De-industrialisation and the post-communist transition:Rowthorn and Wells' model revisited

In this paper we present a simple three-sector model explaining the structural change in employment, which is a modified version of Rowthorn-Wells (1987). We supplement the theoretical analysis with simple econometric tests, which illustrate how the modified Rowthorn-Wells model can be used to (i) motivate empirical estimates of the link between the level of development and structures of employment, (ii) illustrate structural distortions under the command economies, and the structural adjustment that happened during the post-Communist transition. We demonstrate that in the case of these economies, the transition process leads to an adjustment to the employment structures predicted by the model.

Essays on international lending and increasing returns to scale

Standard economic theory suggests that capital should flow from rich countries to poor countries. However, capital has predominantly flowed to rich countries. The three essays in this dissertation attempt to explain this phenomenon. The first two essays suggest theoretical explanations for why capital has not flowed to the poor countries. The third essay empirically tests the theoretical explanations.^ The first essay examines the effects of increasing returns to scale on international lending and borrowing with moral hazard. Introducing increasing returns in a two-country general equilibrium model yields possible multiple equilibria and helps explain the possibility of capital flows from a poor to a rich country. I find that a borrowing country may need to borrow sufficient amounts internationally to reach a minimum investment threshold in order to invest domestically.^ The second essay examines how a poor country may invest in sectors with low productivity because of sovereign risk, and how collateral differences across sectors may exacerbate the problem. I model sovereign borrowing with a two-sector economy: one sector with increasing returns to scale (IRS) and one sector with diminishing returns to scale (DRS). Countries with incomes below a threshold will only invest in the DRS sector, and countries with incomes above a threshold will invest mostly in the IRS sector. The results help explain the existence of a bimodal world income distribution.^ The third essay empirically tests the explanations for why capital has not flowed from the rich to the poor countries, with a focus on institutions and initial capital. I find that institutional variables are a very important factor, but in contrast to other studies, I show that institutions do not account for the Lucas Paradox. Evidence of increasing returns still exists, even when controlling for institutions and other variables. In addition, I find that the determinants of capital flows may depend on whether a country is rich or poor.^

Tubular and sector heat pipes with interconnected branches for gas turbine and/or compressor cooling

Designing turbines for either aerospace or power production is a daunting task for any heat transfer scientist or engineer. Turbine designers are continuously pursuing better ways to convert the stored chemical energy in the fuel into useful work with maximum efficiency. Based on thermodynamic principles, one way to improve thermal efficiency is to increase the turbine inlet pressure and temperature. Generally, the inlet temperature may exceed the capabilities of standard materials for safe and long-life operation of the turbine. Next generation propulsion systems, whether for new supersonic transport or for improving existing aviation transport, will require more aggressive cooling system for many hot-gas-path components of the turbine. Heat pipe technology offers a possible cooling technique for the structures exposed to the high heat fluxes. Hence, the objective of this dissertation is to develop new radially rotating heat pipe systems that integrate multiple rotating miniature heat pipes with a common reservoir for a more effective and practical solution to turbine or compressor cooling. In this dissertation, two radially rotating miniature heat pipes and two sector heat pipes are analyzed and studied by utilizing suitable fluid flow and heat transfer modeling along with experimental tests. Analytical solutions for the film thickness and the lengthwise vapor temperature distribution for a single heat pipe are derived. Experimental tests on single radially rotating miniature heat pipes and sector heat pipes are undertaken with different important parameters and the manner in which these parameters affect heat pipe operation. Analytical and experimental studies have proven that the radially rotating miniature heat pipes have an incredibly high effective thermal conductance and an enormous heat transfer capability. Concurrently, the heat pipe has an uncomplicated structure and relatively low manufacturing costs. The heat pipe can also resist strong vibrations and is well suited for a high temperature environment. Hence, the heat pipes with a common reservoir make incorporation of heat pipes into turbo-machinery much more feasible and cost effective.

The issue of macroeconomic closure revisited and extended

Léon Walras (1874) already had realized that his neo-classical general equilibrium model could not accommodate autonomous investment. Sen analysed the same issue in a simple, one-sector macroeconomic model of a closed economy. He showed that fixing investment in the model, built strictly on neo-classical assumptions, would make the system overdetermined, thus, one should loosen some neo-classical condition of competitive equilibrium. He analysed three not neo-classical “closure options”, which could make the model well determined in the case of fixed investment. Others later extended his list and it showed that the closure dilemma arises in the more complex computable general equilibrium (CGE) models as well, as does the choice of adjustment mechanism assumed to bring about equilibrium at the macro level. By means of numerical models, it was also illustrated that the adopted closure rule can significantly affect the results of policy simulations based on a CGE model. Despite these warnings, the issue of macro closure is often neglected in policy simulations. It is, therefore, worth revisiting the issue and demonstrating by further examples its importance, as well as pointing out that the closure problem in the CGE models extends well beyond the problem of how to incorporate autonomous investment into a CGE model. Several closure rules are discussed in this paper and their diverse outcomes are illustrated by numerical models calibrated on statistical data. First, the analyses is done in a one-sector model, similar to Sen’s, but extended into a model of an open economy. Next, the same analyses are repeated using a fully-fledged multisectoral CGE model, calibrated on the same statistical data. Comparing the results obtained by the two models it is shown that although, using the same closure option, they generate quite similar results in terms of the direction and – to a somewhat lesser extent – of the magnitude of change in the main macro variables, the predictions of the multi-sectoral CGE model are clearly more realistic and balanced.

Using multifractals to evaluate oceanographic model skill

We are in an era of unprecedented data volumes generated from observations and model simulations. This is particularly true from satellite Earth Observations (EO) and global scale oceanographic models. This presents us with an opportunity to evaluate large scale oceanographic model outputs using EO data. Previous work on model skill evaluation has led to a plethora of metrics. The paper defines two new model skill evaluation metrics. The metrics are based on the theory of universal multifractals and their purpose is to measure the structural similarity between the model predictions and the EO data. The two metrics have the following advantages over the standard techniques: a) they are scale-free, b) they carry important part of information about how model represents different oceanographic drivers. Those two metrics are then used in the paper to evaluate the performance of the FVCOM model in the shelf seas around the south-west coast of the UK.

Using multifractals to evaluate oceanographic model skill

We are in an era of unprecedented data volumes generated from observations and model simulations. This is particularly true from satellite Earth Observations (EO) and global scale oceanographic models. This presents us with an opportunity to evaluate large scale oceanographic model outputs using EO data. Previous work on model skill evaluation has led to a plethora of metrics. The paper defines two new model skill evaluation metrics. The metrics are based on the theory of universal multifractals and their purpose is to measure the structural similarity between the model predictions and the EO data. The two metrics have the following advantages over the standard techniques: a) they are scale-free, b) they carry important part of information about how model represents different oceanographic drivers. Those two metrics are then used in the paper to evaluate the performance of the FVCOM model in the shelf seas around the south-west coast of the UK.

Examining the Longitudinal Stability of a Dual-Factor Model of Mental Health in Early Elementary School Students

Thesis (Ph.D.)--University of Washington, 2016-08

Tubular and Sector Heat Pipes with Interconnected Branches for Gas Turbine and/or Compressor Cooling

Designing turbines for either aerospace or power production is a daunting task for any heat transfer scientist or engineer. Turbine designers are continuously pursuing better ways to convert the stored chemical energy in the fuel into useful work with maximum efficiency. Based on thermodynamic principles, one way to improve thermal efficiency is to increase the turbine inlet pressure and temperature. Generally, the inlet temperature may exceed the capabilities of standard materials for safe and long-life operation of the turbine. Next generation propulsion systems, whether for new supersonic transport or for improving existing aviation transport, will require more aggressive cooling system for many hot-gas-path components of the turbine. Heat pipe technology offers a possible cooling technique for the structures exposed to the high heat fluxes. Hence, the objective of this dissertation is to develop new radially rotating heat pipe systems that integrate multiple rotating miniature heat pipes with a common reservoir for a more effective and practical solution to turbine or compressor cooling. In this dissertation, two radially rotating miniature heat pipes and two sector heat pipes are analyzed and studied by utilizing suitable fluid flow and heat transfer modeling along with experimental tests. Analytical solutions for the film thickness and the lengthwise vapor temperature distribution for a single heat pipe are derived. Experimental tests on single radially rotating miniature heat pipes and sector heat pipes are undertaken with different important parameters and the manner in which these parameters affect heat pipe operation. Analytical and experimental studies have proven that the radially rotating miniature heat pipes have an incredibly high effective thermal conductance and an enormous heat transfer capability. Concurrently, the heat pipe has an uncomplicated structure and relatively low manufacturing costs. The heat pipe can also resist strong vibrations and is well suited for a high temperature environment. Hence, the heat pipes with a common reservoir make incorporation of heat pipes into turbo-machinery much more feasible and cost effective.

Rough set-based reasoning and pattern mining for information filtering

An information filtering (IF) system monitors an incoming document stream to find the documents that match the information needs specified by the user profiles. To learn to use the user profiles effectively is one of the most challenging tasks when developing an IF system. With the document selection criteria better defined based on the users’ needs, filtering large streams of information can be more efficient and effective. To learn the user profiles, term-based approaches have been widely used in the IF community because of their simplicity and directness. Term-based approaches are relatively well established. However, these approaches have problems when dealing with polysemy and synonymy, which often lead to an information overload problem. Recently, pattern-based approaches (or Pattern Taxonomy Models (PTM) [160]) have been proposed for IF by the data mining community. These approaches are better at capturing sematic information and have shown encouraging results for improving the effectiveness of the IF system. On the other hand, pattern discovery from large data streams is not computationally efficient. Also, these approaches had to deal with low frequency pattern issues. The measures used by the data mining technique (for example, “support” and “confidences”) to learn the profile have turned out to be not suitable for filtering. They can lead to a mismatch problem. This thesis uses the rough set-based reasoning (term-based) and pattern mining approach as a unified framework for information filtering to overcome the aforementioned problems. This system consists of two stages - topic filtering and pattern mining stages. The topic filtering stage is intended to minimize information overloading by filtering out the most likely irrelevant information based on the user profiles. A novel user-profiles learning method and a theoretical model of the threshold setting have been developed by using rough set decision theory. The second stage (pattern mining) aims at solving the problem of the information mismatch. This stage is precision-oriented. A new document-ranking function has been derived by exploiting the patterns in the pattern taxonomy. The most likely relevant documents were assigned higher scores by the ranking function. Because there is a relatively small amount of documents left after the first stage, the computational cost is markedly reduced; at the same time, pattern discoveries yield more accurate results. The overall performance of the system was improved significantly. The new two-stage information filtering model has been evaluated by extensive experiments. Tests were based on the well-known IR bench-marking processes, using the latest version of the Reuters dataset, namely, the Reuters Corpus Volume 1 (RCV1). The performance of the new two-stage model was compared with both the term-based and data mining-based IF models. The results demonstrate that the proposed information filtering system outperforms significantly the other IF systems, such as the traditional Rocchio IF model, the state-of-the-art term-based models, including the BM25, Support Vector Machines (SVM), and Pattern Taxonomy Model (PTM).

The understanding of avatar design : various types and styles of avatars and the design considerations

People have adopted various formats of media such as graphics, photo and text (nickname) in order to represent themselves when communicate with others online. Avatar is known as a visual form representing a user oneself and one's identity wished. Its form can vary from a two-dimensional model to a three-dimensional model, and can be visualised with various visual forms and styles. In general, two-dimensional images including an animated image are used in online forum communities and live chat software; while three-dimensional models are often used in computer games. Avatar design is often regarded as a graphic designer's visual image creation or a user's output based on one's personal preference, yet it often causes the avatar design having no consideration of its practical visual design and users' interactive communication experience aspects. This paper will review various types and styles of avatar and discuss about avatar design from visual design and online user experience perspectives. It aims to raise a design discourse in avatar design and build up a well-articulated set of design principles for effective avatar design.

Nanoparticle melting as a Stefan moving boundary problem

The melting of spherical nanoparticles is considered from the perspective of heat flow in a pure material and as a moving boundary (Stefan) problem. The dependence of the melting temperature on both the size of the particle and the interfacial tension is described by the Gibbs-Thomson effect, and the resulting two-phase model is solved numerically using a front-fixing method. Results show that interfacial tension increases the speed of the melting process, and furthermore, the temperature distribution within the solid core of the particle exhibits behaviour that is qualitatively different to that predicted by the classical models without interfacial tension.

Simulation of delaminations in composite laminates

Lamb waves propagation in composite materials has been studied extensively since it was first observed in 1982. In this paper, we show a procedure to simulate the propagation of Lamb waves in composite laminates using a two-dimensional model in ANSYS. This is done by simulating the Lamb waves propagating along the plane of the structure in the form of a time dependent force excitation. In this paper, an 8-layered carbon reinforced fibre plastic (CRFP) is modelled as transversely isotropic and dissipative medium and the effect of flaws is analyzed with respect to the defects induced between various layers of the composite laminate. This effort is the basis for the future development of a 3D model for similar applications.

The anatomy of subjective well-being

This paper contributes to the literature on subjective well-being (SWB) by taking into account different aspects of life, called domains, such as health, financial situation, job, leisure, housing, and environment. We postulate a two-layer model where individual total SWB depends on the different subjective domain satisfactions. A distinction is made between long-term and short-term effects. The individual domain satisfactions depend on objectively measurable variables, such as income. The model is estimated using a large German panel data set.

The Validity of the Brief Michigan Alcohol Screening Test (bMAST) as a Problem Drinking Severity Measure

Objective: The Brief Michigan Alcoholism Screening Test (bMAST) is a 10-item test derived from the 25-item Michigan Alcoholism Screening Test (MAST). It is widely used in the assessment of alcohol dependence. In the absence of previous validation studies, the principal aim of this study was to assess the validity and reliability of the bMAST as a measure of the severity of problem drinking. Method: There were 6,594 patients (4,854 men, 1,740 women) who had been referred for alcohol-use disorders to a hospital alcohol and drug service who voluntarily participated in this study. Results: An exploratory factor analysis defined a two-factor solution, consisting of Perception of Current Drinking and Drinking Consequences factors. Structural equation modeling confirmed that the fit of a nine-item, two-factor model was superior to the original one-factor model. Concurrent validity was assessed through simultaneous administration of the Alcohol Use Disorders Identification Test (AUDIT) and associations with alcohol consumption and clinically assessed features of alcohol dependence. The two-factor bMAST model showed moderate correlations with the AUDIT. The two-factor bMAST and AUDIT were similarly associated with quantity of alcohol consumption and clinically assessed dependence severity features. No differences were observed between the existing weighted scoring system and the proposed simple scoring system. Conclusions: In this study, both the existing bMAST total score and the two-factor model identified were as effective as the AUDIT in assessing problem drinking severity. There are additional advantages of employing the two-factor bMAST in the assessment and treatment planning of patients seeking treatment for alcohol-use disorders. (J. Stud. Alcohol Drugs 68: 771-779,2007)

Soil Carbon Turnover Measurement by Physical Fractionation at a Forest-to-Pasture Chronosequence in the Brazilian Amazon

The effect of conversion from forest-to-pasture upon soil carbon stocks has been intensively discussed, but few studies focus on how this land-use change affects carbon (C) distribution across soil fractions in the Amazon basin. We investigated this in the 20 cm depth along a chronosequence of sites from native forest to three successively older pastures. We performed a physicochemical fractionation of bulk soil samples to better understand the mechanisms by which soil C is stabilized and evaluate the contribution of each C fraction to total soil C. Additionally, we used a two-pool model to estimate the mean residence time (MRT) for the slow and active pool C in each fraction. Soil C increased with conversion from forest-to-pasture in the particulate organic matter (> 250 mu m), microaggregate (53-250 mu m), and d-clay (< 2 mu m) fractions. The microaggregate comprised the highest soil C content after the conversion from forest-to-pasture. The C content of the d-silt fraction decreased with time since conversion to pasture. Forest-derived C remained in all fractions with the highest concentration in the finest fractions, with the largest proportion of forest-derived soil C associated with clay minerals. Results from this work indicate that microaggregate formation is sensitive to changes in management and might serve as an indicator for management-induced soil carbon changes, and the soil C changes in the fractions are dependent on soil texture.