Identifying influential nodes for smart enterprises using community structure with Integrated Feature Ranking

Finding influential nodes reshuffles the very notion of linear paths in business processes and replaces it with networks of business value within a smart enterprise system. There are many existing algorithms for identifying influential nodes with certain limitations for applying in large-scale networks. In this paper, we propose a community structure with an Integrated Features Ranking (CIFR) algorithm to find influential nodes in the network. Firstly, we use the community detection algorithm to find communities in the system and then we rank the nodes of network based on three factors, namely- local ranking, gateway ranking, and community ranking, collectively termed as integrated features. Our algorithm intends to select influential nodes, which are both globally and locally optimal, leading to overall high information propagation. We perform the experimental results on total eight networks using various evaluation parameters. The obtained results validate superior performance against contemporary algorithms adding value to smart enterprises

Algorithmic aspects of disjunctive domination in graphs

For a graph $G=(V,E)$, a set $D\subseteq V$ is called a \emph{disjunctive dominating set} of $G$ if for every vertex $v\in V\setminus D$, $v$ is either adjacent to a vertex of $D$ or has at least two vertices in $D$ at distance $2$ from it. The cardinality of a minimum disjunctive dominating set of $G$ is called the \emph{disjunctive domination number} of graph $G$, and is denoted by $\gamma_{2}^{d}(G)$. The \textsc{Minimum Disjunctive Domination Problem} (MDDP) is to find a disjunctive dominating set of cardinality $\gamma_{2}^{d}(G)$. Given a positive integer $k$ and a graph $G$, the \textsc{Disjunctive Domination Decision Problem} (DDDP) is to decide whether $G$ has a disjunctive dominating set of cardinality at most $k$. In this article, we first propose a linear time algorithm for MDDP in proper interval graphs. Next we tighten the NP-completeness of DDDP by showing that it remains NP-complete even in chordal graphs. We also propose a $(\ln(\Delta^{2}+\Delta+2)+1)$-approximation algorithm for MDDP in general graphs and prove that MDDP can not be approximated within $(1-\epsilon) \ln(|V|)$ for any $\epsilon>0$ unless NP $\subseteq$ DTIME$(|V|^{O(\log \log |V|)})$. Finally, we show that MDDP is APX-complete for bipartite graphs with maximum degree $3$

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Heat Kernel Expansion and Extremal Kerr-Newmann Black Hole Entropy in Einstein-Maxwell Theory

We compute the second Seely-DeWitt coefficient of the kinetic operator of the metric and gauge fields in Einstein-Maxwell theory in an arbitrary background field configuration. We then use this result to compute the logarithmic correction to the entropy of an extremal Kerr-Newmann black hole.Comment: 12 page

Lead-free piezoelectric K0.5Bi0.5TiO3–Bi(Mg0.5Ti0.5)O3 ceramics with depolarisation temperatures up to ~220 C

The properties of K0.5Bi0.5TiO3-rich ceramic solid solutions in the system (1 - x)K0.5Bi0.5TiO3– xBi(Mg0.5Ti0.5)O3 are reported. The highest values of piezoelectric charge coefficient, d33, and field-induced strains are found in compositions located close to a compositional boundary between single-phase tetragonal and mixed tetragonal ? cubic perovskite phases. Maximum d33 values were *150 pC/N for x = 0.03, with positive strains of *0.25 %; the x = 0.04 composition had a d33 * 133 pC/N and strain of 0.35 % (bipolar electric field, 50 kV/ cm, 1 Hz). Depolarisation temperature Td is an important selection criterion for any lead-free piezoelectric for actuator or sensor applications. A Td of *220 C for x = 0.03 is *100 C higher than for the widely reported Na0.5Bi0.5TiO3–BaTiO3 system, yet d33 values and strains are similar, suggesting the new material is worthy of further attention as a lead-free piezoceramic for elevated temperature applications

Model based dynamics analysis in live cell microtubule images

Background: The dynamic growing and shortening behaviors of microtubules are central to the fundamental roles played by microtubules in essentially all eukaryotic cells. Traditionally, microtubule behavior is quantified by manually tracking individual microtubules in time-lapse images under various experimental conditions. Manual analysis is laborious, approximate, and often offers limited analytical capability in extracting potentially valuable information from the data. Results: In this work, we present computer vision and machine-learning based methods for extracting novel dynamics information from time-lapse images. Using actual microtubule data, we estimate statistical models of microtubule behavior that are highly effective in identifying common and distinct characteristics of microtubule dynamic behavior. Conclusion: Computational methods provide powerful analytical capabilities in addition to traditional analysis methods for studying microtubule dynamic behavior. Novel capabilities, such as building and querying microtubule image databases, are introduced to quantify and analyze microtubule dynamic behavior

Lmo4 in the Basolateral Complex of the Amygdala Modulates Fear Learning

Pavlovian fear conditioning is an associative learning paradigm in which mice learn to associate a neutral conditioned stimulus with an aversive unconditioned stimulus. In this study, we demonstrate a novel role for the transcriptional regulator Lmo4 in fear learning. LMO4 is predominantly expressed in pyramidal projection neurons of the basolateral complex of the amygdala (BLC). Mice heterozygous for a genetrap insertion in the Lmo4 locus (Lmo4gt/+), which express 50% less Lmo4 than their wild type (WT) counterparts display enhanced freezing to both the context and the cue in which they received the aversive stimulus. Small-hairpin RNA-mediated knockdown of Lmo4 in the BLC, but not the dentate gyrus region of the hippocampus recapitulated this enhanced conditioning phenotype, suggesting an adult- and brain region-specific role for Lmo4 in fear learning. Immunohistochemical analyses revealed an increase in the number of c-Fos positive puncta in the BLC of Lmo4gt/+ mice in comparison to their WT counterparts after fear conditioning. Lastly, we measured anxiety-like behavior in Lmo4gt/+ mice and in mice with BLC-specific downregulation of Lmo4 using the elevated plus maze, open field, and light/dark box tests. Global or BLC-specific knockdown of Lmo4 did not significantly affect anxiety-like behavior. These results suggest a selective role for LMO4 in the BLC in modulating learned but not unlearned fear

Age-Related Changes in the Epithelial and Stromal Compartments of the Mammary Gland in Normocalcemic Mice Lacking the Vitamin D3 Receptor

The vitamin D3 receptor (VDR) serves as a negative growth regulator during mammary gland development via suppression of branching morphogenesis during puberty and modulation of differentiation and apoptosis during pregnancy, lactation and involution. To assess the role of the VDR in the aging mammary gland, we utilized 12, 14, and 16 month old VDR knockout (KO) and wild type (WT) mice for assessment of integrity of the epithelial and stromal compartments, steroid hormone levels and signaling pathways. Our data indicate that VDR ablation is associated with ductal ectasia of the primary mammary ducts, loss of secondary and tertiary ductal branches and atrophy of the mammary fat pad. In association with loss of the white adipose tissue compartment, smooth muscle actin staining is increased in glands from VDR KO mice, suggesting a change in the stromal microenviroment. Activation of caspase-3 and increased Bax expression in mammary tissue of VDR KO mice suggests that enhanced apoptosis may contribute to loss of ductal branching. These morphological changes in the glands of VDR KO mice are associated with ovarian failure and reduced serum 17β-estradiol. VDR KO mice also exhibit progressive loss of adipose tissue stores, hypoleptinemia and increased metabolic rate with age. These developmental studies indicate that, under normocalcemic conditions, loss of VDR signaling is associated with age-related estrogen deficiency, disruption of epithelial ductal branching, abnormal energy expenditure and atrophy of the mammary adipose compartment

The host ubiquitin-dependent segregase VCP/p97 is required for the onset of human cytomegalovirus replication

The human cytomegalovirus major immediate early proteins IE1 and IE2 are critical drivers of virus replication and are considered pivotal in determining the balance between productive and latent infection. IE1 and IE2 are derived from the same primary transcript by alternative splicing and regulation of their expression likely involves a complex interplay between cellular and viral factors. Here we show that knockdown of the host ubiquitin-dependent segregase VCP/p97, results in loss of IE2 expression, subsequent suppression of early and late gene expression and, ultimately, failure in virus replication. RNAseq analysis showed increased levels of IE1 splicing, with a corresponding decrease in IE2 splicing following VCP knockdown. Global analysis of viral transcription showed the expression of a subset of viral genes is not reduced despite the loss of IE2 expression, including UL112/113. Furthermore, Immunofluorescence studies demonstrated that VCP strongly colocalised with the viral replication compartments in the nucleus. Finally, we show that NMS-873, a small molecule inhibitor of VCP, is a potent HCMV antiviral with potential as a novel host targeting therapeutic for HCMV infection

Gene expression profile of peripheral blood lymphocytes from renal cell carcinoma patients treated with IL-2, Interferon-α and dendritic cell vaccine

© The Author(s), 2012. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in PLoS One 7 (2012): e50221, doi:10.1371/journal.pone.0050221.Lymphocytes are a key component of the immune system and their differentiation and function are directly influenced by cancer. We examined peripheral blood lymphocyte (PBL) gene expression as a biomarker of illness and treatment effect using the Affymetrix Human Gene ST1 platform in patients with metastatic renal cell carcinoma (mRCC) who received combined treatment with IL-2, interferon-?-2a and dendritic cell vaccine. We examined gene expression, cytokine levels in patient serum and lymphocyte subsets as determined by flow cytometry (FCM). Pre-treatment PBLs from patients with mRCC exhibit a gene expression profile and serum cytokine profile consistent with inflammation and proliferation not found in healthy donors (HD). PBL gene expression from patients with mRCC showed increased mRNA of genes involved with T-cell and TREG-cell activation pathways, which was also reflected in lymphocyte subset distribution. Overall, PBL gene expression post-treatment (POST) was not significantly different than pre-treatment (PRE). Nevertheless, treatment related changes in gene expression (post-treatment minus pre-treatment) revealed an increased expression of T-cell and B-cell receptor signaling pathways in responding (R) patients compared to non-responding (NR) patients. In addition, we observed down-regulation of TREG-cell pathways post-treatment in R vs. NR patients. While exploratory in nature, this study supports the hypothesis that enhanced inflammatory cytotoxic pathways coupled with blunting of the regulatory pathways is necessary for effective anti-cancer activity associated with immune therapy. This type of analysis can potentially identify additional immune therapeutic targets in patients with mRCC.This work was supported by grants from the National Institutes of Health (RO1 CA5648, R21CA112761, P20RR016437, and P30CA023108)