complex dependencies. Copulas are a useful tool since it allows the user to separately specify the marginal distributions and then link them together with the copula. However, copulas can be quite complex to understand and it is not trivial to know which copula to use. An implemented copula model might give the user a "black-box" feeling and a severe model risk if the user trusts the model too much and is unaware of what is going. Another model would be to use the linear correlation which is also a way to measure dependence. This is an easier model and as such it is believed to be easier for all users to understand. However, linear correlation is only easy to understand in the case of elliptical distributions, and when we move away from this assumption (which is usually the case in financial data), some clear drawbacks and pitfalls become present. A third model, called historical simulation, uses the historical returns of the portfolio and estimate the risk on this data without making any parametric assumptions about the dependence. The dependence is assumed to be incorporated in the historical evolvement of the portfolio. This model is very easy and very popular, but it is more limited than the previous two models to the assumption that history will repeat itself and needs much more historical observations to yield good results. Here we face the risk that the market dynamics has changed when looking too far back in history. In this paper some different copula models are implemented and compared to the historical simulation approach by estimating risk with Value-at-Risk and Expected shortfall. The parameters of the copulas are also investigated under calm and stressed market periods. This information about the parameters is useful when performing stress tests. The empirical study indicates that it is difficult to distinguish the parameters between the stressed and calm market period. The overall conclusion is; which model to use depends on our beliefs about the future distribution. If we believe that the distribution is elliptical then a correlation model is good, if it is believed to have a complex dependence then the user should turn to a copula model, and if we can assume that history will repeat itself then historical simulation is advantageous.

This is a study to see the relationship between earnings per share and dividends during a period of both boom and depression. The study will focus on companies listed on Stockholm stock exchange and see if they follow theories from the past and if the dividend is smooth over times with a fluctuant economy. To see this we had this problem: Is it a relationship between earnings per share and dividend during a fluctuant economy, also if there is a difference between the different Caps on Stockholm stock exchange? We studied 163 stocks of the 293 listed stock on Stockholm stock exchange during a period of 8 years. The study is focused on the time period between year 2005 and year 2012. We used IBM SPSS statistics to see the correlation and regression between earnings per share and dividend and analysed that. We used Microsoft Excel to make graphs and analysed them. The study didn’t find any strong relationship between earnings per share and dividend. The strongest connection we found was for companies listed on Small Cap where the correlation was 0,461. The weakest connection that was found was for companies listed as Mid Cap where the correlation was 0,211. For companies listed as Large Cap the correlation was 0,283.

Iki šiol nėra bendro numerio atpažinimo algoritmo. Pateiktame dokumente analizuojamos esamų numerio atpažinimo algoritmų savybės, problemos. Pateiktas koreliacijos pagrindu grįstas algoritmas numerio vietos radimui bei numerio atpažinimui. / Till now there are no general license plate recognition algorithm. In the presented master paper: analysis of current licence plate recognition algorithms properties and problems. Correlation based licence plate locating and recognition algorithm.

Research in the field of non-viral gene delivery has demonstrated that a deeper understanding of the fundamental processes of nanoparticle assembly is required in order to improve their efficacy. While gemini nanoparticles (gemini NPs) and other non-viral delivery systems have been vigorously characterized using several techniques, our knowledge is still incomplete. The first objective of this study was the development of new methodology using fluorescence correlation spectroscopy (FCS) to investigate the stages of gemini NPs assembly. It was demonstrated that by labeling the plasmid, different stages of gemini NP assembly from the gemini-plasmid pre-complex (GP) to the final gemini nanoparticle (or gemini-plasmid-lipid complex; GPL), could be studied. Based on diffusion coefficients and particle numbers extrapolated from the autocorrelation function (ACF), FCS was able to determine that each phase of assembly had distinct characteristics. The FCS study using 12-3-12 gemini surfactant showed that both the diffusion coefficient and particle number of GPs (0.98??0.31 x 10-12 m2/s) was significantly lower than the final GPL (3.11??0.41 x 10-12 m2/s). Based on the Stokes-Einstein equation the particle size was calculated to be 300-500 nm for GP and 200-300 nm for GPLs. The raw intensity histograms showed that both GPs and GPLs are composed of multiple plasmids. Furthermore the study showed that the final GPLs contain fewer plasmids compared to the intermediate GP. FCS results were validated by using existing characterization methods including dynamic light scattering (DLS), zeta potential and dye exclusion assays. The second objective involved the detailed characterization of gemini NP. Nine different gemini surfactants and two different phospholipids were used in a systematic study to assess the effect of gemini surfactant and lipid structure on the final morphology of gemini NP. The study revealed that gemini surfactant structure had a strong effect on structure of GP intermediates, but addition of phospholipids resulted in the formation of uniform gemini NPs. Based on the results of this study a new model for GP and GPL assembly is proposed based on the formation of supramolecular aggregates of gemini-plasmids, governed by gemini surfactant chemical structure, and dispersed by phospholipids to form GPLs.

Graduate / 0485

During the past decade research has shown that global warming may have disastrous effects on our planet. In order to limit the damage that the human race seems to be causing, it was acknowledged that substances with a high global warming potential (GWP) should be phased out. In due time, R-134a with a GWP = 1300, may probably be phased out to make way for nature friendly refrigerants with a lower GWP. One of these contenders is carbon dioxide, R-744, with a GWP = 1. Literature revealed that various Nusselt number (Nu) correlations have been developed to predict the convection heat transfer coefficients of supercritical R-744 in cooling. No proof could be found that any of the reported correlations accurately predict Nusselt numbers (Nus) and the subsequent convection heat transfer coefficients of supercritical R-744 in cooling. Although there exist a number of Nu correlations that may be used for R-744, eight different correlations were chosen to be compared in a theoretical simulation program forming the first part of this study. A water-to-transcritical R-744 tube-in-tube heat exchanger was simulated. Although the results emphasise the importance of finding a more suitable Nu correlation for cooling supercritical R-744, no explicit conclusions could be made regarding the accuracy of any of the correlations used in this study. For the second part of this study experimental data found in literature were used to evaluate the accuracy of the different correlations. Convection heat transfer coefficients, temperatures, pressures and tube diameter were employed for the calculation of experimental Nusselt numbers (Nuexp). The theoretical Nu and Nuexp were then plotted against the length of the heat exchanger for different pressures. It was observed that both Nuexp and Nu increase progressively to a maximal value and then decline as the tube length increases. From these results it were possible to group correlations according to the general patterns of their Nu variation over the tube length. Graphs of Nuexp against Nus, calculated according to the Gnielinski correlation, generally followed a linear regression, with R2 > 0.9, when the temperature is equal or above the pseudocritical temperature. From this data a new correlation, Correlation I, based on average gradients and intersects, was formulated. Then a modification on the Haaland friction factor was used with the Gnielinski correlation to yield a second correlation, namely Correlation II. A third and more advanced correlation, Correlation III, was then formulated by employing graphs where gradients and y-intercepts were plotted against pressure. From this data a new parameter, namely the turning point pressure ratio of cooling supercritical R-744, was defined. It was concluded that the employed Nu correlations under predict Nu values (a minimum of 0.3% and a maximum of 81.6%). However, two of the correlations constantly over predicted Nus at greater tube lengths, i.e. below pseudocritical temperatures. It was also concluded that Correlation III proved to be more accurate than both Correlations I and II, as well as the existing correlations found in the literature and employed in this study. Correlation III Nus for cooling supercritical R-744 may only be valid for a diameter in the order of the experimental diameter of 7.73 mm, temperatures that are equal or above the pseudocritical temperature and at pressures ranging from 7.5 to 8.8 MPa. / Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2010.

Microhemodynamics is the study of blood flow in small vessels, usually on the order of 50 to 100 µm. The in vitro study of blood flow in small channels is analogous to the in vivo study of the microcirculation. At this scale the Reynolds and Womersly numbers are significantly less than 1 and the viscous stress and pressure gradient are the main determinant of flow. Blood is a non-homogeneous, non-Newtonian fluid and this complex composition and behavior has a greater impact at the microscale. A key parameter is the shear stress at the wall, which is involved in many processes such as platelet activation, gas exchange, embryogenesis and angiogenesis. In order to measure the shear rate in these blood flows the velocity profile must be measured. The measured profile can be characterized by the maximum velocity, the flow rate, the shear rate at the wall, or a shape parameter reflecting the bluntness of the velocity profile. The technique of micro-particle image velocimetry (µPIV) was investigated to measure the velocity profiles of blood microflows. The material of the channel, the type of tracer particles, the camera used, and the choice in data processing were all validated to improve the overall accuracy of µPIV as a blood microflow measurement method. The knowledge gained through these experiments is of immediate interest to applications such as the design of lab-on-a-chip components for blood analysis, analysis of blood flow behavior, understanding the shear stress on blood in the microcirculation and blood substitute analysis. Polymer channels were fabricated from polydimethylsiloxane (PDMS) by soft lithography in a clean room. PDMS was chosen for ease of fabrication and biocompatibility. The contacting properties of saline, water, and blood with various polymer channel materials was measured. As PDMS is naturally hydrophilic, surface treatment options were explored. Oxygenated plasma treatment was found to be less beneficial for blood than for water. The choice of camera and tracer particles were validated. Generally, for in vivo studies, red blood cells (RBCs) are used as tracer particles for the µPIV method, while for in vitro studies, artificial fluorescent micro particles are added to the blood. It is demonstrated here that the use of RBCs as tracer particles creates a large depth of correlation (DOC), which can approach the size of vessel itself and decreases the accuracy of the method. Next, the accuracy of each method is compared directly. Pulsed images used in conjunction with fluorescing tracer particles are shown to give results closest to theoretical approximations. The effect of the various post-processing methods currently available were compared for accuracy and computation time. It was shown that changing the amount of overlap in the post-processing parameters affects the results by nearly 10%. Using the greatest amount of correlation window overlap with elongated windows aligned with the flow was shown to give the best results when coupled with a image pre-processing method previously published for microflows of water. Finally the developed method was applied to a relevant biomedical engineering problem: the evaluation of blood substitutes and blood viscosity modifiers. Alginate is a frequently used viscosity modifier which has many uses in industry, including biomedical applications. Here the effect of alginate on the blood rheology, i.e., the shape of the velocity profile and the maximum velocity of blood flow in microchannels, was investigated. Alginate was found to blunt the shape of the velocity profile while also decreasing the shear rate at the wall. Overall, the accuracy of µPIV measurements of blood flows has been improved by this thesis. The work presented here has extended the known methods and accuracy issues of blood flow measurements in µPIV, improved the understanding of the blood velocity profile behavior, and applied that knowledge and methods to interesting, relevant problems in biomedical and biofluids engineering.