Braids, posets and orthoschemes

In this article we study the curvature properties of the order complex of a graded poset under a metric that we call the ``orthoscheme metric''. In addition to other results, we characterize which rank 4 posets have CAT(0) orthoscheme complexes and by applying this theorem to standard posets and complexes associated with four-generator Artin groups, we are able to show that the 5-string braid group is the fundamental group of a compact nonpositively curved space.Comment: 33 pages, 16 figure

Months-Long Spike in Aqueous Arsenic Following Domestic Well Installation and Disinfection: Short- and Long-Term Drinking Water Quality Implications

Exposure to high concentration geogenic arsenic via groundwater is a worldwide health concern. Well installation introduces oxic drilling fluids and hypochlorite (a strong oxidant) for disinfection, thus inducing geochemical disequilibrium. Well installation causes changes in geochemistry lasting 12 + months, as illustrated in a recent study of 250 new domestic wells in Minnesota, north-central United States. One study well had extremely high initial arsenic (1550 µg/L) that substantially decreased after 15 months (5.2 µg/L). The drilling and development of the study well were typical and ordinary; nothing observable indicated the very high initial arsenic concentration. We hypothesized that oxidation of arsenic-containing sulfides (which lowers pH) combined with low pH dissolution of arsenic-bearing Fe (oxyhydr)oxides caused the very high arsenic concentration. Geochemical equilibrium considerations and modeling supported our hypothesis. Groundwater equilibrium redox conditions are poised at the Fe(III)(s)/Fe(II)(aq) stability boundary, indicating arsenic-bearing Fe (oxyhydr)oxide mineral sensitivity to pH and redox changes. Changing groundwater geochemistry can have negative implications for home water treatment (e.g., reduced arsenic removal efficiency, iron fouling), which can lead to ongoing but unrecognized hazard of arsenic exposure from domestic well water. Our results may inform arsenic mobilization processes and geochemical sensitivity in similarly complex aquifers in Southeast Asia and elsewhere

Arsenic in Petroleum-Contaminated Groundwater Near Bemidji, Minnesota is Predicted to Persist for Centuries

We used a reactive transport model to investigate the cycling of geogenic arsenic (As) in a petroleum-contaminated aquifer. We simulated As mobilization and sequestration using surface complexation reactions with Fe(OH)3 during petroleum biodegradation coupled with Fe-reduction. Model results predict that dissolved As in the plume will exceed the U.S. and EU 10 µg/L drinking water standard for ~400 years. Non-volatile dissolved organic carbon (NVDOC) in the model promotes As mobilization by exerting oxygen demand, which maintains anoxic conditions in the aquifer. After NVDOC degrades, As re-associates with Fe(OH)3 as oxygenated conditions are reestablished. Over the 400-year simulation, As transport resembles a “roll front” in which: (1) arsenic sorbed to Fe(OH)3 is released during Fe-reduction coupled to petroleum biodegradation; (2) dissolved As resorbs to Fe(OH)3 at the plume’s leading edge; and (3) over time, the plume expands, and resorbed As is re-released into groundwater. This “roll front” behavior underscores the transience of sorption as an As attenuation mechanism. Over the plume’s lifespan, simulations suggest that As will contaminate more groundwater than benzene from the oil spill. At its maximum, the model simulates that ~5.7× more groundwater will be contaminated by As than benzene, suggesting that As could pose a greater long-term water quality threat than benzene in this petroleum-contaminated aquifer

Can GPS and GRACE data be used to separate past and present-day surface loading in a data-driven approach?

Glacial isostatic adjustment (GIA) and the hydrological cycle are both associated with mass changes and vertical land motion (VLM), which are observed by GRACE and GPS, respectively. Hydrology-related VLM results from the instantaneous response of the elastic solid Earth to surface loading by freshwater, whereas GIA-related VLM reveals the long-term response of the viscoelastic Earth mantle to past ice loading history. Thus, observations of mass changes and VLM are interrelated, making GIA and hydrology difficult to quantify and study independently. In this work, we investigate the feasibility of separating these processes based on GRACE and GPS observations, in a fully data-driven and physically consistent approach. We take advantage of the differences in the spatio-temporal characteristics of the GIA and hydrology fields to estimate the respective contributions of each component using a Bayesian hierarchical modelling framework. A closed-loop synthetic test confirms that our method successfully solves this source separation problem. However, there are significant challenges when applying the same approach with actual observations and the answer to the main question of this study is more nuanced. In particular, in regions where GPS station coverage is sparse, the lack of informative data becomes a limiting factor

The scope of the Kalman filter for spatio-temporal applications in environmental science

The Kalman filter is a workhorse of dynamical modeling. But there are challenges when using the Kalman filter in environmental science: the complexity of environmental processes, the complicated and irregular nature of many environmental datasets, and the scale of environmental datasets, which may comprise many thousands of observations per time-step. We show how these challenges can be met within the Kalman filter, identifying some situations which are relatively easy to handle, such as datasets which are high-resolution in time, and some which are hard, like areal observations on small contiguous polygons. Overall, we conclude that many applications in environmental science are within the scope of the Kalman filter, or its generalizations

Developmental changes in the role of different metalinguistic awareness skills in Chinese reading acquisition from preschool to third grade

Copyright @ 2014 Wei et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.The present study investigated the relationship between Chinese reading skills and metalinguistic awareness skills such as phonological, morphological, and orthographic awareness for 101 Preschool, 94 Grade-1, 98 Grade-2, and 98 Grade-3 children from two primary schools in Mainland China. The aim of the study was to examine how each of these metalinguistic awareness skills would exert their influence on the success of reading in Chinese with age. The results showed that all three metalinguistic awareness skills significantly predicted reading success. It further revealed that orthographic awareness played a dominant role in the early stages of reading acquisition, and its influence decreased with age, while the opposite was true for the contribution of morphological awareness. The results were in stark contrast with studies in English, where phonological awareness is typically shown as the single most potent metalinguistic awareness factor in literacy acquisition. In order to account for the current data, a three-stage model of reading acquisition in Chinese is discussed.National Natural Science Foundation of China and Knowledge Innovation Program of the Chinese Academy of Sciences

An angiopoietin 2, FGF23, and BMP10 biomarker signature differentiates atrial fibrillation from other concomitant cardiovascular conditions

Early detection of atrial fibrillation (AF) enables initiation of anticoagulation and early rhythm control therapy to reduce stroke, cardiovascular death, and heart failure. In a cross-sectional, observational study, we aimed to identify a combination of circulating biomolecules reflecting different biological processes to detect prevalent AF in patients with cardiovascular conditions presenting to hospital. Twelve biomarkers identified by reviewing literature and patents were quantified on a high-precision, high-throughput platform in 1485 consecutive patients with cardiovascular conditions (median age 69 years [Q1, Q3 60, 78]; 60% male). Patients had either known AF (45%) or AF ruled out by 7-day ECG-monitoring. Logistic regression with backward elimination and a neural network approach considering 7 key clinical characteristics and 12 biomarker concentrations were applied to a randomly sampled discovery cohort (n=933) and validated in the remaining patients (n=552). In addition to age, sex, and body mass index (BMI), BMP10, ANGPT2, and FGF23 identified patients with prevalent AF (AUC 0.743 [95% CI 0.712, 0.775]). These circulating biomolecules represent distinct pathways associated with atrial cardiomyopathy and AF. Neural networks identified the same variables as the regression-based approach. The validation using regression yielded an AUC of 0.719 (95% CI 0.677, 0.762), corroborated using deep neural networks (AUC 0.784 [95% CI 0.745, 0.822]). Age, sex, BMI and three circulating biomolecules (BMP10, ANGPT2, FGF23) are associated with prevalent AF in unselected patients presenting to hospital. Findings should be externally validated. Results suggest that age and different disease processes approximated by these three biomolecules contribute to AF in patients. Our findings have the potential to improve screening programs for AF after external validation

An angiopoietin 2, FGF23, and BMP10 biomarker signature differentiates atrial fibrillation from other concomitant cardiovascular conditions

Abstract Early detection of atrial fibrillation (AF) enables initiation of anticoagulation and early rhythm control therapy to reduce stroke, cardiovascular death, and heart failure. In a cross-sectional, observational study, we aimed to identify a combination of circulating biomolecules reflecting different biological processes to detect prevalent AF in patients with cardiovascular conditions presenting to hospital. Twelve biomarkers identified by reviewing literature and patents were quantified on a high-precision, high-throughput platform in 1485 consecutive patients with cardiovascular conditions (median age 69 years [Q1, Q3 60, 78]; 60% male). Patients had either known AF (45%) or AF ruled out by 7-day ECG-monitoring. Logistic regression with backward elimination and a neural network approach considering 7 key clinical characteristics and 12 biomarker concentrations were applied to a randomly sampled discovery cohort (n = 933) and validated in the remaining patients (n = 552). In addition to age, sex, and body mass index (BMI), BMP10, ANGPT2, and FGF23 identified patients with prevalent AF (AUC 0.743 [95% CI 0.712, 0.775]). These circulating biomolecules represent distinct pathways associated with atrial cardiomyopathy and AF. Neural networks identified the same variables as the regression-based approach. The validation using regression yielded an AUC of 0.719 (95% CI 0.677, 0.762), corroborated using deep neural networks (AUC 0.784 [95% CI 0.745, 0.822]). Age, sex, BMI and three circulating biomolecules (BMP10, ANGPT2, FGF23) are associated with prevalent AF in unselected patients presenting to hospital. Findings should be externally validated. Results suggest that age and different disease processes approximated by these three biomolecules contribute to AF in patients. Our findings have the potential to improve screening programs for AF after external validation

Synthesis of marmycin A and investigation into its cellular activity

Anthracyclines such as doxorubicin are used extensively in the treatment of cancers. Anthraquinone-related angucyclines also exhibit antiproliferative properties and have been proposed to operate via similar mechanisms, including direct genome targeting. Here, we report the chemical synthesis of marmycin A and the study of its cellular activity. The aromatic core was constructed by means of a one-pot multistep reaction comprising a regioselective Diels-Alder cycloaddition, and the complex sugar backbone was introduced through a copper-catalysed Ullmann cross-coupling, followed by a challenging Friedel-Crafts cyclization. Remarkably, fluorescence microscopy revealed that marmycin A does not target the nucleus but instead accumulates in lysosomes, thereby promoting cell death independently of genome targeting. Furthermore, a synthetic dimer of marmycin A and the lysosome-targeting agent artesunate exhibited a synergistic activity against the invasive MDA-MB-231 cancer cell line. These findings shed light on the elusive pathways through which anthraquinone derivatives act in cells, pointing towards unanticipated biological and therapeutic applications