Machine Learning Predicts Reach-Scale Channel Types From Coarse-Scale Geospatial Data in a Large River Basin

Hydrologic and geomorphic classifications have gained traction in response to the increasing need for basin-wide water resources management. Regardless of the selected classification scheme, an open scientific challenge is how to extend information from limited field sites to classify tens of thousands to millions of channel reaches across a basin. To address this spatial scaling challenge, this study leverages machine learning to predict reach-scale geomorphic channel types using publicly available geospatial data. A bottom-up machine learning approach selects the most accurate and stable model among∼20,000 combinations of 287 coarse geospatial predictors, preprocessing methods, and algorithms in a three-tiered framework to (i) define a tractable problem and reduce predictor noise, (ii) assess model performance in statistical learning, and (iii) assess model performance in prediction. This study also addresses key issues related to the design, interpretation, and diagnosis of machine learning models in hydrologic sciences. In an application to the Sacramento River basin (California, USA), the developed framework selects a Random Forest model to predict 10 channel types previously determined from 290 field surveys over 108,943 two hundred-meter reaches. Performance in statistical learning is reasonable with a 61% median cross-validation accuracy, a sixfold increase over the 10% accuracy of the baseline random model, and the predictions coherently capture the large-scale geomorphic organization of the landscape. Interestingly, in the study area, the persistent roughness of the topography partially controls channel types and the variation in the entropy-based predictive performance is explained by imperfect training information and scale mismatch between labels and predictors

Cultivation of a Synergistetes strain representing a previously uncultivated lineage

Subgingival plaque samples obtained from human subjects with periodontitis, shown to include previously uncultivable members of the phylum Synergistetes, were used to inoculate Cooked Meat Medium (CMM). The presence of Cluster A (uncultivable) Synergistetes was monitored by fluorescent in situ hybridization (FISH) and quantitative PCR (Q-PCR). Cluster A Synergistetes were found to grow in CMM in co-culture with other plaque bacteria and growth was stimulated by the addition of mucin and serum. Plaque samples were also used to inoculate Blood Agar (BA) plates and growth of Cluster A Synergistetes was revealed after anaerobic incubation, by colony hybridization with specific probes. Surface growth on the plates in regions identified by colony hybridization was harvested and used to inoculate fresh plates, thus enriching for Cluster A Synergistetes. Cross-streaks of other plaque bacteria were also used to stimulate Synergistetes growth. In the early passages, no discrete Synergistetes colonies were seen, but after eight passages and the use of cross-streaks of other bacteria present in the enriched community, colonies arose, which consisted solely of Cluster A Synergistetes cells, as determined by 16S rRNA gene PCR and cloning. This is the first report of the successful culture of a member of the uncultivable branch of this phylum

Improving performance and fostering accountability in the public sector through system dynamics modelling: From an 'external' to an 'internal' perspective

This paper aims to outline the benefits justifying a tailored approach to System Dynamics (SD) modelling in the public sector, to improve performance and foster decision makers' accountability. The need of combining an 'internal' with an 'external' perspective (in respect to decisionmakers) in developing SDmodels is claimed. Different levels of intervention (i.e. macro, micro and meso) are discussed. Two case studies are analysed. The first one demonstrates how a dynamic resource-based view (DRBV) can support an analysis of the impact of back and front office units on a public sector organization's performance drivers. The second case shows how SD modelling based on a DRBV can also be applied to improve performance on a political level. Copyright \ua9 2010 John Wiley & Sons, Ltd

Cambium non est mutuum: exchange and interest rates in medieval Europe

A major gap in our understanding of the medieval economy concerns interest rates, especially relating to commercial credit. Although direct evidence about interest rates is scattered and anecdotal, there is much more surviving information about exchange rates. Since both contemporaries and historians have suggested that exchange and rechange transactions could be used to disguise the charging of interest in order to circumvent the usury prohibition, it should be possible to back out the interest rates from exchange rates. The following analysis is based on a new dataset of medieval exchange rates collected from commercial correspondence in the archive of Francesco di Marco Datini of Prato, c.1383-1411. It demonstrates that the time value of money was consistently incorporated into market exchange rates. Moreover, these implicit interest rates are broadly comparable to those received from other types of commercial loan and investment. Although on average profitable, the return on any individual exchange and rechange transaction did involve a degree of uncertainty that may have justified their non-usurious nature. However, there were also practical reasons why medieval merchants may have used foreign exchange transactions as a means of extending credit

Conflicts about water in Lake Chad: are environmental, vulnerability and security issues linked?

This paper builds on the growing literature that explores the relations between environmental change and non-traditional security, defined as non-military threats that challenge the survival and well-being of peoples and states. The Lake Chad basin in Africa is used as a case study for analysis. Focusing on a set of questions that has dominated recent theoretical debates, the paper investigates if conflicts resulting from water scarcity are as much about the broader vulnerability of the Lake Chad region as they are about changes in the Lake system and its environment. It argues that conflict is a probable outcome only in locations that are already challenged by a multitude of other context-specific factors beside resource scarcity. In the Lake Chad context, the likelihood of scarcity-driven conflict depends on whether vulnerability increases or decreases in the face of a declining water supply. The paper provides perspectives for a nuanced understanding of how the receding Lake Chad has led to conflict and outlines an integrated, forward-looking research agenda for linking environmental change, vulnerability and security issues in integrated human-environment systems

Exploring links between greenspace and sudden unexpected death: A spatial analysis

Greenspace has been increasingly recognized as having numerous health benefits. However, its effects are unknown concerning sudden unexpected death (SUD), commonly referred to as sudden cardiac death, which constitutes a large proportion of mortality in the United States. Because greenspace can promote physical activity, reduce stress and buffer air pollutants, it may have beneficial effects for people at risk of SUD, such as those with heart disease, hypertension, and diabetes mellitus. Using several spatial techniques, this study explored the relationship between SUD and greenspace. We adjudicated 396 SUD cases that occurred from March 2013 to February 2015 among reports from emergency medical services (EMS) that attended out-of-hospital deaths in Wake County (central North Carolina, USA). We measured multiple greenspace metrics in each census tract, including the percentages of forest, grassland, average tree canopy, tree canopy diversity, near-road tree canopy and greenway density. The associations between SUD incidence and these greenspace metrics were examined using Poisson regression (non-spatial) and Bayesian spatial models. The results from both models indicated that SUD incidence was inversely associated with both greenway density (adjusted risk ratio [RR] = 0.82, 95% credible/ confidence interval [CI]: 0.69–0.97) and the percentage of forest (adjusted RR = 0.90, 95% CI: 0.81–0.99). These results suggest that increases in greenway density by 1 km/km2 and in forest by 10% were associated with a decrease in SUD risk of 18% and 10%, respectively. The inverse relationship was not observed between SUD incidence and other metrics, including grassland, average tree canopy, near-road tree canopy and tree canopy diversity. This study implies that greenspace, specifically greenways and forest, may have beneficial effects for people at risk of SUD. Further studies are needed to investigate potential causal relationships between greenspace and SUD, and potential mechanisms such as promoting physical activity and reducing stress

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Measurement of the polarisation of W bosons produced with large transverse momentum in pp collisions at sqrt(s) = 7 TeV with the ATLAS experiment

This paper describes an analysis of the angular distribution of W->enu and W->munu decays, using data from pp collisions at sqrt(s) = 7 TeV recorded with the ATLAS detector at the LHC in 2010, corresponding to an integrated luminosity of about 35 pb^-1. Using the decay lepton transverse momentum and the missing transverse energy, the W decay angular distribution projected onto the transverse plane is obtained and analysed in terms of helicity fractions f0, fL and fR over two ranges of W transverse momentum (ptw): 35 < ptw < 50 GeV and ptw > 50 GeV. Good agreement is found with theoretical predictions. For ptw > 50 GeV, the values of f0 and fL-fR, averaged over charge and lepton flavour, are measured to be : f0 = 0.127 +/- 0.030 +/- 0.108 and fL-fR = 0.252 +/- 0.017 +/- 0.030, where the first uncertainties are statistical, and the second include all systematic effects.Comment: 19 pages plus author list (34 pages total), 9 figures, 11 tables, revised author list, matches European Journal of Physics C versio