Local Guarantees in Graph Cuts and Clustering

Correlation Clustering is an elegant model that captures fundamental graph cut problems such as Min $s-t$ Cut, Multiway Cut, and Multicut, extensively studied in combinatorial optimization. Here, we are given a graph with edges labeled $+$ or $-$ and the goal is to produce a clustering that agrees with the labels as much as possible: $+$ edges within clusters and $-$ edges across clusters. The classical approach towards Correlation Clustering (and other graph cut problems) is to optimize a global objective. We depart from this and study local objectives: minimizing the maximum number of disagreements for edges incident on a single node, and the analogous max min agreements objective. This naturally gives rise to a family of basic min-max graph cut problems. A prototypical representative is Min Max $s-t$ Cut: find an $s-t$ cut minimizing the largest number of cut edges incident on any node. We present the following results: $(1)$ an $O(\sqrt{n})$-approximation for the problem of minimizing the maximum total weight of disagreement edges incident on any node (thus providing the first known approximation for the above family of min-max graph cut problems), $(2)$ a remarkably simple $7$-approximation for minimizing local disagreements in complete graphs (improving upon the previous best known approximation of $48$), and $(3)$ a $1/(2+\varepsilon)$-approximation for maximizing the minimum total weight of agreement edges incident on any node, hence improving upon the $1/(4+\varepsilon)$-approximation that follows from the study of approximate pure Nash equilibria in cut and party affiliation games

Predicting video game players’ fun from physiological and behavioural data : one algorithm does not fit all

Finding a physiological signature of a player’s fun is a goal yet to be achieved in the field of adaptive gaming. The research presented in this paper tackles this issue by gathering physiological, behavioural and self-report data from over 200 participants who played off-the-shelf video games from the Assassin’s Creed series within a minimally invasive laboratory environment. By leveraging machine learning techniques the prediction of the player’s fun from its physiological and behavioural markers becomes a possibility. They provide clues as to which signals are the most relevant in establishing a physiological signature of the fun factor by providing an important score based on the predictive power of each signal. Identifying those markers and their impact will prove crucial in the development of adaptive video games. Adaptive games tailor their gameplay to the affective state of a player in order to deliver the optimal gaming experience. Indeed, an adaptive video game needs a continuous reading of the fun level to be able to respond to these changing fun levels in real time. While the predictive power of the presented classifier remains limited with a gain in the F1 score of 15% against random chance, it brings insight as to which physiological features might be the most informative for further analysis and discuss means by which low accuracy classification could still improve gaming experience

Lipopolysaccharide Diversity Evolving in Helicobacter pylori Communities through Genetic Modifications in Fucosyltransferases

Helicobacter pylori persistently colonizes the gastric mucosa of half the human population. It is one of the most genetically diverse bacterial organisms and subvariants are continuously emerging within an H. pylori population. In this study we characterized a number of single-colony isolates from H. pylori communities in various environmental settings, namely persistent human gastric infection, in vitro bacterial subcultures on agar medium, and experimental in vivo infection in mice. The lipopolysaccharide (LPS) O-antigen chain revealed considerable phenotypic diversity between individual cells in the studied bacterial communities, as demonstrated by size variable O-antigen chains and different levels of Lewis glycosylation. Absence of high-molecular-weight O-antigen chains was notable in a number of experimentally passaged isolates in vitro and in vivo. This phenotype was not evident in bacteria obtained from a human gastric biopsy, where all cells expressed high-molecular-weight O-antigen chains, which thus may be the preferred phenotype for H. pylori colonizing human gastric mucosa. Genotypic variability was monitored in the two genes encoding α1,3-fucosyltransferases, futA and futB, that are involved in Lewis antigen expression. Genetic modifications that could be attributable to recombination events within and between the two genes were commonly detected and created a diversity, which together with phase variation, contributed to divergent LPS expression. Our data suggest that the surrounding environment imposes a selective pressure on H. pylori to express certain LPS phenotypes. Thus, the milieu in a host will select for bacterial variants with particular characteristics that facilitate adaptation and survival in the gastric mucosa of that individual, and will shape the bacterial community structure

Helicobacter pylori's Unconventional Role in Health and Disease

The discovery of a bacterium, Helicobacter pylori, that is resident in the human stomach and causes chronic disease (peptic ulcer and gastric cancer) was radical on many levels. Whereas the mouth and the colon were both known to host a large number of microorganisms, collectively referred to as the microbiome, the stomach was thought to be a virtual Sahara desert for microbes because of its high acidity. We now know that H. pylori is one of many species of bacteria that live in the stomach, although H. pylori seems to dominate this community. H. pylori does not behave as a classical bacterial pathogen: disease is not solely mediated by production of toxins, although certain H. pylori genes, including those that encode exotoxins, increase the risk of disease development. Instead, disease seems to result from a complex interaction between the bacterium, the host, and the environment. Furthermore, H. pylori was the first bacterium observed to behave as a carcinogen. The innate and adaptive immune defenses of the host, combined with factors in the environment of the stomach, apparently drive a continuously high rate of genomic variation in H. pylori. Studies of this genetic diversity in strains isolated from various locations across the globe show that H. pylori has coevolved with humans throughout our history. This long association has given rise not only to disease, but also to possible protective effects, particularly with respect to diseases of the esophagus. Given this complex relationship with human health, eradication of H. pylori in nonsymptomatic individuals may not be the best course of action. The story of H. pylori teaches us to look more deeply at our resident microbiome and the complexity of its interactions, both in this complex population and within our own tissues, to gain a better understanding of health and disease

A review of elliptical and disc galaxy structure, and modern scaling laws

A century ago, in 1911 and 1913, Plummer and then Reynolds introduced their models to describe the radial distribution of stars in `nebulae'. This article reviews the progress since then, providing both an historical perspective and a contemporary review of the stellar structure of bulges, discs and elliptical galaxies. The quantification of galaxy nuclei, such as central mass deficits and excess nuclear light, plus the structure of dark matter halos and cD galaxy envelopes, are discussed. Issues pertaining to spiral galaxies including dust, bulge-to-disc ratios, bulgeless galaxies, bars and the identification of pseudobulges are also reviewed. An array of modern scaling relations involving sizes, luminosities, surface brightnesses and stellar concentrations are presented, many of which are shown to be curved. These 'redshift zero' relations not only quantify the behavior and nature of galaxies in the Universe today, but are the modern benchmark for evolutionary studies of galaxies, whether based on observations, N-body-simulations or semi-analytical modelling. For example, it is shown that some of the recently discovered compact elliptical galaxies at 1.5 < z < 2.5 may be the bulges of modern disc galaxies.Comment: Condensed version (due to Contract) of an invited review article to appear in "Planets, Stars and Stellar Systems"(www.springer.com/astronomy/book/978-90-481-8818-5). 500+ references incl. many somewhat forgotten, pioneer papers. Original submission to Springer: 07-June-201

A Novel System of Cytoskeletal Elements in the Human Pathogen Helicobacter pylori

Pathogenicity of the human pathogen Helicobacter pylori relies upon its capacity to adapt to a hostile environment and to escape from the host response. Therefore, cell shape, motility, and pH homeostasis of these bacteria are specifically adapted to the gastric mucus. We have found that the helical shape of H. pylori depends on coiled coil rich proteins (Ccrp), which form extended filamentous structures in vitro and in vivo, and are differentially required for the maintenance of cell morphology. We have developed an in vivo localization system for this pathogen. Consistent with a cytoskeleton-like structure, Ccrp proteins localized in a regular punctuate and static pattern within H. pylori cells. Ccrp genes show a high degree of sequence variation, which could be the reason for the morphological diversity between H. pylori strains. In contrast to other bacteria, the actin-like MreB protein is dispensable for viability in H. pylori, and does not affect cell shape, but cell length and chromosome segregation. In addition, mreB mutant cells displayed significantly reduced urease activity, and thus compromise a major pathogenicity factor of H. pylori. Our findings reveal that Ccrp proteins, but not MreB, affect cell morphology, while both cytoskeletal components affect the development of pathogenicity factors and/or cell cycle progression

Single Molecule Analysis Research Tool (SMART): An Integrated Approach for Analyzing Single Molecule Data

Single molecule studies have expanded rapidly over the past decade and have the ability to provide an unprecedented level of understanding of biological systems. A common challenge upon introduction of novel, data-rich approaches is the management, processing, and analysis of the complex data sets that are generated. We provide a standardized approach for analyzing these data in the freely available software package SMART: Single Molecule Analysis Research Tool. SMART provides a format for organizing and easily accessing single molecule data, a general hidden Markov modeling algorithm for fitting an array of possible models specified by the user, a standardized data structure and graphical user interfaces to streamline the analysis and visualization of data. This approach guides experimental design, facilitating acquisition of the maximal information from single molecule experiments. SMART also provides a standardized format to allow dissemination of single molecule data and transparency in the analysis of reported data

The SITLESS project: Exercise referral schemes enhanced by self-management strategies to battle sedentary behaviour in older adults: Study protocol for a randomised controlled trial

Abstract Background Older adults are the fastest growing segment of the world‘s population. Recent evidence indicates that excessive sitting time is harmful to health, independent of meeting the recommended moderate to vigorous physical activity (PA) guidelines. The SITLESS project aims to determine whether exercise referral schemes (ERS) can be enhanced by self-management strategies (SMSs) to reduce sedentary behaviour (SB), increase PA and improve health, quality of life and function in the long term, as well as psychosocial outcomes in community-dwelling older European citizens from four countries, within a three-armed pragmatic randomised controlled trial, compared with ERS alone and also with general recommendations about PA. Methods A total of 1338 older adults will be included in this study, recruited from four European countries through different existing primary prevention pathways. Participants will be randomly allocated into an ERS of 16 weeks (32 sessions, 45–60 min per session), ERS enhanced by seven sessions of SMSs and four telephone prompts, or a control group. Outcomes will be assessed at baseline, month 4 (end of ERS intervention), month 16 (12 months post intervention) and month 22 (18 months post intervention). Primary outcomes will include measures of SB (time spent sedentary) and PA (counts per minute). Secondary outcomes will include muscle and physical function, health economics’ related outcomes, anthropometry, quality of life, social networks, anxiety and depressive symptoms, disability, fear of falling, executive function and fatigue. A process evaluation will be conducted throughout the trial. The full analysis set will follow an intention-to-treat principle and will include all randomised participants for whom a baseline assessment is conducted. The study hypothesis will be tested with mixed linear models with repeated measures, to assess changes in the main outcomes (SB and PA) over time (baseline to month 22) and between study arms. Discussion The findings of this study may help inform the design and implementation of more effective interventions to reduce SB and increase PA levels, and hence improve long-term health outcomes in the older adult population. SITLESS aims to support policy-makers in deciding how or whether ERS should be further implemented or restructured in order to increase its adherence, impact and cost-effectiveness. Trial registration ClinicalTrials.gov, NCT02629666 . Registered 19 November 2015