Shortest Reconfiguration of Colorings Under Kempe Changes

International audienc

Reconfiguration of Minimum Steiner Trees via Vertex Exchanges

In this paper, we study the problem of deciding if there is a transformation between two given minimum Steiner trees of an unweighted graph such that each transformation step respects a prescribed reconfiguration rule and results in another minimum Steiner tree of the graph. We consider two reconfiguration rules, both of which exchange a single vertex at a time, and generalize the known reconfiguration problem for shortest paths in an unweighted graph. This generalization implies that our problems under both reconfiguration rules are PSPACE-complete for bipartite graphs. We thus study the problems with respect to graph classes, and give some boundaries between the polynomial-time solvable and PSPACE-complete cases

Health Information Discrepancies Between Internet Media and Scientific Papers Reporting on Omega-3 Supplement Research: Comparative Analysis

BACKGROUND: Dietary supplements are the most used complementary and alternative health modality in the United States, and omega-3 supplements continue to be the most popularly used nonvitamin or nonmineral supplements by adults. Users of dietary supplements report that they obtain health guidance from internet media resources, but there is question as to whether or not these resources provide the necessary evidence to guide health decisions. Current evidence suggests that there is a mistranslation occurring somewhere between researchers and the media. OBJECTIVE: The aim of this study was to conduct a comparative cross-sectional analysis to identify areas of discordance created when science is translated from the laboratory to Web-based news media. METHODS: A Google news search provided our convenience sample of 40 omega-3 supplement-based media reports stratified by the years 2009 to 2012. Media reports (n=17) were compared with the corresponding scientific papers for content. Report and scientific paper content were extracted using commonly accepted reporting guideline domains, and domains were then compared for detecting underlying omissions or mistranslations in reporting. Mean scores for all of the scientific papers and media reports were assessed for each domain. RESULTS: Scientific papers (n=14) generally maintained a mean close to complete for each reporting domain. The only domain where there was not a significant difference between media and scientific reporting match was within the objectives domain (chi(2)1= 0.8, P=.36). Media reports (n=17) more frequently reported potential caveats and warnings for consumers with a mean domain for caveat reporting of 0.88, with possible scores falling between 0 and 1. CONCLUSIONS: There are inherent differences in the intended audience, structure, and goals in scientific and media communications. These differences should be explored further, and consumers should be made aware of them. Additional considerations for balanced reporting and reader accessibility are also necessary to take into account and are explored further in this analysis

Reconfiguration of Spanning Trees with Degree Constraint or Diameter Constraint

We investigate the complexity of finding a transformation from a given spanning tree in a graph to another given spanning tree in the same graph via a sequence of edge flips. The exchange property of the matroid bases immediately yields that such a transformation always exists if we have no constraints on spanning trees. In this paper, we wish to find a transformation which passes through only spanning trees satisfying some constraint. Our focus is bounding either the maximum degree or the diameter of spanning trees, and we give the following results. The problem with a lower bound on maximum degree is solvable in polynomial time, while the problem with an upper bound on maximum degree is PSPACE-complete. The problem with a lower bound on diameter is NP-hard, while the problem with an upper bound on diameter is solvable in polynomial time

Reconfiguration of Spanning Trees with Many or Few Leaves

Let G be a graph and T?,T? be two spanning trees of G. We say that T? can be transformed into T? via an edge flip if there exist two edges e ? T? and f in T? such that T? = (T??e) ? f. Since spanning trees form a matroid, one can indeed transform a spanning tree into any other via a sequence of edge flips, as observed in [Takehiro Ito et al., 2011]. We investigate the problem of determining, given two spanning trees T?,T? with an additional property ?, if there exists an edge flip transformation from T? to T? keeping property ? all along. First we show that determining if there exists a transformation from T? to T? such that all the trees of the sequence have at most k (for any fixed k ? 3) leaves is PSPACE-complete. We then prove that determining if there exists a transformation from T? to T? such that all the trees of the sequence have at least k leaves (where k is part of the input) is PSPACE-complete even restricted to split, bipartite or planar graphs. We complete this result by showing that the problem becomes polynomial for cographs, interval graphs and when k = n-2

〈研究ノート〉台湾非婚女性とその親との互酬関係への視点

departmental bulletin pape

Estimating and Visualizing Drivers’ Emotions Using the Internet of Digital Reality

Recently, the development of self-driving technology has progressed rapidly. However, self-driving cars have not yet become widespread. Thus, with an aging population, accidents such as road rage and acceleration and brake accidents are likely to continue. Stress is one key reason for such dangerous driving. Thus, technologies must be developed to provide mental support to drivers as required. In this study, we considered estimating driver emotions as a first step along these lines. To this end, we developed a technology to estimate emotions by collecting data on biological signals such as brain waves, heart rate, body movement, and data on a driver's operating status while they are driving. In addition, we introduce a Positive and Negative Affect Schedule (PANAS) to express the psychological states experienced by drivers. We further present the results of an analysis of data on a driver's emotions from PANAS and data obtained from electroencephalogram (EEG) readings and other biological signals from a car. In addition, the relationship between this experimental environment and the Internet of Digital Reality (IoD) is described

A Combination of Multilayer Perceptron, Radial Basis Function Artificial Neural Networks and Machine Learning Image Segmentation for the Dimension Reduction and the Prognosis Assessment of Diffuse Large B-Cell Lymphoma

The prognosis of diffuse large B-cell lymphoma (DLBCL) is heterogeneous. Therefore, we aimed to highlight predictive biomarkers. First, artificial intelligence was applied into a discovery series of gene expression of 414 patients (GSE10846). A dimension reduction algorithm aimed to correlate with the overall survival and other clinicopathological variables; and included a combination of Multilayer Perceptron (MLP) and Radial Basis Function (RBF) artificial neural networks, gene-set enrichment analysis (GSEA), Cox regression and other machine learning and predictive analytics modeling [C5.0 algorithm, logistic regression, Bayesian Network, discriminant analysis, random trees, tree-AS, Chi-squared Automatic Interaction Detection CHAID tree, Quest, classification and regression (C&R) tree and neural net)]. From an initial 54,613 gene-probes, a set of 488 genes and a final set of 16 genes were defined. Secondly, two identified markers of the immune checkpoint, PD-L1 (CD274) and IKAROS (IKZF4), were validated in an independent series from Tokai University, and the immunohistochemical expression was quantified, using a machine-learning-based Weka segmentation. High PD-L1 associated with poor overall and progression-free survival, non-GCB phenotype, Epstein–Barr virus infection (EBER+), high RGS1 expression and several clinicopathological variables, such as high IPI and absence of clinical response. Conversely, high expression of IKAROS was associated with a good overall and progression-free survival, GCB phenotype and a positive clinical response to treatment. Finally, the set of 16 genes (PAF1, USP28, SORT1, MAP7D3, FITM2, CENPO, PRCC, ALDH6A1, CSNK2A1, TOR1AIP1, NUP98, UBE2H, UBXN7, SLC44A2, NR2C2AP and LETM1), in combination with PD-L1, IKAROS, BCL2, MYC, CD163 and TNFAIP8, predicted the survival outcome of DLBCL with an overall accuracy of 82.1%. In conclusion, building predictive models of DLBCL is a feasible analytical strategy