An Analysis of Laypeople’s Beliefs Regarding the Origins of Their Worst Nightmare

Essai présenté à la Faculté des Arts et des Sciences en vue de l’obtention du grade de Doctorat en Psychologie Clinique (D. Psy.)

Development and Analysis of Compact AMicrostrip Antennas

The practical applications of microstrip antennas for mobile systems are in portable or pocket-size equipment and in vehicles. Antennas for VHFIUHF handheld portable equipment, such as pagers, portable telephones and transceivers, must naturally be small in size, light in weight and compact in structure. There is a growing tendency for portable equipment to be made smaller and smaller as the demand for personal communication rapidly increases, and the development of very compact hand-held units has become urgent.In this thesis work, main aim is to develop a more and more reduced sized microstrip patch antenna. It is well known that the smaller the antenna size, the lower the antenna efficiency. During the period of work, three different compact circular sided microstrip patches are developed and analysed, which have a significant size reduction compared to standard circular disk antenna (the most compact one of the basic microstrip patch configurations), without much deterioration of its properties like gain, bandwidth and efficiency. In addition to this the interesting results, dual port operation and circular polarization are also observed for some typical designs of these patches. These make the patches suitable for satellite and mobile communication systems.The theoretical investigations are carried out on these compact patches. The empirical relations are developed by modifying the standard equations of rectangular and circular disk microstrip patches, which helps to predict the resonant frequencies easily.

Weather and climate of Penisular India modulated by Extrinsic factors- Empirical and Numerical Perspectives

The Doctoral thesis focuses on the factors that influence the weather and climate over Peninsular Indias. The first chapter provides a general introduction about the climatic features over peninsular India, various factors dealt in subsequent chapters, such as solar forcing on climate, SST variability in the northern Indian Ocean and its influence on Indian monsoon, moisture content of the atmosphere and its importance in the climate system, empirical formulation of regression forecast of climate and some aspects of regional climate modeling. Chapter 2 deals with the variability in the vertically integrated moisture (VIM) over Peninsular India on various time scales. The third Chapter discusses the influence of solar activity in the low frequency variability in the rainfall of Peninsular India. The study also investigates the influence of solar activity on the horizontal and vertical components of wind and the difference in the forcing before and after the so-called regime shift in the climate system before and after mid-1970s.In Chapter 4 on Peninsular Indian Rainfall and its association with meteorological and oceanic parameters over adjoining oceanic region, a linear regression model was developed and tested for the seasonal rainfall prediction of Peninsular India.

Yield gap analysis and assessment of climate-induced yield trends of irrigated rice in selected provinces of the Philippines

This study describes a combined empirical/modeling approach to assess the possible impact of climate variability on rice production in the Philippines. We collated climate data of the last two decades (1985-2002) as well as yield statistics of six provinces of the Philippines, selected along a North-South gradient. Data from the climate information system of NASA were used as input parameters of the model ORYZA2000 to determine potential yields and, in the next steps, the yield gaps defined as the difference between potential and actual yields. Both simulated and actual yields of irrigated rice varied strongly between years. However, no climate-driven trends were apparent and the variability in actual yields showed no correlation with climatic parameters. The observed variation in simulated yields was attributable to seasonal variations in climate (dry/wet season) and to climatic differences between provinces and agro-ecological zones. The actual yield variation between provinces was not related to differences in the climatic yield potential but rather to soil and management factors. The resulting yield gap was largest in remote and infrastructurally disfavored provinces (low external input use) with a high production potential (high solar radiation and day-night temperature differences). In turn, the yield gap was lowest in central provinces with good market access but with a relatively low climatic yield potential. We conclude that neither long-term trends nor the variability of the climate can explain current rice yield trends and that agroecological, seasonal, and management effects are over-riding any possible climatic variations. On the other hand the lack of a climate-driven trend in the present situation may be superseded by ongoing climate change in the future.

From evolution to co-evolution – An empirical study of the role of innovation, policy and public research in industrial dynamics

In the past decades since Schumpeter’s influential writings economists have pursued research to examine the role of innovation in certain industries on firm as well as on industry level. Researchers describe innovations as the main trigger of industry dynamics, while policy makers argue that research and education are directly linked to economic growth and welfare. Thus, research and education are an important objective of public policy. Firms and public research are regarded as the main actors which are relevant for the creation of new knowledge. This knowledge is finally brought to the market through innovations. What is more, policy makers support innovations. Both actors, i.e. policy makers and researchers, agree that innovation plays a central role but researchers still neglect the role that public policy plays in the field of industrial dynamics. Therefore, the main objective of this work is to learn more about the interdependencies of innovation, policy and public research in industrial dynamics. The overarching research question of this dissertation asks whether it is possible to analyze patterns of industry evolution – from evolution to co-evolution – based on empirical studies of the role of innovation, policy and public research in industrial dynamics. This work starts with a hypothesis-based investigation of traditional approaches of industrial dynamics. Namely, the testing of a basic assumption of the core models of industrial dynamics and the analysis of the evolutionary patterns – though with an industry which is driven by public policy as example. Subsequently it moves to a more explorative approach, investigating co-evolutionary processes. The underlying questions of the research include the following: Do large firms have an advantage because of their size which is attributable to cost spreading? Do firms that plan to grow have more innovations? What role does public policy play for the evolutionary patterns of an industry? Are the same evolutionary patterns observable as those described in the ILC theories? And is it possible to observe regional co-evolutionary processes of science, innovation and industry evolution? Based on two different empirical contexts – namely the laser and the photovoltaic industry – this dissertation tries to answer these questions and combines an evolutionary approach with a co-evolutionary approach. The first chapter starts with an introduction of the topic and the fields this dissertation is based on. The second chapter provides a new test of the Cohen and Klepper (1996) model of cost spreading, which explains the relationship between innovation, firm size and R&D, at the example of the photovoltaic industry in Germany. First, it is analyzed whether the cost spreading mechanism serves as an explanation for size advantages in this industry. This is related to the assumption that the incentives to invest in R&D increase with the ex-ante output. Furthermore, it is investigated whether firms that plan to grow will have more innovative activities. The results indicate that cost spreading serves as an explanation for size advantages in this industry and, furthermore, growth plans lead to higher amount of innovative activities. What is more, the role public policy plays for industry evolution is not finally analyzed in the field of industrial dynamics. In the case of Germany, the introduction of demand inducing policy instruments stimulated market and industry growth. While this policy immediately accelerated market volume, the effect on industry evolution is more ambiguous. Thus, chapter three analyzes this relationship by considering a model of industry evolution, where demand-inducing policies will be discussed as a possible trigger of development. The findings suggest that these instruments can take the same effect as a technical advance to foster the growth of an industry and its shakeout. The fourth chapter explores the regional co-evolution of firm population size, private-sector patenting and public research in the empirical context of German laser research and manufacturing over more than 40 years from the emergence of the industry to the mid-2000s. The qualitative as well as quantitative evidence is suggestive of a co-evolutionary process of mutual interdependence rather than a unidirectional effect of public research on private-sector activities. Chapter five concludes with a summary, the contribution of this work as well as the implications and an outlook of further possible research.

Multivariate ARIMA Compositional Time Series Analysis

A compositional time series is obtained when a compositional data vector is observed at different points in time. Inherently, then, a compositional time series is a multivariate time series with important constraints on the variables observed at any instance in time. Although this type of data frequently occurs in situations of real practical interest, a trawl through the statistical literature reveals that research in the field is very much in its infancy and that many theoretical and empirical issues still remain to be addressed. Any appropriate statistical methodology for the analysis of compositional time series must take into account the constraints which are not allowed for by the usual statistical techniques available for analysing multivariate time series. One general approach to analyzing compositional time series consists in the application of an initial transform to break the positive and unit sum constraints, followed by the analysis of the transformed time series using multivariate ARIMA models. In this paper we discuss the use of the additive log-ratio, centred log-ratio and isometric log-ratio transforms. We also present results from an empirical study designed to explore how the selection of the initial transform affects subsequent multivariate ARIMA modelling as well as the quality of the forecasts

Analysis of Michael Porter’s generic strategies and its usage in a globalized business environment

Michael Porter reconocido como una autoridad en estrategia nos ha motivado a entrar a analizar profundamente sus propuestas e ideas en el campo de su dominio, con el objetivo de analizarlas y validarlas en el actual ambiente de negocios, caracterizado por ser turbulento y dinámico. El método elegido fue contratar éste ambiente con el ambiente bajo el cual se crearon las propuestas estratégicas de Michael Porter. Para esto, nos enfocamos en su propuesta para la estrategia de negocio, específicamente, las Tres Estrategias Genéricas. Tomando el caso de estudio de ZARA y su trayectoria empresarial como una investigación empírica para obtener resultados y discutirlos bajo parámetros que surgen desde las críticas desarrolladas por otros autores. Tomando como fuente de información libros, ensayos, publicaciones en Internet, noticias, entrevistas a clientes y a sus empleados.

The innate concepts in Chomsky’s work: definition and proposal of an empirical method for their study

This article focuses on innate concepts: their definition, according to the linguistic work of Noam Chomsky, and the outline of a method for their study. As an introduction to the subject some academic conceptions of the concept acquisition are pointed out, and it is claimed that there is a lack of an empirical method for the study of innate concepts. Next, the article presents the definition that Chomsky has defended over time about such concepts. Finally, in a theoretical way, it presents the conditions for an empirical procedure for the study of innate concepts, called semantic analysis of corpus

The persistent colombian conflict bubnational analysis of the duration of violence

The growing empirical literature on the analysis of civil war has recently included the study of conflict duration at the cross-country level. This paper presents, for the first time, a within-country analysis of the determinants of violence duration. I focus on the experience of the Colombian armed conflict. While the conflict has been active for about five decades, local violence ebbs and flows and areas experiencing continuous conflict coexist with places that have been able to resile and where violence is mostly absent. I examine a wide range of factors potentially associated with violence duration at the municipal level, including scale variables, geographical conditions, economic and social variables, institutions and state presence, inequality, government intervention, and victimization variables. I characterize a few variables robustly correlated with the persistence of localized conflict, both across specifications and using different econometric models of duration analysis.

Informality in the City: a Theoretical Analysis

This thesis theoretically studies the relationship between the informal sector (both in the labor and the housing market) and the city structure.

Estimating and Forecasting the Term Structure of Interest Rates:US and Colombia Analysis

In this paper we use the most representative models that exist in the literature on term structure of interest rates. In particular, we explore affine one factor models and polynomial-type approximations such as Nelson and Siegel. Our empirical application considers monthly data of USA and Colombia for estimation and forecasting. We find that affine models do not provide adequate performance either in-sample or out-of-sample. On the contrary, parsimonious models such as Nelson and Siegel have adequate results in-sample, however out-of-sample they are not able to systematically improve upon random walk base forecast.

The growth effects of EU cohesion policy: a meta-analysis. Bruegel Working Paper 2012/14, October 2012

We run a standard income convergence analysis for the last decade and confirm an already established finding in the growth economics literature. EU countries are converging. Regions in Europe are also converging. But, within countries, regional disparities are on the rise. At the same time, there is probably no reason for EU Cohesion Policy to be concerned with what happens inside countries. Ultimately, our data shows that national governments redistribute well across regions, whether they are fiscally centralised or decentralised. It is difficult to establish if Structural and Cohesion Funds play any role in recent growth convergence patterns in Europe. Generally, macroeconomic simulations produce better results than empirical tests. It is thus possible that Structural Funds do not fully realise their potential either because they are not efficiently allocated or are badly managed or are used for the wrong investments, or a combination of all three. The approach to assess the effectiveness of EU funds should be consistent with the rationale behind the post-1988 EU Cohesion Policy. Standard income convergence analysis is certainly not sufficient and should be accompanied by an assessment of the changes in the efficiency of the capital stock in the recipient countries or regions as well as by a more qualitative assessment. EU funds for competitiveness and employment should be allocated by looking at each region’s capital efficiency to maximise growth generating effects or on a pure competitive.

Independent component analysis of climate data: A new look at EOF rotation

The complexity inherent in climate data makes it necessary to introduce more than one statistical tool to the researcher to gain insight into the climate system. Empirical orthogonal function (EOF) analysis is one of the most widely used methods to analyze weather/climate modes of variability and to reduce the dimensionality of the system. Simple structure rotation of EOFs can enhance interpretability of the obtained patterns but cannot provide anything more than temporal uncorrelatedness. In this paper, an alternative rotation method based on independent component analysis (ICA) is considered. The ICA is viewed here as a method of EOF rotation. Starting from an initial EOF solution rather than rotating the loadings toward simplicity, ICA seeks a rotation matrix that maximizes the independence between the components in the time domain. If the underlying climate signals have an independent forcing, one can expect to find loadings with interpretable patterns whose time coefficients have properties that go beyond simple noncorrelation observed in EOFs. The methodology is presented and an application to monthly means sea level pressure (SLP) field is discussed. Among the rotated (to independence) EOFs, the North Atlantic Oscillation (NAO) pattern, an Arctic Oscillation–like pattern, and a Scandinavian-like pattern have been identified. There is the suggestion that the NAO is an intrinsic mode of variability independent of the Pacific.

Phosphorus dynamics and export in streams draining micro-catchments: Development of empirical models

Annual total phosphorus (TP) export data from 108 European micro-catchments were analyzed against descriptive catchment data on climate (runoff), soil types, catchment size, and land use. The best possible empirical model developed included runoff, proportion of agricultural land and catchment size as explanatory variables but with a low explanation of the variance in the dataset (R-2 = 0.37). Improved country specific empirical models could be developed in some cases. The best example was from Norway where an analysis of TP-export data from 12 predominantly agricultural micro-catchments revealed a relationship explaining 96% of the variance in TP-export. The explanatory variables were in this case soil-P status (P-AL), proportion of organic soil, and the export of suspended sediment. Another example is from Denmark where an empirical model was established for the basic annual average TP-export from 24 catchments with percentage sandy soils, percentage organic soils, runoff, and application of phosphorus in fertilizer and animal manure as explanatory variables (R-2 = 0.97).