No abstract is provided for this article.
Despite a growing body of empirical evidence that demonstrates the nature of spatial variations in innovation and the adoption of new technologies, few studies have been conducted in such a way as to enable direct comparisons between different countries, either to establish international differences in innovative performance or to identify differences in regional patterns in different national contexts, particularly between EC and non-EC countries within Europe. In this paper the results of recent surveys of comparable industries in Great Britain and Austria are used to begin to address this issue, with particular attention to some of the inherent difficulties in undertaking such comparisons. By using a mixture of simple cross-tabulations and multivariate logit models, differences between the two countries in the adoption of a number of new process technologies based upon microelectronics in the spheres of manufacturing production, design, and coordination are identified. It is suggested that, not only does Austria lag Great Britain in the introduction of new technology, but that variations between similar types of region are more pronounced and entrenched in Austria at the present time.
The center of diversity of the genus Malus is situated in East Asia. The diversity of wild and cultivated apples, as a whole represent a great pool of traits for multiple use. This irretrievable diversity is to be preserved now and in the future by genebanks. This is to be done by: 1) keeping the trees in situ at the natural site (wild species) or on farm; 2) ex situ as grafted trees (cultivars), or as seedlings, and seed lots in the genebanks. For decades, classical collections of wild and cultivated apples have existed. Mostly, the material was collected a long time ago, exchanged between different arboreta, often as open-pollinated seeds. Usually, the original passport data is entirely incomplete. Additionally in collections, many representative Malus species are restricted to only a few accessions. Therefore they are neither representative for the extent of variability within a species nor for usable traits. As a result, in recent years collecting of wild specimens has been revived. For multiple use of genebank material, evaluation and characterization are necessary. The most important traits to be defined are for resistances to biotic and abiotic factors so that they may be used in breeding new cultivars.
No abstract is provided for this article.
No abstract is provided for this article.
131I-meta-iodobenzylguanidine scanning was performed in 14 patients with phaeochromocytomas. In all but one patient scintigraphy successfully localized the lesion(s). The results confirm that scintigraphic imaging with 131I-meta-iodo-benzylguanidine, a noninvasive method, is a valid and reliable procedure for imaging and localization of adrenal and extra-adrenal phaeochromocytomas, both benign and malignant.
The process of economic integration within Europe is a highly complex and multi-faceted phenomenon. There is little doubt, however, that the European Community has made persistent efforts to encourage the widening (territorial enlargement) and deepening (increasing...
This paper presents a methodology for neural spatial interaction modelling. Particular emphasis is laid on design, estimation and performance issues in both cases, unconstrained and singly constrained spatial interaction. Families of classical neural network models, but also less classical ones such as product unit neural network models are considered. Some novel classes of product unit and summation unit models are presented for the case of origin or destination constrained spatial interaction flows. The models are based on a modular connectionist architecture that may be viewed as a linked collection of functionally independent neural modules with identical feedforward topologies, operating under supervised learning algorithms. Parameter estimation is viewed as Maximum Likelihood (ML) learning. The nonconvex nature of the loss function makes the Alopex procedure, a global search procedure, an attractive and appropriate optimising scheme for ML learning. A benchmark comparison against the classical gravity models illustrates the superiority of both, the unconstrained and the origin constrained, neural network model versions in terms of generalization performance measured by Kullback and Leibler`s information criterion. Hereby, the authors make use of the bootstrapping pairs approach to overcome the largely neglected problem of sensitivity to the specific splitting of the data into training, internal validation and testing data sets, and to get a better statistical picture of prediction variability of the models. Keywords: Neural spatial interaction models, origin constrained or destination constrained spatial interaction, product unit network, Alopex procedure, boostrapping, benchmark performance tests.
Club-convergence analysis provides a more realistic and detailed picture about regional income growth than traditional convergence analysis. This paper pre
Artificial intelligence (Al) has received an explosion of interest during the last five years in various fields. There is no longer any question that expert systems and neural networks will be of central importance for developing the next generation of more intelligent geographic information systems. Such knowledge based geographic information systems will especially play a key role in spatial decision and policy analysis related to issues such as environmental monitoring and management, land use planning, motor vehicle navigation and distribution logistics. This paper sketches briefly the major characteristics of conventional geographic information systems, and then looks at some of the potentials of Al principles and techniques in a GIS environment where emphasis is laid on expert systems and artificial neural networks technologies and techniques.
Neu für das Burgenland ist Carpesium cernuum (105); neu für Wien sind Samolus valerandi (122), die Neophyten Medicago arabica (114) und Agastache foeniculum (99); neu für Niederösterreich ist, ebenfalls verschleppt, Cabomba caroliniana (104). Einige Arten bzw. Unterarten sind Wiederfunde nach längerer Zeit: für Österreich der Neophyt Medicago arabica (114); für das Burgenland: Oenanthe fistulosa (115); für Wien: Potamogeton nodosus (119); für Niederösterreich: Rumex salicifolius subsp. triangulivalvis (121). Entgegen neueren Befürchtungen sind Elatine alsinastrum (109) und Hypericum barbatum (110) im Burgenland nicht ausgestorben. Für einige seltene Taxa werden aus der jüngsten Vergangenheit neue Fundorte oder Wiederfunde mitgeteilt: Davon sind Einheimische (Indigene + Archäophyten), die bisher nicht oder ungenügend beachtet worden oder großteils im Rückgang befindlich sind: Arnoseris minima (100), Astragalus sulcatus (103), Doronicum glaciale subsp. glaciale (108), Klasea lycopifolia (112), Orobanche pancicii (117), Ranunculus pygmaeus (120), Scandix pecten-veneris (123). Ein Neophyt ist im Rückgang: Centaurea solstitialis (107); die meisten Neophyten aber sind mehr oder weniger stark im Vormarsch: Artemisia annua (101), Asclepias syriaca (102), Celtis australis (106), Iva xanthiifolia (111), Lathyrus sphaericus (113), Opuntia phaeacantha (116), Polycarpon tetraphyllum (118).
In Deutschland werden pro Jahr Patienten mit etwa 50 neuen Prostatakarzinomen sowie etwa 85 neuen Mammakarzinomen auf 100 000 Einwohner diagnostiziert. Tumorbedingte Schmerzen und die Entwicklung von Knochenmetastasen sind häufig auftretende Begleiterscheinungen. 40–50% der tumorbedingten Schmerzen werden durch Knochenmetastasen hervorgerufen (6). Ziel der Behandlung muss es sein, die Lebensqualität zu verbessern, das heißt „to add life to the years, not years to the life“.
The safety of operating nuclear power plants (NPPs) can be improved either by strengthening the preventive and/or the mitigative path. Though, preventing the accident in the first place is of highest priority, it is evident that, at some point, further improvements in preventive features will no longer lead to a proportional increase in safety, nor can they completely eliminate all possible sequences leading to core melting. Mitigation features can limit and contain the otherwise high negative consequences of a severe accident, by preserving the integrity of the containment under severe accident conditions. One of the relevant containment failure modes is basemat melt-through. Its potentially high relevance has been demonstrated by the Fukushima-Daiichi accidents in which the uncontained interaction of the core melt with the basemat concrete led to long-term activity releases, high costs for containing them, and complicated post-accident fuel removal. While new-build Gen-III NPPs typically prevent molten core-concrete interaction (MCCI) by implementing dedicated measures for core melt stabilization (CMS), no such provisions exist in operating Gen-II plants and therefore would have to be retrofitted. Though retrofitting can result in high related efforts and costs, it may nevertheless be an option in countries where corresponding safety improvements are recommended or even required to either regain the operational license or extend the plant’s lifetime. In this context, Framatome investigated various CMS concepts with respect to their suitability for Gen-II retrofitting, building on the experience gained during the conceptual development of the EPR. One general finding of this exercise was that the chosen best-fit solution always depends on the specific constraints of the plant under consideration, as well as on other aspects, like the spectrum of conditions and assumptions to be covered and the functional requirements to be fulfilled. Last but not least, the solutions must remain simple enough so that efforts for installation and service and the related cost and time constraints stay in an acceptable relation to the achievable safety gain. The paper first provides an overview of the applicable technical solutions, including their specific benefits and disadvantages, then lists the typical functional requirements and limitations and shows which ex-vessel solutions have the highest potential and are currently considered or used for retrofitting. Finally the results of a screening of available melt stabilization solutions for an exemplary Mark-I boiling water reactor (BWR) containment are given.
Building a feedforward computational neural network model (CNN) involves two distinct tasks: determination of the network topology and weight estimation. The specification of a problem adequate network topology is a key issue and the primary focus of this contribution. Up to now, this issue has been either completely neglected in spatial application domains, or tackled by search heuristics (see Fischer and Gopal 1994). With the view of modelling interactions over geographic space, this paper considers this problem as a global optimization problem and proposes a novel approach that embeds backpropagation learning into the evolutionary paradigm of genetic algorithms. This is accomplished by interweaving a genetic search for finding an optimal CNN topology with gradient-based backpropagation learning for determining the network parameters. Thus, the model builder will be relieved of the burden of identifying appropriate CNN-topologies that will allow a problem to be solved with simple, but powerful learning mechanisms, such as backpropagation of gradient descent errors. The approach has been applied to the family of three inputs, single hidden layer, single output feedforward CNN models using interregional telecommunication traffic data for Austria, to illustrate its performance and to evaluate its robustness.
The availability of spatial databases and widespread use of geographic information systems has stimulated increasing interest in the analysis and modelling of spatial data. Spatial data analysis focuses on detecting patterns, and on exploring and modelling relationships between them in order to understand the processes responsible for their emergence. In this way, the role of space is emphasised , and our understanding of the working and representation of space, spatial patterns, and processes is enhanced. In applied research, the recognition of the spatial dimension often yields different and more meaningful results and helps to avoid erroneous conclusions. This book aims to provide an introduction into spatial data analysis to graduates interested in applied statistical research. The text has been structured from a data-driven rather than a theory-based perspective, and focuses on those models, methods and techniques which are both accessible and of practical use for graduate students. Exploratory techniques as well as more formal model-based approaches are presented, and both area data and origin-destination flow data are considered.
