Modelling of hydrogen stratification and gas mixing in containment using the APROS code

Hydrogen stratification and atmosphere mixing is a very important phenomenon in nuclear reactor containments when severe accidents are studied and simulated. Hydrogen generation, distribution and accumulation in certain parts of containment may pose a great risk to pressure increase induced by hydrogen combustion, and thus, challenge the integrity of NPP containment. The accurate prediction of hydrogen distribution is important with respect to the safety design of a NPP. Modelling methods typically used for containment analyses include both lumped parameter and field codes. The lumped parameter method is universally used in the containment codes, because its versatility, flexibility and simplicity. The lumped parameter method allows fast, full-scale simulations, where different containment geometries with relevant engineering safety features can be modelled. Lumped parameter gas stratification and mixing modelling methods are presented and discussed in this master’s thesis. Experimental research is widely used in containment analyses. The HM-2 experiment related to hydrogen stratification and mixing conducted at the THAI facility in Germany is calculated with the APROS lump parameter containment package and the APROS 6-equation thermal hydraulic model. The main purpose was to study, whether the convection term included in the momentum conservation equation of the 6-equation modelling gives some remarkable advantages compared to the simplified lumped parameter approach. Finally, a simple containment test case (high steam release to a narrow steam generator room inside a large dry containment) was calculated with both APROS models. In this case, the aim was to determine the extreme containment conditions, where the effect of convection term was supposed to be possibly high. Calculation results showed that both the APROS containment and the 6-equation model could model the hydrogen stratification in the THAI test well, if the vertical nodalisation was dense enough. However, in more complicated cases, the numerical diffusion may distort the results. Calculation of light gas stratification could be probably improved by applying the second order discretisation scheme for the modelling of gas flows. If the gas flows are relatively high, the convection term of the momentum equation is necessary to model the pressure differences between the adjacent nodes reasonably.

Managing Customer Issues through a Support Channel Network

The importance of after-sales service or service in general can be seen and experienced by customers every day with industrial as well as other non-industrial services or products. This dissertation, drawing on theory and experience, focuses on practical engineering implications, specifically the management of customer issues in the after-sales phase in the mobile phone arena. The main objective of this doctoral dissertation is to investigate customer after-sales issue management, specifically regarding mobile phones. The case studies focus on issue resolution time and the issue of corrective actions. This dissertation consists of a main body and four peer-reviewed journal articles and one manuscript currently under review by a peer-reviewed journal. The main body of this dissertation examines the elements of customer satisfaction, loyalty, and retention with respect to corrective actions to address customer issues and issue resolution time through literature and empirical studies. The five independent works are case studies supporting the thesis research questions. This study examines four questions: 1) What are the factors affecting corrective actions for customers? 2) How can customer issue resolution time be controlled? 3) What are the factors affecting processes in the service chain? and 4) How can communication be measured in a service chain? In this work, both quantitative and qualitative analysis methods are used. The main body of the thesis reviews the literature regarding the elements that bridge the five case studies. The case studies of the articles and surveys lean more toward the methodology of critical positivism and then apply the interpretive approach in interpreting the results. The case study articles employ various statistical methods to analyze and to interpret the empirical and survey data. The statistical methods were used to create a model that is useful for significantly optimizing issue resolution time. Moreover, it was found that samples for verifying issues provided by the customer neither improve the perceived quality of corrective actions nor the perceived quality of issue resolution time. The term “service” in this work is limited to the technical services that are provided by product manufacturers and after-sales authorized service vendors. On the basis of this research work, it has been observed that corrective actions and issue resolution time are associated with customer satisfaction and hence, according to induction theory, to customer loyalty and retention. This thesis utilizes knowledge of marketing and customer relationships to contribute to the existing body of knowledge concerning information and communication technology for after-sales service recovery of mobile terminals. The established models in the thesis contribute to the existing knowledge of the after-sales process of dealing with customer issues in the field of mobile phones. The findings suggest that process managers could focus more on communication and training provided to the staff as new technology evolves rapidly. The study also suggest the managers formulate strategies for how customers can be kept informed on a regular basis of the status of issues that have been escalated for corrective action. The findings also lay the foundation for the comprehensive objective to control the entire product development process, starting with conceptualization. This implies that robust design should be applied to the new products so that problems affecting customer service quality are not repeated. The objective will be achieved when the entire service chain from product development to the final user can be modeled and this model can be used to support the organization at all levels.

Adaptive Dynamics of Resource Specialization

Ecological specialization in resource utilization has various facades ranging from nutritional resources via host use of parasites or phytophagous insects to local adaptation in different habitats. Therefore, the evolution of specialization affects the evolution of most other traits, which makes it one of the core issues in the theory of evolution. Hence, the evolution of specialization has gained enormous amounts of research interest, starting already from Darwin’s Origin of species in 1859. Vast majority of the theoretical studies has, however, focused on the mathematically most simple case with well-mixed populations and equilibrium dynamics. This thesis explores the possibilities to extend the evolutionary analysis of resource usage to spatially heterogeneous metapopulation models and to models with non-equilibrium dynamics. These extensions are enabled by the recent advances in the field of adaptive dynamics, which allows for a mechanistic derivation of the invasion-fitness function based on the ecological dynamics. In the evolutionary analyses, special focus is set to the case with two substitutable renewable resources. In this case, the most striking questions are, whether a generalist species is able to coexist with the two specialist species, and can such trimorphic coexistence be attained through natural selection starting from a monomorphic population. This is shown possible both due to spatial heterogeneity and due to non-equilibrium dynamics. In addition, it is shown that chaotic dynamics may sometimes inflict evolutionary suicide or cyclic evolutionary dynamics. Moreover, the relations between various ecological parameters and evolutionary dynamics are investigated. Especially, the relation between specialization and dispersal propensity turns out to be counter-intuitively non-monotonous. This observation served as inspiration to the analysis of joint evolution of dispersal and specialization, which may provide the most natural explanation to the observed coexistence of specialist and generalist species.

Evaluation of two experimental models of hepatic encephalopathy in rats

The serious neuropsychological repercussions of hepatic encephalopathy have led to the creation of several experimental models in order to better understand the pathogenesis of the disease. In the present investigation, two possible causes of hepatic encephalopathy, cholestasis and portal hypertension, were chosen to study the behavioral impairments caused by the disease using an object recognition task. This working memory test is based on a paradigm of spontaneous delayed non-matching to sample and was performed 60 days after surgery. Male Wistar rats (225-250 g) were divided into three groups: two experimental groups, microsurgical cholestasis (N = 20) and extrahepatic portal hypertension (N = 20), and a control group (N = 20). A mild alteration of the recognition memory occurred in rats with cholestasis compared to control rats and portal hypertensive rats. The latter group showed the poorest performance on the basis of the behavioral indexes tested. In particular, only the control group spent significantly more time exploring novel objects compared to familiar ones (P < 0.001). In addition, the portal hypertension group spent the shortest time exploring both the novel and familiar objects (P < 0.001). These results suggest that the existence of portosystemic collateral circulation per se may be responsible for subclinical encephalopathy.

Fuzzy real option analysis in patent related decision making and patent valuation

The shift towards a knowledge-based economy has inevitably prompted the evolution of patent exploitation. Nowadays, patent is more than just a prevention tool for a company to block its competitors from developing rival technologies, but lies at the very heart of its strategy for value creation and is therefore strategically exploited for economic pro t and competitive advantage. Along with the evolution of patent exploitation, the demand for reliable and systematic patent valuation has also reached an unprecedented level. However, most of the quantitative approaches in use to assess patent could arguably fall into four categories and they are based solely on the conventional discounted cash flow analysis, whose usability and reliability in the context of patent valuation are greatly limited by five practical issues: the market illiquidity, the poor data availability, discriminatory cash-flow estimations, and its incapability to account for changing risk and managerial flexibility. This dissertation attempts to overcome these impeding barriers by rationalizing the use of two techniques, namely fuzzy set theory (aiming at the first three issues) and real option analysis (aiming at the last two). It commences with an investigation into the nature of the uncertainties inherent in patent cash flow estimation and claims that two levels of uncertainties must be properly accounted for. Further investigation reveals that both levels of uncertainties fall under the categorization of subjective uncertainty, which differs from objective uncertainty originating from inherent randomness in that uncertainties labelled as subjective are highly related to the behavioural aspects of decision making and are usually witnessed whenever human judgement, evaluation or reasoning is crucial to the system under consideration and there exists a lack of complete knowledge on its variables. Having clarified their nature, the application of fuzzy set theory in modelling patent-related uncertain quantities is effortlessly justified. The application of real option analysis to patent valuation is prompted by the fact that both patent application process and the subsequent patent exploitation (or commercialization) are subject to a wide range of decisions at multiple successive stages. In other words, both patent applicants and patentees are faced with a large variety of courses of action as to how their patent applications and granted patents can be managed. Since they have the right to run their projects actively, this flexibility has value and thus must be properly accounted for. Accordingly, an explicit identification of the types of managerial flexibility inherent in patent-related decision making problems and in patent valuation, and a discussion on how they could be interpreted in terms of real options are provided in this dissertation. Additionally, the use of the proposed techniques in practical applications is demonstrated by three fuzzy real option analysis based models. In particular, the pay-of method and the extended fuzzy Black-Scholes model are employed to investigate the profitability of a patent application project for a new process for the preparation of a gypsum-fibre composite and to justify the subsequent patent commercialization decision, respectively; a fuzzy binomial model is designed to reveal the economic potential of a patent licensing opportunity.

To divide or differentiate? : nestin-mediated regulation of Cdk5 in cell fate decisions

The molecular functions of the non-cell cycle-related Cyclin-dependent kinase 5 (Cdk5) have been of primary interest within the neuroscience field, but novel undertakings are constantly emerging for the kinase in tissue homeostasis, as well as in diseases such as diabetes and cancer. Although Cdk5 activation is predominantly regulated by specific non-cyclin activator protein binding, additional mechanisms have proved to orchestrate Cdk5 signaling in cells. For example, the interaction between the intermediate filament protein nestin and Cdk5 has been proposed to determine cellular fate during neuronal apoptosis through nestin-dependent adjustment of the sensitive balance and turnover of Cdk5 activators. While nestin constitutes a crucial regulatory scaffold for appropriate Cdk5 activation in apoptosis, Cdk5 itself phosphorylates nestin with the consequence of filament reorganization in both neuronal progenitors and differentiating muscle cells. Interestingly, the two proteins are often found coexpressed in various tissues and cell types, proposing that nestin-mediated scaffolding of Cdk5 and its activators may be applicable to other tissue systems as well. In the literature, the molecular functions of nestin have remained in the shade, as it is mostly exploited as a marker protein for progenitor cells. In light of these studies, the aim of this thesis was to assess the importance of the nestin scaffold in regulation of Cdk5 actions in cell fate decisions. This thesis can be subdivided into two major projects: one that studied the nature of the Cdk5-nestin interplay in muscle, and one that assessed their role in prostate cancer. During differentiation of a myoblast cell line, the filament formation properties of nestin was found to be crucial in directing Cdk5 activity, with direct consequences on the process of differentiation. Also the genetic knockout of nestin was found to influence Cdk5 activity, although differentiation per se was not affected. Instead, the genetic ablation of nestin had broad consequences on muscle homeostasis and regeneration. While the nestin-mediated regulation of Cdk5 in muscle was found to act in multiple ways, the connection remained more elusive in cancer models. Cdk5 was, however, established as a significant determinant of prostate cancer proliferation; a behavior uncharacteristic for this differentiation-associated kinase. Through complex and simultaneous regulation of two major prostate cancer pathways, Cdk5 was placed upstream of both Akt kinase and the androgen receptor. Its action on proliferation was nonetheless mainly exerted through the Akt signaling pathway in various cancer models. In summary, this thesis contributed to the knowledge of Cdk5 regulation and functions in two atypical settings; proliferation (in a cancer framework) and muscle differentiation, which is a poorly understood model system in the Cdk5 field. This balance between proliferation and differentiation implemented by Cdk5 is ultimately regulated (where present) by the dynamics of the cytoskeletal nestin scaffold.

Percutaneous sciatic nerve block with tramadol induces analgesia and motor blockade in two animal pain models

Local anesthetic efficacy of tramadol has been reported following intradermal application. Our aim was to investigate the effect of perineural tramadol as the sole analgesic in two pain models. Male Wistar rats (280-380 g; N = 5/group) were used in these experiments. A neurostimulation-guided sciatic nerve block was performed and 2% lidocaine or tramadol (1.25 and 5 mg) was perineurally injected in two different animal pain models. In the flinching behavior test, the number of flinches was evaluated and in the plantar incision model, mechanical and heat thresholds were measured. Motor effects of lidocaine and tramadol were quantified and a motor block score elaborated. Tramadol, 1.25 mg, completely blocked the first and reduced the second phase of the flinching behavior test. In the plantar incision model, tramadol (1.25 mg) increased both paw withdrawal latency in response to radiant heat (8.3 ± 1.1, 12.7 ± 1.8, 8.4 ± 0.8, and 11.1 ± 3.3 s) and mechanical threshold in response to von Frey filaments (459 ± 82.8, 447.5 ± 91.7, 320.1 ± 120, 126.43 ± 92.8 mN) at 5, 15, 30, and 60 min, respectively. Sham block or contralateral sciatic nerve block did not differ from perineural saline injection throughout the study in either model. The effect of tramadol was not antagonized by intraperitoneal naloxone. High dose tramadol (5 mg) blocked motor function as well as 2% lidocaine. In conclusion, tramadol blocks nociception and motor function in vivo similar to local anesthetics.

Computational models for and from biology : simple gene assembly and reaction systems

The advancement of science and technology makes it clear that no single perspective is any longer sufficient to describe the true nature of any phenomenon. That is why the interdisciplinary research is gaining more attention overtime. An excellent example of this type of research is natural computing which stands on the borderline between biology and computer science. The contribution of research done in natural computing is twofold: on one hand, it sheds light into how nature works and how it processes information and, on the other hand, it provides some guidelines on how to design bio-inspired technologies. The first direction in this thesis focuses on a nature-inspired process called gene assembly in ciliates. The second one studies reaction systems, as a modeling framework with its rationale built upon the biochemical interactions happening within a cell. The process of gene assembly in ciliates has attracted a lot of attention as a research topic in the past 15 years. Two main modelling frameworks have been initially proposed in the end of 1990s to capture ciliates’ gene assembly process, namely the intermolecular model and the intramolecular model. They were followed by other model proposals such as templatebased assembly and DNA rearrangement pathways recombination models. In this thesis we are interested in a variation of the intramolecular model called simple gene assembly model, which focuses on the simplest possible folds in the assembly process. We propose a new framework called directed overlap-inclusion (DOI) graphs to overcome the limitations that previously introduced models faced in capturing all the combinatorial details of the simple gene assembly process. We investigate a number of combinatorial properties of these graphs, including a necessary property in terms of forbidden induced subgraphs. We also introduce DOI graph-based rewriting rules that capture all the operations of the simple gene assembly model and prove that they are equivalent to the string-based formalization of the model. Reaction systems (RS) is another nature-inspired modeling framework that is studied in this thesis. Reaction systems’ rationale is based upon two main regulation mechanisms, facilitation and inhibition, which control the interactions between biochemical reactions. Reaction systems is a complementary modeling framework to traditional quantitative frameworks, focusing on explicit cause-effect relationships between reactions. The explicit formulation of facilitation and inhibition mechanisms behind reactions, as well as the focus on interactions between reactions (rather than dynamics of concentrations) makes their applicability potentially wide and useful beyond biological case studies. In this thesis, we construct a reaction system model corresponding to the heat shock response mechanism based on a novel concept of dominance graph that captures the competition on resources in the ODE model. We also introduce for RS various concepts inspired by biology, e.g., mass conservation, steady state, periodicity, etc., to do model checking of the reaction systems based models. We prove that the complexity of the decision problems related to these properties varies from P to NP- and coNP-complete to PSPACE-complete. We further focus on the mass conservation relation in an RS and introduce the conservation dependency graph to capture the relation between the species and also propose an algorithm to list the conserved sets of a given reaction system.

Public-private partnership investments in dry ports – Russian logistics markets and risks

The investments have always been considered as an essential backbone and so-called ‘locomotive’ for the competitive economies. However, in various countries, the state has been put under tight budget constraints for the investments in capital intensive projects. In response to this situation, the cooperation between public and private sector has grown based on public-private mechanism. The promotion of favorable arrangement for collaboration between public and private sectors for the provision of policies, services, and infrastructure in Russia can help to address the problems of dry ports development that neither municipalities nor the private sector can solve alone. Especially, the stimulation of public-private collaboration is significant under the exposure to externalities that affect the magnitude of the risks during all phases of project realization. In these circumstances, the risk in the projects also is becoming increasingly a part of joint research and risk management practice, which is viewed as a key approach, aiming to take active actions on existing global and specific factors of uncertainties. Meanwhile, a relatively little progress has been made on the inclusion of the resilience aspects into the planning process of a dry ports construction that would instruct the capacity planner, on how to mitigate the occurrence of disruptions that may lead to million dollars of losses due to the deviation of the future cash flows from the expected financial flows on the project. The current experience shows that the existing methodological base is developed fragmentary within separate steps of supply chain risk management (SCRM) processes: risk identification, risk evaluation, risk mitigation, risk monitoring and control phases. The lack of the systematic approach hinders the solution of the problem of risk management processes of dry port implementation. Therefore, management of various risks during the investments phases of dry port projects still presents a considerable challenge from the practical and theoretical points of view. In this regard, the given research became a logical continuation of fundamental research, existing in the financial models and theories (e.g., capital asset pricing model and real option theory), as well as provided a complementation for the portfolio theory. The goal of the current study is in the design of methods and models for the facilitation of dry port implementation through the mechanism of public-private partnership on the national market that implies the necessity to mitigate, first and foremost, the shortage of the investments and consequences of risks. The problem of the research was formulated on the ground of the identified contradictions. They rose as a continuation of the trade-off between the opportunities that the investors can gain from the development of terminal business in Russia (i.e. dry port implementation) and risks. As a rule, the higher the investment risk, the greater should be their expected return. However, investors have a different tolerance for the risks. That is why it would be advisable to find an optimum investment. In the given study, the optimum relates to the search for the efficient portfolio, which can provide satisfaction to the investor, depending on its degree of risk aversion. There are many theories and methods in finance, concerning investment choices. Nevertheless, the appropriateness and effectiveness of particular methods should be considered with the allowance of the specifics of the investment projects. For example, the investments in dry ports imply not only the lump sum of financial inflows, but also the long-term payback periods. As a result, capital intensity and longevity of their construction determine the necessity from investors to ensure the return on investment (profitability), along with the rapid return on investment (liquidity), without precluding the fact that the stochastic nature of the project environment is hardly described by the formula-based approach. The current theoretical base for the economic appraisals of the dry port projects more often perceives net present value (NPV) as a technique superior to other decision-making criteria. For example, the portfolio theory, which considers different risk preference of an investor and structures of utility, defines net present value as a better criterion of project appraisal than discounted payback period (DPP). Meanwhile, in business practice, the DPP is more popular. Knowing that the NPV is based on the assumptions of certainty of project life, it cannot be an accurate appraisal approach alone to determine whether or not the project should be accepted for the approval in the environment that is not without of uncertainties. In order to reflect the period or the project’s useful life that is exposed to risks due to changes in political, operational, and financial factors, the second capital budgeting criterion – discounted payback period is profoundly important, particularly for the Russian environment. Those statements represent contradictions that exist in the theory and practice of the applied science. Therefore, it would be desirable to relax the assumptions of portfolio theory and regard DPP as not fewer relevant appraisal approach for the assessment of the investment and risk measure. At the same time, the rationality of the use of both project performance criteria depends on the methods and models, with the help of which these appraisal approaches are calculated in feasibility studies. The deterministic methods cannot ensure the required precision of the results, while the stochastic models guarantee the sufficient level of the accuracy and reliability of the obtained results, providing that the risks are properly identified, evaluated, and mitigated. Otherwise, the project performance indicators may not be confirmed during the phase of project realization. For instance, the economic and political instability can result in the undoing of hard-earned gains, leading to the need for the attraction of the additional finances for the project. The sources of the alternative investments, as well as supportive mitigation strategies, can be studied during the initial phases of project development. During this period, the effectiveness of the investments undertakings can also be improved by the inclusion of the various investors, e.g. Russian Railways’ enterprises and other private companies in the dry port projects. However, the evaluation of the effectiveness of the participation of different investors in the project lack the methods and models that would permit doing the particular feasibility study, foreseeing the quantitative characteristics of risks and their mitigation strategies, which can meet the tolerance of the investors to the risks. For this reason, the research proposes a combination of Monte Carlo method, discounted cash flow technique, the theory of real options, and portfolio theory via a system dynamics simulation approach. The use of this methodology allows for comprehensive risk management process of dry port development to cover all aspects of risk identification, risk evaluation, risk mitigation, risk monitoring, and control phases. A designed system dynamics model can be recommended for the decision-makers on the dry port projects that are financed via a public-private partnership. It permits investors to make a decision appraisal based on random variables of net present value and discounted payback period, depending on different risks factors, e.g. revenue risks, land acquisition risks, traffic volume risks, construction hazards, and political risks. In this case, the statistical mean is used for the explication of the expected value of the DPP and NPV; the standard deviation is proposed as a characteristic of risks, while the elasticity coefficient is applied for rating of risks. Additionally, the risk of failure of project investments and guaranteed recoupment of capital investment can be considered with the help of the model. On the whole, the application of these modern methods of simulation creates preconditions for the controlling of the process of dry port development, i.e. making managerial changes and identifying the most stable parameters that contribute to the optimal alternative scenarios of the project realization in the uncertain environment. System dynamics model allows analyzing the interactions in the most complex mechanism of risk management process of the dry ports development and making proposals for the improvement of the effectiveness of the investments via an estimation of different risk management strategies. For the comparison and ranking of these alternatives in their order of preference to the investor, the proposed indicators of the efficiency of the investments, concerning the NPV, DPP, and coefficient of variation, can be used. Thus, rational investors, who averse to taking increased risks unless they are compensated by the commensurate increase in the expected utility of a risky prospect of dry port development, can be guided by the deduced marginal utility of investments. It is computed on the ground of the results from the system dynamics model. In conclusion, the outlined theoretical and practical implications for the management of risks, which are the key characteristics of public-private partnerships, can help analysts and planning managers in budget decision-making, substantially alleviating the effect from various risks and avoiding unnecessary cost overruns in dry port projects.

A System for Models of First Order Theories

If you want to know whether a property is true or not in a specific algebraic structure,you need to test that property on the given structure. This can be done by hand, which can be cumbersome and erroneous. In addition, the time consumed in testing depends on the size of the structure where the property is applied. We present an implementation of a system for finding counterexamples and testing properties of models of first-order theories. This system is supposed to provide a convenient and paperless environment for researchers and students investigating or studying such models and algebraic structures in particular. To implement a first-order theory in the system, a suitable first-order language.( and some axioms are required. The components of a language are given by a collection of variables, a set of predicate symbols, and a set of operation symbols. Variables and operation symbols are used to build terms. Terms, predicate symbols, and the usual logical connectives are used to build formulas. A first-order theory now consists of a language together with a set of closed formulas, i.e. formulas without free occurrences of variables. The set of formulas is also called the axioms of the theory. The system uses several different formats to allow the user to specify languages, to define axioms and theories and to create models. Besides the obvious operations and tests on these structures, we have introduced the notion of a functor between classes of models in order to generate more co~plex models from given ones automatically. As an example, we will use the system to create several lattices structures starting from a model of the theory of pre-orders.

Autonomy and Relatedness in Mainland Chinese Adolescents: Social or Personal? Accommodation or Distinctiveness?

Three studies comprised the current research program, in which the major goals were to propose and validate empirically the proposed two-level (universal and culture-specific) model of both autonomy and relatedness, as well as to develop reliable and valid measures for these two constructs. In Study 1, 143 mainland Chinese adolescents were asked open-ended questions about their understanding of autonomy and relatedness in three social contexts (peer, family, school). Chinese youth’s responses captured universal and culturally distinctive forms of autonomy (personal vs. social) and relatedness (accommodation vs. distinctiveness), according to a priori criteria based on the theoretical frameworks. Also, scenarios designed to reflect culture-specific forms of autonomy and relatedness suggested their relevance to Chinese adolescents. With a second sample of 201 mainland Chinese youth, in Study 2, the obtained autonomy and relatedness descriptors were formulated into scale items. Those items were subject to refinement analyses to examine their psychometric properties and centrality to Chinese youth. The findings of Study 1 scenarios were replicated in Study 2. The primary goal of Study 3 was to test empirically the proposed two-level (universal and culture-specific) models of both autonomy and relatedness, using the measures derived from Studies 1 and 2. A third sample of 465 mainland Chinese youth completed a questionnaire booklet consisting of autonomy and relatedness scales and scenarios and achievement motivation orientations measures. A series of confirmatory factor analysis (CFA) autonomy and relatedness measurement models (first-order and second-order), as well as structural models linking culture-specific forms of autonomy and relatedness and achievement motivation orientations, were conducted. The first-order measurement models based on scale and scenario scores consistently confirmed the distinction between personal autonomy and social autonomy, and that of accommodation and distinctiveness. Although the construct validity of the two culture-specific forms of autonomy gained additional support from the structural models, the associations between the two culture-specific forms of relatedness and achievement motivation orientations were relatively weak. In general, the two-level models of autonomy and relatedness were supported in two ways: conceptual analysis of scale items and second-order measurement models. In addition, across the three studies, I explored potential contextual and sex differences in Chinese youth’s endorsement of the diverse forms of autonomy and relatedness. Overall, no substantial contextual variability or sex differences were found. The current research makes an important theoretical contribution to the field of developmental psychology in general, and autonomy and relatedness in particular, by proposing and testing empirically both universal and culture-specific parts of autonomy and relatedness. The current findings have implications for the measurement of autonomy and relatedness across social contexts, as well as for socialization and education practice.

Latent Variable Models for Stochastic Discount Factors.

Latent variable models in finance originate both from asset pricing theory and time series analysis. These two strands of literature appeal to two different concepts of latent structures, which are both useful to reduce the dimension of a statistical model specified for a multivariate time series of asset prices. In the CAPM or APT beta pricing models, the dimension reduction is cross-sectional in nature, while in time-series state-space models, dimension is reduced longitudinally by assuming conditional independence between consecutive returns, given a small number of state variables. In this paper, we use the concept of Stochastic Discount Factor (SDF) or pricing kernel as a unifying principle to integrate these two concepts of latent variables. Beta pricing relations amount to characterize the factors as a basis of a vectorial space for the SDF. The coefficients of the SDF with respect to the factors are specified as deterministic functions of some state variables which summarize their dynamics. In beta pricing models, it is often said that only the factorial risk is compensated since the remaining idiosyncratic risk is diversifiable. Implicitly, this argument can be interpreted as a conditional cross-sectional factor structure, that is, a conditional independence between contemporaneous returns of a large number of assets, given a small number of factors, like in standard Factor Analysis. We provide this unifying analysis in the context of conditional equilibrium beta pricing as well as asset pricing with stochastic volatility, stochastic interest rates and other state variables. We address the general issue of econometric specifications of dynamic asset pricing models, which cover the modern literature on conditionally heteroskedastic factor models as well as equilibrium-based asset pricing models with an intertemporal specification of preferences and market fundamentals. We interpret various instantaneous causality relationships between state variables and market fundamentals as leverage effects and discuss their central role relative to the validity of standard CAPM-like stock pricing and preference-free option pricing.

Exact Skewness-Kurtosis Tests for Multivariate Normality and Goodness-of-fit in Multivariate Regressions with Application to Asset Pricing Models

We study the problem of testing the error distribution in a multivariate linear regression (MLR) model. The tests are functions of appropriately standardized multivariate least squares residuals whose distribution is invariant to the unknown cross-equation error covariance matrix. Empirical multivariate skewness and kurtosis criteria are then compared to simulation-based estimate of their expected value under the hypothesized distribution. Special cases considered include testing multivariate normal, Student t; normal mixtures and stable error models. In the Gaussian case, finite-sample versions of the standard multivariate skewness and kurtosis tests are derived. To do this, we exploit simple, double and multi-stage Monte Carlo test methods. For non-Gaussian distribution families involving nuisance parameters, confidence sets are derived for the the nuisance parameters and the error distribution. The procedures considered are evaluated in a small simulation experi-ment. Finally, the tests are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995.

Finite-Sample Simulation-Based Inference in VAR Models with Applications to Order Selection and Causality Testing

Statistical tests in vector autoregressive (VAR) models are typically based on large-sample approximations, involving the use of asymptotic distributions or bootstrap techniques. After documenting that such methods can be very misleading even with fairly large samples, especially when the number of lags or the number of equations is not small, we propose a general simulation-based technique that allows one to control completely the level of tests in parametric VAR models. In particular, we show that maximized Monte Carlo tests [Dufour (2002)] can provide provably exact tests for such models, whether they are stationary or integrated. Applications to order selection and causality testing are considered as special cases. The technique developed is applied to quarterly and monthly VAR models of the U.S. economy, comprising income, money, interest rates and prices, over the period 1965-1996.

Development of a Chinese version WHO Self-Assessment Tool for Evaluating Health Promotion in Hospital

[Support Institutions:] Department of Administration of Health, University of Montreal, Canada Public Health School of Fudan University, Shanghai, China