Denitrification and inference of nitrogen sources in the karstic Floridan Aquifer

Aquifer denitrification is among the most poorly constrained fluxes in global and regional nitrogen budgets. The few direct measurements of denitrification in groundwaters provide limited information about its spatial and temporal variability, particularly at the scale of whole aquifers. Uncertainty in estimates of denitrification may also lead to underestimates of its effect on isotopic signatures of inorganic N, and thereby confound the inference of N source from these data. In this study, our objectives are to quantify the magnitude and variability of denitrification in the Upper Floridan Aquifer (UFA) and evaluate its effect on N isotopic signatures at the regional scale. Using dual noble gas tracers (Ne, Ar) to generate physical predictions of N2 gas concentrations for 112 observations from 61 UFA springs, we show that excess (i.e. denitrification-derived) N2 is highly variable in space and inversely correlated with dissolved oxygen (O2). Negative relationships between O2 and δ15N NO3 across a larger dataset of 113 springs, well-constrained isotopic fractionation coefficients, and strong 15N:18O covariation further support inferences of denitrification in this uniquely organic-matter-poor system. Despite relatively low average rates, denitrification accounted for 32 % of estimated aquifer N inputs across all sampled UFA springs. Back-calculations of source δ15N NO3 based on denitrification progression suggest that isotopically-enriched nitrate (NO3-) in many springs of the UFA reflects groundwater denitrification rather than urban- or animal-derived inputs. © Author(s) 2012.

Association between DNA damage response and repair genes and risk of invasive serous ovarian cancer.

BACKGROUND: We analyzed the association between 53 genes related to DNA repair and p53-mediated damage response and serous ovarian cancer risk using case-control data from the North Carolina Ovarian Cancer Study (NCOCS), a population-based, case-control study. METHODS/PRINCIPAL FINDINGS: The analysis was restricted to 364 invasive serous ovarian cancer cases and 761 controls of white, non-Hispanic race. Statistical analysis was two staged: a screen using marginal Bayes factors (BFs) for 484 SNPs and a modeling stage in which we calculated multivariate adjusted posterior probabilities of association for 77 SNPs that passed the screen. These probabilities were conditional on subject age at diagnosis/interview, batch, a DNA quality metric and genotypes of other SNPs and allowed for uncertainty in the genetic parameterizations of the SNPs and number of associated SNPs. Six SNPs had Bayes factors greater than 10 in favor of an association with invasive serous ovarian cancer. These included rs5762746 (median OR(odds ratio)(per allele) = 0.66; 95% credible interval (CI) = 0.44-1.00) and rs6005835 (median OR(per allele) = 0.69; 95% CI = 0.53-0.91) in CHEK2, rs2078486 (median OR(per allele) = 1.65; 95% CI = 1.21-2.25) and rs12951053 (median OR(per allele) = 1.65; 95% CI = 1.20-2.26) in TP53, rs411697 (median OR (rare homozygote) = 0.53; 95% CI = 0.35 - 0.79) in BACH1 and rs10131 (median OR( rare homozygote) = not estimable) in LIG4. The six most highly associated SNPs are either predicted to be functionally significant or are in LD with such a variant. The variants in TP53 were confirmed to be associated in a large follow-up study. CONCLUSIONS/SIGNIFICANCE: Based on our findings, further follow-up of the DNA repair and response pathways in a larger dataset is warranted to confirm these results.

Bayesian Gaussian Copula Factor Models for Mixed Data.

Gaussian factor models have proven widely useful for parsimoniously characterizing dependence in multivariate data. There is a rich literature on their extension to mixed categorical and continuous variables, using latent Gaussian variables or through generalized latent trait models acommodating measurements in the exponential family. However, when generalizing to non-Gaussian measured variables the latent variables typically influence both the dependence structure and the form of the marginal distributions, complicating interpretation and introducing artifacts. To address this problem we propose a novel class of Bayesian Gaussian copula factor models which decouple the latent factors from the marginal distributions. A semiparametric specification for the marginals based on the extended rank likelihood yields straightforward implementation and substantial computational gains. We provide new theoretical and empirical justifications for using this likelihood in Bayesian inference. We propose new default priors for the factor loadings and develop efficient parameter-expanded Gibbs sampling for posterior computation. The methods are evaluated through simulations and applied to a dataset in political science. The models in this paper are implemented in the R package bfa.

Changing American Congregations: Findings from the Third Wave of the National Congregations Study

The third wave of the National Congregations Study (NCS-III) was conducted in 2012. The 2012 General Social Survey asked respondents who attend religious services to name their religious congregation, producing a nationally representative cross-section of congregations from across the religious spectrum. Data about these congregations was collected via a 50-minute interview with one key informant from 1,331 congregations. Information was gathered about multiple aspects of congregations’ social composition, structure, activities, and programming. Approximately two-thirds of the NCS-III questionnaire replicates items from 1998 or 2006-07 NCS waves. Each congregation was geocoded, and selected data from the 2010 United States census or American Community Survey have been appended. We describe NCS-III methodology and use the cumulative NCS dataset (containing 4,071 cases) to describe five trends: more ethnic diversity, greater acceptance of gays and lesbians, increasingly informal worship styles, declining size (but not from the perspective of the average attendee), and declining denominational affiliation.

Mainland size variation informs predictive models of exceptional insular body size change in rodents.

The tendency for island populations of mammalian taxa to diverge in body size from their mainland counterparts consistently in particular directions is both impressive for its regularity and, especially among rodents, troublesome for its exceptions. However, previous studies have largely ignored mainland body size variation, treating size differences of any magnitude as equally noteworthy. Here, we use distributions of mainland population body sizes to identify island populations as 'extremely' big or small, and we compare traits of extreme populations and their islands with those of island populations more typical in body size. We find that although insular rodents vary in the directions of body size change, 'extreme' populations tend towards gigantism. With classification tree methods, we develop a predictive model, which points to resource limitations as major drivers in the few cases of insular dwarfism. Highly successful in classifying our dataset, our model also successfully predicts change in untested cases.

Fishing quota markets

In 1986, New Zealand responded to the open-access problem by establishing the world's largest individual transferable quota (ITQ) system. Using a 15-year panel dataset from New Zealand that covers 33 species and more than 150 markets for fishing quotas, we assess trends in market activity, price dispersion, and the fundamentals determining quota prices. We find that market activity is sufficiently high in the economically important markets and that price dispersion has decreased. We also find evidence of economically rational behavior through the relationship between quota lease and sale prices and fishing output and input prices, ecological variability, and market interest rates. Controlling for these factors, our results show a greater increase in quota prices for fish stocks that faced significant reductions, consistent with increased profitability due to rationalization. Overall, this suggests that these markets are operating reasonably well, implying that ITQs can be effective instruments for efficient fisheries management. © 2004 Elsevier Inc. All rights reserved.

A Dynamic Directional Model for Effective Brain Connectivity using Electrocorticographic (ECoG) Time Series.

We introduce a dynamic directional model (DDM) for studying brain effective connectivity based on intracranial electrocorticographic (ECoG) time series. The DDM consists of two parts: a set of differential equations describing neuronal activity of brain components (state equations), and observation equations linking the underlying neuronal states to observed data. When applied to functional MRI or EEG data, DDMs usually have complex formulations and thus can accommodate only a few regions, due to limitations in spatial resolution and/or temporal resolution of these imaging modalities. In contrast, we formulate our model in the context of ECoG data. The combined high temporal and spatial resolution of ECoG data result in a much simpler DDM, allowing investigation of complex connections between many regions. To identify functionally segregated sub-networks, a form of biologically economical brain networks, we propose the Potts model for the DDM parameters. The neuronal states of brain components are represented by cubic spline bases and the parameters are estimated by minimizing a log-likelihood criterion that combines the state and observation equations. The Potts model is converted to the Potts penalty in the penalized regression approach to achieve sparsity in parameter estimation, for which a fast iterative algorithm is developed. The methods are applied to an auditory ECoG dataset.

Functional Variants in Notch Pathway Genes NCOR2, NCSTN, and MAML2 Predict Survival of Patients with Cutaneous Melanoma.

BACKGROUND: The Notch signaling pathway is constitutively activated in human cutaneous melanoma to promote growth and aggressive metastatic potential of primary melanoma cells. Therefore, genetic variants in Notch pathway genes may affect the prognosis of cutaneous melanoma patients. METHODS: We identified 6,256 SNPs in 48 Notch genes in 858 cutaneous melanoma patients included in a previously published cutaneous melanoma genome-wide association study dataset. Multivariate and stepwise Cox proportional hazards regression and false-positive report probability corrections were performed to evaluate associations between putative functional SNPs and cutaneous melanoma disease-specific survival. Receiver operating characteristic curve was constructed, and area under the curve was used to assess the classification performance of the model. RESULTS: Four putative functional SNPs of Notch pathway genes had independent and joint predictive roles in survival of cutaneous melanoma patients. The most significant variant was NCOR2 rs2342924 T>C (adjusted HR, 2.71; 95% confidence interval, 1.73-4.23; Ptrend = 9.62 × 10(-7)), followed by NCSTN rs1124379 G>A, NCOR2 rs10846684 G>A, and MAML2 rs7953425 G>A (Ptrend = 0.005, 0.005, and 0.013, respectively). The receiver operating characteristic analysis revealed that area under the curve was significantly increased after adding the combined unfavorable genotype score to the model containing the known clinicopathologic factors. CONCLUSIONS: Our results suggest that SNPs in Notch pathway genes may be predictors of cutaneous melanoma disease-specific survival. IMPACT: Our discovery offers a translational potential for using genetic variants in Notch pathway genes as a genotype score of biomarkers for developing an improved prognostic assessment and personalized management of cutaneous melanoma patients.

Biogeography in deep time - What do phylogenetics, geology, and paleoclimate tell us about early platyrrhine evolution?

Molecular data have converged on a consensus about the genus-level phylogeny of extant platyrrhine monkeys, but for most extinct taxa and certainly for those older than the Pleistocene we must rely upon morphological evidence from fossils. This raises the question as to how well anatomical data mirror molecular phylogenies and how best to deal with discrepancies between the molecular and morphological data as we seek to extend our phylogenies to the placement of fossil taxa. Here I present parsimony-based phylogenetic analyses of extant and fossil platyrrhines based on an anatomical dataset of 399 dental characters and osteological features of the cranium and postcranium. I sample 16 extant taxa (one from each platyrrhine genus) and 20 extinct taxa of platyrrhines. The tree structure is constrained with a "molecular scaffold" of extant species as implemented in maximum parsimony using PAUP with the molecular-based 'backbone' approach. The data set encompasses most of the known extinct species of platyrrhines, ranging in age from latest Oligocene (∼26 Ma) to the Recent. The tree is rooted with extant catarrhines, and Late Eocene and Early Oligocene African anthropoids. Among the more interesting patterns to emerge are: (1) known early platyrrhines from the Late Oligocene through Early Miocene (26-16.5Ma) represent only stem platyrrhine taxa; (2) representatives of the three living platyrrhine families first occur between 15.7 Ma and 13.5 Ma; and (3) recently extinct primates from the Greater Antilles (Cuba, Jamaica, Hispaniola) are sister to the clade of extant platyrrhines and may have diverged in the Early Miocene. It is probable that the crown platyrrhine clade did not originate before about 20-24 Ma, a conclusion consistent with the phylogenetic analysis of fossil taxa presented here and with recent molecular clock estimates. The following biogeographic scenario is consistent with the phylogenetic findings and climatic and geologic evidence: Tropical South America has been a center for platyrrhine diversification since platyrrhines arrived on the continent in the middle Cenozoic. Platyrrhines dispersed from tropical South America to Patagonia at ∼25-24 Ma via a "Paraná Portal" through eastern South America across a retreating Paranense Sea. Phylogenetic bracketing suggests Antillean primates arrived via a sweepstakes route or island chain from northern South America in the Early Miocene, not via a proposed land bridge or island chain (GAARlandia) in the Early Oligocene (∼34 Ma). Patagonian and Antillean platyrrhines went extinct without leaving living descendants, the former at the end of the Early Miocene and the latter within the past six thousand years. Molecular evidence suggests crown platyrrhines arrived in Central America by crossing an intermittent connection through the Isthmus of Panama at or after 3.5Ma. Any more ancient Central American primates, should they be discovered, are unlikely to have given rise to the extant Central American taxa in situ.

Structured Illumination Microscopy and a Quantitative Image Analysis for the Detection of Positive Margins in a Pre-Clinical Genetically Engineered Mouse Model of Sarcoma.

Intraoperative assessment of surgical margins is critical to ensuring residual tumor does not remain in a patient. Previously, we developed a fluorescence structured illumination microscope (SIM) system with a single-shot field of view (FOV) of 2.1 × 1.6 mm (3.4 mm2) and sub-cellular resolution (4.4 μm). The goal of this study was to test the utility of this technology for the detection of residual disease in a genetically engineered mouse model of sarcoma. Primary soft tissue sarcomas were generated in the hindlimb and after the tumor was surgically removed, the relevant margin was stained with acridine orange (AO), a vital stain that brightly stains cell nuclei and fibrous tissues. The tissues were imaged with the SIM system with the primary goal of visualizing fluorescent features from tumor nuclei. Given the heterogeneity of the background tissue (presence of adipose tissue and muscle), an algorithm known as maximally stable extremal regions (MSER) was optimized and applied to the images to specifically segment nuclear features. A logistic regression model was used to classify a tissue site as positive or negative by calculating area fraction and shape of the segmented features that were present and the resulting receiver operator curve (ROC) was generated by varying the probability threshold. Based on the ROC curves, the model was able to classify tumor and normal tissue with 77% sensitivity and 81% specificity (Youden's index). For an unbiased measure of the model performance, it was applied to a separate validation dataset that resulted in 73% sensitivity and 80% specificity. When this approach was applied to representative whole margins, for a tumor probability threshold of 50%, only 1.2% of all regions from the negative margin exceeded this threshold, while over 14.8% of all regions from the positive margin exceeded this threshold.

Operational scales, sources of finance, and firms’ performance: evidence from Vietnamese longitudinal data

This study investigates a longitudinal dataset consisting of financial and operational data from 37 listed companies listed on Vietnamese stock market, covering the period 2004-13. By performing three main types of regression analysis - pooled OLS, fixed-effect and random-effect regressions - the investigation finds mixed results on the relationships between operational scales, sources of finance and firms' performance, depending on the choice of analytical model and use of independent/dependent variables. In most situation, fixed-effect models appear to be preferable, providing for reasonably consistent results. Toward the end, the paper offers some further explanation about the obtained insights, which reflect the nature of a business environment of a transition economy and an emerging market.

Evaluation of the quality of the management of cancer of the corpus uteri-Selection of relevant quality indicators and implementation in Belgium

Objective Describe the methodology and selection of quality indicators (QI) to be implemented in the EFFECT (EFFectiveness of Endometrial Cancer Treatment) project. EFFECT aims to monitor the variability in Quality of Care (QoC) of uterine cancer in Belgium, to compare the effectiveness of different treatment strategies to improve the QoC and to check the internal validity of the QI to validate the impact of process indicators on outcome. Methods A QI list was retrieved from literature, recent guidelines and QI databases. The Belgian Healthcare Knowledge Center methodology was used for the selection process and involved an expert's panel rating the QI on 4 criteria. The resulting scores and further discussion resulted in a final QI list. An online EFFECT module was developed by the Belgian Cancer Registry including the list of variables required for measuring the QI. Three test phases were performed to evaluate the relevance, feasibility and understanding of the variables and to test the compatibility of the dataset. Results 138 QI were considered for further discussion and 82 QI were eligible for rating. Based on the rating scores and consensus among the expert's panel, 41 QI were considered measurable and relevant. Testing of the data collection enabled optimization of the content and the user-friendliness of the dataset and online module. Conclusions This first Belgian initiative for monitoring the QoC of uterine cancer indicates that the previously used QI selection methodology is reproducible for uterine cancer. The QI list could be applied by other research groups for comparison. © 2013 Elsevier Inc.

Patent litigation in Europe

We compare patent litigation cases across four European jurisdictions – Germany, France, the Netherlands, and the UK – covering cases filed during the period 2000-2008. For our analysis, we assemble a new dataset that contains detailed information at the case, litigant, and patent level for patent cases filed at the major courts in the four jurisdictions. We find substantial differences across jurisdictions in terms of case loads. Courts in Germany hear by far the largest number of cases in absolute terms, but also when taking country size into account. We also find important between-country differences in terms of outcomes, the share of cases that is appealed, as well as the characteristics of litigants and litigated patents. A considerable number of patents are litigated in multiple jurisdictions, but the majority of patents are subject to litigation only in one of the four jurisdictions.

Support vector machines for regression and applications to software quality prediction

Software metrics are the key tool in software quality management. In this paper, we propose to use support vector machines for regression applied to software metrics to predict software quality. In experiments we compare this method with other regression techniques such as Multivariate Linear Regression, Conjunctive Rule and Locally Weighted Regression. Results on benchmark dataset MIS, using mean absolute error, and correlation coefficient as regression performance measures, indicate that support vector machines regression is a promising technique for software quality prediction. In addition, our investigation of PCA based metrics extraction shows that using the first few Principal Components (PC) we can still get relatively good performance.

Modelling pedestrian escalator behaviour

This paper presents an escalator model for use in circulation and evacuation analysis. As part of the model development, human factors data was collected from a Spanish underground station. The collected data relates to: escalator/stair choice, rider/walker preference, rider side preference, walker travel speeds and escalator flow rates. The dataset provides insight into pedestrian behaviour in utilising escalators and is a useful resource for both circulation and evacuation models. Based on insight derived from the dataset a detailed microscopic escalator model which incorporates person-person interactions has been developed. A range of demonstration evacuation scenarios are presented using the newly developed microscopic escalator model.