Effects of extruded or pelleted diet on blood glucose, body weight, feed and water consumption in rats

Extruded diets are claimed to be more digestible, palatable and of a higher hygienic standard compared to pelleted diets. In a comparision of a pelleted and an extruded diet given to Sprague-Dawley rats, we found no difference in weight gain, feed and water consumption or in blood glucose level. In the microbiological analyses, there was no major difference either. When considering choice of diet the physical form seems to be of minor importance. The major factors should be the nutritional value, hygienic level (autoclavable or irradiated vs conventional), reproduciability, availability, confidence in producer and economical values

One model to rule them all: unified classification model for geotagging websites

The paper presents a novel approach to finding regional scopes (geotagging) of websites. It relies on a single binary classification model per region type to perform the multi-label classification and uses a variety of different features that have not been yet used together for machine-learning based regional classification of websites. The evaluation demonstrates the advantage of our one model per region type method versus the traditional one model per region approach

Landauer Conductance of Luttinger Liquids with Leads

We show that the dc conductance of a quantum wire containing a Luttinger liquid and attached to non-interacting leads is given by $e^2/h$ per spin orientation, regardless of the interactions in the wire. This explains the recent observations of the absence of conductance renormalization in long high-mobility $GaAs$ wires by Tarucha, Honda and Saku (Solid State Communications {\bf 94}, 413 (1995)).Comment: 4 two-column pages, RevTeX + 1 uuencoded figure

On the evolution of decoys in plant immune systems

The Guard-Guardee model for plant immunity describes how resistance proteins (guards) in host cells monitor host target proteins (guardees) that are manipulated by pathogen effector proteins. A recently suggested extension of this model includes decoys, which are duplicated copies of guardee proteins, and which have the sole function to attract the effector and, when modified by the effector, trigger the plant immune response. Here we present a proof-of-principle model for the functioning of decoys in plant immunity, quantitatively developing this experimentally-derived concept. Our model links the basic cellular chemistry to the outcomes of pathogen infection and resulting fitness costs for the host. In particular, the model allows identification of conditions under which it is optimal for decoys to act as triggers for the plant immune response, and of conditions under which it is optimal for decoys to act as sinks that bind the pathogen effectors but do not trigger an immune response.Comment: 15 pages, 6 figure

Comparison and validation of community structures in complex networks

The issue of partitioning a network into communities has attracted a great deal of attention recently. Most authors seem to equate this issue with the one of finding the maximum value of the modularity, as defined by Newman. Since the problem formulated this way is NP-hard, most effort has gone into the construction of search algorithms, and less to the question of other measures of community structures, similarities between various partitionings and the validation with respect to external information. Here we concentrate on a class of computer generated networks and on three well-studied real networks which constitute a bench-mark for network studies; the karate club, the US college football teams and a gene network of yeast. We utilize some standard ways of clustering data (originally not designed for finding community structures in networks) and show that these classical methods sometimes outperform the newer ones. We discuss various measures of the strength of the modular structure, and show by examples features and drawbacks. Further, we compare different partitions by applying some graph-theoretic concepts of distance, which indicate that one of the quality measures of the degree of modularity corresponds quite well with the distance from the true partition. Finally, we introduce a way to validate the partitionings with respect to external data when the nodes are classified but the network structure is unknown. This is here possible since we know everything of the computer generated networks, as well as the historical answer to how the karate club and the football teams are partitioned in reality. The partitioning of the gene network is validated by use of the Gene Ontology database, where we show that a community in general corresponds to a biological process.Comment: To appear in Physica A; 25 page

Optimizing and controlling functions of complex networks by manipulating rich-club connections

Traditionally, there is no evidence suggesting that there are strong ties between the rich-club property and the function of complex networks. In this study, we find that whether a very small portion of rich nodes connected to each other or not can strongly affect the frequency of occurrence of basic building blocks (motif) within networks, and therefore the function, of a heterogeneous network. Conversely whether a homogeneous network has a rich-club property or not generally has no significant effect on its structure and function. These findings open the possibility to optimize and control the function of complex networks by manipulating rich-club connections. Furthermore, based on the subgraph ratio profile, we develop a more rigorous approach to judge whether a network has a rich-club or not. The new method does not calculate how many links there are among rich nodes but depends on how the links among rich nodes can affect the overall structure as well as function of a given network. These results can also help us to understand the evolution of dynamical networks and design new models for characterizing real-world networks.Comment: 6 pages, 3 figure