Publications

This paper describes how transport planning is basically concerned with the establishment of a stable relationship between the demand for, and the supply of traffic infrastructure and transport services. In recent years and in the current environment, the relationship between supply and demand has been somewhat one-sided in many European countries in the sense that (commodity and person) transport growth and demand for transport services have outstripped both investment outlay and institutional ability to deal with the complexity of the problem attached to the renewal and expansion of transport infrastructure. This strong contrast between traffic growth and infrastructure investments since the 1970s has resulted in transport bottlenecks in many countries and regions. This paper focuses on passenger transport and travel demand. The legacy of more than three decades of travel demand analysis is a larger, rather diverse and often disparate body of information. No longer is research into travel demand to be focused narrowly on the theme of forecasting. The need for the understanding of travel behavior has become a prominent theme. The paper describes how this broader debate has resulted in an influx of new ideas, methodologies, and techniques, which were stimulating to traffic researchers, but have frustrated transport practitioners seeking to identify state-of-the-art in the field.

A novel rough set approach is proposed in this paper to discover classification rules through a process of knowledge induction which selects optimal decision rules with a minimal set of features necessary and sufficient for classification of real-valued data. A rough set knowledge discovery framework is formulated for the analysis of interval-valued information systems converted from real-valued raw decision tables. The optimal feature selection method for information systems with interval-valued features obtains all classification rules hidden in a system through a knowledge induction process. Numerical examples are employed to substantiate the conceptual arguments.

This paper uses data for 255 NUTS-2 European regions over the period 1995-2003 to test the relative explanatory performance of two important rival theories seeking to explain variations in the level of economic development across regions, namely the neoclassical model originating from the work of Solow (1956) and the so-called Wage Equation, which is one of a set of simultaneous equations consistent with the short-run equilibrium of new economic geography (NEG) theory, as described by Fujita, Krugman and Venables (1999). The rivals are non-nested, so that testing is accomplished both by fitting the reduced form models individually and by simply combining the two rivals to create a composite model in an attempt to identify the dominant theory. We use different estimators for the resulting panel data model to account variously for interregional heterogeneity, endogeneity, and temporal and spatial dependence, including maximum likelihood with and without fixed effects, two stage least squares and feasible generalised spatial two stage least squares plus GMM; also most of these models embody a spatial autoregressive error process. These show that the estimated NEG model parameters correspond to theoretical expectation, whereas the parameter estimates derived from the neoclassical model reduced form are sometimes insignificant or take on counterintuitive signs. This casts doubt on the appropriateness of neoclassical theory as a basis for explaining cross-regional variation in economic development in Europe, whereas NEG theory seems to hold in the face of competition from its rival.

Das Wissen über die Pathophysiologie, den klinischen Verlauf und die therapeutischen Möglichkeiten bei sog. Long-QT-Syndromen (LQTS) ist seit der

No abstract is provided for this article.

Geographical Information Systems (GIS) are capable of acquiring spatially indexed data from a variety of sources, changing the data into useful formats, storing the data, retrieving and manupulating the data for analysis, and then generating the output required by a given user. Their great strength is based on the ability to handle large, multilayered, heterogenous databases and to query about the existence, location and properties of a wide range of spatial objects in an interactive way. The lack of analytical and modelling functionality is, however, widely recognised as a major deficiency of current systems. There is a wide agreement in both the GIS community and the modelling community that the future success of GIS technology will depend to a large extent on incorporating more powerful analytical and modelling capabilities. This paper discusses some major directions and strategies to increase both the analytical and modelling capabilities and the level of intelligence of geographic information systems.

The Pillnitz apple rootstock breeding programme was concluded with the following results:...

This guideline is a prerequisite for the quality management in the treatment of non-Hodgkin-lymphomas using radioimmunotherapy. It is based on an interdisciplinary consensus and contains background information and definitions as well as specified indications and detailed contraindications of treatment. Essential topics are the requirements for institutions performing the therapy. For instance, presence of an expert for medical physics, intense cooperation with all colleagues committed to treatment of lymphomas, and a certificate of instruction in radiochemical labelling and quality control are required. Furthermore, it is specified which patient data have to be available prior to performance of therapy and how the treatment has to be carried out technically. Here, quality control and documentation of labelling are of greatest importance. After treatment, clinical quality control is mandatory (work-up of therapy data and follow-up of patients). Essential elements of follow-up are specified in detail. The complete treatment inclusive after-care has to be realised in close cooperation with those colleagues (haematology-oncology) who propose, in general, radioimmunotherapy under consideration of the development of the disease.

In a postulated core meltdown accident in a light water reactor there are bound to be interactions, in the ex-vessel phase, among the core melt and the structural materials within and below the reactor cavity. In existing plants, these structural materials normally are structural concrete, while future, evolutionary reactor lines are to have sacrificial and protective materials specially designed for this hypothetical case. To add to the state of knowledge about the phenomena occurring, experiments need to be conducted under conditions as realistic as possible. Within the research programs funded by the European Union, the German Federal Ministry for Economics, and the German nuclear power plant operators, experiments on a laboratory as well as an industrial scale on these problems are being carried out in the two projects called CORESA (COrium on REfractory and SAcrificial materials) and ECOSTAR (Ex-vessel COre melt STAbilization Research). The experiments are accompanied by an extensive analytical theoretical program also serving to advance and validate computer codes on the problems under investigation. The projects, which are carried out with international European participation, are expected to allow a concept to be developed for managing postulated accident scenarios involving core meltdown for innovative nuclear power plants, and to provide findings on risk evaluation of plants now in operation so as to further develop accident management measures.

The focus of this article is on precompetitive research and development (R&D) cooperation across Europe, as captured by R&D joint ventures funded by the European Commission in the time period 1998–2002, within the Fifth Framework Programme. The cooperations in this program give rise to a bipartite network with 72,745 network edges between 25,839 actors (representing organizations that include firms, universities, research organizations, and public agencies) and 9,490 R&D projects. Participating actors are linked only through joint projects. In this article, we describe a community-identification problem based on the concept of modularity, use the recently introduced label-propagation algorithm to identify communities in the network and differentiate the identified communities by developing community-specific profiles with social network analysis and geographic visualization techniques. We expect the results to enrich our picture of the European Research Area (ERA) by providing new insights into the global and local structures of R&D cooperation across Europe. Este artículo se centra en la cooperación en investigación precompetitiva y desarrollo (I + D) en toda Europa tal y como se manifiesta en iniciativas conjuntas de I + D financiadas por la Comisión Europea durante el periodo 1998–2002, dentro del Quinto Programa Marco (5PM). La cooperación en este programa dio lugar a una red bipartita con 72.745 conexiones entre los 25.839 agentes (representando organizaciones que incluyen empresas, universidades, organizaciones de investigación y organismos públicos), y 9.490 proyectos de I + D. Los agentes participantes están vinculados sólo a través de proyectos conjuntos. En este artículo describimos un problema de identificación comunitaria basado en el concepto de modularidad, usamos el recientemente introducido algoritmo de propagación de etiquetas, Label-propagation Algorithm (LPA) para identificar las comunidades en la red, y diferenciamos las comunidades identificadas desarrollando perfiles específicos comunitarios mediante el análisis de redes sociales y técnicas de visualización geográfica. Esperamos que los resultados enriquezcan nuestra visión del Espacio Europeo de Investigación (European Research Area, ERA), aportando nuevas perspectivas sobre las estructuras globales y locales de cooperación en I + D en Europa. 本文关注1998–2002年间在第五框架计划(FP5)下由研究与发展联合基金支持的欧盟研发计划中的竞争前欧洲研发合作。该项目合作形成一个在25839个参与者(执行组织,包括企业,大学,研究机构级公共部门)和9490个项目间拥有72745条边的双向网络,参与者仅仅通过合作项目连接。本文描述了基于模块化的社团识别问题。利用最近发展的标签传递算法(LPA)对网络群体进行识别,利用社会网络分析和地理可视化方法构建了群体专属的描述,区分识别出不同研发群体的资料。希望上述结果可以提供欧洲范围内研发合作的全局和局部结构的新视角,从而丰富欧洲研究区(ERA)的图景。

Summary US yield curve dynamics are subject to time‐variation, but there is ambiguity about its precise form. This paper develops a vector autoregressive (VAR) model with time‐varying parameters and stochastic volatility, which treats the nature of parameter dynamics as unknown. Coefficients can evolve according to a random walk, a Markov switching process, observed predictors, or depend on a mixture of these. To decide which form is supported by the data and to carry out model selection, we adopt Bayesian shrinkage priors. Our framework is applied to model the US yield curve. We show that the model forecasts well, and focus on selected in‐sample features to analyze determinants of structural breaks in US yield curve dynamics.

This paper focuses on Austrian outbound foreign direct investment (FDI, measured by sales of Austrian affiliates abroad) in Europe over the period 2009–2013, using a spatial Durbin panel data model specification with fixed effects, and a spatial weight matrix based on the first-order contiguity relationship of the countries and normalised by its largest eigenvalue. Third-country effects essentially enter the empirical analysis in two major ways: first, by the endogenous spatial lag on FDI (measured by FDI into markets nearby the host country), and, second, by including an exogenous market potential variable that measures the size of markets nearby the FDI host country in terms of gross domestic product. The question whether the empirical result is compatible with horizontal, vertical, export-platform or complex vertical FDI then depends on the sign and significance levels of both the coefficient of the spatial lag on FDI and the direct impact estimate of the market potential variable. The paper yields robust results that provide significant empirical evidence for horizontal FDI as the main driver of Austrian outbound FDI in Europe. This result is strengthened by the indirect impact estimate of the market potential variable indicating that spatial spillovers do not matter.

The hypothesis in this paper is that the existence of retail markets may not necessarily be determined by spatial factors and increasing return in transportation (or increasing returns in retailing), but can be explained by the rational behaviour of firms operating in a stochastic environment. It is shown that demand uncertainty can serve as an independent source of retail trade. Consequently, the ability of firms to process information and predict demand (i.e. to decrease demand uncertainty) may affect the characteristics of retail markets. The results indicate that risk-averse firms always devote resources to demand forecasting; producers are better off trading with retailers than with final consumers; and the volume of output supplied through retail markets is greater than it would be if producers traded directly with consumers (thus benefiting social welfare). Furthermore, the contribution shows that technological progress in data-processing, which allows for cheaper and better predictions of market demand, increases the number of firms operating in retail markets.

Gegenstand der Humanökologie ist die Wechselwirkung von Natur und Gesellschaft. Ein zwischen Natur- und Sozialwissenschaften liegender, neu entstehender Ansatz wird notwendig, weil einerseits der Mensch als biologische Art nicht losgelöst von der ihn...

No abstract is provided for this article.