Publications

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.

The focus of this paper is on cross-region R&D collaboration funded by the 5th EU Framework Programme (FP5). The objective is to measure distance, institutional, language and technological barrier effects that may hamper collaborative activities between European regions. Particular emphasis is laid on measuring discrepancies between two types of collaborative R&D activities, those generating output in terms of scientific publications and those that do not. The study area is composed of 255 NUTS-2 regions that cover the pre-2007 member states of the European Union (excluding Malta and Cyprus) as well as Norway and Switzerland. We employ a negative binomial spatial interaction model specification to address the research question, along with an eigenvector spatial filtering technique suggested by Fischer and Griffith (2008) to account for the presence of network autocorrelation in the origin-destination cooperation data. The study provides evidence that the role of geographic distance as collaborative deterrent is significantly lower if collaborations generate scientific output. Institutional barriers do not play a significant role for collaborations with scientific output. Language and technological barriers are smaller but the estimates indicate no significant discrepancies between the two types of collaborative R&D activities that are in focus of this study.

This paper provides some evidence on the importance of geographically mediated knowledge spillovers from university research activities to regional knowled

This study suggests a two-step approach to identifying and interpreting regional convergence clubs in Europe. The first step involves identifying the number and composition of clubs using a space-time panel data model for annual income growth rates in conjunction with Bayesian model comparison methods. A second step uses a Bayesian space-time panel data model to assess how changes in the initial endowments of variables (that explain growth) impact regional income levels over time. These dynamic trajectories of changes in regional income levels over time allow us to draw inferences regarding the timing and magnitude of regional income responses to changes in the initial conditions for the clubs that have been identified in the first step. This is in contrast to conventional practice that involves setting the number of clubs ex ante, selecting the composition of the potential convergence clubs according to some a priori criterion (such as initial per capita income thresholds for example), and using cross-sectional growth regressions for estimation and interpretation purposes. KEYWORDS: Dynamic space-time panel data model, Bayesian model comparison, European regions JEL Classification: C11, C23, O47, O52

This paper presents a theoretical growth model that accounts for technological interdependence among regions in a Mankiw-Romer-Weil world. The reasoning behind the theoretical work is that technological ideas cannot be fully appropriated by investors and these ideas may diffuse and increase the productivity of other firms. We link the diffusion of ideas to spatial proximity and allow for ideas to flow to nearby regional economies. Through the magic of solving for the reduced form of the theoretical model and the magic of spatial autoregressive processes, the simple dependence on a small number of neighbouring regions leads to a reduced form theoretical model and an associated empirical model where changes in a single region can potentially impact all other regions. This implies that conventional regression interpretations of the parameter estimates would be wrong. The proper way to interpret the model has to rely on matrices of partial derivatives of the dependent variable with respect to changes in the Mankiw-Romer-Weil variables, using scalar summary measures for reporting the estimates of the marginal impacts from the model. The summary impact measure estimates indicate that technological interdependence among European regions works through physical rather than human capital externalities.

Über die Variabilität der Mutterbeetleistung in Malus-Populationen mit Schlußfolgerungen für eine mögliche Frühselektion vegetativ vermehrbarer Apfelunterlagen was published in Band 26, Heft 1 1978 on page 47.

Zusammenfassung Die RSO stellt ein anerkanntes, wenig invasives Therapieverfahren bei entzündlichen Gelenkerkrankungen mit einer Synovialitis im Zusammenhang mit einer RA, der reaktiven Arthritis, bei der PVNS sowie einem Haemarthros dar. Auch die eine in Deutschland als Indikation nicht zugelassene Osteoarthritis kann erfolgreich behandelt werden. Dabei werden in Abhängigkeit von den physikalischen Eigenschaften 90Yttriumcitrat für Kniegelenke, 186Rheniumsulfid für mittelgroße Gelenke sowie 169Erbiumcitrat in kolloidaler Form für kleine Gelenke eingesetzt. Die Speicherung der zur RSO eingesetzten kolloidalen Radiopharmaka hängt von der Ausprägung der Synovialitis durch die aktivierten Makrophagen ab 2. So kann aus dem Synovialitis Score schon abgeleitet werden, in welchem Umfang die Akkumulation bei den unspezifischen Synovialitiden stattfindet und wie damit der zu erwartende Therapieerfolg sein wird.

No abstract is provided for this article.

I-131-metaiodobenzylguanidine was used for treatment of neuroblastoma stage IV in three children after surgery and or chemotherapy had failed to be effective. In two of the children with multilocular lesions, after an impressive improvement of clinical symptoms tumor progression was observed. Because in about 25% of children with relapsing neuroblastoma complete remission may be achieved by combining surgery, chemotherapy, and I-131-MIBG treatment, this therapeutic modality should be included in the therapeutic strategy of stage III and IV neuroblastoma.

Two alternative methodological approaches (the IPFP based and the intramax procedures) to the problem of pattern identification in spatial interaction data are compared and evaluated in this paper. After a general discussion of the major characteristics and shortcomings of these methodologies, the paper presents the findings of a case study relying on telecommunication data measured by the Austrian PTT in 1991, in terms of erlangs. The results clearly illustrate the superiority of the intramax approach in the context of medium-sized and relatively centralised flow systems.

In January 2004, EMEA approved 90Y-radiolabelled ibritumomab tiuxetan, Zevalin, in Europe for the treatment of adult patients with rituximab-relapsed or -r

This paper evaluates the classification accuracy of three neural network classifiers on a satellite image-based pattern classification problem. The neural network classifiers used include two types of the Multi-Layer-Perceptron (MLP) and the Radial Basis Function Network. A normal (conventional) classifier is used as a benchmark to evaluate the performance of neural network classifiers. The satellite image consists of 2,460 pixels selected from a section (270 x 360) of a Landsat-5 TM scene from the city of Vienna and its northern surroundings. In addition to evaluation of classification accuracy, the neural classifiers are analysed for generalization capability and stability of results. Best overall results (in terms of accuracy and convergence time) are provided by the MLP-1 classifier with weight elimination. It has a small number of parameters and requires no problem-specific system of initial weight values. Its in-sample classification error is 7.87% and its out-of-sample classification error is 10.24% for the problem at hand. Four classes of simulations serve to illustrate the properties of the classifier in general and the stability of the result with respect to control parameters, and on the training time, the gradient descent control term, initial parameter conditions, and different training and testing sets.

The selective uptake and accumulation of 131J-Metaiodobenzylguanidine in neuroblastoma cells in vivo may be utilized for targeted irradiation. The experience with 32 neuroblastoma patients refractory to conventional high dose chemotherapy is reported. At diagnosis 8 patients had Evans stage III and 22 stage IV. 11/32 experienced recurrences after complete tumor disappearance and before mlBG treatment, 16/32 progressed from residual or nonresponding tumor and in 3/32 insufficient tumor regression by chemotherapy was observed. 2 children received one mlBG course each with no evidence of disease. Mean applied activity was 128 mCi per course (35-300 mCi), 360 mCi per patient (80-1033 mCi) and 19.2 mCi/kg per patient (3.2-37.9 mCi/kg), respectively. A total of 84 courses was given (mean 2.6 per patient). Pain relief was noticed in 14/14 patients with bone pain. Complete or very good partial remission was achieved in 5/32, partial remission in 11/32 and stable disease in 6/32 patients. In 8 children progression occurred and 2 patients were not evaluable. 20 children died, 12 are still alive (6 patients with initial stage IV, 6 with stage III disease). Main side effect was transient thrombocytopenia, which became more severe with increasing number of courses. We conclude that mlBG treatment is effective in some patients with refractory neuroblastoma and may be utilized in the future as front line therapy for patients achieving only incomplete regressions after high dose chemotherapy.

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...

The gravity model for international trade is one of the most successful empirical models in trade literature. There is a long tradition to log-linearise the multiplicative model and to estimate the parameters of interest by least squares. But this practice is inappropriate for several reasons. First of all, bilateral trade flows are frequently zero and disregarding countries that do not trade with each other produces biased results. Second, log-linearisation in the presence of heteroscedasticity leads to inconsistent estimates in general. In recent years, the Poisson gravity model along with pseudo maximum likelihood estimation methods have become popular as a way of dealing with such econometric issues as arise when dealing with origin-destination flows. But the standard Poisson model specification is vulnerable to problems of overdispersion and excess zero flows. To overcome these problems, this paper presents zero-inflated extensions of the Poisson and negative binomial specifications as viable alternatives to both the log-linear and the standard Poisson specifications of the gravity model. The performance of the alternative model specifications is assessed on a real world example, where more than half of country-level trade flows are zero. (authors' abstract)

The Poisson gravity model along with pseudo maximum likelihood (ML) methods has become a popular way to model international trade flows. This approach has several econometric advantages that we outline in the paper. We argue that estimating the parameters by ML would only be justified statistically if the trade flows were independent. Such an assumption, however, is generally not valid, and a failure to account for spatial dependence may lead to biased parameter estimates and misleading inferences. To overcome this estimation problem we suggest eigenvector spatial filtering variants of the Poisson gravity model (without and with zero-inflation) along with pseudo ML estimation.

The focus of this paper is on the neural network modelling approach that has gained increasing recognition in GIScience in recent years. The novelty about neural networks lies in their ability to model non-linear processes with few, if any, a priori assumptions about the nature of the data-generating process. The paper discusses some important issues that are central for successful application development. The scope is limited to feedforward neural networks, the leading example of neural networks. It is argued that failures in applications can usually be attributed to inadequate learning and/or inadequate complexity of the network model. Parameter estimation and a suitably chosen number of hidden units are, thus, of crucial importance for the success of real world neural network applications. The paper views network learning as an optimization problem, reviews two alternative approaches to network learning, and provides insights into current best practice to optimize complexity so to perform well on generalization tasks.