370 research outputs found

    Equivalence of the realized input and output oriented indirect effects metrics in ecological network analysis

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    A new understanding of the consequences of how ecosystem elements are interconnected is emerging from the development and application of Ecological Network Analysis. The relative importance of indirect effects is central to this understanding, and the ratio of indirect flow to direct flow (I/D) is one indicator of their importance. Two methods have been proposed for calculating this indicator. The unit approach shows what would happen if each system member had a unit input or output, while the realized technique determines the ratio using the observed system inputs or outputs. When using the unit method, the input oriented and output oriented ratios can be different, potentially leading to conflicting results. However, we show that the input and output oriented I/D ratios are identical using the realized method when the system is at steady state. This work is a step in the maturation of Ecological Network Analysis that will let it be more readily testable empirically and ultimately more useful for environmental assessment and management.Comment: 13 pages, 1 figure, 1 tabl

    Associations between personal care product use patterns and breast cancer risk among white and black women in the sister study

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    BACKGROUND: Many personal care products include chemicals that might act as endocrine disruptors and thus increase the risk of breast cancer. OBJECTIVE: We examined the association between usage patterns of beauty, hair, and skin-related personal care products and breast cancer incidence in the Sister Study, a national prospective cohort study (enrollment 2003–2009). METHODS: Non-Hispanic black (4,452) and white women (n = 42,453) were examined separately using latent class analysis (LCA) to identify groups of individuals with similar patterns of self-reported product use in three categories (beauty, skin, hair). Multivariable Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between product use and breast cancer incidence. RESULTS: A total of 2,326 women developed breast cancer during follow-up (average follow-up = 5:4 y). Among black women, none of the latent class hazard ratios was elevated, but there were <100 cases in any category, limiting power. Among white women, those classified as “moderate” and “frequent” users of beauty products had increased risk of breast cancer relative to “infrequent” users [HR = 1:13 (95% CI: 1.00, 1.27) and HR = 1:15 (95% CI: 1.02, 1.30), respectively]. Frequent users of skincare products also had increased risk of breast cancer relative to infrequent users [HR = 1:13 (95% CI: 1.00, 1.29)]. None of the hair product classes was associated with increased breast cancer risk. The associations with beauty and skin products were stronger in postmenopausal women than in premenopausal women, but not significantly so. CONCLUSIONS: This work generates novel hypotheses about personal care product use and breast cancer risk. Whether these results are due to specific chemicals or to other correlated behaviors needs to be evaluated. https://doi.org/10.1289/EHP1480

    Measurement of the B0-anti-B0-Oscillation Frequency with Inclusive Dilepton Events

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    The B0B^0-Bˉ0\bar B^0 oscillation frequency has been measured with a sample of 23 million \B\bar B pairs collected with the BABAR detector at the PEP-II asymmetric B Factory at SLAC. In this sample, we select events in which both B mesons decay semileptonically and use the charge of the leptons to identify the flavor of each B meson. A simultaneous fit to the decay time difference distributions for opposite- and same-sign dilepton events gives Δmd=0.493±0.012(stat)±0.009(syst)\Delta m_d = 0.493 \pm 0.012{(stat)}\pm 0.009{(syst)} ps−1^{-1}.Comment: 7 pages, 1 figure, submitted to Physical Review Letter

    Thermomechanical erosion modelling of Baydaratskaya Bay, Russia with COSMOS

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    Rapid coastal erosion threatens Arctic coastal infrastructure, including communities and industrial installations. Erosion of permafrost depends on numerous processes, including thermal and mechanical behaviour of frozen and unfrozen soil, nearshore hydrodynamics, atmospheric forcing, and the presence of sea ice. The quantification and numerical modelling of these processes is essential to predicting Arctic coastal erosion. This paper presents a case study of Baydaratskaya Bay, Russia, using the COSMOS numerical model to predict thermal-mechanical erosion. In particular, this study focuses on thermoabrasional rather than thermodenudational processes. A field dataset of onshore thermal and mechanical soil characteristics was supplemented by sources from the literature to serve as input for the model. A detailed sensitivity analysis has been conducted to determine the influence of key parameters on coastal erosion rates at the study site. This case study highlights the need for expanded data collection on Arctic coastlines and provides direction for future investigations

    Application of compact laser-driven accelerator X-ray sources for industrial imaging

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    X-rays generated by betatron oscillations of electrons in a laser-driven plasma accelerator were characterised and applied to imaging industrial samples. With a 125TW laser, a low divergence beam with 5.2±1.7 × 107photonsmrad−2 per pulse was produced with a synchrotron spectrum with a critical energy of 14.6±1.3keV. Radiographs were obtained of a metrology test sample, battery electrodes, and a damage site in a composite material. These results demonstrate the suitability of the source for non-destructive evaluation applications. The potential for industrial implementation of plasma accelerators is discussed

    A database of chlorophyll a in Australian waters

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    Chlorophyll a is the most commonly used indicator of phytoplankton biomass in the marine environment. It is relatively simple and cost effective to measure when compared to phytoplankton abundance and is thus routinely included in many surveys. Here we collate 173, 333 records of chlorophyll a collected since 1965 from Australian waters gathered from researchers on regular coastal monitoring surveys and ocean voyages into a single repository. This dataset includes the chlorophyll a values as measured from samples analysed using spectrophotometry, fluorometry and high performance liquid chromatography (HPLC). The Australian Chlorophyll a database is freely available through the Australian Ocean Data Network portal (https://portal.aodn.org.au/). These data can be used in isolation as an index of phytoplankton biomass or in combination with other data to provide insight into water quality, ecosystem state, and relationships with other trophic levels such as zooplankton or fish.Claire H. Davies, Penelope Ajani, Linda Armbrecht, Natalia Atkins, Mark E. Baird, Jason Bear

    A review of spatial causal inference methods for environmental and epidemiological applications

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    The scientific rigor and computational methods of causal inference have had great impacts on many disciplines, but have only recently begun to take hold in spatial applications. Spatial casual inference poses analytic challenges due to complex correlation structures and interference between the treatment at one location and the outcomes at others. In this paper, we review the current literature on spatial causal inference and identify areas of future work. We first discuss methods that exploit spatial structure to account for unmeasured confounding variables. We then discuss causal analysis in the presence of spatial interference including several common assumptions used to reduce the complexity of the interference patterns under consideration. These methods are extended to the spatiotemporal case where we compare and contrast the potential outcomes framework with Granger causality, and to geostatistical analyses involving spatial random fields of treatments and responses. The methods are introduced in the context of observational environmental and epidemiological studies, and are compared using both a simulation study and analysis of the effect of ambient air pollution on COVID-19 mortality rate. Code to implement many of the methods using the popular Bayesian software OpenBUGS is provided

    Cross-ancestry genome-wide association analysis of corneal thickness strengthens link between complex and Mendelian eye diseases

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    Central corneal thickness (CCT) is a highly heritable trait associated with complex eye diseases such as keratoconus and glaucoma. We perform a genome-wide association meta-analysis of CCT and identify 19 novel regions. In addition to adding support for known connective tissue-related pathways, pathway analyses uncover previously unreported gene sets. Remarkably, >20% of the CCT-loci are near or within Mendelian disorder genes. These included FBN1, ADAMTS2 and TGFB2 which associate with connective tissue disorders (Marfan, Ehlers-Danlos and Loeys-Dietz syndromes), and the LUM-DCN-KERA gene complex involved in myopia, corneal dystrophies and cornea plana. Using index CCT-increasing variants, we find a significant inverse correlation in effect sizes between CCT and keratoconus (r =-0.62, P = 5.30 × 10-5) but not between CCT and primary open-angle glaucoma (r =-0.17, P = 0.2). Our findings provide evidence for shared genetic influences between CCT and keratoconus, and implicate candidate genes acting in collagen and extracellular matrix regulation
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