Evolutionary Dynamics on Small-Order Graphs

Abstract. We study the stochastic birth-death model for structured finite populations popularized by Lieberman et al. [Lieberman, E., Hauert, C., Nowak, M.A., 2005. Evolutionary dynamics on graphs. Nature 433, 312-316]. We consider all possible connected undirected graphs of orders three through eight. For each graph, using the Monte Carlo Markov Chain simulations, we determine the fixation probability of a mutant introduced at every possible vertex. We show that the fixation probability depends on the vertex and on the graph. A randomly placed mutant has the highest chances of fixation in a star graph, closely followed by star-like graphs. The fixation probability was lowest for regular and almost regular graphs. We also find that within a fixed graph, the fixation probability of a mutant has a negative correlation with the degree of the starting vertex. 1

Measurement of the 58Ni(α, γ) 62Zn reaction and its astrophysical impact

Funding Details: PHY 08-22648, NSF, National Science Foundation; PHY 0969058, NSF, National Science Foundation; PHY 1102511, NSF, National Science FoundationCross section measurements of the 58Ni(α,γ)62Zn reaction were performed in the energy range Eα=5.5to9.5 MeV at the Nuclear Science Laboratory of the University of Notre Dame, using the NSCL Summing NaI(Tl) detector and the γ-summing technique. The measurements are compared to predictions in the statistical Hauser-Feshbach model of nuclear reactions using the SMARAGD code. It is found that the energy dependence of the cross section is reproduced well but the absolute value is overestimated by the prediction. This can be remedied by rescaling the α width by a factor of 0.45. Stellar reactivities were calculated with the rescaled α width and their impact on nucleosynthesis in type Ia supernovae has been studied. It is found that the resulting abundances change by up to 5% when using the new reactivities. © 2014 American Physical Society.Peer reviewe

Indoor dust acts as an adjuvant to promote sensitization to peanut through the airway

Background: There is growing evidence that environmental peanut exposure through non-oral routes, including the skin and respiratory tract, can result in peanut sensitization. Environmental adjuvants in indoor dust can promote sensitization to inhaled antigens, but whether they contribute to peanut allergy development is unclear. Objective: We investigated whether indoor dust promotes airway sensitization to peanut and peanut allergy development in mice. Methods: Female and male C57BL/6J mice were exposed via the airways to peanut, indoor dust extract, or both for 2 weeks. Mice were then challenged with peanut and assessed for anaphylaxis. Peanut-specific immunoglobulins, peanut uptake by lung conventional dendritic cells (cDCs), lung innate cytokines, and T cell differentiation in lung-draining lymph nodes were quantified. Innate cytokine production by primary human bronchial epithelial cells exposed to indoor dust was also determined. Results: Inhalational exposure to low levels of peanut in combination with indoor dust, but neither alone, resulted in production of peanut-specific IgE and development of anaphylaxis upon peanut challenge. Indoor dust triggered production of innate cytokines in murine lungs and in primary human bronchial epithelial cells. Additionally, inhaled indoor dust stimulated maturation and migration of peanut-laden lung type 1 cDCs to draining lymph nodes. Inhalational exposure to peanut and indoor dust induced peanut-specific T helper 2 cell differentiation and accumulation of T follicular helper cells in draining lymph nodes, which were associated with increased B cell numbers and peanut-specific immunoglobulin production. Conclusions & clinical relevance: Indoor dust promotes airway sensitization to peanut and development of peanut allergy in mice. Our findings suggest that environmental adjuvants in indoor dust may be determinants of peanut allergy development in children

Design of SECAR a recoil mass separator for astrophysical capture reactions with radioactive beams

A recoil mass separator SECAR has been designed for the purpose of studying low-energy (p,γ) and (α,γ) reactions in inverse kinematics with radioactive beams for masses up to about A = 65. Their reaction rates are of importance for our understanding of the energy production and nucleosynthesis during explosive hydrogen and helium burning. The radiative capture reactions take place in a windowless hydrogen or He gas target at the entrance of the separator, which consists of four Sections. The first Section selects the charge state of the recoils. The second and third Sections contain Wien Filters providing high mass resolving power to separate efficiently the intense beam from the few reaction products. In the following fourth Section, the reaction products are guided into a detector system capable of position, angle and time-of-flight measurements. In order to accept the complete kinematic cone of recoil particles including multiple scattering in the target in the center of mass energy range of 0.2 MeV to 3.0 MeV, the system must have a large polar angle acceptance of ± 25 mrad. This requires a careful minimization of higher order aberrations. The present system will be installed at the NSCL ReA3 accelerator and will be used with the much higher beam intensities of the FRIB facility when it becomes available

An evaluation of the efficacy of very high resolution air-quality modelling over the Athabasca oil sands region, Alberta, Canada

We examine the potential benefits of very high resolution for air-quality forecast simulations using a nested system of the Global Environmental Multiscale-Modelling Air-quality and Chemistry chemical transport model. We focus on simulations at 1 and 2.5 km grid-cell spacing for the same time period and domain (the industrial emissions region of the Athabasca oil sands). Standard grid cell to observation station pair analyses show no benefit to the higher-resolution simulation (and a degradation of performance for most metrics using this standard form of evaluation). However, when the evaluation methodology is modified, to include a search over equivalent representative regions surrounding the observation locations for the closest fit to the observations, the model simulation with the smaller grid-cell size had the better per

Emotional intelligence and British expatriates’ cross-cultural adjustment in international construction projects

© 2016 Informa UK Limited, trading as Taylor & Francis Group. Today’s internationalized business demands global mindset, intercultural sensitivity and the ability to skilfully negotiate through cross-cultural interactions. Therefore, the overall aim was to investigate the influence of emotional intelligence (EI) on cross-cultural adjustment (CCA) of British expatriates working on International Architectural, Engineering and Construction assignments in Sub-Saharan Africa, China, Middle East and Indian Sub-Continent. Specifically, the causal relationship between EI and three facets of CCA i.e. work, general and interaction adjustment was explored. A sequential exploratory mixed methods design was adopted. These include extensive review of existing literature, eighteen unstructured interviews, and questionnaire survey of 191 British expatriates operating in 29 different countries from the four regions under investigation. Structural equation modelling was used to assess the causal relationship between EI and CCA. Results show that EI accounted for 91, 64 and 24% of the variance in work, interaction and general adjustment respectively. Overall, the model was able to explain 60% variance in CCA, suggesting that EI competencies play a huge role in facilitating an expatriate understand and adapt to host country culture. The findings would help decision-makers (HR managers) during expatriate selection process, in understanding that along with technical skills, it is the emotional competencies that are crucial in assisting expatriates adjust to foreign way of life

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Harmonization of Respiratory Data from 9 US Population-Based Cohorts

Chronic lower respiratory diseases (CLRDs) are the fourth leading cause of death in the United States. To support investigations into CLRD risk determinants and new approaches to primary prevention, we aimed to harmonize and pool respiratory data from US general population-based cohorts. Data were obtained from prospective cohorts that performed prebronchodilator spirometry and were harmonized following 2005 ATS/ERS standards. In cohorts conducting follow-up for noncardiovascular events, CLRD events were defined as hospitalizations/deaths adjudicated as CLRDrelated or assigned relevant administrative codes. Coding and variable names were applied uniformly. The pooled sample included 65,251 adults in 9 cohorts followed-up for CLRD-related mortality over 653,380 person-years during 1983-2016. Average baseline age was 52 years; 56% were female; 49% were never-smokers; and racial/ethnic composition was 44% white, 22% black, 28% Hispanic/Latino, and 5% American Indian. Over 96% had complete data on smoking, clinical CLRD diagnoses, and dyspnea. After excluding invalid spirometry examinations (13%), there were 105,696 valid examinations (median, 2 per participant). Of 29,351 participants followed for CLRD hospitalizations, median follow-up was 14 years; only 5% were lost to follow-up at 10 years. The NHLBI Pooled Cohorts Study provides a harmonization standard applied to a large, US population-based sample that may be used to advance epidemiologic research on CLRD