A polynomial factorization approach to the discrete time GI/G/1/(N) queue size distribution

The queue of a single server is considered with independent and identically distributed interarrivai and service times and an infinite (GI/G/1) or finite (GI/G/1/N) waiting room. The queue discipline is non-preemptive and independent of the service times.

A discrete time version of the system is analyzed, using a two-component state model at the arrival and departure instants of customers. The equilibrium equations are solved by a polynomial factorization method. The steady state distribution of the queue size is then represented as a linear combination of geometrical series, whose parameters are evaluated by closed formulae depending on the roots of a characteristic polynomial.

Considering modified boundary constraints, systems with finite waiting room or with an exceptional first service in each busy period are included.     

Some Notes on the Formal Properties of Bidirectional Optimality Theory

In this paper, we discuss some formal properties of the model ofbidirectional Optimality Theory that was developed inBlutner (2000). We investigate the conditions under whichbidirectional optimization is a well-defined notion, and we give aconceptually simpler reformulation of Blutner's definition. In thesecond part of the paper, we show that bidirectional optimization can bemodeled by means of finite state techniques. There we rely heavily onthe related work of Frank and Satta (1998) about unidirectionaloptimization.     

Granulocyte colony-stimulating factor worsens the outcome of experimental Klebsiella pneumoniae pneumonia through direct interaction with the bacteria

Besides its well-established effects on granulocytopoiesis, granulocyte colony-stimulating factor (G-CSF) has been shown to have direct effects on the recruitment and bactericidal ability of neutrophils, resulting in improved survival of experimentally infected animals. We studied the effect of G-CSF on the course of experimental pneumonia induced by Klebsiella pneumoniae, an important gram-negative bacillary pulmonary pathogen. Using a highly reproducible murine model, we here show the paradoxical finding that mortality from infection was significantly increased when animals received G-CSF before induction of pneumonia. Administration of G-CSF promoted replication of bacteria in the liver and spleen, thus indicating an impairment rather than an enhancement of antibacterial mechanisms. By contrast, a monoclonal antibody against Klebsiella K2 capsule significantly reduced bacterial multiplication in the lung, liver, and spleen, and abrogated the increased mortality caused by G-CSF. In vitro studies showed a direct effect of G-CSF on K pneumoniae resulting in increased capsular polysaccharide (CPS) production. When bacteria were coincubated with therapeutically achievable concentrations of G-CSF, phagocytic uptake and killing by neutrophils was impaired. Western blot analysis showed three binding sites of G-CSF to K pneumoniae. Binding of 125I-G-CSF to K pneumoniae was displaced by an excess of unlabeled G-CSF, whereas an unrelated cytokine, interleukin-1alpha, did not compete with G-CSF binding to the bacteria. Thus, in this model, the direct effect of G-CSF on a bacterial virulence factor, CPS production, outweighed any beneficial effect of G-CSF on recruitment and stimulation of leukocytes.     

Graffiti: graph-based classification in heterogeneous networks

We address the problem of multi-label classification in heterogeneous graphs, where nodes belong to different types and different types have different sets of classification labels. We present a novel approach that aims to classify nodes based on their neighborhoods. We model the mutual influence of nodes as a random walk in which the random surfer aims at distributing class labels to nodes while walking through the graph. When viewing class labels as “colors”, the random surfer is essentially spraying different node types with different color palettes; hence the name Graffiti of our method. In contrast to previous work on topic-based random surfer models, our approach captures and exploits the mutual influence of nodes of the same type based on their connections to nodes of other types. We show important properties of our algorithm such as convergence and scalability. We also confirm the practical viability of Graffiti by an experimental study on subsets of the popular social networks Flickr and LibraryThing. We demonstrate the superiority of our approach by comparing it to three other state-of-the-art techniques for graph-based classification.     

Mikrostrukturuntersuchungen an porösen Feststoffen durch Physisorptionsmessungen

Studies of the microstructure of porous solids by physisorption measurements . The principal experimental methods for studying the microstructure of porous solids are based on physisorption measurements. The resulting sorption isotherms can yield data such as surface area and pore radius distribution, which are of great importance for development and characterization of porous catalysts. After a brief presentation of available measuring equipment, the main concern of this survey is the evaluation of sorption isotherms. In particular, methods for determining the micropore contribution to the total pore volume and the pore radius distribution in the micropore range are examined critically with regard to their reliability.