Approximation Algorithms for the Capacitated Domination Problem

We consider the {\em Capacitated Domination} problem, which models a service-requirement assignment scenario and is also a generalization of the well-known {\em Dominating Set} problem. In this problem, given a graph with three parameters defined on each vertex, namely cost, capacity, and demand, we want to find an assignment of demands to vertices of least cost such that the demand of each vertex is satisfied subject to the capacity constraint of each vertex providing the service. In terms of polynomial time approximations, we present logarithmic approximation algorithms with respect to different demand assignment models for this problem on general graphs, which also establishes the corresponding approximation results to the well-known approximations of the traditional {\em Dominating Set} problem. Together with our previous work, this closes the problem of generally approximating the optimal solution. On the other hand, from the perspective of parameterization, we prove that this problem is {\it W[1]}-hard when parameterized by a structure of the graph called treewidth. Based on this hardness result, we present exact fixed-parameter tractable algorithms when parameterized by treewidth and maximum capacity of the vertices. This algorithm is further extended to obtain pseudo-polynomial time approximation schemes for planar graphs

Characterization, identification, and cloning of the S-layer protein from Cytophaga sp

We characterized, identified, and cloned a major protein which comprised 16% of the total proteins from Cytophaga sp. cell lysate. After French pressing, the fraction of cell envelope was treated with 0.2% Triton X-100 to remove cell membranes. Subsequent SDS-PAGE analysis of the Triton X-100-insoluble cell wall revealed a protein of 120 kDa with a pI of 5.4, which was identified by gold immunostaining as the surface (S)-layer protein of this soil bacterium. The nucleotide sequence of the cloned S-layer protein gene (slp) encoding this protein consisted of 3144 nucleotides with an ORF for 1047 amino acids, which included a typical 32-amino acid leader peptide sequence. Amino acid sequence alignment revealed 29-48% similarity between this protein and the S-layer proteins from other prokaryotic organisms. The 120-kDa protein from the Cytophaga sp. cell lysate has been characterized as a member of the S-layer proteins, and the slp gene was cloned and expressed in Escherichia coli. E. coli harboring the plasmid containing the 600- or 800-bp DNA fragment upstream of the initiation codon of the slp gene, in the presence of the reporter gene rsda (raw starch digesting amylase), showed amylase activity in starch containing plate. The putative promoter region of slp located 600 bp upstream of the initiation codon might be used for foreign gene expression

The infection of primary avian tracheal epithelial cells with infectious bronchitis virus

Here we introduce a culture system for the isolation, passaging and amplification of avian tracheal epithelial (ATE) cells. The ATE medium, which contains chicken embryo extract and fetal bovine serum, supports the growth of ciliated cells, goblet cells and basal cells from chicken tracheas on fibronectin- or matrigel-coated dishes. Non-epithelial cells make up less than 10% of the total population. We further show that ATE cells support the replication and spread of infectious bronchitis virus (IBV). Interestingly, immunocytostaining revealed that basal cells are resistant to IBV infection. We also demonstrate that glycosaminoglycan had no effect on infection of the cells by IBV. Taken together, these findings suggest that primary ATE cells provide a novel cell culture system for the amplification of IBV and the in vitro characterization of viral cytopathogenesis

User-Based Solutions for Increasing Level of Service in Bike-Sharing Transportation Systems

International audienceBike-sharing transportation systems have been well studied from a top-down viewpoint, either for an optimal conception of the system , or for a better statistical understanding of their working mechanisms in the aim of the optimization of the management strategy. Yet bottom-up approaches that could include behavior of users have not been well studied so far. We propose an agent-based model for the short time evolution of a bike-sharing system, with a focus on two strategical parameters that are the role of the quantity of information users have on the all system and the propensity of user to walk after having dropped their bike. We implement the model in a general way so it is applicable to every system as soon as data are available in a certain format. The model of simulation is parametrized and calibrated on processed real time-series of bike movements for the system of Paris. After showing the robustness of the simulations by validating internally and externally the model, we are able to test different user-based strategies for an increase of the level of service. In particular, we show that an increase of user information can have significant impact on the homogeneity of repartition of bikes in docking stations, and, what is important for a future implementation of the strategy, that an action on only 30% of regular users is enough to obtain most of the possible amelioration

Kernel Spectral Clustering and applications

In this chapter we review the main literature related to kernel spectral clustering (KSC), an approach to clustering cast within a kernel-based optimization setting. KSC represents a least-squares support vector machine based formulation of spectral clustering described by a weighted kernel PCA objective. Just as in the classifier case, the binary clustering model is expressed by a hyperplane in a high dimensional space induced by a kernel. In addition, the multi-way clustering can be obtained by combining a set of binary decision functions via an Error Correcting Output Codes (ECOC) encoding scheme. Because of its model-based nature, the KSC method encompasses three main steps: training, validation, testing. In the validation stage model selection is performed to obtain tuning parameters, like the number of clusters present in the data. This is a major advantage compared to classical spectral clustering where the determination of the clustering parameters is unclear and relies on heuristics. Once a KSC model is trained on a small subset of the entire data, it is able to generalize well to unseen test points. Beyond the basic formulation, sparse KSC algorithms based on the Incomplete Cholesky Decomposition (ICD) and $L_0$, $L_1, L_0 + L_1$, Group Lasso regularization are reviewed. In that respect, we show how it is possible to handle large scale data. Also, two possible ways to perform hierarchical clustering and a soft clustering method are presented. Finally, real-world applications such as image segmentation, power load time-series clustering, document clustering and big data learning are considered.Comment: chapter contribution to the book "Unsupervised Learning Algorithms

Branch and bound based coordinate search filter algorithm for nonsmooth nonconvex mixed-integer nonlinear programming problems

Publicado em "Computational science and its applications – ICCSA 2014...", ISBN 978-3-319-09128-0. Series "Lecture notes in computer science", ISSN 0302-9743, vol. 8580.A mixed-integer nonlinear programming problem (MINLP) is a problem with continuous and integer variables and at least, one nonlinear function. This kind of problem appears in a wide range of real applications and is very difficult to solve. The difficulties are due to the nonlinearities of the functions in the problem and the integrality restrictions on some variables. When they are nonconvex then they are the most difficult to solve above all. We present a methodology to solve nonsmooth nonconvex MINLP problems based on a branch and bound paradigm and a stochastic strategy. To solve the relaxed subproblems at each node of the branch and bound tree search, an algorithm based on a multistart strategy with a coordinate search filter methodology is implemented. The produced numerical results show the robustness of the proposed methodology.This work has been supported by FCT (Fundação para a Ciência e aTecnologia) in the scope of the projects: PEst-OE/MAT/UI0013/2014 and PEst-OE/EEI/UI0319/2014

The Earth: Plasma Sources, Losses, and Transport Processes

This paper reviews the state of knowledge concerning the source of magnetospheric plasma at Earth. Source of plasma, its acceleration and transport throughout the system, its consequences on system dynamics, and its loss are all discussed. Both observational and modeling advances since the last time this subject was covered in detail (Hultqvist et al., Magnetospheric Plasma Sources and Losses, 1999) are addressed