Ternary Mixed Magnetic Co/Mn/Ni Dichloride Dihydrate

Ternary mixed magnetic Co1-xMnyNix-yCl2 center dot 2H(2)O has as its components three well studied antiferromagnets. Each is characterized by MCl2MCl2M...chemical and structural chains, with intrachain exchange interactions antiferromagnetic for the Mn component but ferromagnetic for the other two components. Competing ferromagnetic and antiferromagnetic intrachain exchange interactions occur in two different pairwise combinations. Reported here is the magnetic behavior of an equimolar mixture of the three components. One maximum appears in the magnetic susceptibility vs temperature, at 4.85 +/- 0.05 K, a quite interesting result since decidedly lower than the locations of susceptibility maxima in the pure components. A pronounced upturn in the susceptibility below 2.3 K also appears. Magnetization vs field isotherms display increasingly strong convex upward curvature and associated hysteresis with decreasing temperature. All of these characteristics differ markedly from those of the pure components

Community detection based on links and node features in social networks

© Springer International Publishing Switzerland 2015. Community detection is a significant but challenging task in the field of social network analysis. Many effective methods have been proposed to solve this problem. However, most of them are mainly based on the topological structure or node attributes. In this paper, based on SPAEM [1], we propose a joint probabilistic model to detect community which combines node attributes and topological structure. In our model, we create a novel feature-based weighted network, within which each edge weight is represented by the node feature similarity between two nodes at the end of the edge. Then we fuse the original network and the created network with a parameter and employ expectation-maximization algorithm (EM) to identify a community. Experiments on a diverse set of data, collected from Facebook and Twitter, demonstrate that our algorithm has achieved promising results compared with other algorithms

Advanced Multilevel Node Separator Algorithms

A node separator of a graph is a subset S of the nodes such that removing S and its incident edges divides the graph into two disconnected components of about equal size. In this work, we introduce novel algorithms to find small node separators in large graphs. With focus on solution quality, we introduce novel flow-based local search algorithms which are integrated in a multilevel framework. In addition, we transfer techniques successfully used in the graph partitioning field. This includes the usage of edge ratings tailored to our problem to guide the graph coarsening algorithm as well as highly localized local search and iterated multilevel cycles to improve solution quality even further. Experiments indicate that flow-based local search algorithms on its own in a multilevel framework are already highly competitive in terms of separator quality. Adding additional local search algorithms further improves solution quality. Our strongest configuration almost always outperforms competing systems while on average computing 10% and 62% smaller separators than Metis and Scotch, respectively

Review Article p16 INK4A and p14 ARF Gene Promoter Hypermethylation as Prognostic Biomarker in Oral and Oropharyngeal Squamous Cell Carcinoma: A Review

Head and neck squamous cell carcinoma is a heterogeneous group of tumors with each subtype having a distinct histopathological and molecular profile. Most tumors share, to some extent, the same multistep carcinogenic pathways, which include a wide variety of genetic and epigenetic changes. Epigenetic alterations represent all changes in gene expression patterns that do not alter the actual DNA sequence. Recently, it has become clear that silencing of cancer related genes is not exclusively a result of genetic changes such as mutations or deletions, but it can also be regulated on epigenetic level, mostly by means of gene promoter hypermethylation. Results from recent studies have demonstrated that DNA methylation patterns contain tumor-type-specific signatures, which could serve as biomarkers for clinical outcome in the near future. The topic of this review discusses gene promoter hypermethylation in oral and oropharyngeal squamous cell carcinoma (OSCC). The main objective is to analyse the available data on gene promoter hypermethylation of the cell cycle regulatory proteins p16 INK4A and p14 ARF and to investigate their clinical significance as novel biomarkers in OSCC. Hypermethylation of both genes seems to possess predictive properties for several clinicopathological outcomes. We conclude that the methylation status of p16 INK4A is definitely a promising candidate biomarker for predicting clinical outcome of OSCC, especially for recurrence-free survival

iSAM2 : incremental smoothing and mapping using the Bayes tree

Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Sage for personal use, not for redistribution. The definitive version was published in International Journal of Robotics Research 31 (2012): 216-235, doi:10.1177/0278364911430419.We present a novel data structure, the Bayes tree, that provides an algorithmic foundation enabling a better understanding of existing graphical model inference algorithms and their connection to sparse matrix factorization methods. Similar to a clique tree, a Bayes tree encodes a factored probability density, but unlike the clique tree it is directed and maps more naturally to the square root information matrix of the simultaneous localization and mapping (SLAM) problem. In this paper, we highlight three insights provided by our new data structure. First, the Bayes tree provides a better understanding of the matrix factorization in terms of probability densities. Second, we show how the fairly abstract updates to a matrix factorization translate to a simple editing of the Bayes tree and its conditional densities. Third, we apply the Bayes tree to obtain a completely novel algorithm for sparse nonlinear incremental optimization, named iSAM2, which achieves improvements in efficiency through incremental variable re-ordering and fluid relinearization, eliminating the need for periodic batch steps. We analyze various properties of iSAM2 in detail, and show on a range of real and simulated datasets that our algorithm compares favorably with other recent mapping algorithms in both quality and efficiency.M. Kaess, H. Johannsson and J. Leonard were partially supported by ONR grants N00014-06-1-0043 and N00014-10-1-0936. F. Dellaert and R. Roberts were partially supported by NSF, award number 0713162, “RI: Inference in Large-Scale Graphical Models”. V. Ila has been partially supported by the Spanish MICINN under the Programa Nacional de Movilidad de Recursos Humanos de Investigación

Recent Advances in Graph Partitioning

We survey recent trends in practical algorithms for balanced graph partitioning together with applications and future research directions

Rec-DCM-Eigen: Reconstructing a Less Parsimonious but More Accurate Tree in Shorter Time

Maximum parsimony (MP) methods aim to reconstruct the phylogeny of extant species by finding the most parsimonious evolutionary scenario using the species' genome data. MP methods are considered to be accurate, but they are also computationally expensive especially for a large number of species. Several disk-covering methods (DCMs), which decompose the input species to multiple overlapping subgroups (or disks), have been proposed to solve the problem in a divide-and-conquer way

Ensemble approach for generalized network dismantling

Finding a set of nodes in a network, whose removal fragments the network below some target size at minimal cost is called network dismantling problem and it belongs to the NP-hard computational class. In this paper, we explore the (generalized) network dismantling problem by exploring the spectral approximation with the variant of the power-iteration method. In particular, we explore the network dismantling solution landscape by creating the ensemble of possible solutions from different initial conditions and a different number of iterations of the spectral approximation.Comment: 11 Pages, 4 Figures, 4 Table