A THERMODYNAMIC MIXED-SOLID ASPHALTENE PRECIPITATION MODEL

A simple model for the prediction of asphaltene precipitation is proposed. The model is based on an equation of state and uses standard thermodynamics, thus assuming that the precipitation phenomenon is a reversible process. The solid phase is treated as an ideal multicomponent mixture. An activity coefficient model based on the athermal Flory-Huggins expression was included to account for solid phase non-ideality, but was found to have little effect on the results. Only a fraction of each of the heaviest components are considered potentially solid forming. This approach is based on the assumption, that out of the total PNA composition of a crude, the asphaltenes and resins are mainly aromatic-naphtenic in their nature. The predictions shows the correct qualitative behavior with respect to temperature and pressure, but due to lack of data the model was not evaluated quantitatively with respect to these effects     

A new method of characterization for stratified thermal energy stores

A new method for characterization of stratified thermal energy stores (TES) that integrates both the first law and the second law concerns is presented here. The first law concern is incorporated into a quantity called energy response factor and the second law concern into an entropy generation ratio. A product of these two quantities is at the heart of the TES efficiency definitions. This approach removes the overemphasis of the existing methods either on the first or the second law of thermodynamics which often biases the characterization results. The information about the evolution of the temperature field of the system in time is the prerequisite of the new method. It may be obtained from experiments or from suitable numerical simulations. The current method can be easily integrated into computational fluid dynamic (CFD) simulations and thus facilitate CFD-based design analysis. As an example of such CFD-integrated analysis, a large-scale hot water seasonal heat store is numerically studied to identify the effects of aspect ratio, containment shape, internal structures, and containment size on their efficiency. The results suggest the effectiveness of the new method in deriving useful design insights.     

Cytomechanics of axonal development

Mechanical tension is a robust regulator of axonal development of cultured neurons. We review work from our laboratory, using calibrated glass needles to measure or apply tension to chick sensory neurons, chick forebrain neurons, and rat PC12 cells. We survey direct evidence for two different regimes of tension effects on neurons, a fluid-like growth regime, and a nongrowth, elastic regime. Above a minimum tension threshold, we observe growth effects of tension regulating four phases of axonal development: 1. Initiation of process outgrowth from the cell body; 2. Growth cone-mediated elongation of the axon; 3. Elongation of the axon after synaptogenesis, which normally accommodates the skeletal growth of vertebrates; and 4. Axonal elimination by retraction. Significantly, the quantitative relationship between the force and the growth response is surprisingly similar to the simple relationship characteristic of Newtonian fluid mechanical elements: elongation rate is directly proportional to tension (above the threshold), and this robust linear relationship extends from physiological growth rates to far-above-physiological rates. Thus, tension apparently integrates the complex biochemistry of axonal elongation, including cytoskeletal and membrane dynamics, to produce a simple "force input/growth output" relationship. In addition to this fluid-like growth response, peripheral neurons show elastic behaviors at low tensions (below the threshold tension for growth), as do most cell types. Thus, neurites could exert small static forces without diminution for long periods. In addition, axons of peripheral neurons can actively generate modest tensions, presumably similar to muscle contraction, at tensions near zero. The elastic and force-generating capability of neural axons has recently been proposed to play a major role in the morphogenesis of the brain.     

Osmotic dilution stimulates axonal outgrowth by making axons more sensitive to tension

Mechanical tension is a potent stimulator of axonal growth rate, which is also stimulated by osmotic dilution. We wished to determine the relationship, if any, between osmotic stimulation and tensile regulation of axonal growth. We used calibrated glass needles to apply constant force to elongate axons of cultured chick sensory neurons. We find that a neurite being pulled at a constant force will grow 50-300% faster following a 50% dilution of inorganic ions in the culture medium. That is, osmotic dilution appears to cause axons to increase their sensitivity to applied tensions. Experimental interventions suggest that this effect is not mediated by dilution of extracellular calcium, or to osmotic stimulation of adenylate cyclase, or to osmotic stimulation of mechanosensitive ion channels. Rather, experiments measuring the static tension normally borne by neurites suggest a direct mechanical effect on the cytoskeletal proteins of the neurite shaft. Our results are consistent with a formal thermodynamic model for axonal growth in which removing a compressive load on axonal microtubules promotes their assembly, thus promoting axonal elongation.     

Interactive survival analysis with the OCDM system: From development to application

Medical data mining is currently actively pursued in computer science and statistical research but not in medical practice. The reasons therefore lie in the difficulties of handling and statistically analyzing medical data. We have developed a system that allows practitioners in the field to interactively analyze their data without assistance of statisticians or data mining experts. In the course of this paper we will introduce data mining of medical data and show how this can be achieved for survival data. We will demonstrate how to solve common problems of interactive survival analysis by presenting the Online Clinical Data Mining (OCDM) system. Thereby the main focus is on similarity based queries, a new method to select similar cases based on their covariables and the influence of these on their survival.     

Online Social Networks – Ein sozialer und technischer überblick

Online Social Networks wie Xing.com oder Facebook.com geh?ren zu den am st?rksten wachsenden Diensten im Internet. Im Jahr 2008 nutzten gesch?tzte 580 Mio. Menschen weltweit diese Angebote. Entsprechend schnell haben sich Online Social Networks innerhalb weniger Jahre von einem Nischenph?nomen zu einem weltweiten Medium der IT-gestützten Kommunikation entwickelt. Insbesondere aufgrund stark wachsender Mitgliederzahlen entfalten Online Social Networks eine erhebliche gesellschaftliche und wirtschaftliche Bedeutung. Vor diesem Hintergrund ist es Ziel dieses Beitrags, Begriff und Eigenschaften, Entstehung und Entwicklung sowie Nutzenpotenziale und Herausforderungen von Online Social Networks n?her zu untersuchen.     

Efficient Vector Quantization Using the WTA-Rule with Activity Equalization

We propose a new algorithm for vector quantization, the Activity Equalization Vector quantization (AEV). It is based on the winner takes all rule with an additional supervision of the average node activities over a training interval and a subsequent re-positioning of those nodes with low average activities. The re-positioning is aimed to both an exploration of the data space and a better approximation of already discovered data clusters by an equalization of the node activities. We introduce a learning scheme for AEV which requires as previous knowledge about the data only their bounding box. Using an example of Martinetz et al. [1], AEV is compared with the Neural Gas, Frequency Sensitive Competitive Learning (FSCL) and other standard algorithms. It turns out to converge much faster and requires less computational effort.