UCT-Kirchberg algebras have nuclear dimension one

We prove that every Kirchberg algebra in the UCT class has nuclear dimension 1. We first show that Kirchberg 2-graph algebras with trivial $K_0$ and finite $K_1$ have nuclear dimension 1 by adapting a technique developed by Winter and Zacharias for Cuntz algebras. We then prove that every Kirchberg algebra in the UCT class is a direct limit of 2-graph algebras to obtain our main theorem.Comment: 21 pages. Version 2: reference [2] has been added, and the discussion in the introduction updated; a small but important typo has been corrected in the definition of the graph E_T. Version 3: Some typo's corrected and references updated; reference [2] corrected as we had accidentally omitted one of the authors' names in the previous version (sorry Aaron!); this version to appear in Adv. Mat

Eagle: A Team Practices Audit Framework for Agile Software Development

Agile/XP (Extreme Programming) software teams are expected to follow a number of specific practices in each iteration, such as estimating the effort ("points") required to complete user stories, properly using branches and pull requests to coordinate merging multiple contributors’ code, having frequent "standups" to keep all team members in sync, and conducting retrospectives to identify areas of improvement for future iterations. We combine two observations in developing a methodology and tools to help teams monitor their performance on these practices. On the one hand, many Agile practices are increasingly supported by web-based tools whose "data exhaust" can provide insight into how closely the teams are following the practices. On the other hand, some of the practices can be expressed in terms similar to those developed for expressing service level objectives (SLO) in software as a service; as an example, a typical SLO for an interactive Web site might be "over any 5-minute window, 99% of requests to the main page must be delivered within 200ms" and, analogously, a potential Team Practice (TP) for an Agile/XP team might be "over any 2-week iteration, 75% of stories should be ’1-point’ stories". Following this similarity, we adapt a system originally developed for monitoring and visualizing service level agreement (SLA) compliance to monitor selected TPs for Agile/XP software teams. Specifically, the system consumes and analyzes the data exhaust from widely-used tools such as GitHub and Pivotal Tracker and provides team(s) and coach(es) a "dashboard" summarizing the teams’ adherence to various practices. As a qualitative initial investigation of its usefulness, we deployed it to twenty student teams in a four-sprint software engineering project course. We find an improvement of the adherence to team practice and a positive students’ self-evaluations of their team practices when using the tool, compared to previous experiences using an Agile/XP methodology. The demo video is located at https://youtu.be/A4xwJMEQh9c and a landing page with a live demo at https://isa-group.github.io/2019-05-eagle-demo/

A long noncoding RNA influences the choice of the X chromosome to be inactivated

X chromosome inactivation (XCI) is the process of silencing one of the X chromosomes in cells of the female mammal which ensures dosage compensation between the sexes. Although theoretically random in somatic tissues, the choice of which X chromosome is chosen to be inactivated can be biased in mice by genetic element(s) associated with the so-called X-controlling element (Xce). Although the Xce was first described and genetically localized nearly 40 y ago, its mode of action remains elusive. In the approach presented here, we identify a single long noncoding RNA (lncRNA) within the Xce locus, Lppnx, which may be the driving factor in the choice of which X chromosome will be inactivated in the developing female mouse embryo. Comparing weak and strong Xce alleles we show that Lppnx modulates the expression of Xist lncRNA, one of the key factors in XCI, by controlling the occupancy of pluripotency factors at Intron1 of Xist. This effect is counteracted by enhanced binding of Rex1 in DxPas34, another key element in XCI regulating the activity of Tsix lncRNA, the main antagonist of Xist, in the strong but not in the weak Xce allele. These results suggest that the different susceptibility for XCI observed in weak and strong Xce alleles results from differential transcription factor binding of Xist Intron 1 and DxPas34, and that Lppnx represents a decisive factor in explaining the action of the Xce

On fixed point sets and Lefschetz modules for sporadic simple groups

We consider 2-local geometries and other subgroup complexes for sporadic simple groups. For six groups, the fixed point set of a noncentral involution is shown to be equivariantly homotopy equivalent to a standard geometry for the component of the centralizer. For odd primes, fixed point sets are computed for sporadic groups having an extraspecial Sylow p-subgroup of order p^3, acting on the complex of those p-radical subgroups containing a p-central element in their centers. Vertices for summands of the associated reduced Lefschetz modules are described.Comment: 22 page

Genetic Polymorphisms In Estrogen-related Genes And The Risk Of Breast Cancer Among Han Chinese Women

Exposure to high levels of estrogen is considered an important risk factor for susceptibility to breast cancer. Common polymorphisms in genes that affect estrogen levels may be associated with breast cancer risk, but no comprehensive study has been performed among Han Chinese women. In the present study, 32 single-nucleotide polymorphisms (SNPs) in estrogen-related genes were genotyped using the MassARRAY IPLEX platform in 1076 Han Chinese women. Genotypic and allelic frequencies were compared between case and control groups. Unconditional logistic regression was used to assess the effects of SNPs on breast cancer risk. Associations were also evaluated for breast cancer subtypes stratified by estrogen receptor (ER) and progesterone receptor (PR) status. Case-control analysis showed a significant relation between heterozygous genotypes of rs700519 and rs2069522 and breast cancer risk (OR = 0.723, 95% CI = 0.541-0.965, p = 0.028 and OR = 1.500, 95% CI = 1.078-2.087, p = 0.016, respectively). Subgroup comparisons revealed that rs2446405 and rs17268974 were related to ER status, and rs130021 was associated with PR status. Our findings suggest that rs700519 and rs2069522 are associated with susceptibility to breast cancer among the Han Chinese population and have a cumulative effect with three other identified SNPs. Further genetic and functional studies are needed to identify additional SNPs, and to elucidate the underlying molecular mechanisms

Ultra-strong Adhesion of Graphene Membranes

As mechanical structures enter the nanoscale regime, the influence of van der Waals forces increases. Graphene is attractive for nanomechanical systems because its Young's modulus and strength are both intrinsically high, but the mechanical behavior of graphene is also strongly influenced by the van der Waals force. For example, this force clamps graphene samples to substrates, and also holds together the individual graphene sheets in multilayer samples. Here we use a pressurized blister test to directly measure the adhesion energy of graphene sheets with a silicon oxide substrate. We find an adhesion energy of 0.45 \pm 0.02 J/m2 for monolayer graphene and 0.31 \pm 0.03 J/m2 for samples containing 2-5 graphene sheets. These values are larger than the adhesion energies measured in typical micromechanical structures and are comparable to solid/liquid adhesion energies. We attribute this to the extreme flexibility of graphene, which allows it to conform to the topography of even the smoothest substrates, thus making its interaction with the substrate more liquid-like than solid-like.Comment: to appear in Nature Nanotechnolog

Analyzing the impacts of socio-economic factors on French departmental elections with CoDa methods

The vote shares by party on a given subdivision of a territory form a vector called composition (mathematically, a vector belonging to a simplex). It is interesting to model these shares and study the impact of the characteristics of the territorial units on the outcome of the elections. In the political economy literature, few regression models are adapted to the case of more than two political parties. In the statistical literature, there are regression models adapted to share vectors including Compositional Data (CoDa) models, but also Dirichlet models, and others. Our goal is to discuss and illustrate the use CoDa regression models for political economy models for more than two parties. The models are fitted on French electoral data of the 2015 departmental elections

A systems pharmacology model for inflammatory bowel disease

Motivation The literature on complex diseases is abundant but not always quantitative. This is particularly so for Inflammatory Bowel Disease (IBD), where many molecular pathways are qualitatively well described but this information cannot be used in traditional quantitative mathematical models employed in drug development. We propose the elaboration and validation of a logic network for IBD able to capture the information available in the literature that will facilitate the identification/validation of therapeutic targets. Results In this article, we propose a logic model for Inflammatory Bowel Disease (IBD) which consists of 43 nodes and 298 qualitative interactions. The model presented is able to describe the pathogenic mechanisms of the disorder and qualitatively describes the characteristic chronic inflammation. A perturbation analysis performed on the IBD network indicates that the model is robust. Also, as described in clinical trials, a simulation of anti-TNFα, anti-IL2 and Granulocyte and Monocyte Apheresis showed a decrease in the Metalloproteinases node (MMPs), which means a decrease in tissue damage. In contrast, as clinical trials have demonstrated, a simulation of anti-IL17 and anti-IFNγ or IL10 overexpression therapy did not show any major change in MMPs expression, as corresponds to a failed therapy. The model proved to be a promising in silico tool for the evaluation of potential therapeutic targets, the identification of new IBD biomarkers, the integration of IBD polymorphisms to anticipate responders and non-responders and can be reduced and transformed in quantitative model/s