Differences in physical activity time-use composition associated with cardiometabolic risks

This study investigates the association between the overall physical activity composition of the day (sedentary behavior (SB), light intensity physical activity (LIPA) and moderate-to-vigorous physical activity (MVPA)) and cardiometabolic health, and examines whether improved health can be associated with replacing SB with LIPA. A cross-sectional analysis of the Health Survey for England 2008 on N = 1411 adults was undertaken using a compositional analysis approach to examine the relationship between cardiometabolic risk biomarkers and physical activity accounting for co-dependency between relative amounts of time spent in different behavior. Daily time spent in SB, LIPA and MVPA was determined from waist-mounted accelerometry data (Actigraph GT1M) and modelled against BMI, waist circumference, waist-to-hip ratio, blood pressure, total and HDL cholesterol, HbA1c, and VO2 maximum. The composition of time spent in SB, LIPA and MVPA was statistically significantly associated with BMI, waist circumference, waist-to-hips ratio, HDL cholesterol and VO2 maximum (p < 0.001), but not HbA1c, systolic and diastolic blood pressure, or total cholesterol. Increase of relative time spent in MVPA was beneficially associated with obesity markers, HDL cholesterol, and VO2 maximum, and SB with poorer outcomes. The association of changes in LIPA depended on whether it displaced MVPA or SB. Increasing the proportion of MVPA alone may have the strongest potential association with adiposity outcomes and HDL cholesterol but similar outcomes could also be associated with a lower quantity of MVPA provided a greater quantity of SB is replaced overall with LIPA (around 10.5 min of LIPA is equivalent to 1 min of MVPA). Keywords: MVPA, Sedentary behavior, Physical activity, Compositional data analysis, Cardiometabolic health, Adipoisit

A Neo-Institutional Assessment of Cooperative Evolution: Comparing the Australian Wheat Board and the Fonterra Dairy Group

Agribusiness,

The radial evolution of solar wind speeds

The WSA-ENLIL model predicts significant evolution of the solar wind speed. Along a flux tube the solar wind speed at 1.0 AU and beyond is found to be significantly altered from the solar wind speed in the outer corona at 0.1 AU, with most of the change occurring within a few tenths of an AU from the Sun. The evolution of the solar wind speed is most pronounced during solar minimum for solar wind with observed speeds at 1.0 AU between 400 and 500 km/s, while the fastest and slowest solar wind experiences little acceleration or deceleration. Solar wind ionic charge state observations made near 1.0 AU during solar minimum are found to be consistent with a large fraction of the intermediate-speed solar wind having been accelerated or decelerated from slower or faster speeds. This paper sets the groundwork for understanding the evolution of wind speed with distance, which is critical for interpreting the solar wind composition observations near Earth and throughout the inner heliosphere. We show from composition observations that the intermediate-speed solar wind (400-500 km/s) represents a mix of what was originally fast and slow solar wind, which implies a more bimodal solar wind in the corona than observed at 1.0 AU

Exploring Supply Chains from a Technical Debt Perspective

Software development has evolved from software development organizations building custom solutions for every need and creating a backlog of applications needed by users to specialized organizations producing components that are supplied to other software development organizations to speed the development of their software products. Our objective is to illustrate how a manager might use supply chain information to evaluate software being considered for inclusion in a product. We investigated the Eclipse platform code to illustrate analysis methods that produce information of use to decision makers. The technical debt of the software pieces was measured using the Technical Debt plug-in to SONAR as one input into the evaluation of supply chain quality. The dependency graphs of uses relationships among files were analyzed using graph metrics such as betweenness centrality. There was a statistically significant moderate correlation between the technical debt for a file and the betweenness centrality for that file. This relationship is used as the basis for a heuristic approach to forming advice to a development manager regarding which assets to acquire

Sublinear Estimation of Weighted Matchings in Dynamic Data Streams

This paper presents an algorithm for estimating the weight of a maximum weighted matching by augmenting any estimation routine for the size of an unweighted matching. The algorithm is implementable in any streaming model including dynamic graph streams. We also give the first constant estimation for the maximum matching size in a dynamic graph stream for planar graphs (or any graph with bounded arboricity) using $\tilde{O}(n^{4/5})$ space which also extends to weighted matching. Using previous results by Kapralov, Khanna, and Sudan (2014) we obtain a $\mathrm{polylog}(n)$ approximation for general graphs using $\mathrm{polylog}(n)$ space in random order streams, respectively. In addition, we give a space lower bound of $\Omega(n^{1-\varepsilon})$ for any randomized algorithm estimating the size of a maximum matching up to a $1+O(\varepsilon)$ factor for adversarial streams

Longitudinal Analysis of Technical Debt for Strategic Platform Adoption

Increasingly, software producing organizations utilize a common software platform, joining an ecosystem; however, little expertise exists on selecting which platform to use when presented a number of different platforms. While technical debt can be used to examine the quality of a software platform by the organization that produces the software, a single discrete data point does not provide sufficient context for analysis. In this paper, we seek to resolve this difficulty by applying linear regression analysis to technical debt data collected by the SonarQube static analyzer. We apply this method to a case study on Cytoscape network analysis platform to perform a pedagogical investigation on the longitudinal technical debt found in that platform. We present our case study on the longitudinal technical debt in the form of arguments for and against the adoption of the Cytoscape network analysis platform, utilizing the data and analysis generated from our method