Vaccine-Induced Linear Epitope-Specific Antibodies to Simian Immunodeficiency Virus SIVmac239 Envelope Are Distinct from Those Induced to the Human Immunodeficiency Virus Type 1 Envelope in Nonhuman Primates.

To evaluate antibody specificities induced by simian immunodeficiency virus (SIV) versus human immunodeficiency virus type 1 (HIV-1) envelope antigens in nonhuman primate (NHP), we profiled binding antibody responses to linear epitopes in NHP studies with HIV-1 or SIV immunogens. We found that, overall, HIV-1 Env IgG responses were dominated by V3, with the notable exception of the responses to the vaccine strain A244 Env that were dominated by V2, whereas the anti-SIVmac239 Env responses were dominated by V2 regardless of the vaccine regimen.

Time-Varying Benefits of International Diversification for Finnish Investor: Country-Specific Strategy Concentrating on Emerging Markets

The main objective of this study is to investigate whether the Finnish investors’ country-specific strategy concentrating on emerging markets provides diversification benefits. We also analyze whether the benefits of international diversification has been diminished after periods of high volatility caused by different market crisis. The objective is investigated with three methods: Correlation coefficients, rolling correlations added with OLS trend-lines and Box’s M statistic. All the empirical tests are analyzed and calculated with logarithmic returns of weekly time series data from Friday closing values between January 1995 and December 2007. The number of weekly observations is 678. The data type is total return indices of different countries. Data is collected from DataStream and provided by Datastream Financial. Countries investigated are Finland, Argentina, Brazil, Chile, China, India, Mexico, Poland, Russia, South Africa, South Korea, Thailand and Turkey. The current data is quoted both in U.S. Dollars and local currencies. The empirical results of this thesis show that the correlation coefficients are time-varying across Finland and 12 emerging market countries. Although the correlations have risen from 1995 to 2007, there can be found sub-periods where the correlation has declined from earlier period. The results also indicate that a Finnish investor constructing a portfolio of emerging market countries cannot rely on the correlation coefficients estimated from historical data because of the instability of correlation matrices.

The octagon, the hendecagon and the approximation of pi: the geometric design of the clypeus in the enclosure of Imperial cult in Tarraco

The ancient temple dedicated to the Roman Emperor Augustus on the hilltop of Tarraco (today’s Tarragona), was the main element of the sacred precinct of the Imperial cult. It was a two hectare square, bordered by a portico with an attic decorated with a sequence of clypeus (i.e. monumental shields) made with marble plates from the Luni-Carrara’s quarries. This contribution presents the results of the analysis of a three-dimensional photogrammetric survey of one of these clipeus, partially restored and exhibited at the National Archaeological Museum of Tarragona. The perimeter ring was bounded by a sequence of meanders inscribed in a polygon of 11 sides, a hendecagon. Moreover, a closer geometric analysis suggests that the relationship between the outer meander rim and the oval pearl ring that delimited the divinity of Jupiter Ammon can be accurately determined by the diagonals of an octagon inscribed in the perimeter of the clypeus. This double evidence suggests a combined layout, in the same design, of an octagon and a hendecagon. Hypothetically, this could be achieved by combining the octagon with the approximation to Pi used in antiquity: 22/7 of the circle’s diameter. This method allows the drawing of a hendecagon with a clearly higher precision than with other ancient methods. Even the modelling of the motifs that separate the different decorative stripes corroborates the geometric scheme that we propose.

The effect of skewness and kurtosis on the Kenward-Roger approximation when group distributions differ

This study examined the independent effect of skewness and kurtosis on the robustness of the linear mixed model (LMM), with the Kenward-Roger (KR) procedure, when group distributions are different, sample sizes are small, and sphericity cannot be assumed. Methods: A Monte Carlo simulation study considering a split-plot design involving three groups and four repeated measures was performed. Results: The results showed that when group distributions are different, the effect of skewness on KR robustness is greater than that of kurtosis for the corresponding values. Furthermore, the pairings of skewness and kurtosis with group size were found to be relevant variables when applying this procedure. Conclusions: With sample sizes of 45 and 60, KR is a suitable option for analyzing data when the distributions are: (a) mesokurtic and not highly or extremely skewed, and (b) symmetric with different degrees of kurtosis. With total sample sizes of 30, it is adequate when group sizes are equal and the distributions are: (a) mesokurtic and slightly or moderately skewed, and sphericity is assumed; and (b) symmetric with a moderate or high/extreme violation of kurtosis. Alternative analyses should be considered when the distributions are highly or extremely skewed and samples sizes are small.

Application of intravoxel incoherent motion perfusion imaging to shoulder muscles after a lift-off test of varying duration.

Intravoxel incoherent motion (IVIM) MRI is a method to extract microvascular blood flow information out of diffusion-weighted images acquired at multiple b-values. We hypothesized that IVIM can identify the muscles selectively involved in a specific task, by measuring changes in activity-induced local muscular perfusion after exercise. We tested this hypothesis using a widely used clinical maneuver, the lift-off test, which is known to assess specifically the subscapularis muscle functional integrity. Twelve shoulders from six healthy male volunteers were imaged at 3 T, at rest, as well as after a lift-off test hold against resistance for 30 s, 1 and 2 min respectively, in three independent sessions. IVIM parameters, consisting of perfusion fraction (f), diffusion coefficient (D), pseudo-diffusion coefficient D* and blood flow-related fD*, were estimated within outlined muscles of the rotator cuff and the deltoid bundles. The mean values at rest and after the lift-off tests were compared in each muscle using a one-way ANOVA. A statistically significant increase in fD* was measured in the subscapularis, after a lift-off test of any duration, as well as in D. A fD* increase was the most marked (30 s, +103%; 1 min, +130%; 2 min, +156%) and was gradual with the duration of the test (in 10(-3) mm(2) /s: rest, 1.41 ± 0.50; 30 s, 2.86 ± 1.17; 1 min, 3.23 ± 1.22; 2 min, 3.60 ± 1.21). A significant increase in fD* and D was also visible in the posterior bundle of the deltoid. No significant change was consistently visible in the other investigated muscles of the rotator cuff and the other bundles of the deltoid. In conclusion, IVIM fD* allows the demonstration of a task-related microvascular perfusion increase after a specific task and suggests a direct relationship between microvascular perfusion and the duration of the effort. It is a promising method to investigate non-invasively skeletal muscle physiology and clinical perfusion-related muscular disorders.

Classification of textures seen from different distances and under varying illumination direction

Changes in the angle of illumination incident upon a 3D surface texture can significantly alter its appearance, implying variations in the image texture. These texture variations produce displacements of class members in the feature space, increasing the failure rates of texture classifiers. To avoid this problem, a model-based texture recognition system which classifies textures seen from different distances and under different illumination directions is presented in this paper. The system works on the basis of a surface model obtained by means of 4-source colour photometric stereo, used to generate 2D image textures under different illumination directions. The recognition system combines coocurrence matrices for feature extraction with a Nearest Neighbour classifier. Moreover, the recognition allows one to guess the approximate direction of the illumination used to capture the test image

Time-varying Risk Premiums and Conditional Market Risk: Empirical Evidence from European Stock Markets

This study investigates the relationship between the time-varying risk premiums and conditional market risk in the stock markets of the ten member countries of Economy and Monetary Union. Second, it examines whether the conditional second moments change over time and are there asymmetric effects in the conditional covariance matrix. Third, it analyzes the possible effects of the chosen testing framework. Empirical analysis is conducted using asymmetric univariate and multivariate GARCH-in-mean models and assuming three different degrees of market integration. For a daily sample period from 1999 to 2007, the study shows that the time-varying market risk alone is not enough to explain the dynamics of risk premiums and indications are found that the market risk is detected only when its price is allowed to change over time. Also asymmetric effects in the conditional covariance matrix, which is found to be time-varying, are clearly present and should be recognized in empirical asset pricing analyses.

Approximation to the theory of affinities to manage the problems of the groupping process

New economic and enterprise needs have increased the interest and utility of the methods of the grouping process based on the theory of uncertainty. A fuzzy grouping (clustering) process is a key phase of knowledge acquisition and reduction complexity regarding different groups of objects. Here, we considered some elements of the theory of affinities and uncertain pretopology that form a significant support tool for a fuzzy clustering process. A Galois lattice is introduced in order to provide a clearer vision of the results. We made an homogeneous grouping process of the economic regions of Russian Federation and Ukraine. The obtained results gave us a large panorama of a regional economic situation of two countries as well as the key guidelines for the decision-making. The mathematical method is very sensible to any changes the regional economy can have. We gave an alternative method of the grouping process under uncertainty.

New approximation to the third-order density : application to the calculation of correlated multicenter indices

In this work we present the formulas for the calculation of exact three-center electron sharing indices (3c-ESI) and introduce two new approximate expressions for correlated wave functions. The 3c-ESI uses the third-order density, the diagonal of the third-order reduced density matrix, but the approximations suggested in this work only involve natural orbitals and occupancies. In addition, the first calculations of 3c-ESI using Valdemoro's, Nakatsuji's and Mazziotti's approximation for the third-order reduced density matrix are also presented for comparison. Our results on a test set of molecules, including 32 3c-ESI values, prove that the new approximation based on the cubic root of natural occupancies performs the best, yielding absolute errors below 0.07 and an average absolute error of 0.015. Furthemore, this approximation seems to be rather insensitive to the amount of electron correlation present in the system. This newly developed methodology provides a computational inexpensive method to calculate 3c-ESI from correlated wave functions and opens new avenues to approximate high-order reduced density matrices in other contexts, such as the contracted Schrödinger equation and the anti-Hermitian contracted Schrödinger equation

Distribution and role of macrophytes in coastal lagoons : implications of critical shifts

Crossroads, crucibles and refuges are three words that may describe natural coastal lagoon environments. The words refer to the complex mix of marine and terrestrial influences, prolonged dilution due to the semi-enclosed nature and the function of a habitat for highly diverse plant and animal communities, some of which are endangered. To attain a realistic picture of the present situation, high vulnerability to anthropogenic impact should be added to the description. As the sea floor in coastal lagoons is usually entirely photic, macrophyte primary production is accentuated compared with open sea environments. There is, however, a lack of proper knowledge on the importance of vegetation for the general functioning of coastal lagoon ecosystems. The aim of this thesis is to assess the role of macrophyte diversity, cover and species identity over temporal and spatial scales for lagoon functions, and to determine which steering factors primarily restrict the qualitative and quantitative composition of vegetation in coastal lagoons. The results are linked to patterns of related trophic levels and the indicative potential of vegetation for assessment of general conditions in coastal lagoons is evaluated. This thesis includes five field studies conducted in flads and glo-flads in the brackish water northern Baltic Sea. Flads and glo-flads are defined as a Baltic variety of coastal lagoons, which due to an inlet threshold and post-glacial landuplift slowly will be isolated from the open sea. This process shrinks inlet size, increases exposure and water retention, and is called habitat isolation. The studied coastal lagoons are situated in the archipelago areas of the eastern coast of Sweden, the Åland Islands and the south-west mainland of Finland, where land-uplift amounts to ca. 5 mm/ per year. Out of 400 evaluated sites, a total of 70 lagoons varying in inlet size, archipelago position and anthropogenic influence to cover for essential environmental variation were chosen for further inventory. Vegetation composition, cover and richness were measured together with several hydrographic and morphometric variables in the lagoons both seasonally and inter-annually to cover for general regional, local and temporal patterns influencing lagoon and vegetation development. On smaller species-level scale, the effects of macrophyte species identity and richness for the fish habitat function were studied by examining the influence of plant interaction on juvenile fish diversity. Thus, the active election of plant monoand polycultures by fish and the diversity of fish in the respective culture were examined and related to plant height and water depth. The lagoons and vegetation composition were found to experience a regime shift initiated by increased habitat isolation along with land-uplift. Vegetation composition altered, richness decreased and cover increased forming a less isolated and more isolated regime, named the vascular plant regime and charophyte regime, respectively according to the dominant vegetation. As total phosphorus in the water, turbidity and the impact of regional influences decreased in parallel, the dominance of charophytes and increasing cover seemed to buffer and stabilize conditions in the charophyte regime and indicated an increased functional role of vegetation for the lagoon ecosystem. The regime pattern was unaffected by geographical differences, while strong anthropogenic impact seemed to distort the pattern due to loss of especially Chara tomentosa L. in the charophyte regime. The regimes were further found unperturbed by short-time temporal fluctuations. In fact the seasonal and inter-annual dynamics reinforced the functional difference between the regimes by the increasing role of vegetation along habitat isolation and the resemblance to lake environments for the charophyte regime. For instance, greater total phosphorus and chlorophyll a concentrations in the water in the beginning of the season in the charophyte regime compared with the vascular plant regime presented a steeper reduction to even lower values than in the vascular plant regime along the season. Despite a regional importance and positive relationship of macrophyte diversity in relation to trophic diversity, species identity was underlined in the results of this thesis, especially with decreasing spatial scale. This result was supported partly by the increased role of charophytes in the functioning of the charophyte regime, but even more explicitly by the species-specific preference of juvenile fish for tall macrophyte monocultures. On a smaller species-level scale, tall plant species in monoculture seemed to be able to increase their length, indicating that negative selection forms preferred habitat structures, which increase fish diversity. This negative relationship between plant and fish diversity suggest a shift in diversity patterns among trohic levels on smaller scale. Thus, as diversity patterns seem complex and diverge among spatial scales, it might be ambiguous to extend the understanding of diversity relationships from one trophic level to the other. All together, the regime shift described here presents similarities to the regime development in marine lagoon environments and shallow lakes subjected to nutrient enrichment. However, due to nutrient buffering by vegetation with increased isolation and water retention as a consequence of the inlet threshold, the development seems opposite to the course along an eutrophication gradient described in marine lagoons lacking an inlet threshold, where the role of vegetation decreases. Thus, the results imply devastating consequences of inlet dredging (decreasing isolation) in terms of vegetation loss and nutrient release, and call for increased conservational supervision. Especially the red listed charophytes would suffer negatively from such interference and the consequences are likely to also deteriorate juvenile fish production. The fact that a new species to Finland, Chara connivens Salzm. Ex. Braun 1835 was discovered during this study further indicates a potential of the lagoons serving as refuges for rare species.

Non-Linear Unsteady Aerodynamic Response Approximation Using Multi-Layer Functionals

Non-linear functional representation of the aerodynamic response provides a convenient mathematical model for motion-induced unsteady transonic aerodynamic loads response, that accounts for both complex non-linearities and time-history effects. A recent development, based on functional approximation theory, has established a novel functional form; namely, the multi-layer functional. For a large class of non-linear dynamic systems, such multi-layer functional representations can be realised via finite impulse response (FIR) neural networks. Identification of an appropriate FIR neural network model is facilitated by means of a supervised training process in which a limited sample of system input-output data sets is presented to the temporal neural network. The present work describes a procedure for the systematic identification of parameterised neural network models of motion-induced unsteady transonic aerodynamic loads response. The training process is based on a conventional genetic algorithm to optimise the network architecture, combined with a simplified random search algorithm to update weight and bias values. Application of the scheme to representative transonic aerodynamic loads response data for a bidimensional airfoil executing finite-amplitude motion in transonic flow is used to demonstrate the feasibility of the approach. The approach is shown to furnish a satisfactory generalisation property to different motion histories over a range of Mach numbers in the transonic regime.

Stochastic approximation methods in stochastic optimization

Stochastic approximation methods for stochastic optimization are considered. Reviewed the main methods of stochastic approximation: stochastic quasi-gradient algorithm, Kiefer-Wolfowitz algorithm and adaptive rules for them, simultaneous perturbation stochastic approximation (SPSA) algorithm. Suggested the model and the solution of the retailer's profit optimization problem and considered an application of the SQG-algorithm for the optimization problems with objective functions given in the form of ordinary differential equation.

Stiffness based trajectory planning and feedforward based vibration suppression control of parallel robot machines

The dissertation proposes two control strategies, which include the trajectory planning and vibration suppression, for a kinematic redundant serial-parallel robot machine, with the aim of attaining the satisfactory machining performance. For a given prescribed trajectory of the robot's end-effector in the Cartesian space, a set of trajectories in the robot's joint space are generated based on the best stiffness performance of the robot along the prescribed trajectory. To construct the required system-wide analytical stiffness model for the serial-parallel robot machine, a variant of the virtual joint method (VJM) is proposed in the dissertation. The modified method is an evolution of Gosselin's lumped model that can account for the deformations of a flexible link in more directions. The effectiveness of this VJM variant is validated by comparing the computed stiffness results of a flexible link with the those of a matrix structural analysis (MSA) method. The comparison shows that the numerical results from both methods on an individual flexible beam are almost identical, which, in some sense, provides mutual validation. The most prominent advantage of the presented VJM variant compared with the MSA method is that it can be applied in a flexible structure system with complicated kinematics formed in terms of flexible serial links and joints. Moreover, by combining the VJM variant and the virtual work principle, a systemwide analytical stiffness model can be easily obtained for mechanisms with both serial kinematics and parallel kinematics. In the dissertation, a system-wide stiffness model of a kinematic redundant serial-parallel robot machine is constructed based on integration of the VJM variant and the virtual work principle. Numerical results of its stiffness performance are reported. For a kinematic redundant robot, to generate a set of feasible joints' trajectories for a prescribed trajectory of its end-effector, its system-wide stiffness performance is taken as the constraint in the joints trajectory planning in the dissertation. For a prescribed location of the end-effector, the robot permits an infinite number of inverse solutions, which consequently yields infinite kinds of stiffness performance. Therefore, a differential evolution (DE) algorithm in which the positions of redundant joints in the kinematics are taken as input variables was employed to search for the best stiffness performance of the robot. Numerical results of the generated joint trajectories are given for a kinematic redundant serial-parallel robot machine, IWR (Intersector Welding/Cutting Robot), when a particular trajectory of its end-effector has been prescribed. The numerical results show that the joint trajectories generated based on the stiffness optimization are feasible for realization in the control system since they are acceptably smooth. The results imply that the stiffness performance of the robot machine deviates smoothly with respect to the kinematic configuration in the adjacent domain of its best stiffness performance. To suppress the vibration of the robot machine due to varying cutting force during the machining process, this dissertation proposed a feedforward control strategy, which is constructed based on the derived inverse dynamics model of target system. The effectiveness of applying such a feedforward control in the vibration suppression has been validated in a parallel manipulator in the software environment. The experimental study of such a feedforward control has also been included in the dissertation. The difficulties of modelling the actual system due to the unknown components in its dynamics is noticed. As a solution, a back propagation (BP) neural network is proposed for identification of the unknown components of the dynamics model of the target system. To train such a BP neural network, a modified Levenberg-Marquardt algorithm that can utilize an experimental input-output data set of the entire dynamic system is introduced in the dissertation. Validation of the BP neural network and the modified Levenberg- Marquardt algorithm is done, respectively, by a sinusoidal output approximation, a second order system parameters estimation, and a friction model estimation of a parallel manipulator, which represent three different application aspects of this method.

Time Varying Conditional Correlation Between Stock And Bond Returns: Evidence From CIVETS Nations

This thesis estimates long-run time variant conditional correlation between stock and bond returns of CIVETS (Colombia, Indonesia, Vietnam, Egypt, Turkey, and South Africa) nations. Further, aims to analyse the presence of asymmetric volatility effect in both asset returns, as well as, obverses increment or decrement in conditional correlation during pre-crisis and crisis period, which lead to make a reliable diversification decision. The Constant Conditional Correlation (CCC) GARCH model of Bollerslev (1990), the Dynamic Conditional Correlation (DCC) GARCH model (Engle 2002), and the Asymmetric Dynamic Conditional Correlation (ADCC) GARCH model of Cappiello, Engle, and Sheppard (2006) were implemented in the study. The analyses present strong evidence of time-varying conditional correlation in CIVETS markets, excluding Vietnam, during 2005-2013. In addition, negative innovation effects were found in both conditional variance and correlation of the asset returns. The results of this study recommend investors to include financial assets from these markets in portfolios, in order to obtain better stock-bond diversification benefits, especially during high volatility periods.