2,609 research outputs found

    The radial evolution of solar wind speeds

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    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

    Sublinear Estimation of Weighted Matchings in Dynamic Data Streams

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    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 O~(n4/5)\tilde{O}(n^{4/5}) space which also extends to weighted matching. Using previous results by Kapralov, Khanna, and Sudan (2014) we obtain a polylog(n)\mathrm{polylog}(n) approximation for general graphs using polylog(n)\mathrm{polylog}(n) space in random order streams, respectively. In addition, we give a space lower bound of Ω(n1−ε)\Omega(n^{1-\varepsilon}) for any randomized algorithm estimating the size of a maximum matching up to a 1+O(ε)1+O(\varepsilon) factor for adversarial streams

    The impact of constructive operating lease capitalisation on key accounting ratios

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    Current UK lease accounting regulation does not require operating leases to be capitalised in the accounts of lessees, although this is likely to change with the publication of FRS 5. This study conducts a prospective analysis of the effects of such a change. The potential magnitude of the impact of lease capitalisation upon individual users' decisions, market valuations, company cash flows, and managers' behaviour can be indicated by the effect on key accounting ratios, which are employed in decision-making and in financial contracts. The capitalised value of operating leases is estimated using a method similar to that suggested by Imhoff, Lipe and Wright (1991), adapted for the UK accounting and tax environment, and developed to incorporate company-specific assumptions. Results for 1994 for a random sample of 300 listed UK companies show that, on average, the unrecorded long-term liability represented 39% of reported long-term debt, while the unrecorded asset represented 6% of total assets. Capitalisation had a significant impact (at the 1% level) on six of the nine selected ratios (profit margin, return on assets, asset turnover, and three measures of gearing). Moreover, the Spearman rank correlation between each ratio before and after capitalisation revealed that the ranking of companies changed markedly for gearing measures in particular. There were significant inter-industry variations, with the services sector experiencing the greatest impact. An analysis of the impact of capitalisation over the five-year period from 1990 to 1994 showed that capitalisation had the greatest impact during the trough of the recession. Results were shown to be robust with respect to key assumptions of the capitalisation method. These findings contribute to the assessment of the economic consequences of a policy change requiring operating lease capitalisation. Significant changes in the magnitude of key accounting ratios and a major shift in company performance rankings suggest that interested parties' decisions and company cash flows are likely to be affected

    Space physics for graduate students: an activities-based approach

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    The geospace environment is controlled largely by events on the Sun, such as solar flares and coronal mass ejections, which generate significant geomagnetic and upper atmospheric disturbances. The study of this Sun-Earth system, which has become known as space weather, has both intrinsic scientific interest and practical applications. Adverse conditions in space can damage satellites and disrupt communications, navigation, and electric power grids, as well as endanger astronauts. The Center for Integrated Space Weather Modeling (CISM), a Science and Technology Center (STC) funded by the U.S. National Science Foundation (see http://www.bu.edu/cism/), is developing a suite of integrated physics-based computer models that describe the space environment from the Sun to the Earth for use in both research and operations [Hughes and Hudson, 2004, p. 1241]. To further this mission, advanced education and training programs sponsored by CISM encourage students to view space weather as a system that encompasses the Sun, the solar wind, the magnetosphere, and the ionosphere/thermosphere. This holds especially true for participants in the CISM space weather summer school [Simpson, 2004]

    Economic, social and demographic impacts of drought on treatment adherence among people living with HIV in rural South Africa: A qualitative analysis

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    The 2015 El Niño-triggered drought in Southern Africa caused widespread economic and livelihood disruption in South Africa, imposing multiple physical and health challenges for rural populations including people living with HIV (PLHIV). We examined the economic, social and demographic impacts of drought drawing on 27 in-depth interviews in two cohorts of PLHIV in Hlabisa, uMkhanyakude district, KwaZulu-Natal. Thematic analysis revealed how drought-enforced soil water depletion, dried-up rivers, and dams culminated in a continuum of events such as loss of livestock, reduced agricultural production, and insufficient access to water and food which was understood to indirectly have a negative impact on HIV treatment adherence. This was mediated through disruptions in incomes, livelihoods and food systems, increased risk to general health, forced mobility and exacerbation of contextual vulnerabilities linked to poverty and unemployment. The systems approach, drawn from interview themes, hypothesises the complex pathways of plausible networks of impacts from drought through varying socioeconomic factors, exacerbating longstanding contextual precarity, and ultimately challenging HIV care utilisation. Understanding the multidimensional relationships between climate change, especially drought, and poor HIV care outcomes through the prism of contextual vulnerabilities is vital for shaping policy interventions

    Evolution of associative learning in chemical networks

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    Organisms that can learn about their environment and modify their behaviour appropriately during their lifetime are more likely to survive and reproduce than organisms that do not. While associative learning – the ability to detect correlated features of the environment – has been studied extensively in nervous systems, where the underlying mechanisms are reasonably well understood, mechanisms within single cells that could allow associative learning have received little attention. Here, using in silico evolution of chemical networks, we show that there exists a diversity of remarkably simple and plausible chemical solutions to the associative learning problem, the simplest of which uses only one core chemical reaction. We then asked to what extent a linear combination of chemical concentrations in the network could approximate the ideal Bayesian posterior of an environment given the stimulus history so far? This Bayesian analysis revealed the ’memory traces’ of the chemical network. The implication of this paper is that there is little reason to believe that a lack of suitable phenotypic variation would prevent associative learning from evolving in cell signalling, metabolic, gene regulatory, or a mixture of these networks in cells

    Solar Flares and Coronal Mass Ejections: A Statistically Determined Flare Flux-CME Mass Correlation

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    In an effort to examine the relationship between flare flux and corresponding CME mass, we temporally and spatially correlate all X-ray flares and CMEs in the LASCO and GOES archives from 1996 to 2006. We cross-reference 6,733 CMEs having well-measured masses against 12,050 X-ray flares having position information as determined from their optical counterparts. For a given flare, we search in time for CMEs which occur 10-80 minutes afterward, and we further require the flare and CME to occur within +/-45 degrees in position angle on the solar disk. There are 826 CME/flare pairs which fit these criteria. Comparing the flare fluxes with CME masses of these paired events, we find CME mass increases with flare flux, following an approximately log-linear, broken relationship: in the limit of lower flare fluxes, log(CME mass)~0.68*log(flare flux), and in the limit of higher flare fluxes, log(CME mass)~0.33*log(flare flux). We show that this broken power-law, and in particular the flatter slope at higher flare fluxes, may be due to an observational bias against CMEs associated with the most energetic flares: halo CMEs. Correcting for this bias yields a single power-law relationship of the form log(CME mass)~0.70*log(flare flux). This function describes the relationship between CME mass and flare flux over at least 3 dex in flare flux, from ~10^-7 to 10^-4 W m^-2.Comment: 28 pages, 16 figures, accepted to Solar Physic
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