Lebensmittel, die im Emissionsbereich Chemischer Reinigungen gelagert bzw. verkauft werden, können erheblich mit Tetrachlorethen belastet sein. Hohe T
ISHS XI Eucarpia Symposium on Fruit Breeding and Genetics NEW PEAR CULTIVARS FROM DRESDEN-PILLNITZ
As part of the validation of the In-Vessel Melt Retention (IVR) strategy for its KERENA BWR, AREVA NP has performed a quantitative assessment of the potential impact of thermochemical phenomena. This was motivated by the fact that several of these phenomena, namely the formation of a dense metallic phase, have the potential to lead to a strong increase in local heat fluxes, with the risk of early IVR failure. In this context, experiments performed in the MASCA project with PWR-type corium melts were repeated using a typical BWR core melt: characterized by a lower U/Zr-ratio and higher contents of Zr, steel, and boron carbide (B{sub 4}C). Applying an improved 'cold crucible' induction heating technique, two series of test were performed, first without B{sub 4}C and then with a B{sub 4}C content of about 1.4 wt%. These two values bound the uncertainty with respect to the incorporation of B{sub 4}C into the molten pool. The target of the tests was to localize the point of equal densities between the dense metallic phase (Fe, U, Zr and O) and the residual oxidic phase in thermo-chemical equilibrium. An interesting result of these experiments was that, different from earlier MASCA tests with PWR-type coriummore » that showed an only insignificant impact of B{sub 4}C on metal density, the new experiments reveal a strong corresponding effect, which can over-compensates the density increase caused by U-migration into the metallic melt. This deviating result is attributed, first, to the higher Zr-fraction in the BWR-type core melt, and second, to the higher content of B{sub 4}C in the BWR-type melt in comparison to the MASCA tests (B{sub 4}C-content <0.5 wt%). Based on the obtained results it is predicted that - under certain conditions -B{sub 4}C can completely prevent the formation of a dense metallic phase, independent of the amount of molten steel in the melt. The paper gives an overview of the performed experiments and their main results and provides theoretical models to explaining the observed strong reduction in metallic phase density in presence of B{sub 4}C Their predictions are then compared to the experimental data. (authors)« less
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Spatial interaction models of the gravity type are widely used to describe origin-destination flows. They draw attention to three types of variables to explain variation in spatial interactions across geographic space: variables that characterize the origin region of interaction, variables that characterize the destination region of interaction, and variables that measure the separation between origin and destination regions. A violation of standard minimal assumptions for least squares estimation may be associated with two problems: spatial autocorrelation within the residuals, and spatial autocorrelation within explanatory variables. This paper compares a spatial econometric solution with the spatial statistical Moran eigenvector spatial filtering solution to accounting for spatial autocorrelation within model residuals. An example using patent citation data that capture knowledge flows across 257 European regions serves to illustrate the application of the two approaches.
Die folgenden Notizen bilden die Fortsetzung des entsprechenden Artikels in Neilreichia 6: 327–362 (2011). Sie sind in vier Abschnitte gegliedert: 1. Taxonomische Neuerungen. 2. Nomenklatorische Anderungen. 3. Verbesserungen und Erganzungen der Schlussel und der Angaben zu den Taxa. 4. Floristische Neuerungen, floristische Literatur und Naturschutz.
131I-metaiodobenzylguanidine (131I-MIBG) is used for the scintigraphic localization of catecholamine-producing tissue in patients with pheochromocytomas, neuroblastomas, and apudomas. In high concentrations and doses, the same radiopharmaceutical agent...
The aim of the Pillnitz genetic resources programme for fruit is to conserve, evaluate and make available national and international cultivated and local varieties and wild species of apples, cherries, plums, pears, strawberries for genetics, fruit breeding,...
In this paper a systematic introduction to computational neural network models is given in order to help spatial analysts learn about this exciting new field. The power of computational neural networks viz-à-viz conventional modelling is illustrated for an application field with noisy data of limited record length: spatial interaction modelling of telecommunication data in Austria. The computational appeal of neural networks for solving some fundamental spatial analysis problems is summarized and a definition of computational neural network models in mathematical terms is given. Three definitional components of a computational neural network—properties of the processing elements, network topology and learning—are discussed and a taxonomy of computational neural networks is presented, breaking neural networks down according to the topology and type of interconnections and the learning paradigm adopted. The attractiveness of computational neural network models compared with the conventional modelling approach of the gravity type for spatial interaction modelling is illustrated before some conclusions and an outlook are given.
Since the beginning of this decade the use of automated or robotic-systems for analytical purposes has decreased rapidely. Starting from the analysis of agriculturing products or medical samples, these instruments are now more and more common in the pharmaceutical industry. The systems are used for R&D purposes mainly in the area of combinatorial chemistry to analyze the huge amount of synthesis products in the biomedical labs and in chemical-physical laboratories of Quality Contol Units. Extensive stability studies, which have to be perfomed for new drug applications, and the release testing of medicinal products with a very high manufacturing batch-rate per year need highly effective analytical methods. Thus, Byk Gulden has introduced two automated systems based on Zymark products (TPWII and MultiDose), for the stability tests of an enteric-coated tablet. The number of batches, pack types and storage conditions (total number of samples: appr. 40 for the 3- and 6-months timepoints), for this stability study was required automation of the most time consuming test methods for purity, assay and dissolution of the tablets, because of the tight schedule for timepoints in the first year of storage (in general: two weeks). In order to have these automated systems in place for routine testing in a very short time, the method transfer from the manual procedure as well as the optimization and validation work (MTOV), were done completely by the supplier, Zymark. The other system, which is a customer designed robotic system built also by Zymark, is used for the release testing of an x-ray contrast medium with a very high batch-rate per year (approxmimately four batches per day that have to be analyzed). This enormous testing frequency is hardly to be realized by manual methods. Experiences with an already existent robotic systems has shown that the laboratory flow-through times are 30 to 50% decreased compared to manual testing.
The focus in this paper is on knowledge spillovers between high-technology firms in Europe, as captured by patent citations. High-technology is defined to include the ISIC-sectors aerospace (ISIC 3845), electronics-telecommunication (ISIC 3832), computers and office equipment (ISIC 3825), and pharmaceuticals (ISIC 3522). The European coverage is given by patent applications at the European Patent Office that are assigned to high-technology firms located in the EU-25 member states, the two accession countries Bulgaria and Romania, and Norway and Switzerland. By following the paper trail left by citations between these high-technology patents we adopt a Poisson spatial interaction modelling perspective to identify and measure spatial separation effects to interregional knowledge spillovers. In doing so we control for technological proximity between the regions, as geographical distance could be just proxying for technological proximity. The study produces prima facie evidence that geography matters. First, geographical distance has a significant impact on knowledge spillovers, and this effect is substantial. Second, national border effects are important and dominate geographical distance effects. Knowledge flows within European countries more easily than across. Not only geography, but also technological proximity matters. Interregional knowledge flows are industry specific and occur most often between regions located close to each other in technological space.
Although there is a substantial body of literature on labour market analysis, most of it ignores the spatial dimension of the labour market. A spatial perspective in analysing labour market processes is important for several reasons. FIRST, labour markets are by no means as homogeneous as conventional labour market theories assume. SECOND, most countries are displaying strong regional variations in the dynamics of unemployment. THIRD, geographical space exerts a frictional effect on labour market processes. Regional unemployment rates appear to be the most important indicators for analysing labour market processes from a spatial perspective. The paper aims to discuss some of the problems that are associated with the use of regional unemployment rates. We will focus attention on conceptual problems, problems of data quality and on some of the new problems that have arisen due to the widespread use of new computer technology. Solutions to many of the problems are obvious, but many of the new problems will require some extra effort for their solution. The tyranny that threatens the research community is that regional unemployment data exercise a power over us that can lead the naive to misinterpretations. The data may mislead even the most righteous among us. A good deal of research effort is often given to overcome the tyranny that is found in the columns and rows that the lay public likes to call statistics. The discussion will be enriched by means of a study utilizing regional unemployment rates at the district level in West Germany.
This paper exposes problems of the commonly used technique of splitting the available data in neural spatial interaction modelling into training, validation, and test sets that are held fixed and warns about drawing too strong conclusions from such static splits. Using a bootstrapping procedure, we compare the uncertainty in the solution stemming from the data splitting with model specific uncertainties such as parameter initialization. Utilizing the Austrian interregional telecommunication traffic data and the differential evolution method for solving the parameter estimation task for a fixed topology of the network model [i.e. J=8] this paper illustrates that the variation due to different resamplings is significantly larger than the variation due to different parameter initializations. This result implies that it is important to not over-interpret a model, estimated on one specific static split of the data.
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
The context of this chapter is set by the contemporary transition from an industrial to a knowledge-based economy. OECD (1996a) has documented the way in which the knowledge-based economy of learning individuals, organisations and economies is emerging out of the...
