Application of novel extractants for actinide(III)/ lanthanide(III) separation in hollow-fibre modules

Separation tests using hollow-fibre modules were performed for the difficult selective extraction of trivalent actinides over fission lanthanides from acidic media. This article shows that with 2,6-di(5,6-dipropyl-1,2,4-triazin-3-yl)pyridine as the extractant, up to 94% americium could be extracted from 1.0 kmol/m³ HNO₃, with minimal lanthanide co-extraction. Using a synergistic mixture of bis(chlorophenyl)dithiophosphinic acid and tri-n-octyl phosphine oxide, tests were performed on extraction, lanthanide scrubbing and stripping. In the extraction test, up to 99.99% americium could be extracted from 0.5 kmol/m³ HNO₃, with approximately one third of the lanthanides being co-extracted. Mass transfer calculations using a consistent set of input data showed good agreement with the experiments.     

Gasification of Biogenic Solid Fuels

As a result of shrinking fossil fuels, biomass as a regenerative energy source gains importance. To realize biomass projects it is essential to investigate in convenient thermal procedures. On this evidence an analysis and evaluation of diverse gasification technologies with different boundary conditions and diverse biomasses are indispensable. Form and kind of the biomass as well as the type of the gasification plant cause different compositions of the product gas. The gasifiers show advantages and disadvantages concerning the biomass and the produced gas quality, depending on reactor type, kind of heat supply, gasification medium, and the pressure ratio in the reactor. As the ideal gasifier for different biomass is presently not available, it will be shown, which biomass is suitable for fixed bed or fluidized bed gasifiers.     

Minimum spanning trees made easier via multi-objective optimization

Many real-world problems are multi-objective optimization problems and evolutionary algorithms are quite successful on such problems. Since the task is to compute or approximate the Pareto front, multi-objective optimization problems are considered as more difficult than single-objective problems. One should not forget that the fitness vector with respect to more than one objective contains more information that in principle can direct the search of evolutionary algorithms. Therefore, it is possible that a single-objective problem can be solved more efficiently via a generalized multi-objective model of the problem. That this is indeed the case is proved by investigating the computation of minimum spanning trees.This work was supported by the Deutsche Forschungsgemeinschaft (DFG) as part of the Collaborative Research Center Computational Intelligence (SFB 531) and by the German-Israeli Foundation (GIF) in the project Robustness Aspects of Algorithms.     

Airborne scatterometers: investigating ocean backscatter under low and high-wind conditions

Attempting to understand and predict weather on a local and global basis has challenged both the scientific and engineering communities. One key parameter in understanding the weather is the ocean surface wind vector because of its role in the energy exchange at the air-sea surface. scatterometers, radars that measure the reflectivity of a target offer a tool with which to remotely monitor these winds from tower-, aircraft-, and satellite-based platforms. This paper introduces three current airborne scatterometer systems, and presents data collected by these instruments under low-, moderate-, and high-wind conditions. The paper focuses on airborne scatterometers because of their ability to resolve submesoscale variations in wind fields. Discrepancies between existing theory and the observations are noted and the concerns in measuring low-wind speeds discussed. Finally, the application of using this technology for estimating the surface-wind vector during a hurricane is demonstrated     

Noninvasive assessment of the direct action of oral nifedipine and nicardipine on left ventricular contractile state in patients with systemic hypertension: importance of reflex sympathetic responses

BACKGROUND: Alveolar macrophages from patients with sarcoidosis were analyzed for their ability to secrete tumor necrosis factor-alpha (TNF-alpha), interleukin-1-beta (IL-1-beta), and interleukin-6 (IL-6). RESULTS: Constitutive release of all three monokines in these patients was concomitantly increased in the active state of disease in comparison with inactive sarcoidosis or healthy control subjects. Alveolar macrophages from patients with inactive sarcoidosis compared with cells from healthy subjects showed increased spontaneous secretion of TNF-alpha and IL-6 only, whereas the constitutive release of IL-1-beta was similar as in healthy volunteers. In vitro stimulation of alveolar macrophages from healthy control subjects with lipopolysaccharide or pokeweed mitogen led to a time- and dose-dependent enhanced secretion of TNF-alpha, IL-1-beta, and IL-6. In a similar manner, with corresponding cells from patients with sarcoidosis the secretion of all three cytokines could be further increased by stimulation with lipopolysaccharide or pokeweed mitogen. CONCLUSIONS: The data presented indicate that an increased release of TNF-alpha, IL-1-beta, and IL-6 correlates to disease activity and may play a critical part in the pathogenesis of sarcoidosis.     

Radiosity with Well Distributed Ray Sets

In this paper we present a new radiosity algorithm, based on the notion of a well distributed ray set (WDRS). A WDRS is a set of rays, connecting mutually visible points and patches, that forms an approximate representation of the radiosity operator and the radiosity distribution. We propose an algorithm that constructs an optimal WDRS for a given accuracy and mesh. The construction is based on discrete importance sampling as in previously proposed stochastic radiosity algorithms, and on quasi Monte Carlo sampling. Quasi Monte Carlo sampling leads to faster convergence rates and the fact that the sampling is deterministic makes it possible to represent the well distributed ray set very efficiently in computer memory. Like previously proposed stochastic radiosity algorithms, the new algorithm is well suited for computing the radiance distribution in very complex diffuse scenes, when it is not feasible to explicitly compute and store form factors as in classical radiosity algorithms. Experiments show that the new algorithm is often more efficient than previously proposed Monte Carlo radiosity algorithms by half an order of magnitude and more.