Veronica davisii M. A.Fischer, sp. n., limited to the mountains of Kurdistan (S. E. Turkey and N. Iraq), is related to the Turkish-CaucasianV. gentianoides
No abstract is provided for this article.
The development of the MCCI code COSACO specifically addresses the ex-vessel MCCI phase of the core melt retention concept of the EPR. The general philosophy behind COSACO is a rigerous representation of thermochemical phenomena related to the MCCI. In particular, the code incorporates a real solution database to predict the simultaneous formation of solid and liquid phases as well as chemical reactions for a significant number melt constituents. This offers a great flexibility in terms of application to MCCIs involving reactor materials and to tests conducted with simulant melts. The approach to model heat transfer in oxidic melt pools is based on the phase segregation hypothesis. Besides a brief description of the principal models incorporated in COSACO, this paper highlights specific thermochemical effects that arose as part of post-test calculations of the tests MACE M3b and MACE M4 with this new code version. Particular attention is drawn to the effect of melt ejections on the pool temperature as well as to the evolution of solid volumetric fraction and of melt front progression during the MCCI. Finally, the application to a representative EPR specific sequence indicates that the principal objectives of the MCCI in the reactor pit can be safely fulfilled.
No abstract is provided for this article.
In this paper, we explore the relationship between state-level household income inequality and macroeconomic uncertainty in the United States. Using a novel large-scale macroeconometric model, we shed light on regional disparities of inequality responses to a national uncertainty shock. The results suggest that income inequality decreases in most states, with a pronounced degree of heterogeneity in terms of shapes and magnitudes of the dynamic responses. By contrast, some few states, mostly located in the West and South census region, display increasing levels of income inequality over time. We find that this directional pattern in responses is mainly driven by the income composition and labor market fundamentals. In addition, forecast error variance decompositions allow for a quantitative assessment of the importance of uncertainty shocks in explaining income inequality. The findings highlight that volatility shocks account for a considerable fraction of forecast error variance for most states considered. Finally, a regression-based analysis sheds light on the driving forces behind differences in state-specific inequality responses.
Analyses of interaction patterns across geographical space have always been at the forefront of interest in the spatial sciences. Although a wide variety of contexts have been examined, in this paper we shall restrict our attention to those situations in which patterns of communication are affected by the existence or imposition of barriers. According to Nijkamp, Rietveld and Salomon (1990), obstacles in space or time that impede the smooth transfer or free movement of information-related goods can be regarded as barriers to communication. For our present exploratory purpose, significant discontinuities in the flow intensity of communications may signify the existence of barriers. Their effects on communication patterns are generally nonlinear and often stepwise in character. They may not approximate traditional frictions of distance - which are mostly continuous in character.
The efficacy of inhaled products is affected by the degree, and potentially the site, of drug particle deposition in the lungs. Lung deposition correlates with the fine particle fraction (FPF; the proportion of dose containing particles <5 μm in aerodynamic diameter). This in vitro study (defining fluticasone propionate/formoterol particulate size [DIFFUSE]) examined the effects of inhalation flow rate on the FPF of the fluticasone propionate/formoterol (FP/FORM) pMDI aerosol compared with three other inhaled corticosteroids/long-acting β2-agonist (ICS/LABA) combination therapies administered by either DPI or pMDI [fluticasone propionate/salmeterol (FP/SAL), budesonide/formoterol (BUD/FORM) and beclometasone dipropionate/formoterol (BDP/FORM)]. Aerodynamic particle size distribution was determined for each product using an 8-stage Andersen Cascade Impactor at two inhalation flow rates: 28.3 and 60.0 L/min. Fine particle dose (mass of dose <5.0 μm) and FPF were calculated as a percentage of the labeled dose for the LABA and ICS of each product at both flow rates. FP/FORM suspension aerosol provided a high and consistent FPF of approximately 40% for the ICS and LABA components at both flow rates. At 28.3 L/min, the FPF of each component of FP/FORM (41.2% and 39.2%) was greater than that of FP/SAL DPI (12.5% and 11.3%), BUD/FORM DPI (8.2% and 6.6%) and BDP/FORM pMDI (28.5% and 26.0%). At 60.0 L/min, the FPFs of the FP/FORM components (43.7% and 42.1%) were greater than those of FP/SAL (17.8% and 14.8%) and BUD/FORM (35.0% and 30.1%), and similar to those of BDP/FORM (43.0% and 39.5%). The FP/FORM suspension aerosol produced a high and consistent FPF of approximately 40% across both flow rates. The consistent FPF in vitro may be predictive of FP/FORM providing more consistent drug dosing in vivo, helping to counteract variable lung dose due to variation in inspiratory flow rate among patients and between a patient's day-to-day or successive inhalation maneuvers.
Big Data on cities and regions bring new opportunities and challenges to data analysts and city planners. On the one side, they hold great promise to combine increasingly detailed data for each citizen with critical infrastructures to plan, govern and manage cities and regions, improve their sustainability, optimize processes and maximize the provision of public and private services. On the other side, the massive sample size and high-dimensionality of Big Data and their geo-temporal character introduce unique computational and statistical challenges. This chapter provides overviews on the salient characteristics of Big Data and how these features impact on paradigm change of data management and analysis, and also on the computing environment.
The origins of modern spatial analysis lie in the development of quantitative geography and regional science in the late 1950s. The use of quantitative procedures and techniques to analyse patterns of points, lines, areas and surfaces depicted on analogue maps or...
Artificial intelligence (AI) has received an explosion of interest during the last 5 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 play an especially 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 AI principles and techniques in a GIS environment where emphasis is laid on expert systems and artificial neural networks technologies and techniques.
No abstract is provided for this article.
ISHS International Strawberry Symposium STRAWBERRY VARIETIES FOR MECHANICAL HARVESTING
GeoComputation may be a research paradigm still in the making, but it has the potential to dramatically change current research practice in the spatial sciences. Different people, however, have different views of this research paradigm. For some it is synonymous with...
No abstract is provided for this article.
Die drei hochalpinen Polster-ZwergsträucherVeronica caespitosa Boiss.,V. bombycina Boiss. &Kotschy aus Kleinasien und dem Libanon sowieV. thes
Birnengitterrost breitet sich in nicht kommerziell genutzten Anlagen zunehmend aus, vor allem dort, wo Pflanzenschutzmaßnahmen unterbleiben. In unsere
The explosion of activities and requirements associated with the production, processing and transfer of information is increasingly being matched by a profileration and diversification of new telecommunication media for transmitting information, including text processing and transmission services such as facsimile transmission, videotex, teleconference services, electronic mail etc. Nevertheless, the telephone is still - by far - the most important telecommunication service. The paper results from ESF-research undertaken within the Network on European Communication and Transport Activity Research (NECTAR) and relates to telephone communication undertaken for the Netherlands by Rietveld and Jansen (1990) and Switzerland by Rossera (1990). The current study focuses on the Austrian case and relies on data measured by the Austrian PTT in 1991, in terms of erlangs, an internationally widely used and reliable measure of telecommunication contact intensity. The data refer to the total telecommunication traffic on the public network. Due to technical reasons oral communication can not be distinguished from other services such as data transmission, transfer of documents and text (facsimile) etc. But the demand for such new telecommunication services is still at a very modest level in Austria. The paper addresses two major issues. First an attempt is made to explore the factors influencing the spatial pattern of domestic telephone traffic in Austria. The econometric approach applied to this problem belongs to the class of spatial interaction models explaining a telephone communication flow from a region i to a region j by three types of factors, factors associated with the region of origin, factors associated with the region of destination and factors associated with origin-destination pairs (separation factors). In using the spatial interaction modelling approach in telephone traffic analysis various choices need to be made about how the above mentioned factors should be defined. To have confidence in the model results it is desirable that its interpretation is insensitive to the particular choices made. Whether this is so, will be investigated for several potential sources of variation in model performance.
This paper considers the most important aspects of model uncertainty for spatial regression models, namely the appropriate spatial weight matrix to be employed and the appropriate explanatory variables. We focus on the spatial Durbin model (SDM) specification in this study that nests most models used in the regional growth literature, and develop a simple Bayesian model averaging approach that provides a unified and formal treatment of these aspects of model uncertainty for SDM growth models. The approach expands on the work by LeSage and Fischer (2008) by reducing the computational costs through the use of Bayesian information criterion model weights and a matrix exponential specification of the SDM model. The spatial Durbin matrix exponential model has theoretical and computational advantages over the spatial autoregressive specification due to the ease of inversion, differentiation and integration of the matrix exponential. In particular, the matrix exponential has a simple matrix determinant which vanishes for the case of a spatial weight matrix with a trace of zero (LeSage and Pace 2007). This allows for a larger domain of spatial growth regression models to be analysed with this approach, including models based on different classes of spatial weight matrices. The working of the approach is illustrated for the case of 32 potential determinants and three classes of spatial weight matrices (contiguity-based, k-nearest neighbor and distance-based spatial weight matrices), using a dataset of income per capita growth for 273 European regions.
