134 research outputs found
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
Non-Viral Gene Delivery Systems Based on Cholesterol Cationic Lipids: Structure-Activity Relationships
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 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 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
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