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Sample records for metolachlor lasso alachlor

  1. Biodegradation of the acetanilide herbicides alachlor, metolachlor, and propachlor.

    Science.gov (United States)

    Stamper, D M; Tuovinen, O H

    1998-01-01

    Alachlor, metolachlor, and propachlor are detoxified in biological systems by the formation of glutathione-acetanilide conjugates. This conjugation is mediated by glutathione-S-transferase, which is present in microorganisms, plants, and mammals. Other organic sulfides and inorganic sulfide also react through a nucleophilic attack on the 2-chloro group of acetanilide herbicides, but the products are only partially characterized. Sorption in soils and sediments is an important factor controlling the migration and bioavailability of these herbicides, while microbial degradation is the most important factor in determining their overall fate in the environment. The biodegradation of alachlor and metolachlor is proposed to be only partial and primarily cometabolic, and the ring cleavage seems to be slow or insignificant. Propachlor biodegradation has been reported to proceed to substantial (> 50%) mineralization of the ring structure. Reductive dechlorination may be one of the initial breakdown mechanisms under anaerobic conditions. Aerobic and anaerobic transformation products vary in their polarity and therefore in soil binding coefficient. A catabolic pathway for chloroacetanilide herbicides has not been presented in the literature because of the lack of mineralization data under defined cultural conditions.

  2. Effects of Alachlor and Metolachlor on Microbial Populations in the Soil

    Directory of Open Access Journals (Sweden)

    Ismail, B. S.

    2005-01-01

    Full Text Available A study of the impact of two acetanilide herbicides, viz. alachlor and metolachlor on bacterial and fungal populations and biomass in the Sungai Buluh soil series samples was carried out under laboratory conditions. The effects of the two herbicides were monitored for 70 days under ambient conditions. Metolachlor caused greater reduction in bacterial counts than on fungal populations. There was approximately 75% reduction in bacterial counts 14 days after treatment (DAT with 2 µg/g metolachlor. Alachlor however was less toxic to bacterial and fungal populations. Alachlor caused a reduction in bacterial counts at 7 and 14 DAT with 2µg/g or above. Fungal population decreased significantly in the presence of 20 µg/g alachlor at 7 DAT but no further effects were observed as the incubation period was prolonged. The study showed that the microbial biomass immediately decreased significantly in the presence of 2 µg/g or more of metolachlor at 0 and 28 DAT. Alachlor, on the other hands, at the lowest experimental dose of 2 µg/g reduced the microbial biomass almost immediately upon incubation, but had no further effects when the incubation period was prolonged.

  3. Comparative sensitivity of five species of macrophytes and six species of algae to atrazine, metribuzin, alachlor, and metolachlor

    Science.gov (United States)

    Fairchild, James F.; Ruessler, Shane; Carlson, A. Ron

    1998-01-01

    This study determined the relative sensitivity of five species of aquatic macrophytes and six species of algae to four commonly used herbicides (atrazine, metribuzin, alachlor, and metolachlor). Toxicity tests consisted of 96-h (duckweed and algae) or 14-d (submerged macrophytes) static exposures. The triazine herbicides (atrazine and metribuzin) were significantly more toxic to aquatic plants than were the acetanilide herbicides (alachlor and metolachlor). Toxicity studies ranked metribuzin > atrazine > alachlor > metolachlor in decreasing order of overall toxicity to aquatic plants. Relative sensitivities of macrophytes to these herbicides decreased in the order of Ceratophyllum > Najas > Elodea > Lemna > Myriophyllum. Relative sensitivities of algae to herbicides decreased in the order of Selenastrum > Chlorella > Chlamydomonas > Microcystis > Scenedesmus > Anabaena. Algae and macrophytes were of similar overall sensitivities to herbicides. Data indicated that Selenastrum, a commonly tested green alga, was generally more sensitive compared to other plant species. Lemna minor, a commonly tested floating vascular plant, was of intermediate sensitivity, and was fivefold less sensitive than Ceratophyllum, which was the most sensitive species tested. The results indicated that no species was consistently most sensitive, and that a suite of aquatic plant test species may be needed to perform accurate risk assessments of herbicides.

  4. Leaching of Br-, metolachlor, alachlor, atrazine, deethylatrazine and deisopropylatrazine in clayey vadoze zone: a field scale experiment in north-east Greece.

    Science.gov (United States)

    Vryzas, Zisis; Papadakis, Emmanuel Nikolaos; Papadopoulou-Mourkidou, E

    2012-04-15

    An extensive four-year research program has been carried out to explore and acquire knowledge about the fundamental agricultural practices and processes affecting the mobility and bioavailability of pesticides in soils under semi-arid Mediterranean conditions. Pesticide leaching was studied under field conditions at five different depths using suction cups. Monitoring of metolachlor, alachlor, atrazine, deethylatrazine (DEA), deisopropylatrazine (DIA), and bromide ions in soil water, as well as dye patterns made apparent the significant role of preferential flow to the mobility of the studied compounds. Irrespective to their adsorption capacities and degradation rates, atrazine, metolachlor and bromide ions were simultaneously detected to 160 cm depth. Following 40 mm irrigation, just after their application, both alachlor and atrazine were leached to 160 cm depth within 18 h, giving maximum concentrations of 211 and 199 μg L(-1), respectively. Metolachlor was also detected in all depth when its application was followed by a rainfall event (50 mm) two weeks after its application. The greatest concentrations of atrazine, alachlor and metolachlor in soil water were 1795, 1166 and 845 μg L(-1), respectively. The greatest concentrations of atrazine's degradation products (both DEA and DIA) appeared later in the season compared to the parent compound. Metolachlor exhibited the greatest persistence with concentrations up to 10 μg L(-1) appearing in soil water 18 months after its application. Brilliant blue application followed by 40 mm irrigation clearly depict multi-branching network of preferential flow paths allowing the fast flow of the dye down to 150 cm within 24 h. This network was created by soil cracks caused by shrinking of dry soils, earthworms and plant roots. Chromatographic flow of the stained soil solution was evident only in the upper 10-15 cm of soil. Copyright © 2012 Elsevier Ltd. All rights reserved.

  5. METHOD DEVELOPMENT FOR ALACHLOR ESA AND OTHER ACENTANILIDE HERBICIDE DEGRADATION PRODUCTS

    Science.gov (United States)

    Introduction: Acetanilide herbicides are frequently applied in the U.S. on crops (corn, soybeans, popcorn, etc.) to control broadleaf and annual weeds. The acetanilide and acetamide herbicides currently registered for use in the U.S. are alachlor, acetochlor, metolachlor, propa...

  6. Introduction to the LASSO

    Indian Academy of Sciences (India)

    the LASSO method as a constrained quadratic programming prob- lem, and ... solve the LASSO problem. We also ... The problem (2) is equivalent to the best subset selection. .... erator (LASSO), which is based on the following key concepts:.

  7. When Is Network Lasso Accurate?

    Directory of Open Access Journals (Sweden)

    Alexander Jung

    2018-01-01

    Full Text Available The “least absolute shrinkage and selection operator” (Lasso method has been adapted recently for network-structured datasets. In particular, this network Lasso method allows to learn graph signals from a small number of noisy signal samples by using the total variation of a graph signal for regularization. While efficient and scalable implementations of the network Lasso are available, only little is known about the conditions on the underlying network structure which ensure network Lasso to be accurate. By leveraging concepts of compressed sensing, we address this gap and derive precise conditions on the underlying network topology and sampling set which guarantee the network Lasso for a particular loss function to deliver an accurate estimate of the entire underlying graph signal. We also quantify the error incurred by network Lasso in terms of two constants which reflect the connectivity of the sampled nodes.

  8. Photochemical degradation of alachlor in water

    Directory of Open Access Journals (Sweden)

    Tajana Đurkić

    2017-01-01

    Full Text Available This study investigates the photochemical degradation of alachlor, a chloroacetanilide herbicide. All experiments were conducted in ultra-pure deionized water (ASTM Type I quality using direct ultraviolet (UV photolysis and the UV/H2O2 advanced oxidation process. The direct UV photolysis and UV/H2O2 experiments were conducted in a commercial photochemical reactor with a quartz reaction vessel equipped with a 253.7 nm UV low pressure mercury lamp (Philips TUV 16 W. The experimental results demonstrate that UV photolysis was very effective for alachlor degradation (up to 97% removal using a high UV fluence of 4200 mJ/cm2. The UV/H2O2 process promoted alachlor degradation compared to UV photolysis alone, with a high degree of decomposition (97% achieved at a significantly lower UV fluence of 600 mJ/cm2 when combined with 1 mg H2O2/L. The application of UV photolysis alone with a UV fluence of 600 mJ/cm2 gave a negligible 4% alachlor degradation. The photo degradation of alachlor, in both direct UV photolysis and the UV/H2O2 process, followed pseudo first-order kinetics. The degradation rate constant was about 6 times higher for the UV/H2O2 process than for UV photolysis alone.

  9. The Bayesian Covariance Lasso.

    Science.gov (United States)

    Khondker, Zakaria S; Zhu, Hongtu; Chu, Haitao; Lin, Weili; Ibrahim, Joseph G

    2013-04-01

    Estimation of sparse covariance matrices and their inverse subject to positive definiteness constraints has drawn a lot of attention in recent years. The abundance of high-dimensional data, where the sample size ( n ) is less than the dimension ( d ), requires shrinkage estimation methods since the maximum likelihood estimator is not positive definite in this case. Furthermore, when n is larger than d but not sufficiently larger, shrinkage estimation is more stable than maximum likelihood as it reduces the condition number of the precision matrix. Frequentist methods have utilized penalized likelihood methods, whereas Bayesian approaches rely on matrix decompositions or Wishart priors for shrinkage. In this paper we propose a new method, called the Bayesian Covariance Lasso (BCLASSO), for the shrinkage estimation of a precision (covariance) matrix. We consider a class of priors for the precision matrix that leads to the popular frequentist penalties as special cases, develop a Bayes estimator for the precision matrix, and propose an efficient sampling scheme that does not precalculate boundaries for positive definiteness. The proposed method is permutation invariant and performs shrinkage and estimation simultaneously for non-full rank data. Simulations show that the proposed BCLASSO performs similarly as frequentist methods for non-full rank data.

  10. Degradation of alachlor in aqueous solution by using hydrodynamic cavitation.

    Science.gov (United States)

    Wang, Xikui; Zhang, Yong

    2009-01-15

    The degradation of alachlor aqueous solution by using hydrodynamic cavitation was systematically investigated. It was found that alachlor in aqueous solution can be deomposed with swirling jet-induced cavitation. The degradation can be described by a pseudo-first-order kinetics and the degradation rate was found to be 4.90x10(-2)min(-1). The effects of operating parameters such as fluid pressure, solution temperature, initial concentration of alachlor and medium pH on the degradation rates of alachlor were also discussed. The results showed that the degradation rates of alachlor increased with increasing pressure and decreased with increasing initial concentration. An optimum temperature of 40 degrees C existed for the degradation rate of alachlor and the degradation rate was also found to be slightly depend on medium pH. Many degradation products formed during the process, and some of them were qualitatively identified by GC-MS.

  11. Variable selection by lasso-type methods

    Directory of Open Access Journals (Sweden)

    Sohail Chand

    2011-09-01

    Full Text Available Variable selection is an important property of shrinkage methods. The adaptive lasso is an oracle procedure and can do consistent variable selection. In this paper, we provide an explanation that how use of adaptive weights make it possible for the adaptive lasso to satisfy the necessary and almost sufcient condition for consistent variable selection. We suggest a novel algorithm and give an important result that for the adaptive lasso if predictors are normalised after the introduction of adaptive weights, it makes the adaptive lasso performance identical to the lasso.

  12. Pierced Lasso Proteins

    Science.gov (United States)

    Jennings, Patricia

    Entanglement and knots are naturally occurring, where, in the microscopic world, knots in DNA and homopolymers are well characterized. The most complex knots are observed in proteins which are harder to investigate, as proteins are heteropolymers composed of a combination of 20 different amino acids with different individual biophysical properties. As new-knotted topologies and new proteins containing knots continue to be discovered and characterized, the investigation of knots in proteins has gained intense interest. Thus far, the principle focus has been on the evolutionary origin of tying a knot, with questions of how a protein chain `self-ties' into a knot, what the mechanism(s) are that contribute to threading, and the biological relevance and functional implication of a knotted topology in vivo gaining the most insight. Efforts to study the fully untied and unfolded chain indicate that the knot is highly stable, remaining intact in the unfolded state orders of magnitude longer than first anticipated. The persistence of ``stable'' knots in the unfolded state, together with the challenge of defining an unfolded and untied chain from an unfolded and knotted chain, complicates the study of fully untied protein in vitro. Our discovery of a new class of knotted proteins, the Pierced Lassos (PL) loop topology, simplifies the knotting approach. While PLs are not easily recognizable by the naked eye, they have now been identified in many proteins in the PDB through the use of computation tools. PL topologies are diverse proteins found in all kingdoms of life, performing a large variety of biological responses such as cell signaling, immune responses, transporters and inhibitors (http://lassoprot.cent.uw.edu.pl/). Many of these PL topologies are secreted proteins, extracellular proteins, as well as, redox sensors, enzymes and metal and co-factor binding proteins; all of which provide a favorable environment for the formation of the disulphide bridge. In the PL

  13. Efficient methods for overlapping group lasso.

    Science.gov (United States)

    Yuan, Lei; Liu, Jun; Ye, Jieping

    2013-09-01

    The group Lasso is an extension of the Lasso for feature selection on (predefined) nonoverlapping groups of features. The nonoverlapping group structure limits its applicability in practice. There have been several recent attempts to study a more general formulation where groups of features are given, potentially with overlaps between the groups. The resulting optimization is, however, much more challenging to solve due to the group overlaps. In this paper, we consider the efficient optimization of the overlapping group Lasso penalized problem. We reveal several key properties of the proximal operator associated with the overlapping group Lasso, and compute the proximal operator by solving the smooth and convex dual problem, which allows the use of the gradient descent type of algorithms for the optimization. Our methods and theoretical results are then generalized to tackle the general overlapping group Lasso formulation based on the l(q) norm. We further extend our algorithm to solve a nonconvex overlapping group Lasso formulation based on the capped norm regularization, which reduces the estimation bias introduced by the convex penalty. We have performed empirical evaluations using both a synthetic and the breast cancer gene expression dataset, which consists of 8,141 genes organized into (overlapping) gene sets. Experimental results show that the proposed algorithm is more efficient than existing state-of-the-art algorithms. Results also demonstrate the effectiveness of the nonconvex formulation for overlapping group Lasso.

  14. Description of the LASSO Alpha 2 Release

    Energy Technology Data Exchange (ETDEWEB)

    Gustafson, William I. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Vogelmann, Andrew M. [Brookhaven National Lab. (BNL), Upton, NY (United States); Cheng, Xiaoping [Univ. of California, Los Angeles, CA (United States); Endo, Satoshi [Brookhaven National Lab. (BNL), Upton, NY (United States); Krishna, Bhargavi [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Li, Z. [Univ. of California, Los Angeles, CA (United States); Toto, Tami [Brookhaven National Lab. (BNL), Upton, NY (United States); Xiao, H. [Univ. of California, Los Angeles, CA (United States)

    2017-09-01

    The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility began a pilot project in May 2015 to design a routine, high-resolution modeling capability to complement ARM’s extensive suite of measurements. This modeling capability has been named the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project. The initial focus of LASSO is on shallow convection at the ARM Southern Great Plains (SGP) Climate Research Facility. The availability of LES simulations with concurrent observations will serve many purposes. LES helps bridge the scale gap between DOE ARM observations and models, and the use of routine LES adds value to observations. It provides a self-consistent representation of the atmosphere and a dynamical context for the observations. Further, it elucidates unobservable processes and properties. LASSO will generate a simulation library for researchers that enables statistical approaches beyond a single-case mentality. It will also provide tools necessary for modelers to reproduce the LES and conduct their own sensitivity experiments. Many different uses are envisioned for the combined LASSO LES and observational library. For an observationalist, LASSO can help inform instrument remote sensing retrievals, conduct Observation System Simulation Experiments (OSSEs), and test implications of radar scan strategies or flight paths. For a theoretician, LASSO will help calculate estimates of fluxes and co-variability of values, and test relationships without having to run the model yourself. For a modeler, LASSO will help one know ahead of time which days have good forcing, have co-registered observations at high-resolution scales, and have simulation inputs and corresponding outputs to test parameterizations. Further details on the overall LASSO project are available at https://www.arm.gov/capabilities/modeling/lasso.

  15. Oracle Efficient Estimation and Forecasting with the Adaptive LASSO and the Adaptive Group LASSO in Vector Autoregressions

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl; Callot, Laurent

    We show that the adaptive Lasso (aLasso) and the adaptive group Lasso (agLasso) are oracle efficient in stationary vector autoregressions where the number of parameters per equation is smaller than the number of observations. In particular, this means that the parameters are estimated consistently...

  16. Description of the LASSO Alpha 1 Release

    Energy Technology Data Exchange (ETDEWEB)

    Gustafson, William I. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Vogelmann, Andrew M. [Brookhaven National Lab. (BNL), Upton, NY (United States); Cheng, Xiaoping [Univ. of California, Los Angeles, CA (United States); Endo, Satoshi [Brookhaven National Lab. (BNL), Upton, NY (United States); Krishna, Bhargavi [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Li, Zhijin [Univ. of California, Los Angeles, CA (United States); Toto, Tami [Brookhaven National Lab. (BNL), Upton, NY (United States); Xiao, H [Univ. of California, Los Angeles, CA (United States)

    2017-07-31

    The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility began a pilot project in May 2015 to design a routine, high-resolution modeling capability to complement ARM’s extensive suite of measurements. This modeling capability has been named the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project. The availability of LES simulations with concurrent observations will serve many purposes. LES helps bridge the scale gap between DOE ARM observations and models, and the use of routine LES adds value to observations. It provides a self-consistent representation of the atmosphere and a dynamical context for the observations. Further, it elucidates unobservable processes and properties. LASSO will generate a simulation library for researchers that enables statistical approaches beyond a single-case mentality. It will also provide tools necessary for modelers to reproduce the LES and conduct their own sensitivity experiments. Many different uses are envisioned for the combined LASSO LES and observational library. For an observationalist, LASSO can help inform instrument remote-sensing retrievals, conduct Observation System Simulation Experiments (OSSEs), and test implications of radar scan strategies or flight paths. For a theoretician, LASSO will help calculate estimates of fluxes and co-variability of values, and test relationships without having to run the model yourself. For a modeler, LASSO will help one know ahead of time which days have good forcing, have co-registered observations at high-resolution scales, and have simulation inputs and corresponding outputs to test parameterizations. Further details on the overall LASSO project are available at http://www.arm. gov/science/themes/lasso.

  17. Toxicity of three selected pesticides (Alachlor, Atrazine and Diuron ...

    African Journals Online (AJOL)

    The present study aimed to evaluate acute toxicity tests for three selected herbicides: Alachlor, Atrazine and Diuron using turbot flatfish. Larvae were more sensitive than turbot embryos to all pesticides. Median lethal concentrations of the selected pesticides during a 48 h and 96 h exposure for turbot embryos and larvae ...

  18. Bioadsorber efficiency, design, and performance forecasting for alachlor removal.

    Science.gov (United States)

    Badriyha, Badri N; Ravindran, Varadarajan; Den, Walter; Pirbazari, Massoud

    2003-10-01

    This study discusses a mathematical modeling and design protocol for bioactive granular activated carbon (GAC) adsorbers employed for purification of drinking water contaminated by chlorinated pesticides, exemplified by alachlor. A thin biofilm model is discussed that incorporates the following phenomenological aspects: film transfer from the bulk fluid to the adsorbent particles, diffusion through the biofilm immobilized on adsorbent surface, adsorption of the contaminant into the adsorbent particle. The modeling approach involved independent laboratory-scale experiments to determine the model input parameters. These experiments included adsorption isotherm studies, adsorption rate studies, and biokinetic studies. Bioactive expanded-bed adsorber experiments were conducted to obtain realistic experimental data for determining the ability of the model for predicting adsorber dynamics under different operating conditions. The model equations were solved using a computationally efficient hybrid numerical technique combining orthogonal collocation and finite difference methods. The model provided accurate predictions of adsorber dynamics for bioactive and non-bioactive scenarios. Sensitivity analyses demonstrated the significance of various model parameters, and focussed on enhancement in certain key parameters to improve the overall process efficiency. Scale-up simulation studies for bioactive and non-bioactive adsorbers provided comparisons between their performances, and illustrated the advantages of bioregeneration for enhancing their effective service life spans. Isolation of microbial species revealed that fungal strains were more efficient than bacterial strains in metabolizing alachlor. Microbial degradation pathways for alachlor were proposed and confirmed by the detection of biotransformation metabolites and byproducts using gas chromatography/mass spectrometry.

  19. Efficient Smoothed Concomitant Lasso Estimation for High Dimensional Regression

    Science.gov (United States)

    Ndiaye, Eugene; Fercoq, Olivier; Gramfort, Alexandre; Leclère, Vincent; Salmon, Joseph

    2017-10-01

    In high dimensional settings, sparse structures are crucial for efficiency, both in term of memory, computation and performance. It is customary to consider ℓ 1 penalty to enforce sparsity in such scenarios. Sparsity enforcing methods, the Lasso being a canonical example, are popular candidates to address high dimension. For efficiency, they rely on tuning a parameter trading data fitting versus sparsity. For the Lasso theory to hold this tuning parameter should be proportional to the noise level, yet the latter is often unknown in practice. A possible remedy is to jointly optimize over the regression parameter as well as over the noise level. This has been considered under several names in the literature: Scaled-Lasso, Square-root Lasso, Concomitant Lasso estimation for instance, and could be of interest for uncertainty quantification. In this work, after illustrating numerical difficulties for the Concomitant Lasso formulation, we propose a modification we coined Smoothed Concomitant Lasso, aimed at increasing numerical stability. We propose an efficient and accurate solver leading to a computational cost no more expensive than the one for the Lasso. We leverage on standard ingredients behind the success of fast Lasso solvers: a coordinate descent algorithm, combined with safe screening rules to achieve speed efficiency, by eliminating early irrelevant features.

  20. Efeito de fatores ambientais sobre a seletividade do alachlor ao algodoeiro Effect of environmental factors on the selectivity of alachlor to cotton

    Directory of Open Access Journals (Sweden)

    S.C. Guimarães

    2007-12-01

    Full Text Available Cotonicultores do cerrado, receosos da ocorrência de fitotoxicidade, têm utilizado o herbicida alachlor em dosagens inferiores à mínima recomendada na bula, com baixo efeito residual. Com o objetivo de estudar fatores relacionados à seletividade do alachlor ao algodoeiro, foram realizados dois experimentos. No primeiro, em caixas de germinação com substrato areia, foi estudado o herbicida alachlor em dois níveis (sem alachlor e na dose de 96 µg kg-1 de substrato, em ambientes compostos pela combinação das temperaturas de 20, 25, 30 e 35 ºC com três níveis de umidade no substrato (40, 60 e 80% da capacidade de retenção de água. A avaliação foi realizada aos 10 dias. As condições do ambiente influenciaram o crescimento das plântulas, mas essa resposta foi reduzida ou anulada na presença do alachlor; quanto mais favoráveis as condições, proporcionalmente maiores foram as reduções. O herbicida reduziu características da parte aérea e, em maior intensidade, o comprimento das raízes. No segundo ensaio, em vasos com solo, foram estudados três tratamentos de irrigação (23, 34 e 45 mm após aplicação de dois níveis de alachlor (0 e 2,88 kg ha-1. A avaliação foi realizada aos 21 dias. Maiores níveis de irrigação causaram redução na matéria fresca e seca das raízes. O alachlor reduziu todas as variáveis medidas na parte aérea das plantas, mas, de modo geral, esse efeito foi de baixa intensidade e ocorreu de maneira semelhante nos níveis de irrigação. A independência dos efeitos entre alachlor e irrigação não corroboraram a premissa de que maiores níveis de água aumentariam a lixiviação do herbicida e a fitotoxicidade ao algodoeiro.Brazilian savanna cotton growers in fear of phytotoxicity have been using the herbicide alachlor below the minimum dosage recommended by the manufacturer, with low residual activity. Two experiments were carried out to study factors related to alachlor selectivity to

  1. Dissipation and leaching of pyroxasulfone and s-metolachlor

    Science.gov (United States)

    Pyroxasulfone dissipation and mobility in the soil was evaluated and compared to S-metolachlor in 2009 and 2010 at two field sites in northern Colorado, on a Nunn fine clay loam, and Olney fine sandy loam soil. Pyroxasulfone dissipation half-life (DT50) values varied from 47 to 134 d, and those of S...

  2. 77 FR 48902 - S-Metolachlor; Pesticide Tolerances

    Science.gov (United States)

    2012-08-15

    ... fate/transport characteristics of S-metolachlor. Further information regarding EPA drinking water... for which there is reliable information.'' This includes exposure through drinking water and in... information from the United States Department of Agriculture's (USDA) Nationwide Continuing Surveys of Food...

  3. Gamma radiolysis of alachlor aqueous solutions in the presence of hydrogen peroxide

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Dongkyu; Lee, O-Mi; Yu, Seungho [Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute, Jeongeup 580-185 (Korea, Republic of); Jeong, Seung-Woo, E-mail: swjeong@kunsan.ac.kr [Department of Environmental Engineering, Kunsan National University, Kunsan 573-701 (Korea, Republic of)

    2010-12-15

    The enhanced effect of gamma irradiation with hydrogen peroxide (H{sub 2}O{sub 2}) for alachlor degradation in an aqueous solution was first investigated in this study. The combination of gamma irradiation and H{sub 2}O{sub 2} led to an enhanced effect, which remarkably increased the degradation efficiency of alachlor and the total organic carbon (TOC) removal. At a dose of 200 Gy, the degradation degree of the alachlor solution reached 81.7 and 99.2% under H{sub 2}O{sub 2} concentrations of 0 and 0.1 {mu}M, respectively. In addition, the TOC removal efficiencies of the alachlor under initial H{sub 2}O{sub 2} concentrations of 0, 0.5 and 1.0 {mu}M were 59.5, 74.8 and 83.8%, respectively, at an absorbed dose of 20 kGy. However, for higher H{sub 2}O{sub 2} concentrations (greater than 1 {mu}M), the alachlor degradation was reduced because {center_dot}OH radicals were scavenged by the H{sub 2}O{sub 2}. The biodegradability of alachlor solutions prior to and after treatment by gamma irradiation was also assessed using the Closed Bottle Test (CBT). The results showed enhanced biodegradability of alachlor with increasing absorbed doses.

  4. Gamma radiolysis of alachlor aqueous solutions in the presence of hydrogen peroxide

    International Nuclear Information System (INIS)

    Choi, Dongkyu; Lee, O-Mi; Yu, Seungho; Jeong, Seung-Woo

    2010-01-01

    The enhanced effect of gamma irradiation with hydrogen peroxide (H 2 O 2 ) for alachlor degradation in an aqueous solution was first investigated in this study. The combination of gamma irradiation and H 2 O 2 led to an enhanced effect, which remarkably increased the degradation efficiency of alachlor and the total organic carbon (TOC) removal. At a dose of 200 Gy, the degradation degree of the alachlor solution reached 81.7 and 99.2% under H 2 O 2 concentrations of 0 and 0.1 μM, respectively. In addition, the TOC removal efficiencies of the alachlor under initial H 2 O 2 concentrations of 0, 0.5 and 1.0 μM were 59.5, 74.8 and 83.8%, respectively, at an absorbed dose of 20 kGy. However, for higher H 2 O 2 concentrations (greater than 1 μM), the alachlor degradation was reduced because ·OH radicals were scavenged by the H 2 O 2 . The biodegradability of alachlor solutions prior to and after treatment by gamma irradiation was also assessed using the Closed Bottle Test (CBT). The results showed enhanced biodegradability of alachlor with increasing absorbed doses.

  5. ANALYTICAL METHOD DEVELOPMENT FOR ALACHLOR ESA AND OTHER ACETANILIDE HERBICIDE DEGRADATION PRODUCTS

    Science.gov (United States)

    In 1998, USEPA published a Drinking Water Contaminant Candidate List (CCL) of 50 chemicals and 10 microorganisms. "Alachlor ESA and other acetanilide herbicide degradation products" is listed on the the 1998 CCL. Acetanilide degradation products are generally more water soluble...

  6. Sparse inverse covariance estimation with the graphical lasso.

    Science.gov (United States)

    Friedman, Jerome; Hastie, Trevor; Tibshirani, Robert

    2008-07-01

    We consider the problem of estimating sparse graphs by a lasso penalty applied to the inverse covariance matrix. Using a coordinate descent procedure for the lasso, we develop a simple algorithm--the graphical lasso--that is remarkably fast: It solves a 1000-node problem ( approximately 500,000 parameters) in at most a minute and is 30-4000 times faster than competing methods. It also provides a conceptual link between the exact problem and the approximation suggested by Meinshausen and Bühlmann (2006). We illustrate the method on some cell-signaling data from proteomics.

  7. Fused Adaptive Lasso for Spatial and Temporal Quantile Function Estimation

    KAUST Repository

    Sun, Ying; Wang, Huixia J.; Fuentes, Montserrat

    2015-01-01

    and temporal data with a fused adaptive Lasso penalty to accommodate the dependence in space and time. This method penalizes the difference among neighboring quantiles, hence it is desirable for applications with features ordered in time or space without

  8. Recommendations for the Implementation of the LASSO Workflow

    Energy Technology Data Exchange (ETDEWEB)

    Gustafson, William I [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Vogelmann, Andrew M [Brookhaven National Lab. (BNL), Upton, NY (United States); Cheng, Xiaoping [National University of Defense Technology, China; Endo, Satoshi [Brookhaven National Lab. (BNL), Upton, NY (United States); Krishna, Bhargavi [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Li, Zhijin [California Inst. of Technology (CalTech), La Canada Flintridge, CA (United States). Jet Propulsion Lab.; University of California, Los Angeles; Toto, Tami [Brookhaven National Lab. (BNL), Upton, NY (United States); Xiao, Heng [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2017-11-15

    The U. S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Research Fa-cility began a pilot project in May 2015 to design a routine, high-resolution modeling capability to complement ARM’s extensive suite of measurements. This modeling capability, envisioned in the ARM Decadal Vision (U.S. Department of Energy 2014), subsequently has been named the Large-Eddy Simu-lation (LES) ARM Symbiotic Simulation and Observation (LASSO) project, and it has an initial focus of shallow convection at the ARM Southern Great Plains (SGP) atmospheric observatory. This report documents the recommendations resulting from the pilot project to be considered by ARM for imple-mentation into routine operations. During the pilot phase, LASSO has evolved from the initial vision outlined in the pilot project white paper (Gustafson and Vogelmann 2015) to what is recommended in this report. Further details on the overall LASSO project are available at https://www.arm.gov/capabilities/modeling/lasso. Feedback regarding LASSO and the recommendations in this report can be directed to William Gustafson, the project principal investigator (PI), and Andrew Vogelmann, the co-principal investigator (Co-PI), via lasso@arm.gov.

  9. Bayesian LASSO, scale space and decision making in association genetics.

    Science.gov (United States)

    Pasanen, Leena; Holmström, Lasse; Sillanpää, Mikko J

    2015-01-01

    LASSO is a penalized regression method that facilitates model fitting in situations where there are as many, or even more explanatory variables than observations, and only a few variables are relevant in explaining the data. We focus on the Bayesian version of LASSO and consider four problems that need special attention: (i) controlling false positives, (ii) multiple comparisons, (iii) collinearity among explanatory variables, and (iv) the choice of the tuning parameter that controls the amount of shrinkage and the sparsity of the estimates. The particular application considered is association genetics, where LASSO regression can be used to find links between chromosome locations and phenotypic traits in a biological organism. However, the proposed techniques are relevant also in other contexts where LASSO is used for variable selection. We separate the true associations from false positives using the posterior distribution of the effects (regression coefficients) provided by Bayesian LASSO. We propose to solve the multiple comparisons problem by using simultaneous inference based on the joint posterior distribution of the effects. Bayesian LASSO also tends to distribute an effect among collinear variables, making detection of an association difficult. We propose to solve this problem by considering not only individual effects but also their functionals (i.e. sums and differences). Finally, whereas in Bayesian LASSO the tuning parameter is often regarded as a random variable, we adopt a scale space view and consider a whole range of fixed tuning parameters, instead. The effect estimates and the associated inference are considered for all tuning parameters in the selected range and the results are visualized with color maps that provide useful insights into data and the association problem considered. The methods are illustrated using two sets of artificial data and one real data set, all representing typical settings in association genetics.

  10. Analysis of metolachlor ethane sulfonic acid chirality in groundwater: A tool for dating groundwater movement in agricultural settings

    Science.gov (United States)

    Chemical chirality of pesticides can be a useful tool for studying environmental processes. The chiral forms of metolachlor ethane sulfonic acid (MESA), an abundant metabolite of metolachlor, and metolachlor were examined over a 6 year period in groundwater and a groundwater-fed stream in a riparia...

  11. Comparative responses of two species of marine phytoplankton to metolachlor exposure

    International Nuclear Information System (INIS)

    Thakkar, Megha; Randhawa, Varunpreet; Wei Liping

    2013-01-01

    Metolachlor, a chloroacetanilide herbicide, has been frequently detected in coastal waters. This study examined the growth, photosynthesis, and detoxification responses of chlorophyte Dunaliella tertiolecta (DT) and brown tide alga Aureococcus anophagefferens (AA) upon 5-day exposure to 0.5–5 mg L −1 metolachlor. Growth was assessed with exponential growth rate, and 5th day in vivo chlorophyll fluorescence, chlorophyll a, b or c, cell density and cell size. The photosynthesis function was assessed with photochemical parameters of photosystem II (PSII) during the mid-exponential growth phase (i.e. 2–4 day metolachlor exposure). The biochemical detoxification was analyzed with glutathione production and metolachlor degradation. Results show that metolachlor caused up to ∼9% inhibition in growth rate in both species and an expected ∼35% and 25% inhibition in chlorophyll based endpoints in DT and AA respectively. DT had an up to 70% inhibition in cell density, but AA a 35% hormesis at 1 mg L −1 metolachlor and no significant inhibition, as compared to the controls. Both DT and AA's cell sizes were enlarged by metolachlor exposure, but greater in DT (1.2% per mg L −1 ) than in AA (0.68% per mg L −1 ). On PSII photochemistry, maximum quantum yield was not affected in both species; PSII optical cross section and connectivity factor increased in DT but decreased in AA, suggesting species specific impact on PSII function. On detoxification responses, glutathione production, when normalized to total chlorophyll a, was not affected by metolachlor in both species; further, despite of heterotrophic capacity of A. anophagefferens metolachlor was not significantly degraded by this alga during the 5-day incubation. The species specific effects on algal growth have ecological implications of potential selective inhibition of chlorophytes by metolachlor herbicide.

  12. Lasso and probabilistic inequalities for multivariate point processes

    DEFF Research Database (Denmark)

    Hansen, Niels Richard; Reynaud-Bouret, Patricia; Rivoirard, Vincent

    2015-01-01

    Due to its low computational cost, Lasso is an attractive regularization method for high-dimensional statistical settings. In this paper, we consider multivariate counting processes depending on an unknown function parameter to be estimated by linear combinations of a fixed dictionary. To select...... for multivariate Hawkes processes are proven, which allows us to check these assumptions by considering general dictionaries based on histograms, Fourier or wavelet bases. Motivated by problems of neuronal activity inference, we finally carry out a simulation study for multivariate Hawkes processes and compare our...... methodology with the adaptive Lasso procedure proposed by Zou in (J. Amer. Statist. Assoc. 101 (2006) 1418–1429). We observe an excellent behavior of our procedure. We rely on theoretical aspects for the essential question of tuning our methodology. Unlike adaptive Lasso of (J. Amer. Statist. Assoc. 101 (2006...

  13. Effects of alachlor on the early development and induction of estrogen-responsive genes in Medaka, Oryzias latipes

    Energy Technology Data Exchange (ETDEWEB)

    Lee, C.; Ryu, J.; Park, S.Y.; Choi, K.; Jeon, S.H.; Na, J.G.; Rhee, D.G. [National Inst. of Environmental Research, Incheon (Korea)

    2004-09-15

    Alachlor is an acetanilide herbicide used to control annual grasses and weeds in field corn, soybeans, and peanuts. It is a selective systemic herbicide, absorbed by germinating shoots and by roots. Although the specific pathways are not exactly understood, the acetanilide herbicides apparently interfere with several physiological processes including biosynthesis of lipids, proteins and flavonoids. These herbicides are widely used in agriculture and are commonly detected in surface water and groundwater. Alachlor has a relatively low acute toxicity, however, repeated exposure has been reported to cause hepatotoxicity, irreversible uveal degeneration and tumour formation in some animals. Besides alachlor is one of the herbicides reported to have endocrine disrupting effects. 2,4-D, 2,4,5-T, amitrole and atrazine also belong to these types of herbicides. Alachlor is a strongly suspected endocrine disruptor in that it is listed by EPA and the World Wildlife Fund [WWF] as a potential endocrine disrupting chemical. Many mammalian and aquatic toxicological studies with alachlor were performed under the conditions of acute, subacute and chronic experiment. However, not many studies using fish have been carried out with the purpose of screening and testing of endocrine disrupting effects of alachlor. The purpose of this study was to determine the effects of alachlor on the early morphological development of medaka (Oryzias latipes). Embryonic growth, deformation and hatching success were determined to see the effects of this chemical. Also, we tried to measure the estrogenic activity of alachlor using the ELISA and RT-PCR methods. By using these techniques, we evaluated the induction of the estrogen-responsive genes, vitellogenin (precursor of yolk protein) and choriogenin (precursor of egg envelope protein) in male medaka exposed to alachlor.

  14. The Los Alamos Space Science Outreach (LASSO) Program

    Science.gov (United States)

    Barker, P. L.; Skoug, R. M.; Alexander, R. J.; Thomsen, M. F.; Gary, S. P.

    2002-12-01

    The Los Alamos Space Science Outreach (LASSO) program features summer workshops in which K-14 teachers spend several weeks at LANL learning space science from Los Alamos scientists and developing methods and materials for teaching this science to their students. The program is designed to provide hands-on space science training to teachers as well as assistance in developing lesson plans for use in their classrooms. The program supports an instructional model based on education research and cognitive theory. Students and teachers engage in activities that encourage critical thinking and a constructivist approach to learning. LASSO is run through the Los Alamos Science Education Team (SET). SET personnel have many years of experience in teaching, education research, and science education programs. Their involvement ensures that the teacher workshop program is grounded in sound pedagogical methods and meets current educational standards. Lesson plans focus on current LANL satellite projects to study the solar wind and the Earth's magnetosphere. LASSO is an umbrella program for space science education activities at Los Alamos National Laboratory (LANL) that was created to enhance the science and math interests and skills of students from New Mexico and the nation. The LASSO umbrella allows maximum leveraging of EPO funding from a number of projects (and thus maximum educational benefits to both students and teachers), while providing a format for the expression of the unique science perspective of each project.

  15. FFTLasso: Large-Scale LASSO in the Fourier Domain

    KAUST Repository

    Bibi, Adel Aamer

    2017-11-09

    In this paper, we revisit the LASSO sparse representation problem, which has been studied and used in a variety of different areas, ranging from signal processing and information theory to computer vision and machine learning. In the vision community, it found its way into many important applications, including face recognition, tracking, super resolution, image denoising, to name a few. Despite advances in efficient sparse algorithms, solving large-scale LASSO problems remains a challenge. To circumvent this difficulty, people tend to downsample and subsample the problem (e.g. via dimensionality reduction) to maintain a manageable sized LASSO, which usually comes at the cost of losing solution accuracy. This paper proposes a novel circulant reformulation of the LASSO that lifts the problem to a higher dimension, where ADMM can be efficiently applied to its dual form. Because of this lifting, all optimization variables are updated using only basic element-wise operations, the most computationally expensive of which is a 1D FFT. In this way, there is no need for a linear system solver nor matrix-vector multiplication. Since all operations in our FFTLasso method are element-wise, the subproblems are completely independent and can be trivially parallelized (e.g. on a GPU). The attractive computational properties of FFTLasso are verified by extensive experiments on synthetic and real data and on the face recognition task. They demonstrate that FFTLasso scales much more effectively than a state-of-the-art solver.

  16. FFTLasso: Large-Scale LASSO in the Fourier Domain

    KAUST Repository

    Bibi, Adel Aamer; Itani, Hani; Ghanem, Bernard

    2017-01-01

    In this paper, we revisit the LASSO sparse representation problem, which has been studied and used in a variety of different areas, ranging from signal processing and information theory to computer vision and machine learning. In the vision community, it found its way into many important applications, including face recognition, tracking, super resolution, image denoising, to name a few. Despite advances in efficient sparse algorithms, solving large-scale LASSO problems remains a challenge. To circumvent this difficulty, people tend to downsample and subsample the problem (e.g. via dimensionality reduction) to maintain a manageable sized LASSO, which usually comes at the cost of losing solution accuracy. This paper proposes a novel circulant reformulation of the LASSO that lifts the problem to a higher dimension, where ADMM can be efficiently applied to its dual form. Because of this lifting, all optimization variables are updated using only basic element-wise operations, the most computationally expensive of which is a 1D FFT. In this way, there is no need for a linear system solver nor matrix-vector multiplication. Since all operations in our FFTLasso method are element-wise, the subproblems are completely independent and can be trivially parallelized (e.g. on a GPU). The attractive computational properties of FFTLasso are verified by extensive experiments on synthetic and real data and on the face recognition task. They demonstrate that FFTLasso scales much more effectively than a state-of-the-art solver.

  17. Calixarene receptors in the selective separation of alachlor. Characterization of the separated complexes

    International Nuclear Information System (INIS)

    Garcia G, M.C.

    2004-01-01

    Pesticides have been necessary in the agriculture since the plagues control have been remedied thanks to them but it has also provoked pollution. Nowadays, there are several methods which help to decrease or remedy such a pollution provoked. Unfortunately, any of them work out the environmental problem totally. Therefore, alternatives have to be found. The organic and tri dimensional characteristics of these macrocycles afford them a high versatility in such a way that these hosts can interact with organic guests selectively. Alachlor is a chlorinated organic herbicide useful in the plagues control of annual grasses and many broad-leave weeds which grow in maize, peanuts and soyabean. The ability of calixarenes to host organic guests with chemical characteristics similar to pesticides let them to be good candidates to compete with others methods which are used presently to separate organic pesticides. In this direction one of the advantages of proposing the use of calixarenes is, its facility of being modified in the lower and/or upper rims, to adapt them to aqueous, organic, gaseous and aqueous-organic media. Once the characteristics of reagents informed in the literature were confirmed and complemented with others found in this work, we studied, in solution, the interaction of the calixarenes with alachlor using 1 x 10 -5 to 1 x 10 -3 M solutions in acetonitrile for calixarenes fitted with phosphinoyl pendant arms in the lower rim, B n bL n , n= 4, 6) and in chloroform for parents calixarenes (H n bL n n = 4, 6, 8). Meticulous studies monitored by UV-Vis and luminescence were carried out, and the best stoichiometry to be used in further studies resulted to be 1(host): 1(alachlor). Therefore, we chose the 1 x 10 -4 M concentration to find how long the host-guest should be interacting in order to guarantee the formation in solution of the calixarene-alachlor species. It was found 168 h for the alachlor-B n bL n interaction while 165 h were necessary with H n bL n

  18. Bacterial communities in batch and continuous-flow wetlands treating the herbicide S-metolachlor

    International Nuclear Information System (INIS)

    Elsayed, O.F.; Maillard, E.; Vuilleumier, S.; Imfeld, G.

    2014-01-01

    Knowledge of wetland bacterial communities in the context of pesticide contamination and hydrological regime is scarce. We investigated the bacterial composition in constructed wetlands receiving Mercantor Gold ® contaminated water (960 g L −1 of the herbicide S-metolachlor, > 80% of the S-enantiomer) operated under continuous-flow or batch modes to evaluate the impact of the hydraulic regime. In the continuous-flow wetland, S-metolachlor mass removal was > 40%, whereas in the batch wetland, almost complete removal of S-metolachlor (93–97%) was observed. Detection of ethanesulfonic and oxanilic acid degradation products further indicated S-metolachlor biodegradation in the two wetlands. The dominant bacterial populations were characterised by terminal restriction fragment length polymorphism (T-RFLP) and 454 pyrosequencing. The bacterial profiles evolved during the first 35 days of the experiment, starting from a composition similar to that of inlet water, with the use of nitrate and to a lesser extent sulphate and manganese as terminal electron acceptors for microbial metabolism. Proteobacteria were the most abundant phylum, with Beta-, Alpha- and Gammaproteobacteria representing 26%, 19% and 17% respectively of total bacterial abundance. Bacterial composition in wetland water changed gradually over time in continuous-flow wetland and more abruptly in the batch wetland. Differences in overall bacterial water structure in the two systems were modest but significant (p = 0.008), and S-metolachlor, nitrate, and total inorganic carbon concentrations correlated with changes in the bacterial profiles. Together, the results highlight that bacterial composition profiles and their dynamics may be used as bioindicators of herbicide exposure and hydraulic disturbances in wetland systems. - Highlights: • We evaluated the bacterial composition in wetlands treating S-metolachlor • Hydraulic regime impacted biogeochemical processes and S-metolachlor removal

  19. Enantioselective oxidative stress and oxidative damage caused by Rac- and S-metolachlor to Scenedesmus obliquus.

    Science.gov (United States)

    Liu, Huijun; Xia, YiLu; Cai, Weidan; Zhang, Yina; Zhang, Xiaoqiang; Du, Shaoting

    2017-04-01

    The rational use and environmental security of chiral pesticides has gained the interest of many researchers. The enantioselective effects of Rac- and S-metolachlor on oxidative stress in Scenedesmus obliquus were determined in this study. Stronger green fluorescence was observed in response to S-metolachlor treatment than to Rac-metolachlor treatment, suggesting that more reactive oxygen species (ROS) were stimulated by S-metolachlor. ROS levels following S-metolachlor treatment were 1.92-, 8.31-, and 1.08-times higher than those observed following Rac-metolachlor treatment at 0.1, 0.2, and 0.3 mg/L, respectively. Superoxide dismutase (SOD) and catalase (CAT) were stimulated with increasing herbicide concentrations, with S-metolachlor exhibiting a greater effect. Oxidative damage in terms of chlorophyll (Chl) content, cellular membrane permeability, and cellular ultrastructures of S. obliquus were investigated. Chla and Chlb contents in algae treated with Rac-metolachlor were 2-6-fold higher than those in algae treated with S-metolachlor at 0.1, 0.2, and 0.3 mg/L. The cellular membrane permeability of algae exposed to 0.3 mg/L Rac- and S-metolachlor was 6.19- and 42.5-times that of the control. Correlation analysis implied that ROS are the major factor responsible for the oxidative damage caused by Rac- and S-metolachlor. Damage to the chloroplasts and cell membrane of S. obliquus, low production of starch granules, and an increased number of vacuoles were observed upon ultrastructural morphology analysis by transmission electron microscope. These results indicate that S-metolachlor has a greater effect on S. obliquus than Rac-metolachlor. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Effects of atrazine, metolachlor, carbaryl and chlorothalonil on benthic microbes and their nutrient dynamics.

    Directory of Open Access Journals (Sweden)

    Daniel Elias

    Full Text Available Atrazine, metolachlor, carbaryl, and chlorothalonil are detected in streams throughout the U.S. at concentrations that may have adverse effects on benthic microbes. Sediment samples were exposed to these pesticides to quantify responses of ammonium, nitrate, and phosphate uptake by the benthic microbial community. Control uptake rates of sediments had net remineralization of nitrate (-1.58 NO3 µg gdm⁻¹ h⁻¹, and net assimilation of phosphate (1.34 PO4 µg gdm⁻¹ h⁻¹ and ammonium (0.03 NH4 µg gdm⁻¹ h⁻¹. Metolachlor decreased ammonium and phosphate uptake. Chlorothalonil decreased nitrate remineralization and phosphate uptake. Nitrate, ammonium, and phosphate uptake rates are more pronounced in the presence of these pesticides due to microbial adaptations to toxicants. Our interpretation of pesticide availability based on their water/solid affinities supports no effects for atrazine and carbaryl, decreasing nitrate remineralization, and phosphate assimilation in response to chlorothalonil. Further, decreased ammonium and phosphate uptake in response to metolachlor is likely due to affinity. Because atrazine target autotrophs, and carbaryl synaptic activity, effects on benthic microbes were not hypothesized, consistent with results. Metolachlor and chlorothalonil (non-specific modes of action had significant effects on sediment microbial nutrient dynamics. Thus, pesticides with a higher affinity to sediments and/or broad modes of action are likely to affect sediment microbes' nutrient dynamics than pesticides dissolved in water or specific modes of action. Predicted nutrient uptake rates were calculated at mean and peak concentrations of metolachlor and chlorothalonil in freshwaters using polynomial equations generated in this experiment. We concluded that in natural ecosystems, peak chlorothalonil and metolachlor concentrations could affect phosphate and ammonium by decreasing net assimilation, and nitrate uptake rates by

  1. Supervised group Lasso with applications to microarray data analysis

    Directory of Open Access Journals (Sweden)

    Huang Jian

    2007-02-01

    Full Text Available Abstract Background A tremendous amount of efforts have been devoted to identifying genes for diagnosis and prognosis of diseases using microarray gene expression data. It has been demonstrated that gene expression data have cluster structure, where the clusters consist of co-regulated genes which tend to have coordinated functions. However, most available statistical methods for gene selection do not take into consideration the cluster structure. Results We propose a supervised group Lasso approach that takes into account the cluster structure in gene expression data for gene selection and predictive model building. For gene expression data without biological cluster information, we first divide genes into clusters using the K-means approach and determine the optimal number of clusters using the Gap method. The supervised group Lasso consists of two steps. In the first step, we identify important genes within each cluster using the Lasso method. In the second step, we select important clusters using the group Lasso. Tuning parameters are determined using V-fold cross validation at both steps to allow for further flexibility. Prediction performance is evaluated using leave-one-out cross validation. We apply the proposed method to disease classification and survival analysis with microarray data. Conclusion We analyze four microarray data sets using the proposed approach: two cancer data sets with binary cancer occurrence as outcomes and two lymphoma data sets with survival outcomes. The results show that the proposed approach is capable of identifying a small number of influential gene clusters and important genes within those clusters, and has better prediction performance than existing methods.

  2. Fast empirical Bayesian LASSO for multiple quantitative trait locus mapping

    Directory of Open Access Journals (Sweden)

    Xu Shizhong

    2011-05-01

    Full Text Available Abstract Background The Bayesian shrinkage technique has been applied to multiple quantitative trait loci (QTLs mapping to estimate the genetic effects of QTLs on quantitative traits from a very large set of possible effects including the main and epistatic effects of QTLs. Although the recently developed empirical Bayes (EB method significantly reduced computation comparing with the fully Bayesian approach, its speed and accuracy are limited by the fact that numerical optimization is required to estimate the variance components in the QTL model. Results We developed a fast empirical Bayesian LASSO (EBLASSO method for multiple QTL mapping. The fact that the EBLASSO can estimate the variance components in a closed form along with other algorithmic techniques render the EBLASSO method more efficient and accurate. Comparing with the EB method, our simulation study demonstrated that the EBLASSO method could substantially improve the computational speed and detect more QTL effects without increasing the false positive rate. Particularly, the EBLASSO algorithm running on a personal computer could easily handle a linear QTL model with more than 100,000 variables in our simulation study. Real data analysis also demonstrated that the EBLASSO method detected more reasonable effects than the EB method. Comparing with the LASSO, our simulation showed that the current version of the EBLASSO implemented in Matlab had similar speed as the LASSO implemented in Fortran, and that the EBLASSO detected the same number of true effects as the LASSO but a much smaller number of false positive effects. Conclusions The EBLASSO method can handle a large number of effects possibly including both the main and epistatic QTL effects, environmental effects and the effects of gene-environment interactions. It will be a very useful tool for multiple QTL mapping.

  3. Matlab implementation of LASSO, LARS, the elastic net and SPCA

    DEFF Research Database (Denmark)

    2005-01-01

    There are a number of interesting variable selection methods available beside the regular forward selection and stepwise selection methods. Such approaches include LASSO (Least Absolute Shrinkage and Selection Operator), least angle regression (LARS) and elastic net (LARS-EN) regression. There al...... exists a method for calculating principal components with sparse loadings. This software package contains Matlab implementations of these functions. The standard implementations of these functions are available as add-on packages in S-Plus and R....

  4. Lasso and probabilistic inequalities for multivariate point processes

    OpenAIRE

    Hansen, Niels Richard; Reynaud-Bouret, Patricia; Rivoirard, Vincent

    2012-01-01

    Due to its low computational cost, Lasso is an attractive regularization method for high-dimensional statistical settings. In this paper, we consider multivariate counting processes depending on an unknown function parameter to be estimated by linear combinations of a fixed dictionary. To select coefficients, we propose an adaptive $\\ell_{1}$-penalization methodology, where data-driven weights of the penalty are derived from new Bernstein type inequalities for martingales. Oracle inequalities...

  5. Controlling the local false discovery rate in the adaptive Lasso

    KAUST Repository

    Sampson, J. N.

    2013-04-09

    The Lasso shrinkage procedure achieved its popularity, in part, by its tendency to shrink estimated coefficients to zero, and its ability to serve as a variable selection procedure. Using data-adaptive weights, the adaptive Lasso modified the original procedure to increase the penalty terms for those variables estimated to be less important by ordinary least squares. Although this modified procedure attained the oracle properties, the resulting models tend to include a large number of "false positives" in practice. Here, we adapt the concept of local false discovery rates (lFDRs) so that it applies to the sequence, λn, of smoothing parameters for the adaptive Lasso. We define the lFDR for a given λn to be the probability that the variable added to the model by decreasing λn to λn-δ is not associated with the outcome, where δ is a small value. We derive the relationship between the lFDR and λn, show lFDR =1 for traditional smoothing parameters, and show how to select λn so as to achieve a desired lFDR. We compare the smoothing parameters chosen to achieve a specified lFDR and those chosen to achieve the oracle properties, as well as their resulting estimates for model coefficients, with both simulation and an example from a genetic study of prostate specific antigen.

  6. The Bayesian group lasso for confounded spatial data

    Science.gov (United States)

    Hefley, Trevor J.; Hooten, Mevin B.; Hanks, Ephraim M.; Russell, Robin E.; Walsh, Daniel P.

    2017-01-01

    Generalized linear mixed models for spatial processes are widely used in applied statistics. In many applications of the spatial generalized linear mixed model (SGLMM), the goal is to obtain inference about regression coefficients while achieving optimal predictive ability. When implementing the SGLMM, multicollinearity among covariates and the spatial random effects can make computation challenging and influence inference. We present a Bayesian group lasso prior with a single tuning parameter that can be chosen to optimize predictive ability of the SGLMM and jointly regularize the regression coefficients and spatial random effect. We implement the group lasso SGLMM using efficient Markov chain Monte Carlo (MCMC) algorithms and demonstrate how multicollinearity among covariates and the spatial random effect can be monitored as a derived quantity. To test our method, we compared several parameterizations of the SGLMM using simulated data and two examples from plant ecology and disease ecology. In all examples, problematic levels multicollinearity occurred and influenced sampling efficiency and inference. We found that the group lasso prior resulted in roughly twice the effective sample size for MCMC samples of regression coefficients and can have higher and less variable predictive accuracy based on out-of-sample data when compared to the standard SGLMM.

  7. Sparse EEG/MEG source estimation via a group lasso.

    Directory of Open Access Journals (Sweden)

    Michael Lim

    Full Text Available Non-invasive recordings of human brain activity through electroencephalography (EEG or magnetoencelphalography (MEG are of value for both basic science and clinical applications in sensory, cognitive, and affective neuroscience. Here we introduce a new approach to estimating the intra-cranial sources of EEG/MEG activity measured from extra-cranial sensors. The approach is based on the group lasso, a sparse-prior inverse that has been adapted to take advantage of functionally-defined regions of interest for the definition of physiologically meaningful groups within a functionally-based common space. Detailed simulations using realistic source-geometries and data from a human Visual Evoked Potential experiment demonstrate that the group-lasso method has improved performance over traditional ℓ2 minimum-norm methods. In addition, we show that pooling source estimates across subjects over functionally defined regions of interest results in improvements in the accuracy of source estimates for both the group-lasso and minimum-norm approaches.

  8. LES ARM Symbiotic Simulation and Observation (LASSO) Implementation Strategy

    Energy Technology Data Exchange (ETDEWEB)

    Gustafson Jr., WI [Pacific Northwest National Laboratory; Vogelmann, AM [Brookhaven National Laboratory

    2015-09-01

    This document illustrates the design of the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) workflow to provide a routine, high-resolution modeling capability to augment the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s high-density observations. LASSO will create a powerful new capability for furthering ARM’s mission to advance understanding of cloud, radiation, aerosol, and land-surface processes. The combined observational and modeling elements will enable a new level of scientific inquiry by connecting processes and context to observations and providing needed statistics for details that cannot be measured. The result will be improved process understanding that facilitates concomitant improvements in climate model parameterizations. The initial LASSO implementation will be for ARM’s Southern Great Plains site in Oklahoma and will focus on shallow convection, which is poorly simulated by climate models due in part to clouds’ typically small spatial scale compared to model grid spacing, and because the convection involves complicated interactions of microphysical and boundary layer processes.

  9. Impacts of Rac- and S-metolachlor on cyanobacterial cell integrity and release of microcystins at different nitrogen levels.

    Science.gov (United States)

    Wang, Jia; Zhang, Lijuan; Fan, Jiajia; Wen, Yuezhong

    2017-08-01

    Pesticide residues and nitrogen overload (which caused cyanobacteria blooms) have been two serious environmental concerns. In particular, chiral pesticides with different structures may have various impacts on cyanobacteria. Nitrogen may affect the behavior between pesticides and cyanobacteria (e.g., increase the adverse effects of pesticides on cyanobacteria). This study evaluated the impacts of Rac- and S-metolachlor on the cell integrity and toxin release of Microcystis aeruginosa cells at different nitrogen levels. The results showed that (both of the configurations: Rac-, S-) metolachlor could inhibit M. aeruginosa cell growth under most conditions, and the inhibition rates were increased with the growing concentrations of nitrogen and metolachlor. However, cyanobacterial growth was promoted in 48 h under environmental relevant condition (1 mg/L metolachlor and 0.15 mg/L nitrogen). Therefore, the water authorities should adjust the treatment parameters to remove possible larger numbers of cyaonbacteria under that condition. On the other hand, the inhibition degree of M. aeruginosa cell growth by S-metolachlor treatments was obviously larger than Rac-metolachlor treatments. S-metolachlor also had a stronger ability in compromising M. aeruginosa cells than Rac-metolachlor treatments. Compared to control samples, more extracellular toxins (12%-86% increases) were detected after 5 mg/L S-metolachlor treatment for 72 h at different nitrogen levels, but the variations of extracellular toxins caused by 5 mg/L Rac-metolachlor addition could be neglected. Consequently, higher concentrations of metolachlor in source waters are harmful to humans, but it may prevent cyanobacterial blooms. However, the potential risks (e.g. build-up of extracellular toxins) should be considered. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Analysis of metolachlor ethane sulfonic acid (MESA) chirality in groundwater: A tool for dating groundwater movement in agricultural settings.

    Science.gov (United States)

    Rice, Clifford P; McCarty, Gregory W; Bialek-Kalinski, Krystyna; Zabetakis, Kara; Torrents, Alba; Hapeman, Cathleen J

    2016-08-01

    To better address how much groundwater contributes to the loadings of pollutants from agriculture we developed a specific dating tool for groundwater residence times. This tool is based on metolachlor ethane sulfonic acid, which is a major soil metabolite of metolachlor. The chiral forms of metolachlor ethane sulfonic acid (MESA) and the chiral forms of metolachlor were examined over a 6-year period in samples of groundwater and water from a groundwater-fed stream in a riparian buffer zone. This buffer zone bordered cropland receiving annual treatments with metolachlor. Racemic (rac) metolachlor was applied for two years in the neighboring field, and subsequently S-metolachlor was used which is enriched by 88% with the S-enantiomer. Chiral analyses of the samples showed an exponential increase in abundance of the S-enantiomeric forms for MESA as a function of time for both the first order riparian buffer stream (R(2)=0.80) and for groundwater within the riparian buffer (R(2)=0.96). However, the S-enrichment values for metolachlor were consistently high indicating different delivery mechanisms for MESA and metolachlor. A mean residence time of 3.8years was determined for depletion of the initially-applied rac-metolachlor. This approach could be useful in dating groundwater and determining the effectiveness of conservation measures. A mean residence time of 3.8years was calculated for groundwater feeding a first-order stream by plotting the timed-decay for the R-enantiomer of metolachlor ethane sulfonic acid. Published by Elsevier B.V.

  11. Degradation mechanism of alachlor during direct ozonation and O(3)/H(2)O(2) advanced oxidation process.

    Science.gov (United States)

    Qiang, Zhimin; Liu, Chao; Dong, Bingzhi; Zhang, Yalei

    2010-01-01

    The degradation of alachlor by direct ozonation and advanced oxidation process O(3)/H(2)O(2) was investigated in this study with focus on identification of degradation byproducts. The second-order reaction rate constant between ozone and alachlor was determined to be 2.5+/-0.1M(-1)s(-1) at pH 7.0 and 20 degrees C. Twelve and eight high-molecular-weight byproducts (with the benzene ring intact) from alachlor degradation were identified during direct ozonation and O(3)/H(2)O(2), respectively. The common degradation byproducts included N-(2,6-diethylphenyl)-methyleneamine, 8-ethyl-3,4-dihydro-quinoline, 8-ethyl-quinoline, 1-chloroacetyl-2-hydro-3-ketone-7-acetyl-indole, 2-chloro-2',6'-diacetyl-N-(methoxymethyl)acetanilide, 2-chloro-2'-acetyl-6'-ethyl-N-(methoxymethyl)-acetanilide, and two hydroxylated alachlor isomers. In direct ozonation, four more byproducts were also identified including 1-chloroacetyl-2,3-dihydro-7-ethyl-indole, 2-chloro-2',6'-ethyl-acetanilide, 2-chloro-2',6'-acetyl-acetanilide and 2-chloro-2'-ethyl-6'-acetyl-N-(methoxymethyl)-acetanilide. Degradation of alachlor by O(3) and O(3)/H(2)O(2) also led to the formation of low-molecular-weight byproducts including formic, acetic, propionic, monochloroacetic and oxalic acids as well as chloride ion (only detected in O(3)/H(2)O(2)). Nitrite and nitrate formation was negligible. Alachlor degradation occurred via oxidation of the arylethyl group, N-dealkylation, cyclization and cleavage of benzene ring. After O(3) or O(3)/H(2)O(2) treatment, the toxicity of alachlor solution examined by the Daphnia magna bioassay was slightly reduced. 2009 Elsevier Ltd. All rights reserved.

  12. Bacterial communities in batch and continuous-flow wetlands treating the herbicide S-metolachlor

    Energy Technology Data Exchange (ETDEWEB)

    Elsayed, O.F. [Laboratory of Hydrology and Geochemistry of Strasbourg (LHyGeS), UMR 7517 University of Strasbourg/ENGEES/CNRS (France); Génétique Moléculaire, Génomique, Microbiologie (GMGM), UMR 7156 University of Strasbourg/CNRS (France); Maillard, E. [Laboratory of Hydrology and Geochemistry of Strasbourg (LHyGeS), UMR 7517 University of Strasbourg/ENGEES/CNRS (France); Vuilleumier, S. [Génétique Moléculaire, Génomique, Microbiologie (GMGM), UMR 7156 University of Strasbourg/CNRS (France); Imfeld, G., E-mail: imfeld@unistra.fr [Laboratory of Hydrology and Geochemistry of Strasbourg (LHyGeS), UMR 7517 University of Strasbourg/ENGEES/CNRS (France)

    2014-11-15

    Knowledge of wetland bacterial communities in the context of pesticide contamination and hydrological regime is scarce. We investigated the bacterial composition in constructed wetlands receiving Mercantor Gold{sup ®} contaminated water (960 g L{sup −1} of the herbicide S-metolachlor, > 80% of the S-enantiomer) operated under continuous-flow or batch modes to evaluate the impact of the hydraulic regime. In the continuous-flow wetland, S-metolachlor mass removal was > 40%, whereas in the batch wetland, almost complete removal of S-metolachlor (93–97%) was observed. Detection of ethanesulfonic and oxanilic acid degradation products further indicated S-metolachlor biodegradation in the two wetlands. The dominant bacterial populations were characterised by terminal restriction fragment length polymorphism (T-RFLP) and 454 pyrosequencing. The bacterial profiles evolved during the first 35 days of the experiment, starting from a composition similar to that of inlet water, with the use of nitrate and to a lesser extent sulphate and manganese as terminal electron acceptors for microbial metabolism. Proteobacteria were the most abundant phylum, with Beta-, Alpha- and Gammaproteobacteria representing 26%, 19% and 17% respectively of total bacterial abundance. Bacterial composition in wetland water changed gradually over time in continuous-flow wetland and more abruptly in the batch wetland. Differences in overall bacterial water structure in the two systems were modest but significant (p = 0.008), and S-metolachlor, nitrate, and total inorganic carbon concentrations correlated with changes in the bacterial profiles. Together, the results highlight that bacterial composition profiles and their dynamics may be used as bioindicators of herbicide exposure and hydraulic disturbances in wetland systems. - Highlights: • We evaluated the bacterial composition in wetlands treating S-metolachlor • Hydraulic regime impacted biogeochemical processes and S-metolachlor removal

  13. Phytotoxicity of Alachlor, Bromacil and Diuron as single or mixed herbicides applied to wheat, melon, and molokhia.

    Science.gov (United States)

    El-Nahhal, Yasser; Hamdona, Nisreen

    2015-01-01

    This study investigated the phytotoxicity of herbicides applied singly or as mixtures to different crops under greenhouse conditions. Growth inhibition of the crops was taken as an indicator of phytotoxicity. Phytotoxicity of mixtures was estimated by calculating EC50 value in toxic units. EC50 (mg/kg soil) of Alachlor, Bromacil and/or Diuron were: 11.37, 4.77, 1.64, respectively, on melon; 0.11, 0.08, 0.24, respectively, on molokhia, and 3.91, 3.08, 1.83, respectively, on wheat. EC50 values of binary mixture tests of (Alachlor + Bromacil), (Alachlor + Diuron), and (Bromacil + Diuron) were 12.21, 5.84, 10.22 on melon, 0.982, 925.4, 38.1 on molokhia, and 0.673, 1.34, 0.644 on wheat. Tertiary mixture tests showed EC50 values (TU/kg soil) of (Alachlor + Bromacil + Diuron) was 633.9 on melon, 3.02 on molokhia and 32.174 on wheat. Diuron was more toxic than Alachlor and Bromacil to the tested crops based on individual tests. Molokhia was the most sensitive crop to herbicides. Binary mixtures showed a synergistic effect as compared to the tertiary mixtures.

  14. The use of vector bootstrapping to improve variable selection precision in Lasso models

    NARCIS (Netherlands)

    Laurin, C.; Boomsma, D.I.; Lubke, G.H.

    2016-01-01

    The Lasso is a shrinkage regression method that is widely used for variable selection in statistical genetics. Commonly, K-fold cross-validation is used to fit a Lasso model. This is sometimes followed by using bootstrap confidence intervals to improve precision in the resulting variable selections.

  15. Effects of the organic matter from swine wastewater on the adsorption and desorption of alachlor in soil.

    Science.gov (United States)

    Dal Bosco, Tatiane C; Sampaio, Silvio C; Coelho, Silvia R M; Cosmann, Natássia J; Smanhotto, Adriana

    2012-01-01

    The application of swine wastewater to the soil for agricultural purposes results in the addition of total and dissolved organic matter to the soil, which may interfere with the dynamics of pesticides in the soil. The objective of this study was to evaluate the effects of the application of total and dissolved organic matter from a biodigester and a treatment lagoon of swine wastewater in the adsorption and desorption of alachlor [2-chloro-2,6-diethyl-N(methoxymethyl acetamide)]. The assay was performed by the batch equilibrium method, and the results were fitted to the Freundlich model. The curve comparison test revealed a greater adsorption of alachlor in the soil treated with swine wastewater from the biodigester. The adsorption and desorption of alachlor increased in the soils where swine wastewater was added, and hysteresis was observed in all of the treatments. Copyright © Taylor & Francis Group, LLC

  16. Organosilane grafted acid-activated beidellite clay for the removal of non-ionic alachlor and anionic imazaquin

    International Nuclear Information System (INIS)

    Paul, Blain; Martens, Wayde N.; Frost, Ray L.

    2011-01-01

    Clay adsorbents were prepared via two-step method to remove nonionic alachlor and anionic imazaquin herbicides from water. Firstly, layered beidellite clay, a member of smectite family, was treated with acid in hydrothermal process; secondly, common silane coupling agents, 3-chloro-propyl trimethoxysilane or triethoxy silane, were grafted on the acid treated samples to prepare adsorbent materials. The organically modified clay samples were characterized by powder X-ray diffraction, N 2 gas adsorption, and FTIR spectroscopy. It was found that the selective modification of clay samples displayed higher adsorption capacity for herbicides compared with acid activated clay. And the amount of adsorption is increased with increasing the grafting amount of silane groups. Clay grafted with 3-chloro-propyl trimethoxysilane is an excellent adsorbent for both alachlor and imazaquin but triethoxy (octyl) silane grafted clay is more efficient only for alachlor removal.

  17. Maternal and fetal toxicity of Wistar rats exposed to herbicide metolachlor

    Directory of Open Access Journals (Sweden)

    Kátia Cristina de Melo Tavares Vieira

    2016-07-01

    Full Text Available Metolachlor is a selective pre-emergent herbicide widely used in agriculture to control weeds. The aim of this study was to evaluate the possible effects of metolachlor on reproductive performance of adult rats, as well as its teratogenic potential when administered during the period of organogenesis. Pregnant adult female rats were allocated into 4 experimental groups (n = 10 group-1, that received 0 (control; 150 (TA; 300 (TB; or 1000 mg kg-1 bw day-1 (TC of metolachlor, by gavage, from the 6th to 15th gestational day (GD. There is reduction in the weight gain of the animals from TB and TC groups compared to the control group. Liver and placenta weights were reduced in TB and TC groups, respectively, while the percentage of post-implantation loss was increased in the TC group. There were no external malformations in either rat of the control or treated groups. However, an increased incidence of skeletal anomalies and visceral anomalies (especially in the urogenital system was observed in TC group. These results demonstrate that exposure of pregnant rats to metolachlor can lead to signs of general toxicity, late embryonic losses and congenital anomalies.

  18. Sungsanpin, a lasso peptide from a deep-sea streptomycete.

    Science.gov (United States)

    Um, Soohyun; Kim, Young-Joo; Kwon, Hyuknam; Wen, He; Kim, Seong-Hwan; Kwon, Hak Cheol; Park, Sunghyouk; Shin, Jongheon; Oh, Dong-Chan

    2013-05-24

    Sungsanpin (1), a new 15-amino-acid peptide, was discovered from a Streptomyces species isolated from deep-sea sediment collected off Jeju Island, Korea. The planar structure of 1 was determined by 1D and 2D NMR spectroscopy, mass spectrometry, and UV spectroscopy. The absolute configurations of the stereocenters in this compound were assigned by derivatizations of the hydrolysate of 1 with Marfey's reagents and 2,3,4,6-tetra-O-acetyl-β-d-glucopyranosyl isothiocyanate, followed by LC-MS analysis. Careful analysis of the ROESY NMR spectrum and three-dimensional structure calculations revealed that sungsanpin possesses the features of a lasso peptide: eight amino acids (-Gly(1)-Phe-Gly-Ser-Lys-Pro-Ile-Asp(8)-) that form a cyclic peptide and seven amino acids (-Ser(9)-Phe-Gly-Leu-Ser-Trp-Leu(15)) that form a tail that loops through the ring. Sungsanpin is thus the first example of a lasso peptide isolated from a marine-derived microorganism. Sungsanpin displayed inhibitory activity in a cell invasion assay with the human lung cancer cell line A549.

  19. RESPONSES OF MOLECULAR INDICATORS OF EXPOSURE IN MESOCOSMS: COMMON CARP (CYPRINUS CARPIO) EXPOSED TO THE HERBICIDES ALACHLOR AND ATRAZINE

    Science.gov (United States)

    Common carp (Cyprinus carpio) were treated in aquatic mesocosms with a single pulse of the herbicides atrazine or alachlor to study the bioavailability and biological activity of these herbicides using molecular indicators: Liver vitellogenin gene expression in male fish for estr...

  20. The joint graphical lasso for inverse covariance estimation across multiple classes.

    Science.gov (United States)

    Danaher, Patrick; Wang, Pei; Witten, Daniela M

    2014-03-01

    We consider the problem of estimating multiple related Gaussian graphical models from a high-dimensional data set with observations belonging to distinct classes. We propose the joint graphical lasso , which borrows strength across the classes in order to estimate multiple graphical models that share certain characteristics, such as the locations or weights of nonzero edges. Our approach is based upon maximizing a penalized log likelihood. We employ generalized fused lasso or group lasso penalties, and implement a fast ADMM algorithm to solve the corresponding convex optimization problems. The performance of the proposed method is illustrated through simulated and real data examples.

  1. Fused Adaptive Lasso for Spatial and Temporal Quantile Function Estimation

    KAUST Repository

    Sun, Ying

    2015-09-01

    Quantile functions are important in characterizing the entire probability distribution of a random variable, especially when the tail of a skewed distribution is of interest. This article introduces new quantile function estimators for spatial and temporal data with a fused adaptive Lasso penalty to accommodate the dependence in space and time. This method penalizes the difference among neighboring quantiles, hence it is desirable for applications with features ordered in time or space without replicated observations. The theoretical properties are investigated and the performances of the proposed methods are evaluated by simulations. The proposed method is applied to particulate matter (PM) data from the Community Multiscale Air Quality (CMAQ) model to characterize the upper quantiles, which are crucial for studying spatial association between PM concentrations and adverse human health effects. © 2016 American Statistical Association and the American Society for Quality.

  2. Structural Graphical Lasso for Learning Mouse Brain Connectivity

    KAUST Repository

    Yang, Sen

    2015-08-07

    Investigations into brain connectivity aim to recover networks of brain regions connected by anatomical tracts or by functional associations. The inference of brain networks has recently attracted much interest due to the increasing availability of high-resolution brain imaging data. Sparse inverse covariance estimation with lasso and group lasso penalty has been demonstrated to be a powerful approach to discover brain networks. Motivated by the hierarchical structure of the brain networks, we consider the problem of estimating a graphical model with tree-structural regularization in this paper. The regularization encourages the graphical model to exhibit a brain-like structure. Specifically, in this hierarchical structure, hundreds of thousands of voxels serve as the leaf nodes of the tree. A node in the intermediate layer represents a region formed by voxels in the subtree rooted at that node. The whole brain is considered as the root of the tree. We propose to apply the tree-structural regularized graphical model to estimate the mouse brain network. However, the dimensionality of whole-brain data, usually on the order of hundreds of thousands, poses significant computational challenges. Efficient algorithms that are capable of estimating networks from high-dimensional data are highly desired. To address the computational challenge, we develop a screening rule which can quickly identify many zero blocks in the estimated graphical model, thereby dramatically reducing the computational cost of solving the proposed model. It is based on a novel insight on the relationship between screening and the so-called proximal operator that we first establish in this paper. We perform experiments on both synthetic data and real data from the Allen Developing Mouse Brain Atlas; results demonstrate the effectiveness and efficiency of the proposed approach.

  3. Polymeric Nanoparticles as a Metolachlor Carrier: Water-Based Formulation for Hydrophobic Pesticides and Absorption by Plants.

    Science.gov (United States)

    Tong, Yujia; Wu, Yan; Zhao, Caiyan; Xu, Yong; Lu, Jianqing; Xiang, Sheng; Zong, Fulin; Wu, Xuemin

    2017-08-30

    Pesticide formulation is highly desirable for effective utilization of pesticide and environmental pollution reduction. Studies of pesticide delivery system such as microcapsules are developing prosperously. In this work, we chose polymeric nanoparticles as a pesticide delivery system and metolachlor was used as a hydrophobic pesticide model to study water-based mPEG-PLGA nanoparticle formulation. Preparation, characterization results showed that the resulting nanoparticles enhanced "water solubility" of hydrophobic metolachlor and contained no organic solvent or surfactant, which represent one of the most important sources of pesticide pollution. After the release study, absorption of Cy5-labeled nanoparticles into rice roots suggested a possible transmitting pathway of this metolachlor formulation and increased utilization of metolachlor. Furthermore, the bioassay test demonstrated that this nanoparticle showed higher effect than non-nano forms under relatively low concentrations on Oryza sativa, Digitaria sanguinalis. In addition, a simple cytotoxicity test involving metolachlor and metolachlor-loaded nanoparticles was performed, indicating toxicity reduction of the latter to the preosteoblast cell line. All of these results showed that those polymeric nanoparticles could serve as a pesticide carrier with lower environmental impact, comparable effect, and effective delivery.

  4. Biochar characteristics produced from rice husks and their sorption properties for the acetanilide herbicide metolachlor.

    Science.gov (United States)

    Wei, Lan; Huang, Yufen; Li, Yanliang; Huang, Lianxi; Mar, Nyo Nyo; Huang, Qing; Liu, Zhongzhen

    2017-02-01

    Rice husk biochar (RHBC) was prepared for use as adsorbents for the herbicide metolachlor. The characteristics and sorption properties of metolachlor adsorbed by the RHBC prepared at different pyrolysis temperatures were determined by analysis of physico-chemical characteristics, Fourier transform infrared spectroscopy (FTIR), Boehm titration, scanning electron microscopy (SEM), and thermodynamics and kinetics adsorption. With increasing pyrolysis temperature, the RHBC surface area greatly increased (from 2.57 to 53.08 m 2  g -1 ). RHBC produced at the highest temperature (750 °C) had the greatest surface area; SEM also showed the formation of a porous surface on RH-750 biochar. The sorption capacity of RHBC also increased significantly with increasing pyrolysis temperature and was characterized by the Freundlich constant K f for the adsorption capacity increasing from 125.17-269.46 (pyrolysis at 300 °C) to 339.94-765.24 (pyrolysis at 750 °C). The results indicated that the surface area and pore diameter of RHBC produced with high pyrolysis temperature (i.e., 750 °C) had the greatest impact on the adsorption of metolachlor. The FTIR, Boehm titration, and SEM analysis showed that the greatest number of surface groups were on RHBC produced at the lowest temperature (300 °C). The biochars produced at different pyrolysis temperatures had different mechanisms of adsorbing metolachlor, which exhibited a transition from hydrogen bonds dominant at low pyrolytic temperature to pore-filling dominant at higher pyrolytic temperature.

  5. Consistent and Conservative Model Selection with the Adaptive LASSO in Stationary and Nonstationary Autoregressions

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl

    2016-01-01

    We show that the adaptive Lasso is oracle efficient in stationary and nonstationary autoregressions. This means that it estimates parameters consistently, selects the correct sparsity pattern, and estimates the coefficients belonging to the relevant variables at the same asymptotic efficiency...

  6. Treatment of Wastewater Contaminated with Pesticide (Alachlor by Solar Enhanced Advanced Oxidation Processes

    Directory of Open Access Journals (Sweden)

    Yasmen Abdulaziz Mustafa

    2015-11-01

    Full Text Available The degradation performance of aqueous solution of pesticide Alachlor has been studied at solar pilot scale plant in two photocatalytic systems: homogeneous photocatalysis by photo-Fenton and heterogeneous photocatalysis with titanium dioxide. The pilot scale system included of compound parabolic collectors specially designed for solar photocatalytic applications, and installed at University of Baghdad, Department of Environmental Engineering back yard. The influence of different concentrations, H2O2 (200-2400 mg/l, Fe+2(5- 30 mg/l and TiO2 (100-500 mg/l and their relationship with the degradation efficiency were studied. The COD removal efficiency for homogeneous photocatalytic system at the best dosage was found to be 73.7%. The parent pollutant concentrations which were monitored using HPLC decreased to reach zero level at early time of the experiment. For heterogeneous photocatalytic system the COD removal efficiency was found to be 72.7%.

  7. EPS-LASSO: Test for High-Dimensional Regression Under Extreme Phenotype Sampling of Continuous Traits.

    Science.gov (United States)

    Xu, Chao; Fang, Jian; Shen, Hui; Wang, Yu-Ping; Deng, Hong-Wen

    2018-01-25

    Extreme phenotype sampling (EPS) is a broadly-used design to identify candidate genetic factors contributing to the variation of quantitative traits. By enriching the signals in extreme phenotypic samples, EPS can boost the association power compared to random sampling. Most existing statistical methods for EPS examine the genetic factors individually, despite many quantitative traits have multiple genetic factors underlying their variation. It is desirable to model the joint effects of genetic factors, which may increase the power and identify novel quantitative trait loci under EPS. The joint analysis of genetic data in high-dimensional situations requires specialized techniques, e.g., the least absolute shrinkage and selection operator (LASSO). Although there are extensive research and application related to LASSO, the statistical inference and testing for the sparse model under EPS remain unknown. We propose a novel sparse model (EPS-LASSO) with hypothesis test for high-dimensional regression under EPS based on a decorrelated score function. The comprehensive simulation shows EPS-LASSO outperforms existing methods with stable type I error and FDR control. EPS-LASSO can provide a consistent power for both low- and high-dimensional situations compared with the other methods dealing with high-dimensional situations. The power of EPS-LASSO is close to other low-dimensional methods when the causal effect sizes are small and is superior when the effects are large. Applying EPS-LASSO to a transcriptome-wide gene expression study for obesity reveals 10 significant body mass index associated genes. Our results indicate that EPS-LASSO is an effective method for EPS data analysis, which can account for correlated predictors. The source code is available at https://github.com/xu1912/EPSLASSO. hdeng2@tulane.edu. Supplementary data are available at Bioinformatics online. © The Author (2018). Published by Oxford University Press. All rights reserved. For Permissions, please

  8. Identifying the Prognosis Factors in Death after Liver Transplantation via Adaptive LASSO in Iran

    Directory of Open Access Journals (Sweden)

    Hadi Raeisi Shahraki

    2016-01-01

    Full Text Available Despite the widespread use of liver transplantation as a routine therapy in liver diseases, the effective factors on its outcomes are still controversial. This study attempted to identify the most effective factors on death after liver transplantation. For this purpose, modified least absolute shrinkage and selection operator (LASSO, called Adaptive LASSO, was utilized. One of the best advantages of this method is considering high number of factors. Therefore, in a historical cohort study from 2008 to 2013, the clinical findings of 680 patients undergoing liver transplant surgery were considered. Ridge and Adaptive LASSO regression methods were then implemented to identify the most effective factors on death. To compare the performance of these two models, receiver operating characteristic (ROC curve was used. According to the results, 12 factors in Ridge regression and 9 ones in Adaptive LASSO regression were significant. The area under the ROC curve (AUC of Adaptive LASSO was equal to 89% (95% CI: 86%–91%, which was significantly greater than Ridge regression (64%, 95% CI: 61%–68% (p<0.001. As a conclusion, the significant factors and the performance criteria revealed the superiority of Adaptive LASSO method as a penalized model versus traditional regression model in the present study.

  9. Toward Probabilistic Diagnosis and Understanding of Depression Based on Functional MRI Data Analysis with Logistic Group LASSO.

    Directory of Open Access Journals (Sweden)

    Yu Shimizu

    Full Text Available Diagnosis of psychiatric disorders based on brain imaging data is highly desirable in clinical applications. However, a common problem in applying machine learning algorithms is that the number of imaging data dimensions often greatly exceeds the number of available training samples. Furthermore, interpretability of the learned classifier with respect to brain function and anatomy is an important, but non-trivial issue. We propose the use of logistic regression with a least absolute shrinkage and selection operator (LASSO to capture the most critical input features. In particular, we consider application of group LASSO to select brain areas relevant to diagnosis. An additional advantage of LASSO is its probabilistic output, which allows evaluation of diagnosis certainty. To verify our approach, we obtained semantic and phonological verbal fluency fMRI data from 31 depression patients and 31 control subjects, and compared the performances of group LASSO (gLASSO, and sparse group LASSO (sgLASSO to those of standard LASSO (sLASSO, Support Vector Machine (SVM, and Random Forest. Over 90% classification accuracy was achieved with gLASSO, sgLASSO, as well as SVM; however, in contrast to SVM, LASSO approaches allow for identification of the most discriminative weights and estimation of prediction reliability. Semantic task data revealed contributions to the classification from left precuneus, left precentral gyrus, left inferior frontal cortex (pars triangularis, and left cerebellum (c rus1. Weights for the phonological task indicated contributions from left inferior frontal operculum, left post central gyrus, left insula, left middle frontal cortex, bilateral middle temporal cortices, bilateral precuneus, left inferior frontal cortex (pars triangularis, and left precentral gyrus. The distribution of normalized odds ratios further showed, that predictions with absolute odds ratios higher than 0.2 could be regarded as certain.

  10. Breast cancer tumor classification using LASSO method selection approach

    International Nuclear Information System (INIS)

    Celaya P, J. M.; Ortiz M, J. A.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Garza V, I.; Martinez F, M.; Ortiz R, J. M.

    2016-10-01

    Breast cancer is one of the leading causes of deaths worldwide among women. Early tumor detection is key in reducing breast cancer deaths and screening mammography is the widest available method for early detection. Mammography is the most common and effective breast cancer screening test. However, the rate of positive findings is very low, making the radiologic interpretation monotonous and biased toward errors. In an attempt to alleviate radiological workload, this work presents a computer-aided diagnosis (CAD x) method aimed to automatically classify tumor lesions into malign or benign as a means to a second opinion. The CAD x methos, extracts image features, and classifies the screening mammogram abnormality into one of two categories: subject at risk of having malignant tumor (malign), and healthy subject (benign). In this study, 143 abnormal segmentation s (57 malign and 86 benign) from the Breast Cancer Digital Repository (BCD R) public database were used to train and evaluate the CAD x system. Percentile-rank (p-rank) was used to standardize the data. Using the LASSO feature selection methodology, the model achieved a Leave-one-out-cross-validation area under the receiver operating characteristic curve (Auc) of 0.950. The proposed method has the potential to rank abnormal lesions with high probability of malignant findings aiding in the detection of potential malign cases as a second opinion to the radiologist. (Author)

  11. Breast cancer tumor classification using LASSO method selection approach

    Energy Technology Data Exchange (ETDEWEB)

    Celaya P, J. M.; Ortiz M, J. A.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Garza V, I.; Martinez F, M.; Ortiz R, J. M., E-mail: morvymm@yahoo.com.mx [Universidad Autonoma de Zacatecas, Av. Ramon Lopez Velarde 801, Col. Centro, 98000 Zacatecas, Zac. (Mexico)

    2016-10-15

    Breast cancer is one of the leading causes of deaths worldwide among women. Early tumor detection is key in reducing breast cancer deaths and screening mammography is the widest available method for early detection. Mammography is the most common and effective breast cancer screening test. However, the rate of positive findings is very low, making the radiologic interpretation monotonous and biased toward errors. In an attempt to alleviate radiological workload, this work presents a computer-aided diagnosis (CAD x) method aimed to automatically classify tumor lesions into malign or benign as a means to a second opinion. The CAD x methos, extracts image features, and classifies the screening mammogram abnormality into one of two categories: subject at risk of having malignant tumor (malign), and healthy subject (benign). In this study, 143 abnormal segmentation s (57 malign and 86 benign) from the Breast Cancer Digital Repository (BCD R) public database were used to train and evaluate the CAD x system. Percentile-rank (p-rank) was used to standardize the data. Using the LASSO feature selection methodology, the model achieved a Leave-one-out-cross-validation area under the receiver operating characteristic curve (Auc) of 0.950. The proposed method has the potential to rank abnormal lesions with high probability of malignant findings aiding in the detection of potential malign cases as a second opinion to the radiologist. (Author)

  12. YM2: Continuum expectations, lattice convergence, and lassos

    International Nuclear Information System (INIS)

    Driver, B.K.

    1989-01-01

    The two dimensional Yang-Mills theory (YM 2 ) is analyzed in both the continuum and the lattice. In the complete axial gauge the continuum theory may be defined in terms of a Lie algebra valued white noise, and parallel translation may be defined by stochastic differential equations. This machinery is used to compute the expectations of gauge invariant functions of the parallel translation operators along a collection of curves C. The expectation values are expressed as finite dimensional integrals with densities that are products of the heat kernel on the structure group. The time parameters of the heat kernels are determined by the areas enclosed by the collection C, and the arguments are determined by the crossing topologies of the curves in C. The expectations for the Wilson lattice models have a similar structure, and from this it follows that in the limit of small lattice spacing the lattice expectations converge to the continuum expectations. It is also shown that the lasso variables advocated by L. Gross exist and are sufficient to generate all the measurable functions on the YM 2 -measure space. (orig.)

  13. Biodegradation of Aged Residues of Atrazine and Alachlor in a Mix-Load Site Soil by Fungal Enzymes

    OpenAIRE

    Chirnside, Anastasia E. M.; Ritter, William F.; Radosevich, Mark

    2011-01-01

    Soils from bulk pesticide mixing and loading (mix-load) sites are often contaminated with a complex mixture of pesticides, herbicides, and other organic compounds used in pesticide formulations that limits the success of remediation efforts. Therefore, there is a need to find remediation strategies that can successfully clean up these mix-load site soils. This paper examined the degradation of atrazine (2-chloro-4-ethylamino-6-isopropylamino-S-triazine; AT) and alachlor (2-chloro- 2  , 6  -...

  14. Effect of controlled release formulations of diuron and alachlor herbicides on the biochemical activity of agricultural soils.

    Science.gov (United States)

    Tejada, Manuel; Morillo, Esmeralda; Gómez, Isidoro; Madrid, Fernando; Undabeytia, Tomás

    2017-01-15

    The use of pesticides in agriculture is essential because it reduces the economic losses caused by pests, improving crop yields. In spite of the growing number of studies concerning the development and application of controlled release formulations (CRFs) of pesticides in agricultural soils, there are no studies about the effects of such formulations on the biochemical properties. In this paper the dissipation of diuron and alachlor in three agricultural soils for 127days, applied either as commercial or CRFs, was determined as well as their concomitant effects on soil biochemical properties. Dehydrogenase, urease, β-glucosidase and phosphatase activities were measured thought the experimental period. The application of alachlor as CRF increases its half-life time in soils, whereas no differences were noticed between diuron formulations due to its slower degradation, which takes longer than its release from the CRF. At the end of the incubation period, the enzymatic activities were the same after the use of diuron either as commercial or CRF, recovering the soil previous status. For alachlor formulations, no differences in enzymatic activities were again observed between both formulations, but their levels in soils were enhanced. Therefore, the use of these CRFs does not adversely affect the soil biochemical properties. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. Building interpretable predictive models for pediatric hospital readmission using Tree-Lasso logistic regression.

    Science.gov (United States)

    Jovanovic, Milos; Radovanovic, Sandro; Vukicevic, Milan; Van Poucke, Sven; Delibasic, Boris

    2016-09-01

    Quantification and early identification of unplanned readmission risk have the potential to improve the quality of care during hospitalization and after discharge. However, high dimensionality, sparsity, and class imbalance of electronic health data and the complexity of risk quantification, challenge the development of accurate predictive models. Predictive models require a certain level of interpretability in order to be applicable in real settings and create actionable insights. This paper aims to develop accurate and interpretable predictive models for readmission in a general pediatric patient population, by integrating a data-driven model (sparse logistic regression) and domain knowledge based on the international classification of diseases 9th-revision clinical modification (ICD-9-CM) hierarchy of diseases. Additionally, we propose a way to quantify the interpretability of a model and inspect the stability of alternative solutions. The analysis was conducted on >66,000 pediatric hospital discharge records from California, State Inpatient Databases, Healthcare Cost and Utilization Project between 2009 and 2011. We incorporated domain knowledge based on the ICD-9-CM hierarchy in a data driven, Tree-Lasso regularized logistic regression model, providing the framework for model interpretation. This approach was compared with traditional Lasso logistic regression resulting in models that are easier to interpret by fewer high-level diagnoses, with comparable prediction accuracy. The results revealed that the use of a Tree-Lasso model was as competitive in terms of accuracy (measured by area under the receiver operating characteristic curve-AUC) as the traditional Lasso logistic regression, but integration with the ICD-9-CM hierarchy of diseases provided more interpretable models in terms of high-level diagnoses. Additionally, interpretations of models are in accordance with existing medical understanding of pediatric readmission. Best performing models have

  16. Exact Covariance Thresholding into Connected Components for Large-Scale Graphical Lasso.

    Science.gov (United States)

    Mazumder, Rahul; Hastie, Trevor

    2012-03-01

    We consider the sparse inverse covariance regularization problem or graphical lasso with regularization parameter λ. Suppose the sample covariance graph formed by thresholding the entries of the sample covariance matrix at λ is decomposed into connected components. We show that the vertex-partition induced by the connected components of the thresholded sample covariance graph (at λ) is exactly equal to that induced by the connected components of the estimated concentration graph, obtained by solving the graphical lasso problem for the same λ. This characterizes a very interesting property of a path of graphical lasso solutions. Furthermore, this simple rule, when used as a wrapper around existing algorithms for the graphical lasso, leads to enormous performance gains. For a range of values of λ, our proposal splits a large graphical lasso problem into smaller tractable problems, making it possible to solve an otherwise infeasible large-scale problem. We illustrate the graceful scalability of our proposal via synthetic and real-life microarray examples.

  17. Single-step uncalcined N-TiO{sub 2} synthesis, characterizations and its applications on alachlor photocatalytic degradations

    Energy Technology Data Exchange (ETDEWEB)

    Suwannaruang, Totsaporn, E-mail: totsaporn.eng.kku@gmail.com [Department of Chemical Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002 (Thailand); Chemical Kinetics and Applied Catalysis Laboratory (CKCL), Faculty of Engineering, Khon Kaen University, Khon Kaen 40002 (Thailand); Wantala, Kitirote, E-mail: kitirote@kku.ac.th [Department of Chemical Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002 (Thailand); Chemical Kinetics and Applied Catalysis Laboratory (CKCL), Faculty of Engineering, Khon Kaen University, Khon Kaen 40002 (Thailand); Research Center for Environmental and Hazardous Substance Management (EHSM), Faculty of Engineering, Khon Kaen University, Khon Kaen 40002 (Thailand)

    2016-09-01

    Graphical abstract: - Highlights: • N-TiO{sub 2} can be synthesized on one crystal in one particle. • Surface area has been relating to performance of photocatalysts. • Energy band-gap of N-TiO{sub 2} show lower than 3.0 eV. - Abstract: The aims of this research were to synthesize nitrogen doped TiO{sub 2} (N-TiO{sub 2}) photocatalysts produced by hydrothermal technique and to test the degradation performance of alachlor by photocatalytic process under UV irradiations in the effect of aging temperature and time in the preparation process. The characterizations of synthesized TiO{sub 2} such as specific surface area, particle size, phase structure and elements were analyzed by using the Brunauer–Emmett–Teller (BET) technique, Transmission Electron Microscopy (TEM), X-ray Diffractometer (XRD) and Energy Dispersive X-ray spectrometer (EDX), respectively. The Central Composite Design (CCD) was used to design the experiment to determine the optimal condition, main effects and their interactions by using specific surface area, percent alachlor removal and observed first-order rate constant as responses. The kinetic reactions of alachlor degradation were explained by using Langmuir-Hinshelwood expression to confirm the reaction took place on the surface of photocatalyst. The results showed that the effect of aging temperatures was significant on surface area, whereas aging time was insignificant. Additionally, the square term of aging temperature and interaction term were shown significant on the specific surface area as well. The highest specific surface area from response surface at aging temperature between 150–175 °C and aging time between 6–13 h was found in a range of 100–106 m{sup 2}/g. The average particle size of TiO{sub 2} was similar to crystallite size. Therefore, it can be concluded that one particle has only one crystal. The element analysis has shown 10% of nitrogen in TiO{sub 2} structure that the energy band-gap about 2.95 eV was found

  18. Degradation rates of alachlor, atrazine and bentazone in the profiles of Polish Luvisols

    Science.gov (United States)

    Paszko, Tadeusz; Muszyński, Paweł

    2017-07-01

    The degradation rates of three herbicides (alachlor, atrazine, and bentazone) were examined according to OECD Guideline 307 in three profiles of grey-brown podzolic soil (Luvisol) in a laboratory experiment. The aim of the experiment was to determine herbicide degradation parameters and their relationships with soil properties. Degradation processes were effectively described by a first-order model. However, in some cases, the best results were produced by bi-phasic kinetics (hockey-stick and bi-exponential model). The degradation rates of the tested herbicides at 25°C and 40% maximum water holding capacity, established based on half-life values in the Ap horizon, increased in the following order: atrazine (32.6-42.8 days) herbicide degradation rates and the organic matter content of soils. The depth-dependent degradation factors obtained for topsoil and two subsoil horizons (1: 0.42: 0.11 - based on average values, and 1: 0.31: 0.12 - based on median values) reflect the degradation abilities of Polish Luvisols. The values noted are soil-specific; therefore, they can also be applied to other pesticides in Polish Luvisols.

  19. Multivariate sparse group lasso for the multivariate multiple linear regression with an arbitrary group structure.

    Science.gov (United States)

    Li, Yanming; Nan, Bin; Zhu, Ji

    2015-06-01

    We propose a multivariate sparse group lasso variable selection and estimation method for data with high-dimensional predictors as well as high-dimensional response variables. The method is carried out through a penalized multivariate multiple linear regression model with an arbitrary group structure for the regression coefficient matrix. It suits many biology studies well in detecting associations between multiple traits and multiple predictors, with each trait and each predictor embedded in some biological functional groups such as genes, pathways or brain regions. The method is able to effectively remove unimportant groups as well as unimportant individual coefficients within important groups, particularly for large p small n problems, and is flexible in handling various complex group structures such as overlapping or nested or multilevel hierarchical structures. The method is evaluated through extensive simulations with comparisons to the conventional lasso and group lasso methods, and is applied to an eQTL association study. © 2015, The International Biometric Society.

  20. Inference for feature selection using the Lasso with high-dimensional data

    DEFF Research Database (Denmark)

    Brink-Jensen, Kasper; Ekstrøm, Claus Thorn

    2014-01-01

    Penalized regression models such as the Lasso have proved useful for variable selection in many fields - especially for situations with high-dimensional data where the numbers of predictors far exceeds the number of observations. These methods identify and rank variables of importance but do...... not generally provide any inference of the selected variables. Thus, the variables selected might be the "most important" but need not be significant. We propose a significance test for the selection found by the Lasso. We introduce a procedure that computes inference and p-values for features chosen...... by the Lasso. This method rephrases the null hypothesis and uses a randomization approach which ensures that the error rate is controlled even for small samples. We demonstrate the ability of the algorithm to compute $p$-values of the expected magnitude with simulated data using a multitude of scenarios...

  1. Effects of the herbicides linuron and S-metolachlor on Perez's frog embryos.

    Science.gov (United States)

    Quintaneiro, Carla; Soares, Amadeu M V M; Monteiro, Marta S

    2018-03-01

    Presence of pesticides in the environment and their possible effects on aquatic organisms are of great concern worldwide. The extensive use of herbicides in agricultural areas are one of the factors contributing to the known decline of amphibian populations. Thus, as non-target species, amphibians can be exposed in early life stages to herbicides in aquatic systems. In this context, this study aims to evaluate effects of increasing concentrations of two maize herbicides, linuron and S-metolachlor on embryos of the Perez' frog (Pelophylax perezi) during 192 h. Apical endpoints were determined for each herbicide: mortality, hatching rate, malformations and length. Frog embryos presented a LC 50 of 21 mg/l linuron and 37.5 mg/l S-metolachlor. Furthermore, sub-lethal concentrations of both herbicides affected normal embryonic development, delaying hatching, decreasing larvae length and causing several malformations. Length of larvae decreased with increasing concentrations of each herbicide, even at the lower concentrations tested. Malformations observed in larvae exposed to both herbicides were oedemas, spinal curvature and deformation, blistering and microphtalmia. Overall, these results highlight the need to assess adverse effects of xenobiotics to early life stages of amphibians regarding beside mortality the embryonic development, which could result in impairments at later stages. However, to unravel mechanisms involved in toxicity of these herbicides further studies regarding lower levels of biological organisation such as biochemical and genomic level should be performed. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Association between biomarkers and clinical characteristics in chronic subdural hematoma patients assessed with lasso regression.

    Directory of Open Access Journals (Sweden)

    Are Hugo Pripp

    Full Text Available Chronic subdural hematoma (CSDH is characterized by an "old" encapsulated collection of blood and blood breakdown products between the brain and its outermost covering (the dura. Recognized risk factors for development of CSDH are head injury, old age and using anticoagulation medication, but its underlying pathophysiological processes are still unclear. It is assumed that a complex local process of interrelated mechanisms including inflammation, neomembrane formation, angiogenesis and fibrinolysis could be related to its development and propagation. However, the association between the biomarkers of inflammation and angiogenesis, and the clinical and radiological characteristics of CSDH patients, need further investigation. The high number of biomarkers compared to the number of observations, the correlation between biomarkers, missing data and skewed distributions may limit the usefulness of classical statistical methods. We therefore explored lasso regression to assess the association between 30 biomarkers of inflammation and angiogenesis at the site of lesions, and selected clinical and radiological characteristics in a cohort of 93 patients. Lasso regression performs both variable selection and regularization to improve the predictive accuracy and interpretability of the statistical model. The results from the lasso regression showed analysis exhibited lack of robust statistical association between the biomarkers in hematoma fluid with age, gender, brain infarct, neurological deficiencies and volume of hematoma. However, there were associations between several of the biomarkers with postoperative recurrence requiring reoperation. The statistical analysis with lasso regression supported previous findings that the immunological characteristics of CSDH are local. The relationship between biomarkers, the radiological appearance of lesions and recurrence requiring reoperation have been inclusive using classical statistical methods on these data

  3. Non-Asymptotic Oracle Inequalities for the High-Dimensional Cox Regression via Lasso.

    Science.gov (United States)

    Kong, Shengchun; Nan, Bin

    2014-01-01

    We consider finite sample properties of the regularized high-dimensional Cox regression via lasso. Existing literature focuses on linear models or generalized linear models with Lipschitz loss functions, where the empirical risk functions are the summations of independent and identically distributed (iid) losses. The summands in the negative log partial likelihood function for censored survival data, however, are neither iid nor Lipschitz.We first approximate the negative log partial likelihood function by a sum of iid non-Lipschitz terms, then derive the non-asymptotic oracle inequalities for the lasso penalized Cox regression using pointwise arguments to tackle the difficulties caused by lacking iid Lipschitz losses.

  4. Dictionary-Based Image Denoising by Fused-Lasso Atom Selection

    Directory of Open Access Journals (Sweden)

    Ao Li

    2014-01-01

    Full Text Available We proposed an efficient image denoising scheme by fused lasso with dictionary learning. The scheme has two important contributions. The first one is that we learned the patch-based adaptive dictionary by principal component analysis (PCA with clustering the image into many subsets, which can better preserve the local geometric structure. The second one is that we coded the patches in each subset by fused lasso with the clustering learned dictionary and proposed an iterative Split Bregman to solve it rapidly. We present the capabilities with several experiments. The results show that the proposed scheme is competitive to some excellent denoising algorithms.

  5. Manejo de plantas daninhas na cultura do algodoeiro com S-metolachlor e trifloxysulfuron-sodium em sistema de plantio convencional Weed Management with S-metolachlor and trifloxysulfuron-sodium in cotton field

    Directory of Open Access Journals (Sweden)

    R.S. Freitas

    2006-06-01

    Full Text Available Objetivou-se com este trabalho desenvolver tecnologia para manejo de plantas daninhas na cultura do algodoeiro, em sistema de plantio convencional, combinando os herbicidas S-metolachlor em pré-emergência com trifloxysulfuron-sodium em pós-emergência. Foram avaliados 14 tratamentos, em arranjo fatorial 3 x 4 (três doses de S-metolachlor: 384, 768 e 1.152 g ha-1 e quatro doses de trifloxysulfuron-sodium: 0,0; 2,625; 5,250; e 7,875 g ha-1, mais duas testemunhas (com e sem convivência com as plantas daninhas por todo o ciclo do algodoeiro, em delineamento de blocos casualizados, com quatro repetições. Na área, foi verificada a presença das seguintes espécies daninhas: Alternanthera tenella, representando mais de 80% do total, Bidens spp., Acanthospermum hispidum, Cenchrus echinatus, Digitaria horizontalis, Eleusine indica e Commelina benghalensis. S-metolachlor apresentou alta eficiência no controle de A. tenella, C. echinatus, D. horizontalis, E. indica e C. benghalensis. Trifloxysulfuron-sodium controlou as espécies dicotiledôneas eficientemente. Os tratamentos que proporcionaram melhor produtividade de algodão em caroço foram Smetolachlor (768 g ha-1 mais trifloxysulfuron-sodium (7,875 g ha-1 e S-metolachlor (1.152 g ha-1 mais trifloxysulfuron-sodium (5,250 e 7,875 g ha-1. O melhor controle de plantas daninhas na colheita do algodão foi obtido com 1.152 g ha-1 de S-metolachlor mais 7,875 g ha-1 de trifloxysulfuron-sodium.This work aimed to develop a strategy for weed management in conventionally tilled cotton by combining the herbicides S-metolachlor in pre-emergence and trifloxysulfuron-sodium in post-emergence. Fourteen treatments were evaluated arranged in a factorial scheme 3 (three doses of S-metolachlor 384; 768 and 1,152 g ha-1 x 4 (four doses of trifloxysulfuron-sodium 0.0; 2.625; 5.250 and 7.875 g ha-1, plus two controls (with and without weeds throughout the cotton planting cycle. The following weed species were

  6. Accurate mass analysis of ethanesulfonic acid degradates of acetochlor and alachlor using high-performance liquid chromatography and time-of-flight mass spectrometry

    Science.gov (United States)

    Thurman, E.M.; Ferrer, I.; Parry, R.

    2002-01-01

    Degradates of acetochlor and alachlor (ethanesulfonic acids, ESAs) were analyzed in both standards and in a groundwater sample using high-performance liquid chromatography-time-of-flight mass spectrometry with electrospray ionization. The negative pseudomolecular ion of the secondary amide of acetochlor ESA and alachlor ESA gave average masses of 256.0750??0.0049 amu and 270.0786??0.0064 amu respectively. Acetochlor and alachlor ESA gave similar masses of 314.1098??0.0061 amu and 314.1153??0.0048 amu; however, they could not be distinguished by accurate mass because they have the same empirical formula. On the other hand, they may be distinguished using positive-ion electrospray because of different fragmentation spectra, which did not occur using negative-ion electrospray.

  7. Variable Levels of Glutathione S-Transferases Are Responsible for the Differential Tolerance to Metolachlor between Maize (Zea mays) Shoots and Roots.

    Science.gov (United States)

    Li, Dongzhi; Xu, Li; Pang, Sen; Liu, Zhiqian; Wang, Kai; Wang, Chengju

    2017-01-11

    Glutathione S-transferases (GSTs) play important roles in herbicide tolerance. However, studies on GST function in herbicide tolerance among plant tissues are still lacking. To explore the mechanism of metolachlor tolerance difference between maize shoots and roots, the effects of metolachlor on growth, GST activity, and the expression of the entire GST gene family were investigated. It was found that this differential tolerance to metolachlor was correlated with contrasting GST activity between the two tissues and can be eliminated by a GST inhibitor. An in vitro metolachlor-glutathione conjugation assay confirmed that the transformation of metolachlor is 2-fold faster in roots than in shoots. The expression analysis of the GST gene family revealed that most GST genes are expressed much higher in roots than shoots, both in control and in metolachlor-treated plants. Taken together, higher level expression of most GST genes, leading to higher GST activity and faster herbicide transformation, appears to be responsible for the higher tolerance to metolachlor of maize roots than shoots.

  8. Phytotoxicity of Alachlor, Bromacil and Diuron as single or mixed herbicides applied to wheat, melon, and molokhia

    OpenAIRE

    El-Nahhal, Yasser; Hamdona, Nisreen

    2015-01-01

    This study investigated the phytotoxicity of herbicides applied singly or as mixtures to different crops under greenhouse conditions. Growth inhibition of the crops was taken as an indicator of phytotoxicity. Phytotoxicity of mixtures was estimated by calculating EC50 value in toxic units. EC50 (mg/kg soil) of Alachlor, Bromacil and/or Diuron were: 11.37, 4.77, 1.64, respectively, on melon; 0.11, 0.08, 0.24, respectively, on molokhia, and 3.91, 3.08, 1.83, respectively, on wheat. EC50 values ...

  9. Detection of radionuclides from weak and poorly resolved spectra using Lasso and subsampling techniques

    International Nuclear Information System (INIS)

    Bai, Er-Wei; Chan, Kung-sik; Eichinger, William; Kump, Paul

    2011-01-01

    We consider a problem of identification of nuclides from weak and poorly resolved spectra. A two stage algorithm is proposed and tested based on the principle of majority voting. The idea is to model gamma-ray counts as Poisson processes. Then, the average part is taken to be the model and the difference between the observed gamma-ray counts and the average is considered as random noise. In the linear part, the unknown coefficients correspond to if isotopes of interest are present or absent. Lasso types of algorithms are applied to find non-vanishing coefficients. Since Lasso or any prediction error based algorithm is inconsistent with variable selection for finite data length, an estimate of parameter distribution based on subsampling techniques is added in addition to Lasso. Simulation examples are provided in which the traditional peak detection algorithms fail to work and the proposed two stage algorithm performs well in terms of both the False Negative and False Positive errors. - Highlights: → Identification of nuclides from weak and poorly resolved spectra. → An algorithm is proposed and tested based on the principle of majority voting. → Lasso types of algorithms are applied to find non-vanishing coefficients. → An estimate of parameter distribution based on sub-sampling techniques is included. → Simulations compare the results of the proposed method with those of peak detection.

  10. Detection of radionuclides from weak and poorly resolved spectra using Lasso and subsampling techniques

    Energy Technology Data Exchange (ETDEWEB)

    Bai, Er-Wei, E-mail: er-wei-bai@uiowa.edu [Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242 (United States); Chan, Kung-sik, E-mail: kung-sik-chan@uiowa.edu [Department of Statistical and Actuarial Science, University of Iowa, Iowa City, IA 52242 (United States); Eichinger, William, E-mail: william-eichinger@uiowa.edu [Department of Civil and Environmental Engineering, University of Iowa, Iowa City, IA 52242 (United States); Kump, Paul [Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242 (United States)

    2011-10-15

    We consider a problem of identification of nuclides from weak and poorly resolved spectra. A two stage algorithm is proposed and tested based on the principle of majority voting. The idea is to model gamma-ray counts as Poisson processes. Then, the average part is taken to be the model and the difference between the observed gamma-ray counts and the average is considered as random noise. In the linear part, the unknown coefficients correspond to if isotopes of interest are present or absent. Lasso types of algorithms are applied to find non-vanishing coefficients. Since Lasso or any prediction error based algorithm is inconsistent with variable selection for finite data length, an estimate of parameter distribution based on subsampling techniques is added in addition to Lasso. Simulation examples are provided in which the traditional peak detection algorithms fail to work and the proposed two stage algorithm performs well in terms of both the False Negative and False Positive errors. - Highlights: > Identification of nuclides from weak and poorly resolved spectra. > An algorithm is proposed and tested based on the principle of majority voting. > Lasso types of algorithms are applied to find non-vanishing coefficients. > An estimate of parameter distribution based on sub-sampling techniques is included. > Simulations compare the results of the proposed method with those of peak detection.

  11. LASSO-ligand activity by surface similarity order: a new tool for ligand based virtual screening.

    Science.gov (United States)

    Reid, Darryl; Sadjad, Bashir S; Zsoldos, Zsolt; Simon, Aniko

    2008-01-01

    Virtual Ligand Screening (VLS) has become an integral part of the drug discovery process for many pharmaceutical companies. Ligand similarity searches provide a very powerful method of screening large databases of ligands to identify possible hits. If these hits belong to new chemotypes the method is deemed even more successful. eHiTS LASSO uses a new interacting surface point types (ISPT) molecular descriptor that is generated from the 3D structure of the ligand, but unlike most 3D descriptors it is conformation independent. Combined with a neural network machine learning technique, LASSO screens molecular databases at an ultra fast speed of 1 million structures in under 1 min on a standard PC. The results obtained from eHiTS LASSO trained on relatively small training sets of just 2, 4 or 8 actives are presented using the diverse directory of useful decoys (DUD) dataset. It is shown that over a wide range of receptor families, eHiTS LASSO is consistently able to enrich screened databases and provides scaffold hopping ability.

  12. On the Oracle Property of the Adaptive LASSO in Stationary and Nonstationary Autoregressions

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl

    We show that the Adaptive LASSO is oracle efficient in stationary and non-stationary autoregressions. This means that it estimates parameters consistently, selects the correct sparsity pattern, and estimates the coefficients belonging to the relevant variables at the same asymptotic efficiency...

  13. Breakthrough dynamics of s-metolachlor metabolites in drinking water wells: Transport pathways and time to trend reversal

    Science.gov (United States)

    Farlin, Julien; Gallé, Tom; Bayerle, Michael; Pittois, Denis; Köppchen, Stephan; Krause, Martina; Hofmann, Diana

    2018-06-01

    We present the results of a two years study on the contamination of the Luxembourg Sandstone aquifer by metolachlor-ESA and metolachlor-OXA, two major transformation products of s-metolachlor. The aim of the study was twofold: (i) assess whether elevated concentrations of both transformation products (up to 1000 ng/l) were due to fast flow breakthough events of short duration or the signs of a contamination of the entire aquifer and (ii) estimate the time to trend reversal once the parent compound was withdrawn from the market. These two questions were addressed by a combined use of groundwater monitoring, laboratory experiments and numerical simulations of the fate of the degradation products in the subsurface. Twelve springs were sampled weekly over an eighteen month period, and the degradation rates of both the parent compound and its transformation products were measured on a representative soil in the laboratory using a radiolabeled precursor. Modelling with the numeric code PEARL simulating pesticide fate in soil coupled to a simple transfer function model for the aquifer compartment, and calibrated from the field and laboratory data, predicts a significant damping by the aquifer of the peaks of concentration of both metolachlor-ESA and -OXA leached from the soil. The time to trend reversal following the ban of s-metolachlor in spring protection zones should be observed before the end of the decade, while the return of contaminant concentrations below the drinking water limit of 100 ng/l however is expected to last up to twelve years. The calculated contribution to total water discharge of the fast-flow component from cropland and short-circuiting the aquifer was small in most springs (median of 1.2%), but sufficient to cause additional peaks of concentration of several hundred nanograms per litre in spring water. These peaks are superimposed on the more steady contamination sustained by the base flow, and should cease immediately once application of the

  14. Enhancement of Catalytic Performance of MCM-41 Synthesized with Rice Husk Silica by Addition of Titanium Dioxide for Photodegradation of Alachlor

    Directory of Open Access Journals (Sweden)

    Surachai Artkla

    2009-01-01

    Full Text Available Photocatalytic degradation of alachlor, a herbicide, in water on both bare TiO2 and TiO2 supported on mesoporous material, marked as TiO2/RH-MCM-41 were studied. The RH-MCM-41 support was synthesized from rice husk silica and other reagents by hydrothermal method. The required amount of titanium precursor (TiO2 P25 Degussa to give 10-60% was mixed with RH-MCM-41 and calcined at 300 °C for 6 h. The catalytic activities of TiO2 and TiO2/RH-MCM-41 for alachlor degradation were performed under UV radiation with wavelength of 300 nm. The ratio of catalyst weight to volume of alachlor solution was 1 g/L and all products were characterized by high performance liquid chromatograph. The reaction equilibrium was established in 30 min. in deionized water without adjusting the solution pH. The TiO2/RH-MCM-41 could adsorb alachlor more than the bare TiO2 (namely, 17% vs. 5% and the photocatalytic activity of alachlor degration on all TiO2/RH-MCM-41s was higher than that on the bare TiO2. By comparison per weight of TiO2, the 10%TiO2/RH-MCM-41 gave the highest alachlor conversion of 100% after 20 min. while 1% bare TiO2 showed conversion of 95%.

  15. Validating the LASSO algorithm by unmixing spectral signatures in multicolor phantoms

    Science.gov (United States)

    Samarov, Daniel V.; Clarke, Matthew; Lee, Ji Yoon; Allen, David; Litorja, Maritoni; Hwang, Jeeseong

    2012-03-01

    As hyperspectral imaging (HSI) sees increased implementation into the biological and medical elds it becomes increasingly important that the algorithms being used to analyze the corresponding output be validated. While certainly important under any circumstance, as this technology begins to see a transition from benchtop to bedside ensuring that the measurements being given to medical professionals are accurate and reproducible is critical. In order to address these issues work has been done in generating a collection of datasets which could act as a test bed for algorithms validation. Using a microarray spot printer a collection of three food color dyes, acid red 1 (AR), brilliant blue R (BBR) and erioglaucine (EG) are mixed together at dierent concentrations in varying proportions at dierent locations on a microarray chip. With the concentration and mixture proportions known at each location, using HSI an algorithm should in principle, based on estimates of abundances, be able to determine the concentrations and proportions of each dye at each location on the chip. These types of data are particularly important in the context of medical measurements as the resulting estimated abundances will be used to make critical decisions which can have a serious impact on an individual's health. In this paper we present a novel algorithm for processing and analyzing HSI data based on the LASSO algorithm (similar to "basis pursuit"). The LASSO is a statistical method for simultaneously performing model estimation and variable selection. In the context of estimating abundances in an HSI scene these so called "sparse" representations provided by the LASSO are appropriate as not every pixel will be expected to contain every endmember. The algorithm we present takes the general framework of the LASSO algorithm a step further and incorporates the rich spatial information which is available in HSI to further improve the estimates of abundance. We show our algorithm's improvement

  16. Runoff and leaching of metolachlor from Mississippi River alluvial soil during seasons of average and below-average rainfall.

    Science.gov (United States)

    Southwick, Lloyd M; Appelboom, Timothy W; Fouss, James L

    2009-02-25

    The movement of the herbicide metolachlor [2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl)acetamide] via runoff and leaching from 0.21 ha plots planted to corn on Mississippi River alluvial soil (Commerce silt loam) was measured for a 6-year period, 1995-2000. The first three years received normal rainfall (30 year average); the second three years experienced reduced rainfall. The 4-month periods prior to application plus the following 4 months after application were characterized by 1039 +/- 148 mm of rainfall for 1995-1997 and by 674 +/- 108 mm for 1998-2000. During the normal rainfall years 216 +/- 150 mm of runoff occurred during the study seasons (4 months following herbicide application), accompanied by 76.9 +/- 38.9 mm of leachate. For the low-rainfall years these amounts were 16.2 +/- 18.2 mm of runoff (92% less than the normal years) and 45.1 +/- 25.5 mm of leachate (41% less than the normal seasons). Runoff of metolachlor during the normal-rainfall seasons was 4.5-6.1% of application, whereas leaching was 0.10-0.18%. For the below-normal periods, these losses were 0.07-0.37% of application in runoff and 0.22-0.27% in leachate. When averages over the three normal and the three less-than-normal seasons were taken, a 35% reduction in rainfall was characterized by a 97% reduction in runoff loss and a 71% increase in leachate loss of metolachlor on a percent of application basis. The data indicate an increase in preferential flow in the leaching movement of metolachlor from the surface soil layer during the reduced rainfall periods. Even with increased preferential flow through the soil during the below-average rainfall seasons, leachate loss (percent of application) of the herbicide remained below 0.3%. Compared to the average rainfall seasons of 1995-1997, the below-normal seasons of 1998-2000 were characterized by a 79% reduction in total runoff and leachate flow and by a 93% reduction in corresponding metolachlor movement via these routes

  17. Effects of an atrazine, metolachlor and fipronil mixture on Hyalella azteca (Saussure) in a modified backwater wetland.

    Science.gov (United States)

    Lizotte, Richard E; Knight, Scott S; Shields, F Douglas; Bryant, Charles T

    2009-12-01

    We examined the toxicity mitigation efficiency of a hydrologically modified backwater wetland amended with a pesticide mixture of atrazine, metolachlor, and fipronil, using 96 h survival bioassays with Hyalella azteca. Significant H. azteca 96 h mortality occurred within the first 2 h of amendment at the upstream amendment site but not at any time at the downstream site. H. azteca survival varied spatially and temporally in conjunction with measured pesticide mixture concentrations. Hyalella azteca 96 h survival pesticide mixture effects concentrations ranges were 10.214–11.997, 5.822–6.658, 0.650–0.817, and 0.030–0.048 μg L−1 for atrazine, metolachlor, fipronil, and fipronil-sulfone, respectively.

  18. Buffer strip effect on terbuthylazine, desethyl-terbuthylazine and S-metolachlor runoff from maize fields in Northern Italy.

    Science.gov (United States)

    Milan, Marco; Vidotto, Francesco; Piano, Serenella; Negre, Michèle; Ferrero, Aldo

    2013-01-01

    The effectiveness of a 6 m wide vegetative buffer strip for reducing runoff of S-metolachlor, terbuthylazine and desethyl-terbuthylazine was studied in 2007-2008 in Northern Italy. Two cultivated fields, with and without the buffer strip, were compared. Residues of the chemicals were investigated in runoff water collected after runoff events and their dissipation in the soil was studied. The highest concentration of the chemicals in water occurred in samples collected from the unbuffered field at the first runoff events. Losses of terbuthylazine and S-metolachlor in runoff waters were particularly high in 2007 (2.6% and 0.9% of the amount applied, respectively). Soil half-life of terbuthylazine and S-metolachlor ranged between 12.1 and 8.9 days and 16 and 7 days, respectively. The presence of desethyl-terbuthylazine was related to parent compound degradation. The buffer strip allowed an important reduction of chemical content in water (> 90%), in particular during the first runoff events.

  19. Degradation and leaching of the herbicides metolachlor and diuron: a case study in an area of Northern Italy

    International Nuclear Information System (INIS)

    Barra Caracciolo, A.; Giuliano, G.; Grenni, P.; Guzzella, L.; Pozzoni, F.; Bottoni, P.; Fava, L.; Crobe, A.; Orru, M.; Funari, E.

    2005-01-01

    In this work the degradation of the herbicides metolachlor, diuron, monuron and of the metabolites 2-ethyl-6-methylaniline (EMA), and 3,4-dichloroaniline (DCA) was assessed in laboratory experiments on microbiologically active and sterilized soils. Their leaching potentials were calculated, using Gustafson's equation, by determining their mobility (as K oc ) and persistence (expressed as DT 50 ). Lysimeter experiments were also conducted to assess the actual leaching of the studied herbicides in a cereal crop tillage area vulnerable to groundwater contamination. The data obtained from the field were compared to the laboratory results. Moreover, some compounds of particular concern were searched for in the groundwater located near the experimental area in order to evaluate actual contamination and to test the reliability of the leaching potential. The GUS index, computed on data from microbiologically active soil, shows monuron as a leacher compound, EMA and DCA as non-leachers, metolachlor and diuron as transient ones. The presence of metolachlor in the groundwater monitored, even at concentrations up to 0.1 μg/l, confirms the possibility that transient compounds can be leached if microbial activity has not completely occurred in active surface soil. - Pesticide mobility to vulnerable groundwaters in Italy is assessed and ranked

  20. Dissipation of hydrological tracers and the herbicide S-metolachlor in batch and continuous-flow wetlands.

    Science.gov (United States)

    Maillard, Elodie; Lange, Jens; Schreiber, Steffi; Dollinger, Jeanne; Herbstritt, Barbara; Millet, Maurice; Imfeld, Gwenaël

    2016-02-01

    Pesticide dissipation in wetland systems with regard to hydrological conditions and operational modes is poorly known. Here, we investigated in artificial wetlands the impact of batch versus continuous-flow modes on the dissipation of the chiral herbicide S-metolachlor (S-MET) and hydrological tracers (bromide, uranine and sulforhodamine B). The wetlands received water contaminated with the commercial formulation Mercantor Gold(®) (960 g L(-1) of S-MET, 87% of the S-enantiomer). The tracer mass budget revealed that plant uptake, sorption, photo- and presumably biodegradation were prominent under batch mode (i.e. characterized by alternating oxic-anoxic conditions), in agreement with large dissipation of S-MET (90%) under batch mode. Degradation was the main dissipation pathway of S-MET in the wetlands. The degradate metolachlor oxanilic acid (MOXA) mainly formed under batch mode, whereas metolachlor ethanesulfonic acid (MESA) prevailed under continuous-flow mode, suggesting distinct degradation pathways in each wetland. R-enantiomer was preferentially degraded under batch mode, which indicated enantioselective biodegradation. The release of MESA and MOXA by the wetlands as well as the potential persistence of S-MET compared to R-MET under both oxic and anoxic conditions may be relevant for groundwater and ecotoxicological risk assessment. This study shows the effect of batch versus continuous modes on pollutant dissipation in wetlands, and that alternate biogeochemical conditions under batch mode enhance S-MET biodegradation. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Cross-resistance to prosulfocarb + S-metolachlor and pyroxasulfone selected by either herbicide in Lolium rigidum.

    Science.gov (United States)

    Busi, Roberto; Powles, Stephen B

    2016-09-01

    Weeds can be a greater constraint to crop production than animal pests and pathogens. Pre-emergence herbicides are crucial in many cropping systems to control weeds that have evolved resistance to selective post-emergence herbicides. In this study we assessed the potential to evolve resistance to the pre-emergence herbicides prosulfocarb + S-metolachlor or pyroxasulfone in 50 individual field Lolium rigidum populations collected in a random survey in Western Australia prior to commercialisation of these pre-emergence herbicides. This study shows for the first time that in randomly collected L. rigidum field populations the selection with either prosulfocarb + S-metolachlor or pyroxasulfone can result in concomitant evolution of resistance to both prosulfocarb + S-metolachlor and pyroxasulfone after three generations. In the major weed L. rigidum, traits conferring resistance to new herbicides can be present before herbicide commercialisation. Proactive and multidisciplinary research (evolutionary ecology, modelling and molecular biology) is required to detect and analyse resistant populations before they can appear in the field. Several studies show that evolved cross-resistance in weeds is complex and often unpredictable. Thus, long-term management of cross-resistant weeds must be achieved through heterogeneity of selection by effective chemical, cultural and physical weed control strategies that can delay herbicide resistance evolution. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  2. Leaching of the S-metolachlor herbicide associated with paraquat or glyphosate in a no-tillage system

    Directory of Open Access Journals (Sweden)

    Anderson Luis Nunes

    2016-09-01

    Full Text Available The combined use of desiccant and residual herbicides is a common management practice under no-tillage systems. However, the effect of desiccant herbicides and mulch on the leaching of residual herbicide is unknown. This study aimed at assessing the leaching of the S-metolachlor herbicide applied to ryegrass sequentially or in association with paraquat or glyphosate. A randomized blocks design was used, with four repetitions and treatments distributed over split-plots. The desiccant herbicides paraquat (600 g ha-1 or glyphosate (720 g ha-1 were used in the main plot, while S-metolachlor (2,800 g ha-1 was applied sequentially or in association with the desiccant herbicides in the subplots. There was also a control containing only desiccant herbicide, with no application of residual herbicide. The type of desiccant did not affect the leaching of the residual herbicide. In addition, the chosen method to apply the residual herbicide, sequentially or in association with the desiccant, did not impact the S-metolachlor behavior in the soil. The bioavailable concentration in the soil, 25 days after the application, was 90 g a.i. ha-1, at a depth of 18 cm.

  3. AN ANALYTIC OUTLOOK OF THE MADRIGAL MORO LASSO AL MIO DUOLO BY GESUALDO DA VENOSA

    Directory of Open Access Journals (Sweden)

    MURARU AUREL

    2015-09-01

    Full Text Available The analysis of the madrigal Moro lasso al mio duolo reveals the melancholic, thoughtful and grieving atmosphere, gene­rating shady, silent, sometimes dark soundscapes. Gesualdo shapes the poliphony through chromatic licenses, in order to create a tense musical discourse, permanently yearning for stability and balance amidst a harmonic construction lacking any attempt for resolution. Thus the strange harmonies of Gesualdo are shaped, giving birth to a unique musical style, full of dissonances and endless musical tension.

  4. Calixarene receptors in the selective separation of alachlor. Characterization of the separated complexes; Receptores calixarenicos en la separacion selectiva de alaclor. Caracterizacion de los complejos separados

    Energy Technology Data Exchange (ETDEWEB)

    Garcia G, M C

    2004-07-01

    Pesticides have been necessary in the agriculture since the plagues control have been remedied thanks to them but it has also provoked pollution. Nowadays, there are several methods which help to decrease or remedy such a pollution provoked. Unfortunately, any of them work out the environmental problem totally. Therefore, alternatives have to be found. The organic and tri dimensional characteristics of these macrocycles afford them a high versatility in such a way that these hosts can interact with organic guests selectively. Alachlor is a chlorinated organic herbicide useful in the plagues control of annual grasses and many broad-leave weeds which grow in maize, peanuts and soyabean. The ability of calixarenes to host organic guests with chemical characteristics similar to pesticides let them to be good candidates to compete with others methods which are used presently to separate organic pesticides. In this direction one of the advantages of proposing the use of calixarenes is, its facility of being modified in the lower and/or upper rims, to adapt them to aqueous, organic, gaseous and aqueous-organic media. Once the characteristics of reagents informed in the literature were confirmed and complemented with others found in this work, we studied, in solution, the interaction of the calixarenes with alachlor using 1 x 10{sup -5} to 1 x 10{sup -3} M solutions in acetonitrile for calixarenes fitted with phosphinoyl pendant arms in the lower rim, B{sub n}bL{sup n}, n= 4, 6) and in chloroform for parents calixarenes (H{sub n}bL{sup n} n = 4, 6, 8). Meticulous studies monitored by UV-Vis and luminescence were carried out, and the best stoichiometry to be used in further studies resulted to be 1(host): 1(alachlor). Therefore, we chose the 1 x 10{sup -4} M concentration to find how long the host-guest should be interacting in order to guarantee the formation in solution of the calixarene-alachlor species. It was found 168 h for the alachlor-B{sub n}bL{sup n} interaction

  5. LASSO observations at McDonald and OCA/CERGA: A preliminary analysis

    Science.gov (United States)

    Veillet, CH.; Fridelance, P.; Feraudy, D.; Boudon, Y.; Shelus, P. J.; Ricklefs, R. L.; Wiant, J. R.

    1993-01-01

    The Laser Synchronization from Synchronous Orbit (LASSO) observations between USA and Europe were made possible with the move of Meteosat 3/P2 toward 50 deg W. Two Lunar Laser Ranging stations participated into the observations: the MLRS at McDonald Observatory (Texas, USA) and OCA/CERGA (Grasse, France). Common sessions were performed since 30 Apr. 1992, and will be continued up to the next Meteosat 3/P2 move further West (planned for January 1993). The preliminary analysis made with the data already collected by the end of Nov. 1992 shows that the precision which can be obtained from LASSO is better than 100 ps, the accuracy depending on how well the stations maintain their time metrology, as well as on the quality of the calibration (still to be made.) For extracting such a precision from the data, the processing has been drastically changed compared to the initial LASSO data analysis. It takes into account all the measurements made, timings on board, and echoes at each station. This complete use of the data increased dramatically the confidence into the synchronization results.

  6. IPF-LASSO: Integrative L1-Penalized Regression with Penalty Factors for Prediction Based on Multi-Omics Data

    Directory of Open Access Journals (Sweden)

    Anne-Laure Boulesteix

    2017-01-01

    Full Text Available As modern biotechnologies advance, it has become increasingly frequent that different modalities of high-dimensional molecular data (termed “omics” data in this paper, such as gene expression, methylation, and copy number, are collected from the same patient cohort to predict the clinical outcome. While prediction based on omics data has been widely studied in the last fifteen years, little has been done in the statistical literature on the integration of multiple omics modalities to select a subset of variables for prediction, which is a critical task in personalized medicine. In this paper, we propose a simple penalized regression method to address this problem by assigning different penalty factors to different data modalities for feature selection and prediction. The penalty factors can be chosen in a fully data-driven fashion by cross-validation or by taking practical considerations into account. In simulation studies, we compare the prediction performance of our approach, called IPF-LASSO (Integrative LASSO with Penalty Factors and implemented in the R package ipflasso, with the standard LASSO and sparse group LASSO. The use of IPF-LASSO is also illustrated through applications to two real-life cancer datasets. All data and codes are available on the companion website to ensure reproducibility.

  7. Dissipation of S-metolachlor in plant and soil and effect on enzymatic activities.

    Science.gov (United States)

    Wołejko, Elżbieta; Kaczyński, Piotr; Łozowicka, Bożena; Wydro, Urszula; Borusiewicz, Andrzej; Hrynko, Izabela; Konecki, Rafał; Snarska, Krystyna; Dec, Dorota; Malinowski, Paweł

    2017-07-01

    The present study aimed at evaluating the dissipation of S-metolachlor (S-MET) at three doses in maize growing on diverse physico-chemical properties of soil. The effect of herbicide on dehydrogenase (DHA) and acid phosphatase (ACP) activity was estimated. A modified QuEChERS method using LC-MS/MS has been developed. The limit of quantification (0.001 mg kg -1 ) and detection (0.0005 mg kg -1 ) were very low for soil and maize samples. The mean recoveries and RSDs for the six spiked levels (0.001-0.5 mg kg -1 ) were 91.3 and 5.8%. The biggest differences in concentration of S-MET in maize were observed between the 28th and 63rd days. The dissipation of S-MET in the alkaline soil was the slowest between the 2nd and 7th days, and in the acidic soil between the 5th and 11th days. DT 50 of S-MET calculated according to the first-order kinetics model was 11.1-14.7 days (soil) and 9.6-13.9 days (maize). The enzymatic activity of soil was higher in the acidic environment. One observed the significant positive correlation of ACP with pH of soil and contents of potassium and magnesium and negative with contents of phosphorus and organic carbon. The results indicated that at harvest time, the residues of S-MET in maize were well below the safety limit for maize. The findings of this study will foster the research on main parameters influencing the dissipation in maize ecosystems.

  8. Pierced Lasso Bundles are a new class of knot-like motifs.

    Directory of Open Access Journals (Sweden)

    Ellinor Haglund

    2014-06-01

    Full Text Available A four-helix bundle is a well-characterized motif often used as a target for designed pharmaceutical therapeutics and nutritional supplements. Recently, we discovered a new structural complexity within this motif created by a disulphide bridge in the long-chain helical bundle cytokine leptin. When oxidized, leptin contains a disulphide bridge creating a covalent-loop through which part of the polypeptide chain is threaded (as seen in knotted proteins. We explored whether other proteins contain a similar intriguing knot-like structure as in leptin and discovered 11 structurally homologous proteins in the PDB. We call this new helical family class the Pierced Lasso Bundle (PLB and the knot-like threaded structural motif a Pierced Lasso (PL. In the current study, we use structure-based simulation to investigate the threading/folding mechanisms for all the PLBs along with three unthreaded homologs as the covalent loop (or lasso in leptin is important in folding dynamics and activity. We find that the presence of a small covalent loop leads to a mechanism where structural elements slipknot to thread through the covalent loop. Larger loops use a piercing mechanism where the free terminal plugs through the covalent loop. Remarkably, the position of the loop as well as its size influences the native state dynamics, which can impact receptor binding and biological activity. This previously unrecognized complexity of knot-like proteins within the helical bundle family comprises a completely new class within the knot family, and the hidden complexity we unraveled in the PLBs is expected to be found in other protein structures outside the four-helix bundles. The insights gained here provide critical new elements for future investigation of this emerging class of proteins, where function and the energetic landscape can be controlled by hidden topology, and should be take into account in ab initio predictions of newly identified protein targets.

  9. OPTIMAL WAVELENGTH SELECTION ON HYPERSPECTRAL DATA WITH FUSED LASSO FOR BIOMASS ESTIMATION OF TROPICAL RAIN FOREST

    Directory of Open Access Journals (Sweden)

    T. Takayama

    2016-06-01

    Full Text Available Above-ground biomass prediction of tropical rain forest using remote sensing data is of paramount importance to continuous large-area forest monitoring. Hyperspectral data can provide rich spectral information for the biomass prediction; however, the prediction accuracy is affected by a small-sample-size problem, which widely exists as overfitting in using high dimensional data where the number of training samples is smaller than the dimensionality of the samples due to limitation of require time, cost, and human resources for field surveys. A common approach to addressing this problem is reducing the dimensionality of dataset. Also, acquired hyperspectral data usually have low signal-to-noise ratio due to a narrow bandwidth and local or global shifts of peaks due to instrumental instability or small differences in considering practical measurement conditions. In this work, we propose a methodology based on fused lasso regression that select optimal bands for the biomass prediction model with encouraging sparsity and grouping, which solves the small-sample-size problem by the dimensionality reduction from the sparsity and the noise and peak shift problem by the grouping. The prediction model provided higher accuracy with root-mean-square error (RMSE of 66.16 t/ha in the cross-validation than other methods; multiple linear analysis, partial least squares regression, and lasso regression. Furthermore, fusion of spectral and spatial information derived from texture index increased the prediction accuracy with RMSE of 62.62 t/ha. This analysis proves efficiency of fused lasso and image texture in biomass estimation of tropical forests.

  10. Rapid detection of atrazine and metolachlor in farm soils: gas chromatography-mass spectrometry-based analysis using the bubble-in-drop single drop microextraction enrichment method.

    Science.gov (United States)

    Williams, D Bradley G; George, Mosotho J; Marjanovic, Ljiljana

    2014-08-06

    Tracking of metolachlor and atrazine herbicides in agricultural soils, from spraying through to harvest, was conducted using our recently reported "bubble-in-drop single-drop microextraction" method. The method showed good linearity (R(2) = 0.999 and 0.999) in the concentration range of 0.01-1.0 ng/mL with LOD values of 0.01 and 0.02 ng/mL for atrazine and metolachlor, respectively. Sonication methods were poor at releasing these herbicides from the soil matrixes, while hot water extraction readily liberated them, providing an efficient accessible alternative to sonication techniques. Good recoveries of 97% and 105% were shown for atrazine and metolachlor, respectively, from the soil. The spiking protocol was also investigated, resulting in a traceless spiking method. We demonstrate a very sensitive technique by which to assess, for example, the length of residence of pesticides in given soils and thus risk of exposure.

  11. Similarity regularized sparse group lasso for cup to disc ratio computation.

    Science.gov (United States)

    Cheng, Jun; Zhang, Zhuo; Tao, Dacheng; Wong, Damon Wing Kee; Liu, Jiang; Baskaran, Mani; Aung, Tin; Wong, Tien Yin

    2017-08-01

    Automatic cup to disc ratio (CDR) computation from color fundus images has shown to be promising for glaucoma detection. Over the past decade, many algorithms have been proposed. In this paper, we first review the recent work in the area and then present a novel similarity-regularized sparse group lasso method for automated CDR estimation. The proposed method reconstructs the testing disc image based on a set of reference disc images by integrating the similarity between testing and the reference disc images with the sparse group lasso constraints. The reconstruction coefficients are then used to estimate the CDR of the testing image. The proposed method has been validated using 650 images with manually annotated CDRs. Experimental results show an average CDR error of 0.0616 and a correlation coefficient of 0.7, outperforming other methods. The areas under curve in the diagnostic test reach 0.843 and 0.837 when manual and automatically segmented discs are used respectively, better than other methods as well.

  12. Genetic risk prediction using a spatial autoregressive model with adaptive lasso.

    Science.gov (United States)

    Wen, Yalu; Shen, Xiaoxi; Lu, Qing

    2018-05-31

    With rapidly evolving high-throughput technologies, studies are being initiated to accelerate the process toward precision medicine. The collection of the vast amounts of sequencing data provides us with great opportunities to systematically study the role of a deep catalog of sequencing variants in risk prediction. Nevertheless, the massive amount of noise signals and low frequencies of rare variants in sequencing data pose great analytical challenges on risk prediction modeling. Motivated by the development in spatial statistics, we propose a spatial autoregressive model with adaptive lasso (SARAL) for risk prediction modeling using high-dimensional sequencing data. The SARAL is a set-based approach, and thus, it reduces the data dimension and accumulates genetic effects within a single-nucleotide variant (SNV) set. Moreover, it allows different SNV sets having various magnitudes and directions of effect sizes, which reflects the nature of complex diseases. With the adaptive lasso implemented, SARAL can shrink the effects of noise SNV sets to be zero and, thus, further improve prediction accuracy. Through simulation studies, we demonstrate that, overall, SARAL is comparable to, if not better than, the genomic best linear unbiased prediction method. The method is further illustrated by an application to the sequencing data from the Alzheimer's Disease Neuroimaging Initiative. Copyright © 2018 John Wiley & Sons, Ltd.

  13. Simultaneous Channel and Feature Selection of Fused EEG Features Based on Sparse Group Lasso

    Directory of Open Access Journals (Sweden)

    Jin-Jia Wang

    2015-01-01

    Full Text Available Feature extraction and classification of EEG signals are core parts of brain computer interfaces (BCIs. Due to the high dimension of the EEG feature vector, an effective feature selection algorithm has become an integral part of research studies. In this paper, we present a new method based on a wrapped Sparse Group Lasso for channel and feature selection of fused EEG signals. The high-dimensional fused features are firstly obtained, which include the power spectrum, time-domain statistics, AR model, and the wavelet coefficient features extracted from the preprocessed EEG signals. The wrapped channel and feature selection method is then applied, which uses the logistical regression model with Sparse Group Lasso penalized function. The model is fitted on the training data, and parameter estimation is obtained by modified blockwise coordinate descent and coordinate gradient descent method. The best parameters and feature subset are selected by using a 10-fold cross-validation. Finally, the test data is classified using the trained model. Compared with existing channel and feature selection methods, results show that the proposed method is more suitable, more stable, and faster for high-dimensional feature fusion. It can simultaneously achieve channel and feature selection with a lower error rate. The test accuracy on the data used from international BCI Competition IV reached 84.72%.

  14. Whole Genome Sequence Analysis of an Alachlor and Endosulfan Degrading Micrococcus sp. strain 2385 Isolated from Ochlockonee River, Florida.

    Science.gov (United States)

    Pathak, Ashish; Chauhan, Ashvini; Ewida, Ayman Y I; Stothard, Paul

    2016-01-01

    We recently isolated Micrococcus sp. strain 2385 from Ochlockonee River, Florida and demonstrated potent biodegradative activity against two commonly used pesticides- alachlor [(2-chloro-2`,6`-diethylphenyl-N (methoxymethyl)acetanilide)] and endosulfan [(6,7,8,9,10,10-hexachloro-1,5,5a,6,9,9a-hexahydro-6,9methano-2,3,4-benzo(e)di-oxathiepin-3-oxide], respectively. To further identify the repertoire of metabolic functions possessed by strain 2385, a draft genome sequence was obtained, assembled, annotated and analyzed. The genome sequence of Micrococcus sp. strain 2385 consisted of 1,460,461,440 bases which assembled into 175 contigs with an N50 contig length of 50,109 bases and a coverage of 600x. The genome size of this strain was estimated at 2,431,226 base pairs with a G+C content of 72.8 and a total number of 2,268 putative genes. RAST annotated a total of 340 subsystems in the genome of strain 2385 along with the presence of 2,177 coding sequences. A genome wide survey indicated that that strain 2385 harbors a plethora of genes to degrade other pollutants including caprolactam, PAHs (such as naphthalene), styrene, toluene and several chloroaromatic compounds.

  15. Biodegradation of Aged Residues of Atrazine and Alachlor in a Mix-Load Site Soil by Fungal Enzymes

    Directory of Open Access Journals (Sweden)

    Anastasia E. M. Chirnside

    2011-01-01

    Full Text Available Soils from bulk pesticide mixing and loading (mix-load sites are often contaminated with a complex mixture of pesticides, herbicides, and other organic compounds used in pesticide formulations that limits the success of remediation efforts. Therefore, there is a need to find remediation strategies that can successfully clean up these mix-load site soils. This paper examined the degradation of atrazine (2-chloro-4-ethylamino-6-isopropylamino-S-triazine; AT and alachlor (2-chloro-2, 6-diethyl-N-[methoxymethyl]-acetanilide in contaminated mix-load site soil utilizing an extracellular fungal enzyme solution derived from the white rot fungus, Phanerochaete chrysosporium, grown in a packed bed bioreactor. Thirty-two percent of AT and 54% of AL were transformed in the biometers. The pseudo first-order rate constant for AT and AL biodegradation was 0.0882 d−1 and 0.2504 d−1, respectively. The half-life (1/2 for AT and AL was 8.0 and 3.0 days, respectively. Compared to AT, the initial disappearance of AL proceeded at a faster rate and resulted in a greater amount of AL transformed. Based on the net Co2 evolved from the biometers, about 4% of the AT and AL initially present in the soil was completely mineralized.

  16. Improving the prediction of going concern of Taiwanese listed companies using a hybrid of LASSO with data mining techniques.

    Science.gov (United States)

    Goo, Yeung-Ja James; Chi, Der-Jang; Shen, Zong-De

    2016-01-01

    The purpose of this study is to establish rigorous and reliable going concern doubt (GCD) prediction models. This study first uses the least absolute shrinkage and selection operator (LASSO) to select variables and then applies data mining techniques to establish prediction models, such as neural network (NN), classification and regression tree (CART), and support vector machine (SVM). The samples of this study include 48 GCD listed companies and 124 NGCD (non-GCD) listed companies from 2002 to 2013 in the TEJ database. We conduct fivefold cross validation in order to identify the prediction accuracy. According to the empirical results, the prediction accuracy of the LASSO-NN model is 88.96 % (Type I error rate is 12.22 %; Type II error rate is 7.50 %), the prediction accuracy of the LASSO-CART model is 88.75 % (Type I error rate is 13.61 %; Type II error rate is 14.17 %), and the prediction accuracy of the LASSO-SVM model is 89.79 % (Type I error rate is 10.00 %; Type II error rate is 15.83 %).

  17. Calixarene receptors in the selective separation of alachlor. Characterization of the separated complexes; Receptores calixarenicos en la separacion selectiva de alaclor. Caracterizacion de los complejos separados

    Energy Technology Data Exchange (ETDEWEB)

    Garcia G, M.C

    2004-07-01

    Pesticides have been necessary in the agriculture since the plagues control have been remedied thanks to them but it has also provoked pollution. Nowadays, there are several methods which help to decrease or remedy such a pollution provoked. Unfortunately, any of them work out the environmental problem totally. Therefore, alternatives have to be found. The organic and tri dimensional characteristics of these macrocycles afford them a high versatility in such a way that these hosts can interact with organic guests selectively. Alachlor is a chlorinated organic herbicide useful in the plagues control of annual grasses and many broad-leave weeds which grow in maize, peanuts and soyabean. The ability of calixarenes to host organic guests with chemical characteristics similar to pesticides let them to be good candidates to compete with others methods which are used presently to separate organic pesticides. In this direction one of the advantages of proposing the use of calixarenes is, its facility of being modified in the lower and/or upper rims, to adapt them to aqueous, organic, gaseous and aqueous-organic media. Once the characteristics of reagents informed in the literature were confirmed and complemented with others found in this work, we studied, in solution, the interaction of the calixarenes with alachlor using 1 x 10{sup -5} to 1 x 10{sup -3} M solutions in acetonitrile for calixarenes fitted with phosphinoyl pendant arms in the lower rim, B{sub n}bL{sup n}, n= 4, 6) and in chloroform for parents calixarenes (H{sub n}bL{sup n} n = 4, 6, 8). Meticulous studies monitored by UV-Vis and luminescence were carried out, and the best stoichiometry to be used in further studies resulted to be 1(host): 1(alachlor). Therefore, we chose the 1 x 10{sup -4} M concentration to find how long the host-guest should be interacting in order to guarantee the formation in solution of the calixarene-alachlor species. It was found 168 h for the alachlor-B{sub n}bL{sup n} interaction

  18. Comparison of partial least squares and lasso regression techniques as applied to laser-induced breakdown spectroscopy of geological samples

    International Nuclear Information System (INIS)

    Dyar, M.D.; Carmosino, M.L.; Breves, E.A.; Ozanne, M.V.; Clegg, S.M.; Wiens, R.C.

    2012-01-01

    A remote laser-induced breakdown spectrometer (LIBS) designed to simulate the ChemCam instrument on the Mars Science Laboratory Rover Curiosity was used to probe 100 geologic samples at a 9-m standoff distance. ChemCam consists of an integrated remote LIBS instrument that will probe samples up to 7 m from the mast of the rover and a remote micro-imager (RMI) that will record context images. The elemental compositions of 100 igneous and highly-metamorphosed rocks are determined with LIBS using three variations of multivariate analysis, with a goal of improving the analytical accuracy. Two forms of partial least squares (PLS) regression are employed with finely-tuned parameters: PLS-1 regresses a single response variable (elemental concentration) against the observation variables (spectra, or intensity at each of 6144 spectrometer channels), while PLS-2 simultaneously regresses multiple response variables (concentrations of the ten major elements in rocks) against the observation predictor variables, taking advantage of natural correlations between elements. Those results are contrasted with those from the multivariate regression technique of the least absolute shrinkage and selection operator (lasso), which is a penalized shrunken regression method that selects the specific channels for each element that explain the most variance in the concentration of that element. To make this comparison, we use results of cross-validation and of held-out testing, and employ unscaled and uncentered spectral intensity data because all of the input variables are already in the same units. Results demonstrate that the lasso, PLS-1, and PLS-2 all yield comparable results in terms of accuracy for this dataset. However, the interpretability of these methods differs greatly in terms of fundamental understanding of LIBS emissions. PLS techniques generate principal components, linear combinations of intensities at any number of spectrometer channels, which explain as much variance in the

  19. Comparison of partial least squares and lasso regression techniques as applied to laser-induced breakdown spectroscopy of geological samples

    Energy Technology Data Exchange (ETDEWEB)

    Dyar, M.D., E-mail: mdyar@mtholyoke.edu [Dept. of Astronomy, Mount Holyoke College, 50 College St., South Hadley, MA 01075 (United States); Carmosino, M.L.; Breves, E.A.; Ozanne, M.V. [Dept. of Astronomy, Mount Holyoke College, 50 College St., South Hadley, MA 01075 (United States); Clegg, S.M.; Wiens, R.C. [Los Alamos National Laboratory, P.O. Box 1663, MS J565, Los Alamos, NM 87545 (United States)

    2012-04-15

    A remote laser-induced breakdown spectrometer (LIBS) designed to simulate the ChemCam instrument on the Mars Science Laboratory Rover Curiosity was used to probe 100 geologic samples at a 9-m standoff distance. ChemCam consists of an integrated remote LIBS instrument that will probe samples up to 7 m from the mast of the rover and a remote micro-imager (RMI) that will record context images. The elemental compositions of 100 igneous and highly-metamorphosed rocks are determined with LIBS using three variations of multivariate analysis, with a goal of improving the analytical accuracy. Two forms of partial least squares (PLS) regression are employed with finely-tuned parameters: PLS-1 regresses a single response variable (elemental concentration) against the observation variables (spectra, or intensity at each of 6144 spectrometer channels), while PLS-2 simultaneously regresses multiple response variables (concentrations of the ten major elements in rocks) against the observation predictor variables, taking advantage of natural correlations between elements. Those results are contrasted with those from the multivariate regression technique of the least absolute shrinkage and selection operator (lasso), which is a penalized shrunken regression method that selects the specific channels for each element that explain the most variance in the concentration of that element. To make this comparison, we use results of cross-validation and of held-out testing, and employ unscaled and uncentered spectral intensity data because all of the input variables are already in the same units. Results demonstrate that the lasso, PLS-1, and PLS-2 all yield comparable results in terms of accuracy for this dataset. However, the interpretability of these methods differs greatly in terms of fundamental understanding of LIBS emissions. PLS techniques generate principal components, linear combinations of intensities at any number of spectrometer channels, which explain as much variance in the

  20. Biodegradation of a commercial mixture of the herbicides atrazine and S-metolachlor in a multi-channel packed biofilm reactor.

    Science.gov (United States)

    Cabrera-Orozco, Alberto; Galíndez-Nájera, Silvia Patricia; Ruiz-Ordaz, Nora; Galíndez-Mayer, Juvencio; Martínez-Jerónimo, Fernando

    2017-11-01

    Atrazine and S-metolachlor are two of the most widely used herbicides for agricultural purposes; consequently, residues of both compounds and their metabolites had been detected in ground and superficial waters. Unlike atrazine, the complete degradation of metolachlor has not been achieved. Hence, the purpose of this research is to study the biodegradation of a commercial mixture of atrazine and S-metolachlor in a prototype of a multi-channel packed-bed-biofilm reactor (MC-PBR) designed with the aim of solving the problems of pressure drop and oxygen transfer, typically found on this type of bioreactors.Because the removal efficiency of the herbicides was increased when Candida tropicalis was added to the original microbial community isolated, the reactor was inoculated with this enriched community. The operational conditions tested in batch and continuous mode did not affect the removal efficiency of atrazine; however, this was not the case for S-metolachlor. The removal rates and efficiencies showed a notable variation along the MC-PBR operation.

  1. Environmental concentrations of irgarol, diuron and S-metolachlor induce deleterious effects on gametes and embryos of the Pacific oyster, Crassostrea gigas.

    Science.gov (United States)

    Mai, Huong; Morin, Bénédicte; Pardon, Patrick; Gonzalez, Patrice; Budzinski, Hélène; Cachot, Jérôme

    2013-08-01

    Irgarol and diuron are the most representative "organic booster biocides" that replace organotin compounds in antifouling paints, and metolachlor is one of the most extensively used chloroacetamide herbicides in agriculture. The toxicity of S-metolachlor, irgarol and diuron was evaluated in Pacific oyster (Crassostrea gigas) gametes or embryos exposed to concentrations of pesticides ranging from 0.1× to 1000×, with 1× corresponding to environmental concentrations of the three studied pesticides in Arcachon Bay (France). Exposures were performed on (1) spermatozoa alone (2) oocytes alone and (3) both spermatozoa and oocytes, and adverse effects on fertilization success and offspring development were recorded. The results showed that the fertilizing capacity of spermatozoa was significantly affected after gamete exposure to pesticide concentrations as low as 1× of irgarol and diuron and 10× of metolachlor. The offspring obtained from pesticide-exposed spermatozoa displayed a dose-dependent increase in developmental abnormalities. In contrast, treating oocytes with pesticide concentrations up to 10× did not alter fertilization rate and offspring quality. However, a significant decline in fertilization success and increase in abnormal D-larvae prevalence were observed at higher concentrations 10× (0.1 μg L(-1)) for S-metolachlor and 100× for irgarol (1.0 μg L(-1)) and diuron (4.0 μg L(-1)). Irgarol, diuron and S-metolachlor also induced a dose-dependent increase in abnormal D-larvae prevalence when freshly fertilized embryos were treated with pesticide concentrations as low as concentration of 1× (0.01 μg L(-1) for irgarol or S-metolachlor, and 0.04 μg L(-1) for diuron). The two bioassays on C. gigas spermatozoa and embryos displayed similar sensitivities to the studied pesticides while oocytes were less sensitive. Diuron, irgarol and S-metolachlor induced spermiotoxicity and embryotoxicity at environmentally relevant concentrations and therefore might be

  2. Integrative Sparse K-Means With Overlapping Group Lasso in Genomic Applications for Disease Subtype Discovery.

    Science.gov (United States)

    Huo, Zhiguang; Tseng, George

    2017-06-01

    Cancer subtypes discovery is the first step to deliver personalized medicine to cancer patients. With the accumulation of massive multi-level omics datasets and established biological knowledge databases, omics data integration with incorporation of rich existing biological knowledge is essential for deciphering a biological mechanism behind the complex diseases. In this manuscript, we propose an integrative sparse K -means (is- K means) approach to discover disease subtypes with the guidance of prior biological knowledge via sparse overlapping group lasso. An algorithm using an alternating direction method of multiplier (ADMM) will be applied for fast optimization. Simulation and three real applications in breast cancer and leukemia will be used to compare is- K means with existing methods and demonstrate its superior clustering accuracy, feature selection, functional annotation of detected molecular features and computing efficiency.

  3. Discovery and replication of gene influences on brain structure using LASSO regression

    Directory of Open Access Journals (Sweden)

    Omid eKohannim

    2012-08-01

    Full Text Available We implemented LASSO (least absolute shrinkage and selection operator regression to evaluate gene effects in genome-wide association studies (GWAS of brain images, using an MRI-derived temporal lobe volume measure from 729 subjects scanned as part of the Alzheimer’s Disease Neuroimaging Initiative (ADNI. Sparse groups of SNPs in individual genes were selected by LASSO, which identifies efficient sets of variants influencing the data. These SNPs were considered jointly when assessing their association with neuroimaging measures. We discovered 22 genes that passed genome-wide significance for influencing temporal lobe volume. This was a substantially greater number of significant genes compared to those found with standard, univariate GWAS. These top genes are all expressed in the brain and include genes previously related to brain function or neuropsychiatric disorders such as MACROD2, SORCS2, GRIN2B, MAGI2, NPAS3, CLSTN2, GABRG3, NRXN3, PRKAG2, GAS7, RBFOX1, ADARB2, CHD4 and CDH13. The top genes we identified with this method also displayed significant and widespread post-hoc effects on voxelwise, tensor-based morphometry (TBM maps of the temporal lobes. The most significantly associated gene was an autism susceptibility gene known as MACROD2. We were able to successfully replicate the effect of the MACROD2 gene in an independent cohort of 564 young, Australian healthy adult twins and siblings scanned with MRI (mean age: 23.8±2.2 SD years. In exploratory analyses, three selected SNPs in the MACROD2 gene were also significantly associated with performance intelligence quotient (PIQ. Our approach powerfully complements univariate techniques in detecting influences of genes on the living brain.

  4. The Spike-and-Slab Lasso Generalized Linear Models for Prediction and Associated Genes Detection.

    Science.gov (United States)

    Tang, Zaixiang; Shen, Yueping; Zhang, Xinyan; Yi, Nengjun

    2017-01-01

    Large-scale "omics" data have been increasingly used as an important resource for prognostic prediction of diseases and detection of associated genes. However, there are considerable challenges in analyzing high-dimensional molecular data, including the large number of potential molecular predictors, limited number of samples, and small effect of each predictor. We propose new Bayesian hierarchical generalized linear models, called spike-and-slab lasso GLMs, for prognostic prediction and detection of associated genes using large-scale molecular data. The proposed model employs a spike-and-slab mixture double-exponential prior for coefficients that can induce weak shrinkage on large coefficients, and strong shrinkage on irrelevant coefficients. We have developed a fast and stable algorithm to fit large-scale hierarchal GLMs by incorporating expectation-maximization (EM) steps into the fast cyclic coordinate descent algorithm. The proposed approach integrates nice features of two popular methods, i.e., penalized lasso and Bayesian spike-and-slab variable selection. The performance of the proposed method is assessed via extensive simulation studies. The results show that the proposed approach can provide not only more accurate estimates of the parameters, but also better prediction. We demonstrate the proposed procedure on two cancer data sets: a well-known breast cancer data set consisting of 295 tumors, and expression data of 4919 genes; and the ovarian cancer data set from TCGA with 362 tumors, and expression data of 5336 genes. Our analyses show that the proposed procedure can generate powerful models for predicting outcomes and detecting associated genes. The methods have been implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). Copyright © 2017 by the Genetics Society of America.

  5. Scoring relevancy of features based on combinatorial analysis of Lasso with application to lymphoma diagnosis

    Directory of Open Access Journals (Sweden)

    Zare Habil

    2013-01-01

    Full Text Available Abstract One challenge in applying bioinformatic tools to clinical or biological data is high number of features that might be provided to the learning algorithm without any prior knowledge on which ones should be used. In such applications, the number of features can drastically exceed the number of training instances which is often limited by the number of available samples for the study. The Lasso is one of many regularization methods that have been developed to prevent overfitting and improve prediction performance in high-dimensional settings. In this paper, we propose a novel algorithm for feature selection based on the Lasso and our hypothesis is that defining a scoring scheme that measures the "quality" of each feature can provide a more robust feature selection method. Our approach is to generate several samples from the training data by bootstrapping, determine the best relevance-ordering of the features for each sample, and finally combine these relevance-orderings to select highly relevant features. In addition to the theoretical analysis of our feature scoring scheme, we provided empirical evaluations on six real datasets from different fields to confirm the superiority of our method in exploratory data analysis and prediction performance. For example, we applied FeaLect, our feature scoring algorithm, to a lymphoma dataset, and according to a human expert, our method led to selecting more meaningful features than those commonly used in the clinics. This case study built a basis for discovering interesting new criteria for lymphoma diagnosis. Furthermore, to facilitate the use of our algorithm in other applications, the source code that implements our algorithm was released as FeaLect, a documented R package in CRAN.

  6. Spatio Temporal EEG Source Imaging with the Hierarchical Bayesian Elastic Net and Elitist Lasso Models.

    Science.gov (United States)

    Paz-Linares, Deirel; Vega-Hernández, Mayrim; Rojas-López, Pedro A; Valdés-Hernández, Pedro A; Martínez-Montes, Eduardo; Valdés-Sosa, Pedro A

    2017-01-01

    The estimation of EEG generating sources constitutes an Inverse Problem (IP) in Neuroscience. This is an ill-posed problem due to the non-uniqueness of the solution and regularization or prior information is needed to undertake Electrophysiology Source Imaging. Structured Sparsity priors can be attained through combinations of (L1 norm-based) and (L2 norm-based) constraints such as the Elastic Net (ENET) and Elitist Lasso (ELASSO) models. The former model is used to find solutions with a small number of smooth nonzero patches, while the latter imposes different degrees of sparsity simultaneously along different dimensions of the spatio-temporal matrix solutions. Both models have been addressed within the penalized regression approach, where the regularization parameters are selected heuristically, leading usually to non-optimal and computationally expensive solutions. The existing Bayesian formulation of ENET allows hyperparameter learning, but using the computationally intensive Monte Carlo/Expectation Maximization methods, which makes impractical its application to the EEG IP. While the ELASSO have not been considered before into the Bayesian context. In this work, we attempt to solve the EEG IP using a Bayesian framework for ENET and ELASSO models. We propose a Structured Sparse Bayesian Learning algorithm based on combining the Empirical Bayes and the iterative coordinate descent procedures to estimate both the parameters and hyperparameters. Using realistic simulations and avoiding the inverse crime we illustrate that our methods are able to recover complicated source setups more accurately and with a more robust estimation of the hyperparameters and behavior under different sparsity scenarios than classical LORETA, ENET and LASSO Fusion solutions. We also solve the EEG IP using data from a visual attention experiment, finding more interpretable neurophysiological patterns with our methods. The Matlab codes used in this work, including Simulations, Methods

  7. LASSO NTCP predictors for the incidence of xerostomia in patients with head and neck squamous cell carcinoma and nasopharyngeal carcinoma

    Science.gov (United States)

    Lee, Tsair-Fwu; Liou, Ming-Hsiang; Huang, Yu-Jie; Chao, Pei-Ju; Ting, Hui-Min; Lee, Hsiao-Yi

    2014-01-01

    To predict the incidence of moderate-to-severe patient-reported xerostomia among head and neck squamous cell carcinoma (HNSCC) and nasopharyngeal carcinoma (NPC) patients treated with intensity-modulated radiotherapy (IMRT). Multivariable normal tissue complication probability (NTCP) models were developed by using quality of life questionnaire datasets from 152 patients with HNSCC and 84 patients with NPC. The primary endpoint was defined as moderate-to-severe xerostomia after IMRT. The numbers of predictive factors for a multivariable logistic regression model were determined using the least absolute shrinkage and selection operator (LASSO) with bootstrapping technique. Four predictive models were achieved by LASSO with the smallest number of factors while preserving predictive value with higher AUC performance. For all models, the dosimetric factors for the mean dose given to the contralateral and ipsilateral parotid gland were selected as the most significant predictors. Followed by the different clinical and socio-economic factors being selected, namely age, financial status, T stage, and education for different models were chosen. The predicted incidence of xerostomia for HNSCC and NPC patients can be improved by using multivariable logistic regression models with LASSO technique. The predictive model developed in HNSCC cannot be generalized to NPC cohort treated with IMRT without validation and vice versa. PMID:25163814

  8. Geographically weighted lasso (GWL) study for modeling the diarrheic to achieve open defecation free (ODF) target

    Science.gov (United States)

    Arumsari, Nurvita; Sutidjo, S. U.; Brodjol; Soedjono, Eddy S.

    2014-03-01

    Diarrhea has been one main cause of morbidity and mortality to children around the world, especially in the developing countries According to available data that was mentioned. It showed that sanitary and healthy lifestyle implementation by the inhabitants was not good yet. Inadequacy of environmental influence and the availability of health services were suspected factors which influenced diarrhea cases happened followed by heightened percentage of the diarrheic. This research is aimed at modelling the diarrheic by using Geographically Weighted Lasso method. With the existence of spatial heterogeneity was tested by Breusch Pagan, it was showed that diarrheic modeling with weighted regression, especially GWR and GWL, can explain the variation in each location. But, the absence of multi-collinearity cases on predictor variables, which were affecting the diarrheic, resulted in GWR and GWL modelling to be not different or identical. It is shown from the resulting MSE value. While from R2 value which usually higher on GWL model showed a significant variable predictor based on more parametric shrinkage value.

  9. Statistically Modeling I-V Characteristics of CNT-FET with LASSO

    Science.gov (United States)

    Ma, Dongsheng; Ye, Zuochang; Wang, Yan

    2017-08-01

    With the advent of internet of things (IOT), the need for studying new material and devices for various applications is increasing. Traditionally we build compact models for transistors on the basis of physics. But physical models are expensive and need a very long time to adjust for non-ideal effects. As the vision for the application of many novel devices is not certain or the manufacture process is not mature, deriving generalized accurate physical models for such devices is very strenuous, whereas statistical modeling is becoming a potential method because of its data oriented property and fast implementation. In this paper, one classical statistical regression method, LASSO, is used to model the I-V characteristics of CNT-FET and a pseudo-PMOS inverter simulation based on the trained model is implemented in Cadence. The normalized relative mean square prediction error of the trained model versus experiment sample data and the simulation results show that the model is acceptable for digital circuit static simulation. And such modeling methodology can extend to general devices.

  10. Comparative toxic responses of male and female lizards (Eremias argus) exposed to (S)-metolachlor-contaminated soil.

    Science.gov (United States)

    Chen, Li; Wang, Dezhen; Tian, Zhongnan; Di, Shanshan; Zhang, Wenjun; Wang, Fang; Zhou, Zhiqiang; Diao, Jinling

    2017-08-01

    Soil contamination caused by the widespread use of pesticides is one of the main environmental problems facing conservation organizations. (S)-metolachlor (SM) is a selective pre-emergent herbicide that poses potential risks to soil-related organisms such as reptiles. The present study elucidated the toxic effects of SM (3 and 30 mg/kg soil weight) in Eremias argus. The results showed that growth pattern was similar between the sexes in breeding season. For males, both kidney coefficient (KC) and testis coefficient in the exposure group were significantly different from those in the control group, while only KC in the high-dose group was significantly higher for females. Based on histopathological analysis, the livers of female lizards were more vulnerable than those of males in the exposure group. A reduction in total egg output was observed in SM exposed lizards. Accumulation studies indicated that skin exposure may be an important route for SM uptake in E. argus, and that the liver and lung have strong detoxification abilities. In addition, the body burdens of the lizards increased with increasing SM concentration in the soil. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Efeito da irrigação inicial na profundidade de lixiviação do herbicida s-metolachlor em diferentes tipos de solos Effects of the initial irrigation on the s-metolachlor herbicide leaching depth in different types of soils

    Directory of Open Access Journals (Sweden)

    S.O. Procópio

    2001-12-01

    Full Text Available Muitas vezes a profundidade de lixiviação dos herbicidas aplicados ao solo afeta a seletividade destes às culturas. O objetivo deste trabalho foi estudar a lixiviação do herbicida s-metolachlor em cinco tipos de solos (Podzólico Vermelho-Amarelo, Latossolo Roxo, Latossolo Vermelho-Amarelo, Areia Quartzosa-turfosa e Areia Quartzosa, bem como avaliar o efeito do manejo das primeiras irrigações antes e após a aplicação do herbicida sobre esse processo, por meio de bioensaios, relacionando os resultados encontrados com possíveis efeitos fitotóxicos ocorridos em algumas culturas comerciais. Os experimentos foram realizados em casa de vegetação, utilizando-se colunas de lixiviação, sendo compostos de oito tratamentos, formados da combinação de dois tipos de irrigação inicial (lâmina de irrigação de 25 mm antes ou depois da aplicação do s-metolachlor com quatro faixas de profundidade de coleta dos solos (0-5, 5-10, 10-15 e 15-20 cm, com cinco tipos de solos. O herbicida s-metolachlor foi pulverizado na dose de 1,92 kg ha-1 em todos os tratamentos, e a planta indicadora utilizada foi o sorgo-granífero (Sorghum bicolor, híbrido BR 304. Observou-se tendência de maior lixiviação e maior disponibilidade do s-metolachlor em todos os solos avaliados quando a irrigação foi realizada após a aplicação do herbicida. Na Areia Quartzosa ocorreu a maior lixiviação e disponibilidade do herbicida. Em todos os solos, o s-metolachlor concentrou-se na camada mais superficial do solo de 0-5 cm. Conclui-se que solos com baixos teor de matéria orgânica e CTC efetiva aumentam a predisposição da ocorrência de efeitos fitotóxicos do s-metolachlor às culturas e a probabilidade de contaminação de águas subterrâneas.The leaching depth of the herbicides applied on the soil often affects their selectivity to crops. This work aimed to study soil mobility of s-metolachlor in five types of soils (Red-yellow Podzolic, Purple Latosol, Red

  12. Does S-metolachlor affect the performance of Pseudomonas sp. strain ADP as bioaugmentation bacterium for atrazine-contaminated soils?

    Directory of Open Access Journals (Sweden)

    Cristina A Viegas

    Full Text Available Atrazine (ATZ and S-metolachlor (S-MET are two herbicides widely used, often as mixtures. The present work examined whether the presence of S-MET affects the ATZ-biodegradation activity of the bioaugmentation bacterium Pseudomonas sp. strain ADP in a crop soil. S-MET concentrations were selected for their relevance in worst-case scenarios of soil contamination by a commercial formulation containing both herbicides. At concentrations representative of application of high doses of the formulation (up to 50 µg g(-1 of soil, corresponding to a dose approximately 50× higher than the recommended field dose (RD, the presence of pure S-MET significantly affected neither bacteria survival (~10(7 initial viable cells g(-1 of soil nor its ATZ-mineralization activity. Consistently, biodegradation experiments, in larger soil microcosms spiked with 20× or 50 × RD of the double formulation and inoculated with the bacterium, revealed ATZ to be rapidly (in up to 5 days and extensively (>96% removed from the soil. During the 5 days, concentration of S-MET decreased moderately to about 60% of the initial, both in inoculated and non-inoculated microcosms. Concomitantly, an accumulation of the two metabolites S-MET ethanesulfonic acid and S-MET oxanilic acid was found. Despite the dissipation of almost all the ATZ from the treated soils, the respective eluates were still highly toxic to an aquatic microalgae species, being as toxic as those from the untreated soil. We suggest that this high toxicity may be due to the S-MET and/or its metabolites remaining in the soil.

  13. Implementations of geographically weighted lasso in spatial data with multicollinearity (Case study: Poverty modeling of Java Island)

    Science.gov (United States)

    Setiyorini, Anis; Suprijadi, Jadi; Handoko, Budhi

    2017-03-01

    Geographically Weighted Regression (GWR) is a regression model that takes into account the spatial heterogeneity effect. In the application of the GWR, inference on regression coefficients is often of interest, as is estimation and prediction of the response variable. Empirical research and studies have demonstrated that local correlation between explanatory variables can lead to estimated regression coefficients in GWR that are strongly correlated, a condition named multicollinearity. It later results on a large standard error on estimated regression coefficients, and, hence, problematic for inference on relationships between variables. Geographically Weighted Lasso (GWL) is a method which capable to deal with spatial heterogeneity and local multicollinearity in spatial data sets. GWL is a further development of GWR method, which adds a LASSO (Least Absolute Shrinkage and Selection Operator) constraint in parameter estimation. In this study, GWL will be applied by using fixed exponential kernel weights matrix to establish a poverty modeling of Java Island, Indonesia. The results of applying the GWL to poverty datasets show that this method stabilizes regression coefficients in the presence of multicollinearity and produces lower prediction and estimation error of the response variable than GWR does.

  14. Logistic LASSO regression for the diagnosis of breast cancer using clinical demographic data and the BI-RADS lexicon for ultrasonography.

    Science.gov (United States)

    Kim, Sun Mi; Kim, Yongdai; Jeong, Kuhwan; Jeong, Heeyeong; Kim, Jiyoung

    2018-01-01

    The aim of this study was to compare the performance of image analysis for predicting breast cancer using two distinct regression models and to evaluate the usefulness of incorporating clinical and demographic data (CDD) into the image analysis in order to improve the diagnosis of breast cancer. This study included 139 solid masses from 139 patients who underwent a ultrasonography-guided core biopsy and had available CDD between June 2009 and April 2010. Three breast radiologists retrospectively reviewed 139 breast masses and described each lesion using the Breast Imaging Reporting and Data System (BI-RADS) lexicon. We applied and compared two regression methods-stepwise logistic (SL) regression and logistic least absolute shrinkage and selection operator (LASSO) regression-in which the BI-RADS descriptors and CDD were used as covariates. We investigated the performances of these regression methods and the agreement of radiologists in terms of test misclassification error and the area under the curve (AUC) of the tests. Logistic LASSO regression was superior (Pcomparable to the AUC with CDD (0.873 vs. 0.880, P=0.141). Logistic LASSO regression based on BI-RADS descriptors and CDD showed better performance than SL in predicting the presence of breast cancer. The use of CDD as a supplement to the BI-RADS descriptors significantly improved the prediction of breast cancer using logistic LASSO regression.

  15. Whole genome sequence analysis of an Alachlor and Endosulfan degrading Pseudomonas strain W15Feb9B isolated from Ochlockonee River, Florida

    Directory of Open Access Journals (Sweden)

    Ashvini Chauhan

    2016-06-01

    Full Text Available We recently isolated a Pseudomonas sp. strain W15Feb9B from Ochlockonee River, Florida and demonstrated potent biodegradative activity against two commonly used pesticides - Alachlor [(2-chloro-2′,6′-diethylphenyl-N (methoxymethylacetanilide] and Endosulfan [(6,7,8,9,10,10-hexachloro-1,5,5a,6,9,9a-hexahydro-6,9methano-2,3,4-benzo(edi-oxathiepin-3-oxide], respectively. To further identify the repertoire of metabolic functions possessed by strain W15Feb9B, a draft genome sequence was obtained, assembled, annotated and analyzed. The genome sequence of strain 2385 has been deposited in GenBank under accession number JTKF00000000; BioSample number SAMN03151543. The sequences obtained from strain 2385 assembled into 192 contigs with a genome size of 6,031,588, G + C content of 60.34, and 5512 total number of putative genes. RAST annotated a total of 542 subsystems in the genome of strain W15Feb9B along with the presence of 5360 coding sequences. A genome wide survey of strain W15Feb9B indicated that it has the potential to degrade several other pollutants including atrazine, caprolactam, dioxin, PAHs (such as naphthalene and several chloroaromatic compounds.

  16. A Novel SCCA Approach via Truncated ℓ1-norm and Truncated Group Lasso for Brain Imaging Genetics.

    Science.gov (United States)

    Du, Lei; Liu, Kefei; Zhang, Tuo; Yao, Xiaohui; Yan, Jingwen; Risacher, Shannon L; Han, Junwei; Guo, Lei; Saykin, Andrew J; Shen, Li

    2017-09-18

    Brain imaging genetics, which studies the linkage between genetic variations and structural or functional measures of the human brain, has become increasingly important in recent years. Discovering the bi-multivariate relationship between genetic markers such as single-nucleotide polymorphisms (SNPs) and neuroimaging quantitative traits (QTs) is one major task in imaging genetics. Sparse Canonical Correlation Analysis (SCCA) has been a popular technique in this area for its powerful capability in identifying bi-multivariate relationships coupled with feature selection. The existing SCCA methods impose either the ℓ 1 -norm or its variants to induce sparsity. The ℓ 0 -norm penalty is a perfect sparsity-inducing tool which, however, is an NP-hard problem. In this paper, we propose the truncated ℓ 1 -norm penalized SCCA to improve the performance and effectiveness of the ℓ 1 -norm based SCCA methods. Besides, we propose an efficient optimization algorithms to solve this novel SCCA problem. The proposed method is an adaptive shrinkage method via tuning τ . It can avoid the time intensive parameter tuning if given a reasonable small τ . Furthermore, we extend it to the truncated group-lasso (TGL), and propose TGL-SCCA model to improve the group-lasso-based SCCA methods. The experimental results, compared with four benchmark methods, show that our SCCA methods identify better or similar correlation coefficients, and better canonical loading profiles than the competing methods. This demonstrates the effectiveness and efficiency of our methods in discovering interesting imaging genetic associations. The Matlab code and sample data are freely available at http://www.iu.edu/∼shenlab/tools/tlpscca/ . © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  17. Using Multivariate Regression Model with Least Absolute Shrinkage and Selection Operator (LASSO) to Predict the Incidence of Xerostomia after Intensity-Modulated Radiotherapy for Head and Neck Cancer

    Science.gov (United States)

    Ting, Hui-Min; Chang, Liyun; Huang, Yu-Jie; Wu, Jia-Ming; Wang, Hung-Yu; Horng, Mong-Fong; Chang, Chun-Ming; Lan, Jen-Hong; Huang, Ya-Yu; Fang, Fu-Min; Leung, Stephen Wan

    2014-01-01

    Purpose The aim of this study was to develop a multivariate logistic regression model with least absolute shrinkage and selection operator (LASSO) to make valid predictions about the incidence of moderate-to-severe patient-rated xerostomia among head and neck cancer (HNC) patients treated with IMRT. Methods and Materials Quality of life questionnaire datasets from 206 patients with HNC were analyzed. The European Organization for Research and Treatment of Cancer QLQ-H&N35 and QLQ-C30 questionnaires were used as the endpoint evaluation. The primary endpoint (grade 3+ xerostomia) was defined as moderate-to-severe xerostomia at 3 (XER3m) and 12 months (XER12m) after the completion of IMRT. Normal tissue complication probability (NTCP) models were developed. The optimal and suboptimal numbers of prognostic factors for a multivariate logistic regression model were determined using the LASSO with bootstrapping technique. Statistical analysis was performed using the scaled Brier score, Nagelkerke R2, chi-squared test, Omnibus, Hosmer-Lemeshow test, and the AUC. Results Eight prognostic factors were selected by LASSO for the 3-month time point: Dmean-c, Dmean-i, age, financial status, T stage, AJCC stage, smoking, and education. Nine prognostic factors were selected for the 12-month time point: Dmean-i, education, Dmean-c, smoking, T stage, baseline xerostomia, alcohol abuse, family history, and node classification. In the selection of the suboptimal number of prognostic factors by LASSO, three suboptimal prognostic factors were fine-tuned by Hosmer-Lemeshow test and AUC, i.e., Dmean-c, Dmean-i, and age for the 3-month time point. Five suboptimal prognostic factors were also selected for the 12-month time point, i.e., Dmean-i, education, Dmean-c, smoking, and T stage. The overall performance for both time points of the NTCP model in terms of scaled Brier score, Omnibus, and Nagelkerke R2 was satisfactory and corresponded well with the expected values. Conclusions

  18. Group spike-and-slab lasso generalized linear models for disease prediction and associated genes detection by incorporating pathway information.

    Science.gov (United States)

    Tang, Zaixiang; Shen, Yueping; Li, Yan; Zhang, Xinyan; Wen, Jia; Qian, Chen'ao; Zhuang, Wenzhuo; Shi, Xinghua; Yi, Nengjun

    2018-03-15

    Large-scale molecular data have been increasingly used as an important resource for prognostic prediction of diseases and detection of associated genes. However, standard approaches for omics data analysis ignore the group structure among genes encoded in functional relationships or pathway information. We propose new Bayesian hierarchical generalized linear models, called group spike-and-slab lasso GLMs, for predicting disease outcomes and detecting associated genes by incorporating large-scale molecular data and group structures. The proposed model employs a mixture double-exponential prior for coefficients that induces self-adaptive shrinkage amount on different coefficients. The group information is incorporated into the model by setting group-specific parameters. We have developed a fast and stable deterministic algorithm to fit the proposed hierarchal GLMs, which can perform variable selection within groups. We assess the performance of the proposed method on several simulated scenarios, by varying the overlap among groups, group size, number of non-null groups, and the correlation within group. Compared with existing methods, the proposed method provides not only more accurate estimates of the parameters but also better prediction. We further demonstrate the application of the proposed procedure on three cancer datasets by utilizing pathway structures of genes. Our results show that the proposed method generates powerful models for predicting disease outcomes and detecting associated genes. The methods have been implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). nyi@uab.edu. Supplementary data are available at Bioinformatics online.

  19. EM Adaptive LASSO – A Multilocus Modeling Strategy for Detecting SNPs Associated With Zero-inflated Count Phenotypes

    Directory of Open Access Journals (Sweden)

    Himel eMallick

    2016-03-01

    Full Text Available Count data are increasingly ubiquitous in genetic association studies, where it is possible to observe excess zero counts as compared to what is expected based on standard assumptions. For instance, in rheumatology, data are usually collected in multiple joints within a person or multiple sub-regions of a joint, and it is not uncommon that the phenotypes contain enormous number of zeroes due to the presence of excessive zero counts in majority of patients. Most existing statistical methods assume that the count phenotypes follow one of these four distributions with appropriate dispersion-handling mechanisms: Poisson, Zero-inflated Poisson (ZIP, Negative Binomial, and Zero-inflated Negative Binomial (ZINB. However, little is known about their implications in genetic association studies. Also, there is a relative paucity of literature on their usefulness with respect to model misspecification and variable selection. In this article, we have investigated the performance of several state-of-the-art approaches for handling zero-inflated count data along with a novel penalized regression approach with an adaptive LASSO penalty, by simulating data under a variety of disease models and linkage disequilibrium patterns. By taking into account data-adaptive weights in the estimation procedure, the proposed method provides greater flexibility in multi-SNP modeling of zero-inflated count phenotypes. A fast coordinate descent algorithm nested within an EM (expectation-maximization algorithm is implemented for estimating the model parameters and conducting variable selection simultaneously. Results show that the proposed method has optimal performance in the presence of multicollinearity, as measured by both prediction accuracy and empirical power, which is especially apparent as the sample size increases. Moreover, the Type I error rates become more or less uncontrollable for the competing methods when a model is misspecified, a phenomenon routinely

  20. Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model

    KAUST Repository

    Camilo, Daniela Castro

    2017-08-30

    Grid-based landslide susceptibility models at regional scales are computationally demanding when using a fine grid resolution. Conversely, Slope-Unit (SU) based susceptibility models allows to investigate the same areas offering two main advantages: 1) a smaller computational burden and 2) a more geomorphologically-oriented interpretation. In this contribution, we generate SU-based landslide susceptibility for the Sado Island in Japan. This island is characterized by deep-seated landslides which we assume can only limitedly be explained by the first two statistical moments (mean and variance) of a set of predictors within each slope unit. As a consequence, in a nested experiment, we first analyse the distributions of a set of continuous predictors within each slope unit computing the standard deviation and quantiles from 0.05 to 0.95 with a step of 0.05. These are then used as predictors for landslide susceptibility. In addition, we combine shape indices for polygon features and the normalized extent of each class belonging to the outcropping lithology in a given SU. This procedure significantly enlarges the size of the predictor hyperspace, thus producing a high level of slope-unit characterization. In a second step, we adopt a LASSO-penalized Generalized Linear Model to shrink back the predictor set to a sensible and interpretable number, carrying only the most significant covariates in the models. As a result, we are able to document the geomorphic features (e.g., 95% quantile of Elevation and 5% quantile of Plan Curvature) that primarily control the SU-based susceptibility within the test area while producing high predictive performances. The implementation of the statistical analyses are included in a parallelized R script (LUDARA) which is here made available for the community to replicate analogous experiments.

  1. Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model

    KAUST Repository

    Camilo, Daniela Castro; Lombardo, Luigi; Mai, Paul Martin; Dou, Jie; Huser, Raphaë l

    2017-01-01

    Grid-based landslide susceptibility models at regional scales are computationally demanding when using a fine grid resolution. Conversely, Slope-Unit (SU) based susceptibility models allows to investigate the same areas offering two main advantages: 1) a smaller computational burden and 2) a more geomorphologically-oriented interpretation. In this contribution, we generate SU-based landslide susceptibility for the Sado Island in Japan. This island is characterized by deep-seated landslides which we assume can only limitedly be explained by the first two statistical moments (mean and variance) of a set of predictors within each slope unit. As a consequence, in a nested experiment, we first analyse the distributions of a set of continuous predictors within each slope unit computing the standard deviation and quantiles from 0.05 to 0.95 with a step of 0.05. These are then used as predictors for landslide susceptibility. In addition, we combine shape indices for polygon features and the normalized extent of each class belonging to the outcropping lithology in a given SU. This procedure significantly enlarges the size of the predictor hyperspace, thus producing a high level of slope-unit characterization. In a second step, we adopt a LASSO-penalized Generalized Linear Model to shrink back the predictor set to a sensible and interpretable number, carrying only the most significant covariates in the models. As a result, we are able to document the geomorphic features (e.g., 95% quantile of Elevation and 5% quantile of Plan Curvature) that primarily control the SU-based susceptibility within the test area while producing high predictive performances. The implementation of the statistical analyses are included in a parallelized R script (LUDARA) which is here made available for the community to replicate analogous experiments.

  2. Fine-mapping additive and dominant SNP effects using group-LASSO and Fractional Resample Model Averaging

    Science.gov (United States)

    Sabourin, Jeremy; Nobel, Andrew B.; Valdar, William

    2014-01-01

    Genomewide association studies sometimes identify loci at which both the number and identities of the underlying causal variants are ambiguous. In such cases, statistical methods that model effects of multiple SNPs simultaneously can help disentangle the observed patterns of association and provide information about how those SNPs could be prioritized for follow-up studies. Current multi-SNP methods, however, tend to assume that SNP effects are well captured by additive genetics; yet when genetic dominance is present, this assumption translates to reduced power and faulty prioritizations. We describe a statistical procedure for prioritizing SNPs at GWAS loci that efficiently models both additive and dominance effects. Our method, LLARRMA-dawg, combines a group LASSO procedure for sparse modeling of multiple SNP effects with a resampling procedure based on fractional observation weights; it estimates for each SNP the robustness of association with the phenotype both to sampling variation and to competing explanations from other SNPs. In producing a SNP prioritization that best identifies underlying true signals, we show that: our method easily outperforms a single marker analysis; when additive-only signals are present, our joint model for additive and dominance is equivalent to or only slightly less powerful than modeling additive-only effects; and, when dominance signals are present, even in combination with substantial additive effects, our joint model is unequivocally more powerful than a model assuming additivity. We also describe how performance can be improved through calibrated randomized penalization, and discuss how dominance in ungenotyped SNPs can be incorporated through either heterozygote dosage or multiple imputation. PMID:25417853

  3. New method for the determination of metolachlor and buprofezin in natural water using orthophthalaldehyde by thermochemically-induced fluorescence derivatization (TIFD).

    Science.gov (United States)

    Mendy, Alphonse; Thiaré, Diène Diégane; Sambou, Souleymane; Khonté, Abdourahmane; Coly, Atanasse; Gaye-Seye, Mame Diabou; Delattre, François; Tine, Alphonse

    2016-05-01

    Herbicide metolachlor (MET) and insecticide buprofezin (BUP) were determined in natural waters by means of a newly-developed, simple and sensitive thermochemically-induced fluorescence derivatization (TIFD) method. The TIFD approach is based on the thermolysis transformation of naturally non-fluorescent pesticides into fluorescent complex O-phthalaldehyde-thermoproduct(s) in water at 70°C for MET and at 80°C for BUP. The TIFD method was optimized with respect to the temperature, pH, complex formation kinetic and pesticides concentrations. The limit of detection (LOD=0.8ngmL(-1) for MET and 3.0ngmL(-1) for BUP) and quantification (LOQ=2.6ngmL(-1) for MET and 9.5 ngmL(-1) for BUP) values were low, and the relative standard deviation (RSD) values were small (between 1.2% and 1.8%), which indicates a good analytical sensitivity and a great repeatability of TIFD method. Recovery studies were performed on spiked well, sea and draining waters samples collected in the Niayes area by using the solid phase extraction (SPE) procedure. Satisfactory recovery results (84-118%) were obtained for the determination of MET and BUP in these natural waters. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Improved Variable Selection Algorithm Using a LASSO-Type Penalty, with an Application to Assessing Hepatitis B Infection Relevant Factors in Community Residents

    Science.gov (United States)

    Guo, Pi; Zeng, Fangfang; Hu, Xiaomin; Zhang, Dingmei; Zhu, Shuming; Deng, Yu; Hao, Yuantao

    2015-01-01

    Objectives In epidemiological studies, it is important to identify independent associations between collective exposures and a health outcome. The current stepwise selection technique ignores stochastic errors and suffers from a lack of stability. The alternative LASSO-penalized regression model can be applied to detect significant predictors from a pool of candidate variables. However, this technique is prone to false positives and tends to create excessive biases. It remains challenging to develop robust variable selection methods and enhance predictability. Material and methods Two improved algorithms denoted the two-stage hybrid and bootstrap ranking procedures, both using a LASSO-type penalty, were developed for epidemiological association analysis. The performance of the proposed procedures and other methods including conventional LASSO, Bolasso, stepwise and stability selection models were evaluated using intensive simulation. In addition, methods were compared by using an empirical analysis based on large-scale survey data of hepatitis B infection-relevant factors among Guangdong residents. Results The proposed procedures produced comparable or less biased selection results when compared to conventional variable selection models. In total, the two newly proposed procedures were stable with respect to various scenarios of simulation, demonstrating a higher power and a lower false positive rate during variable selection than the compared methods. In empirical analysis, the proposed procedures yielding a sparse set of hepatitis B infection-relevant factors gave the best predictive performance and showed that the procedures were able to select a more stringent set of factors. The individual history of hepatitis B vaccination, family and individual history of hepatitis B infection were associated with hepatitis B infection in the studied residents according to the proposed procedures. Conclusions The newly proposed procedures improve the identification of

  5. Logistic LASSO regression for the diagnosis of breast cancer using clinical demographic data and the BI-RADS lexicon for ultrasonography

    Directory of Open Access Journals (Sweden)

    Sun Mi Kim

    2018-01-01

    Full Text Available Purpose The aim of this study was to compare the performance of image analysis for predicting breast cancer using two distinct regression models and to evaluate the usefulness of incorporating clinical and demographic data (CDD into the image analysis in order to improve the diagnosis of breast cancer. Methods This study included 139 solid masses from 139 patients who underwent a ultrasonography-guided core biopsy and had available CDD between June 2009 and April 2010. Three breast radiologists retrospectively reviewed 139 breast masses and described each lesion using the Breast Imaging Reporting and Data System (BI-RADS lexicon. We applied and compared two regression methods-stepwise logistic (SL regression and logistic least absolute shrinkage and selection operator (LASSO regression-in which the BI-RADS descriptors and CDD were used as covariates. We investigated the performances of these regression methods and the agreement of radiologists in terms of test misclassification error and the area under the curve (AUC of the tests. Results Logistic LASSO regression was superior (P<0.05 to SL regression, regardless of whether CDD was included in the covariates, in terms of test misclassification errors (0.234 vs. 0.253, without CDD; 0.196 vs. 0.258, with CDD and AUC (0.785 vs. 0.759, without CDD; 0.873 vs. 0.735, with CDD. However, it was inferior (P<0.05 to the agreement of three radiologists in terms of test misclassification errors (0.234 vs. 0.168, without CDD; 0.196 vs. 0.088, with CDD and the AUC without CDD (0.785 vs. 0.844, P<0.001, but was comparable to the AUC with CDD (0.873 vs. 0.880, P=0.141. Conclusion Logistic LASSO regression based on BI-RADS descriptors and CDD showed better performance than SL in predicting the presence of breast cancer. The use of CDD as a supplement to the BI-RADS descriptors significantly improved the prediction of breast cancer using logistic LASSO regression.

  6. Factors associated with performing tuberculosis screening of HIV-positive patients in Ghana: LASSO-based predictor selection in a large public health data set

    Directory of Open Access Journals (Sweden)

    Susanne Mueller-Using

    2016-07-01

    Full Text Available Abstract Background The purpose of this study is to propose the Least Absolute Shrinkage and Selection Operators procedure (LASSO as an alternative to conventional variable selection models, as it allows for easy interpretation and handles multicollinearities. We developed a model on the basis of LASSO-selected parameters in order to link associated demographical, socio-economical, clinical and immunological factors to performing tuberculosis screening in HIV-positive patients in Ghana. Methods Applying the LASSO method and multivariate logistic regression analysis on a large public health data set, we selected relevant predictors related to tuberculosis screening. Results One Thousand Ninety Five patients infected with HIV were enrolled into this study with 691 (63.2 % of them having tuberculosis screening documented in their patient folders. Predictors found to be significantly associated with performance of tuberculosis screening can be classified into factors related to the clinician’s perception of the clinical state, as well as those related to PLHIV’s awareness. These factors include newly diagnosed HIV infections (n = 354 (32.42 %, aOR 1.84, current CD4+ T cell count (aOR 0.92, non-availability of HIV type (n = 787 (72.07 %, aOR 0.56, chronic cough (n = 32 (2.93 %, aOR 5.07, intake of co-trimoxazole (n = 271 (24.82 %, aOR 2.31, vitamin supplementation (n = 220 (20.15 %, aOR 2.64 as well as the use of mosquito bed nets (n = 613 (56.14 %, aOR 1.53. Conclusions Accelerated TB screening among newly diagnosed HIV-patients indicates that application of the WHO screening form for intensifying tuberculosis case finding among HIV-positive individuals in resource-limited settings is increasingly adopted. However, screening for TB in PLHIV is still impacted by clinician’s perception of patient’s health state and PLHIV’s health awareness. Education of staff, counselling of PLHIV and sufficient financing are

  7. Removal of alachlor, diuron and isoproturon in water in a falling film dielectric barrier discharge (DBD) reactor combined with adsorption on activated carbon textile: Reaction mechanisms and oxidation by-products.

    Science.gov (United States)

    Vanraes, Patrick; Wardenier, Niels; Surmont, Pieter; Lynen, Frederic; Nikiforov, Anton; Van Hulle, Stijn W H; Leys, Christophe; Bogaerts, Annemie

    2018-05-03

    A falling film dielectric barrier discharge (DBD) plasma reactor combined with adsorption on activated carbon textile material was optimized to minimize the formation of hazardous oxidation by-products from the treatment of persistent pesticides (alachlor, diuron and isoproturon) in water. The formation of by-products and the reaction mechanism was investigated by HPLC-TOF-MS. The maximum concentration of each by-product was at least two orders of magnitude below the initial pesticide concentration, during the first 10 min of treatment. After 30 min of treatment, the individual by-product concentrations had decreased to values of at least three orders of magnitude below the initial pesticide concentration. The proposed oxidation pathways revealed five main oxidation steps: dechlorination, dealkylation, hydroxylation, addition of a double-bonded oxygen and nitrification. The latter is one of the main oxidation mechanisms of diuron and isoproturon for air plasma treatment. To our knowledge, this is the first time that the formation of nitrificated intermediates is reported for the plasma treatment of non-phenolic compounds. Copyright © 2018 Elsevier B.V. All rights reserved.

  8. Application of multi-SNP approaches Bayesian LASSO and AUC-RF to detect main effects of inflammatory-gene variants associated with bladder cancer risk.

    Directory of Open Access Journals (Sweden)

    Evangelina López de Maturana

    Full Text Available The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988 controls from the Spanish Bladder Cancer (SBC/EPICURO Study. A preliminary exploration with the widely used univariate logistic regression approach did not identify any significant SNP after correcting for multiple testing. We further applied two more comprehensive methods to capture the complexity of bladder cancer genetic susceptibility: Bayesian Threshold LASSO (BTL, a regularized regression method, and AUC-Random Forest, a machine-learning algorithm. Both approaches explore the joint effect of markers. BTL analysis identified a signature of 37 SNPs in 34 genes showing an association with bladder cancer. AUC-RF detected an optimal predictive subset of 56 SNPs. 13 SNPs were identified by both methods in the total population. Using resources from the Texas Bladder Cancer study we were able to replicate 30% of the SNPs assessed. The associations between inflammatory SNPs and bladder cancer were reexamined among non-smokers to eliminate the effect of tobacco, one of the strongest and most prevalent environmental risk factor for this tumor. A 9 SNP-signature was detected by BTL. Here we report, for the first time, a set of SNP in inflammatory genes jointly associated with bladder cancer risk. These results highlight the importance of the complex structure of genetic susceptibility associated with cancer risk.

  9. Performance Analysis of Hospitals Affiliated to Mashhad University of Medical Sciences Using the Pabon Lasso Model: A Six-Year-Trend Study

    Directory of Open Access Journals (Sweden)

    Kalhor

    2016-08-01

    Full Text Available Background Nowadays, productivity and efficiency are considered a culture and a perspective in both life and work environments. This is the starting point of human development. Objectives The aim of the present study was to investigate the performance of hospitals affiliated to Mashhad University of Medical Sciences using the Pabon Lasso Model. Methods The present study was a descriptive-analytic research, with a cross-sectional design, conducted during six years (2009 - 2014, at selected hospitals. The studied hospitals of this study were 21 public hospitals affiliated to Mashhad University of Medical Sciences. The data was obtained from the treatment Deputy of Khorasan Razavi province. Results Results from the present study showed that only 19% of the studied hospitals were located in zone 3 of the diagram, indicating a perfect performance. Twenty-eight percent were in zone 1, 19% in zone 2, and 28% in zone 4. Conclusions According to the findings, only a few hospitals are at the desirable zone (zone 3; the rest of the hospitals fell in other zones, which could be a result of poor performance and poor management of hospital resources. Most of the hospitals were in zones 1 and 4, whose characteristics are low bed turnover and longer stay, indicating higher bed supply than demand for healthcare services or longer hospitalization, less outpatient equipment use, and higher costs.

  10. Diseño de un modelo de descripción, valoración, clasificación y remuneración de puestos para la empresa Novacero S.A., planta Lasso

    OpenAIRE

    Cajas Garzón, Alexandra Maribel

    2012-01-01

    208 hojas : ilustraciones, 29 x 21 cm El presente proyecto de titulación tiene por objetivo diseñar un Modelo de Descripción, Valoración, Clasificación y Remuneración de Puestos, aplicando la Metodología HAY de Valoración de Cargos por Perfiles y Escalas, para la Empresa NOVACERO S.A. Planta Lasso. Se definió un Mapa de Procesos, considerando los que están orientados a satisfacer las necesidades del cliente interno y externo lo cual es un insumo básico para proceder con la identificación ...

  11. Lassoing the Determinants of Retirement

    DEFF Research Database (Denmark)

    Kallestrup-Lamb, Malene; Kock, Anders Bredahl; Kristensen, Johannes Tang

    2016-01-01

    This article uses Danish register data to explain the retirement decision of workers in 1990 and 1998. Many variables might be conjectured to influence this decision such as demographic, socioeconomic, financial, and health related variables as well as all the same factors for the spouse in case ...... that this is the case for core variables such as age, income, wealth, and general health. We also point out the most important differences between these groups and explain why these might be present.......This article uses Danish register data to explain the retirement decision of workers in 1990 and 1998. Many variables might be conjectured to influence this decision such as demographic, socioeconomic, financial, and health related variables as well as all the same factors for the spouse in case...

  12. Lassoing the Determinants of Retirement

    DEFF Research Database (Denmark)

    Kallestrup-Lamb, Malene; Kock, Anders Bredahl; Kristensen, Johannes Tang

    This paper uses Danish register data to explain the retirement decision of workers in 1990 and 1998.Many variables might be conjectured to influence this decision such as demographic, socio-economic, financially and health related variables as well as all the same factors for the spouse in case t...... such as age, income, wealth and general health. We also point out themost important differences between these groups and explain why these might be present.......This paper uses Danish register data to explain the retirement decision of workers in 1990 and 1998.Many variables might be conjectured to influence this decision such as demographic, socio-economic, financially and health related variables as well as all the same factors for the spouse in case...

  13. ACETANILIDE HERBICIDE DEGRADATION PRODUCTS BY LC/MS

    Science.gov (United States)

    Acetanilide herbicides are frequently applied in the U.S. on crops (corn, soybeans, popcorn, etc.) to control broadleaf and annual weeds. The acetanilide and acetamide herbicides currently registered for use in the U.S. are alachlor, acetochlor, metolachlor, propachlor, flufen...

  14. Identification and ecotoxicity of degradation products of chloroacetamide herbicides from UV-treatment of water

    DEFF Research Database (Denmark)

    Souissi, Yasmine; Bouchonnet, Stéphane; Bourcier, Sophie

    2013-01-01

    The widespread occurrence of chlorinated herbicides and their degradation products in the aquatic environment raises health and environmental concerns. As a consequence pesticides, and to a lesser degree their degradation products, are monitored by authorities both in surface waters and drinking...... waters. In this study the formation of degradation products from ultraviolet (UV) treatment of the three chloroacetamide herbicides acetochlor, alachlor and metolachlor and their biological effects were investigated. UV treatment is mainly used for disinfection in water and wastewater treatments. First...

  15. Capturing the musical brain with Lasso

    DEFF Research Database (Denmark)

    Toiviainen, Petri; Alluri, Vinoo; Brattico, Elvira

    2014-01-01

    accuracy using a leave-one-out cross-validation scheme. The method was applied to functional magnetic resonance imaging (fMRI) data that were collected using a naturalistic paradigm, in which participants' brain responses were recorded while they were continuously listening to pieces of real music...... to be consistent with areas of significant activation observed in previous research using a naturalistic paradigm with fMRI. Of the six musical features considered, five could be significantly predicted for the majority of participants. The areas significantly contributing to the optimal decoding models agreed...

  16. Influence of herbicide structure, clay acidity, and humic acid coating on acetanilide herbicide adsorption on homoionic clays.

    Science.gov (United States)

    Liu, Weiping; Gan, Jianying; Yates, Scott R

    2002-07-03

    Adsorption of chloroacetanilide herbicides on homoionic montmorillonite was studied by coupling batch equilibration and FT-IR analysis. Adsorption decreased in the order metolachlor > acetochlor > alachlor > propachlor on Ca(2+)- or Mg(2+)-saturated clays and in the order metolachlor > alachlor > acetachlor > propachlor on Al(3+)- or Fe(3+)-saturated clays. FT-IR spectra showed that the carbonyl group of the herbicide molecule was involved in bonding. For the same herbicide, adsorption of alachlor, acetachlor, and metolachlor on clay followed the order Ca(2+) approximately Mg(2+) < Al(3+) < or = Fe(3+), which coincided with the increasing acidity of homoionic clays. Adsorption of propachlor, however, showed an opposite dependence, suggesting a different governing interaction. In clay and humic acid mixtures, herbicide adsorption was less than that expected from independent additive adsorption by the individual constituents, and the deviation was dependent on the clay-to-humic acid ratio, with the greatest deviation consistently occurring at a 60:40 clay-to-humic acid ratio.

  17. Comparative metabolism and elimination of acetanilide compounds by rat.

    Science.gov (United States)

    Davison, K L; Larsen, G L; Feil, V J

    1994-10-01

    1. 14C-labelled propachlor, alachlor, butachlor, metolachlor, methoxypropachlor and some of their mercapturic acid pathway metabolites (MAP) were given to rat either by gavage or by perfusion into a renal artery. MAP metabolites were isolated from bile and urine. 2. Rat gavaged with propachlor and methoxypropachlor eliminated 14C mostly in urine, whereas rat gavaged with alachlor, butachlor and metolachlor eliminated 14C about equally divided between urine and faeces. When bile ducts were cannulated, the gavaged rat eliminated most of the 14C in bile for all compounds. The amount of 14C in bile from the propachlor-gavaged rat was less than that for the other acetanilides, with the difference being in the urine. 3. The mercapturic acid metabolites 2-methylsulphinyl-N-(1-methylhydroxyethyl)-N-phenylacetam ide and 2-methylsulphinyl-N-(1-methylmethoxyethyl)-N-phenylacetam ide were isolated from the urine and bile of the methoxypropachlor-gavaged rat. 4. Bile was the major route for 14C elimination when MAP metabolites of alachlor, butachlor and metolachlor were perfused into a renal artery. Urine was the major route for 14C elimination when MAP metabolites of propachlor and methoxypropachlor were perfused. Mercapturic acid conjugates were major metabolites in bile and urine when MAP metabolites were perfused. 5. We conclude that alkyl groups on the phenyl portion of the acetanilide causes biliary elimination to be favoured over urinary elimination.

  18. 40 CFR 180.249 - Alachlor; tolerances for residues.

    Science.gov (United States)

    2010-07-01

    ... seed 0.03 Cowpea, forage 5.0 Cowpea, hay 5.0 Egg 0.02 Goat, fat 0.02 Goat, meat byproducts 0.02 Goat, meat 0.02 Hog, fat 0.02 Hog meat byproducts 0.02 Hog, meat 0.02 Horse, fat 0.02 Horse, meat byproducts..., dry 0.1 Beans, succulent lima 0.1 Cattle, fat 0.02 Cattle, meat byproducts 0.02 Cattle, meat 0.02 Corn...

  19. Toxicity of three selected pesticides (Alachlor, Atrazine and Diuron ...

    African Journals Online (AJOL)

    Lazhar Mhadhbi

    2012-06-26

    Jun 26, 2012 ... The present study aimed to evaluate acute toxicity tests for three selected ... Median lethal concentrations of the selected pesticides during a 48 h and 96 h exposure for .... Dunnett's post-hoc test, using the SPSS application, version 19.0. ..... to define the primary mode of toxic action for diverse industrial.

  20. Eleven-year trend in acetanilide pesticide degradates in the Iowa River, Iowa.

    Science.gov (United States)

    Kalkhoff, Stephen J; Vecchia, Aldo V; Capel, Paul D; Meyer, Michael T

    2012-01-01

    Trends in concentration and loads of acetochlor, alachlor, and metolachlor and their ethanasulfonic (ESA) and oxanilic (OXA) acid degradates were studied from 1996 through 2006 in the main stem of the Iowa River, Iowa and in the South Fork Iowa River, a small tributary near the headwaters of the Iowa River. Concentration trends were determined using the parametric regression model SEAWAVE-Q, which accounts for seasonal and flow-related variability. Daily estimated concentrations generated from the model were used with daily streamflow to calculate daily and yearly loads. Acetochlor, alachlor, metolachlor, and their ESA and OXA degradates were generally present in >50% of the samples collected from both sites throughout the study. Their concentrations generally decreased from 1996 through 2006, although the rate of decrease was slower after 2001. Concentrations of the ESA and OXA degradates decreased from 3 to about 23% yr. The concentration trend was related to the decreasing use of these compounds during the study period. Decreasing concentrations and constant runoff resulted in an average reduction of 10 to >3000 kg per year of alachlor and metolachlor ESA and OXA degradates being transported out of the Iowa River watershed. Transport of acetochlor and metolachlor parent compounds and their degradates from the Iowa River watershed ranged from <1% to about 6% of the annual application. These trends were related to the decreasing use of these compounds during the study period, but the year-to-year variability cannot explain changes in loads based on herbicide use alone. The trends were also affected by the timing and amount of precipitation. As expected, increased amounts of water moving through the watershed moved a greater percentage of the applied herbicides, especially the relatively soluble degradates, from the soils into the rivers through surface runoff, shallow groundwater inflow, and subsurface drainage. Copyright © by the American Society of Agronomy

  1. 40 CFR 180.368 - Metolachlor; tolerances for residues.

    Science.gov (United States)

    2010-07-01

    ...) PESTICIDE PROGRAMS TOLERANCES AND EXEMPTIONS FOR PESTICIDE CHEMICAL RESIDUES IN FOOD Specific Tolerances....02 Poultry, meat byproducts 0.05 Pumpkin 0.10 Safflower, seed 0.10 Shallot, bulb 0.10 Sheep, fat 0.02... or on the following food commodities: Commodity Parts per million Animal feed, nongrass, group 18 1.0...

  2. effect of fluazitopbutyl and atrazine/metolachlor for weed control

    African Journals Online (AJOL)

    COCOYAM

    also gave the highest yield and monetary gain when compares with manual weeding. This technique will be ... be a “back yard” crop or “gap filler”. Survey reports in .... Critical period of weed interference intercropped with maize and cocoyam.

  3. 75 FR 56897 - S-metolachlor; Pesticide Tolerances

    Science.gov (United States)

    2010-09-17

    ... not limited to those engaged in the following activities: Crop production (NAICS code 111). Animal production (NAICS code 112). Food manufacturing (NAICS code 311). Pesticide manufacturing (NAICS code 32532... 13-07B at 0.15 ppm; onion, bulb, subgroup 3-07A at 0.1 ppm; and onion, green, subgroup 3-07B at 2.0...

  4. Overexpression of a specific soybean GmGSTU4 isoenzyme improves diphenyl ether and chloroacetanilide herbicide tolerance of transgenic tobacco plants.

    Science.gov (United States)

    Benekos, Kostantinos; Kissoudis, Christos; Nianiou-Obeidat, Irini; Labrou, Nikolaos; Madesis, Panagiotis; Kalamaki, Mary; Makris, Antonis; Tsaftaris, Athanasios

    2010-10-01

    Plant glutathione transferases (GSTs) superfamily consists of multifunctional enzymes and forms a major part of the plants herbicide detoxification enzyme network. The tau class GST isoenzyme GmGSTU4 from soybean, exhibits catalytic activity towards the diphenyl ether herbicide fluorodifen and is active as glutathione-dependent peroxidase (GPOX). Transgenic tobacco plants of Basmas cultivar were generated via Agrobacterium transformation. The aim was to evaluate in planta, GmGSTU4's role in detoxifying the diphenyl ether herbicides fluorodifen and oxyfluorfen and the chloroacetanilides alachlor and metolachlor. Transgenic tobacco plants were verified by PCR and Southern blot hybridization and expression of GmGSTU4 was determined by RT-PCR. Leaf extracts from transgenic plants showed moderate increase in GST activity towards CDNB and a significant increase towards fluorodifen and alachlor, and at the same time an increased GPOX activity towards cumene hydroperoxide. GmGSTU4 overexpressing plants when treated with 200 μM fluorodifen or oxyfluorfen exhibited reduced relative electrolyte leakage compared to wild type plants. Moreover all GmGSTU4 overexpressing lines exhibited significantly increased tolerance towards alachlor when grown in vitro at 7.5 mg/L alachlor compared to wild type plants. No significant increased tolerance was observed to metolachlor. These results confirm the contribution of this particular GmGSTU4 isoenzyme from soybean in the detoxification of fluorodifen and alachlor, and provide the basis towards the development of transgenic plants with improved phytoremediation capabilities for future use in environmental cleanup of herbicides. Copyright © 2010 Elsevier B.V. All rights reserved.

  5. Using compound-specific isotope analysis to assess the degradation of chloroacetanilide herbicides in lab-scale wetlands.

    Science.gov (United States)

    Elsayed, O F; Maillard, E; Vuilleumier, S; Nijenhuis, I; Richnow, H H; Imfeld, G

    2014-03-01

    Compound-specific isotope analysis (CSIA) is a promising tool to study the environmental fate of a wide range of contaminants including pesticides. In this study, a novel CSIA method was developed to analyse the stable carbon isotope signatures of widely used chloroacetanilide herbicides. The developed method was applied in combination with herbicide concentration and hydrochemical analyses to investigate in situ biodegradation of metolachlor, acetochlor and alachlor during their transport in lab-scale wetlands. Two distinct redox zones were identified in the wetlands. Oxic conditions prevailed close to the inlet of the four wetlands (oxygen concentration of 212±24μM), and anoxic conditions (oxygen concentrations of 28±41μM) prevailed towards the outlet, where dissipation of herbicides mainly occurred. Removal of acetochlor and alachlor from inlet to outlet of wetlands was 56% and 51%, whereas metolachlor was more persistent (23% of load dissipation). CSIA of chloroacetanilides at the inlet and outlet of the wetlands revealed carbon isotope fractionation of alachlor (εbulk=-2.0±0.3‰) and acetochlor (εbulk=-3.4±0.5‰), indicating that biodegradation contributes to the dissipation of both herbicides. This study is a first step towards the application of CSIA to evaluate the transport and degradation of chloroacetanilide herbicides in the environment. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. Estudo de sorção de herbicidas pelos argilominerais vermiculita e montmorilonita

    Directory of Open Access Journals (Sweden)

    Edivaltrys Inayve Pissinati de Rezende

    2011-01-01

    Full Text Available The clay minerals montmorillonite (MT and vermiculite (VT, previously treated with Ca2+, K+ and Na+, were employed in a sorption study with herbicides. The herbicides 2,4-D, diuron, alachlor and metolachlor showed no interaction with MT and VT. On the other hand, the triazines presented a good sorption process, close to 100% for ametrine removal and near to 56 and 69% for atrazine and simazine, respectively, by MT. These results suggest that the MT specie may be a good material for triazines removal from aqueous medium and an alternative phase to preconcentration process, besides to exhibit a good selectivity.

  7. Work plan for determining the occurrence of glyphosate, its transformation product AMPA, other herbicide compounds, and antibiotics in midwestern United States streams, 2002

    Science.gov (United States)

    Battaglin, W.A.; Thurman, E.M.; Kolpin, D.W.; Scribner, E.A.; Sandstrom, M.W.; Kuivila, K.M.

    2003-01-01

    Changes in herbicide use in the Midwestern United States have been substantial over the last 5 years. Most significant is a tripling in the use of glyphosate (N-[phosphonomethyl]glycin). Over this same time period (1997­2001), atrazine use increased by 20 percent and acetochlor use increased by 10 percent, while cyanazine use decreased by 99 percent, alachlor use decreased by 70 percent, and metolachlor use decreased by 55 percent. Previous studies have documented that herbicide flushes occur in midwestern streams during runoff events for several weeks to several months following application, and that herbicide concentrations in midwestern streams during flushing events are related to rates of herbicide use.

  8. Synthetic organic agrochemicals in the lower Mississippi River and its major tributaries: Distribution, transport and fate

    Science.gov (United States)

    Pereira, W.E.; Rostad, C.E.; Leiker, T.J.; ,

    1992-01-01

    The Mississippi River and its major tributaries transport herbicides and their degradation products from agricultural areas in the mid-western U.S.A. These compounds include atrazine and its degradation products (desethyl- and desisopropylatrazine), simazine, cyanazine, metolachlor, and alachlor and its degradation products (2-chloro-2',6'-diethylacetanilide, 2-hydroxy-2',6'-diethylacetanilide and 2,6-diethylaniline). These compounds were identified and confirmed by gas chromatography-ion trap mass spectrometry. Loads of these compounds were determined during five sampling trips in 1987-1989. Stream loads of these compounds indicated that atrazine and metolachlor were relatively conservative in downstream transport. Alachlor and its degradation products were generated from point and non-point sources. Seasonal variations and hydrologic conditions controlled the loads of these compounds in the Mississippi River. Cross-channel mixing was slow downstream from major river confluences, possibly requiring several hundred kilometers of downriver transit for completion. The annual transport of these compounds into the Gulf of Mexico was estimated to be < 2% of the annual application of each herbicide in the Midwest.The Mississippi River and its major tributaries transport herbicides and their degradation products from agricultural areas in the mid-western U.S.A. These compounds include atrazine and its degradation products (desethyl- and desisopropylatrazine), simazine, cyanazine, metolachlor, and alachlor and its degradation products (2-chloro-2???,6???-diethylacetanilide, 2-hydroxy-2???,6???-diethylacetanilide and 2,6-diethylaniline). These compounds were identified and confirmed by gas chromatography-ion trap mass spectrometry. Loads of these compounds were determined during five sampling trips in 1987-1989. Stream loads of these compounds indicated that atrazine and metolachlor were relatively conservative in downstream transport. Alachlor and its degradation products

  9. Mapping Haplotype-haplotype Interactions with Adaptive LASSO

    Directory of Open Access Journals (Sweden)

    Li Ming

    2010-08-01

    Full Text Available Abstract Background The genetic etiology of complex diseases in human has been commonly viewed as a complex process involving both genetic and environmental factors functioning in a complicated manner. Quite often the interactions among genetic variants play major roles in determining the susceptibility of an individual to a particular disease. Statistical methods for modeling interactions underlying complex diseases between single genetic variants (e.g. single nucleotide polymorphisms or SNPs have been extensively studied. Recently, haplotype-based analysis has gained its popularity among genetic association studies. When multiple sequence or haplotype interactions are involved in determining an individual's susceptibility to a disease, it presents daunting challenges in statistical modeling and testing of the interaction effects, largely due to the complicated higher order epistatic complexity. Results In this article, we propose a new strategy in modeling haplotype-haplotype interactions under the penalized logistic regression framework with adaptive L1-penalty. We consider interactions of sequence variants between haplotype blocks. The adaptive L1-penalty allows simultaneous effect estimation and variable selection in a single model. We propose a new parameter estimation method which estimates and selects parameters by the modified Gauss-Seidel method nested within the EM algorithm. Simulation studies show that it has low false positive rate and reasonable power in detecting haplotype interactions. The method is applied to test haplotype interactions involved in mother and offspring genome in a small for gestational age (SGA neonates data set, and significant interactions between different genomes are detected. Conclusions As demonstrated by the simulation studies and real data analysis, the approach developed provides an efficient tool for the modeling and testing of haplotype interactions. The implementation of the method in R codes can be freely downloaded from http://www.stt.msu.edu/~cui/software.html.

  10. Structural Graphical Lasso for Learning Mouse Brain Connectivity

    KAUST Repository

    Yang, Sen; Sun, Qian; Ji, Shuiwang; Wonka, Peter; Davidson, Ian; Ye, Jieping

    2015-01-01

    Investigations into brain connectivity aim to recover networks of brain regions connected by anatomical tracts or by functional associations. The inference of brain networks has recently attracted much interest due to the increasing availability

  11. Controlling the local false discovery rate in the adaptive Lasso

    KAUST Repository

    Sampson, J. N.; Chatterjee, N.; Carroll, R. J.; Muller, S.

    2013-01-01

    FDR. We compare the smoothing parameters chosen to achieve a specified lFDR and those chosen to achieve the oracle properties, as well as their resulting estimates for model coefficients, with both simulation and an example from a genetic study of prostate

  12. ORACLE INEQUALITIES FOR THE LASSO IN THE COX MODEL.

    Science.gov (United States)

    Huang, Jian; Sun, Tingni; Ying, Zhiliang; Yu, Yi; Zhang, Cun-Hui

    2013-06-01

    We study the absolute penalized maximum partial likelihood estimator in sparse, high-dimensional Cox proportional hazards regression models where the number of time-dependent covariates can be larger than the sample size. We establish oracle inequalities based on natural extensions of the compatibility and cone invertibility factors of the Hessian matrix at the true regression coefficients. Similar results based on an extension of the restricted eigenvalue can be also proved by our method. However, the presented oracle inequalities are sharper since the compatibility and cone invertibility factors are always greater than the corresponding restricted eigenvalue. In the Cox regression model, the Hessian matrix is based on time-dependent covariates in censored risk sets, so that the compatibility and cone invertibility factors, and the restricted eigenvalue as well, are random variables even when they are evaluated for the Hessian at the true regression coefficients. Under mild conditions, we prove that these quantities are bounded from below by positive constants for time-dependent covariates, including cases where the number of covariates is of greater order than the sample size. Consequently, the compatibility and cone invertibility factors can be treated as positive constants in our oracle inequalities.

  13. Accelerated remediation of pesticide-contaminated soil with zerovalent iron

    Energy Technology Data Exchange (ETDEWEB)

    Shea, P.J. [University of Nebraska-Lincoln, Lincoln, NE 68583-0915 (United States)]. E-mail: pshea@unl.edu; Machacek, T.A. [University of Nebraska-Lincoln, Lincoln, NE 68583-0915 (United States); Comfort, S.D. [University of Nebraska-Lincoln, Lincoln, NE 68583-0915 (United States)

    2004-11-01

    High pesticide concentrations in soil from spills or discharges can result in point-source contamination of ground and surface waters. Cost-effective technologies are needed for on-site treatment that meet clean-up goals and restore soil function. Remediation is particularly challenging when a mixture of pesticides is present. Zerovalent iron (Fe{sup 0}) has been shown to promote reductive dechlorination and nitro group reduction of a wide range of contaminants in soil and water. We employed Fe{sup 0} for on-site treatment of soil containing >1000 mg metolachlor, >55 mg alachlor, >64 mg atrazine, >35 mg pendimethalin, and >10 mg chlorpyrifos kg{sup -1}. While concentrations were highly variable within the windrowed soil, treatment with 5% (w/w) Fe{sup 0} resulted in >60% destruction of the five pesticides within 90 d and increased to >90% when 2% (w/w) Al{sub 2}(SO{sub 4}){sub 3} was added to the Fe{sup 0}. GC/MS analysis confirmed dechlorination of metolachlor and alachlor during treatment. Our observations support the use of Fe{sup 0} for ex situ treatment of pesticide-contaminated soil. - Capsule: Zerovalent iron promotes pesticide degradation in highly contaminated soil.

  14. Determination of chloroacetanilide herbicide metabolites in water using high-performance liquid chromatography-diode array detection and high-performance liquid chromatography/mass spectrometry

    Science.gov (United States)

    Hostetler, K.A.; Thurman, E.M.

    2000-01-01

    Analytical methods using high-performance liquid chromatography-diode array detection (HPLC-DAD) and high-performance liquid chromatography/mass spectrometry (HPLC/MS) were developed for the analysis of the following chloroacetanilide herbicide metabolites in water: alachlor ethanesulfonic acid (ESA); alachlor oxanilic acid; acetochlor ESA; acetochlor oxanilic acid; metolachlor ESA; and metolachlor oxanilic acid. Good precision and accuracy were demonstrated for both the HPLC-DAD and HPLC/MS methods in reagent water, surface water, and ground water. The average HPLC-DAD recoveries of the chloroacetanilide herbicide metabolites from water samples spiked at 0.25, 0.5 and 2.0 ??g/l ranged from 84 to 112%, with relative standard deviations of 18% or less. The average HPLC/MS recoveries of the metabolites from water samples spiked at 0.05, 0.2 and 2.0 ??g/l ranged from 81 to 118%, with relative standard deviations of 20% or less. The limit of quantitation (LOQ) for all metabolites using the HPLC-DAD method was 0.20 ??g/l, whereas the LOQ using the HPLC/MS method was at 0.05 ??g/l. These metabolite-determination methods are valuable for acquiring information about water quality and the fate and transport of the parent chloroacetanilide herbicides in water. Copyright (C) 2000 Elsevier Science B.V.

  15. Synthetic organic agrochemicals in the lower Mississippi River and its major tributaries--Distribution, transport and fate

    Science.gov (United States)

    Pereira, W.E.; Rostad, C.E.; Leiker, T.J.

    1992-01-01

    The Mississippi River and its major tributaries transport herbicides and their degradation products from agricultural areas in the mid-western U.S.A. These compounds include atrazine and its degradation products (desethyl- and desisopropylatrazine), simazine, cyanazine, metolachlor, and alachlor and its degradation products (2-chloro-2′,6′-diethylacetanilide 2-hydroxy-2′,6′-diethylacetanilide and 2,6-diethylaniline). These compounds were identified and confirmed by gas chromatography-ion trap mass spectrometry. Loads of these compounds were determined during five sampling trips in 1987–1989. Stream loads of these compounds indicated that atrazine and metolachlor were relatively conservative in downstream transport. Alachlor and its degradation products were generated from point and non-point sources. Seasonal variations and hydrologic conditions controlled the loads of these compounds in the Mississippi River. Cross-channel mixing was slow downstream from major river confluences, possibly requiring several hundred kilometers of downriver transit for completion. The annual transport of these compounds into the Gulf of Mexico was estimated to be < 2% of the annual application of each herbicide in the Midwest.

  16. Determination of trace triazine and chloroacetamide herbicides in tile-fed drainage ditch water using solid-phase microextraction coupled with GC-MS

    Energy Technology Data Exchange (ETDEWEB)

    Rocha, Cleonice [Catholic University of Goias, Av. Universitaria, 1440 S. Universitario, Cx (Brazil); Pappas, Elizabeth A. [USDA ARS, National Soil Erosion Research Laboratory, 275 S. Russell Street, West Lafayette, IN 47907 (United States)], E-mail: bets@purdue.edu; Huang, C.-H. [USDA ARS, National Soil Erosion Research Laboratory, 275 S. Russell Street, West Lafayette, IN 47907 (United States)

    2008-03-15

    Solid-phase microextraction coupled with gas chromatography-mass spectrometry (SPME-GC-MS) was used to analyze two triazine (atrazine and simazine) and three chloroacetamide herbicides (acetochlor, alachlor, and metolachlor) in water samples from a midwest US agricultural drainage ditch for two growing seasons. The effects of salt concentration, sample volume, extraction time, and injection time on extraction efficiency using a 100-{mu}m polydimethylsiloxane-coated fiber were investigated. By optimizing these parameters, ditch water detection limits of 0.5 {mu}g L{sup -1} simazine and 0.25 {mu}g L{sup -1} atrazine, acetochlor, alachlor, and metolachlor were achieved. The optimum salt concentration was found to be 83% NaCl, while sample volume (10 or 20 mL) negligibly affected analyte peak areas. The optimum extraction time was 40 min, and the optimum injection time was 15 min. Results indicated that atrazine levels in the ditch water exceeded the US maximum contaminant level for drinking water 12% of the time, and atrazine was the most frequently detected among studied analytes. - Solid-phase microextraction methods were successfully developed to quantify low levels of herbicides in tile-fed drain water by gas chromatography-mass spectrometry.

  17. Characterization of acetanilide herbicides degrading bacteria isolated from tea garden soil.

    Science.gov (United States)

    Wang, Yei-Shung; Liu, Jian-Chang; Chen, Wen-Ching; Yen, Jui-Hung

    2008-04-01

    Three different green manures were added to the tea garden soils separately and incubated for 40 days. After, incubation, acetanilide herbicides alachlor and metolachlor were spiked into the soils, separately, followed by the isolation of bacteria in each soil at designed intervals. Several bacterial strains were isolated from the soils and identified as Bacillus silvestris, B. niacini, B. pseudomycoides, B. cereus, B. thuringiensis, B. simplex, B. megaterium, and two other Bacillus sp. (Met1 and Met2). Three unique strains with different morphologies were chosen for further investigation. They were B. megaterium, B. niacini, and B. silvestris. The isolated herbicide-degrading bacteria showed optimal performance among three incubation temperatures of 30 degrees C and the best activity in the 10 to 50 microg/ml concentration of the herbicide. Each bacterial strain was able to degrade more than one kind of test herbicides. After incubation for 119 days, B. cereus showed the highest activity to degrade alachlor and propachlor, and B. thuringiensis to degrade metolachlor.

  18. Adsorption of chloroacetanilide herbicides on soil and its components. III. Influence of clay acidity, humic acid coating and herbicide structure on acetanilide herbicide adsorption on homoionic clays.

    Science.gov (United States)

    Liu, Wei-ping; Fang, Zhuo; Liu, Hui-jun; Yang, Wei-chun

    2002-04-01

    Adsorption of chloroacetanilide herbicides on homoionic montmorillonite, soil humic acid, and their mixtures was studied by coupling batch equilibration and FT-IR analysis. Adsorption isotherms of acetochlor, alachlor, metolachlor and propachlor on Ca(2+)-, Mg(2+)-, Al(3+)- and Fe(3+)-saturated clays were well described by the Freundlich equation. Regardless of the type of exchange cations, Kf decreased in the order of metolachlor > acetolachlor > alachlor > propachlor on the same clay. FT-IR spectra showed that the carbonyl group of the herbicide molecule was involved in binding, probably via H-bond with water molecules in the clay interlayer. The type and position of substitutions around the carbonyl group may have affected the electronegativity of oxygen, thus influencing the relative adsorption of these herbicides. For the same herbicide, adsorption on clay increased in the order of Mg2+ < Ca2+ < Al3+ < or = Fe3+ which coincided with the increasing acidity of homoionic clays. Acidity of cations may have affected the protonation of water, and thus the strength of H-bond between the clay water and herbicide. Complexation of clay and humic acid resulted in less adsorption than that expected from independent adsorption by the individual constituents. The effect varied with herbicides, but the greatest decrease in adsorption occurred at a 60:40 clay-to-humic acid ratio for all the herbicides. Causes for the decreased adsorption need to be characterized to better understand adsorption mechanisms and predict adsorption from soil compositions.

  19. HPLC-NMR INVESTIGATION OF THE ISOMERIZATION OF ALACHLOR-ETHANE SULFONIC ACID. (R829008)

    Science.gov (United States)

    The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

  20. Pesticide and transformation product detections and age-dating relations from till and sand deposits

    Science.gov (United States)

    Warner, K.L.; Morrow, W.S.

    2007-01-01

    Pesticide and transformation product concentrations and frequencies in ground water from areas of similar crop and pesticide applications may vary substantially with differing lithologies. Pesticide analysis data for atrazine, metolachlor, alachlor, acetochlor, and cyanazine and their pesticide transformation products were collected at 69 monitoring wells in Illinois and northern Indiana to document occurrence of pesticides and their transformation products in two agricultural areas of differing lithologies, till, and sand. The till is primarily tile drained and has preferential fractured flow, whereas the sand primarily has surface water drainage and primary porosity flow. Transformation products represent most of the agricultural pesticides in ground water regardless of aquifer material - till or sand. Transformation products were detected more frequently than parent pesticides in both the till and sand, with metolachlor ethane sulfonic acid being most frequently detected. Estimated ground-water recharge dates for the sand were based on chlorofluorocarbon analyses. These age-dating data indicate that ground water recharged prior to 1990 is more likely to have a detection of a pesticide or pesticide transformation product. Detections were twice as frequent in ground water recharged prior to 1990 (82%) than in ground water recharged on or after 1990 (33%). The highest concentrations of atrazine, alachlor, metolachlor, and their transformation products, also were detected in samples from ground water recharged prior to 1990. These age/pesticide detection relations are opposite of what would normally be expected, and may be the result of preferential flow and/or ground-water mixing between aquifers and aquitards as evident by the detection of acetochlor transformation products in samples with estimated ground-water ages predating initial pesticide application. ?? 2007 American Water Resources Association.

  1. Contribution of subsoil and aquifer microorganisms to ground-water quality. Technical report, 1 July 1988-30 June 1989. (Final)

    International Nuclear Information System (INIS)

    Turco, R.F.; Konopka, A.E.

    1989-06-01

    Little information about the microbiology of the subsurface environment is available. The study was conducted to better understand the microbiology and microbial processes that occur in the subsurface under a typical midwestern agricultural soil. A 26-meter bore was installed in November of 1988. Sterile collections of soils were made at 17 different depths. A physical as well as biological investigation of the subsurface materials was conducted. Among the measured parameters were particle-size analysis, carbon, carbonates, nitrogen, phosphorus, potassium, and water-holding capacity. The level of three pesticides, atrazine, metolachlor, and alachlor, was determined. Microbial biomass was assessed using direct counts, phospholipid content, and plate counts. The ability of microbial populations resident in the strata to use glucose, phenol, aniline, (14)C-ring labeled 2-methyl-6-ethyl-aniline, (14)C-ring labeled metolachlor, (14)C-carbonyl labeled metolachlor, and atrazine was assessed. Physical analysis indicated that the site contained up to 17 different strata. The site materials were primarily glacial tills with high carbonate content. Microbial numbers and activity in the tills was much lower than either in the surface materials or the aquifer located at 25 m

  2. Effect of meteorology and soil condition on metolachlor and atrazine volatilization over a 10 year period

    Science.gov (United States)

    Volatilization of pesticides can detrimentally affect the environment by contaminating soil and surface waters far away from where the pesticides were applied. A 10-year study was conducted to focus on the impact of soil and climatic factors governing herbicide volatilization from an agricultural f...

  3. Occurrence of pesticides in groundwater and sediments and mineralogy of sediments and grain coatings underlying the Rutgers Agricultural Research and Extension Center, Upper Deerfield, New Jersey, 2007

    Science.gov (United States)

    Reilly, Timothy J.; Smalling, Kelly L.; Meyer, Michael T.; Sandstrom, Mark W.; Hladik, Michelle; Boehlke, Adam R.; Fishman, Neil S.; Battaglin, William A.; Kuivila, Kathryn

    2014-01-01

    Water and sediment samples were collected from June through October 2007 from seven plots at the Rutgers Agricultural Research and Extension Center in Upper Deerfield, New Jersey, and analyzed for a suite of pesticides (including fungicides) and other physical and chemical parameters (including sediment mineralogy) by the U.S. Geological Survey. Plots were selected for inclusion in this study on the basis of the crops grown and the pesticides used. Forty-one pesticides were detected in 14 water samples; these include 5 fungicides, 13 herbicides, 1 insecticide, and 22 pesticide degradates. The following pesticides and pesticide degradates were detected in 50 percent or more of the groundwater samples: 1-amide-4-hydroxy-chorothalonil, alachlor sulfonic acid, metolachlor oxanilic acid, metolachlor sulfonic acid, metalaxyl, and simazine. Dissolved-pesticide concentrations ranged from below their instrumental limit of detection to 36 micrograms per liter (for metolachlor sulfonic acid, a degradate of the herbicide metolachlor). The total number of pesticides found in groundwater samples ranged from 0 to 29. Fourteen pesticides were detected in sediment samples from continuous cores collected within each of the seven sampled plots; these include 4 fungicides, 2 herbicides, and 7 pesticide degradates. Pesticide concentrations in sediment samples ranged from below their instrumental limit of detection to 34.2 nanograms per gram (for azoxystrobin). The total number of pesticides found in sediment samples ranged from 0 to 8. Quantitative whole-rock and grain-coating mineralogy of sediment samples were determined by x-ray diffraction. Whole-rock analysis indicated that sediments were predominantly composed of quartz. The materials coating the quartz grains were removed to allow quantification of the trace mineral phases present.

  4. Seletividade de clomazone isolado ou em mistura para a cultura do algodoeiro Selectivity of clomazone applied alone or in tank mixtures to cotton

    Directory of Open Access Journals (Sweden)

    H.A Dan

    2011-09-01

    Full Text Available O clomazone destaca-se como um dos principais herbicidas utilizados em pré-emergência na cultura do algodoeiro, mesmo levando-se em conta o fato de que muito pouco se sabe em relação à sua seletividade para a cultura. Objetivou-se com este trabalho avaliar a seletividade do clomazone isolado ou em mistura com outros herbicidas utilizados em pré-emergência na cultura do algodoeiro. O delineamento experimental foi o de blocos ao acaso, com quatro repetições, com a utilização de testemunhas duplas. Foram avaliados 13 tratamentos, os quais foram constituídos de clomazone isolado ou combinado com os herbicidas S-metolachlor, diuron, prometryne, alachlor, oxyfluorfen e trifluralin. Foram avaliados porcentagem de fitointoxicação, estande final, altura de plantas, número de maçãs e rendimento final de algodão em caroço. O clomazone, isolado nas doses de 1,00 e 1,25 kg ha-1 ou em associação com S-metolachlor (0,76 kg ha-1, diuron (1,50 kg ha-1, prometryne (1,50 kg ha-1, alachlor (1,44 kg ha-1 e trifluralin (1,80 kg ha-1, foi seletivo à cultura do algodão cv. Nu Opal. Em contrapartida, sua associação com oxyfluorfen (1,25 + 0,19 kg ha-1, trifluralin + diuron (1,25 + 1,80 + 1,50 kg ha-1 e trifluralin + prometryne (1,25 + 1,80 + 1,50 kg ha-1 proporcionou redução na produtividade do algodoeiro.Clomazone is one of the most important herbicides applied in pre-emergence in cotton, even though not much is known about its selectivity to this crop. This work was carried out to evaluate the selectivity of clomazone applied alone or in tank mixtures with other herbicides applied in pre-emergence in cotton. The experiment was designed as a randomized block, with four replicates, using two-fold checks. Thirteen treatments were evaluated, constituted by different combinations of clomazone with S-metolachlor, diuron, prometryne, alachlor, oxyfluorfen, and trifluralin. After herbicide application, visual crop injury was evaluated, as well as

  5. Comparative sensitivity of Selenastrum capricornutum and Lemna minor to sixteen herbicides

    Science.gov (United States)

    Fairchild, J.F.; Ruessler, D.S.; Haverland, P.S.; Carlson, A.R.

    1997-01-01

    Aquatic plant toxicity tests are frequently conducted in environmental risk assessments to determine the potential impacts of contaminants on primary producers. An examination of published plant toxicity data demonstrates that wide differences in sensitivity can occur across phylogenetic groups of plants. Yet relatively few studies have been conducted with the specific intent to compare the relative sensitivity of various aquatic plant species to contaminants. We compared the relative sensitivity of the algae Selenestrum capricornutum and the floating vascular plant Lemna minor to 16 herbicides (atrazine, metribuzin, simazine, cyanazine, alachlor, metolachlor, chlorsulfuron, metsulfuron, triallate, EPTC, trifluralin, diquat, paraquat, dicamba, bromoxynil, and 2,4-D). The herbicides studied represented nine chemical classes and several modes of action and were chosen to represent major current uses in the United States. Both plant species were generally sensitive to the triazines (atrazine, metribuzin, simazine, and cyanazine), sulfonureas (metsulfuron and chlorsulfuron), pyridines (diquat and paraquat), dinitroaniline (trifluralin), and acetanilide (alachlor and metolachlor) herbicides. Neither plant species was uniformly more sensitive than the other across the broad range of herbicides tested. Lemna was more sensitive to the sulfonureas (metsulfuron and chlorsulfuron) and the pyridines (diquat and parequat) than Selenastrum. However Selenastrum was more sensitive than Lemna to one of two thiocarbamates (triallate) and one of the triazines (cyanazine). Neither species was sensitive to selective broadleaf herbicides including bromoxynil, EPTC, dicamba, or 2,4-D. Results were not always predictable in spite of obvious differences in herbicide modes of action and plant phylogeny. Major departures in sensitivity of Selenastrum occurred between chemicals within individual classes of the triazine, acetanilide, and thiocarbamate herbicides. Results indicate that neither

  6. Potencial de lixiviação de herbicidas utilizados na cultura do algodão em colunas de solo Leaching potential of herbicides used in cotton crop under soil column conditions

    Directory of Open Access Journals (Sweden)

    M.H Inoue

    2010-12-01

    Full Text Available O intenso uso de herbicidas implica a necessidade de determinar o potencial dessas substâncias em contaminar fontes aquáticas subsuperficiais. Diante dessa preocupação, o objetivo deste trabalho foi avaliar o efeito de diferentes lâminas de água sobre o potencial de lixiviação de quatro herbicidas utilizados em pré-emergência na cultura do algodão, em dois solos provenientes de Campo Novo do Parecis-MT (RQ - textura arenosa e Tangará da Serra-MT (LV - textura argilosa. No desenvolvimento deste trabalho utilizouse a técnica de bioensaio em colunas de solo, nas quais foram simuladas irrigações de 0, 20, 40, 60, 80 e 100 mm, após a aplicação de alachlor (RQ 2,40; LV 3,36 kg ha-1, oxyfluorfen (RQ 0,48; LV 0,72 kg ha-1, prometryne (RQ 0,75; LV 1,50 kg ha-1 e S-metolachlor (RQ 1,20; LV 1,44 kg ha-1. Nas amostras de solo com textura arenosa (RQ, evidenciou-se que lâminas de 80 e 100 mm de água proporcionaram lixiviação até a profundidade de 10-15 cm do alachlor e até 15-20 cm do S-metolachlor. Independentemente da lâmina de água aplicada, nas amostras de RQ oxyfluorfen não ultrapassou a camada de 5-10 cm, e o prometryne movimentou-se até a camada de 10-15 cm somente na lâmina de 100 mm de água. Nas amostras de solo com textura argilosa (LV, o oxyfluorfen não se movimentou além da camada superficial, mesmo sob as maiores lâminas de irrigação, e o prometryne atingiu 5-10 cm de profundidade sob lâminas de 80 e 100 mm. Os herbicidas alachlor e S-metolachlor atingiram 10-15 cm de profundidade sob lâminas de 80 e 100 mm no LV. Evidenciou-se uma maior movimentação efetiva das moléculas de herbicidas nas amostras de solo com textura arenosa (RQ, em relação às amostras de solo com textura argilosa (LV.Herbicide use intensification implies in the need to determine the potential of these substances to reach groundwater. Thus, this study aimed to evaluate the influence of different irrigation depths on the leaching

  7. Methods of Analysis by the U.S. Geological Survey Organic Geochemistry Research Group?Determination of acetamide herbicides and their degradation products in water using online solid-phase extraction and liquid chromatography/mass spectrometry

    Science.gov (United States)

    Lee, E.A.; Strahan, A.P.

    2003-01-01

    An analytical method for the determination of 6 acetamide herbicides (acetochlor, alachlor, dimethenamid, flufenacet, metolachlor, and propachlor) and 16 of their degradation products in natural water samples using solid-phase extraction and liquid chromatography/mass spectrometry is described in this report. Special consideration was given during the development of the method to prevent the formation of degradation products during the analysis. Filtered water samples were analyzed using octadecylsilane as the solid-phase extraction media on online automated equipment followed by liquid chromatography/mass spectrometry. The method uses only 10 milliliters of sample per injection. Three different water-sample matrices, a reagent-water, a ground-water, and a surface-water sample spiked at 0.10 and 1.0 microgram per liter, were analyzed to determine method performance. Method detection limits ranged from 0.004 to 0.051 microgram per liter for the parent acetamide herbicides and their degradation products. Mean recoveries for the acetamide compounds in the ground- and surface-water samples ranged from 62.3 to 117.4 percent. The secondary amide of acetochlor/metolachlor ethanesulfonic acid (ESA) was recovered at an average rate of 43.5 percent. The mean recoveries for propachlor and propachlor oxanilic acid (OXA) were next lowest, ranging from 62.3 to 95.5 percent. Mean recoveries from reagent-water samples ranged from 90.3 to 118.3 percent for all compounds. Overall the mean of the mean recoveries of all compounds in the three matrices spiked at 0.10 and 1.0 microgram per liter ranged from 89.9 to 100.7 percent, including the secondary amide of acetochlor/metolachlor ESA and the propachlor compounds. The acetamide herbicides and their degradation products are reported in concentrations ranging from 0.05 to 2.0 micrograms per liter. The upper concentration limit is 2.0 micrograms per liter for all compounds without dilution. With the exception of the secondary amide of

  8. Avaliação de angustifoliadicidas na cultura da soja em Minas Gerais Grass weed control with herbicides in soybeans in Minas Gerais

    Directory of Open Access Journals (Sweden)

    Itamar Ferreira de Souza

    1985-12-01

    Full Text Available Três experimentos de campo foram conduzidos em Latossolos Vermelho-Escuro e Vermelho-Amarelo, nos anos 1981/82 e 1982/83 com o objetivo de determinar o efeito de herbicidas para o controle de plantas daninhas angustifoliadas e fitotoxidade sobre a cultura de soja, cultivares UFV-1 e Cristalina. O grupo das acetanilidas e pendimethalin controlaram a trapoeraba. Para as três espécies latifoliadas, o acetochlor, trifluralin e oryzalin foram eficientes. Além disso, o metolachlor controlou a poaia e o pendimethalin controlou a poaia e o apaga-fogo. Para o controle do capim-marmelada, todos os produtos foram eficientes, exceto quizalofop-etil e mefluidide, enquanto que para o capim-colchão apenas o mefluidide não foi eficiente. Finalmente, o timbete não foi eficientemente controlado por alachlor, metolachlor, pentimethalin e mefluidide. Acetochlor e oryzalin afetaram negativamente o stand inicial. Além disso, o acetochlor reduziu altura da inserção da primeira vagem. O quizalofop-etil causou uma redução na produção de grãos.Three field experiments were carried out on Dark Red Latosol and Yellow Red Latosol in 1981/82 and 1982/83 to evaluate the efficiency of herbicides upon grassy and their phytotoxicity upon “UFV-1” and Cristalina soybeans cultivars. The acetoanilide group and pendimethalin showed good epiderwort control. For the three broadleaved weed species, acetochlor, trifluralin and oryzalin were efficient. More over, metolachlor controlled Brazil pusley and A. ficoidea. For alexandergrass control all herbicides tested were efficient but quizalofop-ethyl and mefluidide, whereas crabgrass was not controlled by mefluidide only. Acetochlor and oryzalin treatments decreases initial stand. Besides, acetochlor decreased height of insertion of first pod. Quizalofop-ethil reduced grain yield of soybeans.

  9. Agricultural pesticides in six drainage basins used for public water supply in New Jersey, 1990

    Science.gov (United States)

    Ivahnenko, Tamara; Buxton, D.E.

    1994-01-01

    A reconnaissance study of six drainage basins in New Jersey was conducted to evaluate the presence of pesticides from agricultural runoff in surface water. In the first phase of the study, surface-water public-supply drainage basins throughout New Jersey that could be affected by pesticide applications were identified by use of a Geographic Information System. Six basins--Lower Mine Hill Reservoir, South Branch of the Raritan River, Main Branch of the Raritan River, Millstone River, Manasquan River, and Matchaponix Brook--were selected as those most likely to be affected by pesticides on the basis of calculated pesticide-application rates and percentage of agricultural land. The second phase of the project was a short-term water-quality reconnaissance of the six drainage basins to determine whether pesticides were present in the surface waters. Twenty-eight surface-water samples (22 water-quality samples, 3 sequentially collected samples, and 3 trip blanks), and 6 samples from water-treatment facilities were collected. Excluding trip blanks, samples from water-treatment facilities, and sequentially collected samples, the pesticides detected in the samples and the percentage of samples in which they were detected, were as follows: atrazine and metolachlor, 86 percent; alachlor, 55 percent; simazine, 45 percent; diazinon, 27 percent; cyanazine and carbaryl, 23 percent; linuron and isophenfos, 9 percent; and chlorpyrifos, 5 percent.Diazinon, detected in one stormflow sample collected from Matchaponix Brook on August 6, 1990, was the only compound to exceed the U.S. Environmental Protection Agency's recommended Lifetime Health Advisory Limit. Correlation between ranked metolachlor concentrations and ranked flow rates was high, and 25 percent of the variance in metolachlor concentrations can be attributed to variations in flow rate. Pesticide residues were detected in samples of pretreated and treated water from water-treatment facilities. Concentrations of all

  10. Inference in partially identified models with many moment inequalities using Lasso

    DEFF Research Database (Denmark)

    Bugni, Federico A.; Caner, Mehmet; Kock, Anders Bredahl

    This paper considers the problem of inference in a partially identified moment (in)equality model with possibly many moment inequalities. Our contribution is to propose a novel two-step new inference method based on the combination of two ideas. On the one hand, our test statistic and critical...

  11. Discovery of salivary gland tumors’ biomarkers via co-regularized sparse-group lasso

    NARCIS (Netherlands)

    Imangaliyev, S.; Matse, J.H.; Bolscher, J.G.M.; Brakenhoff, R.H.; Wong, D.T.W.; Bloemena, E.; Veerman, E.C.I.; Levin, E.; Yamamoto, A.; Kida, T.; Uno, T.; Kuboyama, T.

    2017-01-01

    In this study, we discovered a panel of discriminative microRNAs in salivary gland tumors by application of statistical machine learning methods. We modelled multi-component interactions of salivary microRNAs to detect group-based associations among the features, enabling the distinction of

  12. Exploiting Attribute Correlations: A Novel Trace Lasso-Based Weakly Supervised Dictionary Learning Method.

    Science.gov (United States)

    Wu, Lin; Wang, Yang; Pan, Shirui

    2017-12-01

    It is now well established that sparse representation models are working effectively for many visual recognition tasks, and have pushed forward the success of dictionary learning therein. Recent studies over dictionary learning focus on learning discriminative atoms instead of purely reconstructive ones. However, the existence of intraclass diversities (i.e., data objects within the same category but exhibit large visual dissimilarities), and interclass similarities (i.e., data objects from distinct classes but share much visual similarities), makes it challenging to learn effective recognition models. To this end, a large number of labeled data objects are required to learn models which can effectively characterize these subtle differences. However, labeled data objects are always limited to access, committing it difficult to learn a monolithic dictionary that can be discriminative enough. To address the above limitations, in this paper, we propose a weakly-supervised dictionary learning method to automatically learn a discriminative dictionary by fully exploiting visual attribute correlations rather than label priors. In particular, the intrinsic attribute correlations are deployed as a critical cue to guide the process of object categorization, and then a set of subdictionaries are jointly learned with respect to each category. The resulting dictionary is highly discriminative and leads to intraclass diversity aware sparse representations. Extensive experiments on image classification and object recognition are conducted to show the effectiveness of our approach.

  13. The Ins & Outs of Developing a Field-Based Science Project: Learning by Lassoing Lizards

    Science.gov (United States)

    Matthews, Catherine E.; Huffling, Lacey D.; Benavides, Aerin

    2014-01-01

    We describe a field-based lizard project we did with high school students as a part of our summer Herpetological Research Experiences. We describe data collection on lizards captured, identified, and marked as a part of our mark-recapture study. We also describe other lizard projects that are ongoing in the United States and provide resources for…

  14. Tracking of time-varying genomic regulatory networks with a LASSO-Kalman smoother

    OpenAIRE

    Khan, Jehandad; Bouaynaya, Nidhal; Fathallah-Shaykh, Hassan M

    2014-01-01

    It is widely accepted that cellular requirements and environmental conditions dictate the architecture of genetic regulatory networks. Nonetheless, the status quo in regulatory network modeling and analysis assumes an invariant network topology over time. In this paper, we refocus on a dynamic perspective of genetic networks, one that can uncover substantial topological changes in network structure during biological processes such as developmental growth. We propose a novel outlook on the inf...

  15. Lasso of Truth”: Rediscovering the Forgotten History of Wonder Woman

    Directory of Open Access Journals (Sweden)

    Irena Jurković

    2015-06-01

    Full Text Available In a period witnessing the increasing popularity of superhero franchises, comic book historian Tim Hanley sheds light on the forgotten history of the world’s most famous female superhero, Wonder Woman. Tim Hanley’s Wonder Woman Unbound: The Curious History of the World’s Most Famous Heroine, as its title suggests, aims to explore the curious path of Wonder Woman: from the creation of the character to her contemporary iconic status. The book is comprised of three sections that follow the eras of American comic books: Golden Age, Silver Age and Bronze Age. Hanley starts off with Wonder Woman’s origin story, associating it primarily with the life and work of her creator, psychologist William Marston. The story begins when an American pilot, Steve Trevor, crashes on the hidden Paradise Island and is found injured by Diana and her fellow Amazons. Paradise Island is the home of mythical Amazons guided by goddesses Aphrodite and Athena. Their world is an only-female utopia situated far away from the outside, violent, world of men. However, while Amazons live in peace, the outside world is bursting with war and Steve needs to return to America to fulfill his soldier duties. The Amazon goddesses decide to send a warrior, Diana, to help Steve through his journey. That warrior later becomes a superheroine known by the name of Wonder Woman.

  16. Spontaneous rupture of the esophagus associated with intramural rupture caused by ingestion of weeding medicine (Lasso)

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jong Keon; Park, Heung Il; Kwun, Chung Sik [Chun Nam University College of Medicine, Kwangju (Korea, Republic of)

    1975-06-15

    This is a report of a case of spontaneous rupture of the esophagus associated with intramural rupture caused by ingestion of weeding medicine for the purpose of suicide in a 27 year old Korean male whose chief complaints were dyspnea, epigastric pain, swallowing disturbance, and hoarseness for 3 days prior to admission. A review of literature is submitted.

  17. Pesticides in ground water in selected agricultural land-use areas and hydrogeologic settings in Pennsylvania, 2003-07

    Science.gov (United States)

    Loper, Connie A.; Breen, Kevin J.; Zimmerman, Tammy M.; Clune, John W.

    2009-01-01

    absence of bacteria only for the 10 wells representing the Blue Ridge crystalline and Triassic Lowland siliciclastic setting. Results of Spearman’s rank test showed strong positive correlations in the Devonian-Silurian carbonate setting between 1) the number of pesticides above the MRLs and nitrate concentration, and 2) concentrations of atrazine and nitrate. Atrazine concentration and nitrate concentration also showed a statistically significant positive correlation in the Great Valley siliciclastic setting. An additional component of baseline monitoring was to evaluate changes in pesticide concentration in water from wells representing hydrogeologic settings most vulnerable to contamination from pesticides. In 2003, 16 wells originally sampled in the 1990s were resampled—4 each in the Appalachian Mountain carbonate, Triassic Lowland siliciclastic, Great Valley carbonate, and Piedmont carbonate settings. Nine of these wells, where pesticide concentrations from 1993 and 2003 were analyzed at the NWQL, were chosen for a paired-sample analysis using concentrations of atrazine and metolachlor. A statistically significant decrease in atrazine concentration was identified using the Wilcoxon signed-rank test (p = 0.004); significant temporal changes in metolachlor concentrations were not observed (p = 0.625). Monitoring in three areas of special ground-water protection, where selected pesticide concentrations in well water were at or above the PPGWS action levels, was done at wells BE 1370 (Berks County, Oley Township), BA 437 (Blair County, North Woodbury Township), and LN 1842 (Lancaster County, Earl Township). Co-occurrence of pesticide-degradation products with parent compounds was documented for the first time in ground-water samples collected from these three wells. Degradation products of atrazine, cyanazine, acetochlor, alachlor, and metolachlor were commonly at larger concentrations than the parent compound in the same water sample. Pesticide occurrence in water

  18. GREEN RUST AND IRON OXIDE FORMATION INFLUENCES METOLACHLOR DECHLORINATION DURING ZEROVALENT IRON TREATMENT. (R829422E03)

    Science.gov (United States)

    The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

  19. Atividade residual de herbicidas aplicados ao solo em relação ao controle de quatro espécies de Amaranthus Residual activity of herbicides applied to the soil in relation to control of four Amaranthus Species

    Directory of Open Access Journals (Sweden)

    M.A. Raimondi

    2010-01-01

    Full Text Available Herbicidas aplicados em pré-emergência normalmente apresentam atividade residual no solo, controlando os primeiros fluxos germinativos das plantas daninhas e prevenindo a matocompetição inicial. O objetivo deste trabalho foi verificar o período de atividade residual proporcionado por doses de herbicidas suficientes para o controle pontual de 95% (C95 das espécies Amaranthus hybridus, A. lividus, A. spinosus e A. viridis, além de avaliar doses recomendadas desses herbicidas. O trabalho foi realizado em casa de vegetação, em solo de textura franco-argiloarenosa (20% de argila e 1,9 de matéria orgânica, e as doses dos herbicidas alachlor, diuron, oxyfluorfen, pendimethalin, prometryne, oxyfluorfen, S-metolachlor, trifluralin 450 e trifluralin 600 foram aplicadas aos 30, 20, 10 e 0 dias antes da semeadura das plantas daninhas. Avaliou-se o controle das plantas daninhas após a permanência dos herbicidas no solo por períodos de 0, 10, 20 e 30 dias depois da aplicação dos tratamentos (DAA. A atividade residual de alachlor e prometryne, na dose C95, não foi suficiente para o controle eficiente (>80% das espécies por períodos de até 30 DAA. Quanto ao alachlor, o emprego da dose recomendada não se refletiu em aumento considerável da atividade residual, exceto em relação a A. viridis. A dose recomendada de prometryne proporcionou controle eficiente das espécies até 30 DAA, exceto de A. hybridus. A dose recomendada de oxyfluorfen controlou eficientemente A. hybridus e A. spinosus até 30 DAA, espécies estas que não haviam sido eficientemente controladas pela dose C95. Trifluralin 450 promoveu controle residual eficiente de 30 DAA somente em relação a A. hybridus. Trifluralin 600 foi eficiente no controle de A. hybridus e A. viridis até os 30 DAA e até 29 e 28 DAA para A. lividus e A. spinosus, respectivamente. Clomazone não promoveu controle eficiente das espécies até 30 DAA, exceto de A. viridis. Diuron, pendimethalin e S-metolachlor

  20. Pesticides analysed in rainwater in Alsace region (Eastern France): Comparison between urban and rural sites

    Science.gov (United States)

    Scheyer, Anne; Morville, Stéphane; Mirabel, Philippe; Millet, Maurice

    Current-used pesticides commonly applied in Alsace region (Eastern France) on diverse crops (maize, vineyard, vegetables, etc.) were analysed, together with Lindane, in rainwater between January 2002 and June 2003 simultaneously on two sites situated in a typical rural (Erstein, France) and urban area (Strasbourg, France). Rainwater samples were collected on a weekly basis by using two automatic wet only collectors associated with an open collector for the measurement of rainwater height. Pesticides were analysed by GC-MSMS and extracted from rainwater by SPME. Two runs were performed. The first one was performed by using a PDMS (100 μm) fibre for pesticides where direct injection into GC is possible (alachlor, atrazine, azinphos-ethyl, azinphos-methyl, captan, chlorfenvinphos, dichlorvos, diflufenican, α- and β-endosulfan, iprodione, lindane, metolachlor, mevinphos, parathion-methyl, phosalone, phosmet, tebuconazole, triadimefon and trifluralin). The second run was performed by using PDMS/DVB fibre and this run concerns pesticides where a preliminary derivatisation step with pentafluorobenzylbromide (PFBBr) is required for very low volatiles (bromoxynil,2,4-MCPA, MCPP and 2,4-D) or thermo labiles (chlorotoluron, diuron and isoproturon) pesticides. Results showed that the more concentrated pesticides detected were those used as herbicides in large quantities in Alsace region for maize crops (alachlor, metolachlor and atrazine). Maximum concentrations for these herbicides have been measured during intensive applications periods on maize crops following by rapid decrease immediately after use. For Alachlor, most important peaks have been observed between 21 and 28 April 2003 (3327 ng L -1 at Erstein and 5590 ng L -1 at Strasbourg). This is also the case for Metolachlor where most important peak was observed during the same week. Concentrations of pesticides measured out of application periods were very low for many pesticides and some others where never detected

  1. Controle de capim-annoni-2 (Eragrostis plana com herbicidas pré-emergentes em associação com diferentes métodos de manejo do campo nativo Control of South African lovegrass (Eragrostis plana in natural pastures using pre emergent herbicides and different vegetation management methods

    Directory of Open Access Journals (Sweden)

    I.C.G.R. Goulart

    2009-03-01

    Full Text Available A planta daninha capim-annoni-2 (Eragrostis plana é um dos principais limitantes ao desenvolvimento da pecuária extensiva no Sul do Brasil. Vários fatores dificultam o controle dessa espécie em condições de pastagem natural. O objetivo deste trabalho foi avaliar o controle de capim-annoni-2 por meio de herbicidas aplicados em pré-emergência que possam apresentar seletividade de posição no solo à pastagem nativa. Dois experimentos foram realizados neste estudo. O primeiro foi conduzido em casa de vegetação, onde sementes de capim-annoni-2 foram semeadas em vasos. O delineamento utilizado foi o completamente casualizado com seis repetições. Os herbicidas avaliados foram alachlor, ametryne, ametryne + tebuthiuron, atrazine, clomazone, diuron, flumioxazin, imazaquin, mesotrione, metribuzin, oxadiazon, S-metolachlor, sulfentrazone, terbuthylazine e trifluralin. Todos os produtos controlaram satisfatoriamente o capim-annoni-2. O segundo experimento foi conduzido em campo nativo com alta infestação de capim-annoni-2, em delineamento de blocos completamente casualizados, em esquema de parcelas subsubdivididas. Nas parcelas principais foram alocados os tratamentos de manejo da vegetação em antecedência a aplicação dos herbicidas: fogo técnico e roçada em altura alta e baixa; nas subparcelas, as doses dos herbicidas: 75 e 100% da dose de rótulo; e, nas subsubparcelas, os herbicidas atrazine, flumioxazin, mesotrione, S-metolachlor, sulfentrazone, trifluralin e testemunha não tratada. Nenhum dos herbicidas testados controlou efetivamente o capim-annoni-2 em campo, provavelmente devido à grande presença de plantas perenizadas. No entanto, os efeitos dos herbicidas foram mais pronunciados quando associados a fogo técnico e roçada baixa.The weed South African lovegrass (Eragrostis plana is one of the most important problems of rangelands and native pastures in southern Brazil. Several factors have limited its management in these

  2. Water Quality Conditions at Tributary Projects in the Omaha District: 2008 Report

    Science.gov (United States)

    2009-01-01

    benfluralin. butylate, chlorpyrifos. cyanazine, cycloate. EPTC. hexazinone, isopropalin, metribuzin, metolachlor. molinate, oxadiazon, oxyfluorfen ...metolachlor, metribuzin, molinate, oxadiazon, oxyfluorfen , pebulate, pendimethalin, profluralin, prometon, propachlor, propazine, simazine, trifluralin, and...chlorpyrifos, cyanazine, cycloate, EPTC, hexazinone, isopropalin, metolachlor, metribuzin, molinate, oxadiazon, oxyfluorfen , pebulate

  3. Poster: Brush, Lasso, or Magic Wand? Picking the Right Tool for Large-Scale Multiple Object Selection Tasks

    DEFF Research Database (Denmark)

    Stenholt, Rasmus; Madsen, Claus B.

    2012-01-01

    are presented with a range of different geometric layouts of selection targets, to investigate the pros and cons of each of the MOS techniques. The evaluation shows that the magic wand is significantly faster to use than the other techniques, however the quality of the magic wand's selections is highly...

  4. Evaluating the Predictive Power of Multivariate Tensor-based Morphometry in Alzheimers Disease Progression via Convex Fused Sparse Group Lasso.

    Science.gov (United States)

    Tsao, Sinchai; Gajawelli, Niharika; Zhou, Jiayu; Shi, Jie; Ye, Jieping; Wang, Yalin; Lepore, Natasha

    2014-03-21

    Prediction of Alzheimers disease (AD) progression based on baseline measures allows us to understand disease progression and has implications in decisions concerning treatment strategy. To this end we combine a predictive multi-task machine learning method 1 with novel MR-based multivariate morphometric surface map of the hippocampus 2 to predict future cognitive scores of patients. Previous work by Zhou et al. 1 has shown that a multi-task learning framework that performs prediction of all future time points (or tasks) simultaneously can be used to encode both sparsity as well as temporal smoothness. They showed that this can be used in predicting cognitive outcomes of Alzheimers Disease Neuroimaging Initiative (ADNI) subjects based on FreeSurfer-based baseline MRI features, MMSE score demographic information and ApoE status. Whilst volumetric information may hold generalized information on brain status, we hypothesized that hippocampus specific information may be more useful in predictive modeling of AD. To this end, we applied Shi et al. 2 s recently developed multivariate tensor-based (mTBM) parametric surface analysis method to extract features from the hippocampal surface. We show that by combining the power of the multi-task framework with the sensitivity of mTBM features of the hippocampus surface, we are able to improve significantly improve predictive performance of ADAS cognitive scores 6, 12, 24, 36 and 48 months from baseline.

  5. Evaluating the predictive power of multivariate tensor-based morphometry in Alzheimer's disease progression via convex fused sparse group Lasso

    Science.gov (United States)

    Tsao, Sinchai; Gajawelli, Niharika; Zhou, Jiayu; Shi, Jie; Ye, Jieping; Wang, Yalin; Lepore, Natasha

    2014-03-01

    Prediction of Alzheimers disease (AD) progression based on baseline measures allows us to understand disease progression and has implications in decisions concerning treatment strategy. To this end we combine a predictive multi-task machine learning method1 with novel MR-based multivariate morphometric surface map of the hippocampus2 to predict future cognitive scores of patients. Previous work by Zhou et al.1 has shown that a multi-task learning framework that performs prediction of all future time points (or tasks) simultaneously can be used to encode both sparsity as well as temporal smoothness. They showed that this can be used in predicting cognitive outcomes of Alzheimers Disease Neuroimaging Initiative (ADNI) subjects based on FreeSurfer-based baseline MRI features, MMSE score demographic information and ApoE status. Whilst volumetric information may hold generalized information on brain status, we hypothesized that hippocampus specific information may be more useful in predictive modeling of AD. To this end, we applied Shi et al.2s recently developed multivariate tensor-based (mTBM) parametric surface analysis method to extract features from the hippocampal surface. We show that by combining the power of the multi-task framework with the sensitivity of mTBM features of the hippocampus surface, we are able to improve significantly improve predictive performance of ADAS cognitive scores 6, 12, 24, 36 and 48 months from baseline.

  6. Vdrive Evaluation of Remote Steering and Testing in Lasso Electrophysiology Procedures Study: The VERSATILE Study in Atrial Fibrillation Ablation.

    Science.gov (United States)

    Nölker, Georg; Schwagten, Bruno; Deville, J Brian; Burkhardt, J David; Horton, Rodney P; Sha, Qun; Tomassoni, Gery

    2016-03-01

    Circular mapping catheters (CMC) are an essential tool in most atrial fibrillation ablation procedures. The Vdrive™ with V-Loop™ system enables a physician to remotely manipulate a CMC during electrophysiology studies. Our aim was to compare the clinical performance of the system to conventional CMC navigation according to efficiency and safety endpoints. A total of 120 patients scheduled to undergo a CMC study followed by pulmonary vein isolation (PVI) were included. Treatment allocation was randomized 2:1, remote navigation:manual navigation. The primary effectiveness endpoint was assessed based on both successful navigation to the targeted pulmonary vein (PV) and successful recording of PV electrograms. All PVs were treated independently within and between patients. The primary safety endpoint was assessed based on the occurrence of major adverse events (MAEs) through seven days after the study procedure. Primary effectiveness endpoints were achieved in 295/302 PVs in the Vdrive arm (97.7%) and 167/167 PVs in the manual arm (100%). Effectiveness analysis indicates Vdrive non-inferiority (pnon-inferiority = 0.0405; δ = -0.05) per the Cochran-Mantel-Haenszel test adjusted for PV correlation. Five MAEs related to the ablation procedure occurred (three in the Vdrive arm-3.9%; two in the manual arm-2.33%). No device-related MAEs were observed; safety analysis indicates Vdrive non-inferiority (pnon-inferiority = 0.0441; δ = 0.07) per the normal Z test. Remote navigation of a CMC is equivalent to manual in PVI in terms of safety and effectiveness. This allows for single-operator procedures in conjunction with a magnetically guided ablation catheter. © 2016 Wiley Periodicals, Inc.

  7. Regional patterns of pesticide concentrations in surface waters of New York in 1997

    Science.gov (United States)

    Phillips, P.J.; Eckhardt, D.A.; Freehafer, D.A.; Wall, G.R.; Ingleston, H.H.

    2002-01-01

    The predominant mixtures of pesticides found in New York surface waters consist of five principal components. First, herbicides commonly used on corn (atrazine, metolachlor, alachlor, cyanazine) and a herbicide degradate (deethylatrazine) were positively correlated to a corn-herbicide component, and watersheds with the highest corn-herbicide component scores were those in which large amounts of row crops are grown. Second, two insecticides (diazinon and carbaryl) and one herbicide (prometon) widely used in urban and residential settings were positively correlated to an urban/residential component. Watersheds with the highest urban/residential component scores were those with large amounts of urban and residential land use. A third component was related to two herbicides (EPTC and cyanazine) used on dry beans and corn, the fourth to an herbicide (simazine) and an insecticide (carbaryl) commonly used in orchards and vineyards, and the fifth to an herbicide (DCPA). Results of this study indicate that this approach can be used to: (1) identify common mixtures of pesticides in surface waters, (2) relate these mixtures to land use and pesticide applications, and (3) indicate regions where these mixtures of pesticides are commonly found.

  8. The status of pesticide pollution in surface waters (rivers and lakes) of Greece. Part I. Review on occurrence and levels

    International Nuclear Information System (INIS)

    Konstantinou, Ioannis K.; Hela, Dimitra G.; Albanis, Triantafyllos A.

    2006-01-01

    This review evaluates and summarizes the results of long-term research projects, monitoring programs and published papers concerning the pollution of surface waters (rivers and lakes) of Greece by pesticides. Pesticide classes mostly detected involve herbicides used extensively in corn, cotton and rice production, organophosphorus insecticides as well as the banned organochlorines insecticides due to their persistence in the aquatic environment. The compounds most frequently detected were atrazine, simazine, alachlor, metolachlor and trifluralin of the herbicides, diazinon, parathion methyl of the insecticides and lindane, endosulfan and aldrin of the organochlorine pesticides. Rivers were found to be more polluted than lakes. The detected concentrations of most pesticides follow a seasonal variation, with maximum values occurring during the late spring and summer period followed by a decrease during winter. Nationwide, in many cases the reported concentrations ranged in low ppb levels. However, elevated concentrations were recorded in areas of high pesticide use and intense agricultural practices. Generally, similar trends and levels of pesticides were found in Greek rivers compared to pesticide contamination in other European rivers. Monitoring of the Greek water resources for pesticide residues must continue, especially in agricultural regions, because the nationwide patterns of pesticide use are constantly changing. Moreover, emphasis should be placed on degradation products not sufficiently studied so far. - Information on pesticide pollution of surface waters in Greece is reviewed

  9. Identification of ionic chloroacetanilide-herbicide metabolites in surface water and groundwater by HPLC/MS using negative ion spray

    Science.gov (United States)

    Ferrer, I.; Thurman, E.M.; Barcelo, D.

    1997-01-01

    Solid-phase extraction (SPE) was combined with high-performance liquid chromatography/high-flow pneumatically assisted electrospray mass spectrometry (HPLC/ESP/MS) for the trace analysis of oxanilic and sulfonic acids of acetochlor, alachlor, and metolachlor. The isolation procedure separated the chloroacetanilide metabolites from the parent herbicides during the elution from C18 cartridges using ethyl acetate for parent compounds, followed by methanol for the anionic metabolites. The metabolites were separated chromatographically using reversed-phase HPLC and analyzed by negative-ion MS using electrospray ionization in selected ion mode. Quantitation limits were 0.01 ??g/L for both the oxanilic and sulfonic acids based on a 100-mL water sample. This combination of methods represents an important advance in environmental analysis of chloroacetanilide-herbicide metabolites in surface water and groundwater for two reasons. First, anionic chloroacetanilide metabolites are a major class of degradation products that are readily leached to groundwater in agricultural areas. Second, anionic metabolites, which are not able to be analyzed by conventional methods such as liquid extraction and gas chromatography/mass spectrometry, are effectively analyzed by SPE and high-flow pneumatically assisted electrospray mass spectrometry. This paper reports the first HPLC/MS identification of these metabolites in surface water and groundwater.

  10. Integrated use of biomarkers and bioaccumulation data in Zebra mussel (Dreissena polymorpha) for site-specific quality assessment.

    Science.gov (United States)

    Binelli, A; Ricciardi, F; Riva, C; Provini, A

    2006-01-01

    One of the useful biological tools for environmental management is the measurement of biomarkers whose changes are related to the exposure to chemicals or environmental stress. Since these responses might vary with different contaminants or depending on the pollutant concentration reached in the organism, the support of bioaccumulation data is needed to prevent false conclusions. In this study, several persistent organic pollutants -- 23 polychlorinated biphenyl (PCB) congeners, 11 polycyclic aromatic hydrocarbons (PAHs), six dichlorodiphenyltricholroethane (DDT) relatives, hexachlorobenzene (HCB), chlorpyrifos and its oxidized metabolite -- and some herbicides (lindane and the isomers alpha, beta, delta; terbutilazine; alachlor; metolachlor) were measured in the soft tissues of the freshwater mollusc Zebra mussel (Dreissena polymorpha) from 25 sampling sites in the Italian portions of the sub-alpine great lakes along with the measure of ethoxyresorufin dealkylation (EROD) and acetylcholinesterase (AChE) activity. The linkage between bioaccumulation and biomarker data allowed us to create site-specific environmental quality indexes towards man-made chemicals. This classification highlighted three different degrees of xenobiotic contamination of the Italian sub-alpine great lakes: a high water quality in Lake Lugano with negligible pollutant levels and no effects on enzyme activities, an homogeneous poor quality for Lakes Garda, Iseo and Como, and the presence of some xenobiotic point-sources in Lake Maggiore, whose ecological status could be jeopardized, also due to the heavy DDT contamination revealed since 1996.

  11. [Reactivity of several classes of pesticides with UV, ozone and permanganate].

    Science.gov (United States)

    Liu, Chao; Qiang, Zhi-min; Tian, Fang; Zhang, Tao

    2009-01-01

    The reactivity of eight classes of 26 extensively used pesticides, namely, organochlorines, thiadiazole, dinitroanaline, acetamides, triazines, uracil and carbamates, with three common disinfectants or oxidants including UV254 (average intensity of 10.8 mW x cm(-2)), ozone (dosage of 4.1 - 6.2 mg x L(-1)) and permanganate (dosage of 15.8 mg x L(-1)) was investigated. The reactions were allowed to proceed for 30 min at pH 7.0 and ambient temperature (25 degrees C +/- 3 degrees C). Results indicate that under the applied experimental conditions, more than 95% of chlorobenzilate, etridiazole, alachlor, butachlor, metolachlor, propachlor, atrazine, simazine, aldicarb, oxamyl and methiocarb could be effectively removed by UV254; and the removal efficiencies of other pesticides were in a range of 12.9%-77.7%. Ozone could completely degrade chloroneb, dichlorvos, bromacil, aldicarb, carbaryl, carbofuran, oxamyl and methiocarb; prometon and aldicarb sulfone were resistant to ozonation; and the removal efficiencies of other pesticides varied from 19.0% to 93.1%. Permanganate could fully degrade dichlorvos, aldicarb and methiocarb; organochlorines, dinitroanaline, thiadiazole, acetamides and other carbamates were resistant to permanganate oxidation; and the removal efficiencies of other pesticides ranged from 16.0% to 88.2%. If the practical dosage applied in drinking water treatment is considered, it is expected that most of the pesticides will be completely degraded by ozone, a few by permanganate, but probably none by UV254 .

  12. Heterologous expression of the yeast Tpo1p or Pdr5p membrane transporters in Arabidopsis confers plant xenobiotic tolerance.

    Science.gov (United States)

    Remy, Estelle; Niño-González, María; Godinho, Cláudia P; Cabrito, Tânia R; Teixeira, Miguel C; Sá-Correia, Isabel; Duque, Paula

    2017-07-03

    Soil contamination is a major hindrance for plant growth and development. The lack of effective strategies to remove chemicals released into the environment has raised the need to increase plant resilience to soil pollutants. Here, we investigated the ability of two Saccharomyces cerevisiae plasma-membrane transporters, the Major Facilitator Superfamily (MFS) member Tpo1p and the ATP-Binding Cassette (ABC) protein Pdr5p, to confer Multiple Drug Resistance (MDR) in Arabidopsis thaliana. Transgenic plants expressing either of the yeast transporters were undistinguishable from the wild type under control conditions, but displayed tolerance when challenged with the herbicides 2,4-D and barban. Plants expressing ScTPO1 were also more resistant to the herbicides alachlor and metolachlor as well as to the fungicide mancozeb and the Co 2+ , Cu 2+ , Ni 2+ , Al 3+ and Cd 2+ cations, while ScPDR5-expressing plants exhibited tolerance to cycloheximide. Yeast mutants lacking Tpo1p or Pdr5p showed increased sensitivity to most of the agents tested in plants. Our results demonstrate that the S. cerevisiae Tpo1p and Pdr5p transporters are able to mediate resistance to a broad range of compounds of agricultural interest in yeast as well as in Arabidopsis, underscoring their potential in future biotechnological applications.

  13. Simultaneous quantification of acetanilide herbicides and their oxanilic and sulfonic acid metabolites in natural waters.

    Science.gov (United States)

    Heberle, S A; Aga, D S; Hany, R; Müller, S R

    2000-02-15

    This paper describes a procedure for simultaneous enrichment, separation, and quantification of acetanilide herbicides and their major ionic oxanilic acid (OXA) and ethanesulfonic acid (ESA) metabolites in groundwater and surface water using Carbopack B as a solid-phase extraction (SPE) material. The analytes adsorbed on Carbopack B were eluted selectively from the solid phase in three fractions containing the parent compounds (PCs), their OXA metabolites, and their ESA metabolites, respectively. The complete separation of the three compound classes allowed the analysis of the neutral PCs (acetochlor, alachlor, and metolachlor) and their methylated OXA metabolites by gas chromatography/mass spectrometry. The ESA compounds were analyzed by high-performance liquid chromatography with UV detection. The use of Carbopack B resulted in good recoveries of the polar metabolites even from large sample volumes (1 L). Absolute recoveries from spiked surface and groundwater samples ranged between 76 and 100% for the PCs, between 41 and 91% for the OXAs, and between 47 and 96% for the ESAs. The maximum standard deviation of the absolute recoveries was 12%. The method detection limits are between 1 and 8 ng/L for the PCs, between 1 and 7 ng/L for the OXAs, and between 10 and 90 ng/L for the ESAs.

  14. Distribution of agrochemicals in the lower Mississippi River and its tributaries

    Science.gov (United States)

    Pereira, W.E.; Rostad, C.E.; Leiker, T.J.

    1990-01-01

    The Mississippi River and its tributaries drain extensive agricultural regions of the Mid-Continental United States. Millions of pounds of herbicides are applied annually in these areas to improve crop yields. Many of these compounds are transported into the river from point and nonpoint sources, and eventually are discharged into the Gulf of Mexico. Studies being conducted by the U.S. Geological Survey along the lower Mississippi River and its major tributaries, representing a 2000 km river reach, have confirmed that several triazine and acetanilide herbicides and their degradation products are ubiquitous in this riverine system. These compounds include atrazine and its degradation products desethyl and desisopropylatrazine, cyanazine, simazine, metolachlor, and alachlor and its degradation products 2-chloro-2',6'-diethylacetanilide, 2-hydroxy-2',6-diethylacetanilide and 2,6-diethylaniline. Loads of these compounds were determined at 16 different sampling stations. Stream-load calculations provided information concerning (a) conservative or nonconservative behavior of herbicides; (b) point sources or nonpoint sources; (c) validation of sampling techniques; and (d) transport past each sampling station.

  15. Comparison of annual dry and wet deposition fluxes of selected pesticides in Strasbourg, France

    International Nuclear Information System (INIS)

    Sauret, Nathalie; Wortham, Henri; Strekowski, Rafal; Herckes, Pierre; Nieto, Laura Ines

    2009-01-01

    This work summarizes the results of a study of atmospheric wet and dry deposition fluxes of Deisopropyl-atrazine (DEA), Desethyl-atrazine (DET), Atrazine, Terbuthylazine, Alachlor, Metolachlor, Diflufenican, Fenoxaprop-p-ethyl, Iprodione, Isoproturon and Cymoxanil pesticides conducted in Strasbourg, France, from August 2000 through August 2001. The primary objective of this work was to calculate the total atmospheric pesticide deposition fluxes induced by atmospheric particles. To do this, a modified one-dimensional cloud water deposition model was used. All precipitation and deposition samples were collected at an urban forested park environment setting away from any direct point pesticide sources. The obtained deposition fluxes induced by atmospheric particles over a forested area showed that the dry deposition flux strongly contributes to the total deposition flux. The dry particle deposition fluxes are shown to contribute from 4% (DET) to 60% (cymoxanil) to the total deposition flux (wet + dry). - A modified one-dimensional cloud water deposition model is used to estimate the deposition fluxes of pesticides in the particle phase and compare the relative importance of dry and wet depositions

  16. Comparison of annual dry and wet deposition fluxes of selected pesticides in Strasbourg, France

    Energy Technology Data Exchange (ETDEWEB)

    Sauret, Nathalie [Marseilles University, Laboratoire Chimie Provence - UMR 6264, Campus Saint Charles, Case 29, 3 Place Victor Hugo, 13331 Marseilles Cedex 03 (France); Wortham, Henri [Marseilles University, Laboratoire Chimie Provence - UMR 6264, Campus Saint Charles, Case 29, 3 Place Victor Hugo, 13331 Marseilles Cedex 03 (France)], E-mail: Henri.Wortham@univ-provence.fr; Strekowski, Rafal [Marseilles University, Laboratoire Chimie Provence - UMR 6264, Campus Saint Charles, Case 29, 3 Place Victor Hugo, 13331 Marseilles Cedex 03 (France); Herckes, Pierre [Arizona State University, Department of Chemistry and Biochemistry, Tempe, AZ 85287-1604 (United States); Nieto, Laura Ines [Marseilles University, Laboratoire Chimie Provence - UMR 6264, Campus Saint Charles, Case 29, 3 Place Victor Hugo, 13331 Marseilles Cedex 03 (France)

    2009-01-15

    This work summarizes the results of a study of atmospheric wet and dry deposition fluxes of Deisopropyl-atrazine (DEA), Desethyl-atrazine (DET), Atrazine, Terbuthylazine, Alachlor, Metolachlor, Diflufenican, Fenoxaprop-p-ethyl, Iprodione, Isoproturon and Cymoxanil pesticides conducted in Strasbourg, France, from August 2000 through August 2001. The primary objective of this work was to calculate the total atmospheric pesticide deposition fluxes induced by atmospheric particles. To do this, a modified one-dimensional cloud water deposition model was used. All precipitation and deposition samples were collected at an urban forested park environment setting away from any direct point pesticide sources. The obtained deposition fluxes induced by atmospheric particles over a forested area showed that the dry deposition flux strongly contributes to the total deposition flux. The dry particle deposition fluxes are shown to contribute from 4% (DET) to 60% (cymoxanil) to the total deposition flux (wet + dry). - A modified one-dimensional cloud water deposition model is used to estimate the deposition fluxes of pesticides in the particle phase and compare the relative importance of dry and wet depositions.

  17. Pesticide monitoring in surface water and groundwater using passive samplers

    Science.gov (United States)

    Kodes, V.; Grabic, R.

    2009-04-01

    Passive samplers as screening devices have been used within a czech national water quality monitoring network since 2002 (SPMD and DGT samplers for non polar substances and metals). The passive sampler monitoring of surface water was extended to polar substances, in 2005. Pesticide and pharmaceutical POCIS samplers have been exposed in surface water at 21 locations and analysed for polar pesticides, perfluorinated compounds, personal care products and pharmaceuticals. Pesticide POCIS samplers in groundwater were exposed at 5 locations and analysed for polar pesticides. The following active substances of plant protection products were analyzed in surface water and groundwater using LC/MS/MS: 2,4,5-T, 2,4-D, Acetochlor, Alachlor, Atrazine, Atrazine_desethyl, Azoxystrobin, Bentazone, Bromacil, Bromoxynil, Carbofuran, Clopyralid, Cyanazin, Desmetryn, Diazinon, Dicamba, Dichlobenil, Dichlorprop, Dimethoat, Diuron, Ethofumesate, Fenarimol, Fenhexamid, Fipronil, Fluazifop-p-butyl, Hexazinone, Chlorbromuron, Chlorotoluron, Imazethapyr, Isoproturon, Kresoxim-methyl, Linuron, MCPA, MCPP, Metalaxyl, Metamitron, Methabenzthiazuron, Methamidophos, Methidathion, Metobromuron, Metolachlor, Metoxuron, Metribuzin, Monolinuron, Nicosulfuron, Phorate, Phosalone, Phosphamidon, Prometryn, Propiconazole, Propyzamide, Pyridate, Rimsulfuron, Simazine, Tebuconazole, Terbuthylazine, Terbutryn, Thifensulfuron-methyl, Thiophanate-methyl and Tri-allate. The POCIS samplers performed very well being able to provide better picture than grab samples. The results show that polar pesticides and also perfluorinated compounds, personal care products and pharmaceuticals as well occur in hydrosphere of the Czech republic. Acknowledgment: Authors acknowledge the financial support of grant No. 2B06095 by the Ministry of Education, Youth and Sports.

  18. Evaluation of herbicides for use in transplanting leucaena leucocephala and prosopis alba on semi-arid lands without irrigation

    Energy Technology Data Exchange (ETDEWEB)

    Felker, P.; Smith, D.; Smith, M.; Bingham, R.L.; Reyes, I.

    1984-01-01

    Five herbicides were applied to plots at 2 rates in April 1982, and 3-month old seedlings planted 2 days later. Basal diameter was measured after 110 days and converted to dry weight using published equations. Percent weed cover was recorded 45, 75, and 105 days after planting. All herbicides increased survival over untreated controls. The greatest biomass production of both species was obtained with oryzalin treatment at 2.8 kg/ha active ingredient, which increased production 4-5X compared with control plots. Oryzalin was second to napropamide (2.24 kg/ha active ingredient) in grass control and equal to oxyfluorfen (1.12 kg/ha active ingredient) in forb control, oxyfluorfen at this rate also gave the second best biomass production. Oryzalin increased survival from 71 to 87% for Leucaena and from 81-94% for Prosopis, and is considered to be the best herbicide tested, followed by oxyfluorfen and metolachlor. Alachlor was considered to be too short-lived and napropamide too expensive.

  19. DEGRADATION OF ATRAZINE, METOLACHLOR, AND PENDIMETHALIN IN PESTICIDE-CONTAMINATED SOILS: EFFECTS OF AGED RESIDUES ON SOIL RESPIRATION AND PLANT SURVIVAL. (R825549C045)

    Science.gov (United States)

    The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

  20. Seletividade de herbicidas aplicados em pré-emergência na cultura do algodão Selectivity of herbicides applied to pre-emergent cotton crops

    Directory of Open Access Journals (Sweden)

    Miriam Hiroko Inoue

    2013-03-01

    Full Text Available A cultura do algodão tem grande importância econômica e social, visto que é a fibra mais utilizada no setor têxtil. Contudo é uma cultura que apresenta alta sensibilidade a plantas daninhas e há poucos herbicidas seletivos à cultura. Neste contexto o trabalho objetivou avaliar a seletividade de herbicidas aplicados em pré-emergência na cultura do algodão. Os herbicidas alachlor, S-metolachlor, diuron, prometryne, trifluralin e oxyfluorfen foram aplicados isoladamente e em misturas sobre a variedade FMT-701, nas localidades de Diamantino-MT e Campos de Júlio-MT. O delineamento experimental utilizado foi em blocos casualizados com 16 tratamentos e 4 repetições. Para avaliar a seletividade foram realizadas avaliações de altura aos 36; 66 e 150 dias após a aplicação (DAA, fitointoxicação aos 14; 21; 29 e 36 DAA, estande aos 21 e 49 DAA, número de maçãs aos 141 DAA e produtividade do algodão em caroço aos 193 DAA. Os dados foram submetidos à análise conjunta e ao teste de agrupamento Scott-Knott (p>0,05. Os resultados indicaram que alguns tratamentos proporcionaram menor altura de plantas em determinadas avaliações e grande parte dos tratamentos causou injúrias na fase inicial da cultura. Verificou-se que os tratamentos não proporcionaram diferença significativa para as características de estande de plantas, número de maçãs e produtividade de algodão em caroço, comprovando que todos os tratamentos avaliados podem ser utilizados no manejo de plantas daninhas.The cultivation of cotton has great economic and social importance as it is the most widely used fibre in the textile sector. It is however a crop that is highly sensitive tweeds, and there are few selective herbicides for the crop. With this in mind, this study aimed to evaluate the selectivity of herbicides applied to pre-emergent cotton crops. The herbicides, alachlor, S-metolachlor, diuron, prometryne, trifluralin and oxyfluorfen were applied both

  1. Seletividade de herbicidas aplicados em pré-emergência, isolados e em misturas, na cultura do algodão = Selective of applied herbicides in pre-emergency, isolated and in mixtures, in the culture of the cotton.

    Directory of Open Access Journals (Sweden)

    Miriam Hiroko Inoue

    2012-08-01

    Full Text Available A cultura do algodão tem grande importância econômica e social, visto que é a fibra mais utilizada no setor têxtil. Contudo, apresenta alta sensibilidade a plantas daninhas e há poucos herbicidas seletivos à cultura. Neste contexto objetivouse com este trabalho avaliar a seletividade de herbicidas aplicados em pré-emergência na cultura do algodão. Os herbicidas alachlor, S-metolachlor, diuron, prometryne, trifluralin e oxyfluorfen foram aplicados isoladamente e em misturas sobre a variedade FMT-701, nas localidades de Diamantino-MT e Campos de Júlio-MT. O delineamento experimental utilizado foiem blocos casualizados com 16 tratamentos e 4 repetições. Para avaliar a seletividade foram realizadas avaliações de alturaaos 36, 66 e 150 dias após a aplicação (DAA, fitointoxicação aos 14, 21, 29 e 36 DAA, estande aos 21 e 49 DAA, número de maçãs aos 141 DAA e produtividade do algodão em caroço aos 193 DAA. Os resultados indicaram que grande parte dos tratamentos causou injúrias na fase inicial da cultura e alguns tratamentos também proporcionaram menor altura de plantas em determinadas avaliações. Verificou-se ainda que os tratamentos não proporcionaram diferença significativa no estande de plantas, no número de maçãs e nem na produtividade de algodão em caroço, evidenciando que todos os tratamentos avaliados podem ser utilizados no manejo de plantas daninhas.The culture of the cotton has great economic and social importance, because it is the fiber more frequently used in the textile section. However, the crop has high sensibility to weed and there are few selective herbicides for this crop. In this context, the objective of this study was to evaluate the selectivity of applied herbicides in pre-emergency on the culture of the cotton. The herbicides alachlor, S-metolachlor, diuron, prometryne, trifluralin and oxyfluorfen were separately applied and in mixtures with the variety FMT-701, in the places of Diamantino

  2. Pesticide use and risk of end-stage renal disease among licensed pesticide applicators in the Agricultural Health Study.

    Science.gov (United States)

    Lebov, Jill F; Engel, Lawrence S; Richardson, David; Hogan, Susan L; Hoppin, Jane A; Sandler, Dale P

    2016-01-01

    Experimental studies suggest a relationship between pesticide exposure and renal impairment, but epidemiological evidence is limited. We evaluated the association between exposure to 39 specific pesticides and end-stage renal disease (ESRD) incidence in the Agricultural Health Study, a prospective cohort study of licensed pesticide applicators in Iowa and North Carolina. Via linkage to the US Renal Data System, we identified 320 ESRD cases diagnosed between enrolment (1993-1997) and December 2011 among 55 580 male licensed pesticide applicators. Participants provided information on use of pesticides via self-administered questionnaires. Lifetime pesticide use was defined as the product of duration and frequency of use and then modified by an intensity factor to account for differences in pesticide application practices. Cox proportional hazards models, adjusted for age and state, were used to estimate associations between ESRD and: (1) ordinal categories of intensity-weighted lifetime use of 39 pesticides, (2) poisoning and high-level pesticide exposures and (3) pesticide exposure resulting in a medical visit or hospitalisation. Positive exposure-response trends were observed for the herbicides alachlor, atrazine, metolachlor, paraquat, and pendimethalin, and the insecticide permethrin. More than one medical visit due to pesticide use (HR=2.13; 95% CI 1.17 to 3.89) and hospitalisation due to pesticide use (HR=3.05; 95% CI 1.67 to 5.58) were significantly associated with ESRD. Our findings support an association between ESRD and chronic exposure to specific pesticides, and suggest pesticide exposures resulting in medical visits may increase the risk of ESRD. Clinicaltrials.gov NCT00352924. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  3. Occurrence of sulfonylurea, sulfonamide, imidazolinone, and other herbicides in rivers, reservoirs and ground water in the Midwestern United States, 1998

    Science.gov (United States)

    Battaglin, W.A.; Furlong, E.T.; Burkhardt, M.R.; Peter, C.J.

    2000-01-01

    Sulfonylurea (SU), sulfonamide (SA), and imidazolinone (IMI) herbicides are relatively new classes of chemical compounds that function by inhibiting the action of a plant enzyme, stopping plant growth, and eventually killing the plant. These compounds generally have low mammalian toxicity, but plants demonstrate a wide range in sensitivity to SUs, SAs, and IMIs with over a 10000-fold difference in observed toxicity levels for some compounds. SUs, SAs, and IMIs are applied either pre- or post-emergence to crops commonly at 1/50th or less of the rate of other herbicides. Little is known about their occurrence, fate, or transport in surface water or ground water in the USA. To obtain information on the occurrence of SU, SA, and IMI herbicides in the Midwestern United States, 212 water samples were collected from 75 surface-water and 25 ground-water sites in 1998. These samples were analyzed for 16 SU, SA and IMI herbicides by USGS Methods Research and Development Program staff using high-performance liquid chromatography/mass spectrometry. Samples were also analyzed for 47 pesticides or pesticide degradation products. At least one of the 16 SUs, SAs or IMIs was detected above the method reporting limit (MRL) of 0.01 ??g/l in 83% of 130 stream samples. Imazethapyr was detected most frequently (71% of samples) followed by flumetsulam (63% of samples) and nicosulfuron (52% of samples). The sum of SU, SA and IMI concentrations exceeded 0.5 ??g/l in less than 10% of stream samples. Acetochlor, alachlor, atrazine, cyanazine and metolachlor were all detected in 90% or more of 129 stream samples. The sum of the concentration of these five herbicides exceeded 50 ??g/l in approximately 10% of stream samples. At least one SU, SA, or IMI herbicide was detected above the MRL in 24% of 25 ground-water samples and 86% of seven reservoir samples. Copyright (C) 2000 Elsevier Science B.V.

  4. Microwave-assisted extraction through an aqueous medium and simultaneous cleanup by partition on hexane for determining pesticides in agricultural soils by gas chromatography: A critical study

    International Nuclear Information System (INIS)

    Fuentes, Edwar; Baez, Maria E.; Reyes, Dana

    2006-01-01

    A simple microwave-assisted extraction and partitioning method (MAEP) using water-acetonitrile and n-hexane for desorption and simultaneous partitioning, respectively, together with gas chromatography (GC) was studied to determine representative pesticides (trifluralin, metolachlor, chlorpyriphos and triadimefon) with a broad range of physico-chemical properties in agricultural soils. Three points were considered crucial in this study: instrumental and sample-associated factors affecting extraction of the target compounds were studied through experimental design; the spiking procedure at trace levels was carried out to reproduce the solute-soil sorption taking place in the environment as closely as possible; and results were analyzed taking into account the adsorption behaviour of the compounds on different kinds of soils. The complete analytical procedure proposed consisted of the MAEP of pesticides from 1.0 g of soil with 1 mL of 1:1 water/acetonitrile mixture, and 5 mL of hexane for trapping. The microwave heating program applied was 2 min at 250 W and 10 min at 900 W, and 130 deg. C maximum temperature. After extraction, the hexane layer was evaporated to dryness; the residue was re-dissolved and directly analyzed by gas chromatography electron capture detection (GC-ECD). Clean chromatograms were obtained without any additional cleanup step. Besides the four pesticides used to optimise MAEP, the method was applied to determine an additional group of pesticides (triallate, acetochlor, alachlor, endosulphan I and II, endrin, methoxychlor and tetradifon) in different soils. Most of the compounds studied were recovered in good yields with relative standard deviations (R.S.D.s) below 9% and detection limits ranged from 0.004 to 0.036 μg g -1 . The described method is efficient and fast to determine hydrophobic pesticides at ng g -1 level in soil with different clay-to-organic matter ratios

  5. Microwave-assisted extraction through an aqueous medium and simultaneous cleanup by partition on hexane for determining pesticides in agricultural soils by gas chromatography: A critical study

    Energy Technology Data Exchange (ETDEWEB)

    Fuentes, Edwar [Departamento de Quimica Inorganica y Analitica, Facultad de Ciencias Quimicas y Farmaceuticas, Universidad de Chile, Santiago, Casilla 233 (Chile)]. E-mail: edfuentes@ciq.uchile.cl; Baez, Maria E. [Departamento de Quimica Inorganica y Analitica, Facultad de Ciencias Quimicas y Farmaceuticas, Universidad de Chile, Santiago, Casilla 233 (Chile); Reyes, Dana [Departamento de Quimica Inorganica y Analitica, Facultad de Ciencias Quimicas y Farmaceuticas, Universidad de Chile, Santiago, Casilla 233 (Chile)

    2006-09-25

    A simple microwave-assisted extraction and partitioning method (MAEP) using water-acetonitrile and n-hexane for desorption and simultaneous partitioning, respectively, together with gas chromatography (GC) was studied to determine representative pesticides (trifluralin, metolachlor, chlorpyriphos and triadimefon) with a broad range of physico-chemical properties in agricultural soils. Three points were considered crucial in this study: instrumental and sample-associated factors affecting extraction of the target compounds were studied through experimental design; the spiking procedure at trace levels was carried out to reproduce the solute-soil sorption taking place in the environment as closely as possible; and results were analyzed taking into account the adsorption behaviour of the compounds on different kinds of soils. The complete analytical procedure proposed consisted of the MAEP of pesticides from 1.0 g of soil with 1 mL of 1:1 water/acetonitrile mixture, and 5 mL of hexane for trapping. The microwave heating program applied was 2 min at 250 W and 10 min at 900 W, and 130 deg. C maximum temperature. After extraction, the hexane layer was evaporated to dryness; the residue was re-dissolved and directly analyzed by gas chromatography electron capture detection (GC-ECD). Clean chromatograms were obtained without any additional cleanup step. Besides the four pesticides used to optimise MAEP, the method was applied to determine an additional group of pesticides (triallate, acetochlor, alachlor, endosulphan I and II, endrin, methoxychlor and tetradifon) in different soils. Most of the compounds studied were recovered in good yields with relative standard deviations (R.S.D.s) below 9% and detection limits ranged from 0.004 to 0.036 {mu}g g{sup -1}. The described method is efficient and fast to determine hydrophobic pesticides at ng g{sup -1} level in soil with different clay-to-organic matter ratios.

  6. A review on environmental monitoring of water organic pollutants identified by EU guidelines.

    Science.gov (United States)

    Sousa, João C G; Ribeiro, Ana R; Barbosa, Marta O; Pereira, M Fernando R; Silva, Adrián M T

    2018-02-15

    The contamination of fresh water is a global concern. The huge impact of natural and anthropogenic organic substances that are constantly released into the environment, demands a better knowledge of the chemical status of Earth's surface water. Water quality monitoring studies have been performed targeting different substances and/or classes of substances, in different regions of the world, using different types of sampling strategies and campaigns. This review article aims to gather the available dispersed information regarding the occurrence of priority substances (PSs) and contaminants of emerging concern (CECs) that must be monitored in Europe in surface water, according to the European Union Directive 2013/39/EU and the Watch List of Decision 2015/495/EU, respectively. Other specific organic pollutants not considered in these EU documents as substances of high concern, but with reported elevated frequency of detection at high concentrations, are also discussed. The search comprised worldwide publications from 2012, considering at least one of the following criteria: 4 sampling campaigns per year, wet and dry seasons, temporal and/or spatial monitoring of surface (river, estuarine, lake and/or coastal waters) and ground waters. The highest concentrations were found for: (i) the PSs atrazine, alachlor, trifluralin, heptachlor, hexachlorocyclohexane, polycyclic aromatic hydrocarbons and di(2-ethylhexyl)phthalate; (ii) the CECs azithromycin, clarithromycin, erythromycin, diclofenac, 17α-ethinylestradiol, imidacloprid and 2-ethylhexyl 4-methoxycinnamate; and (iii) other unregulated organic compounds (caffeine, naproxen, metolachlor, estriol, dimethoate, terbuthylazine, acetaminophen, ibuprofen, trimethoprim, ciprofloxacin, ketoprofen, atenolol, Bisphenol A, metoprolol, carbofuran, malathion, sulfamethoxazole, carbamazepine and ofloxacin). Most frequent substances as well as those found at highest concentrations in different seasons and regions, together with

  7. Pesticides in rain in four agricultural watersheds in the United States

    Science.gov (United States)

    Vogel, J.R.; Majewski, M.S.; Capel, P.D.

    2008-01-01

    Rainfall samples were collected during the 2003 and 2004 growing seasons at four agricultural locales across the USA in Maryland, Indiana, Nebraska, and California. The samples were analyzed for 21 insecticides, 18 herbicides, three fungicides, and 40 pesticide degradates. Data from all sites combined show that 7 of the 10 most frequently detected pesticides were herbicides, with atrazine (70%) and metolachlor (83%) detected at every site. Dacthal, acetochlor, simazine, alachlor, and pendimethalin were detected in more than 50% of the samples. Chlorpyrifos, carbaryl, and diazinon were the only insecticides among the 10 most frequently detected compounds. Of the remaining pesticide parent compounds, 18 were detected in fewer than 30% of the samples, and 13 were not detected. The most frequently detected degradates were deethylatrazine; the oxygen analogs (OAs) of the organophosphorus insecticides chlorpyrifos, diazinon, and malathion; and 1-napthol (degradate of carbaryl). Deethylatrazine was detected in nearly 70% of the samples collected in Maryland, Indiana, and Nebraska but was detected only once in California. The OAs of chlorpyrifos and diazinon were detected primarily in California. Degradates of the acetanilide herbicides were rarely detected in rain, indicating that they are not formed in the atmosphere or readily volatilized from soils. Herbicides accounted for 91 to 98% of the total pesticide mass deposited by rain except in California, where insecticides accounted for 61% in 2004. The mass of pesticides deposited by rainfall was estimated to be less than 2% of the total applied in these agricultural areas. Copyright ?? 2008 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. All rights reserved.

  8. Water-quality assessment of the Kentucky River basin, Kentucky; results of investigations of surface-water quality, 1987-90

    Science.gov (United States)

    Haag, K.H.; Garcia, Rene; Jarrett, G.L.; Porter, S.D.

    1995-01-01

    The U.S. Geological Survey investigated the water quality of the Kentucky River Basin in Kentucky as part of the National Water-Quality Assessment program. Data collected during 1987-90 were used to describe the spatial and temporal variability of water-quality constituents including metals and trace elements, nutrients, sediments, pesticides, dissolved oxygen, and fecal-coliform bacteria. Oil-production activities were the source of barium, bromide, chloride, magnesium, and sodium in several watersheds. High concentrations of aluminum, iron, and zinc were related to surface mining in the Eastern Coal Field Region. High concentrations of lead and zinc occurred in streambed sediments in urban areas, whereas concentrations of arsenic, strontium, and uranium were associated with natural geologic sources. Concentrations of phosphorus were significantly correlated with urban and agricultural land use. The high phosphorus content of Bluegrass Region soils was an important source of phosphorus in streams. At many sites in urban areas, most of the stream nitrogen load was attributable to wastewater-treatment-plant effluent. Average suspended-sediment concentrations were positively correlated with discharge. There was a downward trend in suspended-sediment concentrations downstream in the Kentucky River main stem during the study. The most frequently detected herbicides in water samples were atrazine, 2,4-D, alachlor, metolachlor, and dicamba. Diazinon, malathion, and parathion were the most frequently detected organophosphate insecticides in water samples. Detectable concentrations of aldrin, chlordane, DDT, DDE, dieldrin, endrin, endosulfan, heptachlor, and lindane were found in streambed-sediment samples. Dissolved-oxygen concentrations were sometimes below the minimum concentration needed to sustain aquatic life. At some sites, high concentrations of fecal-indicator bacteria were found and water samples did not meet sanitary water-quality criteria.

  9. Water Quality Conditions Monitored at the Corps’ Fort Randall Project in South Dakota during the 3-Year Period 2006 through 2008

    Science.gov (United States)

    2009-02-01

    dimethenamid, diuron, EPTC, ethalfluralin, fonofos, hexazinone, isophenphos, isopropalin, metolachlor, metribuzin, molinate, oxiadiazon, oxyfluorfen , pebulate...metolachlor, metribuzin, molinate, oxiadiazon, oxyfluorfen , pebulate, pendimethalin, phorate, profluralin, prometon, prometryn, propachlor, propazine...dimethenamid, diuron, EPTC, ethalfluralin, fonofos, hexazinone, isophenphos, isopropalin, metolachlor, metribuzin, molinate, oxiadiazon, oxyfluorfen

  10. Analysis of polar organic contaminants in surface water of the northern Adriatic Sea by solid-phase extraction followed by ultrahigh-pressure liquid chromatography-QTRAP® MS using a hybrid triple-quadrupole linear ion trap instrument.

    Science.gov (United States)

    Loos, Robert; Tavazzi, Simona; Paracchini, Bruno; Canuti, Elisabetta; Weissteiner, Christof

    2013-07-01

    Water-soluble polar organic contaminants are discharged by rivers, cities, and ships into the oceans. Little is known on the fate, pollution effects, and thresholds of toxic chemical mixtures in the marine environment. A new trace analytical method was developed for the multi-compound analysis of polar organic chemical contaminants in marine waters. The method is based on automated solid-phase extraction (SPE) of one-liter water samples followed by ultrahigh-pressure liquid chromatography triple-quadrupole linear ion-trap mass spectrometry (UHPLC-QTRAP(®) MS). Marine water samples from the open Adriatic Sea taken 16 km offshore from Venice (Italy) were analyzed. Method limits of quantification (LOQs) in the low picogram per liter (pg/l) concentration range were achieved. Among the 67 target chemicals analyzed, 45 substances could be detected above the LOQ. The chemicals detected at the highest concentrations were caffeine (up to 367 ng/l), nitrophenol (36 ng/l), 2,4-dinitrophenol (34 ng/l), 5-methyl-1H-benzotriazole (18.5 ng/l), sucralose (11 ng/l), 1H-benzotriazole (9.2 ng/l), terbuthylazine (9 ng/l), alachlor (7.7 ng/l), atrazine-desisopropyl (6.6 ng/l), diethyltoluamide (DEET) (5.0 ng/l), terbuthylazine-desethyl (4.3 ng/l), metolachlor (2.8 ng/l), perfluorooctanoic acid (PFOA) (2.5 ng/l), perfluoropentanoic acid (PFPeA) (2.3 ng/l), linuron (2.3 ng/l), perfluorohexanoic acid (PFHxA) (2.2 ng/l), diuron (2.0 ng/l), perfluorohexane sulfonate (PFHxS) (1.6 ng/l), simazine (1.6 ng/l), atrazine (1.5 ng/l), and perfluorooctane sulfonate (PFOS) (1.3 ng/l). Higher concentrations were detected during summer due to increased levels of tourist activity during this period.

  11. Risk assessment of herbicides and booster biocides along estuarine continuums in the Bay of Vilaine area (Brittany, France).

    Science.gov (United States)

    Caquet, Th; Roucaute, M; Mazzella, N; Delmas, F; Madigou, C; Farcy, E; Burgeot, Th; Allenou, J-P; Gabellec, R

    2013-02-01

    A 2-year study was implemented to characterize the contamination of estuarine continuums in the Bay of Vilaine area (NW Atlantic Coast, Southern Brittany, France) by 30 pesticide and biocide active substances and metabolites. Among these, 11 triazines (ametryn, atrazine, desethylatrazine, desethylterbuthylazine, desisopropyl atrazine, Irgarol 1051, prometryn, propazine, simazine, terbuthylazine, and terbutryn), 10 phenylureas (chlortoluron, diuron, 1-(3,4-dichlorophenyl)-3-methylurea, fenuron, isoproturon, 1-(4-isopropylphenyl)-3-methylurea, 1-(4-isopropylphenyl)-urea, linuron, metoxuron, and monuron), and 4 chloroacetanilides (acetochlor, alachlor, metolachlor, and metazachlor) were detected at least once. The objectives were to assess the corresponding risk for aquatic primary producers and to provide exposure information for connected studies on the responses of biological parameters in invertebrate sentinel species. The risk associated with contaminants was assessed using risk quotients based on the comparison of measured concentrations with original species sensitivity distribution-derived hazardous concentration values. For EU Water Framework Directive priority substances, results of monitoring were also compared with regulatory Environmental Quality Standards. The highest residue concentrations and risks for primary producers were recorded for diuron and Irgarol 1051 in Arzal reservoir, close to a marina. Diuron was present during almost the all survey periods, whereas Irgarol 1051 exhibited a clear seasonal pattern, with highest concentrations recorded in June and July. These results suggest that the use of antifouling biocides is responsible for a major part of the contamination of the lower part of the Vilaine River course for Irgarol 1051. For diuron, agricultural sources may also be involved. The presence of isoproturon and chloroacetanilide herbicides on some dates indicated a significant contribution of the use of plant protection products in

  12. IMPROVING STRUCTURE-LINKED ACCESS TO PUBLICLY AVAILABLE CHEMICAL TOXICITY INFORMATION

    Science.gov (United States)

    Hepatotoxicity of the Herbicide Alachlor Associated with Glutathione Depletion, Oxidative Damage and Protein S-Cysteinyl Adduction.Toxicity of the herbicide alachlor (2-chloro-2',6'-diethtl-N-[methoxtmethtl]-acetanilide) has been attributed to cytochrome P450-dependent me...

  13. Water Quality Conditions Monitored at the Corps’ Oahe Project in South Dakota during the 3-Year Period 2005 through 2007

    Science.gov (United States)

    2008-02-01

    isophenphos, isopropalin, metolachlor, metribuzin, molinate, oxadiazon, oxyfluorfen , pebulate, pendimethalin, phorate, profluralin, prometon, propachlor...EPTC, ethalfluralin, fonofos, hexazinone, isophenphos, isopropalin, metolachlor, metribuzin, molinate, oxadiazon, oxyfluorfen , pebulate, pendimethalin...oxadiazon, oxyfluorfen , pebulate, pendimethalin, phorate, profluralin, prometon, propachlor, propazine, simazine, terbufos, triallate, trifluralin

  14. Water Quality Time Series, Aggregate values, and Related Aggregate Risk Measures

    Data.gov (United States)

    U.S. Environmental Protection Agency — The excel file contains time series data of flow rates, concentrations of alachlor , atrazine, ammonia, total phosphorus, and total suspended solids observed in two...

  15. Quality optimization of H.264/AVC video transmission over noisy environments using a sparse regression framework

    Science.gov (United States)

    Pandremmenou, K.; Tziortziotis, N.; Paluri, S.; Zhang, W.; Blekas, K.; Kondi, L. P.; Kumar, S.

    2015-03-01

    We propose the use of the Least Absolute Shrinkage and Selection Operator (LASSO) regression method in order to predict the Cumulative Mean Squared Error (CMSE), incurred by the loss of individual slices in video transmission. We extract a number of quality-relevant features from the H.264/AVC video sequences, which are given as input to the LASSO. This method has the benefit of not only keeping a subset of the features that have the strongest effects towards video quality, but also produces accurate CMSE predictions. Particularly, we study the LASSO regression through two different architectures; the Global LASSO (G.LASSO) and Local LASSO (L.LASSO). In G.LASSO, a single regression model is trained for all slice types together, while in L.LASSO, motivated by the fact that the values for some features are closely dependent on the considered slice type, each slice type has its own regression model, in an e ort to improve LASSO's prediction capability. Based on the predicted CMSE values, we group the video slices into four priority classes. Additionally, we consider a video transmission scenario over a noisy channel, where Unequal Error Protection (UEP) is applied to all prioritized slices. The provided results demonstrate the efficiency of LASSO in estimating CMSE with high accuracy, using only a few features. les that typically contain high-entropy data, producing a footprint that is far less conspicuous than existing methods. The system uses a local web server to provide a le system, user interface and applications through an web architecture.

  16. Occurrence and distribution of dissolved pesticides in the San Joaquin River basin, California

    Science.gov (United States)

    Panshin, Sandra Yvonne; Dubrovsky, Neil M.; Gronberg, JoAnn M.; Domagalski, Joseph L.

    1998-01-01

    The effects of pesticide application, hydrology, and chemical and physical properties on the occurrence of pesticides in surface water in the San Joaquin River Basin, California, were examined. The study of pesticide occurrence in the highly agricultural San Joaquin?Tulare Basins is part of the National Water-Quality Assessment Program of the U.S. Geological Survey. One hundred forty-three water samples were collected throughout 1993 from sites on the San Joaquin River and three of its tributaries: Orestimba Creek, Salt Slough, and the Merced River. Of the 83 pesticides selected for analysis in this study, 49 different compounds were detected in samples from the four sites and ranged in concentration from less than the detection limit to 20 micrograms per liter. All but one sample contained at least one pesticide, and more than 50 percent of the samples contained seven or more pesticides. Six compounds were detected in more than 50 percent of the samples: four herbicides (dacthal, EPTC, metolachlor, and simazine) and two insecticides (chlorpyrifos and diazinon). None of the measured concentrations exceeded U.S. Environmental Protection Agency drinking water criteria, and many of the measured concentrations were very low. The concentrations of seven pesticides exceeded criteria for the protection of freshwater aquatic life: azinphos-methyl, carbaryl, chlorpyrifos, diazinon, diuron, malathion, and trifluralin. Overall, some criteria for protection of aquatic life were exceeded in a total of 97 samples. Factors affecting the spatial patterns of occurrence of the pesticides in the different subbasins included the pattern of application and hydrology. Seventy percent of pesticides with known application were detected. Overall, 40 different pesticides were detected in Orestimba Creek, 33 in Salt Slough, and 26 in the Merced River. Samples from the Merced River had a relatively low number of detections, despite the high number (35) of pesticides applied, owing to the

  17. Occurrence of Agricultural Chemicals in Shallow Ground Water and the Unsaturated Zone, Northeast Nebraska Glacial Till, 2002-04

    Science.gov (United States)

    Stanton, Jennifer S.; Steele, Gregory V.; Vogel, Jason R.

    2007-01-01

    included parent or degradate compounds of acetochlor, alachlor, atrazine, and metolachlor. Overall, pesticide concentrations in ground-water samples collected in 2003 and 2004 were small and did not exceed public drinking-water standards where established. On average, more pesticides were detected in the flow-path wells than in the glacial-till network wells. The presence of a perennial stream within 1,640 feet of a well was correlated to smaller nitrate-N concentrations in the well water, and the presence of a road ditch within 164 feet of the well was correlated to the presence of detectable pesticides in the well water. All other variables tested showed no significant correlations to nitrate-N concentrations or pesticide detections. Unsaturated zone soil cores collected in 2002 from well boreholes indicated that nitrogen in the forms of nitrate-N and ammonia as nitrogen (ammonia-N) was available in the unsaturated zone for transport to ground water. Concentrations of nitrate-N and ammonia-N in these soil cores were inversely correlated to depth, and nitrate-N concentrations were correlated to chloride concentrations.

  18. Oracle Inequalities for High Dimensional Vector Autoregressions

    DEFF Research Database (Denmark)

    Callot, Laurent; Kock, Anders Bredahl

    This paper establishes non-asymptotic oracle inequalities for the prediction error and estimation accuracy of the LASSO in stationary vector autoregressive models. These inequalities are used to establish consistency of the LASSO even when the number of parameters is of a much larger order...

  19. 77 FR 30526 - Product Cancellation Order for Certain Pesticide Registrations

    Science.gov (United States)

    2012-05-23

    ... Transplant. NC910011 Drexel Sucker Alcohols, Cx--Cxx. Plucker Concentrate. OH080002 Tree-Age Emamectin benzoate. OR100006 Dual Magnum S-Metolachlor. Herbicide. SC910006 Drexel Sucker Alcohols, Cx--Cxx. Plucker...

  20. Corn stover harvest increases herbicide movement to subsurface drains: RZWQM simulations

    Science.gov (United States)

    Shipitalo, Martin J.; Malone, Robert W.; Ma, Liwang; Nolan, Bernard T.; Kanwar, Rameshwar S.; Shaner, Dale L.; Pederson, Carl H.

    2016-01-01

    BACKGROUND Crop residue removal for bioenergy production can alter soil hydrologic properties and the movement of agrochemicals to subsurface drains. The Root Zone Water Quality Model (RZWQM), previously calibrated using measured flow and atrazine concentrations in drainage from a 0.4 ha chisel-tilled plot, was used to investigate effects of 50 and 100% corn (Zea mays L.) stover harvest and the accompanying reductions in soil crust hydraulic conductivity and total macroporosity on transport of atrazine, metolachlor, and metolachlor oxanilic acid (OXA). RESULTS The model accurately simulated field-measured metolachlor transport in drainage. A 3-yr simulation indicated that 50% residue removal decreased subsurface drainage by 31% and increased atrazine and metolachlor transport in drainage 4 to 5-fold when surface crust conductivity and macroporosity were reduced by 25%. Based on its measured sorption coefficient, ~ 2-fold reductions in OXA losses were simulated with residue removal. CONCLUSION RZWQM indicated that if corn stover harvest reduces crust conductivity and soil macroporosity, losses of atrazine and metolachlor in subsurface drainage will increase due to reduced sorption related to more water moving through fewer macropores. Losses of the metolachlor degradation product OXA will decrease due to the more rapid movement of the parent compound into the soil.

  1. Preemergence herbicides on weed control in elephant grass pasture

    Directory of Open Access Journals (Sweden)

    Alexandre Magno Brighenti

    Full Text Available ABSTRACT Elephant grass (Pennisetum purpureum Schum. is an important forage crop that has been proposed as a potential feedstock for bioenergy production. However, weed interference is a major factor limiting elephant grass production. Field experiments were conducted in 2014 and 2015 to evaluate preemergence herbicides for selective weed control in an elephant grass pasture. Herbicide treatments included atrazine + S-metolachlor, atrazine + simazine, ametryn, ethoxysulfuron, S-metolachlor, diuron + hexazinone, sulfentrazone, imazethapyr, and atrazine at label use rates. Weedy and weed-free treatments were included. Atrazine + S-metolachlor, atrazine + simazine, ametryn, ethoxysulfuron, S-metolachlor, sulfentrazone, and atrazine did not cause phytotoxicity on elephantgrass 35 days after treatment (DAT. However, diuron + hexazinone and imazethapyr were the most phytotoxic on elephantgrass, resulting in 81 and 70% phytotoxicity in 2014, and 7 and 6% phytotoxicity in 2015 respectively 35 DAT. All treatments provided effective weed control (>81% with the exception of ethoxysulfuron (0 and 11% in 2014 and 2015, respectively, and atrazine (59% in 2014. These results show that atrazine + S-metolachlor, atrazine + simazine, ametryn, ethoxysulfuron, S-metolachlor, sulfentrazone, and atrazine were selectives when applied in preemergence in elephant grass pasture.

  2. Allelopathic sorghum water extract helps to improve yield of sunflower (helianthus annuus l.)

    International Nuclear Information System (INIS)

    Shah, S.; Khan, E.A.

    2016-01-01

    Allelopathy provides eco-friendly environment in managing weeds by reducing the use of synthetic herbicides that cause environmental pollution and herbicide resistance problems. Therefore, weeds have been controlling by plant derived organic compounds as an alternative of inorganic herbicides since the last two decades. In this study, sorghum aqueous extracts were applied individually as well as accumulatively with reduced levels of Dual Gold at the rate (S-Metolachlor) as foliar sprays in sunflower at 50, 70 and 90 DAS. For comparison, standard level of S-Metolachlor was also applied as foliar sprays along with weedy check. The highest reduction of total weed density (93.7%) was recorded by three sprays of sorghum aqueous extracts at rate of 15 L/ha mixed with 1/3rd S-Metolachlor at 1.6 L/ha as foliar applications. This reduction rate was statistically similar to one that was obtained by standard level of S-Metolachlor (1.6 L/ha). The highest achene yield was achieved by applying three foliar sprays of aqueous sorghum extracts along with reduced doses of S-Metolachlor, which was almost similar to full recommended dose of S-Metolachlor. These findings demonstrate that allelopathy offers environment friendly and economical opportunity for weed control in sunflower reducing the dependence and cost of herbicides. (author)

  3. The Response of Lemna minor to Mixtures of Pesticides That Are Commonly Used in Thailand.

    Science.gov (United States)

    Tagun, Rungnapa; Boxall, Alistair B A

    2018-04-01

    In the field, aquatic organisms are exposed to multiple contaminants rather than to single compounds. It is therefore important to understand the toxic interactions of co-occurring substances in the environment. The aim of the study was to assess the effects of individual herbicides (atrazine, 2,4-D, alachlor and paraquat) that are commonly used in Thailand and their mixtures on Lemna minor. Plants were exposed to individual and binary mixtures for 7 days and the effects on plant growth rate were assesed based on frond area measurements. Experimental observations of mixture toxicity were compared with predictions based on single herbicide exposure data using concentration addition and independent action models. The single compound studies showed that paraquat and alachlor were most toxic to L. minor, followed by atrazine and then 2,4-D. For the mixtures, atrazine with 2,4-D appeared to act antagonistically, whereas alachlor and paraquat showed synergism.

  4. Least absolute shrinkage and selection operator type methods for the identification of serum biomarkers of overweight and obesity: simulation and application

    Directory of Open Access Journals (Sweden)

    Monica M. Vasquez

    2016-11-01

    Full Text Available Abstract Background The study of circulating biomarkers and their association with disease outcomes has become progressively complex due to advances in the measurement of these biomarkers through multiplex technologies. The Least Absolute Shrinkage and Selection Operator (LASSO is a data analysis method that may be utilized for biomarker selection in these high dimensional data. However, it is unclear which LASSO-type method is preferable when considering data scenarios that may be present in serum biomarker research, such as high correlation between biomarkers, weak associations with the outcome, and sparse number of true signals. The goal of this study was to compare the LASSO to five LASSO-type methods given these scenarios. Methods A simulation study was performed to compare the LASSO, Adaptive LASSO, Elastic Net, Iterated LASSO, Bootstrap-Enhanced LASSO, and Weighted Fusion for the binary logistic regression model. The simulation study was designed to reflect the data structure of the population-based Tucson Epidemiological Study of Airway Obstructive Disease (TESAOD, specifically the sample size (N = 1000 for total population, 500 for sub-analyses, correlation of biomarkers (0.20, 0.50, 0.80, prevalence of overweight (40% and obese (12% outcomes, and the association of outcomes with standardized serum biomarker concentrations (log-odds ratio = 0.05–1.75. Each LASSO-type method was then applied to the TESAOD data of 306 overweight, 66 obese, and 463 normal-weight subjects with a panel of 86 serum biomarkers. Results Based on the simulation study, no method had an overall superior performance. The Weighted Fusion correctly identified more true signals, but incorrectly included more noise variables. The LASSO and Elastic Net correctly identified many true signals and excluded more noise variables. In the application study, biomarkers of overweight and obesity selected by all methods were Adiponectin, Apolipoprotein H, Calcitonin, CD

  5. Least absolute shrinkage and selection operator type methods for the identification of serum biomarkers of overweight and obesity: simulation and application.

    Science.gov (United States)

    Vasquez, Monica M; Hu, Chengcheng; Roe, Denise J; Chen, Zhao; Halonen, Marilyn; Guerra, Stefano

    2016-11-14

    The study of circulating biomarkers and their association with disease outcomes has become progressively complex due to advances in the measurement of these biomarkers through multiplex technologies. The Least Absolute Shrinkage and Selection Operator (LASSO) is a data analysis method that may be utilized for biomarker selection in these high dimensional data. However, it is unclear which LASSO-type method is preferable when considering data scenarios that may be present in serum biomarker research, such as high correlation between biomarkers, weak associations with the outcome, and sparse number of true signals. The goal of this study was to compare the LASSO to five LASSO-type methods given these scenarios. A simulation study was performed to compare the LASSO, Adaptive LASSO, Elastic Net, Iterated LASSO, Bootstrap-Enhanced LASSO, and Weighted Fusion for the binary logistic regression model. The simulation study was designed to reflect the data structure of the population-based Tucson Epidemiological Study of Airway Obstructive Disease (TESAOD), specifically the sample size (N = 1000 for total population, 500 for sub-analyses), correlation of biomarkers (0.20, 0.50, 0.80), prevalence of overweight (40%) and obese (12%) outcomes, and the association of outcomes with standardized serum biomarker concentrations (log-odds ratio = 0.05-1.75). Each LASSO-type method was then applied to the TESAOD data of 306 overweight, 66 obese, and 463 normal-weight subjects with a panel of 86 serum biomarkers. Based on the simulation study, no method had an overall superior performance. The Weighted Fusion correctly identified more true signals, but incorrectly included more noise variables. The LASSO and Elastic Net correctly identified many true signals and excluded more noise variables. In the application study, biomarkers of overweight and obesity selected by all methods were Adiponectin, Apolipoprotein H, Calcitonin, CD14, Complement 3, C-reactive protein, Ferritin

  6. Estimating High-Dimensional Time Series Models

    DEFF Research Database (Denmark)

    Medeiros, Marcelo C.; Mendes, Eduardo F.

    We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. We assume both the number of covariates in the model and candidate variables can increase with the number of observations and the number of candidate variables is, possibly......, larger than the number of observations. We show the adaLASSO consistently chooses the relevant variables as the number of observations increases (model selection consistency), and has the oracle property, even when the errors are non-Gaussian and conditionally heteroskedastic. A simulation study shows...

  7. Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models

    Energy Technology Data Exchange (ETDEWEB)

    Xu Chengjian, E-mail: c.j.xu@umcg.nl [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van' t [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands)

    2012-03-15

    Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

  8. Impact of statistical learning methods on the predictive power of multivariate normal tissue complication probability models.

    Science.gov (United States)

    Xu, Cheng-Jian; van der Schaaf, Arjen; Schilstra, Cornelis; Langendijk, Johannes A; van't Veld, Aart A

    2012-03-15

    To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended. Copyright © 2012 Elsevier Inc. All rights reserved.

  9. Statistical validation of normal tissue complication probability models

    NARCIS (Netherlands)

    Xu, Cheng-Jian; van der Schaaf, Arjen; van t Veld, Aart; Langendijk, Johannes A.; Schilstra, Cornelis

    2012-01-01

    PURPOSE: To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. METHODS AND MATERIALS: A penalized regression method, LASSO (least absolute shrinkage

  10. Investigation of factors affecting the intelligence quotient (IQ) of ...

    African Journals Online (AJOL)

    ... and social risk factors play a role in the development of intellectual disability. ... Results: The optimal model was obtained with the Lasso approach and ... of attention-deficit hyperactivity disorder, family income, and number of siblings, ...

  11. Chemical agnostic hazard prediction: Statistical inference of toxicity pathways - data for Figure 2

    Data.gov (United States)

    U.S. Environmental Protection Agency — This dataset comprises one SigmaPlot 13 file containing measured survival data and survival data predicted from the model coefficients selected by the LASSO...

  12. Empirical Performance of Cross-Validation With Oracle Methods in a Genomics Context.

    Science.gov (United States)

    Martinez, Josue G; Carroll, Raymond J; Müller, Samuel; Sampson, Joshua N; Chatterjee, Nilanjan

    2011-11-01

    When employing model selection methods with oracle properties such as the smoothly clipped absolute deviation (SCAD) and the Adaptive Lasso, it is typical to estimate the smoothing parameter by m-fold cross-validation, for example, m = 10. In problems where the true regression function is sparse and the signals large, such cross-validation typically works well. However, in regression modeling of genomic studies involving Single Nucleotide Polymorphisms (SNP), the true regression functions, while thought to be sparse, do not have large signals. We demonstrate empirically that in such problems, the number of selected variables using SCAD and the Adaptive Lasso, with 10-fold cross-validation, is a random variable that has considerable and surprising variation. Similar remarks apply to non-oracle methods such as the Lasso. Our study strongly questions the suitability of performing only a single run of m-fold cross-validation with any oracle method, and not just the SCAD and Adaptive Lasso.

  13. Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models

    International Nuclear Information System (INIS)

    Xu Chengjian; Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van’t

    2012-01-01

    Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

  14. The behavior and bioactivity of imazaquin in soils

    International Nuclear Information System (INIS)

    McKinnon, E.J.

    1989-01-01

    Laboratory studies were conducted to determine the adsorption and relative mobility of 14 C-labelled imazaquin (2-[4,5-dihydro-4-methyl-4-(1-methylethyl)-5-oxo-1H-imadazol-2-yl]-3-quinolinecarboxylic acid) and 14 C labelled metolachlor (2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl) acetamide) on Norfolk sand loan (Typic Paleudult), Rion sandy clay loam (Typic Hapludult), Cape Fear sandy clay loam (Typic Umbraquult) and Webster clay loam (Typic Hapluquoll). Imazaquin was more mobile than metolachlor on all four soils. Soils high in humic matter content retained between 45 and 48% of the applied imazaquin and 93 and 97% of the applied metolachlor. The relative order of mobility of imazaquin in the soils was Rion = Norfolk > Cape Fear = Webster. The order for metolachlor in the soils was Rion > Norfolk > Cape Fear > Webster. Adsorption of imazaquin and metolachlor was inversely related to their mobility in the soil columns. Adsorption of imazaquin increased as the suspension pH decreased

  15. NOVEL CHROMATOGRAPHIC SEPARATION AND CARBON SOLID PHASE EXTRACTION OF ACETANILIDE HERBICIDE DEGRADATION PRODUCTS

    Science.gov (United States)

    Six acetanilide herbicides are currently registered for use in the U.S. Over the past several years, ethanesufonic acid (ESA) and oxanilic acid (OA) degradatoin products of these acetanilide herbicides have been found in U.S. ground waters and surface waters. "Alachlor ESA and ...

  16. DEVELOPMENT OF METHOD 535 FOR THE DETERMINATION OF CHLOROACETANILIDE AND OTHER ACETAMIDE HERBICIDE DEGRADATES IN DRINKING WATER BY SOLID PHASE EXTRACTION AND LIQUID CHROMATOGRAPHY/TANDEM MASS SPECTROMETRY

    Science.gov (United States)

    EPA Method 535 has been developed in order to provide a method for the analysis of "Alachlor ESA and other acetanilide degradation products" which are listed on U.S. EPA's 1998 Drinking Water Contaminant Candidate List. Method 535 uses solid phase extraction with a nonporous gr...

  17. Relation of Land Use to Streamflow and Water Quality at Selected Sites in the City of Charlotte and Mecklenburg County, North Carolina, 1993-98

    Science.gov (United States)

    Bales, Jerad D.; Weaver, J. Curtis; Robinson, Jerald B.

    1999-01-01

    were several times greater than median concentrations in small Piedmont streams but almost an order of magnitude less than total phosphorus concentrations in Charlotte streams during the late 1970's.Bacteria concentrations are not correlated to streamflow. The highest bacteria levels were found in 'first-flush' samples. Higher fecal coliform concentrations were associated with residential land use.Chromium, copper, lead, and zinc occurred at all sites in concentrations that exceeded the North Carolina ambient water-quality standards. The median chromium concentration in the developing basin was more than double the median concentration at any other site. As with chromium, the maximum copper concentration in the developing basin was almost an order of magnitude greater than maximum concentrations at other sites. The highest zinc concentration also occurred in the developing basin. Samples were analyzed for 121 organic compounds and 57 volatile organic compounds. Forty-five organic compounds and seven volatile organic compounds were detected. At least five compounds were detected at all sites, and 15 or more compounds were detected at all sites except two mixed land-use basins. Atrazine, carbaryl, and metolachlor were detected at eight sites, and 90 percent of all samples had measurable amounts of atrazine. About 60 percent of the samples had detectable levels of carbaryl and metolachlor. Diazinon and malathion were measured in samples from seven sites, and methyl parathion, chlorpyrifos, alachlor, and 2,4-D were detected at four or more sites. The fewest compounds were detected in the larger, mixed land-use basins. Residential basins and the developing basin had the greatest number of detections of organic compounds.The pH of wet atmospheric deposition in three Charlotte basins was more variable than the pH measured at a National Atmospheric Deposition Program (NADP)site in Rowan County. Summer pH values were significantly lower than pH measured during the remainder of

  18. Programas de manejo químico de plantas daninhas em plantio de cana-de-açúcar fundamentados em duas aplicações de herbicidas

    Directory of Open Access Journals (Sweden)

    Marcelo Nicolai

    2010-12-01

    -metolachlor + (diuron + hexazinone [1.920 + (198 + 702]; S-metolachlor (2.400; tebuthiuron + ametrina (1.000 + 1.500; ametrina (2.000; ametrina + diuron (2.000 + 1.500; clomazone + ametrina (1.500 + 1.000 e testemunha sem aplicação. Conclui-se que os programas de manejo com duas aplicações de herbicidas controlaram as plantas daninhas até os 90 dias após a segunda aplicação. Aplicações de S-metolachlor, tebuthiuron e clomazone + ametrina, complementadas por metribuzin + (diuron + hexazinone, controlaram as plantas daninhas em mais de 90%, em todas as avaliações.

  19. Leaching and degradation of corn and soybean pesticides in an Oxisol of the Brazilian Cerrados.

    Science.gov (United States)

    Laabs, V; Amelung, W; Pinto, A; Altstaedt, A; Zech, W

    2000-11-01

    Pesticide pollution of ground and surface water is of growing concern in tropical countries. The objective of this pilot study was to evaluate the leaching potential of eight pesticides in a Brazilian Oxisol. In a field experiment near Cuiabá, Mato Grosso, atrazine, chlorpyrifos, lambda-cyhalothrin, endosulfane alpha, metolachlor, monocrotofos, simazine, and trifluraline were applied onto a Typic Haplustox. Dissipation in the topsoil, mobility within the soil profile and leaching of pesticides were studied for a period of 28 days after application. The dissipation half-life of pesticides in the topsoil ranged from 0.9 to 14 d for trifluraline and metolachlor, respectively. Dissipation curves were described by exponential functions for polar pesticides (atrazine, metolachlor, monocrotofos, simazine) and bi-exponential ones for apolar substances (chlorpyrifos, lambda-cyhalothrin, endosulfane alpha, trifluraline). Atrazine, simazine and metolachlor were moderately leached beyond 15 cm soil depth, whereas all other compounds remained within the top 15 cm of the soil. In lysimeter percolates (at 35 cm soil depth), 0.8-2.0% of the applied amounts of atrazine, simazine, and metolachlor were measured within 28 days after application. Of the other compounds less than 0.03% of the applied amounts was detected in the soil water percolates. The relative contamination potentials of pesticides, according to the lysimeter study, were ranked as follows: metolachlor > atrazine = simazine > monocrotofos > endsulfane alpha > chlorpyrifos > trifluraline > lambda-cyhalothrin. This order of the pesticides was also achieved by ranking them according to their effective sorption coefficient Ke, which is the ratio of Koc to field-dissipation half-life.

  20. Occurrence and distribution of organic chemicals and nutrients and comparison of water-quality data from public drinking-water supplies in the Columbia aquifer in Delaware, 2000-08

    Science.gov (United States)

    Reyes, Betzaida

    2010-01-01

    The U.S. Geological Survey, in cooperation with the Delaware Department of Natural Resources and Environmental Control and the Delaware Geological Survey, conducted a groundwater-quality investigation to (a) describe the occurrence and distribution of selected contaminants, and (b) document any changes in groundwater quality in the Columbia aquifer public water-supply wells in the Coastal Plain in Delaware between 2000 and 2008. Thirty public water-supply wells located throughout the Columbia aquifer of the Delaware Coastal Plain were sampled from August through November of 2008. Twenty-two of the wells in the sampling network for this project were previously sampled in 2000. Eight new wells were selected to replace wells no longer in use. Groundwater collected from the wells was analyzed for the occurrence and distribution of selected pesticides, pesticide degradates, volatile organic compounds, nutrients, and major inorganic ions. Nine of the wells were analyzed for radioactive elements (radium-226, radium-228, and radon). Groundwater-quality data were compared for sites sampled in both 2000 and 2008 to document any changes in water quality. One or more pesticides were detected in samples from 29 of the 30 wells. There were no significant differences in pesticide and pesticide degradate concentrations and similar compounds were detected when comparing sampling results from 2000 and 2008. Pesticide and pesticide degradate concentrations were generally less than 1 microgram per liter. Twenty-four compounds, 14 pesticides, and 10 pesticide degradates were detected in at least one sample; the pesticide degradates, metolachlor ethanesulfonic acid, deethylatrazine, and alachlor ethanesulfonic acid were the most frequently detected compounds, each found in more than 50 percent of samples. Almost 80 percent of the detected pesticides were agricultural herbicides, which reflects the prevalence and wide distribution of agriculture in sampled areas, as well the dominance of

  1. Comparative responses of river biofilms at the community level to common organic solvent and herbicide exposure.

    Science.gov (United States)

    Paule, A; Roubeix, V; Swerhone, G D W; Roy, J; Lauga, B; Duran, R; Delmas, F; Paul, E; Rols, J L; Lawrence, J R

    2016-03-01

    Residual pesticides applied to crops migrate from agricultural lands to surface and ground waters. River biofilms are the first aquatic non-target organisms which interact with pesticides. Therefore, ecotoxicological experiments were performed at laboratory scale under controlled conditions to investigate the community-level responses of river biofilms to a chloroacetanilide herbicide (alachlor) and organic solvent (methanol) exposure through the development referenced to control. Triplicate rotating annular bioreactors, inoculated with river water, were used to cultivate river biofilms under the influence of 1 and 10 μg L(-1) of alachlor and 25 mg L(-1) of methanol. For this purpose, functional (thymidine incorporation and carbon utilization spectra) and structural responses of microbial communities were assessed after 5 weeks of development. Structural aspects included biomass (chlorophyll a, confocal laser scanning microscopy) and composition (fluor-conjugated lectin binding, molecular fingerprinting, and diatom species composition). The addition of alachlor resulted in a significant reduction of bacterial biomass at 1 μg L(-1), whereas at 10 μg L(-1), it induced a significant reduction of exopolymer lectin binding, algal, bacterial, and cyanobacterial biomass. However, there were no changes in biofilm thickness or thymidine incorporation. No significant difference between the bacterial community structures of control and alachlor-treated biofilms was revealed by terminal restriction fragment length polymorphism (T-RFLP) analyses. However, the methanol-treated bacterial communities appeared different from control and alachlor-treated communities. Moreover, methanol treatment resulted in an increase of bacterial biomass and thymidine incorporation as well. Changes in dominant lectin binding suggested changes in the exopolymeric substances and community composition. Chlorophyll a and cyanobacterial biomass were also altered by methanol. This study suggested

  2. SELECTIVITY OF DIFFERENT HERBICIDES TO COWPEA

    Directory of Open Access Journals (Sweden)

    Francisco Aires Sizenando Filho2

    2013-12-01

    1.5 = recommended rate + half the recommended rate. At the end of the experiment it was found that: the cowpea showed phytotoxicity to use herbicide among 14 and 21 AAD; the herbicides diuron and metolachlor showed a rate "middle" in control weed, while the pendimethalin wasn't efficient for those function.

  3. Responses of Hyalella azteca and phytoplankton to a simulated agricultural runoff event in a managed backwater wetland

    Science.gov (United States)

    We assessed the aqueous toxicity mitigation capacity of a hydrologically managed floodplain wetland following a synthetic runoff event amended with a mixture of sediments, nutrients (nitrogen and phosphorus), and pesticides (atrazine, S-metolachlor, and permethrin) using 48-h Hyalella azteca surviva...

  4. Responses of phytoplankton and Hyalella azteca to agrichemical mixtures in a constructed wetland mesocosms

    Science.gov (United States)

    We assessed the capability of a constructed wetland to mitigate toxicity of a variety of possible mixtures such as nutrients only (N, P), pesticides only (atrazine, S-metolachlor, permethrin), and nutrients+pesticides on phytoplankton chlorophyll a, 48 h aqueous Hyalella azteca survival, and 10 d se...

  5. Water Quality Conditions Monitored at the Corps’ Garrison Project in North Dakota during the 3-Year Period 2003 through 2005

    Science.gov (United States)

    2006-07-01

    Isopropalin, Metolachlor, Metribuzin, Molinate, Oxadiazon, Oxyfluorfen , Pebulate, Pendimethalin, Profluralin, Prometon, Propachlor, Propazine, Simazine...butylate, chlorpyrifos, cyanazine, cycloate, EPTC, hexazinone, isopropalin, metribuzin, molinate, oxadiazon, oxyfluorfen , pebulate, pendimethalin...butylate, chlorpyrifos, cyanazine, cycloate, EPTC, hexazinone, isopropalin, metribuzin, molinate, oxadiazon, oxyfluorfen , pebulate, pendimethalin

  6. Water Quality Conditions at Tributary Projects in the Omaha District

    Science.gov (United States)

    2012-02-01

    Oxyfluorfen 1 0.86 0.86 0.86 0.86 ----- ----- ----- n.d. = Not detected. (A) Nondetect values set to 0 to calculate mean. If 20% or more...chlorpyrifos, cyanazine, cycloate, EPTC, hexazinone, isopropalin, metribuzin, metolachlor, molinate, oxadiazon, oxyfluorfen , pebulate, pendimethalin...metribuzin, molinate, oxadiazon, oxyfluorfen , pebulate, pendimethalin, profluralin, prometon, propachlor, propazine, simazine, trifluralin, and vernolate

  7. Pesticide mitigation capacities of constructed wetlands

    Science.gov (United States)

    Matthew T. Moore; Charles M. Cooper; Sammie Smith; John H. Rodgers

    2000-01-01

    This research focused on using constructed wetlands along field perimeters to buffer receiving water against potential effects of pesticides associated with storm runoff. The current study incorporated wetland mesocosm sampling following simulated runoff events using chlorpyrifos, atrazine, and metolachlor. Through this data collection and simple model analysis,...

  8. Ecole d'été de probabilités de Saint-Flour XLV

    CERN Document Server

    van de Geer, Sara

    2016-01-01

    Taking the Lasso method as its starting point, this book describes the main ingredients needed to study general loss functions and sparsity-inducing regularizers. It also provides a semi-parametric approach to establishing confidence intervals and tests. Sparsity-inducing methods have proven to be very useful in the analysis of high-dimensional data. Examples include the Lasso and group Lasso methods, and the least squares method with other norm-penalties, such as the nuclear norm. The illustrations provided include generalized linear models, density estimation, matrix completion and sparse principal components. Each chapter ends with a problem section. The book can be used as a textbook for a graduate or PhD course.

  9. Integrative Modeling and Inference in High Dimensional Genomic and Metabolic Data

    DEFF Research Database (Denmark)

    Brink-Jensen, Kasper

    in Manuscript I preserves the attributes of the compounds found in LC–MS samples while identifying genes highly associated with these. The main obstacles that must be overcome with this approach are dimension reduction and variable selection, here done with PARAFAC and LASSO respectively. One important drawback...... of the LASSO has been the lack of inference, the variables selected could potentially just be the most important from a set of non–important variables. Manuscript II addresses this problem with a permutation based significance test for the variables chosen by the LASSO. Once a set of relevant variables has......, particularly it scales to many lists and it provides an intuitive interpretation of the measure....

  10. Improved Sparse Channel Estimation for Cooperative Communication Systems

    Directory of Open Access Journals (Sweden)

    Guan Gui

    2012-01-01

    Full Text Available Accurate channel state information (CSI is necessary at receiver for coherent detection in amplify-and-forward (AF cooperative communication systems. To estimate the channel, traditional methods, that is, least squares (LS and least absolute shrinkage and selection operator (LASSO, are based on assumptions of either dense channel or global sparse channel. However, LS-based linear method neglects the inherent sparse structure information while LASSO-based sparse channel method cannot take full advantage of the prior information. Based on the partial sparse assumption of the cooperative channel model, we propose an improved channel estimation method with partial sparse constraint. At first, by using sparse decomposition theory, channel estimation is formulated as a compressive sensing problem. Secondly, the cooperative channel is reconstructed by LASSO with partial sparse constraint. Finally, numerical simulations are carried out to confirm the superiority of proposed methods over global sparse channel estimation methods.

  11. A Permutation Approach for Selecting the Penalty Parameter in Penalized Model Selection

    Science.gov (United States)

    Sabourin, Jeremy A; Valdar, William; Nobel, Andrew B

    2015-01-01

    Summary We describe a simple, computationally effcient, permutation-based procedure for selecting the penalty parameter in LASSO penalized regression. The procedure, permutation selection, is intended for applications where variable selection is the primary focus, and can be applied in a variety of structural settings, including that of generalized linear models. We briefly discuss connections between permutation selection and existing theory for the LASSO. In addition, we present a simulation study and an analysis of real biomedical data sets in which permutation selection is compared with selection based on the following: cross-validation (CV), the Bayesian information criterion (BIC), Scaled Sparse Linear Regression, and a selection method based on recently developed testing procedures for the LASSO. PMID:26243050

  12. Influence of surfactants on the sorption of two chloroacetanilide in an Romanian chernozem soil.

    Science.gov (United States)

    Coroi, I G; De Wilde, T; Cara, M S; Jitareanu, G; Steurbaut, W

    2011-01-01

    Pesticides have been extensively used in modern agriculture. Due to the prevalent use, there have been serious problems generated by pesticides wastes which could eventually endanger water resources and human health. The development of technologies for the decontamination of soils and waters polluted by hydrophobic organic compounds has encouraged research into the use of non-ionic surfactants as potential agents for the enhanced solubilization and removal of contaminants from soils and sediments. Sorption of two chloroacetanilide herbicides, acetochlor and metolachlor was studied on a representative chernozem soil of the Main Agricultural Research Station Ezareni belonging to the "Ion Ionescu de la Brad" University of Agriculture and Veterinary Medicine lasi, Romania, in the presence and absence of surfactants. Three different non-ionic surfactants were selected: Tween-20, Synperonic 91/5 and Silwet L-77, to verify the influence of their presence on herbicide sorption at different concentrations. Our results showed that the sorption of the studied herbicides within the soil-water-non-ionic surfactant system was influenced by the presence of non-ionic surfactants. The n values obtained were lower than 1 for all pesticide-surfactant combinations, which indicates that the amount of acetochor and metolachlor sorbed decreased with an increase in pesticide concentration. The sorption of acetochlor increased in the following order: Acetochlor+Synperonic 91/5 < Acetochlor < Acetochlor+Tween-20 < Acetochlor+Silwet L-77. In the case of metolachlor+Synperonic and metolachlor+Silwet L-77, the Kf values were significantly higher than the Kf value of metolachlor+Tween-20 on soil, where a lower Kf value could be observed with however a higher n value which indicate a higher sorption capacity at higher concentrations.

  13. Coupling Fenton and biological oxidation for the removal of nitrochlorinated herbicides from water.

    Science.gov (United States)

    Sanchis, S; Polo, A M; Tobajas, M; Rodriguez, J J; Mohedano, A F

    2014-02-01

    The combination of Fenton and biological oxidation for the removal of the nitrochlorinated herbicides alachlor, atrazine and diuron in aqueous solution has been studied. The H2O2 dose was varied from 20 to 100% of the stoichiometric amount related to the initial chemical oxygen demand (COD). The effluents from Fenton oxidation were analyzed for ecotoxicity, biodegradability, total organic carbon (TOC), COD and intermediate byproducts. The chemical step resulted in a significant improvement of the biodegradability in spite of its negligible or even slightly negative effect on the ecotoxicity. Working at 60% of the stoichiometric H2O2 dose allowed obtaining highly biodegradable effluents in the cases of alachlor and atrazine. That dose was even lower (40% of the stoichiometric) for diuron. The subsequent biological treatment was carried out in a sequencing batch reactor (SBR) and the combined Fenton-biological treatment allowed up to around 80% of COD reduction. Copyright © 2013 Elsevier Ltd. All rights reserved.

  14. Toxicidade aguda de herbicidas a tilápia (Oreochromis niloticus Acute toxicity to herbicides to Oreochromis niloticus

    Directory of Open Access Journals (Sweden)

    R.G. Botelho

    2009-01-01

    Full Text Available Esta pesquisa teve como objetivo avaliar a sensibilidade de alevinos de Oreochromis niloticus a diversos herbicidas. Para isso, foram realizados dois ensaios, sendo, no primeiro, avaliadas concentrações de atrazina (0; 2,5; 5; 10; e 20 mg L-1, visando a determinação da concentração letal a 50% dos indivíduos (CL50, e, no segundo, a sensibilidade às mesclas dos herbicidas alachlor + atrazina (5,33 + 5,33 mg L-1, diuron + MSMA (5,33 + 2,13 mg L-1, paraquat (1,33 mg L-1 e 2,4-D + picloram (1,28 + 0,34 mg L-1, com contagem de mortes 96 horas após exposição aos produtos. No primeiro ensaio foi observado elevado declínio na sobrevivência dos alevinos a partir de 3 mg L-1 do herbicida atrazina, com CL50 estimada de 5,02 mg L-1. No segundo, a mistura alachlor + atrazina promoveu o maior efeito de mortalidade sobre os alevinos de tilápia. Com 72 horas de exposição, a escala de intoxicação evidenciou redução nos números de indivíduos de, aproximadamente, 17,4% para os produtos paraquat, 2,4-D + picloram e diuron + MSMA e de 100% para alachlor + atrazina. Os dados permitem concluir que a CL50 obtida para o atrazina é inferior àquela mencionada como tóxica para truta e que a mistura alachlor + atrazina pode ser caracterizada como de risco para O. niloticus, mesmo quando aplicada em doses normais de uso.Two assays were carried out to evaluate Oreochromis niloticus sensitivity to different herbicides. In the first experiment, atrazin concentrations (0; 2.5; 5; 10 and 20 mg L-1 were evaluated aiming to determine lethal concentration (LC50 to O. niloticus. In the second assay, the effects of the herbicide mixtures alachlor + atrazin (5.33 + 5.33 mg L-1, diuron + MSMA (5.33 + 2.13 mg L-1 , paraquat (1.33 mg L-1 and 2,4-D + picloran (1.28 + 0.34 mg L-1 , were evaluated on O. niloticus survival after 96 h of exposure. In the first assay, a sharp decrease in fingerlings survival was observed from 3 mg L-1 of atrazin with CL50 value of 5

  15. Detection of Pesticides and Pesticide Metabolites Using the Cross Reactivity of Enzyme Immunoassays

    Science.gov (United States)

    Thurman, E.M.; Aga, D.S.

    2001-01-01

    Enzyme immunoassay is an important environmental analysis method that may be used to identify many pesticide analytes in water samples. Because of similarities in chemical structure between various members of a pesticide class, there often may be an unwanted response that is characterized by a percentage of cross reactivity. Also, there may be cross reactivity caused by degradation products of the target analyte that may be present in the sample. In this paper, the concept of cross reactivity caused by degradation products or by nontarget analytes is explored as a tool for identification of metabolites or structurally similar compounds not previously known to be present in water samples. Two examples are examined in this paper from various water quality studies. They are alachlor and its metabolite, alachlor ethane sulfonic acid, and atrazine and its class members, prometryn and propazine. A method for using cross reactivity for the detection of these compounds is explained in this paper.

  16. Determinação de herbicidas usados no cultivo de arroz irrigado na região sul do estado de Santa Catarina através da SPME-GC-ECD Determination of herbicides used in irrigated rice cultivation in the south of Santa Catarina using SPME-GC-ECD

    Directory of Open Access Journals (Sweden)

    Léa L. F. Costa

    2008-01-01

    Full Text Available Evaluation of the pollution by the herbicides alachlor, propanil and atrazine in water samples from four rivers in the cities of Turvo and Meleiro, south of Santa Catarina State, was made using the SPME-GC-ECD method. The proposed method was optimized and validated. The correlation coefficients were higher than 0.997 and linear ranges of the analytical curves were 0.1-4; 0.1-2.5 and 0.1-5 µg L-1 for atrazine, alachlor and propanil, respectively. The herbicides were quantified by GC-ECD and identified by GC-MS. Both of the selected rivers presented contamination by at least one of the studied herbicides.

  17. A flexible framework for sparse simultaneous component based data integration

    Directory of Open Access Journals (Sweden)

    Van Deun Katrijn

    2011-11-01

    Full Text Available Abstract 1 Background High throughput data are complex and methods that reveal structure underlying the data are most useful. Principal component analysis, frequently implemented as a singular value decomposition, is a popular technique in this respect. Nowadays often the challenge is to reveal structure in several sources of information (e.g., transcriptomics, proteomics that are available for the same biological entities under study. Simultaneous component methods are most promising in this respect. However, the interpretation of the principal and simultaneous components is often daunting because contributions of each of the biomolecules (transcripts, proteins have to be taken into account. 2 Results We propose a sparse simultaneous component method that makes many of the parameters redundant by shrinking them to zero. It includes principal component analysis, sparse principal component analysis, and ordinary simultaneous component analysis as special cases. Several penalties can be tuned that account in different ways for the block structure present in the integrated data. This yields known sparse approaches as the lasso, the ridge penalty, the elastic net, the group lasso, sparse group lasso, and elitist lasso. In addition, the algorithmic results can be easily transposed to the context of regression. Metabolomics data obtained with two measurement platforms for the same set of Escherichia coli samples are used to illustrate the proposed methodology and the properties of different penalties with respect to sparseness across and within data blocks. 3 Conclusion Sparse simultaneous component analysis is a useful method for data integration: First, simultaneous analyses of multiple blocks offer advantages over sequential and separate analyses and second, interpretation of the results is highly facilitated by their sparseness. The approach offered is flexible and allows to take the block structure in different ways into account. As such

  18. A flexible framework for sparse simultaneous component based data integration.

    Science.gov (United States)

    Van Deun, Katrijn; Wilderjans, Tom F; van den Berg, Robert A; Antoniadis, Anestis; Van Mechelen, Iven

    2011-11-15

    High throughput data are complex and methods that reveal structure underlying the data are most useful. Principal component analysis, frequently implemented as a singular value decomposition, is a popular technique in this respect. Nowadays often the challenge is to reveal structure in several sources of information (e.g., transcriptomics, proteomics) that are available for the same biological entities under study. Simultaneous component methods are most promising in this respect. However, the interpretation of the principal and simultaneous components is often daunting because contributions of each of the biomolecules (transcripts, proteins) have to be taken into account. We propose a sparse simultaneous component method that makes many of the parameters redundant by shrinking them to zero. It includes principal component analysis, sparse principal component analysis, and ordinary simultaneous component analysis as special cases. Several penalties can be tuned that account in different ways for the block structure present in the integrated data. This yields known sparse approaches as the lasso, the ridge penalty, the elastic net, the group lasso, sparse group lasso, and elitist lasso. In addition, the algorithmic results can be easily transposed to the context of regression. Metabolomics data obtained with two measurement platforms for the same set of Escherichia coli samples are used to illustrate the proposed methodology and the properties of different penalties with respect to sparseness across and within data blocks. Sparse simultaneous component analysis is a useful method for data integration: First, simultaneous analyses of multiple blocks offer advantages over sequential and separate analyses and second, interpretation of the results is highly facilitated by their sparseness. The approach offered is flexible and allows to take the block structure in different ways into account. As such, structures can be found that are exclusively tied to one data platform

  19. Biomonitoring of Environmental Status and Trends (BEST) Program: Selected Methods for Monitoring Chemical Contaminants and their Effects in Aquatic Ecosystems

    Science.gov (United States)

    2000-02-01

    1995. New nephron devel- opment in fish from polluted waters: a possi- ble biomarker. Ecotoxicology 4:157-68. Couch JA. 1985. Prospective study of...Carlson AR. 1998. Comparative sensitivity of five species of macrophytes and six species of algae to atrazine, metribuzin, alachlor, and meto...Stevenson JC, Jones TW, Means JC. 1985. Effects of atrazine and linuron on photosynthesis and growth of the macrophytes Potamogeton per- foliatus L

  20. CRAN - Package msgl (Version:2.0.125.0)

    DEFF Research Database (Denmark)

    2014-01-01

    Sparse group lasso multiclass classification, suitable for high dimensional problems with many classes. Fast algorithm for solving the multinomial sparse group lasso convex optimization problem. This package apply template metaprogramming techniques, therefore – when compiling the package from so...... source – a high level of optimization is needed to gain full speed (e.g. for the GCC compiler use -O3). Use of multiple processors for cross validation and subsampling is supported through OpenMP. The Armadillo C++ library is used as the primary linear algebra engine....

  1. Adaptive L1/2 Shooting Regularization Method for Survival Analysis Using Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Xiao-Ying Liu

    2013-01-01

    Full Text Available A new adaptive L1/2 shooting regularization method for variable selection based on the Cox’s proportional hazards mode being proposed. This adaptive L1/2 shooting algorithm can be easily obtained by the optimization of a reweighed iterative series of L1 penalties and a shooting strategy of L1/2 penalty. Simulation results based on high dimensional artificial data show that the adaptive L1/2 shooting regularization method can be more accurate for variable selection than Lasso and adaptive Lasso methods. The results from real gene expression dataset (DLBCL also indicate that the L1/2 regularization method performs competitively.

  2. High-dimensional model estimation and model selection

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    I will review concepts and algorithms from high-dimensional statistics for linear model estimation and model selection. I will particularly focus on the so-called p>>n setting where the number of variables p is much larger than the number of samples n. I will focus mostly on regularized statistical estimators that produce sparse models. Important examples include the LASSO and its matrix extension, the Graphical LASSO, and more recent non-convex methods such as the TREX. I will show the applicability of these estimators in a diverse range of scientific applications, such as sparse interaction graph recovery and high-dimensional classification and regression problems in genomics.

  3. New insights into the interactions between cork chemical components and pesticides. The contribution of π-π interactions, hydrogen bonding and hydrophobic effect.

    Science.gov (United States)

    Olivella, M À; Bazzicalupi, C; Bianchi, A; Fiol, N; Villaescusa, I

    2015-01-01

    The role of chemical components of cork in the sorption of several pesticides has been investigated. For this purpose raw cork and three cork extracted fractions (i.e. cork free of aliphatic extractives, cork free of all extractives and cork free of all extractives and suberin) were used as sorbent of three ionic pesticides (propazine, 2,4-dichlorophenoxy acetic acid (2,4-D) and alachlor) and five non-ionic pesticides (chlorpyrifos, isoproturon, metamitron, methomyl and oxamyl) with a logKow within the range -0.47 to 4.92. The effect of cations on the ionic pesticides, propazine and 2,4-D sorption was also analyzed. Results indicated that the highest yields were obtained for chlorpyrifos and alachlor sorption onto raw cork (>55%). After removal of aliphatic extractives sorption of all pesticides increased that ranged from 3% for propazine to 31% for alachlor. In contrast, removal of phenolic extractives caused a sorption decrease. Low sorption yields were obtained for hydrophobic pesticides such as metamitron, oxamyl and methomyl (cork fractions and extremely low when using raw cork (cork toward aromatic pesticides. Results presented in this paper gain insights into the cork affinities for pesticides and the interactions involved in the sorption process and also enables to envisage sorption affinity of cork for other organic pollutants. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. Calibration with Absolute Shrinkage

    DEFF Research Database (Denmark)

    Øjelund, Henrik; Madsen, Henrik; Thyregod, Poul

    2001-01-01

    In this paper, penalized regression using the L-1 norm on the estimated parameters is proposed for chemometric je calibration. The algorithm is of the lasso type, introduced by Tibshirani in 1996 as a linear regression method with bound on the absolute length of the parameters, but a modification...

  5. Texas hospitals riding tall. While hospitals post robust profit margins, HMOs are saddled with mounting losses.

    Science.gov (United States)

    Saphir, A

    1999-02-08

    In Texas, they do things differently, and they do things big. Hospitals in the Lone Star State have been banding together more often and more effectively than elsewhere. Swinging their lassos, they are riding herd on HMOs, enjoying record profits and making ever-larger deals.

  6. Superhero science: from fiction to fact

    Science.gov (United States)

    Follows, Michael

    2017-11-01

    At the 2016 Manchester Science Festival, a team of like-minded scientists came together to try to suss out the real-world science behind everything from Wonder Woman's lasso to the Hulk's gigantic transformation. The result is The Secret Science of Superheroes- an eclectic collection of essays.

  7. Sparse Reduced-Rank Regression for Simultaneous Dimension Reduction and Variable Selection

    KAUST Repository

    Chen, Lisha; Huang, Jianhua Z.

    2012-01-01

    and hence improves predictive accuracy. We propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty. We apply a group-lasso type penalty that treats each row of the matrix of the regression coefficients as a group

  8. Modeling and Forecasting Large Realized Covariance Matrices and Portfolio Choice

    NARCIS (Netherlands)

    Callot, Laurent A.F.; Kock, Anders B.; Medeiros, Marcelo C.

    2017-01-01

    We consider modeling and forecasting large realized covariance matrices by penalized vector autoregressive models. We consider Lasso-type estimators to reduce the dimensionality and provide strong theoretical guarantees on the forecast capability of our procedure. We show that we can forecast

  9. Selecting Sensitive Parameter Subsets in Dynamical Models With Application to Biomechanical System Identification.

    Science.gov (United States)

    Ramadan, Ahmed; Boss, Connor; Choi, Jongeun; Peter Reeves, N; Cholewicki, Jacek; Popovich, John M; Radcliffe, Clark J

    2018-07-01

    Estimating many parameters of biomechanical systems with limited data may achieve good fit but may also increase 95% confidence intervals in parameter estimates. This results in poor identifiability in the estimation problem. Therefore, we propose a novel method to select sensitive biomechanical model parameters that should be estimated, while fixing the remaining parameters to values obtained from preliminary estimation. Our method relies on identifying the parameters to which the measurement output is most sensitive. The proposed method is based on the Fisher information matrix (FIM). It was compared against the nonlinear least absolute shrinkage and selection operator (LASSO) method to guide modelers on the pros and cons of our FIM method. We present an application identifying a biomechanical parametric model of a head position-tracking task for ten human subjects. Using measured data, our method (1) reduced model complexity by only requiring five out of twelve parameters to be estimated, (2) significantly reduced parameter 95% confidence intervals by up to 89% of the original confidence interval, (3) maintained goodness of fit measured by variance accounted for (VAF) at 82%, (4) reduced computation time, where our FIM method was 164 times faster than the LASSO method, and (5) selected similar sensitive parameters to the LASSO method, where three out of five selected sensitive parameters were shared by FIM and LASSO methods.

  10. Shaping 3-D Volumes in Immersive Virtual Environments

    DEFF Research Database (Denmark)

    Stenholt, Rasmus

    of the user’s work in such tasks. This tech- nique is compared to two other techniques, a spherical brush and a box-shaped lasso, in an evaluation which seeks to identify the pros and cons of the tools. The magic wand proves to be faster to use than the other, but only in certain geomet- ric scenarios...

  11. 2625-IJBCS-Article-Adjima Ouoba

    African Journals Online (AJOL)

    hp

    favorite variety is the cream-colored white hilum for its organoleptic, agronomic and aesthetic qualities. Lack of awareness ... réduire l'impact de ces contraintes. ..... de. BoboDiou- lasso, Burkina Faso, 73p. Deressa TT, Hassan RM, Ringler C, Alemu T,. Yusuf M. 2009. Determinants of farmers' choice of adaptation methods.

  12. Bernstein approximations in glasso-based estimation of biological networks

    NARCIS (Netherlands)

    Purutcuoglu, Vilda; Agraz, Melih; Wit, Ernst

    The Gaussian graphical model (GGM) is one of the common dynamic modelling approaches in the construction of gene networks. In inference of this modelling the interaction between genes can be detected mainly via graphical lasso (glasso) or coordinate descent-based approaches. Although these methods

  13. LASSO—ligand activity by surface similarity order: a new tool for ligand based virtual screening

    Science.gov (United States)

    Reid, Darryl; Sadjad, Bashir S.; Zsoldos, Zsolt; Simon, Aniko

    2008-06-01

    Virtual Ligand Screening (VLS) has become an integral part of the drug discovery process for many pharmaceutical companies. Ligand similarity searches provide a very powerful method of screening large databases of ligands to identify possible hits. If these hits belong to new chemotypes the method is deemed even more successful. eHiTS LASSO uses a new interacting surface point types (ISPT) molecular descriptor that is generated from the 3D structure of the ligand, but unlike most 3D descriptors it is conformation independent. Combined with a neural network machine learning technique, LASSO screens molecular databases at an ultra fast speed of 1 million structures in under 1 min on a standard PC. The results obtained from eHiTS LASSO trained on relatively small training sets of just 2, 4 or 8 actives are presented using the diverse directory of useful decoys (DUD) dataset. It is shown that over a wide range of receptor families, eHiTS LASSO is consistently able to enrich screened databases and provides scaffold hopping ability.

  14. Griffe cubitale d'origine lépreuse traitée par transfert tendineux de ...

    African Journals Online (AJOL)

    Griffe cubitale d'origine lépreuse traitée par transfert tendineux de Lasso Zancolli: à propos d'un cas. Adil El Alaoui, Mouhcine Sbiyaa, Aliou Bah, Ilyas Rabhi, Amine Mezzani, Amine Marzouki, Fawzi Boutayeb ...

  15. Identifying Associations Between Brain Imaging Phenotypes and Genetic Factors via A Novel Structured SCCA Approach.

    Science.gov (United States)

    Du, Lei; Zhang, Tuo; Liu, Kefei; Yan, Jingwen; Yao, Xiaohui; Risacher, Shannon L; Saykin, Andrew J; Han, Junwei; Guo, Lei; Shen, Li

    2017-06-01

    Brain imaging genetics attracts more and more attention since it can reveal associations between genetic factors and the structures or functions of human brain. Sparse canonical correlation analysis (SCCA) is a powerful bi-multivariate association identification technique in imaging genetics. There have been many SCCA methods which could capture different types of structured imaging genetic relationships. These methods either use the group lasso to recover the group structure, or employ the graph/network guided fused lasso to find out the network structure. However, the group lasso methods have limitation in generalization because of the incomplete or unavailable prior knowledge in real world. The graph/network guided methods are sensitive to the sign of the sample correlation which may be incorrectly estimated. We introduce a new SCCA model using a novel graph guided pairwise group lasso penalty, and propose an efficient optimization algorithm. The proposed method has a strong upper bound for the grouping effect for both positively and negatively correlated variables. We show that our method performs better than or equally to two state-of-the-art SCCA methods on both synthetic and real neuroimaging genetics data. In particular, our method identifies stronger canonical correlations and captures better canonical loading profiles, showing its promise for revealing biologically meaningful imaging genetic associations.

  16. Probabilistic Signal Recovery and Random Matrices

    Science.gov (United States)

    2016-12-08

    that classical methods for linear regression (such as Lasso) are applicable for non- linear data. This surprising finding has already found several...we studied the complexity of convex sets. In numerical linear algebra , we analyzed the fastest known randomized approximation algorithm for...and perfect matchings In numerical linear algebra , we studied the fastest known randomized approximation algorithm for computing the permanents of

  17. Inference in High-dimensional Dynamic Panel Data Models

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl; Tang, Haihan

    We establish oracle inequalities for a version of the Lasso in high-dimensional fixed effects dynamic panel data models. The inequalities are valid for the coefficients of the dynamic and exogenous regressors. Separate oracle inequalities are derived for the fixed effects. Next, we show how one can...

  18. Michigan has a sleeping giant

    CERN Multimedia

    Brock, Raymond; Nichols, Sue

    2007-01-01

    "That giant is 750 miles of fiber optic cable that lassoes its three biggest research universities and Van Andel Institute to the future. Its mission: to uncover the nature of the Big Bang by connecton U.S. physicists to their huge experiment ATLAS in Geneva.." (4 pages)

  19. Tracing the breeding farm of domesticated pig using feature selection (

    Directory of Open Access Journals (Sweden)

    Taehyung Kwon

    2017-11-01

    Full Text Available Objective Increasing food safety demands in the animal product market have created a need for a system to trace the food distribution process, from the manufacturer to the retailer, and genetic traceability is an effective method to trace the origin of animal products. In this study, we successfully achieved the farm tracing of 6,018 multi-breed pigs, using single nucleotide polymorphism (SNP markers strictly selected through least absolute shrinkage and selection operator (LASSO feature selection. Methods We performed farm tracing of domesticated pig (Sus scrofa from SNP markers and selected the most relevant features for accurate prediction. Considering multi-breed composition of our data, we performed feature selection using LASSO penalization on 4,002 SNPs that are shared between breeds, which also includes 179 SNPs with small between-breed difference. The 100 highest-scored features were extracted from iterative simulations and then evaluated using machine-leaning based classifiers. Results We selected 1,341 SNPs from over 45,000 SNPs through iterative LASSO feature selection, to minimize between-breed differences. We subsequently selected 100 highest-scored SNPs from iterative scoring, and observed high statistical measures in classification of breeding farms by cross-validation only using these SNPs. Conclusion The study represents a successful application of LASSO feature selection on multi-breed pig SNP data to trace the farm information, which provides a valuable method and possibility for further researches on genetic traceability.

  20. The impact of pre-selected variance inflation factor thresholds on the ...

    African Journals Online (AJOL)

    It is basically an index that measures how much the variance of an estimated ... the literature were not considered, such as penalised regularisation methods like the Lasso ... Y = 1 if a customer has defaulted, otherwise Y = 0). ..... method- ology is applied, but different VIF-thresholds have to be satisfied during the collinearity.

  1. Evaluation of the Achieve Mapping Catheter in cryoablation for atrial fibrillation: a prospective randomized trial.

    Science.gov (United States)

    Gang, Yi; Gonna, Hanney; Domenichini, Giulia; Sampson, Michael; Aryan, Niloufar; Norman, Mark; Behr, Elijah R; Zuberi, Zia; Dhillon, Paramdeep; Gallagher, Mark M

    2016-03-01

    The purpose of this study is to establish the role of Achieve Mapping Catheter in cryoablation for paroxysmal atrial fibrillation (PAF) in a randomized trial. A total of 102 patients undergoing their first ablation for PAF were randomized at 2:1 to an Achieve- or Lasso-guided procedure. Study patients were systematically followed up for 12 months with Holter monitoring. Primary study endpoint was acute procedure success. Secondary endpoint was clinical outcomes assessed by AF free at 6 and 12 months after the procedure. Of 102 participants, 99 % of acute procedure success was achieved. Significantly shorter procedure duration with the Achieve-guided group than with the Lasso-guided group (118 ± 18 vs. 129 ± 21 min, p < 0.05) was observed as was the duration of fluoroscopy (17 ± 5 vs. 20 ± 7 min, p < 0.05) by subgroup analysis focused on procedures performed by experienced operators. In the whole study patients, procedure and fluoroscopic durations were similar in the Achieve- (n = 68) and Lasso-guided groups (n = 34). Transient phrenic nerve weakening was equally prevalent with the Achieve and Lasso. No association was found between clinical outcomes and the mapping catheter used. The use of second-generation cryoballoon (n = 68) reduced procedure time significantly compared to the first-generation balloon (n = 34); more patients were free of AF in the former than the latter group during follow-up. The use of the Achieve Mapping Catheter can reduce procedure and fluoroscopic durations compared with Lasso catheters in cryoablation for PAF after operators gained sufficient experience. The type of mapping catheter used does not affect procedure efficiency and safety by models of cryoballoon.

  2. Pulmonary vein isolation using the Rhythmia mapping system: Verification of intracardiac signals using the Orion mini-basket catheter.

    Science.gov (United States)

    Anter, Elad; Tschabrunn, Cory M; Contreras-Valdes, Fernando M; Li, Jianqing; Josephson, Mark E

    2015-09-01

    During pulmonary vein isolation (PVI), a circular lasso catheter is positioned at the junction between the left atrium (LA) and the pulmonary vein (PV) to confirm PVI. The Rhythmia mapping system uses the Orion mini-basket catheter with 64 electrodes instead of the lasso catheter. However, its feasibility to determine PVI has not been studied. The purpose of this study was to compare signals between the mini-basket and lasso catheters at the LA-PV junction. In 12 patients undergoing PVI using Rhythmia, the mini-basket and lasso catheters were placed simultaneously at the LA-PV junction for baseline and post-PVI signal assessment. Pacing from both catheters was performed to examine the presence of exit block. At baseline, recordings of LA and PV potentials were concordant in all PVs. However, after PVI, concordance between the catheters was only 68%. Discordance in all cases resulted from loss of PV potentials on the lasso catheter with persistence of PV potentials on the mini-basket catheter. In 9 of 13 PVs (69%), these potentials represented true PV potentials that were exclusively recorded with the smaller and closely spaced mini-basket electrodes. In the other 4 PVs (31%), these potentials originated from neighboring structures and resulted in underestimation of PVI. The use of the mini-basket catheter alone is sufficient to determine PVI. While it improves recording of PV potentials after incomplete ablation, it is also associated with frequent recording of "PV-like" potentials originating from neighboring structures. In these cases, pacing maneuvers are helpful to determine PVI and avoid excessive ablation. Copyright © 2015 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

  3. Multi-omics facilitated variable selection in Cox-regression model for cancer prognosis prediction.

    Science.gov (United States)

    Liu, Cong; Wang, Xujun; Genchev, Georgi Z; Lu, Hui

    2017-07-15

    New developments in high-throughput genomic technologies have enabled the measurement of diverse types of omics biomarkers in a cost-efficient and clinically-feasible manner. Developing computational methods and tools for analysis and translation of such genomic data into clinically-relevant information is an ongoing and active area of investigation. For example, several studies have utilized an unsupervised learning framework to cluster patients by integrating omics data. Despite such recent advances, predicting cancer prognosis using integrated omics biomarkers remains a challenge. There is also a shortage of computational tools for predicting cancer prognosis by using supervised learning methods. The current standard approach is to fit a Cox regression model by concatenating the different types of omics data in a linear manner, while penalty could be added for feature selection. A more powerful approach, however, would be to incorporate data by considering relationships among omics datatypes. Here we developed two methods: a SKI-Cox method and a wLASSO-Cox method to incorporate the association among different types of omics data. Both methods fit the Cox proportional hazards model and predict a risk score based on mRNA expression profiles. SKI-Cox borrows the information generated by these additional types of omics data to guide variable selection, while wLASSO-Cox incorporates this information as a penalty factor during model fitting. We show that SKI-Cox and wLASSO-Cox models select more true variables than a LASSO-Cox model in simulation studies. We assess the performance of SKI-Cox and wLASSO-Cox using TCGA glioblastoma multiforme and lung adenocarcinoma data. In each case, mRNA expression, methylation, and copy number variation data are integrated to predict the overall survival time of cancer patients. Our methods achieve better performance in predicting patients' survival in glioblastoma and lung adenocarcinoma. Copyright © 2017. Published by Elsevier

  4. Channel selection for simultaneous and proportional myoelectric prosthesis control of multiple degrees-of-freedom

    Science.gov (United States)

    Hwang, Han-Jeong; Hahne, Janne Mathias; Müller, Klaus-Robert

    2014-10-01

    Objective. Recent studies have shown the possibility of simultaneous and proportional control of electrically powered upper-limb prostheses, but there has been little investigation on optimal channel selection. The objective of this study is to find a robust channel selection method and the channel subsets most suitable for simultaneous and proportional myoelectric prosthesis control of multiple degrees-of-freedom (DoFs). Approach. Ten able-bodied subjects and one person with congenital upper-limb deficiency took part in this study, and performed wrist movements with various combinations of two DoFs (flexion/extension and radial/ulnar deviation). During the experiment, high density electromyographic (EMG) signals and the actual wrist angles were recorded with an 8 × 24 electrode array and a motion tracking system, respectively. The wrist angles were estimated from EMG features with ridge regression using the subsets of channels chosen by three different channel selection methods: (1) least absolute shrinkage and selection operator (LASSO), (2) sequential feature selection (SFS), and (3) uniform selection (UNI). Main results. SFS generally showed higher estimation accuracy than LASSO and UNI, but LASSO always outperformed SFS in terms of robustness, such as noise addition, channel shift and training data reduction. It was also confirmed that about 95% of the original performance obtained using all channels can be retained with only 12 bipolar channels individually selected by LASSO and SFS. Significance. From the analysis results, it can be concluded that LASSO is a promising channel selection method for accurate simultaneous and proportional prosthesis control. We expect that our results will provide a useful guideline to select optimal channel subsets when developing clinical myoelectric prosthesis control systems based on continuous movements with multiple DoFs.

  5. Efeito de herbicidas aplicados em solo de várzea sobre a cultura do girassol Effect of herbicides applied on sunflower crop in wetland soil

    Directory of Open Access Journals (Sweden)

    E.A.L Erasmo

    2010-12-01

    Full Text Available Objetivou-se neste trabalho avaliar em solos de várzea o efeito de herbicidas préemergentes, aplicados isoladamente e em mistura, sobre a cultura do girassol. A variedade de girassol Embrapa V122 e o híbrido triplo Agrobel 972 foram avaliados individualmente, utilizando-se o delineamento experimental de blocos casualizados, com quatro repetições. Foram realizados dois experimentos, e os tratamentos utilizados em ambos foram: oxadiazon (250 g ha-1, oxyfluorfen (240 g ha-1, S-metolachlor (1.440 g ha-1, flumetsulam (120 g ha-1, pendimethalin (1.000 g ha-1, oxyfluorfen+S-metolachlor (192+960 g ha-1, flumetsulam +S-metolachlor (72+960 g ha-1, pendimethalin+S-metolachlor (1.000 + 1.440 g ha-1, pendimethalin+flumetsulam (1.000+72 g ha-1, além de duas testemunhas, sem e com capina. Os dados de altura de planta, diâmetro do caule, diâmetro do capítulo e da produção de grãos foram submetidos aos testes estatísticos multivariados de análise de agrupamento e análise de componentes principais. Os resultados foram semelhantes em ambos os cultivares, com a formação de três grupos principais, sendo o primeiro e o segundo constituídos pelas testemunhas sem e com capina, respectivamente. O terceiro grupo foi constituído pelos herbicidas aplicados isoladamente e em mistura. Dessa forma, verificou-se que os efeitos causados pelos herbicidas aplicados isoladamente e em mistura sobre as variáveis analisadas foram menos prejudiciais em relação aos da interferência das plantas daninhas. Esses resultados evidenciaram potencial de seletividade dos herbicidas aplicados isoladamente e em mistura na variedade de girassol Embrapa V122 e no híbrido triplo Agrobel 972, nas condições em que foram avaliados.This study aimed to evaluate the effect of applying different pre-emergent herbicides, alone and in combination, on sunflower crop in wetland soil. The sunflower variety Embrapa V122 and the triple hybrid Agrobel 972 were evaluated individually

  6. Comparative assessment of herbicide and fungicide runoff risk: a case study for peanut production in the Southern Atlantic Coastal Plain (USA).

    Science.gov (United States)

    Potter, Thomas L; Bosch, David D; Strickland, Timothy C

    2014-08-15

    Peanut (Arachis hypogaea) is produced intensively in the southern Atlantic Coastal Plain of the eastern USA. To effectively protect the region's water quality data are needed which quantify runoff of pesticides used to protect these crops. Fungicides are used intensively yet there is little published data which describe their potential for loss in surface runoff. This study compared runoff of a fungicide, tebuconazole (α-[2-(4-chlorophenyl)ethyl]-α-(1,1-dimethylethyl)-1H-1,2,4-triazole-1-ethanol), and an herbicide, metolachlor (2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl)acetamide) from 0.2 ha fields in strip (ST), a commonly used conservation-tillage practice, and conventional tillage (CT) near Tifton, GA (USA). Following their first application, metolachlor and tebuconazole were detected at high frequency in runoff. Concentrations and their annual losses increased with application frequency and runoff event timing and frequency with respect to applications, and when fields were positioned at the top of the slope and CT was practiced. Runoff one day after treatment (DAT) contributed to high tebuconazole runoff loss, up to 9.8% of the amount applied on an annual basis. In all cases, metolachlor loss was more than 10 times less even though total application was 45% higher. This was linked to the fact that the one metolachlor application to each crop was in May, one of the region's driest months. In sum, studies showed that fungicide runoff rates may be relatively high and emphasize the need to focus on these products in future studies on peanut and other crops. The study also showed that peanut farmers should be encouraged to use conservation tillage practices like ST which can substantially reduce pesticide runoff. Published by Elsevier B.V.

  7. Impact of rainfall patterns and frequency on the export of pesticides and heavy-metals from agricultural soils.

    Science.gov (United States)

    Meite, Fatima; Alvarez-Zaldívar, Pablo; Crochet, Alexandre; Wiegert, Charline; Payraudeau, Sylvain; Imfeld, Gwenaël

    2018-03-01

    The combined influence of soil characteristics, pollutant aging and rainfall patterns on the export of pollutants from topsoils is poorly understood. We used laboratory experiments and parsimonious modeling to evaluate the impact of rainfall characteristics on the ponding and the leaching of a pollutant mixture from topsoils. The mixture included the fungicide metalaxyl, the herbicide S-metolachlor, as well as copper (Cu) and zinc (Zn). Four rainfall patterns, which differed in their durations and intensities, were applied twice successively with a 7days interval on each soil type. To evaluate the influence of soil type and aging, experiments included crop and vineyard soils and two stages of pollutant aging (0 and 10days). The global export of pollutants was significantly controlled by the rainfall duration and frequency (Pexport of metalaxyl (44.5±21.5% of the initial mass spiked in the soils), S-metolachlor (8.1±3.1%) and Cu (3.1±0.3%). Soil compaction caused by the first rainfall reduced in the second rainfall the leaching of remaining metalaxyl, S-metolachlor, Cu and Zn by 2.4-, 2.9-, 30- and 50-fold, respectively. In contrast, soil characteristics and aging had less influence on pollutant mass export. The soil type significantly influenced the leaching of Zn, while short-term aging impacted Cu leaching. Our results suggest that rainfall characteristics predominantly control export patterns of metalaxyl and S-metolachlor, in particular when the aging period is short. We anticipate our study to be a starting point for more systematic evaluation of the dissolved pollutant ponding/leaching partitioning and the export of pollutant mixtures from different soil types in relation to rainfall patterns. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Sistemas de control de malezas en maiz (Zea mays L.: efecto de metodos de control, densidad y distribucion del cultivo Weed control systems in corn: effects of control methods, density and plant distribution

    Directory of Open Access Journals (Sweden)

    G. Martinez

    1982-12-01

    Full Text Available Con el objetivo de integrar diferentes prácticas culturales en un sistema de control de malezas en maíz, se instaló un ensayo en el Campo Experimental de la Universidad Autónoma Chapingo (México (2250 msnm, precipitación media anual 550 mm, suelo franco, 1.7% M.O. bajo condiciones de secano, en donde se evaluaron dos densidades (44.400 y 66.600 pl/ha, dos distribuciones (normal y equidistante y siete métodos de control de malezas (cyanazine + alachlor (1,2 + 1,92 kg/ha, atrazine + alachlor (1,2 + 1,44 kg/ha, un escarda, dos escardas, testigo siempre desmalezado, testigo siempre desmalezado + dos escardas y testigo siempre enmalezado. Las principales malezas presentes fueron: quelite (Amaranthus sp., perlilla (Lopezia mexicana Jacq., rosilla chita (Galinsoga parviflora Cav., acahual (Encelia mexicana Mart., Sporobulus poiretti (Roem, et Sch. Hichc. y fresadilla (Digitaria sanguinalis (L. Scop.. El aumento de la densidad de siembra no se reflejó en el control de malezas, incidencia de enfermedades, crescimiento vegetativo y reproductivo del cultivo. La distribución equidistante aparejó un mejor control de malezas, en relación a la distribución normal, pero la incidencia de enfermedades fue mayor, lo que quizá pudo haber determinado la ausencia de diferencias en crecimiento vegetativo, un menor número de mazorcas/ha y consecuentemente la ausencia de respuesta en rendimiento de grano. De los tratamientos químicos, atrazine + alachlor tuvo un comportamiento superior a cyanazine + alachlor, en control de malezas, aunque sólo fue detectable estadisticamente en las evaluaciones. No hubo diferencia entre ambos en la incidencia de enfermedades, ni en su efecto sobre el cultivo. aunque el rendimiento de cyanazine + alachlor fue ligeramente inferior. Los métodos químicos fueron superiores a los mecánicos en control de malezas, pero no difirie -ron en la incidencia de enfermedades ni en los parámetros de desarrollo del cultivo. La

  9. Weed Control in White Bean with Various Halosulfuron Tankmixes

    Directory of Open Access Journals (Sweden)

    Nader Soltani

    2014-01-01

    Full Text Available Four field trials were conducted over a three-year period (2011–2013 in southwestern Ontario to evaluate the level of weed control provided by various halosulfuron tankmixes applied preplant incorporated (PPI in white bean. Trifluralin, s-metolachlor, halosulfuron, and imazethapyr applied alone or in combination caused 4% or less visible injury 1 and 4 weeks after emergence (WAE in white bean. Trifluralin, s-metolachlor, halosulfuron, and imazethapyr applied PPI provided 80–96%, 84–95%, 83–100%, and 75–92% control of redroot pigweed; 19–28%, 30–40%, 97–99%, and 73–84% control of common ragweed; 94–96%, 63–82%, 96–100%, and 96–100% control of common lambsquarters; 14-15%, 12–35%, 100%, and 96–97% control of wild mustard; and 96–97%, 95–97%, 53–56%, and 80–82% control of green foxtail, respectively. The two- and three-way tankmixes of halosulfuron with trifluralin, s-metolachlor, or imazethapyr provided 85–100% control of redroot pigweed, 90–98% control of common ragweed, 97–100% control of common lambsquarters, 100% control of wild mustard, and 93–98% control of green foxtail. Weed density, weed biomass and white bean seed yields reflected the level of visible weed control.

  10. A study on Sorghum bicolor (L. Moench response to split application of herbicides

    Directory of Open Access Journals (Sweden)

    Kaczmarek Sylwia

    2017-06-01

    Full Text Available Field experiments to evaluate the split application of mesotrione + s-metolachlor, mesotrione + terbuthylazine, dicamba + prosulfuron, terbuthylazine + mesotrione + s-metolachlor, and sulcotrione in the cultivation of sorghum var. Rona 1 were carried out in 2012 and 2013. The field tests were conducted at the field experimental station in Winna Góra, Poznań, Poland. Treatments with the herbicides were performed directly after sowing (PE and at leaf stage 1–2 (AE1 or at leaf stage 3–4 (AE2 of sorghum. The treatments were carried out in a laid randomized block design with 4 replications. The results showed that the tested herbicides applied at split doses were effective in weed control. After the herbicide application weed density and weed biomass were significantly reduced compared to the infested control. The best results were achieved after the application of mesotrione tank mixture with s-metolachlor and terbuthylazine. Application of split doses of herbicides was also correlated with the density, biomass, and height of sorghum.

  11. Influence of tank mixtures of pre-emergence herbicides on growing leeks (Allium porrum L.

    Directory of Open Access Journals (Sweden)

    Gerasimova Nina

    2015-01-01

    Full Text Available The effect of mixtures of pre-emergence herbicides on weed infestation and yield of leek was evaluated. Three tank mixtures were applied: s-metolachlor (Dual Gold 960 EC at a dose of 80 ml/da + oxyfluorfen (Goal 2 E at a dose of 100 ml/da; s-metolachlor (Dual Gold 960 EC at a dose of 60 ml/da + oxyfluorfen (Goal 2 E at a dose of 75 ml/da; and s-metolachlor (Dual Gold 960 EC at a dose of 40 ml/da + oxyfluorfen (Goal 2 E at a dose of 50 ml/da. The number of weeds was recorded following the application of the tank mixture. It was found that treatment with a tank mixture of herbicides Dual Gold 960 EC and Goal 2 E caused a reduction in weed infestation at all three application rates as compared to the control. The lowest weed infestation was established after treatment with the highest doses of herbicides. It was suggested that the applied herbicide mixture could be used effectively at the leeks growth stage.

  12. Gas-phase pesticide measurement using iodide ionization time-of-flight mass spectrometry

    Directory of Open Access Journals (Sweden)

    T. Murschell

    2017-06-01

    Full Text Available Volatilization and subsequent processing in the atmosphere are an important environmental pathway for the transport and chemical fate of pesticides. However, these processes remain a particularly poorly understood component of pesticide lifecycles due to analytical challenges in measuring pesticides in the atmosphere. Most pesticide measurements require long (hours to days sampling times coupled with offline analysis, inhibiting observation of meteorologically driven events or investigation of rapid oxidation chemistry. Here, we present chemical ionization time-of-flight mass spectrometry with iodide reagent ions as a fast and sensitive measurement of four current-use pesticides. These semi-volatile pesticides were calibrated with injections of solutions onto a filter and subsequently volatilized to generate gas-phase analytes. Trifluralin and atrazine are detected as iodide–molecule adducts, while permethrin and metolachlor are detected as adducts between iodide and fragments of the parent analyte molecule. Limits of detection (1 s are 0.37, 0.67, 0.56, and 1.1 µg m−3 for gas-phase trifluralin, metolachlor, atrazine, and permethrin, respectively. The sensitivities of trifluralin and metolachlor depend on relative humidity, changing as much as 70 and 59, respectively, as relative humidity of the sample air varies from 0 to 80 %. This measurement approach is thus appropriate for laboratory experiments and potentially near-source field measurements.

  13. Avaliação de tratamentos químicos e mecânicos no controle de plantas daninhas na cultura do algodão Mechanical and chemical treatments in the weed controls in the cotton crop

    Directory of Open Access Journals (Sweden)

    Luiz L. Foloni

    1999-04-01

    Full Text Available O presente trabalho teve como objetivo avaliar a eficiência de diferentes combinações de tratamentos herbicidas integrado, aplicados em PPI, pré, pós, cultivo mecânico e jato dirigido em cultura de algodão (Gossypium hirsutum L.. O experimento foi conduzido em campo, sendo a área experimental instalada na cultura de algodão cultivar IAC-20. Foram testados tratamentos com os seguintes produtos: trifluralina na dose de 1,068 kg i.a./ha; alachlor na dose de 1,584 kg i.a./ha; M.S.M.A. nas doses de 1,44 e 1,68 kg i.a./ha; nicosulfuron nas doses de 0,0201; 0,030 e 0,040 kg i.a./ha; diuron nas doses de 1,0 e 1,5 kg i.a./ha; lactofen na dose de 0,18 kg i.a./ha; cyanazine nas doses de 1,0 e 1,5 kg i.a./ha e diuron nas doses de 1,0 e 1,5 kg i.a./ha.Os tratamentos herbicidas foram efetuados em pré-plantio incorporado (PPI, pré-emergência (PRE, pós-emergência (POS, cultivo mecânico (CM e jato dirigido (JD. Os resultados obtidos levaram a concluir que o sistema de trifluralina (PPI, alachlor (PRE, CM, M.S.M.A. + lactofen apresentaram a maior produtividade. Os sistemas herbicidas compostos por aplicação de trifluralina (PPI, alachlor (PRE, M.S.M.A. (POS, CM ao redor dos 50 a 60 D.A.P. (dias após o plantio e a aplicação de jato dirigido de diuron, lactofen + cyanazine, lactofen + diuron, M.S.M.A. + cyanazine, M.S.M.A. + lactofen e M.S.M.A. + diuron, propiciaram de forma geral controle das principais plantas daninhas.The objective of this work was to evaluate the efficacy of different combinations of integrated herbicide treatments, applied at PPI, pre, post, mechanical cultivation and direct spray on cotton crop (Gossypium hirsutum. The trial was conducted in the field, being cotton crop cultivar IAC-20 the experiment area. The treatments were tested with the following products: trifluralina at the dose of 1.068 kg a.i./ha; alachlor at the dose of 1.584 kg a.i/ha; M.S.M.A. at the doses of 1.44 and 1.68 kg a.i./ha; nicosulfuron at the doses

  14. Nitrate and herbicide loading in two groundwater basins of Illinois' sinkhole plain

    Science.gov (United States)

    Panno, S.V.; Kelly, W.R.

    2004-01-01

    This investigation was designed to estimate the mass loading of nitrate (NO3-) and herbicides in spring water discharging from groundwater basins in an agriculturally dominated, mantled karst terrain. The loading was normalized to land use and NO3- and herbicide losses were compared to estimated losses in other agricultural areas of the Midwestern USA. Our study area consisted of two large karst springs that drain two adjoining groundwater basins (total area of 37.7 km2) in southwestern Illinois' sinkhole plain, USA. The springs and stream that they form were monitored for almost 2 years. Nitrate-nitrogen (NO3-N) concentrations at three monitoring sites were almost always above the background concentration (1.9 mg/l). NO3-N concentrations at the two springs ranged from 1.08 to 6.08 with a median concentration of 3.61 mg/l. Atrazine and alachlor concentrations ranged from <0.01 to 34 ??g/l and <0.01 to 0.98 ??g/l, respectively, with median concentrations of 0.48 and 0.12 ??g/l, respectively. Approximately 100,000 kg/yr of NO3-N, 39 kg/yr of atrazine, and 2.8 kg/yr of alachlor were discharged from the two springs. Slightly more than half of the discharged NO3- came from background sources and most of the remainder probably came from fertilizer. This represents a 21-31% loss of fertilizer N from the groundwater basins. The pesticide losses were 3.8-5.8% of the applied atrazine, and 0.05-0.08% of the applied alachlor. The loss of atrazine adsorbed to the suspended solid fraction was about 2 kg/yr, only about 5% of the total mass of atrazine discharged from the springs. ?? 2004 Elsevier B.V. All rights reserved.

  15. Pesticide sorption and leaching potential on three Hawaiian soils.

    Science.gov (United States)

    Hall, Kathleen E; Ray, Chittaranjan; Ki, Seo Jin; Spokas, Kurt A; Koskinen, William C

    2015-08-15

    On the Hawaiian Islands, groundwater is the principal source of potable water and contamination of this key resource by pesticides is of great concern. To evaluate the leaching potential of four weak acid herbicides [aminocyclopyrachlor, picloram, metsulfuron-methyl, biologically active diketonitrile degradate of isoxaflutole (DKN)] and two neutral non-ionizable herbicides [oxyfluorfen, alachlor], their sorption coefficients were determined on three prevalent soils from the island of Oahu. Metsulfuron-methyl, aminocylcopyrachlor, picloram, and DKN were relatively low sorbing herbicides (K(oc) = 3-53 mL g(-1)), alachlor was intermediate (K(oc) = 120-150 mL g(-1)), and oxyfluorfen sorbed very strongly to the three soils (K(oc) > 12,000 mL g(-1)). Following determination of K(oc) values, the groundwater ubiquity score (GUS) indices for these compounds were calculated to predicted their behavior with the Comprehensive Leaching Risk Assessment System (CLEARS; Tier-1 methodology for Hawaii). Metsulfuron-methyl, aminocyclopyrachlor, picloram, and DKN would be categorized as likely leachers in all three Hawaiian soils, indicating a high risk of groundwater contamination across the island of Oahu. In contrast, oxyfluorfen, regardless of the degradation rate, would possess a low and acceptable leaching risk due to its high sorption on all three soils. The leaching potential of alachlor was more difficult to classify, with a GUS value between 1.8 and 2.8. In addition, four different biochar amendments to these soils did not significantly alter their sorption capacities for aminocyclopyrachlor, indicating a relatively low impact of black carbon additions from geologic volcanic inputs of black carbon. Due to the fact that pesticide environmental risks are chiefly dependent on local soil characteristics, this work has demonstrated that once soil specific sorption parameters are known one can assess the potential pesticide leaching risks. Published by Elsevier Ltd.

  16. Real-time x-ray fluoroscopy-based catheter detection and tracking for cardiac electrophysiology interventions

    International Nuclear Information System (INIS)

    Ma Yingliang; Housden, R. James; Razavi, Reza; Rhode, Kawal S.; Gogin, Nicolas; Cathier, Pascal; Gijsbers, Geert; Cooklin, Michael; O'Neill, Mark; Gill, Jaswinder; Rinaldi, C. Aldo

    2013-01-01

    Purpose: X-ray fluoroscopically guided cardiac electrophysiology (EP) procedures are commonly carried out to treat patients with arrhythmias. X-ray images have poor soft tissue contrast and, for this reason, overlay of a three-dimensional (3D) roadmap derived from preprocedural volumetric images can be used to add anatomical information. It is useful to know the position of the catheter electrodes relative to the cardiac anatomy, for example, to record ablation therapy locations during atrial fibrillation therapy. Also, the electrode positions of the coronary sinus (CS) catheter or lasso catheter can be used for road map motion correction.Methods: In this paper, the authors present a novel unified computational framework for image-based catheter detection and tracking without any user interaction. The proposed framework includes fast blob detection, shape-constrained searching and model-based detection. In addition, catheter tracking methods were designed based on the customized catheter models input from the detection method. Three real-time detection and tracking methods are derived from the computational framework to detect or track the three most common types of catheters in EP procedures: the ablation catheter, the CS catheter, and the lasso catheter. Since the proposed methods use the same blob detection method to extract key information from x-ray images, the ablation, CS, and lasso catheters can be detected and tracked simultaneously in real-time.Results: The catheter detection methods were tested on 105 different clinical fluoroscopy sequences taken from 31 clinical procedures. Two-dimensional (2D) detection errors of 0.50 ± 0.29, 0.92 ± 0.61, and 0.63 ± 0.45 mm as well as success rates of 99.4%, 97.2%, and 88.9% were achieved for the CS catheter, ablation catheter, and lasso catheter, respectively. With the tracking method, accuracies were increased to 0.45 ± 0.28, 0.64 ± 0.37, and 0.53 ± 0.38 mm and success rates increased to 100%, 99.2%, and 96

  17. Real-time x-ray fluoroscopy-based catheter detection and tracking for cardiac electrophysiology interventions

    Energy Technology Data Exchange (ETDEWEB)

    Ma Yingliang; Housden, R. James; Razavi, Reza; Rhode, Kawal S. [Division of Imaging Sciences and Biomedical Engineering, King' s College London, London SE1 7EH (United Kingdom); Gogin, Nicolas; Cathier, Pascal [Medisys Research Group, Philips Healthcare, Paris 92156 (France); Gijsbers, Geert [Interventional X-ray, Philips Healthcare, Best 5680 DA (Netherlands); Cooklin, Michael; O' Neill, Mark; Gill, Jaswinder; Rinaldi, C. Aldo [Department of Cardiology, Guys and St. Thomas' Hospitals NHS Foundation Trust, London SE1 7EH (United Kingdom)

    2013-07-15

    Purpose: X-ray fluoroscopically guided cardiac electrophysiology (EP) procedures are commonly carried out to treat patients with arrhythmias. X-ray images have poor soft tissue contrast and, for this reason, overlay of a three-dimensional (3D) roadmap derived from preprocedural volumetric images can be used to add anatomical information. It is useful to know the position of the catheter electrodes relative to the cardiac anatomy, for example, to record ablation therapy locations during atrial fibrillation therapy. Also, the electrode positions of the coronary sinus (CS) catheter or lasso catheter can be used for road map motion correction.Methods: In this paper, the authors present a novel unified computational framework for image-based catheter detection and tracking without any user interaction. The proposed framework includes fast blob detection, shape-constrained searching and model-based detection. In addition, catheter tracking methods were designed based on the customized catheter models input from the detection method. Three real-time detection and tracking methods are derived from the computational framework to detect or track the three most common types of catheters in EP procedures: the ablation catheter, the CS catheter, and the lasso catheter. Since the proposed methods use the same blob detection method to extract key information from x-ray images, the ablation, CS, and lasso catheters can be detected and tracked simultaneously in real-time.Results: The catheter detection methods were tested on 105 different clinical fluoroscopy sequences taken from 31 clinical procedures. Two-dimensional (2D) detection errors of 0.50 {+-} 0.29, 0.92 {+-} 0.61, and 0.63 {+-} 0.45 mm as well as success rates of 99.4%, 97.2%, and 88.9% were achieved for the CS catheter, ablation catheter, and lasso catheter, respectively. With the tracking method, accuracies were increased to 0.45 {+-} 0.28, 0.64 {+-} 0.37, and 0.53 {+-} 0.38 mm and success rates increased to 100%, 99

  18. Manejo de plantas daninhas na cultura do algodoeiro em sistema de plantio direto Weed management of cotton under no-tillage

    Directory of Open Access Journals (Sweden)

    R.S. Freitas

    2006-06-01

    Full Text Available Este trabalho foi realizado com objetivo de avaliar a eficiência dos herbicidas smetolachlor, em pré-emergência, e trifloxysulfuron-sodium, aplicado aos 18 dias após a emergência do algodão (DAE, em sistema de plantio direto. Foi utilizado o arranjo fatorial (4 x 4 + 1, sob delineamento de blocos casualizados, com quatro repetições. O primeiro fator constituiu-se de quatro doses de S-metolachlor (0, 384, 768 e 1.152 g ha-1 e o segundo de quatro doses de trifloxysulfuron-sodium (0,0; 2,625; 5,250; e 7,875 g ha-1, mais uma testemunha mantida no limpo por todo o ciclo do algodoeiro. As plantas daninhas foram avaliadas aos 25, 45 e 60 DAE. Na área, foi verificada a presença das seguintes espécies daninhas: Alternanthera tenella (apaga-fogo, representando mais de 80% do total, Tridax procumbens (erva-de-touro, Bidens sp. (picão-preto, Acanthospermum hispidum (carrapicho-de-carneiro, Cenchrus echinatus (capim-carrapicho, Digitaria horizontalis (capimcolchão, Eleusine indica (capim-pé-de-galinha e Commelina benghalensis (trapoeraba. O S-metolachlor apresentou baixa eficiência de controle destas espécies, no entanto o trifloxysulfuron-sodium teve seu desempenho melhorado quando foi aplicado S-metolachlor. O melhor controle foi obtido com a combinação de S-metolachlor a 1.152 g ha-1 com trifloxysulfuron-sodium a 7,875 g ha-1, que apresentou controle superior a 90% de A. tenella e do total de plantas daninhas até 60 DAE. Todavia, esse controle não foi suficiente para permitir a colheita do algodão no limpo. As combinações de S-metolachlor a 384 e 768 g ha-1 com trifloxysulfuron-sodium a 7,875 g ha-1 e de S-metolachlor a 1.152 g ha-1 com trifloxysulfuron-sodium nas doses de 5,250 e 7,875 g ha-1 proporcionaram rendimentos semelhantes aos da testemunha capinada.The objective of this study was to evaluate the efficiency of the herbicides Smetolachlor in pre-emergence and trifloxysulfuron-sodium applied 18 days after crop emergence (DAE

  19. Partial degradation of five pesticides and an industrial pollutant by ozonation in a pilot-plant scale reactor

    International Nuclear Information System (INIS)

    Maldonado, M.I.; Malato, S.; Perez-Estrada, L.A.; Gernjak, W.; Oller, I.; Domenech, Xavier; Peral, Jose

    2006-01-01

    Aqueous solutions of a mixture of several pesticides (alachlor, atrazine, chlorfenvinphos, diuron and isoproturon), considered PS (priority substances) by the European Commission, and an intermediate product of the pharmaceutical industry (α-methylphenylglycine, MPG) chosen as a model industrial pollutant, have been degraded at pilot-plant scale using ozonation. This study is part of a large research project [CADOX Project, A Coupled Advanced Oxidation-Biological Process for Recycling of Industrial Wastewater Containing Persistent Organic Contaminants, Contract No.: EVK1-CT-2002-00122, European Commission, http://www.psa.es/webeng/projects/cadox/index.html[1

  20. Partial degradation of five pesticides and an industrial pollutant by ozonation in a pilot-plant scale reactor

    Energy Technology Data Exchange (ETDEWEB)

    Maldonado, M.I. [PSA - Plataforma Solar de Almeria, CIEMAT, Crta Senes km 4, Tabernas, Almeria 04200 (Spain); Malato, S. [PSA - Plataforma Solar de Almeria, CIEMAT, Crta Senes km 4, Tabernas, Almeria 04200 (Spain); Perez-Estrada, L.A. [PSA - Plataforma Solar de Almeria, CIEMAT, Crta Senes km 4, Tabernas, Almeria 04200 (Spain); Gernjak, W. [PSA -Plataforma Solar de Almeria, CIEMAT, Crta Senes km 4, Tabernas, Almeria 04200 (Spain); Oller, I. [PSA - Plataforma Solar de Almeria, CIEMAT, Crta Senes km 4, Tabernas, Almeria 04200 (Spain); Domenech, Xavier [Departament de Quimica, Edifici Cn, Universitat Autonoma de Barcelona, E-08193 Bellaterra, Barcelona (Spain); Peral, Jose [Departament de Quimica, Edifici Cn, Universitat Autonoma de Barcelona, E-08193 Bellaterra, Barcelona (Spain)]. E-mail: jose.peral@uab.es

    2006-11-16

    Aqueous solutions of a mixture of several pesticides (alachlor, atrazine, chlorfenvinphos, diuron and isoproturon), considered PS (priority substances) by the European Commission, and an intermediate product of the pharmaceutical industry ({alpha}-methylphenylglycine, MPG) chosen as a model industrial pollutant, have been degraded at pilot-plant scale using ozonation. This study is part of a large research project [CADOX Project, A Coupled Advanced Oxidation-Biological Process for Recycling of Industrial Wastewater Containing Persistent Organic Contaminants, Contract No.: EVK1-CT-2002-00122, European Commission, http://www.psa.es/webeng/projects/cadox/index.html[1

  1. Ultrahigh Dimensional Variable Selection for Interpolation of Point Referenced Spatial Data: A Digital Soil Mapping Case Study

    Science.gov (United States)

    Lamb, David W.; Mengersen, Kerrie

    2016-01-01

    Modern soil mapping is characterised by the need to interpolate point referenced (geostatistical) observations and the availability of large numbers of environmental characteristics for consideration as covariates to aid this interpolation. Modelling tasks of this nature also occur in other fields such as biogeography and environmental science. This analysis employs the Least Angle Regression (LAR) algorithm for fitting Least Absolute Shrinkage and Selection Operator (LASSO) penalized Multiple Linear Regressions models. This analysis demonstrates the efficiency of the LAR algorithm at selecting covariates to aid the interpolation of geostatistical soil carbon observations. Where an exhaustive search of the models that could be constructed from 800 potential covariate terms and 60 observations would be prohibitively demanding, LASSO variable selection is accomplished with trivial computational investment. PMID:27603135

  2. Two-step variable selection in quantile regression models

    Directory of Open Access Journals (Sweden)

    FAN Yali

    2015-06-01

    Full Text Available We propose a two-step variable selection procedure for high dimensional quantile regressions, in which the dimension of the covariates, pn is much larger than the sample size n. In the first step, we perform ℓ1 penalty, and we demonstrate that the first step penalized estimator with the LASSO penalty can reduce the model from an ultra-high dimensional to a model whose size has the same order as that of the true model, and the selected model can cover the true model. The second step excludes the remained irrelevant covariates by applying the adaptive LASSO penalty to the reduced model obtained from the first step. Under some regularity conditions, we show that our procedure enjoys the model selection consistency. We conduct a simulation study and a real data analysis to evaluate the finite sample performance of the proposed approach.

  3. On Weighted Support Vector Regression

    DEFF Research Database (Denmark)

    Han, Xixuan; Clemmensen, Line Katrine Harder

    2014-01-01

    We propose a new type of weighted support vector regression (SVR), motivated by modeling local dependencies in time and space in prediction of house prices. The classic weights of the weighted SVR are added to the slack variables in the objective function (OF‐weights). This procedure directly...... shrinks the coefficient of each observation in the estimated functions; thus, it is widely used for minimizing influence of outliers. We propose to additionally add weights to the slack variables in the constraints (CF‐weights) and call the combination of weights the doubly weighted SVR. We illustrate...... the differences and similarities of the two types of weights by demonstrating the connection between the Least Absolute Shrinkage and Selection Operator (LASSO) and the SVR. We show that an SVR problem can be transformed to a LASSO problem plus a linear constraint and a box constraint. We demonstrate...

  4. Technical report on semiautomatic segmentation using the Adobe Photoshop.

    Science.gov (United States)

    Park, Jin Seo; Chung, Min Suk; Hwang, Sung Bae; Lee, Yong Sook; Har, Dong-Hwan

    2005-12-01

    The purpose of this research is to enable users to semiautomatically segment the anatomical structures in magnetic resonance images (MRIs), computerized tomographs (CTs), and other medical images on a personal computer. The segmented images are used for making 3D images, which are helpful to medical education and research. To achieve this purpose, the following trials were performed. The entire body of a volunteer was scanned to make 557 MRIs. On Adobe Photoshop, contours of 19 anatomical structures in the MRIs were semiautomatically drawn using MAGNETIC LASSO TOOL and manually corrected using either LASSO TOOL or DIRECT SELECTION TOOL to make 557 segmented images. In a similar manner, 13 anatomical structures in 8,590 anatomical images were segmented. Proper segmentation was verified by making 3D images from the segmented images. Semiautomatic segmentation using Adobe Photoshop is expected to be widely used for segmentation of anatomical structures in various medical images.

  5. Integration of transcriptomics and metabonomics

    DEFF Research Database (Denmark)

    Bjerrum, Jacob Tveiten; Rantalainen, Mattias; Wang, Yulan

    2014-01-01

    performance was evaluated using nested Monte Carlo cross-validation. The prediction performance of the merged data sets and that of relative small (... profiles were generated using (1)H Nuclear magnetic resonance spectroscopy (Bruker 600 MHz, Bruker BioSpin, Rheinstetten, Germany). Data were analyzed with the use of orthogonal-projection to latent structure-discriminant analysis and a multivariate logistic regression model fitted by lasso. Prediction...

  6. Machine Learning for Education: Learning to Teach

    Science.gov (United States)

    2016-12-01

    silhouette is high, and there are enough data points within each cluster. Of course, one could use a Bayesian prior (e.g., Chinese restaurant process...over k if one believes their data are well-suited to such an interpretation. Based on our data and the metrics shown in Figure 2, we select k = 4 for our...to evaluate during training for the shrinkage parameter, λ. Our approach combines a feature selection subroutine [31] as well as LASSO regression [38

  7. Economic sustainability in franchising: a model to predict franchisor success or failure

    OpenAIRE

    Calderón Monge, Esther; Pastor Sanz, Ivan .; Huerta Zavala, Pilar Angélica

    2017-01-01

    As a business model, franchising makes a major contribution to gross domestic product (GDP). A model that predicts franchisor success or failure is therefore necessary to ensure economic sustainability. In this study, such a model was developed by applying Lasso regression to a sample of franchises operating between 2002 and 2013. For franchises with the highest likelihood of survival, the franchise fees and the ratio of company-owned to franchised outlets were suited to the age ...

  8. Accelerating Deep Learning with Shrinkage and Recall

    OpenAIRE

    Zheng, Shuai; Vishnu, Abhinav; Ding, Chris

    2016-01-01

    Deep Learning is a very powerful machine learning model. Deep Learning trains a large number of parameters for multiple layers and is very slow when data is in large scale and the architecture size is large. Inspired from the shrinking technique used in accelerating computation of Support Vector Machines (SVM) algorithm and screening technique used in LASSO, we propose a shrinking Deep Learning with recall (sDLr) approach to speed up deep learning computation. We experiment shrinking Deep Lea...

  9. Fast Adaptive Least Trimmed Squares for Robust Evaluation of Quality of Experience

    Science.gov (United States)

    2014-07-01

    fact that not every Internet user is trustworthy . In other words, due to the lack of supervision when subjects perform experiments in crowdsourcing, they...21], [22], etc. However, a major challenge of crowdsourcing QoE evaluation is that not every Internet user is trustworthy . That is, some raters try...regularization paths of the LASSO problem could provide us an order on samples tending to be outliers. Such an approach is inspired by Huber’s celebrated work on

  10. Quantifying predictive capability of electronic health records for the most harmful breast cancer

    Science.gov (United States)

    Wu, Yirong; Fan, Jun; Peissig, Peggy; Berg, Richard; Tafti, Ahmad Pahlavan; Yin, Jie; Yuan, Ming; Page, David; Cox, Jennifer; Burnside, Elizabeth S.

    2018-03-01

    Improved prediction of the "most harmful" breast cancers that cause the most substantive morbidity and mortality would enable physicians to target more intense screening and preventive measures at those women who have the highest risk; however, such prediction models for the "most harmful" breast cancers have rarely been developed. Electronic health records (EHRs) represent an underused data source that has great research and clinical potential. Our goal was to quantify the value of EHR variables in the "most harmful" breast cancer risk prediction. We identified 794 subjects who had breast cancer with primary non-benign tumors with their earliest diagnosis on or after 1/1/2004 from an existing personalized medicine data repository, including 395 "most harmful" breast cancer cases and 399 "least harmful" breast cancer cases. For these subjects, we collected EHR data comprised of 6 components: demographics, diagnoses, symptoms, procedures, medications, and laboratory results. We developed two regularized prediction models, Ridge Logistic Regression (Ridge-LR) and Lasso Logistic Regression (Lasso-LR), to predict the "most harmful" breast cancer one year in advance. The area under the ROC curve (AUC) was used to assess model performance. We observed that the AUCs of Ridge-LR and Lasso-LR models were 0.818 and 0.839 respectively. For both the Ridge-LR and LassoLR models, the predictive performance of the whole EHR variables was significantly higher than that of each individual component (pbreast cancer, providing the possibility to personalize care for those women at the highest risk in clinical practice.

  11. PERBANDINGAN ANALISIS LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR DAN PARTIAL LEAST SQUARES (Studi Kasus: Data Microarray

    Directory of Open Access Journals (Sweden)

    KADEK DWI FARMANI

    2012-09-01

    Full Text Available Linear regression analysis is one of the parametric statistical methods which utilize the relationship between two or more quantitative variables. In linear regression analysis, there are several assumptions that must be met that is normal distribution of errors, there is no correlation between the error and error variance is constant and homogent. There are some constraints that caused the assumption can not be met, for example, the correlation between independent variables (multicollinearity, constraints on the number of data and independent variables are obtained. When the number of samples obtained less than the number of independent variables, then the data is called the microarray data. Least Absolute shrinkage and Selection Operator (LASSO and Partial Least Squares (PLS is a statistical method that can be used to overcome the microarray, overfitting, and multicollinearity. From the above description, it is necessary to study with the intention of comparing LASSO and PLS method. This study uses coronary heart and stroke patients data which is a microarray data and contain multicollinearity. With these two characteristics of the data that most have a weak correlation between independent variables, LASSO method produces a better model than PLS seen from the large RMSEP.

  12. Detection of shielded radionuclides from weak and poorly resolved spectra using group positive RIVAL

    International Nuclear Information System (INIS)

    Kump, Paul; Bai, Er-Wei; Chan, Kung-Sik; Eichinger, William

    2013-01-01

    This paper is concerned with the identification of nuclides from weak and poorly resolved spectra in the presence of unknown radiation shielding materials such as carbon, water, concrete and lead. Since a shield will attenuate lower energies more so than higher ones, isotope sub-spectra must be introduced into models and into detection algorithms. We propose a new algorithm for detection, called group positive RIVAL, that encourages the selection of groups of sub-spectra rather than the selection of individual sub-spectra that may be from the same parent isotope. Indeed, the proposed algorithm incorporates group positive LASSO, and, as such, we supply the consistency results of group positive LASSO and adaptive group positive LASSO. In an example employing various shielding materials and material thicknesses, group positive RIVAL is shown to perform well in all scenarios with the exception of ones in which the shielding material is lead. - Highlights: ► Identification of nuclides from weak and poorly resolved spectra. ► Shielding materials such as carbon, water, concrete, and lead are considered. ► Isotope spectra are decomposed into their sub-spectra. ► A variable selection algorithm is proposed that encourages group selection. ► Simulations demonstrate the proposed method's performance when nuclides have been shielded

  13. Regularized rare variant enrichment analysis for case-control exome sequencing data.

    Science.gov (United States)

    Larson, Nicholas B; Schaid, Daniel J

    2014-02-01

    Rare variants have recently garnered an immense amount of attention in genetic association analysis. However, unlike methods traditionally used for single marker analysis in GWAS, rare variant analysis often requires some method of aggregation, since single marker approaches are poorly powered for typical sequencing study sample sizes. Advancements in sequencing technologies have rendered next-generation sequencing platforms a realistic alternative to traditional genotyping arrays. Exome sequencing in particular not only provides base-level resolution of genetic coding regions, but also a natural paradigm for aggregation via genes and exons. Here, we propose the use of penalized regression in combination with variant aggregation measures to identify rare variant enrichment in exome sequencing data. In contrast to marginal gene-level testing, we simultaneously evaluate the effects of rare variants in multiple genes, focusing on gene-based least absolute shrinkage and selection operator (LASSO) and exon-based sparse group LASSO models. By using gene membership as a grouping variable, the sparse group LASSO can be used as a gene-centric analysis of rare variants while also providing a penalized approach toward identifying specific regions of interest. We apply extensive simulations to evaluate the performance of these approaches with respect to specificity and sensitivity, comparing these results to multiple competing marginal testing methods. Finally, we discuss our findings and outline future research. © 2013 WILEY PERIODICALS, INC.

  14. Joint effect of unlinked genotypes: application to type 2 diabetes in the EPIC-Potsdam case-cohort study.

    Science.gov (United States)

    Knüppel, Sven; Meidtner, Karina; Arregui, Maria; Holzhütter, Hermann-Georg; Boeing, Heiner

    2015-07-01

    Analyzing multiple single nucleotide polymorphisms (SNPs) is a promising approach to finding genetic effects beyond single-locus associations. We proposed the use of multilocus stepwise regression (MSR) to screen for allele combinations as a method to model joint effects, and compared the results with the often used genetic risk score (GRS), conventional stepwise selection, and the shrinkage method LASSO. In contrast to MSR, the GRS, conventional stepwise selection, and LASSO model each genotype by the risk allele doses. We reanalyzed 20 unlinked SNPs related to type 2 diabetes (T2D) in the EPIC-Potsdam case-cohort study (760 cases, 2193 noncases). No SNP-SNP interactions and no nonlinear effects were found. Two SNP combinations selected by MSR (Nagelkerke's R² = 0.050 and 0.048) included eight SNPs with mean allele combination frequency of 2%. GRS and stepwise selection selected nearly the same SNP combinations consisting of 12 and 13 SNPs (Nagelkerke's R² ranged from 0.020 to 0.029). LASSO showed similar results. The MSR method showed the best model fit measured by Nagelkerke's R² suggesting that further improvement may render this method a useful tool in genetic research. However, our comparison suggests that the GRS is a simple way to model genetic effects since it does not consider linkage, SNP-SNP interactions, and no non-linear effects. © 2015 John Wiley & Sons Ltd/University College London.

  15. Perceptual quality estimation of H.264/AVC videos using reduced-reference and no-reference models

    Science.gov (United States)

    Shahid, Muhammad; Pandremmenou, Katerina; Kondi, Lisimachos P.; Rossholm, Andreas; Lövström, Benny

    2016-09-01

    Reduced-reference (RR) and no-reference (NR) models for video quality estimation, using features that account for the impact of coding artifacts, spatio-temporal complexity, and packet losses, are proposed. The purpose of this study is to analyze a number of potentially quality-relevant features in order to select the most suitable set of features for building the desired models. The proposed sets of features have not been used in the literature and some of the features are used for the first time in this study. The features are employed by the least absolute shrinkage and selection operator (LASSO), which selects only the most influential of them toward perceptual quality. For comparison, we apply feature selection in the complete feature sets and ridge regression on the reduced sets. The models are validated using a database of H.264/AVC encoded videos that were subjectively assessed for quality in an ITU-T compliant laboratory. We infer that just two features selected by RR LASSO and two bitstream-based features selected by NR LASSO are able to estimate perceptual quality with high accuracy, higher than that of ridge, which uses more features. The comparisons with competing works and two full-reference metrics also verify the superiority of our models.

  16. Multiscale Data Assimilation for Large-Eddy Simulations

    Science.gov (United States)

    Li, Z.; Cheng, X.; Gustafson, W. I., Jr.; Xiao, H.; Vogelmann, A. M.; Endo, S.; Toto, T.

    2017-12-01

    Large-eddy simulation (LES) is a powerful tool for understanding atmospheric turbulence, boundary layer physics and cloud development, and there is a great need for developing data assimilation methodologies that can constrain LES models. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility has been developing the capability to routinely generate ensembles of LES. The LES ARM Symbiotic Simulation and Observation (LASSO) project (https://www.arm.gov/capabilities/modeling/lasso) is generating simulations for shallow convection days at the ARM Southern Great Plains site in Oklahoma. One of major objectives of LASSO is to develop the capability to observationally constrain LES using a hierarchy of ARM observations. We have implemented a multiscale data assimilation (MSDA) scheme, which allows data assimilation to be implemented separately for distinct spatial scales, so that the localized observations can be effectively assimilated to constrain the mesoscale fields in the LES area of about 15 km in width. The MSDA analysis is used to produce forcing data that drive LES. With such LES workflow we have examined 13 days with shallow convection selected from the period May-August 2016. We will describe the implementation of MSDA, present LES results, and address challenges and opportunities for applying data assimilation to LES studies.

  17. Structured sparse canonical correlation analysis for brain imaging genetics: an improved GraphNet method.

    Science.gov (United States)

    Du, Lei; Huang, Heng; Yan, Jingwen; Kim, Sungeun; Risacher, Shannon L; Inlow, Mark; Moore, Jason H; Saykin, Andrew J; Shen, Li

    2016-05-15

    Structured sparse canonical correlation analysis (SCCA) models have been used to identify imaging genetic associations. These models either use group lasso or graph-guided fused lasso to conduct feature selection and feature grouping simultaneously. The group lasso based methods require prior knowledge to define the groups, which limits the capability when prior knowledge is incomplete or unavailable. The graph-guided methods overcome this drawback by using the sample correlation to define the constraint. However, they are sensitive to the sign of the sample correlation, which could introduce undesirable bias if the sign is wrongly estimated. We introduce a novel SCCA model with a new penalty, and develop an efficient optimization algorithm. Our method has a strong upper bound for the grouping effect for both positively and negatively correlated features. We show that our method performs better than or equally to three competing SCCA models on both synthetic and real data. In particular, our method identifies stronger canonical correlations and better canonical loading patterns, showing its promise for revealing interesting imaging genetic associations. The Matlab code and sample data are freely available at http://www.iu.edu/∼shenlab/tools/angscca/ shenli@iu.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  18. Comparison of methods used to identify superior individuals in genomic selection in plant breeding.

    Science.gov (United States)

    Bhering, L L; Junqueira, V S; Peixoto, L A; Cruz, C D; Laviola, B G

    2015-09-10

    The aim of this study was to evaluate different methods used in genomic selection, and to verify those that select a higher proportion of individuals with superior genotypes. Thus, F2 populations of different sizes were simulated (100, 200, 500, and 1000 individuals) with 10 replications each. These consisted of 10 linkage groups (LG) of 100 cM each, containing 100 equally spaced markers per linkage group, of which 200 controlled the characteristics, defined as the 20 initials of each LG. Genetic and phenotypic values were simulated assuming binomial distribution of effects for each LG, and the absence of dominance. For phenotypic values, heritabilities of 20, 50, and 80% were considered. To compare methodologies, the analysis processing time, coefficient of coincidence (selection of 5, 10, and 20% of superior individuals), and Spearman correlation between true genetic values, and the genomic values predicted by each methodology were determined. Considering the processing time, the three methodologies were statistically different, rrBLUP was the fastest, and Bayesian LASSO was the slowest. Spearman correlation revealed that the rrBLUP and GBLUP methodologies were equivalent, and Bayesian LASSO provided the lowest correlation values. Similar results were obtained in coincidence variables among the individuals selected, in which Bayesian LASSO differed statistically and presented a lower value than the other methodologies. Therefore, for the scenarios evaluated, rrBLUP is the best methodology for the selection of genetically superior individuals.

  19. Prediction of genetic values of quantitative traits with epistatic effects in plant breeding populations.

    Science.gov (United States)

    Wang, D; Salah El-Basyoni, I; Stephen Baenziger, P; Crossa, J; Eskridge, K M; Dweikat, I

    2012-11-01

    Though epistasis has long been postulated to have a critical role in genetic regulation of important pathways as well as provide a major source of variation in the process of speciation, the importance of epistasis for genomic selection in the context of plant breeding is still being debated. In this paper, we report the results on the prediction of genetic values with epistatic effects for 280 accessions in the Nebraska Wheat Breeding Program using adaptive mixed least absolute shrinkage and selection operator (LASSO). The development of adaptive mixed LASSO, originally designed for association mapping, for the context of genomic selection is reported. The results show that adaptive mixed LASSO can be successfully applied to the prediction of genetic values while incorporating both marker main effects and epistatic effects. Especially, the prediction accuracy is substantially improved by the inclusion of two-locus epistatic effects (more than onefold in some cases as measured by cross-validation correlation coefficient), which is observed for multiple traits and planting locations. This points to significant potential in using non-additive genetic effects for genomic selection in crop breeding practices.

  20. [Multi-mathematical modelings for compatibility optimization of Jiangzhi granules].

    Science.gov (United States)

    Yang, Ming; Zhang, Li; Ge, Yingli; Lu, Yanliu; Ji, Guang

    2011-12-01

    To investigate into the method of "multi activity index evaluation and combination optimized of mult-component" for Chinese herbal formulas. According to the scheme of uniform experimental design, efficacy experiment, multi index evaluation, least absolute shrinkage, selection operator (LASSO) modeling, evolutionary optimization algorithm, validation experiment, we optimized the combination of Jiangzhi granules based on the activity indexes of blood serum ALT, ALT, AST, TG, TC, HDL, LDL and TG level of liver tissues, ratio of liver tissue to body. Analytic hierarchy process (AHP) combining with criteria importance through intercriteria correlation (CRITIC) for multi activity index evaluation was more reasonable and objective, it reflected the information of activity index's order and objective sample data. LASSO algorithm modeling could accurately reflect the relationship between different combination of Jiangzhi granule and the activity comprehensive indexes. The optimized combination of Jiangzhi granule showed better values of the activity comprehensive indexed than the original formula after the validation experiment. AHP combining with CRITIC can be used for multi activity index evaluation and LASSO algorithm, it is suitable for combination optimized of Chinese herbal formulas.

  1. On the MSE Performance and Optimization of Regularized Problems

    KAUST Repository

    Alrashdi, Ayed

    2016-11-01

    The amount of data that has been measured, transmitted/received, and stored in the recent years has dramatically increased. So, today, we are in the world of big data. Fortunately, in many applications, we can take advantages of possible structures and patterns in the data to overcome the curse of dimensionality. The most well known structures include sparsity, low-rankness, block sparsity. This includes a wide range of applications such as machine learning, medical imaging, signal processing, social networks and computer vision. This also led to a specific interest in recovering signals from noisy compressed measurements (Compressed Sensing (CS) problem). Such problems are generally ill-posed unless the signal is structured. The structure can be captured by a regularizer function. This gives rise to a potential interest in regularized inverse problems, where the process of reconstructing the structured signal can be modeled as a regularized problem. This thesis particularly focuses on finding the optimal regularization parameter for such problems, such as ridge regression, LASSO, square-root LASSO and low-rank Generalized LASSO. Our goal is to optimally tune the regularizer to minimize the mean-squared error (MSE) of the solution when the noise variance or structure parameters are unknown. The analysis is based on the framework of the Convex Gaussian Min-max Theorem (CGMT) that has been used recently to precisely predict performance errors.

  2. Relationships Between the External and Internal Training Load in Professional Soccer: What Can We Learn From Machine Learning?

    Science.gov (United States)

    Jaspers, Arne; Beéck, Tim Op De; Brink, Michel S; Frencken, Wouter G P; Staes, Filip; Davis, Jesse J; Helsen, Werner F

    2017-12-28

    Machine learning may contribute to understanding the relationship between the external load and internal load in professional soccer. Therefore, the relationship between external load indicators and the rating of perceived exertion (RPE) was examined using machine learning techniques on a group and individual level. Training data were collected from 38 professional soccer players over two seasons. The external load was measured using global positioning system technology and accelerometry. The internal load was obtained using the RPE. Predictive models were constructed using two machine learning techniques, artificial neural networks (ANNs) and least absolute shrinkage and selection operator (LASSO), and one naive baseline method. The predictions were based on a large set of external load indicators. Using each technique, one group model involving all players and one individual model for each player was constructed. These models' performance on predicting the reported RPE values for future training sessions was compared to the naive baseline's performance. Both the ANN and LASSO models outperformed the baseline. Additionally, the LASSO model made more accurate predictions for the RPE than the ANN model. Furthermore, decelerations were identified as important external load indicators. Regardless of the applied machine learning technique, the group models resulted in equivalent or better predictions for the reported RPE values than the individual models. Machine learning techniques may have added value in predicting the RPE for future sessions to optimize training design and evaluation. Additionally, these techniques may be used in conjunction with expert knowledge to select key external load indicators for load monitoring.

  3. Ensembling Variable Selectors by Stability Selection for the Cox Model

    Directory of Open Access Journals (Sweden)

    Qing-Yan Yin

    2017-01-01

    Full Text Available As a pivotal tool to build interpretive models, variable selection plays an increasingly important role in high-dimensional data analysis. In recent years, variable selection ensembles (VSEs have gained much interest due to their many advantages. Stability selection (Meinshausen and Bühlmann, 2010, a VSE technique based on subsampling in combination with a base algorithm like lasso, is an effective method to control false discovery rate (FDR and to improve selection accuracy in linear regression models. By adopting lasso as a base learner, we attempt to extend stability selection to handle variable selection problems in a Cox model. According to our experience, it is crucial to set the regularization region Λ in lasso and the parameter λmin properly so that stability selection can work well. To the best of our knowledge, however, there is no literature addressing this problem in an explicit way. Therefore, we first provide a detailed procedure to specify Λ and λmin. Then, some simulated and real-world data with various censoring rates are used to examine how well stability selection performs. It is also compared with several other variable selection approaches. Experimental results demonstrate that it achieves better or competitive performance in comparison with several other popular techniques.

  4. Redução da interferência de Brachiaria decumbens na formação de pastagem com Penisetum purpureum através de herbicidas Reduction of Brachiaria decumbens interference on Pennisetum purpureum pasture establishment through herbicides

    Directory of Open Access Journals (Sweden)

    W. Silva

    2002-08-01

    Full Text Available A tolerância da gramínea forrageira capim-elefante a herbicidas aplicados isoladamente ou em misturas entre si, aplicados em condições de pré e pós-emergência da forrageira, bem como a eficiência desses produtos no controle de B. decumbens e outras espécies de plantas daninhas, foram avaliadas em dois experimentos. Os herbicidas aplicados no experimento conduzido em condições de pré-emergência do capim-elefante, com as respectivas doses em kg ha-1, foram: metolachlor (1,152; 2,304; e 3,456, oxyfluorfen (0,48; 0,96 e 1,44 e a formulação comercial de atrazine + metolachlor (1,25; 2,50; e 3,75, três repetições. Os herbicidas aplicados no experimento instalado em condições de pós-emergência da forrageira, com as respectivas doses em kg ha-1,foram: ametryne (1,25; 2,50; e 3,75 e oxyfluorfen (0,48; 0,96; e 1,44, com quatro repetições. Os tratamentos foram distribuídos em blocos ao acaso; sendo que, em ambos os experimentos foram adicionadas as testemunhas (capinada e sem capina, e os cultivares de capim-elefante utilizados em ambos os experimentos foram Cameroon e Pioneiro. A aplicação dos herbicidas em pré-emergência da forrageira foi feita um dia após o plantio com solo úmido; no experimento em pós-emergência do capim-elefante os herbicidas foram aplicados sobre o topo das plantas da cultura forrageira, aos 20 dias após a emergência. Metolachlor e atrazine + metolachlor, em pré-emergência, foram seletivos para os dois cultivares testados. O oxyfluorfen, até 0,96 kg ha-1, foi seletivo para a cultura forrageira nas aplicações tanto em pré- como em pós-emergência. O ametryne, em pós-emergência, também foi seletivo aos cultivares na dose inferior a 2,50 kg ha-1. B. decumbens e B. brizantha foram eficientemente controladas (90,9% em pré-emergência, exceto na menor dose de metolachlor e atrazine + metolachlor. O controle das dicotiledôneas atingiu 85% com metolachlor, atrazine + metolachlor e oxyfluorfen

  5. Batch vs continuous-feeding operational mode for the removal of pesticides from agricultural run-off by microalgae systems: A laboratory scale study

    Energy Technology Data Exchange (ETDEWEB)

    Matamoros, Víctor, E-mail: victor.matamoros@idaea.csic.es; Rodríguez, Yolanda

    2016-05-15

    Highlights: • The effect of microalgae on the removal of pesticides has been evaluated. • Continuous feeding operational mode is more efficient for removing pesticides. • Microalgae increased the removal of some pesticides. • Pesticide TPs confirmed that biodegradation was relevant. - Abstract: Microalgae-based water treatment technologies have been used in recent years to treat different water effluents, but their effectiveness for removing pesticides from agricultural run-off has not yet been addressed. This paper assesses the effect of microalgae in pesticide removal, as well as the influence of different operation strategies (continuous vs batch feeding). The following pesticides were studied: mecoprop, atrazine, simazine, diazinone, alachlor, chlorfenvinphos, lindane, malathion, pentachlorobenzene, chlorpyrifos, endosulfan and clofibric acid (tracer). 2 L batch reactors and 5 L continuous reactors were spiked to 10 μg L{sup −1} of each pesticide. Additionally, three different hydraulic retention times (HRTs) were assessed (2, 4 and 8 days) in the continuous feeding reactors. The batch-feeding experiments demonstrated that the presence of microalgae increased the efficiency of lindane, alachlor and chlorpyrifos by 50%. The continuous feeding reactors had higher removal efficiencies than the batch reactors for pentachlorobenzene, chlorpyrifos and lindane. Whilst longer HRTs increased the technology’s effectiveness, a low HRT of 2 days was capable of removing malathion, pentachlorobenzene, chlorpyrifos, and endosulfan by up to 70%. This study suggests that microalgae-based treatment technologies can be an effective alternative for removing pesticides from agricultural run-off.

  6. The competition of Linum with Camelina for minerals. 3

    International Nuclear Information System (INIS)

    Kranz, E.; Jacob, F.

    1978-01-01

    The competitive condition in the sulphate uptake of flax (Linum usitatissimum L.) and Camelina sativa (L.) Crantz was influenced by the herbicides MCPA, fenuron, alachlor and chloropham. Those herbicides (10 -4 M in each case) inhibited the uptake of sulphate of the plants. 12 h after exposing the plants in a solution deficient in sulphate flax plants in mixed culture took up less sulphate under the influence of MCPA, fenuron and chlorpropham. Camelina plants, however, also in mixed culture, with the exception of the MCPA variant, took up more of those ions than in monoculture. Under these conditions no essential change of the competitive conditions was found. In mixed culture, however, the sulphate uptake of Camelina plants - in percent of the untreated variant - was lower than in monoculture. In contrast to the untreated variants the sulphate uptake of Camelina plants decreased under the influence of alachlor in mixture, whereas there was no decrease found with Linum plants, both compared with the monoculture controls. Under influence of chlorpropham (10 -4 M) with an increased level of sulphate no essential decrease of sulphate uptake of Linum plants in mixture was found. With Camelina plants, however, a decrease of uptake in mixed culture was examined, both compared again with uptake in monoculture. (author)

  7. Batch vs continuous-feeding operational mode for the removal of pesticides from agricultural run-off by microalgae systems: A laboratory scale study

    International Nuclear Information System (INIS)

    Matamoros, Víctor; Rodríguez, Yolanda

    2016-01-01

    Highlights: • The effect of microalgae on the removal of pesticides has been evaluated. • Continuous feeding operational mode is more efficient for removing pesticides. • Microalgae increased the removal of some pesticides. • Pesticide TPs confirmed that biodegradation was relevant. - Abstract: Microalgae-based water treatment technologies have been used in recent years to treat different water effluents, but their effectiveness for removing pesticides from agricultural run-off has not yet been addressed. This paper assesses the effect of microalgae in pesticide removal, as well as the influence of different operation strategies (continuous vs batch feeding). The following pesticides were studied: mecoprop, atrazine, simazine, diazinone, alachlor, chlorfenvinphos, lindane, malathion, pentachlorobenzene, chlorpyrifos, endosulfan and clofibric acid (tracer). 2 L batch reactors and 5 L continuous reactors were spiked to 10 μg L"−"1 of each pesticide. Additionally, three different hydraulic retention times (HRTs) were assessed (2, 4 and 8 days) in the continuous feeding reactors. The batch-feeding experiments demonstrated that the presence of microalgae increased the efficiency of lindane, alachlor and chlorpyrifos by 50%. The continuous feeding reactors had higher removal efficiencies than the batch reactors for pentachlorobenzene, chlorpyrifos and lindane. Whilst longer HRTs increased the technology’s effectiveness, a low HRT of 2 days was capable of removing malathion, pentachlorobenzene, chlorpyrifos, and endosulfan by up to 70%. This study suggests that microalgae-based treatment technologies can be an effective alternative for removing pesticides from agricultural run-off.

  8. Novel chromatographic separation and carbon solid-phase extraction of acetanilide herbicide degradation products.

    Science.gov (United States)

    Shoemaker, Jody A

    2002-01-01

    One acetamide and 5 acetanilide herbicides are currently registered for use in the United States. Over the past several years, ethanesulfonic acid (ESA) and oxanilic acid (OA) degradation products of these acetanilide/acetamide herbicides have been found in U.S. ground waters and surface waters. Alachlor ESA and other acetanilide degradation products are listed on the U.S. Environmental Protection Agency's (EPA) 1998 Drinking Water Contaminant Candidate List. Consequently, EPA is interested in obtaining national occurrence data for these contaminants in drinking water. EPA currently does not have a method for determining these acetanilide degradation products in drinking water; therefore, a research method is being developed using liquid chromatography/negative ion electrospray/mass spectrometry with solid-phase extraction (SPE). A novel chromatographic separation of the acetochlor/alachlor ESA and OA structural isomers was developed which uses an ammonium acetate-methanol gradient combined with heating the analytical column to 70 degrees C. Twelve acetanilide degradates were extracted by SPE from 100 mL water samples using carbon cartridges with mean recoveries >90% and relative standard deviations < or =16%.

  9. Controle de Commelina benghalensis, C. erecta e Tripogandra diuretica na cultura do café Interference of Dayflower Species in Coffee Culture

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    A.R. Oliveira

    2009-01-01

    Full Text Available O objetivo deste trabalho foi avaliar o efeito de diferentes herbicidas/misturas no controle de três espécies de trapoeraba (Commelina benghalensis, C. erecta e Tripogandra diuretica e a tolerância de plantas jovens de café aos herbicidas. O delineamento experimental foi inteiramente casualizado, com quatro repetições. Os tratamentos foram constituídos por dez diferentes herbicidas/misturas e uma testemunha, associados a três espécies de trapoeraba. As avaliações foram realizadas aos 21 e 50 dias após a aplicação (DAP dos herbicidas, por meio de análise visual, seguindo-se escala de nível de controle. Avaliou-se a tolerância das mudas de café aos herbicidas (escala de avaliação visual da fitotoxicidade e as características de crescimento (diâmetro, número de folhas e estatura das mudas de café. A espécie C. benghalensis foi melhor controlada quando se utilizaram os herbicidas: diuron, 2,4-D + picloram, atrazine + metolachlor, metribuzin, glyphosate WG e acetochlor. A espécie C. erecta foi controlada pelos herbicidas diuron, 2,4-D + picloram, atrazine + metolachlor, glyphosate CS e acetochlor. Os herbicidas diuron, 2,4-D + picloram, atrazine + metolachlor, metribuzin, glyphosate WG e paraquat + diuron foram os que melhor controlaram T. diuretica. Metribuzin, diuron e acetochlor mostraram-se mais fitotóxicos para a cultura do café. O diuron reduziu a massa da matéria seca e o número de folhas do cafeeiro. O diâmetro do caule e a estatura foram afetados pelos herbicidas metribuzin e 2,4-D. O metribuzin foi o herbicida que maior prejuízo causou às características de crescimento da planta de café.This work aimed to evaluate the effect of different herbicides/mixtures on the control of three dayflower species (Commelina benghalensis, C. erecta. and Tripogandra diuretica and the tolerance of young coffee plants to the herbicides. The trial was arranged in a completely randomized design, constituted by ten different

  10. Detection of Independent Associations of Plasma Lipidomic Parameters with Insulin Sensitivity Indices Using Data Mining Methodology.

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    Steffi Kopprasch

    Full Text Available Glucolipotoxicity is a major pathophysiological mechanism in the development of insulin resistance and type 2 diabetes mellitus (T2D. We aimed to detect subtle changes in the circulating lipid profile by shotgun lipidomics analyses and to associate them with four different insulin sensitivity indices.The cross-sectional study comprised 90 men with a broad range of insulin sensitivity including normal glucose tolerance (NGT, n = 33, impaired glucose tolerance (IGT, n = 32 and newly detected T2D (n = 25. Prior to oral glucose challenge plasma was obtained and quantitatively analyzed for 198 lipid molecular species from 13 different lipid classes including triacylglycerls (TAGs, phosphatidylcholine plasmalogen/ether (PC O-s, sphingomyelins (SMs, and lysophosphatidylcholines (LPCs. To identify a lipidomic signature of individual insulin sensitivity we applied three data mining approaches, namely least absolute shrinkage and selection operator (LASSO, Support Vector Regression (SVR and Random Forests (RF for the following insulin sensitivity indices: homeostasis model of insulin resistance (HOMA-IR, glucose insulin sensitivity index (GSI, insulin sensitivity index (ISI, and disposition index (DI. The LASSO procedure offers a high prediction accuracy and and an easier interpretability than SVR and RF.After LASSO selection, the plasma lipidome explained 3% (DI to maximal 53% (HOMA-IR variability of the sensitivity indexes. Among the lipid species with the highest positive LASSO regression coefficient were TAG 54:2 (HOMA-IR, PC O- 32:0 (GSI, and SM 40:3:1 (ISI. The highest negative regression coefficient was obtained for LPC 22:5 (HOMA-IR, TAG 51:1 (GSI, and TAG 58:6 (ISI.Although a substantial part of lipid molecular species showed a significant correlation with insulin sensitivity indices we were able to identify a limited number of lipid metabolites of particular importance based on the LASSO approach. These few selected lipids with the closest

  11. PLS-based and regularization-based methods for the selection of relevant variables in non-targeted metabolomics data

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    Renata Bujak

    2016-07-01

    Full Text Available Non-targeted metabolomics constitutes a part of systems biology and aims to determine many metabolites in complex biological samples. Datasets obtained in non-targeted metabolomics studies are multivariate and high-dimensional due to the sensitivity of mass spectrometry-based detection methods as well as complexity of biological matrices. Proper selection of variables which contribute into group classification is a crucial step, especially in metabolomics studies which are focused on searching for disease biomarker candidates. In the present study, three different statistical approaches were tested using two metabolomics datasets (RH and PH study. Orthogonal projections to latent structures-discriminant analysis (OPLS-DA without and with multiple testing correction as well as least absolute shrinkage and selection operator (LASSO were tested and compared. For the RH study, OPLS-DA model built without multiple testing correction, selected 46 and 218 variables based on VIP criteria using Pareto and UV scaling, respectively. In the case of the PH study, 217 and 320 variables were selected based on VIP criteria using Pareto and UV scaling, respectively. In the RH study, OPLS-DA model built with multiple testing correction, selected 4 and 19 variables as statistically significant in terms of Pareto and UV scaling, respectively. For PH study, 14 and 18 variables were selected based on VIP criteria in terms of Pareto and UV scaling, respectively. Additionally, the concept and fundaments of the least absolute shrinkage and selection operator (LASSO with bootstrap procedure evaluating reproducibility of results, was demonstrated. In the RH and PH study, the LASSO selected 14 and 4 variables with reproducibility between 99.3% and 100%. However, apart from the popularity of PLS-DA and OPLS-DA methods in metabolomics, it should be highlighted that they do not control type I or type II error, but only arbitrarily establish a cut-off value for PLS-DA loadings

  12. Herbicide micropollutants in surface, ground and drinking waters within and near the area of Zagreb, Croatia.

    Science.gov (United States)

    Fingler, Sanja; Mendaš, G; Dvoršćak, M; Stipičević, S; Vasilić, Ž; Drevenkar, V

    2017-04-01

    The frequency and mass concentrations of 13 herbicide micropollutants (triazines, phenylureas, chloroacetanilides and trifluralin) were investigated during 2014 in surface, ground and drinking waters in the area of the city of Zagreb and its suburbs. Herbicide compounds were accumulated from water by solid-phase extraction using either octadecylsilica or styrene-divinylbenzene sorbent cartridges and analysed either by high-performance liquid chromatography with UV-diode array detector or gas chromatography with mass spectrometric detection. Atrazine was the most frequently detected herbicide in drinking (84 % of samples) and ground (61 % of samples) waters in mass concentrations of 5 to 68 ng L -1 . It was followed by metolachlor and terbuthylazine, the former being detected in 54 % of drinking (up to 15 ng L -1 ) and 23 % of ground (up to 100 ng L -1 ) waters, and the latter in 45 % of drinking (up to 20 ng L -1 ) and 26 % of ground (up to 25 ng L -1 ) water samples. Acetochlor was the fourth most abundant herbicide in drinking waters, detected in 32 % of samples. Its mass concentrations of 107 to 117 ng L -1 in three tap water samples were the highest of all herbicides measured in the drinking waters. The most frequently (62 % of samples) and highly (up to 887 ng L -1 ) detected herbicide in surface waters was metolachlor, followed by terbuthylazine detected in 49 % of samples in mass concentrations of up to 690 ng L -1 , and atrazine detected in 30 % of samples in mass concentrations of up to 18 ng L -1 . The seasonal variations in herbicide concentrations in surface waters were observed for terbuthylazine, metolachlor, acetochlor, chlortoluron and isoproturon with the highest concentrations measured from April to August.

  13. Pesticide fate on catchment scale: conceptual modelling of stream CSIA data

    Science.gov (United States)

    Lutz, Stefanie R.; van der Velde, Ype; Elsayed, Omniea F.; Imfeld, Gwenaël; Lefrancq, Marie; Payraudeau, Sylvain; van Breukelen, Boris M.

    2017-10-01

    Compound-specific stable isotope analysis (CSIA) has proven beneficial in the characterization of contaminant degradation in groundwater, but it has never been used to assess pesticide transformation on catchment scale. This study presents concentration and carbon CSIA data of the herbicides S-metolachlor and acetochlor from three locations (plot, drain, and catchment outlets) in a 47 ha agricultural catchment (Bas-Rhin, France). Herbicide concentrations at the catchment outlet were highest (62 µg L-1) in response to an intense rainfall event following herbicide application. Increasing δ13C values of S-metolachlor and acetochlor by more than 2 ‰ during the study period indicated herbicide degradation. To assist the interpretation of these data, discharge, concentrations, and δ13C values of S-metolachlor were modelled with a conceptual mathematical model using the transport formulation by travel-time distributions. Testing of different model setups supported the assumption that degradation half-lives (DT50) increase with increasing soil depth, which can be straightforwardly implemented in conceptual models using travel-time distributions. Moreover, model calibration yielded an estimate of a field-integrated isotopic enrichment factor as opposed to laboratory-based assessments of enrichment factors in closed systems. Thirdly, the Rayleigh equation commonly applied in groundwater studies was tested by our model for its potential to quantify degradation on catchment scale. It provided conservative estimates on the extent of degradation as occurred in stream samples. However, largely exceeding the simulated degradation within the entire catchment, these estimates were not representative of overall degradation on catchment scale. The conceptual modelling approach thus enabled us to upscale sample-based CSIA information on degradation to the catchment scale. Overall, this study demonstrates the benefit of combining monitoring and conceptual modelling of concentration

  14. Controle de plantas daninhas na cultura do milho (Zea mays L. por meio de herbicidas Weed control in maize (Zea mays L. with herbicides

    Directory of Open Access Journals (Sweden)

    C. A. L. dos Santos

    1979-12-01

    Full Text Available Com o objetivo de se verificar a ação do butylate, aplicado isoladamente e em mistura com atrazine, no controle de plantas daninhas da cultura do milho, foi instalado um experimento de campo em solo fino areno-argiloso. Foram utilizados os seguintes tratamentos: butylate a 2,80; 3,60 e 4,32 kg/ha (p.p.i.; butylate + atrazine a 3,24 + 0,80; 3,24 + 1,20 e 3,60 + 0,96 kg/ha (p.p.i.; atrazine a 3,00 kg/ha e atrazine + metolachlor a 1,40 + 2,10 kg/ha, ambos aplicados em pré-emergência e empregados como herbicidas padrão para a cultura. As plantas daninhas encontradas foram: tiririca - Cyperus rotundus L., carurú comum - .:maranthus viridis L., capim de colchão - Digitaria sanguinalis (L. Scop. e capim pé-de-galinha Eleusine indica (L. Gaertn. Butylate nas três doses apresentou-se bem contra C. rotundus e E. indica; nas doses de 3,60 e 4,32 kg foram obtidos bons resultados sobre D. sanguinalis. Butylate + atrazine controlou, nas três doses, todas as espécies incidentes, o mesmo ocorrendo com a mistura atrazine + metolachlor. Atrazine foi mais eficiente para A. viridis e E. indica. Nas condições em que foi conduzido o experimento nenhum dos herbicidas foi prejudicial para a cultura.Butylate at 2.80; 3.60 and 4.32 kg/ha and butylate + atrazine at. 3.24 + 0.80; 3.24 + 1.20 and 3.60 + 0.96 kg, were applied in preplant incorporated; atrazine at 3.00 kg and atrazine + metolachlor at 1.40 + 2.10 kg were applied in preemergence on corn. The weeds were represented by Cyperus rotundus L., Amaranthus viridis L., Digitaria sanguinalis (L. Scop. and Eleusine indica (L. Gaertn. Butylate + atrazine, in all rates, atrazine + metolachlor and atrazine gave good control of the weeds in general. Butylate, in the three rates, controlled C. rotundus and E. indica; at 3.60 and 4.32 kg/ha controlled well D. sanguinalis. The herbicides did not cause injuries to the crop.

  15. Physiological aspects and growth of sunflower after application of pre-emergent herbicides = Aspectos fisiológicos e crescimento do girassol após aplicação de herbicidas em pré-emergência.

    Directory of Open Access Journals (Sweden)

    Ronaldo Matias Reis

    2014-12-01

    Full Text Available - Studies aim to evaluate effects of different herbicides applied pre-emergence on the characteristics related to sunflower plants growth and physiology. The experiment was conducted in a greenhouse using a completely randomized design with five replications and the treatments consisted of application, sunflower pre-emergence, following herbicides: flumioxazin, sulfentrazone, oxyfluorfen, oxadiazon, s-metolachlor, linuron and pendimethalin, and an untreated control. The gas exchange was evaluated at 27 days after herbicide application (DAAs, while the analysis of growth and visual intoxication culture were measured at 50 DAAs. Evaluated the physiological characteristics were not altered by herbicides application. However, these products interfered variously related to growth of sunflower plants characteristics. While sunflower recovered from poisoning caused by the oxadiazon was noted slower growth in culture by application of flumioxazin. We conclude that at the doses evaluated in this study, the herbicide oxyfluorfen, s-metolachlor, linuron, oxadiazon and pendimethalin have potential for application in sunflower pre-emergence. = Objetivou-se com este trabalho avaliar os efeitos de diferentes herbicidas aplicados em pré-emergência sobre as características relacionadas ao crescimento e à fisiologia das plantas de girassol. O experimento foi conduzido em casa de vegetação, utilizando o delineamento inteiramente casualizado com cinco repetições, sendo os tratamentos constituídos da aplicação, em pré-emergência do girassol, dos seguintes herbicidas: flumioxazin, sulfentrazone, oxyfluorfen, oxadiazon, s-metolachlor, linuron e pendimethalin, além de uma testemunha sem aplicação. As avaliações das trocas gasosas foram realizadas aos 27 dias após a aplicação (DAAs dos herbicidas, enquanto as análises de crescimento e intoxicação visual da cultura foram mensuradas aos 50 DAAs. As características fisiológicas avaliadas n

  16. Bias analysis applied to Agricultural Health Study publications to estimate non-random sources of uncertainty.

    Science.gov (United States)

    Lash, Timothy L

    2007-11-26

    The associations of pesticide exposure with disease outcomes are estimated without the benefit of a randomized design. For this reason and others, these studies are susceptible to systematic errors. I analyzed studies of the associations between alachlor and glyphosate exposure and cancer incidence, both derived from the Agricultural Health Study cohort, to quantify the bias and uncertainty potentially attributable to systematic error. For each study, I identified the prominent result and important sources of systematic error that might affect it. I assigned probability distributions to the bias parameters that allow quantification of the bias, drew a value at random from each assigned distribution, and calculated the estimate of effect adjusted for the biases. By repeating the draw and adjustment process over multiple iterations, I generated a frequency distribution of adjusted results, from which I obtained a point estimate and simulation interval. These methods were applied without access to the primary record-level dataset. The conventional estimates of effect associating alachlor and glyphosate exposure with cancer incidence were likely biased away from the null and understated the uncertainty by quantifying only random error. For example, the conventional p-value for a test of trend in the alachlor study equaled 0.02, whereas fewer than 20% of the bias analysis iterations yielded a p-value of 0.02 or lower. Similarly, the conventional fully-adjusted result associating glyphosate exposure with multiple myleoma equaled 2.6 with 95% confidence interval of 0.7 to 9.4. The frequency distribution generated by the bias analysis yielded a median hazard ratio equal to 1.5 with 95% simulation interval of 0.4 to 8.9, which was 66% wider than the conventional interval. Bias analysis provides a more complete picture of true uncertainty than conventional frequentist statistical analysis accompanied by a qualitative description of study limitations. The latter approach is

  17. Bias analysis applied to Agricultural Health Study publications to estimate non-random sources of uncertainty

    Directory of Open Access Journals (Sweden)

    Lash Timothy L

    2007-11-01

    Full Text Available Abstract Background The associations of pesticide exposure with disease outcomes are estimated without the benefit of a randomized design. For this reason and others, these studies are susceptible to systematic errors. I analyzed studies of the associations between alachlor and glyphosate exposure and cancer incidence, both derived from the Agricultural Health Study cohort, to quantify the bias and uncertainty potentially attributable to systematic error. Methods For each study, I identified the prominent result and important sources of systematic error that might affect it. I assigned probability distributions to the bias parameters that allow quantification of the bias, drew a value at random from each assigned distribution, and calculated the estimate of effect adjusted for the biases. By repeating the draw and adjustment process over multiple iterations, I generated a frequency distribution of adjusted results, from which I obtained a point estimate and simulation interval. These methods were applied without access to the primary record-level dataset. Results The conventional estimates of effect associating alachlor and glyphosate exposure with cancer incidence were likely biased away from the null and understated the uncertainty by quantifying only random error. For example, the conventional p-value for a test of trend in the alachlor study equaled 0.02, whereas fewer than 20% of the bias analysis iterations yielded a p-value of 0.02 or lower. Similarly, the conventional fully-adjusted result associating glyphosate exposure with multiple myleoma equaled 2.6 with 95% confidence interval of 0.7 to 9.4. The frequency distribution generated by the bias analysis yielded a median hazard ratio equal to 1.5 with 95% simulation interval of 0.4 to 8.9, which was 66% wider than the conventional interval. Conclusion Bias analysis provides a more complete picture of true uncertainty than conventional frequentist statistical analysis accompanied by a

  18. Multiple stressor effects in Chlamydomonas reinhardtii--toward understanding mechanisms of interaction between effects of ultraviolet radiation and chemical pollutants.

    Science.gov (United States)

    Korkaric, Muris; Behra, Renata; Fischer, Beat B; Junghans, Marion; Eggen, Rik I L

    2015-05-01

    The effects of chemical pollutants and environmental stressors, such as ultraviolet radiation (UVR), can interact when organisms are simultaneously exposed, resulting in higher (synergistic) or lower (antagonistic) multiple stressor effects than expected based on the effects of single stressors. Current understanding of interactive effects is limited due to a lack of mechanism-based multiple stressor studies. It has been hypothesized that effect interactions may generally occur if chemical and non-chemical stressors cause similar physiological effects in the organism. To test this hypothesis, we exposed the model green alga Chlamydomonas reinhardtii to combinations of UVR and single chemicals displaying modes of action (MOA) similar or dissimilar to the impact of UVR on photosynthesis. Stressor interactions were analyzed based on the independent action model. Effect interactions were found to depend on the MOA of the chemicals, and also on their concentrations, the exposure time and the measured endpoint. Indeed, only chemicals assumed to cause effects on photosynthesis similar to UVR showed interactions with UVR on photosynthetic yield: synergistic in case of Cd(II) and paraquat and antagonistic in case of diuron. No interaction on photosynthesis was observed for S-metolachlor, which acts dissimilarly to UVR. However, combined effects of S-metolachlor and UVR on algal reproduction were synergistic, highlighting the importance of considering additional MOA of UVR. Possible mechanisms of stressor effect interactions are discussed. Copyright © 2015 Elsevier B.V. All rights reserved.

  19. Growth, production and quality of pineapple in response to herbicide use

    Directory of Open Access Journals (Sweden)

    Leonardo Carvalho Brant Maia

    2012-09-01

    Full Text Available In pineapple fields, weed competition is exacerbated by the fact that the crop is small and has a very slow vegetative development. The objective of this study was to determine the effects of herbicides on growth, yield and quality of pineapple, cultivar 'Pérola'. The experimental design was in randomized blocks with four treatments and four replications. Treatments consisted of weeding by hoe and the herbicides diuron; fluazifop-p-butyl and atrazine + S-metolachlor applied in post-emergence. The characteristics evaluated monthly during the vegetative stage were stem diameter, D-leaf length, number of leaves, number of emitted leaves and percentage of natural floral induction. In the reproductive phase, evaluations were made of average fruit weight (g with and without crown, fruits length and diameter, number of slip, slip-sucker and sucker type seedlings, determination of soluble solids and pH in the pulp. There was no effect of herbicide treatment on the vegetative growth characteristics. Stem diameter increased until 330 days after planting, showing a decrease after this period. The D-leaf grew over time in all treatments, although phytotoxicity symptoms were observed after the first application of herbicides. The traits evaluated on the reproductive phase showed no significant differences in response to treatments. Therefore, the use of diuron fluazifop-p-butyl and atrazine + S-metolachlor did not affect growth, yield and fruit quality of pineapple, cultivar 'Pérola'.

  20. Toxicity of pesticides associated with potato production, including soil fumigants, to snapping turtle eggs (Chelydra serpentina).

    Science.gov (United States)

    de Solla, Shane Raymond; Palonen, Kimberley Elizabeth; Martin, Pamela Anne

    2014-01-01

    Turtles frequently oviposit in soils associated with agriculture and, thus, may be exposed to pesticides or fertilizers. The toxicity of a pesticide regime that is used for potato production in Ontario on the survivorship of snapping turtle (Chelydra serpentina) eggs was evaluated. The following treatments were applied to clean soil: 1) a mixture of the pesticides chlorothalonil, S-metolachlor, metribuzin, and chlorpyrifos, and 2) the soil fumigant metam sodium. Turtle eggs were incubated in soil in outdoor plots in which these mixtures were applied at typical and higher field application rates, where the eggs were subject to ambient temperature and weather conditions. The pesticide mixture consisting of chlorothalonil, S-metolachlor, metribuzin, and chlorpyrifos did not affect survivorship, deformities, or body size at applications up to 10 times the typical field application rates. Hatching success ranged between 87% and 100% for these treatments. Metam sodium was applied at 0.1¯ times, 0.3¯ times, 1 times, and 3 times field application rates. Eggs exposed to any application of metam sodium had 100% mortality. At typical field application rates, the chemical regime associated with potato production does not appear to have any detrimental impacts on turtle egg development, except for the use of the soil fumigant metam sodium, which is highly toxic to turtle eggs at the lowest recommended application rate. © 2013 SETAC.

  1. Herbicides and nitrates in groundwater of Maryland and childhood cancers: a geographic information systems approach.

    Science.gov (United States)

    Thorpe, Nancy; Shirmohammadi, Adel

    2005-01-01

    This hypothesis-generating study explores spatial patterns of childhood cancers in Maryland and investigates their potential associations with herbicides and nitrates in groundwater. The Maryland Cancer Registry (MCR) provided data for bone and brain cancers, leukemia, and lymphoma, for ages 0-17, during the years 1992-1998. Cancer clusters and relative risks generated in the study indicate higher relative risk areas and potential clusters in several counties. Contingency table analysis indicates a potential association with several herbicides and nitrates. Cancer rates for the four types have a crude odds ratio (OR) = 1.10 (0.78-1.56) in relationship to atrazine, and an OR = 1.54 (1.14-2.07) for metolachlor. Potential association to mixtures of three compounds give an OR = 7.56 (4.16-13.73). A potential association is indicated between leukemia and nitrates, OR = 1.81 (1.35-2.42), and bone cancer with metolachlor, OR = 2.26 (0.97-5.24). These results give insight to generate a hypothesis of the potential association between exposure to these herbicides and nitrates and specific types of childhood cancer.

  2. Effect of some herbicides on weeds and vines in mother plantation of Cabernet sauvignon

    Directory of Open Access Journals (Sweden)

    N.Prodanova-Marinova

    2016-09-01

    Full Text Available Abstract. To maintain soil surface clean of weeds in the parent vineyard for producing cuttings for scions, the efficiency and selectivity of Gardoprim plus Gold (312.5 g/l s-metolachlor + 187.5 g/l terbuthylazine, Wing P (pendimethalin 250 g/l + dimethenamid P 212.5 g/l and Lumax 538 SC (375 g/l s-metolachlor + 125 g/l terbuthylazine + 337.5 g/l mesotrione at doses of 0.4 and 0.6 l/da was studied. Lumax 538 SC, Wing P and Gardoprim Plus Gold controlling efficiently annual weeds established in parent vineyard, except Xanthium strumarium L.. Lumax 538 SC and Gardoprim plus Gold showed long-term (90 days activity. Wing P activity decreases after the thirtieth day. The tested herbicides do not damage the buds and do not lead to a reduction of shoots developed from them. Lumax 538 SC and Gardoprim plus Gold at doses of 0.4 and 0.6 l/da and Wing P at dose of 0.4 l/da do not inhibit the growth of shoots. The largest number of cuttings for scions were obtained after treatment with Lumax 538 SC.

  3. Leaching of the Neonicotinoids Thiamethoxam and Imidacloprid from Sugar Beet Seed Dressings to Subsurface Tile Drains.

    Science.gov (United States)

    Wettstein, Felix E; Kasteel, Roy; Garcia Delgado, Maria F; Hanke, Irene; Huntscha, Sebastian; Balmer, Marianne E; Poiger, Thomas; Bucheli, Thomas D

    2016-08-24

    Pesticide transport from seed dressings toward subsurface tile drains is still poorly understood. We monitored the neonicotinoid insecticides imidacloprid and thiamethoxam from sugar beet seed dressings in flow-proportional drainage water samples, together with spray applications of bromide and the herbicide S-metolachlor in spring and the fungicides epoxiconazole and kresoxim-methyl in summer. Event-driven, high first concentration maxima up to 2830 and 1290 ng/L for thiamethoxam and imidacloprid, respectively, were followed by an extended period of tailing and suggested preferential flow. Nevertheless, mass recoveries declined in agreement with the degradation and sorption properties collated in the groundwater ubiquity score, following the order bromide (4.9%), thiamethoxam (1.2%), imidacloprid (0.48%), kresoxim-methyl acid (0.17%), S-metolachlor (0.032%), epoxiconazole (0.013%), and kresoxim-methyl (0.003%), and indicated increased leaching from seed dressings compared to spray applications. Measured concentrations and mass recoveries indicate that subsurface tile drains contribute to surface water contamination with neonicotinoids from seed dressings.

  4. Data worth and prediction uncertainty for pesticide transport and fate models in Nebraska and Maryland, United States

    Science.gov (United States)

    Nolan, Bernard T.; Malone, Robert W.; Doherty, John E.; Barbash, Jack E.; Ma, Liwang; Shaner, Dale L.

    2015-01-01

    BACKGROUND Complex environmental models are frequently extrapolated to overcome data limitations in space and time, but quantifying data worth to such models is rarely attempted. The authors determined which field observations most informed the parameters of agricultural system models applied to field sites in Nebraska (NE) and Maryland (MD), and identified parameters and observations that most influenced prediction uncertainty. RESULTS The standard error of regression of the calibrated models was about the same at both NE (0.59) and MD (0.58), and overall reductions in prediction uncertainties of metolachlor and metolachlor ethane sulfonic acid concentrations were 98.0 and 98.6% respectively. Observation data groups reduced the prediction uncertainty by 55–90% at NE and by 28–96% at MD. Soil hydraulic parameters were well informed by the observed data at both sites, but pesticide and macropore properties had comparatively larger contributions after model calibration. CONCLUSIONS Although the observed data were sparse, they substantially reduced prediction uncertainty in unsampled regions of pesticide breakthrough curves. Nitrate evidently functioned as a surrogate for soil hydraulic data in well-drained loam soils conducive to conservative transport of nitrogen. Pesticide properties and macropore parameters could most benefit from improved characterization further to reduce model misfit and prediction uncertainty.   

  5. Weed Control and Peanut Tolerance with Ethalfluralin-Based Herbicide Systems

    Directory of Open Access Journals (Sweden)

    W. J. Grichar

    2012-01-01

    Full Text Available Field studies were conducted from 2007 through 2009 to determine weed efficacy and peanut (Arachis hypogaea L. response to herbicide systems that included ethalfluralin applied preplant incorporated. Control of devil's claw (Proboscidea louisianica (Mill. Thellung, yellow nutsedge (Cyperus esculentus L., Palmer amaranth (Amaranthus palmeri S. Wats., and puncturevine (Tribulus terrestris L. was most consistent with ethalfluralin followed by either imazapic or imazethapyr applied postemergence. Peanut stunting was 19% when paraquat alone was applied early-postemergence. Stunting increased to greater than 30% when ethalfluralin applied preplant incorporated was followed by S-metolachlor applied preemergence and paraquat applied early-postemergence. Stunting (7% was also observed when ethalfluralin was followed by flumioxazin plus S-metolachlor applied preemergence with lactofen applied mid-postemergence. Ethalfluralin followed by paraquat applied early-postemergence reduced peanut yield when compared to the nontreated check. Ethalfluralin applied preplant incorporated followed by imazapic applied mid-postemergence provided the greatest yield (6220 kg/ha. None of the herbicide treatments reduced peanut grade (sound mature kernels plus sound splits when compared with the nontreated check.

  6. Influence of light, UV-B radiation, and herbicides on wax biosynthesis of cucumber seedlings

    International Nuclear Information System (INIS)

    Tevini, M.; Steinmüller, D.

    1987-01-01

    The behavior of cuticular alkane-1-ols and alkanes were studied in different developmental stages of cucumber seedlings grown in the dark or under white light, with or without UV-B radiation or in presence of wax biosynthesis inhibitors, trichloroacetic acid and metolachlor. Accumulation of alkane-1-ols increased light independently with seedling age. Synthesis of alkanes was strictly light and dose dependent. Addition of UV-B radiation did not alter the amounts of alkanes or alcohols, however, the distribution of homologues was shifted towards shorter chain homologues. Treatments with Cl 3 AcOH resulted in strong inhibition of alkane accumulation, whereas the amount of alkane-1-ols was changed neither at low nor at moderate concentrations of Cl 3 AcOH but their homologue distribution shifted towards longer chain lengths. This shifting was depressed in the presence of UV-B. At high concentrations of Cl 3 Ac0H similar homologue distributions as produced by UV-B (shift to shorter homologues) were observed. Metolachlor treatment resulted in an inhibition of alkane-1-ol production connected with rising amounts of alkanes, predominantly of short chain species. A simple model of wax biosynthesis is proposed which describes the interactions with white light, UV-B radiation and herbicides. (author)

  7. Civil migration and risk assessment methodology

    International Nuclear Information System (INIS)

    Onishi, Y.; Brown, S.M.; Olsen, A.R.; Parkhurst, M.A.

    1981-01-01

    To provide a scientific basis for risk assessment and decision making, the Chemical Migration and Risk Assessment (CMRA) Methodology was developed to simulate overland and instream toxic containment migration and fate, and to predict the probability of acute and chronic impacts on aquatic biota. The simulation results indicated that the time between the pesticide application and the subsequent runoff producing event was the most important factor determining the amount of the alachlor. The study also revealed that sediment transport has important effects on contaminant migration when sediment concentrations in receiving streams are high or contaminants are highly susceptible to adsorption by sediment. Although the capabilities of the CMRA methodology were only partially tested in this study, the results demonstrate that methodology can be used as a scientific decision-making tool for toxic chemical regulations, a research tool to evaluate the relative significance of various transport and degradation phenomena, as well as a tool to examine the effectiveness of toxic chemical control practice

  8. Organomineral Interactions and Herbicide Sorption in Brazilian Tropical and Subtropical Oxisols under No-Tillage.

    Science.gov (United States)

    Bonfleur, Eloana J; Kookana, Rai S; Tornisielo, Valdemar L; Regitano, Jussara B

    2016-05-25

    We evaluated the effects of the soil organic matter (SOM) composition, distribution between soil aggregates size, and their interactions with the mineral phase on herbicide sorption (alachlor, bentazon, and imazethapyr) in tropical and subtropical Oxisols under no-till systems (NT). Using soil physical fractionation approach, sorption experiments were performed on whole soils and their aggregates. SOM chemistry was assessed by CP/MAS (13)C NMR. The lower sorption observed in tropical soils was attributed to the greater blockage of SOM sorption sites than in subtropical soils. When these sites were exposed upon physical fractionation, sorption of the three herbicides in tropical soils increased, especially for imazethapyr. High amounts of poorly crystallized sesquioxides in these soils may have contributed to masking of sorption sites, indicating that organomineral interactions may lead to blockage of sorption sites on SOM in tropical soils.

  9. Extraction of acetanilides in rice using ionic liquid-based matrix solid phase dispersion-solvent flotation.

    Science.gov (United States)

    Zhang, Liyuan; Wang, Changyuan; Li, Zuotong; Zhao, Changjiang; Zhang, Hanqi; Zhang, Dongjie

    2018-04-15

    Ionic liquid-based matrix solid phase dispersion-solvent flotation coupled with high performance liquid chromatography was developed for the determination of the acetanilide herbicides, including metazachlor, propanil, alachlor, propisochlor, pretilachlor, and butachlor in rice samples. Some experimental parameters, including the type of dispersant, the mass ratio of dispersant to sample, pH of sample solution, the type of extraction solvent, the type of ionic liquid, flotation time, and flow rate of N 2 were optimized. The average recoveries of the acetanilide herbicides at spiked concentrations of 50, 125, and 250 µg/kg ranged from 89.4% to 108.7%, and relative standard deviations were equal to or lower than 7.1%, the limits of quantification were in the range of 38.0 to 84.7 µg/kg. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Solar photocatalytic degradation and detoxification of EU priority substances

    Energy Technology Data Exchange (ETDEWEB)

    Hincapie, M. [Facultad de Ingeniera Ambiental, Universidad de Medellin, Carrera 87 No. 30-65, P.O. Box 1983, Medellin (Colombia); Maldonado, M.I.; Oller, I.; Gernjak, W.; Malato, S. [Plataforma Solar de Almeria-CIEMAT, Carretera Senes km4, 04200 Tabernas (Almeria) (Spain); Sanchez-Perez, J.A.; Ballesteros, M.M. [Departamento de Ingenieria Quimica, Universidad de Almeria Crta de Sacramento s/n, 04120 Almeria (Spain)

    2005-04-15

    Several different pesticides (alachlor, atrazine, chlorfenvinphos, diuron, isoproturon and pentachlorophenol) considered PS (priority substances) by the European Commission and dissolved in water at 50mg/L (or at maximum water solubility) have been degraded at pilot-plant scale using photo-Fenton and TiO{sub 2} photocatalysis driven by solar energy. Two different iron concentrations (2 and 55mg/L) and TiO{sub 2} at 200mg/L have been tested and discussed, using mainly TOC mineralisation for comparison of treatment effectiveness. Vibrio fischeri (Microtox{sup (}R)) toxicity assays were also employed for evaluating the photocatalytic treatments, and comparison between these results and parent compound disappearance, TOC evolution and anion (or ammonia) release were discussed. Almost complete mineralisation and total detoxification were always attained. It has been demonstrated that evolution of chloride could be a key-parameter for predicting toxicity of chlorinated compounds.

  11. Genomic Prediction Accuracy for Resistance Against Piscirickettsia salmonis in Farmed Rainbow Trout

    Directory of Open Access Journals (Sweden)

    Grazyella M. Yoshida

    2018-02-01

    Full Text Available Salmonid rickettsial syndrome (SRS, caused by the intracellular bacterium Piscirickettsia salmonis, is one of the main diseases affecting rainbow trout (Oncorhynchus mykiss farming. To accelerate genetic progress, genomic selection methods can be used as an effective approach to control the disease. The aims of this study were: (i to compare the accuracy of estimated breeding values using pedigree-based best linear unbiased prediction (PBLUP with genomic BLUP (GBLUP, single-step GBLUP (ssGBLUP, Bayes C, and Bayesian Lasso (LASSO; and (ii to test the accuracy of genomic prediction and PBLUP using different marker densities (0.5, 3, 10, 20, and 27 K for resistance against P. salmonis in rainbow trout. Phenotypes were recorded as number of days to death (DD and binary survival (BS from 2416 fish challenged with P. salmonis. A total of 1934 fish were genotyped using a 57 K single-nucleotide polymorphism (SNP array. All genomic prediction methods achieved higher accuracies than PBLUP. The relative increase in accuracy for different genomic models ranged from 28 to 41% for both DD and BS at 27 K SNP. Between different genomic models, the highest relative increase in accuracy was obtained with Bayes C (∼40%, where 3 K SNP was enough to achieve a similar accuracy to that of the 27 K SNP for both traits. For resistance against P. salmonis in rainbow trout, we showed that genomic predictions using GBLUP, ssGBLUP, Bayes C, and LASSO can increase accuracy compared with PBLUP. Moreover, it is possible to use relatively low-density SNP panels for genomic prediction without compromising accuracy predictions for resistance against P. salmonis in rainbow trout.

  12. Improved intact soil-core carbon determination applying regression shrinkage and variable selection techniques to complete spectrum laser-induced breakdown spectroscopy (LIBS).

    Science.gov (United States)

    Bricklemyer, Ross S; Brown, David J; Turk, Philip J; Clegg, Sam M

    2013-10-01

    Laser-induced breakdown spectroscopy (LIBS) provides a potential method for rapid, in situ soil C measurement. In previous research on the application of LIBS to intact soil cores, we hypothesized that ultraviolet (UV) spectrum LIBS (200-300 nm) might not provide sufficient elemental information to reliably discriminate between soil organic C (SOC) and inorganic C (IC). In this study, using a custom complete spectrum (245-925 nm) core-scanning LIBS instrument, we analyzed 60 intact soil cores from six wheat fields. Predictive multi-response partial least squares (PLS2) models using full and reduced spectrum LIBS were compared for directly determining soil total C (TC), IC, and SOC. Two regression shrinkage and variable selection approaches, the least absolute shrinkage and selection operator (LASSO) and sparse multivariate regression with covariance estimation (MRCE), were tested for soil C predictions and the identification of wavelengths important for soil C prediction. Using complete spectrum LIBS for PLS2 modeling reduced the calibration standard error of prediction (SEP) 15 and 19% for TC and IC, respectively, compared to UV spectrum LIBS. The LASSO and MRCE approaches provided significantly improved calibration accuracy and reduced SEP 32-55% over UV spectrum PLS2 models. We conclude that (1) complete spectrum LIBS is superior to UV spectrum LIBS for predicting soil C for intact soil cores without pretreatment; (2) LASSO and MRCE approaches provide improved calibration prediction accuracy over PLS2 but require additional testing with increased soil and target analyte diversity; and (3) measurement errors associated with analyzing intact cores (e.g., sample density and surface roughness) require further study and quantification.

  13. Genome-Wide Association Studies and Comparison of Models and Cross-Validation Strategies for Genomic Prediction of Quality Traits in Advanced Winter Wheat Breeding Lines

    Directory of Open Access Journals (Sweden)

    Peter S. Kristensen

    2018-02-01

    Full Text Available The aim of the this study was to identify SNP markers associated with five important wheat quality traits (grain protein content, Zeleny sedimentation, test weight, thousand-kernel weight, and falling number, and to investigate the predictive abilities of GBLUP and Bayesian Power Lasso models for genomic prediction of these traits. In total, 635 winter wheat lines from two breeding cycles in the Danish plant breeding company Nordic Seed A/S were phenotyped for the quality traits and genotyped for 10,802 SNPs. GWAS were performed using single marker regression and Bayesian Power Lasso models. SNPs with large effects on Zeleny sedimentation were found on chromosome 1B, 1D, and 5D. However, GWAS failed to identify single SNPs with significant effects on the other traits, indicating that these traits were controlled by many QTL with small effects. The predictive abilities of the models for genomic prediction were studied using different cross-validation strategies. Leave-One-Out cross-validations resulted in correlations between observed phenotypes corrected for fixed effects and genomic estimated breeding values of 0.50 for grain protein content, 0.66 for thousand-kernel weight, 0.70 for falling number, 0.71 for test weight, and 0.79 for Zeleny sedimentation. Alternative cross-validations showed that the genetic relationship between lines in training and validation sets had a bigger impact on predictive abilities than the number of lines included in the training set. Using Bayesian Power Lasso instead of GBLUP models, gave similar or slightly higher predictive abilities. Genomic prediction based on all SNPs was more effective than prediction based on few associated SNPs.

  14. T2L2 on JASON-2: First Evaluation of the Flying Model

    Science.gov (United States)

    2007-01-01

    Para, J.-M. Torre R&D Metrology CNRS/GEMINI Observatoire de la Côte d’Azur Caussol, France E-mail: philippe.guillemot@cnes.fr Abstract...Laser Link” experiment T2L2 [1], under development at OCA (Observatoire de la Côte d’Azur) and CNES (Centre National d’Etudes Spatiales), France, will be...Experimental Astronomy, 7, 191-207. [2] P. Fridelance and C. Veillet, 1995, “Operation and data analysis in the LASSO experiment,” Metrologia

  15. Diffusion Indexes with Sparse Loadings

    DEFF Research Database (Denmark)

    Kristensen, Johannes Tang

    The use of large-dimensional factor models in forecasting has received much attention in the literature with the consensus being that improvements on forecasts can be achieved when comparing with standard models. However, recent contributions in the literature have demonstrated that care needs...... to the problem by using the LASSO as a variable selection method to choose between the possible variables and thus obtain sparse loadings from which factors or diffusion indexes can be formed. This allows us to build a more parsimonious factor model which is better suited for forecasting compared...... it to be an important alternative to PC....

  16. Do Red Edge and Texture Attributes from High-Resolution Satellite Data Improve Wood Volume Estimation in a Semi-Arid Mountainous Region?

    DEFF Research Database (Denmark)

    Schumacher, Paul; Mislimshoeva, Bunafsha; Brenning, Alexander

    2016-01-01

    to overcome this issue. However, clear recommendations on the suitability of specific proxies to provide accurate biomass information in semi-arid to arid environments are still lacking. This study contributes to the understanding of using multispectral high-resolution satellite data (RapidEye), specifically...... red edge and texture attributes, to estimate wood volume in semi-arid ecosystems characterized by scarce vegetation. LASSO (Least Absolute Shrinkage and Selection Operator) and random forest were used as predictive models relating in situ-measured aboveground standing wood volume to satellite data...

  17. Coupling bacterioplankton populations and environment to community function in coastal temperate waters

    DEFF Research Database (Denmark)

    Traving, S. J.; Bentzon-Tilia, Mikkel; Knudsen-Leerbeck, H.

    2016-01-01

    drivers of bacterioplankton community functions, taking into account the variability in community composition and environmental conditions over seasons, in two contrasting coastal systems. A Least Absolute Shrinkage and Selection Operator (LASSO) analysis of the biological and chemical data obtained from...... surface waters over a full year indicated that specific bacterial populations were linked to measured functions. Namely, Synechococcus (Cyanobacteria) was strongly correlated with protease activity. Both function and community composition showed seasonal variation. However, the pattern of substrate...... of common drivers of bacterioplankton community functions in two different systems indicates that the drivers may be of broader relevance in coastal temperate waters....

  18. Efficient Selection of Multiple Objects on a Large Scale

    DEFF Research Database (Denmark)

    Stenholt, Rasmus

    2012-01-01

    The task of multiple object selection (MOS) in immersive virtual environments is important and still largely unexplored. The diffi- culty of efficient MOS increases with the number of objects to be selected. E.g. in small-scale MOS, only a few objects need to be simultaneously selected. This may...... consuming. Instead, we have implemented and tested two of the existing approaches to 3-D MOS, a brush and a lasso, as well as a new technique, a magic wand, which automati- cally selects objects based on local proximity to other objects. In a formal user evaluation, we have studied how the performance...

  19. Guía docente para desarrollo de destrezas lectoras en estudiantes de séptimo año de educación básica intercultural biblingüe en el CECIB "Tarquino Idrobo" de la comunidad de Ucsha parroquia San Pablo, año 2011.

    OpenAIRE

    Yánez Colta, María Cristina

    2012-01-01

    El Centro Educativo Comunitario Intercultural Bilingüe (CECIB), que está ubicado en la Comunidad Primavera Ucsha, Parroquia San Pablo Cantón Otavalo, Provincia Imbabura, dicha institución ha laborado hace aproximadamente 40 años en las casa de hacienda del señor Galo Plaza Lasso, de quien el Sr. Tarquino Idrobo fue amigo e ilustre colaborador, razón por la cual se crea la escuela con el nombre de Tarquino Idrobo vista la necesidad del bienestar de la gente indígena de esta comunidad. En es...

  20. Robust estimation of the expected survival probabilities from high-dimensional Cox models with biomarker-by-treatment interactions in randomized clinical trials

    Directory of Open Access Journals (Sweden)

    Nils Ternès

    2017-05-01

    Full Text Available Abstract Background Thanks to the advances in genomics and targeted treatments, more and more prediction models based on biomarkers are being developed to predict potential benefit from treatments in a randomized clinical trial. Despite the methodological framework for the development and validation of prediction models in a high-dimensional setting is getting more and more established, no clear guidance exists yet on how to estimate expected survival probabilities in a penalized model with biomarker-by-treatment interactions. Methods Based on a parsimonious biomarker selection in a penalized high-dimensional Cox model (lasso or adaptive lasso, we propose a unified framework to: estimate internally the predictive accuracy metrics of the developed model (using double cross-validation; estimate the individual survival probabilities at a given timepoint; construct confidence intervals thereof (analytical or bootstrap; and visualize them graphically (pointwise or smoothed with spline. We compared these strategies through a simulation study covering scenarios with or without biomarker effects. We applied the strategies to a large randomized phase III clinical trial that evaluated the effect of adding trastuzumab to chemotherapy in 1574 early breast cancer patients, for which the expression of 462 genes was measured. Results In our simulations, penalized regression models using the adaptive lasso estimated the survival probability of new patients with low bias and standard error; bootstrapped confidence intervals had empirical coverage probability close to the nominal level across very different scenarios. The double cross-validation performed on the training data set closely mimicked the predictive accuracy of the selected models in external validation data. We also propose a useful visual representation of the expected survival probabilities using splines. In the breast cancer trial, the adaptive lasso penalty selected a prediction model with 4

  1. The role of personality, disability and physical activity in the development of medication-overuse headache: a prospective observational study.

    Science.gov (United States)

    Mose, Louise S; Pedersen, Susanne S; Debrabant, Birgit; Jensen, Rigmor H; Gram, Bibi

    2018-05-25

    Factors associated with development of medication-overuse headache (MOH) in migraine patients are not fully understood, but with respect to prevention, the ability to predict the onset of MOH is clinically important. The aims were to examine if personality characteristics, disability and physical activity level are associated with the onset of MOH in a group of migraine patients and explore to which extend these factors combined can predict the onset of MOH. The study was a single-center prospective observational study of migraine patients. At inclusion, all patients completed questionnaires evaluating 1) personality (NEO Five-Factor Inventory), 2) disability (Migraine Disability Assessment), and 3) physical activity level (Physical Activity Scale 2.1). Diagnostic codes from patients' electronic health records confirmed if they had developed MOH during the study period of 20 months. Analyses of associations were performed and to identify which of the variables predict onset MOH, a multivariable least absolute shrinkage and selection operator (LASSO) logistic regression model was fitted to predict presence or absence of MOH. Out of 131 participants, 12 % (n=16) developed MOH. Migraine disability score (OR=1.02, 95 % CI: 1.00 to 1.04), intensity of headache (OR=1.49, 95 % CI: 1.03 to 2.15) and headache frequency (OR=1.02, 95 % CI: 1.00 to 1.04) were associated with the onset of MOH adjusting for age and gender. To identify which of the variables predict onset MOH, we used a LASSO regression model, and evaluating the predictive performance of the LASSO-mode (containing the predictors MIDAS score, MIDAS-intensity and -frequency, neuroticism score, time with moderate physical activity, educational level, hours of sleep daily and number of contacts to the headache clinic) in terms of area under the curve (AUC) was weak (apparent AUC=0.62, 95% CI: 0.41-0.82). Disability, headache intensity and frequency were associated with the onset of MOH whereas personality and the

  2. Realizing a Clean Energy Future: Highlights of NREL Analysis (Brochure)

    Energy Technology Data Exchange (ETDEWEB)

    2013-12-01

    Profound energy system transformation is underway. In Hawaiian mythology, Maui set out to lasso the sun in order to capture its energy. He succeeded. That may have been the most dramatic leap forward in clean energy systems that the world has known. Until now. Today, another profound transformation is underway. A combination of forces is taking us from a carbon-centric, inefficient energy system to one that draws from diverse energy sources - including the sun. NREL analysis is helping guide energy systems policy and investment decisions through this transformation. This brochure highlights NREL analysis accomplishments in the context of four thematic storylines.

  3. Regression and Sparse Regression Methods for Viscosity Estimation of Acid Milk From it’s Sls Features

    DEFF Research Database (Denmark)

    Sharifzadeh, Sara; Skytte, Jacob Lercke; Nielsen, Otto Højager Attermann

    2012-01-01

    Statistical solutions find wide spread use in food and medicine quality control. We investigate the effect of different regression and sparse regression methods for a viscosity estimation problem using the spectro-temporal features from new Sub-Surface Laser Scattering (SLS) vision system. From...... with sparse LAR, lasso and Elastic Net (EN) sparse regression methods. Due to the inconsistent measurement condition, Locally Weighted Scatter plot Smoothing (Loess) has been employed to alleviate the undesired variation in the estimated viscosity. The experimental results of applying different methods show...

  4. Evaluation of digital soil mapping approaches with large sets of environmental covariates

    Science.gov (United States)

    Nussbaum, Madlene; Spiess, Kay; Baltensweiler, Andri; Grob, Urs; Keller, Armin; Greiner, Lucie; Schaepman, Michael E.; Papritz, Andreas

    2018-01-01

    The spatial assessment of soil functions requires maps of basic soil properties. Unfortunately, these are either missing for many regions or are not available at the desired spatial resolution or down to the required soil depth. The field-based generation of large soil datasets and conventional soil maps remains costly. Meanwhile, legacy soil data and comprehensive sets of spatial environmental data are available for many regions. Digital soil mapping (DSM) approaches relating soil data (responses) to environmental data (covariates) face the challenge of building statistical models from large sets of covariates originating, for example, from airborne imaging spectroscopy or multi-scale terrain analysis. We evaluated six approaches for DSM in three study regions in Switzerland (Berne, Greifensee, ZH forest) by mapping the effective soil depth available to plants (SD), pH, soil organic matter (SOM), effective cation exchange capacity (ECEC), clay, silt, gravel content and fine fraction bulk density for four soil depths (totalling 48 responses). Models were built from 300-500 environmental covariates by selecting linear models through (1) grouped lasso and (2) an ad hoc stepwise procedure for robust external-drift kriging (georob). For (3) geoadditive models we selected penalized smoothing spline terms by component-wise gradient boosting (geoGAM). We further used two tree-based methods: (4) boosted regression trees (BRTs) and (5) random forest (RF). Lastly, we computed (6) weighted model averages (MAs) from the predictions obtained from methods 1-5. Lasso, georob and geoGAM successfully selected strongly reduced sets of covariates (subsets of 3-6 % of all covariates). Differences in predictive performance, tested on independent validation data, were mostly small and did not reveal a single best method for 48 responses. Nevertheless, RF was often the best among methods 1-5 (28 of 48 responses), but was outcompeted by MA for 14 of these 28 responses. RF tended to over

  5. Allele frequency changes due to hitch-hiking in genomic selection programs

    DEFF Research Database (Denmark)

    Liu, Huiming; Sørensen, Anders Christian; Meuwissen, Theo H E

    2014-01-01

    of inbreeding due to changes in allele frequencies and hitch-hiking. This study aimed at understanding the impact of using long-term genomic selection on changes in allele frequencies, genetic variation and the level of inbreeding. Methods Selection was performed in simulated scenarios with a population of 400......-BLUP, Genomic BLUP and Bayesian Lasso. Changes in allele frequencies at QTL, markers and linked neutral loci were investigated for the different selection criteria and different scenarios, along with the loss of favourable alleles and the rate of inbreeding measured by pedigree and runs of homozygosity. Results...

  6. Asymptotically Honest Confidence Regions for High Dimensional

    DEFF Research Database (Denmark)

    Caner, Mehmet; Kock, Anders Bredahl

    While variable selection and oracle inequalities for the estimation and prediction error have received considerable attention in the literature on high-dimensional models, very little work has been done in the area of testing and construction of confidence bands in high-dimensional models. However...... develop an oracle inequality for the conservative Lasso only assuming the existence of a certain number of moments. This is done by means of the Marcinkiewicz-Zygmund inequality which in our context provides sharper bounds than Nemirovski's inequality. As opposed to van de Geer et al. (2014) we allow...

  7. Model selection emphasises the importance of non-chromosomal information in genetic studies.

    Directory of Open Access Journals (Sweden)

    Reda Rawi

    Full Text Available Ever since the case of the missing heritability was highlighted some years ago, scientists have been investigating various possible explanations for the issue. However, none of these explanations include non-chromosomal genetic information. Here we describe explicitly how chromosomal and non-chromosomal modifiers collectively influence the heritability of a trait, in this case, the growth rate of yeast. Our results show that the non-chromosomal contribution can be large, adding another dimension to the estimation of heritability. We also discovered, combining the strength of LASSO with model selection, that the interaction of chromosomal and non-chromosomal information is essential in describing phenotypes.

  8. The validation and assessment of machine learning: a game of prediction from high-dimensional data

    DEFF Research Database (Denmark)

    Pers, Tune Hannes; Albrechtsen, A; Holst, C

    2009-01-01

    In applied statistics, tools from machine learning are popular for analyzing complex and high-dimensional data. However, few theoretical results are available that could guide to the appropriate machine learning tool in a new application. Initial development of an overall strategy thus often...... the ideas, the game is applied to data from the Nugenob Study where the aim is to predict the fat oxidation capacity based on conventional factors and high-dimensional metabolomics data. Three players have chosen to use support vector machines, LASSO, and random forests, respectively....

  9. Seletividade de herbicidas pós-emergentes aplicados na soja geneticamente modificada Selectivity of post-emergence herbicides applied on genetically modified soybeans

    Directory of Open Access Journals (Sweden)

    M.E.F. Neto

    2009-06-01

    Full Text Available O experimento foi instalado em área de plantio comercial de soja Roundup Ready®, na região do Pontal do Paranapanema, no município de Euclides da Cunha Paulista-SP, localizada a 20º 43' 11'' S e 50º 10' 20'' W, com uma altitude de 270 m. A fase experimental foi conduzida de dezembro de 2006 a abril de 2007, sob sistema plantio direto, com uma temperatura média de 25 ºC e índice pluviométrico de 800 mm. O solo da área experimental apresenta classe textural franco-argilo arenosa. Objetivou-se com este trabalho avaliar a eficácia e seletividade de glyphosate na formulação Roundup Transorb®, associado aos herbicidas diclosulam, cloransulam-methyl, flumioxazina e S-metolachlor em duas modalidades de aplicação: única, com associação do glyphosate aos herbicidas; e uma sequencial apenas com glyphosate aos 15 DAA, no manejo das plantas daninhas trapoeraba (Commelina benghalensis e corda-de-viola (Ipomoea triloba durante o cultivo da soja. O experimento foi instalado no delineamento de blocos ao acaso, com 12 tratamentos e quatro repetições. Os tratamentos foram distribuídos em arranjo fatorial acrescido de duas testemunhas: sem capina manual e com capina manual. O arranjo fatorial 2 x 5 contemplou duas condições de aplicação dos herbicidas (única e sequencial e cinco herbicidas (glyphosate, glyphosate + diclosulam, glyphosate + cloransulam-methyl, glyphosate + flumioxazin e glyphosate + S-metolachlor. Nas condições de produtos, épocas de aplicação e doses, os resultados mostraram que o herbicida glyphosate aplicado em dose única ou sequencial e suas combinações com diclosulam e cloransulam-methyl na primeira aplicação não promovem fitointoxicação nas plantas de soja. A combinação com flumioxazin e S-metolachlor promoveu atraso no crescimento das plantas e no fechamento da cultura, em razão do efeito na altura dos indivíduos e comprimento dos ramos. No tratamento com o S-metolachlor, isso pode ser explicado

  10. Characterization of cholinesterases in Chironomus riparius and the effects of three herbicides on chlorpyrifos toxicity.

    Science.gov (United States)

    Pérez, Joanne; Monteiro, Marta S; Quintaneiro, Carla; Soares, Amadeu M V M; Loureiro, Susana

    2013-11-15

    In this study, the toxicities of four pesticides (the herbicides atrazine, terbuthylazine, metolachlor and the insecticide chlorpyrifos) previously detected in the Alqueva reservoir/dam (south of Portugal) were evaluated individually and in binary combinations of the herbicides and the insecticide using fourth-instar larvae of the aquatic midge Chironomus riparius. Chlorpyrifos induced toxicity to midges in all the 48 h toxicity bioassays performed. The swimming behaviour of the larvae was impaired, with EC50 values ranging from 0.15 to 0.17 μg/L. However, neither s-triazine (atrazine and terbuthylazine) herbicides nor metolachlor alone at concentrations up to 200 μg/L caused significant toxicity to C. riparius. When combined with both s-triazine herbicides, chlorpyrifos toxicity was enhanced by approximately 2-fold when tested in a binary mixture experimental setup, at the 50% effective concentration levels. To evaluate how chlorpyrifos toxicity was being increased, the cholinesterases (ChE) were characterized biochemically using different substrates and selective inhibitors. The results obtained suggested that the main enzyme present in this species is acetylcholinesterase (AChE) and therefore it was assayed upon C. riparius exposures to all pesticides individually and as binary mixtures. Although atrazine and terbuthylazine are not effective inhibitors of AChE, the potentiation of chlorpyrifos toxicity by the two s-triazine herbicides was associated with a potentiation in the inhibition of AChE in midges; both s-triazine herbicides at 200 μg/L increased the inhibition of the AChE activity by 7 and 8-fold, respectively. A strong correlation was observed between swimming behaviour disturbances of larvae and the inhibition of the AChE activity. In contrast, metolachlor did not affect chlorpyrifos toxicity at any of the concentrations tested. Therefore, the herbicides atrazine and terbuthylazine can act as synergists in the presence of chlorpyrifos, increasing

  11. Prediction-Oriented Marker Selection (PROMISE): With Application to High-Dimensional Regression.

    Science.gov (United States)

    Kim, Soyeon; Baladandayuthapani, Veerabhadran; Lee, J Jack

    2017-06-01

    In personalized medicine, biomarkers are used to select therapies with the highest likelihood of success based on an individual patient's biomarker/genomic profile. Two goals are to choose important biomarkers that accurately predict treatment outcomes and to cull unimportant biomarkers to reduce the cost of biological and clinical verifications. These goals are challenging due to the high dimensionality of genomic data. Variable selection methods based on penalized regression (e.g., the lasso and elastic net) have yielded promising results. However, selecting the right amount of penalization is critical to simultaneously achieving these two goals. Standard approaches based on cross-validation (CV) typically provide high prediction accuracy with high true positive rates but at the cost of too many false positives. Alternatively, stability selection (SS) controls the number of false positives, but at the cost of yielding too few true positives. To circumvent these issues, we propose prediction-oriented marker selection (PROMISE), which combines SS with CV to conflate the advantages of both methods. Our application of PROMISE with the lasso and elastic net in data analysis shows that, compared to CV, PROMISE produces sparse solutions, few false positives, and small type I + type II error, and maintains good prediction accuracy, with a marginal decrease in the true positive rates. Compared to SS, PROMISE offers better prediction accuracy and true positive rates. In summary, PROMISE can be applied in many fields to select regularization parameters when the goals are to minimize false positives and maximize prediction accuracy.

  12. Understanding the spectrum of residential energy-saving behaviours: French evidence using disaggregated data

    International Nuclear Information System (INIS)

    Belaïd, Fateh; Garcia, Thomas

    2016-01-01

    Analysing household energy-saving behaviours is crucial to improve energy consumption predictions and energy policy making. How should we quantitatively measure them? What are their determinants? This study explores the main factors influencing residential energy-saving behaviours based on a bottom-up multivariate statistical approach using data from the recent French PHEBUS survey. Firstly, we assess energy-saving behaviours on a one-dimension scale using IRT. Secondly, we use linear regression with an innovative variable selection method via adaptive lasso to tease out the effects of both macro and micro factors on the behavioural score. The results highlight the impact of five main attributes incentivizing energy-saving behaviours based on cross-variable analyses: energy price, household income, education level, age of head of household and dwelling energy performance. In addition, our results suggest that the analysis of the inverted U-shape impact of age enables the expansion of the energy consumption life cycle theory to energy-saving behaviours. - Highlights: • We examine the main factors influencing residential energy-saving behaviours. • We use data from the recent French PHEBUS survey. • We use IRT to assess energy-saving behaviours on a one-dimension scale. • We use linear regression with an innovative variable selection method via adaptive lasso. • We highlight the impact of five main attributes incentivizing energy-saving behaviours.

  13. Variance Component Selection With Applications to Microbiome Taxonomic Data

    Directory of Open Access Journals (Sweden)

    Jing Zhai

    2018-03-01

    Full Text Available High-throughput sequencing technology has enabled population-based studies of the role of the human microbiome in disease etiology and exposure response. Microbiome data are summarized as counts or composition of the bacterial taxa at different taxonomic levels. An important problem is to identify the bacterial taxa that are associated with a response. One method is to test the association of specific taxon with phenotypes in a linear mixed effect model, which incorporates phylogenetic information among bacterial communities. Another type of approaches consider all taxa in a joint model and achieves selection via penalization method, which ignores phylogenetic information. In this paper, we consider regression analysis by treating bacterial taxa at different level as multiple random effects. For each taxon, a kernel matrix is calculated based on distance measures in the phylogenetic tree and acts as one variance component in the joint model. Then taxonomic selection is achieved by the lasso (least absolute shrinkage and selection operator penalty on variance components. Our method integrates biological information into the variable selection problem and greatly improves selection accuracies. Simulation studies demonstrate the superiority of our methods versus existing methods, for example, group-lasso. Finally, we apply our method to a longitudinal microbiome study of Human Immunodeficiency Virus (HIV infected patients. We implement our method using the high performance computing language Julia. Software and detailed documentation are freely available at https://github.com/JingZhai63/VCselection.

  14. High-Dimensional Additive Hazards Regression for Oral Squamous Cell Carcinoma Using Microarray Data: A Comparative Study

    Directory of Open Access Journals (Sweden)

    Omid Hamidi

    2014-01-01

    Full Text Available Microarray technology results in high-dimensional and low-sample size data sets. Therefore, fitting sparse models is substantial because only a small number of influential genes can reliably be identified. A number of variable selection approaches have been proposed for high-dimensional time-to-event data based on Cox proportional hazards where censoring is present. The present study applied three sparse variable selection techniques of Lasso, smoothly clipped absolute deviation and the smooth integration of counting, and absolute deviation for gene expression survival time data using the additive risk model which is adopted when the absolute effects of multiple predictors on the hazard function are of interest. The performances of used techniques were evaluated by time dependent ROC curve and bootstrap .632+ prediction error curves. The selected genes by all methods were highly significant (P<0.001. The Lasso showed maximum median of area under ROC curve over time (0.95 and smoothly clipped absolute deviation showed the lowest prediction error (0.105. It was observed that the selected genes by all methods improved the prediction of purely clinical model indicating the valuable information containing in the microarray features. So it was concluded that used approaches can satisfactorily predict survival based on selected gene expression measurements.

  15. A Hierarchical Poisson Log-Normal Model for Network Inference from RNA Sequencing Data

    Science.gov (United States)

    Gallopin, Mélina; Rau, Andrea; Jaffrézic, Florence

    2013-01-01

    Gene network inference from transcriptomic data is an important methodological challenge and a key aspect of systems biology. Although several methods have been proposed to infer networks from microarray data, there is a need for inference methods able to model RNA-seq data, which are count-based and highly variable. In this work we propose a hierarchical Poisson log-normal model with a Lasso penalty to infer gene networks from RNA-seq data; this model has the advantage of directly modelling discrete data and accounting for inter-sample variance larger than the sample mean. Using real microRNA-seq data from breast cancer tumors and simulations, we compare this method to a regularized Gaussian graphical model on log-transformed data, and a Poisson log-linear graphical model with a Lasso penalty on power-transformed data. For data simulated with large inter-sample dispersion, the proposed model performs better than the other methods in terms of sensitivity, specificity and area under the ROC curve. These results show the necessity of methods specifically designed for gene network inference from RNA-seq data. PMID:24147011

  16. Molecular structure of human KATP in complex with ATP and ADP.

    Science.gov (United States)

    Lee, Kenneth Pak Kin; Chen, Jue; MacKinnon, Roderick

    2017-12-29

    In many excitable cells, KATP channels respond to intracellular adenosine nucleotides: ATP inhibits while ADP activates. We present two structures of the human pancreatic KATP channel, containing the ABC transporter SUR1 and the inward-rectifier K + channel Kir6.2, in the presence of Mg 2+ and nucleotides. These structures, referred to as quatrefoil and propeller forms, were determined by single-particle cryo-EM at 3.9 Å and 5.6 Å, respectively. In both forms, ATP occupies the inhibitory site in Kir6.2. The nucleotide-binding domains of SUR1 are dimerized with Mg 2+ -ATP in the degenerate site and Mg 2+ -ADP in the consensus site. A lasso extension forms an interface between SUR1 and Kir6.2 adjacent to the ATP site in the propeller form and is disrupted in the quatrefoil form. These structures support the role of SUR1 as an ADP sensor and highlight the lasso extension as a key regulatory element in ADP's ability to override ATP inhibition. © 2017, Lee et al.

  17. Measurement error correction in the least absolute shrinkage and selection operator model when validation data are available.

    Science.gov (United States)

    Vasquez, Monica M; Hu, Chengcheng; Roe, Denise J; Halonen, Marilyn; Guerra, Stefano

    2017-01-01

    Measurement of serum biomarkers by multiplex assays may be more variable as compared to single biomarker assays. Measurement error in these data may bias parameter estimates in regression analysis, which could mask true associations of serum biomarkers with an outcome. The Least Absolute Shrinkage and Selection Operator (LASSO) can be used for variable selection in these high-dimensional data. Furthermore, when the distribution of measurement error is assumed to be known or estimated with replication data, a simple measurement error correction method can be applied to the LASSO method. However, in practice the distribution of the measurement error is unknown and is expensive to estimate through replication both in monetary cost and need for greater amount of sample which is often limited in quantity. We adapt an existing bias correction approach by estimating the measurement error using validation data in which a subset of serum biomarkers are re-measured on a random subset of the study sample. We evaluate this method using simulated data and data from the Tucson Epidemiological Study of Airway Obstructive Disease (TESAOD). We show that the bias in parameter estimation is reduced and variable selection is improved.

  18. Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat.

    Science.gov (United States)

    Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne

    2012-12-01

    In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.

  19. Processing ARM VAP data on an AWS cluster

    Science.gov (United States)

    Martin, T.; Macduff, M.; Shippert, T.

    2017-12-01

    The Atmospheric Radiation Measurement (ARM) Data Management Facility (DMF) manages over 18,000 processes and 1.3 TB of data each day. This includes many Value Added Products (VAPs) that make use of multiple instruments to produce the derived products that are scientifically relevant. A thermodynamic and cloud profile VAP is being developed to provide input to the ARM Large-eddy simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project (https://www.arm.gov/capabilities/vaps/lasso-122) . This algorithm is CPU intensive and the processing requirements exceeded the available DMF computing capacity. Amazon Web Service (AWS) along with CfnCluster was investigated to see how it would perform. This cluster environment is cost effective and scales dynamically based on demand. We were able to take advantage of autoscaling which allowed the cluster to grow and shrink based on the size of the processing queue. We also were able to take advantage of the Amazon Web Services spot market to further reduce the cost. Our test was very successful and found that cloud resources can be used to efficiently and effectively process time series data. This poster will present the resources and methodology used to successfully run the algorithm.

  20. Agreement between clinical estimation and a new quantitative analysis by Photoshop software in fundus and angiographic image variables.

    Science.gov (United States)

    Ramezani, Alireza; Ahmadieh, Hamid; Azarmina, Mohsen; Soheilian, Masoud; Dehghan, Mohammad H; Mohebbi, Mohammad R

    2009-12-01

    To evaluate the validity of a new method for the quantitative analysis of fundus or angiographic images using Photoshop 7.0 (Adobe, USA) software by comparing with clinical evaluation. Four hundred and eighteen fundus and angiographic images of diabetic patients were evaluated by three retina specialists and then by computing using Photoshop 7.0 software. Four variables were selected for comparison: amount of hard exudates (HE) on color pictures, amount of HE on red-free pictures, severity of leakage, and the size of the foveal avascular zone (FAZ). The coefficient of agreement (Kappa) between the two methods in the amount of HE on color and red-free photographs were 85% (0.69) and 79% (0.59), respectively. The agreement for severity of leakage was 72% (0.46). In the two methods for the evaluation of the FAZ size using the magic and lasso software tools, the agreement was 54% (0.09) and 89% (0.77), respectively. Agreement in the estimation of the FAZ size by the lasso magnetic tool was excellent and was almost as good in the quantification of HE on color and on red-free images. Considering the agreement of this new technique for the measurement of variables in fundus images using Photoshop software with the clinical evaluation, this method seems to have sufficient validity to be used for the quantitative analysis of HE, leakage, and FAZ size on the angiograms of diabetic patients.

  1. Techniques on semiautomatic segmentation using the Adobe Photoshop

    Science.gov (United States)

    Park, Jin Seo; Chung, Min Suk; Hwang, Sung Bae

    2005-04-01

    The purpose of this research is to enable anybody to semiautomatically segment the anatomical structures in the MRIs, CTs, and other medical images on the personal computer. The segmented images are used for making three-dimensional images, which are helpful in medical education and research. To achieve this purpose, the following trials were performed. The entire body of a volunteer was MR scanned to make 557 MRIs, which were transferred to a personal computer. On Adobe Photoshop, contours of 19 anatomical structures in the MRIs were semiautomatically drawn using MAGNETIC LASSO TOOL; successively, manually corrected using either LASSO TOOL or DIRECT SELECTION TOOL to make 557 segmented images. In a likewise manner, 11 anatomical structures in the 8,500 anatomcial images were segmented. Also, 12 brain and 10 heart anatomical structures in anatomical images were segmented. Proper segmentation was verified by making and examining the coronal, sagittal, and three-dimensional images from the segmented images. During semiautomatic segmentation on Adobe Photoshop, suitable algorithm could be used, the extent of automatization could be regulated, convenient user interface could be used, and software bugs rarely occurred. The techniques of semiautomatic segmentation using Adobe Photoshop are expected to be widely used for segmentation of the anatomical structures in various medical images.

  2. Sleep duration, daytime napping, markers of obstructive sleep apnea and stroke in a population of southern China

    Science.gov (United States)

    Wen, Ye; Pi, Fu-Hua; Guo, Pi; Dong, Wen-Ya; Xie, Yu-Qing; Wang, Xiang-Yu; Xia, Fang-Fang; Pang, Shao-Jie; Wu, Yan-Chun; Wang, Yuan-Yuan; Zhang, Qing-Ying

    2016-01-01

    Sleep habits are associated with stroke in western populations, but this relation has been rarely investigated in China. Moreover, the differences among stroke subtypes remain unclear. This study aimed to explore the associations of total stroke, including ischemic and hemorrhagic type, with sleep habits of a population in southern China. We performed a case-control study in patients admitted to the hospital with first stroke and community control subjects. A total of 333 patients (n = 223, 67.0%, with ischemic stroke; n = 110, 23.0%, with hemorrhagic stroke) and 547 controls were enrolled in the study. Participants completed a structured questionnaire to identify sleep habits and other stroke risk factors. Least absolute shrinkage and selection operator (Lasso) and multiple logistic regression were performed to identify risk factors of disease. Incidence of stroke, and its subtypes, was significantly associated with snorting/gasping, snoring, sleep duration, and daytime napping. Snorting/gasping was identified as an important risk factor in the Lasso logistic regression model (Lasso’ β = 0.84), and the result was proven to be robust. This study showed the association between stroke and sleep habits in the southern Chinese population and might help in better detecting important sleep-related factors for stroke risk. PMID:27698374

  3. Novel high-resolution computed tomography-based radiomic classifier for screen-identified pulmonary nodules in the National Lung Screening Trial.

    Science.gov (United States)

    Peikert, Tobias; Duan, Fenghai; Rajagopalan, Srinivasan; Karwoski, Ronald A; Clay, Ryan; Robb, Richard A; Qin, Ziling; Sicks, JoRean; Bartholmai, Brian J; Maldonado, Fabien

    2018-01-01

    Optimization of the clinical management of screen-detected lung nodules is needed to avoid unnecessary diagnostic interventions. Herein we demonstrate the potential value of a novel radiomics-based approach for the classification of screen-detected indeterminate nodules. Independent quantitative variables assessing various radiologic nodule features such as sphericity, flatness, elongation, spiculation, lobulation and curvature were developed from the NLST dataset using 726 indeterminate nodules (all ≥ 7 mm, benign, n = 318 and malignant, n = 408). Multivariate analysis was performed using least absolute shrinkage and selection operator (LASSO) method for variable selection and regularization in order to enhance the prediction accuracy and interpretability of the multivariate model. The bootstrapping method was then applied for the internal validation and the optimism-corrected AUC was reported for the final model. Eight of the originally considered 57 quantitative radiologic features were selected by LASSO multivariate modeling. These 8 features include variables capturing Location: vertical location (Offset carina centroid z), Size: volume estimate (Minimum enclosing brick), Shape: flatness, Density: texture analysis (Score Indicative of Lesion/Lung Aggression/Abnormality (SILA) texture), and surface characteristics: surface complexity (Maximum shape index and Average shape index), and estimates of surface curvature (Average positive mean curvature and Minimum mean curvature), all with Pscreen-detected nodule characterization appears extremely promising however independent external validation is needed.

  4. Prediction models for solitary pulmonary nodules based on curvelet textural features and clinical parameters.

    Science.gov (United States)

    Wang, Jing-Jing; Wu, Hai-Feng; Sun, Tao; Li, Xia; Wang, Wei; Tao, Li-Xin; Huo, Da; Lv, Ping-Xin; He, Wen; Guo, Xiu-Hua

    2013-01-01

    Lung cancer, one of the leading causes of cancer-related deaths, usually appears as solitary pulmonary nodules (SPNs) which are hard to diagnose using the naked eye. In this paper, curvelet-based textural features and clinical parameters are used with three prediction models [a multilevel model, a least absolute shrinkage and selection operator (LASSO) regression method, and a support vector machine (SVM)] to improve the diagnosis of benign and malignant SPNs. Dimensionality reduction of the original curvelet-based textural features was achieved using principal component analysis. In addition, non-conditional logistical regression was used to find clinical predictors among demographic parameters and morphological features. The results showed that, combined with 11 clinical predictors, the accuracy rates using 12 principal components were higher than those using the original curvelet-based textural features. To evaluate the models, 10-fold cross validation and back substitution were applied. The results obtained, respectively, were 0.8549 and 0.9221 for the LASSO method, 0.9443 and 0.9831 for SVM, and 0.8722 and 0.9722 for the multilevel model. All in all, it was found that using curvelet-based textural features after dimensionality reduction and using clinical predictors, the highest accuracy rate was achieved with SVM. The method may be used as an auxiliary tool to differentiate between benign and malignant SPNs in CT images.

  5. Combination of radiological and gray level co-occurrence matrix textural features used to distinguish solitary pulmonary nodules by computed tomography.

    Science.gov (United States)

    Wu, Haifeng; Sun, Tao; Wang, Jingjing; Li, Xia; Wang, Wei; Huo, Da; Lv, Pingxin; He, Wen; Wang, Keyang; Guo, Xiuhua

    2013-08-01

    The objective of this study was to investigate the method of the combination of radiological and textural features for the differentiation of malignant from benign solitary pulmonary nodules by computed tomography. Features including 13 gray level co-occurrence matrix textural features and 12 radiological features were extracted from 2,117 CT slices, which came from 202 (116 malignant and 86 benign) patients. Lasso-type regularization to a nonlinear regression model was applied to select predictive features and a BP artificial neural network was used to build the diagnostic model. Eight radiological and two textural features were obtained after the Lasso-type regularization procedure. Twelve radiological features alone could reach an area under the ROC curve (AUC) of 0.84 in differentiating between malignant and benign lesions. The 10 selected characters improved the AUC to 0.91. The evaluation results showed that the method of selecting radiological and textural features appears to yield more effective in the distinction of malignant from benign solitary pulmonary nodules by computed tomography.

  6. Risk Prediction Using Genome-Wide Association Studies on Type 2 Diabetes

    Directory of Open Access Journals (Sweden)

    Sungkyoung Choi

    2016-12-01

    Full Text Available The success of genome-wide association studies (GWASs has enabled us to improve risk assessment and provide novel genetic variants for diagnosis, prevention, and treatment. However, most variants discovered by GWASs have been reported to have very small effect sizes on complex human diseases, which has been a big hurdle in building risk prediction models. Recently, many statistical approaches based on penalized regression have been developed to solve the “large p and small n” problem. In this report, we evaluated the performance of several statistical methods for predicting a binary trait: stepwise logistic regression (SLR, least absolute shrinkage and selection operator (LASSO, and Elastic-Net (EN. We first built a prediction model by combining variable selection and prediction methods for type 2 diabetes using Affymetrix Genome-Wide Human SNP Array 5.0 from the Korean Association Resource project. We assessed the risk prediction performance using area under the receiver operating characteristic curve (AUC for the internal and external validation datasets. In the internal validation, SLR-LASSO and SLR-EN tended to yield more accurate predictions than other combinations. During the external validation, the SLR-SLR and SLR-EN combinations achieved the highest AUC of 0.726. We propose these combinations as a potentially powerful risk prediction model for type 2 diabetes.

  7. A Bayesian Framework That Integrates Heterogeneous Data for Inferring Gene Regulatory Networks

    Energy Technology Data Exchange (ETDEWEB)

    Santra, Tapesh, E-mail: tapesh.santra@ucd.ie [Systems Biology Ireland, University College Dublin, Dublin (Ireland)

    2014-05-20

    Reconstruction of gene regulatory networks (GRNs) from experimental data is a fundamental challenge in systems biology. A number of computational approaches have been developed to infer GRNs from mRNA expression profiles. However, expression profiles alone are proving to be insufficient for inferring GRN topologies with reasonable accuracy. Recently, it has been shown that integration of external data sources (such as gene and protein sequence information, gene ontology data, protein–protein interactions) with mRNA expression profiles may increase the reliability of the inference process. Here, I propose a new approach that incorporates transcription factor binding sites (TFBS) and physical protein interactions (PPI) among transcription factors (TFs) in a Bayesian variable selection (BVS) algorithm which can infer GRNs from mRNA expression profiles subjected to genetic perturbations. Using real experimental data, I show that the integration of TFBS and PPI data with mRNA expression profiles leads to significantly more accurate networks than those inferred from expression profiles alone. Additionally, the performance of the proposed algorithm is compared with a series of least absolute shrinkage and selection operator (LASSO) regression-based network inference methods that can also incorporate prior knowledge in the inference framework. The results of this comparison suggest that BVS can outperform LASSO regression-based method in some circumstances.

  8. Standardized comparison of the relative impacts of HIV-1 reverse transcriptase (RT) mutations on nucleoside RT inhibitor susceptibility.

    Science.gov (United States)

    Melikian, George L; Rhee, Soo-Yon; Taylor, Jonathan; Fessel, W Jeffrey; Kaufman, David; Towner, William; Troia-Cancio, Paolo V; Zolopa, Andrew; Robbins, Gregory K; Kagan, Ron; Israelski, Dennis; Shafer, Robert W

    2012-05-01

    Determining the phenotypic impacts of reverse transcriptase (RT) mutations on individual nucleoside RT inhibitors (NRTIs) has remained a statistical challenge because clinical NRTI-resistant HIV-1 isolates usually contain multiple mutations, often in complex patterns, complicating the task of determining the relative contribution of each mutation to HIV drug resistance. Furthermore, the NRTIs have highly variable dynamic susceptibility ranges, making it difficult to determine the relative effect of an RT mutation on susceptibility to different NRTIs. In this study, we analyzed 1,273 genotyped HIV-1 isolates for which phenotypic results were obtained using the PhenoSense assay (Monogram, South San Francisco, CA). We used a parsimonious feature selection algorithm, LASSO, to assess the possible contributions of 177 mutations that occurred in 10 or more isolates in our data set. We then used least-squares regression to quantify the impact of each LASSO-selected mutation on each NRTI. Our study provides a comprehensive view of the most common NRTI resistance mutations. Because our results were standardized, the study provides the first analysis that quantifies the relative phenotypic effects of NRTI resistance mutations on each of the NRTIs. In addition, the study contains new findings on the relative impacts of thymidine analog mutations (TAMs) on susceptibility to abacavir and tenofovir; the impacts of several known but incompletely characterized mutations, including E40F, V75T, Y115F, and K219R; and a tentative role in reduced NRTI susceptibility for K64H, a novel NRTI resistance mutation.

  9. Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

    Science.gov (United States)

    Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao

    2015-01-01

    Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

  10. Dark History of Our Lady of the Slash-Knife

    Directory of Open Access Journals (Sweden)

    John C. Dawsey

    2009-01-01

    Full Text Available In the Garden of Flowers, over the ashes of the old Slash-Knife District, live the daughters – or granddaughters and great-granddaughters – of slaves and native South-American women “lassoed in the woods”. Many consider themselves also to be the daughters of Our Lady. The juxtaposition of maternal lineages may produce a montage-like effect. Do gestures of Indians and slaves flash in the bodily innervations of Our Lady? Signs of “dark histories” of Our Lady are found in subterranean regions of symbols. On this terrain, the study of historical patterns of settlement in Piracicaba, a city of the interior of São Paulo, may require a certain type of archaeology, involving a double dislocation, from bandeirante explorers to Our Lady, and from Our Lady to Indian and slave women “lassoed in the woods”. In these substrata the gesture of a boia-fria woman who “cut a man into pieces” stirs up the shadows of a nation.

  11. A Bayesian Framework That Integrates Heterogeneous Data for Inferring Gene Regulatory Networks

    International Nuclear Information System (INIS)

    Santra, Tapesh

    2014-01-01

    Reconstruction of gene regulatory networks (GRNs) from experimental data is a fundamental challenge in systems biology. A number of computational approaches have been developed to infer GRNs from mRNA expression profiles. However, expression profiles alone are proving to be insufficient for inferring GRN topologies with reasonable accuracy. Recently, it has been shown that integration of external data sources (such as gene and protein sequence information, gene ontology data, protein–protein interactions) with mRNA expression profiles may increase the reliability of the inference process. Here, I propose a new approach that incorporates transcription factor binding sites (TFBS) and physical protein interactions (PPI) among transcription factors (TFs) in a Bayesian variable selection (BVS) algorithm which can infer GRNs from mRNA expression profiles subjected to genetic perturbations. Using real experimental data, I show that the integration of TFBS and PPI data with mRNA expression profiles leads to significantly more accurate networks than those inferred from expression profiles alone. Additionally, the performance of the proposed algorithm is compared with a series of least absolute shrinkage and selection operator (LASSO) regression-based network inference methods that can also incorporate prior knowledge in the inference framework. The results of this comparison suggest that BVS can outperform LASSO regression-based method in some circumstances.

  12. Efeitos da aplicação de vinhaça sobre a população e controle químico de plantas daninhas na cultura da cana-de-açucar (Saccharum SPP. Effects of vinasse application on the population and chemical control of weeds in the sugarcane (Saccharum spp.

    Directory of Open Access Journals (Sweden)

    P.J. Christoffoleti

    1985-12-01

    Full Text Available Para avaliar o controle químico e a influência na população de plantas daninhas incidentes na cultura da cana-de-açucar (cana-soca, 3o corte, variedade NA56-79, em função da aplicação de diferentes doses de vinhaça, foi instalado um ensaio em solo pertencente a Usina Santa Lúcia de Açúcar e Álcool, do município de Araras-SP. O solo foi um Latassol Vermelho Amarelo distrófico, textura média, Haplorthox. O experimento foi instalado no dia 10/08/83, com o solo seco no momento da aplicação da vinhaça, não ocorrendo qualquer precipitação nos dez dias seguintes à aplicação. A aplicação da vinhaça foi feita através de veículos tanque, e a aplicação regulada para uma vazão de 50m3/ha , de tal forma que nas dosagens de 100 e 150m3 /ha foram feitas 2 e 3 passadas, respectivamente. Os herbicidas foram aplicados através de pulverizador costal à pressão constante, com um consumo de calda de 370 1/ha. O delineamento experimental foi de blocos casualizados com parcelas subdivididas e 3 repetições e os tratamentos foram vinhaça a 0,50, 100 e 150 m3 /ha e adubação mineral. Por outro lado os subtratamentos foram os herbicidas das alachlor (2-cloro-2-6-dietil-metoximetil-acetanilida a 2,40 kg i.a/ha, diuron (3-(3,4-dicloro-fenil-1, 1-dimetil-uréia a 1,6 kg i.a/há, ametrin (2-(etilamino-4-(isopropilano-6-(metiltio-S-triazina a 2,40 kg i.a/ha e tebuthiuron (N-(5-(1,1-dimetiletil-1, 3,4-tiadiazol-2-il-1,3-N, N-dimetil-uréia a 0,96 kg i.a/ha. A infestação do capim-colchão (Digitaria horizontalis Willd foi maior na área que recebeu apenas adubação mineral, com doses crescentes da vinhaça a população dessa espécie foi se elevando. O controle mais eficiente foi proporcionado por tebuthiuron. Com alachlor houve melhora pronunciada de controle, quando aplicado com 100 m3 /ha de vinhaça. Este fato também ocorreu com o diuron e menos acentuadamente com o ametrin. A tiririca (Cyperus rotundus L. infestou menos

  13. Translocation of labelled assimilates, ion uptake and nucleic acids contents in zea mays plants as influenced by application of the herbicide dual and the bioregulaators GA3 and kinetin

    International Nuclear Information System (INIS)

    Hassanein, R.AA.; Khodary, S.E.A.; Abdel-Aziz, S.M.

    2001-01-01

    Maize seedlings, grown hydroponic for one month, were undertaken o investigate the effect of dual (metolachlor), bio regulators (GA 3 and kinetin) and their interaction with dual on translocation rate of assimilates, nucleic acids content. ion uptake and the activities of protease and nitrate reductase enzymes. Dual at all concentrations decreased the rate of assimilates translocation and nucleic acids levels. Also reduction in the ability of the treated plants to absorb ions from the growth medium as well as the activities of nitrate reductase and protease enzymes were retarded upon dual application. The results also revealed that treatment with either GA 3 or kinetin in combination with dual, reversed the adverse action of the herbicide on zea mays plants

  14. Avaliação de herbicidas para dois cultivares de mandioca Selectivity of herbicide alternatives for two cassava cultivars

    Directory of Open Access Journals (Sweden)

    D.F Biffe

    2010-12-01

    Full Text Available É importante avaliar a tolerância de variedade de mandioca a novas alternativas de controle químico, com o intuito de ampliar as opções disponíveis. Este trabalho teve como objetivo avaliar a seletividade de herbicidas aplicados em pré-emergência, para duas importantes variedades de mandioca cultivadas no Estado do Paraná. Os herbicidas e respectivas doses (g i.a. ha-1 avaliadas foram: diuron (400 e 800, metribuzin (360 e 720, isoxaflutole (60, atrazine (720, S-metolachlor (1.920 e as misturas ametryn + clomazone (1.350+1.900, ametryn+trifluralin (1.500+1.350, isoxaflutole+metribuzin (60+320, isoxaflutole+diuron (60+400, combinados com uso de uma testemunha dupla adjacente a cada tratamento. Os cultivares utilizados neste trabalho foram Fécula Branca e Fibra. Apenas o herbicida S-metolachlor, para ambos os cultivares, e metribuzin (360 g i.a. ha-1, para o cultivar Fibra, não provocaram injúrias. Atrazine provocou redução de estande para o cultivar Fécula Branca aos 60 DAP, mas não foi detectada redução na altura de plantas. Tanto atrazine (para os dois cultivares quanto diuron na dose de 800 g i.a. ha-1 (para o cultivar Fécula Branca afetaram a produtividade de raízes. Dessa forma, atrazine foi considerado não seletivo para ambos os cultivares, e a maior dose de diuron foi também considerada não seletiva para o cultivar Fécula Branca. Há diferenças de tolerância entre os cultivares, sendo o Fibra, de modo geral, mais tolerante aos herbicidas avaliados.It is important to evaluate the tolerance of cassava varieties under new weed chemical control alternatives. Thus, this study aimed to evaluate the selectivity of herbicides, applied at pre-emergence, for two important cassava varieties grown in the state of Paraná, Brazil. The herbicides and respective doses (g a.i. ha-1 were: diuron (400 and 800, metribuzin (360 and 720, isoxaflutole (60, atrazine (720, S-metolachlor (1,920 and mixtures ametryn+clomazone (1

  15. Aumento da população de plantas e uso de herbicidas no controle de plantas daninhas em milho Increase of plant population and use of herbicides to control weeds in corn

    Directory of Open Access Journals (Sweden)

    Aldo Merotto Junior

    1997-01-01

    Full Text Available O objetivo deste trabalho foi determinar a capacidade de controle de plantas daninhas efetuada pelo aumento da população de plantas de milho em associação com diferentes métodos de controle de plantas daninhas. O experimento foi conduzido em Lages (SC sob o delineamento de blocos ao acaso em parcelas subdivididas. Nas parcelas principais foram alocados os métodos de controle de plantas daninhas: 1 sem controle; 2 atrazine + metolachlor (1,4 + 2,1 kg/h a em pré emergência; 3 nicosulfuron (60 g/ ha em pós - emergência; 4 atrazine + metolachlor em pré emergência e nicosulfuron em pós-emergência; e 5 capina até o florescimento. Nas sub parcelas foram alocadas as populações de plantas: 35.000, 50.000, 68.000 e 80.000 plantas ha-1. O aumento da população de plantas foi mais efetivo na diminuição da matéria seca de plantas daninhas nos tratamentos sem controle e com herbicida em pré emergência. As plantas daninhas promoveram maiores decréscimos no rendimento de grão s de milho na população de 80000 plantas ha-1, onde a competição com plantas daninhas somou-se à competição intraespecífica que também é maior do que nas menores populações . O uso de altas populações de plantas diminui a competição com plantas daninhas , mas deve ser complementado com outros métodos de controle no início do desenvolvimento da cultura.The objective of this experiment was to evaluate the effectiveness of increasing corn plant population in association with differe nt methods to control weeds. The trial was conduted in Lages, SC, using a randomized complete block desing in a split plot arragement. Fiv e methods of weed control were located at the main plots: 1 check without control, 2 atrazine + metolachlor (1,4 + 2,1 kg/ha in pre-emergency, 3 nicosulfuron (60 g/ha in post emergency, 4 atrazine + metolachlor in pre-emergency and nicosulfuron in post emergency, and 5 hoeing up to flowerin g. Four plant population were tested at split

  16. Herbicide contamination in carrot grown in punjab, pakistan

    International Nuclear Information System (INIS)

    Amjad, M.; Ahmad, T.; Jahangir, M.M.

    2013-01-01

    Food safety and security is a burning issue of the time whereas vegetable production is an important aspect of agriculture. Use of herbicides for vegetable production is very common in Pakistan but no proper procedure has been planned to keep optimal level of doses of herbicide under permissible limit. To estimate the pesticide residues, samples from the leading carrot producing sites were collected along with the samples from the market. The samples were processed using standard procedures and qualitative and quantitative analysis was performed by Gas Chromatography-Mass Spectrometry (GC-MS). It was concluded that all the samples were contaminated with S-metolachlor in the range of 0.45 to 0.73 mg kg-1 which was above the permissible limit (0.40 mg kg-1). (author)

  17. Nitrapyrin in streams: The first study documenting off-field transport of a nitrogen stabilizer compound

    Science.gov (United States)

    Woodward, Emily; Hladik, Michelle; Kolpin, Dana W.

    2016-01-01

    Nitrapyrin is a bactericide that is co-applied with fertilizer to prevent nitrification and enhance corn yields. While there have been studies of the environmental fate of nitrapyrin, there is no documentation of its off-field transport to streams. In 2016, 59 water samples from 11 streams across Iowa were analyzed for nitrapyrin and its degradate, 6-chloropicolinic acid (6-CPA), along with three widely used herbicides, acetochlor, atrazine, and metolachlor. Nitrapyrin was detected in seven streams (39% of water samples) with concentrations ranging from 12 to 240 ng/L; 6-CPA was never detected. The herbicides were ubiquitously detected (100% of samples, 28–16000 ng/L). Higher nitrapyrin concentrations in streams were associated with rainfall events following spring fertilizer applications. Nitrapyrin persisted in streams for up to 5 weeks. These results highlight the need for more research focused on the environmental fate and transport of nitrapyrin and the potential toxicity this compound could have on nontarget organisms.

  18. Occurrence and Distribution of Pesticides in the St. Lucie River Watershed, South-Central Florida, 2000-01, Based on Enzyme-Linked Immunosorbent Assay (ELISA) Screening

    Science.gov (United States)

    Lietz, A.C.

    2003-01-01

    , respectively. The highest median triazine concentration was found in the cropland/pastureland area. Chloroacetanilide concentra-tions ranged from highest to lowest in the citrus, integrated, urban/built-up, and cropland/pastureland areas, respectively. Chlorophenoxy compound concentrations ranged from highest to lowest in the urban/built-up, integrated, citrus, and cropland/pastureland areas, respectively. The maximum concentrations of triazines, chloroacetanilides, and chlorophenoxy compounds were 0.63, 1.0, and 14 micrograms per liter, respectively. Organophosphate was detected once at an integrated site at a concentration of 0.20 microgram per liter. Currently, the U.S. Environmental Protection Agency has no aquatic life guidelines for atrazine and metolachlor. However, assuming that all triazine and metolachlor concentrations from ELISA and gas chromatography/mass spectrometry (GC/MS) analyses were the result of atrazine and metolachlor detections, no concentrations exceeded the Canadian aquatic life guidelines for atrazine and metolachlor. One organophosphate detection (0.2 microgram per liter) did exceed the U.S. Environmental Protection Agency aquatic life guideline for chlorpyrifos. The deethylatrazine/atrazine ratio (DAR) is an important indicator of atrazine transport in the environment. The DAR ranged from 0.25 to 0.33, indicating that postapplication runoff was the most likely source of atrazine to the environment at the time of sampling. Deisopropylatrazine is a metabolite of atrazine and structurally similar compounds, such as simazine and cyanazine. The deisopropylatrazine/deethylatrazine ratio (D2R) is an indicator of nonpoint sources of deisopropylatrazine to the environment. The ratio ranged from 1 to 3 in this study, indicating simazine was an important source of deisopropylatrazine to the environment at the time of sampling, as opposed to atrazine alone. Confirmation analyses by GC/MS for triazines detected by ELISA indicated t

  19. Biosurfactant-enhanced soil bioremediation

    Energy Technology Data Exchange (ETDEWEB)

    Kosaric, N.; Lu, G.; Velikonja, J. [Univ. of Western Ontario, London, Ontario (Canada)

    1995-12-01

    Bioremediation of soil contaminated with organic chemicals is a viable alternative method for clean-up and remedy of hazardous waste sites. The final objective in this approach is to convert the parent toxicant into a readily biodegradable product which is harmless to human health and/or the environment. Biodegradation of hydrocarbons in soil can also efficiently be enhanced by addition or in-situ production of biosufactants. It was generally observed that the degradation time was shortened and particularly the adaptation time for the microbes. More data from our laboratories showed that chlorinated aromatic compounds, such as 2,4-dichlorophenol, a herbicide Metolachlor, as well as naphthalene are degraded faster and more completely when selected biosurfactants are added to the soil. More recent data demonstrated an enhanced biodegradation of heavy hydrocarbons in petrochemical sludges, and in contaminated oil when biosurfactants were present or were added prior to the biodegradation process.

  20. Pesticides in storm runoff from agricultural and urban areas in the Tuolumne River basin in the vicinity of Modesto, California

    Science.gov (United States)

    Kratzer, Charles R.

    1998-01-01

    The occurrence, concentrations, and loads of dissolved pesticides in storm runoff were compared for two contrasting land uses in the Tuolumne River Basin, California, during two different winter storms: agricultural areas (February 1994) and the Modesto urban area (February 1995). Both storms followed the main application period of pesticides on dormant almond orchards. Eight samples of runoff from agricultural areas were collected from a Tuolumne River site, and 10 samples of runoff from urban areas were collected from five storm drains. All samples were analyzed for 46 pesticides. Six pesticides were detected in runoff from agricultural areas, and 15 pesticides were detected in runoff from urban areas. Chlorpyrifos, diazinon, dacthal (DCPA), metolachlor, and simazine were detected in almost every sample. Median concentrations were higher in the runoff from urban areas for all pesticides except napropamide and simazine. The greater occurrence and concentrations in storm drains is partly attributed to dilution of agricultural runoff by nonstorm base-flow in the Tuolumne River and by storm runoff from nonagricultural and nonurban land. In most cases, the occurrence and relative concentrations of pesticides found in storm runoff from agricultural and urban areas were related to reported pesticide application. Pesticide concentrations in runoff from agricultural areas were more variable during the storm hydrograph than were concentrations in runoff from urban areas. All peak pesticide concentrations in runoff from agricultural areas occurred during the rising limb of the storm hydrograph, whereas peak concentrations in the storm drains occurred at varying times during the storm hydrograph. Transport of pesticides from agricultural areas during the February 1994 storm exceeded transport from urban areas during the February 1995 storm for chlorpyrifos, diazinon, metolachlor, napropamide, and simazine. Transport of DCPA was about the same from agricultural and urban

  1. Comparison of the behavioural effects of pharmaceuticals and pesticides on Diamesa zernyi larvae (Chironomidae).

    Science.gov (United States)

    Villa, Sara; Di Nica, Valeria; Pescatore, Tanita; Bellamoli, Francesco; Miari, Francesco; Finizio, Antonio; Lencioni, Valeria

    2018-07-01

    Several studies have indicated the presence of contaminants in Alpine aquatic ecosystems. Even if measured concentrations are far below those that cause acute effects, continuous exposure to sub-lethal concentrations may have detrimental effects on the aquatic species present in these remote environments. This may lead to a cascade of indirect effects at higher levels of the ecological hierarchy (i.e., the community). To improve the determination of ecologically relevant risk endpoints, behavioural alterations in organisms due to pollutants are increasingly studied in ecotoxicology. In fact, behaviour links physiological function with ecological processes, and can be very sensitive to environmental stimuli and chemical exposure. This is the first study on behavioural alteration in a wild population of an Alpine species. In the present study, a video tracking system was standardized and subsequently used to identify contaminant-induced behavioural alterations in Diamesa zernyi larvae (Diptera, Chironomidae). Diamesa zernyi larvae, collected in an Italian Alpine stream (Rio Presena, Trentino Region), were acclimated for 24 h and successively exposed to several aquatic contaminants (pesticides: chlorpyrifos, metolachlor, boscalid, captan; pharmaceuticals: ibuprofen, furosemide, trimethoprim) at concentrations corresponding to their Lowest Observed Effect Concentration (LOEC). After 24, 48, 72, and 96 h of exposure, changes in the distance moved, the average speed, and the frequency of body bends were taken to reflect contaminant- and time-dependent effects on larval behaviour. In general, metolachlor, captan, and trimethoprim tended to reduce all the endpoints under consideration, whereas chlorpyrifos, boscalid, ibuprofen, and furosemide seemed to increase the distances moved by the larvae. This could be related to the different mechanisms of action of the investigated chemicals. Independently of the contaminant, after 72 h a general slowing down of all the

  2. Multiple stressor effects in Chlamydomonas reinhardtii – Toward understanding mechanisms of interaction between effects of ultraviolet radiation and chemical pollutants

    Energy Technology Data Exchange (ETDEWEB)

    Korkaric, Muris [Eawag, Swiss Federal Institute of Aquatic Science and Technology, Department of Environmental Toxicology, 8600, Duebendorf (Switzerland); ETH Zürich, Institute of Biogeochemistry and Pollutant Dynamics, 8092 Zürich (Switzerland); Behra, Renata; Fischer, Beat B. [Eawag, Swiss Federal Institute of Aquatic Science and Technology, Department of Environmental Toxicology, 8600, Duebendorf (Switzerland); Junghans, Marion [Swiss Center for Applied Ecotoxicology Eawag-EPFL, 8600, Duebendorf (Switzerland); Eggen, Rik I.L., E-mail: rik.eggen@eawag.ch [Eawag, Swiss Federal Institute of Aquatic Science and Technology, Department of Environmental Toxicology, 8600, Duebendorf (Switzerland); ETH Zürich, Institute of Biogeochemistry and Pollutant Dynamics, 8092 Zürich (Switzerland)

    2015-05-15

    Highlights: • Systematic study of multiple stressor effects of UVR and chemicals in C. reinhardtii. • UVR and chemicals did not act independently on algal photosynthesis and reproduction. • Multiple stressor effects of UVR and chemicals depended on chemical MOA. • Synergistic effect interactions not limited to oxidative stress inducing chemicals. • Multiple MOAs of UVR may limit applicability of current prediction models. - Abstract: The effects of chemical pollutants and environmental stressors, such as ultraviolet radiation (UVR), can interact when organisms are simultaneously exposed, resulting in higher (synergistic) or lower (antagonistic) multiple stressor effects than expected based on the effects of single stressors. Current understanding of interactive effects is limited due to a lack of mechanism-based multiple stressor studies. It has been hypothesized that effect interactions may generally occur if chemical and non-chemical stressors cause similar physiological effects in the organism. To test this hypothesis, we exposed the model green alga Chlamydomonas reinhardtii to combinations of UVR and single chemicals displaying modes of action (MOA) similar or dissimilar to the impact of UVR on photosynthesis. Stressor interactions were analyzed based on the independent action model. Effect interactions were found to depend on the MOA of the chemicals, and also on their concentrations, the exposure time and the measured endpoint. Indeed, only chemicals assumed to cause effects on photosynthesis similar to UVR showed interactions with UVR on photosynthetic yield: synergistic in case of Cd(II) and paraquat and antagonistic in case of diuron. No interaction on photosynthesis was observed for S-metolachlor, which acts dissimilarly to UVR. However, combined effects of S-metolachlor and UVR on algal reproduction were synergistic, highlighting the importance of considering additional MOA of UVR. Possible mechanisms of stressor effect interactions are

  3. Interactions of tillage and cover crop on water, sediment, and pre-emergence herbicide loss in glyphosate-resistant cotton: implications for the control of glyphosate-resistant weed biotypes.

    Science.gov (United States)

    Krutz, L Jason; Locke, Martin A; Steinriede, R Wade

    2009-01-01

    The need to control glyphosate [N-(phosphonomethyl)glycine]-resistant weed biotypes with tillage and preemergence herbicides in glyphosate-resistant crops (GRCs) is causing a reduction in no-tillage hectarage thereby threatening the advances made in water quality over the past decade. Consequently, if environmental gains afforded by GRCs are to be maintained, then an in-field best management practice (BMP) compatible with tillage is required for hectarage infested with glyphosate-resistant weed biotypes. Thus, 1 d after a preemergent application of fluometuron [N,N-dimethyl-N'-(3-(trifluoromethyl)phenyl)urea] (1.02 kg ha(-1)) and metolachlor [2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl)acetamide] (1.18 kg ha(-1)) to a Dundee silt loam (fine-silty, mixed, active, thermic Typic Endoaqualf), simulated rainfall (60 mm h(-1)) was applied to 0.0002-ha microplots for approximately 1.25 h to elucidate tillage (no tillage [NT] and reduced tillage [RT])and cover crop (no cover [NC] and rye cover [RC]) effects on water, sediment, and herbicide loss in surface runoff. Regardless of tillage, RC delayed time-to-runoff 1.3-fold, reduced cumulative runoff volume 1.4-fold, and decreased cumulative sediment loss 4.7-fold. Cumulative fluometuron loss was not affected by tillage or cover crop. Conversely, total metolachlor loss was 1.3-fold lower in NT than RT and 1.4-fold lower in RC than NC. These data indicate that RC can be established in hectarage requiring tillage and potentially curtail water, sediment, and preemergence herbicide losses in the spring to levels equivalent to or better than that of NT, thereby protecting environmental gains provided by GRCs.

  4. Multiple stressor effects in Chlamydomonas reinhardtii – Toward understanding mechanisms of interaction between effects of ultraviolet radiation and chemical pollutants

    International Nuclear Information System (INIS)

    Korkaric, Muris; Behra, Renata; Fischer, Beat B.; Junghans, Marion; Eggen, Rik I.L.

    2015-01-01

    Highlights: • Systematic study of multiple stressor effects of UVR and chemicals in C. reinhardtii. • UVR and chemicals did not act independently on algal photosynthesis and reproduction. • Multiple stressor effects of UVR and chemicals depended on chemical MOA. • Synergistic effect interactions not limited to oxidative stress inducing chemicals. • Multiple MOAs of UVR may limit applicability of current prediction models. - Abstract: The effects of chemical pollutants and environmental stressors, such as ultraviolet radiation (UVR), can interact when organisms are simultaneously exposed, resulting in higher (synergistic) or lower (antagonistic) multiple stressor effects than expected based on the effects of single stressors. Current understanding of interactive effects is limited due to a lack of mechanism-based multiple stressor studies. It has been hypothesized that effect interactions may generally occur if chemical and non-chemical stressors cause similar physiological effects in the organism. To test this hypothesis, we exposed the model green alga Chlamydomonas reinhardtii to combinations of UVR and single chemicals displaying modes of action (MOA) similar or dissimilar to the impact of UVR on photosynthesis. Stressor interactions were analyzed based on the independent action model. Effect interactions were found to depend on the MOA of the chemicals, and also on their concentrations, the exposure time and the measured endpoint. Indeed, only chemicals assumed to cause effects on photosynthesis similar to UVR showed interactions with UVR on photosynthetic yield: synergistic in case of Cd(II) and paraquat and antagonistic in case of diuron. No interaction on photosynthesis was observed for S-metolachlor, which acts dissimilarly to UVR. However, combined effects of S-metolachlor and UVR on algal reproduction were synergistic, highlighting the importance of considering additional MOA of UVR. Possible mechanisms of stressor effect interactions are

  5. Community air monitoring for pesticides-part 2: multiresidue determination of pesticides in air by gas chromatography, gas chromatography-mass spectrometry, and liquid chromatography-mass spectrometry.

    Science.gov (United States)

    Hengel, Matt; Lee, P

    2014-03-01

    Two multiresidue methods were developed to determine pesticides in air collected in California. Pesticides were trapped using XAD-4 resin and extracted with ethyl acetate. Based on an analytical method from the University of California Davis Trace Analytical Laboratory, pesticides were detected by analyzing the extract by gas chromatography-mass spectrometry (GC-MS) to determine chlorothalonil, chlorthal-dimethyl, cycloate, dicloran, dicofol, EPTC, ethalfluralin, iprodione, mefenoxam, metolachlor, PCNB, permethrin, pronamide, simazine, trifluralin, and vinclozolin. A GC with a flame photometric detector was used to determine chlorpyrifos, chlorpyrifos oxon, diazinon, diazinon oxon, dimethoate, dimethoate oxon, fonophos, fonophos oxon, malathion, malathion oxon, naled, and oxydemeton. Trapping efficiencies ranged from 78 to 92 % for low level (0.5 μg) and 37-104 % for high level (50 and 100 μg) recoveries. Little to no degradation of compounds occurred over 31 days; recoveries ranged from 78 to 113 %. In the California Department of Food and Agriculture (CDFA) method, pesticides were detected by analyzing the extract by GC-MS to determine chlorothalonil, chlorpyrifos, cypermethrin, dichlorvos, dicofol, endosulfan 1, endosulfan sulfate, oxyfluorfen, permethrin, propargite, and trifluralin. A liquid chromatograph coupled to a MS was used to determine azinphos-methyl, chloropyrifos oxon, DEF, diazinon, diazinon oxon, dimethoate, dimethoate oxon, diuron, EPTC, malathion, malathion oxon, metolachlor, molinate, norflurazon, oryzalin, phosmet, propanil, simazine and thiobencarb. Trapping efficiencies for compounds determined by the CDFA method ranged from 10 to 113, 22 to 114, and 56 to 132 % for 10, 5, and 2 μg spikes, respectively. Storage tests yielded 70-170 % recovery for up to 28 days. These multiresidue methods represent flexible, sensitive, accurate, and cost-effective ways to determine residues of various pesticides in ambient air.

  6. Performance and Economics of Growing Maize under Organic and Inorganic Fertilization and Weed Management

    International Nuclear Information System (INIS)

    Ali, A.; Khan, M. A.; Jan, A. U.; Jan, D.; Sattar, S.; Saleem, A.; Marwat, K. B.

    2016-01-01

    Weed competition and imbalanced fertilizers are important yield reducing factors in maize. To investigate the impact of weed management and combinations of fertilizers on yield and net income of maize, a field trial was conducted at National Agricultural Research Centre, Islamabad, Pakistan during summer 2014. Randomized complete block design with split-plot arrangement was used with three replications. Four weeds pressures viz. (1) hand weeding at 25 cm on both sides of each row of maize plants, (2) No hand weeding at 25 cm on both sides of maize rows, (3) application of Primextra gold (atrazine plus S-metolachlor) at the rate of 1.44 kg a.i. ha/sup -1/ as pre-emergence and (4) weedy check (control) were assigned to main plots. While different combinations of NPK were assigned to sub plots. Data revealed that dry weed biomass close to maize plants were significantly lower (140.4 kg ha/sup -1/) as compared to weeds 25 cm away from maize plants (153.2 kg ha/sup -1/). However, the application of atrazine plus S-metolachlor showed promising results by decreasing the weed biomass (53.6 kg ha/sup -1/) as compared to 155.6 kg ha/sup -1/ in control. Combination of fertilizers, also significantly affected the weed biomass. As compared to control, all the fertilizers (N, P and K) significantly increased weed biomass. Presence of weeds close to the crop rows, proved more harmful for grain yield of maize. Overall, application of herbicide in combination with NPK showed promising results in term of weed control and grain yield. Net income was higher when herbicide in combination with N, P or NP was used. (author)

  7. Environmental monitoring of selected pesticides and organic chemicals in urban stormwater recycling systems using passive sampling techniques.

    Science.gov (United States)

    Page, Declan; Miotliński, Konrad; Gonzalez, Dennis; Barry, Karen; Dillon, Peter; Gallen, Christie

    2014-03-01

    Water recycling via aquifers has become a valuable tool to augment urban water supplies in many countries. This study reports the first use of passive samplers for monitoring of organic micropollutants in Managed Aquifer Recharge (MAR). Five different configurations of passive samplers were deployed in a stormwater treatment wetland, groundwater monitoring wells and a recovery tank to capture a range of polar and non-polar micropollutants present in the system. The passive samplers were analysed for a suite of pesticides, polycyclic aromatic hydrocarbons (PAHs) and other chemicals. As a result, 17 pesticides and pesticide degradation products, 5 PAHs and 8 other organic chemicals including flame retardants and fragrances were detected in urban stormwater recharging Aquifer Storage and Recovery (ASR) and an Aquifer Storage Transfer and Recovery (ASTR) system. Of the pesticides detected, diuron, metolachlor and chlorpyrifos were generally detected at the highest concentrations in one or more passive samplers, whereas chlorpyrifos, diuron, metolachlor, simazine, galaxolide and triallate were detected in multiple samplers. Fluorene was the PAH detected at the highest concentration and the flame retardant Tris(1-chloro-2-propyl)phosphate was the chemical detected in the greatest abundance at all sites. The passive samplers showed different efficiencies for capture of micropollutants with the Empore disc samplers giving the most reliable results. The results indicate generally low levels of organic micropollutants in the stormwater, as the contaminants detected were present at very low ng/L levels, generally two to four orders of magnitude below the drinking water guidelines (NHMRC, 2011). The efficiency of attenuation of these organic micropollutants during MAR was difficult to determine due to variations in the source water concentrations. Comparisons were made between different samplers, to give a field-based calibration where existing lab-based calibrations were

  8. Controle de plantas daninhas com cyanazine aplicado em mistura com outros herbicidas, na cultura do algodão (Gossypium hirsutum L. Weed control in cotton (Gossypium hirsutum L. with cyanazine and other herbicides

    Directory of Open Access Journals (Sweden)

    Julio Pedro Laca-Buendia

    1985-12-01

    Full Text Available Com a finalidade de estudar a mistura de tanque mais eficiente com cyanazine em aplicação de pré-emergência na cultura algodoeira (Gossypium hirsutum L. , foram estudados os seguintes tratamentos: cyanazine + diuron nas doses de 0,8 + 0,8 kg i.a/ha e 1,0 + 1,0 kg i.a/ha; cyanazine+ oryzalin , nas do sés de 1,2 + 0,8 kg i.a/ha e 1,6 + 1,2 kg i.a/h a; cyanazyne + metol a chlor, nas doses de 1,4 + 2,0 kg i.a/ha e 1,75 + 2,52 kg i.a/ ha;cianazine na dose de 1,75 kg i.a /ha; oryzalin na dose de 1,12 kg i.a/ha; metol achlor na dose de 2,52 kg i.a /ha e diuron na dose de 1,6 kg i.a /ha. Para efeito de comparação, utilizou-se uma testemunha sem capina e outra com capina manual. Nenhum tratamento apresentou injúria para as plantas de algodão e não houve diferenças significativas para o "stand" inicial. Já no "stand" final, a testemunha sem capina apresentou o menor número de plantas, sendo que não houve diferenças significativas dos outros tratamentos com a testemunha capinada. Para o rendimento, a mistura cyanazine + metolachior em ambas as doses estudadas, não apresentaram diferenças significativas da testemunha capinada. Quanto à altura da planta, peso de 100 sementes, porcentagem e índice de fibras não houve diferenças significativas entre os tratamentos estudados, somente o peso do capulho foi afetado pelo oryzalin. Pela avaliação visual (EWRC 1 a 9*, os herbicidas apres entaram um controle satisfatório somente até os 30 dias após aplicação, sendo que a mistura cyanazine + metolachlor foi efici ente quanto a testemunha capinada. No controle da Portulaca oleracea , a mistura cyanazine + oryzalin na maior dose e oryzalin apresentaram 71,4% de controle ate os 30 dias e 79,4% e 82,4%, respectivamente, até 45 dias da aplicação. Para Amaranthus sp., à exceção da cyanazine e cyanazine + diuron nas doses menores, não apresentaram nenhum controle, sendo que os outros herbicidas controlaram com eficiência superior a 70

  9. Tolerância inicial de plantas de pinhão-manso a herbicidas aplicados em pré e pós-emergência Initial tolerance of physic nut plants to pre and post-emergence herbicide application

    Directory of Open Access Journals (Sweden)

    E.A.L. Erasmo

    2009-01-01

    Full Text Available O presente trabalho teve por objetivo avaliar a tolerância inicial de plantas de pinhão-manso a herbicidas pré e pós-emergentes, aplicados isolados e em misturas. Foram realizados dois experimentos em condições de campo, sendo um com herbicidas pré-emergentes e outro com herbicidas pós-emergentes. Os tratamentos com os herbicidas pré-emergentes utilizados foram: atrazine (3.000 g ha-1, diuron (2.000 g ha-1, oxyfluorfen (720 g ha-1, trifluralin (890 g ha-1, pendimethalin (1.250 g ha-1, isoxaflutole (93,8 g ha-1, S-metolachlor (1.920 g ha-1, atrazine+S-metolachlor (1.500+960 g ha-1, isoxaflutole+diuron (46,9+1.000 g ha-1, trifluralin+diuron (450+1.000 g ha-1, além de uma testemunha sem aplicação. Os tratamentos com os herbicidas pós-emergentes foram: haloxyfop-methyl (60 g ha-1, nicosulfuron (60 g ha-1, sethoxydim (368 g ha-1, fluazifop-p-butyl (125 g ha-1, fluazifop-p-butyl (250 g ha-1, fomesafen (125 g ha-1, fomesafen (250 g ha-1, fluazifop-p-butyl+fomesafen (250+250 g ha-1, fluazifop-p-butyl+fomesafen (200+250 g ha ¹, clethodim + fenoxaprop-p-ethyl (50+50 g ha-1, além de uma testemunha sem aplicação e outra capinada. Os tratamentos foram dispostos em delineamento experimental de blocos casualizados, com quatro repetições. No experimento com herbicidas pré-emergentes verificou-se que plantas de pinhão-manso foram tolerantes ao diuron, trifluralin, pendimethalin, isoxaflutole, S-metolachlor e às misturas isoxaflutole+diuron e trifluralin+diuron. Com relação ao experimento com herbicidas pós-emergentes, destacaram-se o haloxyfop-methyl, sethoxydim, fluazifop-p-butyl (125 g ha-1 e a mistura clethodim+fenoxaprop-p-ethyl.This study aimed to evaluate the initial tolerance of physic nut plants to pre and post-emergence herbicides, applied alone and in mixtures. Thus, two experiments were conducted under field conditions, one with pre-emergence herbicides and the other with post-emergence herbicides. The treatments using the pre

  10. Exploring Large Scale Data Analysis and Visualization for ARM Data Discovery Using NoSQL Technologies

    Science.gov (United States)

    Krishna, B.; Gustafson, W. I., Jr.; Vogelmann, A. M.; Toto, T.; Devarakonda, R.; Palanisamy, G.

    2016-12-01

    This paper presents a new way of providing ARM data discovery through data analysis and visualization services. ARM stands for Atmospheric Radiation Measurement. This Program was created to study cloud formation processes and their influence on radiative transfer and also include additional measurements of aerosol and precipitation at various highly instrumented ground and mobile stations. The total volume of ARM data is roughly 900TB. The current search for ARM data is performed by using its metadata, such as the site name, instrument name, date, etc. NoSQL technologies were explored to improve the capabilities of data searching, not only by their metadata, but also by using the measurement values. Two technologies that are currently being implemented for testing are Apache Cassandra (noSQL database) and Apache Spark (noSQL based analytics framework). Both of these technologies were developed to work in a distributed environment and hence can handle large data for storing and analytics. D3.js is a JavaScript library that can generate interactive data visualizations in web browsers by making use of commonly used SVG, HTML5, and CSS standards. To test the performance of NoSQL for ARM data, we will be using ARM's popular measurements to locate the data based on its value. Recently noSQL technology has been applied to a pilot project called LASSO, which stands for LES ARM Symbiotic Simulation and Observation Workflow. LASSO will be packaging LES output and observations in "data bundles" and analyses will require the ability for users to analyze both observations and LES model output either individually or together across multiple time periods. The LASSO implementation strategy suggests that enormous data storage is required to store the above mentioned quantities. Thus noSQL was used to provide a powerful means to store portions of the data that provided users with search capabilities on each simulation's traits through a web application. Based on the user selection

  11. Je ne menge poinct de porcq: Orlando di Lasso’s Early Parody Mass

    Directory of Open Access Journals (Sweden)

    Klemen Grabnar

    2013-07-01

    Full Text Available One of the most remarkable 16th-century composers was Orlando di Lasso (1530/1532–1594, perhaps the most prominent musician of his time. In the second half of the 16th and the early 17th centuries, his works were widespread across Europe, especially in its central and western part. Some of the surviving contemporary sources of Lasso’s music – both printed and manuscript – are preserved in Slovenian libraries and archives. Among them are two incompletely preserved manuscripts, dating from ca. 1600, today kept at the National and University Library in Ljubljana (Ms 232 and Ms 285. They both contain Lasso’s Missa super Je ne menge poinct de porcq, first published in Lasso’s second book of Masses, Quinque missae, by Claudio Merulo in 1570. Interestingly, this early Munich-period Mass is based on a Parisian chanson by Claudin de Sermisy (ca. 1490–1562, whose content is unequivocally scatological. It was quite common for 16th-century composers to base their settings of the Mass Ordinary on pre-existent polyphonic compositions, whether sacred or secular. One of the rare descriptions of this technique – widely known as parody technique – is given in Pietro Cerone’s El melopeo y maestro (1613. It can serve as the basis for an elementary analysis of how Lasso employed Sermisy’s chanson Je ne menge point de porc. The analysis shows that Lasso, for various reasons, does not always follow the established practices as they can be observed from Cerone’s treatise. Nevertheless he demonstrates significant skill in utilising borrowed material to compose his parody Mass. Lasso’s Missa super Je ne menge poinct de porcq is particularly intriguing due to its use of Sermisy’s chanson; what could be the reason for Lasso’s decision to use Sermisy’s profoundly secular chanson in order to compose a Mass setting? Although the answer can be multifaceted (such as an intention to establish a special textual relation between the Mass and the

  12. Predicting adenocarcinoma recurrence using computational texture models of nodule components in lung CT

    International Nuclear Information System (INIS)

    Depeursinge, Adrien; Yanagawa, Masahiro; Leung, Ann N.; Rubin, Daniel L.

    2015-01-01

    Purpose: To investigate the importance of presurgical computed tomography (CT) intensity and texture information from ground-glass opacities (GGO) and solid nodule components for the prediction of adenocarcinoma recurrence. Methods: For this study, 101 patients with surgically resected stage I adenocarcinoma were selected. During the follow-up period, 17 patients had disease recurrence with six associated cancer-related deaths. GGO and solid tumor components were delineated on presurgical CT scans by a radiologist. Computational texture models of GGO and solid regions were built using linear combinations of steerable Riesz wavelets learned with linear support vector machines (SVMs). Unlike other traditional texture attributes, the proposed texture models are designed to encode local image scales and directions that are specific to GGO and solid tissue. The responses of the locally steered models were used as texture attributes and compared to the responses of unaligned Riesz wavelets. The texture attributes were combined with CT intensities to predict tumor recurrence and patient hazard according to disease-free survival (DFS) time. Two families of predictive models were compared: LASSO and SVMs, and their survival counterparts: Cox-LASSO and survival SVMs. Results: The best-performing predictive model of patient hazard was associated with a concordance index (C-index) of 0.81 ± 0.02 and was based on the combination of the steered models and CT intensities with survival SVMs. The same feature group and the LASSO model yielded the highest area under the receiver operating characteristic curve (AUC) of 0.8 ± 0.01 for predicting tumor recurrence, although no statistically significant difference was found when compared to using intensity features solely. For all models, the performance was found to be significantly higher when image attributes were based on the solid components solely versus using the entire tumors (p < 3.08 × 10 −5 ). Conclusions: This study

  13. One-carbon metabolism, cognitive impairment and CSF measures of Alzheimer pathology: homocysteine and beyond.

    Science.gov (United States)

    Dayon, Loïc; Guiraud, Seu Ping; Corthésy, John; Da Silva, Laeticia; Migliavacca, Eugenia; Tautvydaitė, Domilė; Oikonomidi, Aikaterini; Moullet, Barbara; Henry, Hugues; Métairon, Sylviane; Marquis, Julien; Descombes, Patrick; Collino, Sebastiano; Martin, François-Pierre J; Montoliu, Ivan; Kussmann, Martin; Wojcik, Jérôme; Bowman, Gene L; Popp, Julius

    2017-06-17

    Hyperhomocysteinemia is a risk factor for cognitive decline and dementia, including Alzheimer disease (AD). Homocysteine (Hcy) is a sulfur-containing amino acid and metabolite of the methionine pathway. The interrelated methionine, purine, and thymidylate cycles constitute the one-carbon metabolism that plays a critical role in the synthesis of DNA, neurotransmitters, phospholipids, and myelin. In this study, we tested the hypothesis that one-carbon metabolites beyond Hcy are relevant to cognitive function and cerebrospinal fluid (CSF) measures of AD pathology in older adults. Cross-sectional analysis was performed on matched CSF and plasma collected from 120 older community-dwelling adults with (n = 72) or without (n = 48) cognitive impairment. Liquid chromatography-mass spectrometry was performed to quantify one-carbon metabolites and their cofactors. Least absolute shrinkage and selection operator (LASSO) regression was initially applied to clinical and biomarker measures that generate the highest diagnostic accuracy of a priori-defined cognitive impairment (Clinical Dementia Rating-based) and AD pathology (i.e., CSF tau phosphorylated at threonine 181 [p-tau181]/β-Amyloid 1-42 peptide chain [Aβ 1-42 ] >0.0779) to establish a reference benchmark. Two other LASSO-determined models were generated that included the one-carbon metabolites in CSF and then plasma. Correlations of CSF and plasma one-carbon metabolites with CSF amyloid and tau were explored. LASSO-determined models were stratified by apolipoprotein E (APOE) ε4 carrier status. The diagnostic accuracy of cognitive impairment for the reference model was 80.8% and included age, years of education, Aβ 1-42 , tau, and p-tau181. A model including CSF cystathionine, methionine, S-adenosyl-L-homocysteine (SAH), S-adenosylmethionine (SAM), serine, cysteine, and 5-methyltetrahydrofolate (5-MTHF) improved the diagnostic accuracy to 87.4%. A second model derived from plasma included cystathionine

  14. How powerful are summary-based methods for identifying expression-trait associations under different genetic architectures?

    Science.gov (United States)

    Veturi, Yogasudha; Ritchie, Marylyn D

    2018-01-01

    Transcriptome-wide association studies (TWAS) have recently been employed as an approach that can draw upon the advantages of genome-wide association studies (GWAS) and gene expression studies to identify genes associated with complex traits. Unlike standard GWAS, summary level data suffices for TWAS and offers improved statistical power. Two popular TWAS methods include either (a) imputing the cis genetic component of gene expression from smaller sized studies (using multi-SNP prediction or MP) into much larger effective sample sizes afforded by GWAS - TWAS-MP or (b) using summary-based Mendelian randomization - TWAS-SMR. Although these methods have been effective at detecting functional variants, it remains unclear how extensive variability in the genetic architecture of complex traits and diseases impacts TWAS results. Our goal was to investigate the different scenarios under which these methods yielded enough power to detect significant expression-trait associations. In this study, we conducted extensive simulations based on 6000 randomly chosen, unrelated Caucasian males from Geisinger's MyCode population to compare the power to detect cis expression-trait associations (within 500 kb of a gene) using the above-described approaches. To test TWAS across varying genetic backgrounds we simulated gene expression and phenotype using different quantitative trait loci per gene and cis-expression /trait heritability under genetic models that differentiate the effect of causality from that of pleiotropy. For each gene, on a training set ranging from 100 to 1000 individuals, we either (a) estimated regression coefficients with gene expression as the response using five different methods: LASSO, elastic net, Bayesian LASSO, Bayesian spike-slab, and Bayesian ridge regression or (b) performed eQTL analysis. We then sampled with replacement 50,000, 150,000, and 300,000 individuals respectively from the testing set of the remaining 5000 individuals and conducted GWAS on each

  15. Coupled bias-variance tradeoff for cross-pose face recognition.

    Science.gov (United States)

    Li, Annan; Shan, Shiguang; Gao, Wen

    2012-01-01

    Subspace-based face representation can be looked as a regression problem. From this viewpoint, we first revisited the problem of recognizing faces across pose differences, which is a bottleneck in face recognition. Then, we propose a new approach for cross-pose face recognition using a regressor with a coupled bias-variance tradeoff. We found that striking a coupled balance between bias and variance in regression for different poses could improve the regressor-based cross-pose face representation, i.e., the regressor can be more stable against a pose difference. With the basic idea, ridge regression and lasso regression are explored. Experimental results on CMU PIE, the FERET, and the Multi-PIE face databases show that the proposed bias-variance tradeoff can achieve considerable reinforcement in recognition performance.

  16. The Moonlandings

    Science.gov (United States)

    Turnill, Reginald; Buzz Aldrin, Foreword by

    2007-01-01

    Foreword Buzz Aldrin; Growing up with space - sources and acknowledgments; 1. The context: a twentieth-century Faust; 2. Preparing for manned spaceflight; 3. Gagarin puts Russia ahead; 4. The Moon and how to get there; 5. The seven story begins; 6. Glenn gets there first; 7. Sequels to the seven story; 8. Space travel: learning the rules; 9. Overtaking the Russians; 10. Apollo's bad start; 11. Lassoing the moon; 12. What makes an astronaut?; 13. Final rehearsals; 14. The eagle soars; 15. The eagle swoops; 16. First steps - and where they led; 17. The moonrocks - and Mars!; 18. Second steps on the moon; 19. The thirteen story; 20. Last men on the moon; 21. Apollo's inconclusive findings; 22. Epilogues to Apollo; 23. John Glenn's Apollo postscript; Bibliography; Appendices; Index.

  17. Partial correlation matrix estimation using ridge penalty followed by thresholding and re-estimation.

    Science.gov (United States)

    Ha, Min Jin; Sun, Wei

    2014-09-01

    Motivated by the problem of construction of gene co-expression network, we propose a statistical framework for estimating high-dimensional partial correlation matrix by a three-step approach. We first obtain a penalized estimate of a partial correlation matrix using ridge penalty. Next we select the non-zero entries of the partial correlation matrix by hypothesis testing. Finally we re-estimate the partial correlation coefficients at these non-zero entries. In the second step, the null distribution of the test statistics derived from penalized partial correlation estimates has not been established. We address this challenge by estimating the null distribution from the empirical distribution of the test statistics of all the penalized partial correlation estimates. Extensive simulation studies demonstrate the good performance of our method. Application on a yeast cell cycle gene expression data shows that our method delivers better predictions of the protein-protein interactions than the Graphic Lasso. © 2014, The International Biometric Society.

  18. Partial Correlation Matrix Estimation using Ridge Penalty Followed by Thresholding and Reestimation

    Science.gov (United States)

    2014-01-01

    Summary Motivated by the problem of construction gene co-expression network, we propose a statistical framework for estimating high-dimensional partial correlation matrix by a three-step approach. We first obtain a penalized estimate of a partial correlation matrix using ridge penalty. Next we select the non-zero entries of the partial correlation matrix by hypothesis testing. Finally we reestimate the partial correlation coefficients at these non-zero entries. In the second step, the null distribution of the test statistics derived from penalized partial correlation estimates has not been established. We address this challenge by estimating the null distribution from the empirical distribution of the test statistics of all the penalized partial correlation estimates. Extensive simulation studies demonstrate the good performance of our method. Application on a yeast cell cycle gene expression data shows that our method delivers better predictions of the protein-protein interactions than the Graphic Lasso. PMID:24845967

  19. Genomic-Enabled Prediction Based on Molecular Markers and Pedigree Using the Bayesian Linear Regression Package in R

    Directory of Open Access Journals (Sweden)

    Paulino Pérez

    2010-09-01

    Full Text Available The availability of dense molecular markers has made possible the use of genomic selection in plant and animal breeding. However, models for genomic selection pose several computational and statistical challenges and require specialized computer programs, not always available to the end user and not implemented in standard statistical software yet. The R-package BLR (Bayesian Linear Regression implements several statistical procedures (e.g., Bayesian Ridge Regression, Bayesian LASSO in a unified framework that allows including marker genotypes and pedigree data jointly. This article describes the classes of models implemented in the BLR package and illustrates their use through examples. Some challenges faced when applying genomic-enabled selection, such as model choice, evaluation of predictive ability through cross-validation, and choice of hyper-parameters, are also addressed.

  20. VQABQ: Visual Question Answering by Basic Questions

    KAUST Repository

    Huang, Jia-Hong

    2017-03-19

    Taking an image and question as the input of our method, it can output the text-based answer of the query question about the given image, so called Visual Question Answering (VQA). There are two main modules in our algorithm. Given a natural language question about an image, the first module takes the question as input and then outputs the basic questions of the main given question. The second module takes the main question, image and these basic questions as input and then outputs the text-based answer of the main question. We formulate the basic questions generation problem as a LASSO optimization problem, and also propose a criterion about how to exploit these basic questions to help answer main question. Our method is evaluated on the challenging VQA dataset and yields state-of-the-art accuracy, 60.34% in open-ended task.

  1. Covariate selection for the semiparametric additive risk model

    DEFF Research Database (Denmark)

    Martinussen, Torben; Scheike, Thomas

    2009-01-01

    This paper considers covariate selection for the additive hazards model. This model is particularly simple to study theoretically and its practical implementation has several major advantages to the similar methodology for the proportional hazards model. One complication compared...... and study their large sample properties for the situation where the number of covariates p is smaller than the number of observations. We also show that the adaptive Lasso has the oracle property. In many practical situations, it is more relevant to tackle the situation with large p compared with the number...... of observations. We do this by studying the properties of the so-called Dantzig selector in the setting of the additive risk model. Specifically, we establish a bound on how close the solution is to a true sparse signal in the case where the number of covariates is large. In a simulation study, we also compare...

  2. Diffusion Indexes With Sparse Loadings

    DEFF Research Database (Denmark)

    Kristensen, Johannes Tang

    2017-01-01

    The use of large-dimensional factor models in forecasting has received much attention in the literature with the consensus being that improvements on forecasts can be achieved when comparing with standard models. However, recent contributions in the literature have demonstrated that care needs...... to the problem by using the least absolute shrinkage and selection operator (LASSO) as a variable selection method to choose between the possible variables and thus obtain sparse loadings from which factors or diffusion indexes can be formed. This allows us to build a more parsimonious factor model...... in forecasting accuracy and thus find it to be an important alternative to PC. Supplementary materials for this article are available online....

  3. Supervised Learning for Dynamical System Learning.

    Science.gov (United States)

    Hefny, Ahmed; Downey, Carlton; Gordon, Geoffrey J

    2015-01-01

    Recently there has been substantial interest in spectral methods for learning dynamical systems. These methods are popular since they often offer a good tradeoff between computational and statistical efficiency. Unfortunately, they can be difficult to use and extend in practice: e.g., they can make it difficult to incorporate prior information such as sparsity or structure. To address this problem, we present a new view of dynamical system learning: we show how to learn dynamical systems by solving a sequence of ordinary supervised learning problems, thereby allowing users to incorporate prior knowledge via standard techniques such as L 1 regularization. Many existing spectral methods are special cases of this new framework, using linear regression as the supervised learner. We demonstrate the effectiveness of our framework by showing examples where nonlinear regression or lasso let us learn better state representations than plain linear regression does; the correctness of these instances follows directly from our general analysis.

  4. Statistical Validation of Normal Tissue Complication Probability Models

    Energy Technology Data Exchange (ETDEWEB)

    Xu Chengjian, E-mail: c.j.xu@umcg.nl [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schaaf, Arjen van der; Veld, Aart A. van' t; Langendijk, Johannes A. [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schilstra, Cornelis [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Radiotherapy Institute Friesland, Leeuwarden (Netherlands)

    2012-09-01

    Purpose: To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. Methods and Materials: A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Results: Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Conclusion: Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use.

  5. Testing the Lag Structure of Assets’ Realized Volatility Dynamics

    Directory of Open Access Journals (Sweden)

    Francesco Audrino

    2017-12-01

    Full Text Available A (conservative test is applied to investigate the optimal lag structure for modelingrealized volatility dynamics. The testing procedure relies on the recent theoretical results that showthe ability of the adaptive least absolute shrinkage and selection operator (adaptive lasso to combinee cient parameter estimation, variable selection, and valid inference for time series processes. In anapplication to several constituents of the S&P 500 index it is shown that (i the optimal significantlag structure is time-varying and subject to drastic regime shifts that seem to happen across assetssimultaneously; (ii in many cases the relevant information for prediction is included in the first 22lags, corroborating previous results concerning the accuracy and the diffculty of outperforming outof-sample the heterogeneous autoregressive (HAR model; and (iii some common features of theoptimal lag structure can be identified across assets belonging to the same market segment or showinga similar beta with respect to the market index.

  6. Novel Harmonic Regularization Approach for Variable Selection in Cox’s Proportional Hazards Model

    Directory of Open Access Journals (Sweden)

    Ge-Jin Chu

    2014-01-01

    Full Text Available Variable selection is an important issue in regression and a number of variable selection methods have been proposed involving nonconvex penalty functions. In this paper, we investigate a novel harmonic regularization method, which can approximate nonconvex Lq  (1/2Lasso series methods.

  7. Statistical validation of normal tissue complication probability models.

    Science.gov (United States)

    Xu, Cheng-Jian; van der Schaaf, Arjen; Van't Veld, Aart A; Langendijk, Johannes A; Schilstra, Cornelis

    2012-09-01

    To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use. Copyright © 2012 Elsevier Inc. All rights reserved.

  8. Sparse and shrunken estimates of MRI networks in the brain and their influence on network properties

    DEFF Research Database (Denmark)

    Romero-Garcia, Rafael; Clemmensen, Line Katrine Harder

    2014-01-01

    approaches showed more stable results with a relative low variance at the expense of a little bias. Interestingly, topological properties as local and global efficiency estimated in networks constructed from traditional non-regularized correlations also showed higher variability when compared to those from...... regularized networks. Our findings suggest that a population-based connectivity study can achieve a more robust description of cortical topology through regularization of the correlation estimates. Four regularization methods were examined: Two with shrinkage (Ridge and Schäfer’s shrinkage), one with sparsity...... (Lasso) and one with both shrinkage and sparsity (Elastic net). Furthermore, the different regularizations resulted in different correlation estimates as well as network properties. The shrunken estimates resulted in lower variance of the estimates than the sparse estimates....

  9. Statistical learning and selective inference.

    Science.gov (United States)

    Taylor, Jonathan; Tibshirani, Robert J

    2015-06-23

    We describe the problem of "selective inference." This addresses the following challenge: Having mined a set of data to find potential associations, how do we properly assess the strength of these associations? The fact that we have "cherry-picked"--searched for the strongest associations--means that we must set a higher bar for declaring significant the associations that we see. This challenge becomes more important in the era of big data and complex statistical modeling. The cherry tree (dataset) can be very large and the tools for cherry picking (statistical learning methods) are now very sophisticated. We describe some recent new developments in selective inference and illustrate their use in forward stepwise regression, the lasso, and principal components analysis.

  10. Quantum annealing versus classical machine learning applied to a simplified computational biology problem

    Science.gov (United States)

    Li, Richard Y.; Di Felice, Rosa; Rohs, Remo; Lidar, Daniel A.

    2018-01-01

    Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to predict binding specificity. Using simplified datasets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified datasets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems. PMID:29652405

  11. Which variety is free? Discerning the impact of product variety in the process industry

    DEFF Research Database (Denmark)

    Trattner, Alexandria Lee; Hvam, Lars; Herbert-Hansen, Zaza Nadja Lee

    In the pursuit of mass customization, it is a great challenge for companies to maintain mass production efficiencies while producing a wide range of prod-ucts. This poses an even a greater challenge to process industry manufactur-ing systems which are built for high volume, low variety operations...... and which are sensitive to changes in process parameters. Many studies have been performed to quantify the impact of product variety on the efficiency of automotive assembly processes, but little work has been done to address pro-cess manufacturing systems. This study aims to determine the effects of in......-dividual product features on machine productivity at a process industry manufacturer. A lasso regression model is developed and tested using actual product and process level data from a stone wool manufacturer in central Eu-rope. Results show that product features are less correlated to machine effi-ciency than...

  12. On Solving Lq-Penalized Regressions

    Directory of Open Access Journals (Sweden)

    Tracy Zhou Wu

    2007-01-01

    Full Text Available Lq-penalized regression arises in multidimensional statistical modelling where all or part of the regression coefficients are penalized to achieve both accuracy and parsimony of statistical models. There is often substantial computational difficulty except for the quadratic penalty case. The difficulty is partly due to the nonsmoothness of the objective function inherited from the use of the absolute value. We propose a new solution method for the general Lq-penalized regression problem based on space transformation and thus efficient optimization algorithms. The new method has immediate applications in statistics, notably in penalized spline smoothing problems. In particular, the LASSO problem is shown to be polynomial time solvable. Numerical studies show promise of our approach.

  13. Offshore high - Titanic challenge: Mastering moving mountains of ice tests men and machines

    Energy Technology Data Exchange (ETDEWEB)

    Will, G.

    1998-06-01

    Hibernia`s iceberg management program, which includes the difficult but occasional lassoing and towing of an iceberg to alter its direction away from the platform, was described. The platform has a concrete ice wall built around it which can withstand a six-million tonne iceberg, however, even small `bergy bits` or `growlers`, no larger than a typical bungalow, can inflict serious damage on semi-submersibles and other oil and gas installations on the Grand Banks. In the case of these smaller ice structures, propeller washing and water blasting are the favored techniques. With water blasting two water cannons are turned on the growler bobbing in the waves, the force of the jets driving it away from potential danger. Propeller washing is a similar technique, but instead of water cannons the ship`s churning propellers are used to send a bergy bit on its way, away from oil and gas installations.

  14. Prediction based on mean subset

    DEFF Research Database (Denmark)

    Øjelund, Henrik; Brown, P. J.; Madsen, Henrik

    2002-01-01

    , it is found that the proposed mean subset method has superior prediction performance than prediction based on the best subset method, and in some settings also better than the ridge regression and lasso methods. The conclusions drawn from the Monte Carlo study is corroborated in an example in which prediction......Shrinkage methods have traditionally been applied in prediction problems. In this article we develop a shrinkage method (mean subset) that forms an average of regression coefficients from individual subsets of the explanatory variables. A Bayesian approach is taken to derive an expression of how...... the coefficient vectors from each subset should be weighted. It is not computationally feasible to calculate the mean subset coefficient vector for larger problems, and thus we suggest an algorithm to find an approximation to the mean subset coefficient vector. In a comprehensive Monte Carlo simulation study...

  15. Learning investment indicators through data extension

    Science.gov (United States)

    Dvořák, Marek

    2017-07-01

    Stock prices in the form of time series were analysed using single and multivariate statistical methods. After simple data preprocessing in the form of logarithmic differences, we augmented this single variate time series to a multivariate representation. This method makes use of sliding windows to calculate several dozen of new variables using simple statistic tools like first and second moments as well as more complicated statistic, like auto-regression coefficients and residual analysis, followed by an optional quadratic transformation that was further used for data extension. These were used as a explanatory variables in a regularized logistic LASSO regression which tried to estimate Buy-Sell Index (BSI) from real stock market data.

  16. Simulation and inference for stochastic processes with YUIMA a comprehensive R framework for SDEs and other stochastic processes

    CERN Document Server

    Iacus, Stefano M

    2018-01-01

    The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stochastic differential equations driven by Wiener process, Lévy processes or fractional Brownian motion, as well as CARMA processes. The package performs various central statistical analyses such as quasi maximum likelihood estimation, adaptive Bayes estimation, structural change point analysis, hypotheses testing, asynchronous covariance estimation, lead-lag estimation, LASSO model selection, and so on. YUIMA also supports stochastic numerical analysis by fast computation of the expected value of functionals of stochastic processes through automatic asymptotic expansion by means of the Malliavin calculus. All models can be multidimensional, multiparametric or non parametric.The book explains briefly the underlying theory for simulation and inference of several classes of stochastic processes and then presents both simulation experiments and applications to real data. Although these ...

  17. Analysis of Genome-Wide Association Studies with Multiple Outcomes Using Penalization

    Science.gov (United States)

    Liu, Jin; Huang, Jian; Ma, Shuangge

    2012-01-01

    Genome-wide association studies have been extensively conducted, searching for markers for biologically meaningful outcomes and phenotypes. Penalization methods have been adopted in the analysis of the joint effects of a large number of SNPs (single nucleotide polymorphisms) and marker identification. This study is partly motivated by the analysis of heterogeneous stock mice dataset, in which multiple correlated phenotypes and a large number of SNPs are available. Existing penalization methods designed to analyze a single response variable cannot accommodate the correlation among multiple response variables. With multiple response variables sharing the same set of markers, joint modeling is first employed to accommodate the correlation. The group Lasso approach is adopted to select markers associated with all the outcome variables. An efficient computational algorithm is developed. Simulation study and analysis of the heterogeneous stock mice dataset show that the proposed method can outperform existing penalization methods. PMID:23272092

  18. Complete hazard ranking to analyze right-censored data: An ALS survival study.

    Directory of Open Access Journals (Sweden)

    Zhengnan Huang

    2017-12-01

    Full Text Available Survival analysis represents an important outcome measure in clinical research and clinical trials; further, survival ranking may offer additional advantages in clinical trials. In this study, we developed GuanRank, a non-parametric ranking-based technique to transform patients' survival data into a linear space of hazard ranks. The transformation enables the utilization of machine learning base-learners including Gaussian process regression, Lasso, and random forest on survival data. The method was submitted to the DREAM Amyotrophic Lateral Sclerosis (ALS Stratification Challenge. Ranked first place, the model gave more accurate ranking predictions on the PRO-ACT ALS dataset in comparison to Cox proportional hazard model. By utilizing right-censored data in its training process, the method demonstrated its state-of-the-art predictive power in ALS survival ranking. Its feature selection identified multiple important factors, some of which conflicts with previous studies.

  19. Finger vein recognition with personalized feature selection.

    Science.gov (United States)

    Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Meng, Xianjing

    2013-08-22

    Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG). For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG.

  20. Finger Vein Recognition with Personalized Feature Selection

    Directory of Open Access Journals (Sweden)

    Xianjing Meng

    2013-08-01

    Full Text Available Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG. For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG.

  1. Coupling bacterioplankton populations and environment to community function in coastal temperate waters

    DEFF Research Database (Denmark)

    Traving, S. J.; Bentzon-Tilia, Mikkel; Knudsen-Leerbeck, H.

    2016-01-01

    Bacterioplankton play a key role in marine waters facilitating processes important for carbon cycling. However, the influence of specific bacterial populations and environmental conditions on bacterioplankton community performance remains unclear. The aim of the present study was to identify...... drivers of bacterioplankton community functions, taking into account the variability in community composition and environmental conditions over seasons, in two contrasting coastal systems. A Least Absolute Shrinkage and Selection Operator (LASSO) analysis of the biological and chemical data obtained from...... surface waters over a full year indicated that specific bacterial populations were linked to measured functions. Namely, Synechococcus (Cyanobacteria) was strongly correlated with protease activity. Both function and community composition showed seasonal variation. However, the pattern of substrate...

  2. Predictive Modeling in Race Walking

    Directory of Open Access Journals (Sweden)

    Krzysztof Wiktorowicz

    2015-01-01

    Full Text Available This paper presents the use of linear and nonlinear multivariable models as tools to support training process of race walkers. These models are calculated using data collected from race walkers’ training events and they are used to predict the result over a 3 km race based on training loads. The material consists of 122 training plans for 21 athletes. In order to choose the best model leave-one-out cross-validation method is used. The main contribution of the paper is to propose the nonlinear modifications for linear models in order to achieve smaller prediction error. It is shown that the best model is a modified LASSO regression with quadratic terms in the nonlinear part. This model has the smallest prediction error and simplified structure by eliminating some of the predictors.

  3. Complete hazard ranking to analyze right-censored data: An ALS survival study.

    Science.gov (United States)

    Huang, Zhengnan; Zhang, Hongjiu; Boss, Jonathan; Goutman, Stephen A; Mukherjee, Bhramar; Dinov, Ivo D; Guan, Yuanfang

    2017-12-01

    Survival analysis represents an important outcome measure in clinical research and clinical trials; further, survival ranking may offer additional advantages in clinical trials. In this study, we developed GuanRank, a non-parametric ranking-based technique to transform patients' survival data into a linear space of hazard ranks. The transformation enables the utilization of machine learning base-learners including Gaussian process regression, Lasso, and random forest on survival data. The method was submitted to the DREAM Amyotrophic Lateral Sclerosis (ALS) Stratification Challenge. Ranked first place, the model gave more accurate ranking predictions on the PRO-ACT ALS dataset in comparison to Cox proportional hazard model. By utilizing right-censored data in its training process, the method demonstrated its state-of-the-art predictive power in ALS survival ranking. Its feature selection identified multiple important factors, some of which conflicts with previous studies.

  4. Performance of Dower's inverse transform and Frank lead system for Identification of Myocardial Infarction.

    Science.gov (United States)

    Aranda, A; Bonizzi, P; Karel, J; Peeters, R

    2015-08-01

    This study performs a comparison between Dower's inverse transform and Frank lead system for Myocardial Infarction (MI) identification. We have selected a set of relevant features for MI detection from the vectorcardiogram and used the lasso method after that to build a model for the Dower's inverse transform and one for the Frank leads system. Then we analyzed the performance between both models on MI detection. The proposed methods have been tested using PhysioNet PTB database that contains 550 records from which 368 are MIs. Two main conclusions are coming from this study. The first one is that Dower's inverse transform performs equally well than Frank leads in identification of MI patients. The second one is that lead positions have a large influence on the accuracy of MI patient identification.

  5. VQABQ: Visual Question Answering by Basic Questions

    KAUST Repository

    Huang, Jia-Hong; Alfadly, Modar; Ghanem, Bernard

    2017-01-01

    Taking an image and question as the input of our method, it can output the text-based answer of the query question about the given image, so called Visual Question Answering (VQA). There are two main modules in our algorithm. Given a natural language question about an image, the first module takes the question as input and then outputs the basic questions of the main given question. The second module takes the main question, image and these basic questions as input and then outputs the text-based answer of the main question. We formulate the basic questions generation problem as a LASSO optimization problem, and also propose a criterion about how to exploit these basic questions to help answer main question. Our method is evaluated on the challenging VQA dataset and yields state-of-the-art accuracy, 60.34% in open-ended task.

  6. DISIS: prediction of drug response through an iterative sure independence screening.

    Directory of Open Access Journals (Sweden)

    Yun Fang

    Full Text Available Prediction of drug response based on genomic alterations is an important task in the research of personalized medicine. Current elastic net model utilized a sure independence screening to select relevant genomic features with drug response, but it may neglect the combination effect of some marginally weak features. In this work, we applied an iterative sure independence screening scheme to select drug response relevant features from the Cancer Cell Line Encyclopedia (CCLE dataset. For each drug in CCLE, we selected up to 40 features including gene expressions, mutation and copy number alterations of cancer-related genes, and some of them are significantly strong features but showing weak marginal correlation with drug response vector. Lasso regression based on the selected features showed that our prediction accuracies are higher than those by elastic net regression for most drugs.

  7. Meta-analytic framework for sparse K-means to identify disease subtypes in multiple transcriptomic studies.

    Science.gov (United States)

    Huo, Zhiguang; Ding, Ying; Liu, Silvia; Oesterreich, Steffi; Tseng, George

    Disease phenotyping by omics data has become a popular approach that potentially can lead to better personalized treatment. Identifying disease subtypes via unsupervised machine learning is the first step towards this goal. In this paper, we extend a sparse K -means method towards a meta-analytic framework to identify novel disease subtypes when expression profiles of multiple cohorts are available. The lasso regularization and meta-analysis identify a unique set of gene features for subtype characterization. An additional pattern matching reward function guarantees consistent subtype signatures across studies. The method was evaluated by simulations and leukemia and breast cancer data sets. The identified disease subtypes from meta-analysis were characterized with improved accuracy and stability compared to single study analysis. The breast cancer model was applied to an independent METABRIC dataset and generated improved survival difference between subtypes. These results provide a basis for diagnosis and development of targeted treatments for disease subgroups.

  8. Genome wide association studies for body conformation traits in the Chinese Holstein cattle population

    DEFF Research Database (Denmark)

    Wu, Xiaoping; Fang, Ming; Liu, Lin

    2013-01-01

    .Results: The Illumina BovineSNP50 BeadChip was used to identify single nucleotide polymorphisms (SNPs) that are associated with body conformation traits. A least absolute shrinkage and selection operator (LASSO) was applied to detect multiple SNPs simultaneously for 29 body conformation traits with 1,314 Chinese...... Holstein cattle and 52,166 SNPs. Totally, 59 genome-wide significant SNPs associated with 26 conformation traits were detected by genome-wide association analysis; five SNPs were within previously reported QTL regions (Animal Quantitative Trait Loci (QTL) database) and 11 were very close to the reported...... SNPs. Twenty-two SNPs were located within annotated gene regions, while the remainder were 0.6-826 kb away from known genes. Some of the genes had clear biological functions related to conformation traits. By combining information about the previously reported QTL regions and the biological functions...

  9. Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling.

    Science.gov (United States)

    Wu, Hulin; Lu, Tao; Xue, Hongqi; Liang, Hua

    2014-04-02

    The gene regulation network (GRN) is a high-dimensional complex system, which can be represented by various mathematical or statistical models. The ordinary differential equation (ODE) model is one of the popular dynamic GRN models. High-dimensional linear ODE models have been proposed to identify GRNs, but with a limitation of the linear regulation effect assumption. In this article, we propose a sparse additive ODE (SA-ODE) model, coupled with ODE estimation methods and adaptive group LASSO techniques, to model dynamic GRNs that could flexibly deal with nonlinear regulation effects. The asymptotic properties of the proposed method are established and simulation studies are performed to validate the proposed approach. An application example for identifying the nonlinear dynamic GRN of T-cell activation is used to illustrate the usefulness of the proposed method.

  10. Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data.

    Science.gov (United States)

    Ching, Travers; Zhu, Xun; Garmire, Lana X

    2018-04-01

    Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet.

  11. Quantum annealing versus classical machine learning applied to a simplified computational biology problem

    Science.gov (United States)

    Li, Richard Y.; Di Felice, Rosa; Rohs, Remo; Lidar, Daniel A.

    2018-03-01

    Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to classify and rank binding affinities. Using simplified data sets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified data sets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems.

  12. Identification of biomarkers for Mycobacterium tuberculosis infection and disease in BCG-vaccinated young children in Southern India

    DEFF Research Database (Denmark)

    Dhanasekaran, S; Jenum, S; Stavrum, R

    2013-01-01

    Pediatric tuberculosis (TB) often goes undiagnosed because of the lack of reliable diagnostic methods. With the aim of assessing biomarker(s) that can aid in the diagnosis of TB infection and disease, we investigated 746 Indian children with suspected TB. Whole-blood mRNA from 210 children...... or equal to0.05) was downregulated in TB disease compared with uninfected controls, while transcription of RAB33A was downregulated in TB disease compared with both latent TB (Pcontrols (P....05) was upregulated in latent TB compared with that in controls. Using the Least Absolute Shrinkage and Selection Operator (lasso) model, RAB33A alone discriminated between TB disease and latent TB (area under the curve (AUC) 77.5%), whereas a combination of RAB33A, CXCL10, SEC14L1, FOXP3 and TNFRSF1A was effective...

  13. Predicting the Trends of Social Events on Chinese Social Media.

    Science.gov (United States)

    Zhou, Yang; Zhang, Lei; Liu, Xiaoqian; Zhang, Zhen; Bai, Shuotian; Zhu, Tingshao

    2017-09-01

    Growing interest in social events on social media came along with the rapid development of the Internet. Social events that occur in the "real" world can spread on social media (e.g., Sina Weibo) rapidly, which may trigger severe consequences and thus require the government's timely attention and responses. This article proposes to predict the trends of social events on Sina Weibo, which is currently the most popular social media in China. Based on the theories of social psychology and communication sciences, we extract an unprecedented amount of comprehensive and effective features that relate to the trends of social events on Chinese social media, and we construct the trends of prediction models by using three classical regression algorithms. We found that lasso regression performed better with the precision 0.78 and the recall 0.88. The results of our experiments demonstrated the effectiveness of our proposed approach.

  14. Stratification of TAD boundaries reveals preferential insulation of super-enhancers by strong boundaries.

    Science.gov (United States)

    Gong, Yixiao; Lazaris, Charalampos; Sakellaropoulos, Theodore; Lozano, Aurelie; Kambadur, Prabhanjan; Ntziachristos, Panagiotis; Aifantis, Iannis; Tsirigos, Aristotelis

    2018-02-07

    The metazoan genome is compartmentalized in areas of highly interacting chromatin known as topologically associating domains (TADs). TADs are demarcated by boundaries mostly conserved across cell types and even across species. However, a genome-wide characterization of TAD boundary strength in mammals is still lacking. In this study, we first use fused two-dimensional lasso as a machine learning method to improve Hi-C contact matrix reproducibility, and, subsequently, we categorize TAD boundaries based on their insulation score. We demonstrate that higher TAD boundary insulation scores are associated with elevated CTCF levels and that they may differ across cell types. Intriguingly, we observe that super-enhancers are preferentially insulated by strong boundaries. Furthermore, we demonstrate that strong TAD boundaries and super-enhancer elements are frequently co-duplicated in cancer patients. Taken together, our findings suggest that super-enhancers insulated by strong TAD boundaries may be exploited, as a functional unit, by cancer cells to promote oncogenesis.

  15. Applied multivariate statistical analysis

    CERN Document Server

    Härdle, Wolfgang Karl

    2015-01-01

    Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners.  It surveys the basic principles and emphasizes both exploratory and inferential statistics; a new chapter on Variable Selection (Lasso, SCAD and Elastic Net) has also been added.  All chapters include practical exercises that highlight applications in different multivariate data analysis fields: in quantitative financial studies, where the joint dynamics of assets are observed; in medicine, where recorded observations of subjects in different locations form the basis for reliable diagnoses and medication; and in quantitative marketing, where consumers’ preferences are collected in order to construct models of consumer behavior.  All of these examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. The fourth edition of this book on Applied Multivariate ...

  16. Multitask Classification Hypothesis Space With Improved Generalization Bounds.

    Science.gov (United States)

    Li, Cong; Georgiopoulos, Michael; Anagnostopoulos, Georgios C

    2015-07-01

    This paper presents a pair of hypothesis spaces (HSs) of vector-valued functions intended to be used in the context of multitask classification. While both are parameterized on the elements of reproducing kernel Hilbert spaces and impose a feature mapping that is common to all tasks, one of them assumes this mapping as fixed, while the more general one learns the mapping via multiple kernel learning. For these new HSs, empirical Rademacher complexity-based generalization bounds are derived, and are shown to be tighter than the bound of a particular HS, which has appeared recently in the literature, leading to improved performance. As a matter of fact, the latter HS is shown to be a special case of ours. Based on an equivalence to Group-Lasso type HSs, the proposed HSs are utilized toward corresponding support vector machine-based formulations. Finally, experimental results on multitask learning problems underline the quality of the derived bounds and validate this paper's analysis.

  17. Lassomycin, a ribosomally synthesized cyclic peptide, kills mycobacterium tuberculosis by targeting the ATP-dependent protease ClpC1P1P2.

    Science.gov (United States)

    Gavrish, Ekaterina; Sit, Clarissa S; Cao, Shugeng; Kandror, Olga; Spoering, Amy; Peoples, Aaron; Ling, Losee; Fetterman, Ashley; Hughes, Dallas; Bissell, Anthony; Torrey, Heather; Akopian, Tatos; Mueller, Andreas; Epstein, Slava; Goldberg, Alfred; Clardy, Jon; Lewis, Kim

    2014-04-24

    Languishing antibiotic discovery and flourishing antibiotic resistance have prompted the development of alternative untapped sources for antibiotic discovery, including previously uncultured bacteria. Here, we screen extracts from uncultured species against Mycobacterium tuberculosis and identify lassomycin, an antibiotic that exhibits potent bactericidal activity against both growing and dormant mycobacteria, including drug-resistant forms of M. tuberculosis, but little activity against other bacteria or mammalian cells. Lassomycin is a highly basic, ribosomally encoded cyclic peptide with an unusual structural fold that only partially resembles that of other lasso peptides. We show that lassomycin binds to a highly acidic region of the ClpC1 ATPase complex and markedly stimulates its ATPase activity without stimulating ClpP1P2-catalyzed protein breakdown, which is essential for viability of mycobacteria. This mechanism, uncoupling ATPase from proteolytic activity, accounts for the bactericidal activity of lassomycin. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. A computational model for biosonar echoes from foliage.

    Directory of Open Access Journals (Sweden)

    Chen Ming

    Full Text Available Since many bat species thrive in densely vegetated habitats, echoes from foliage are likely to be of prime importance to the animals' sensory ecology, be it as clutter that masks prey echoes or as sources of information about the environment. To better understand the characteristics of foliage echoes, a new model for the process that generates these signals has been developed. This model takes leaf size and orientation into account by representing the leaves as circular disks of varying diameter. The two added leaf parameters are of potential importance to the sensory ecology of bats, e.g., with respect to landmark recognition and flight guidance along vegetation contours. The full model is specified by a total of three parameters: leaf density, average leaf size, and average leaf orientation. It assumes that all leaf parameters are independently and identically distributed. Leaf positions were drawn from a uniform probability density function, sizes and orientations each from a Gaussian probability function. The model was found to reproduce the first-order amplitude statistics of measured example echoes and showed time-variant echo properties that depended on foliage parameters. Parameter estimation experiments using lasso regression have demonstrated that a single foliage parameter can be estimated with high accuracy if the other two parameters are known a priori. If only one parameter is known a priori, the other two can still be estimated, but with a reduced accuracy. Lasso regression did not support simultaneous estimation of all three parameters. Nevertheless, these results demonstrate that foliage echoes contain accessible information on foliage type and orientation that could play a role in supporting sensory tasks such as landmark identification and contour following in echolocating bats.

  19. Genome-wide prediction of traits with different genetic architecture through efficient variable selection.

    Science.gov (United States)

    Wimmer, Valentin; Lehermeier, Christina; Albrecht, Theresa; Auinger, Hans-Jürgen; Wang, Yu; Schön, Chris-Carolin

    2013-10-01

    In genome-based prediction there is considerable uncertainty about the statistical model and method required to maximize prediction accuracy. For traits influenced by a small number of quantitative trait loci (QTL), predictions are expected to benefit from methods performing variable selection [e.g., BayesB or the least absolute shrinkage and selection operator (LASSO)] compared to methods distributing effects across the genome [ridge regression best linear unbiased prediction (RR-BLUP)]. We investigate the assumptions underlying successful variable selection by combining computer simulations with large-scale experimental data sets from rice (Oryza sativa L.), wheat (Triticum aestivum L.), and Arabidopsis thaliana (L.). We demonstrate that variable selection can be successful when the number of phenotyped individuals is much larger than the number of causal mutations contributing to the trait. We show that the sample size required for efficient variable selection increases dramatically with decreasing trait heritabilities and increasing extent of linkage disequilibrium (LD). We contrast and discuss contradictory results from simulation and experimental studies with respect to superiority of variable selection methods over RR-BLUP. Our results demonstrate that due to long-range LD, medium heritabilities, and small sample sizes, superiority of variable selection methods cannot be expected in plant breeding populations even for traits like FRIGIDA gene expression in Arabidopsis and flowering time in rice, assumed to be influenced by a few major QTL. We extend our conclusions to the analysis of whole-genome sequence data and infer upper bounds for the number of causal mutations which can be identified by LASSO. Our results have major impact on the choice of statistical method needed to make credible inferences about genetic architecture and prediction accuracy of complex traits.

  20. Directional migration of recirculating lymphocytes through lymph nodes via random walks.

    Directory of Open Access Journals (Sweden)

    Niclas Thomas

    Full Text Available Naive T lymphocytes exhibit extensive antigen-independent recirculation between blood and lymph nodes, where they may encounter dendritic cells carrying cognate antigen. We examine how long different T cells may spend in an individual lymph node by examining data from long term cannulation of blood and efferent lymphatics of a single lymph node in the sheep. We determine empirically the distribution of transit times of migrating T cells by applying the Least Absolute Shrinkage & Selection Operator (LASSO or regularised S-LASSO to fit experimental data describing the proportion of labelled infused cells in blood and efferent lymphatics over time. The optimal inferred solution reveals a distribution with high variance and strong skew. The mode transit time is typically between 10 and 20 hours, but a significant number of cells spend more than 70 hours before exiting. We complement the empirical machine learning based approach by modelling lymphocyte passage through the lymph node insilico. On the basis of previous two photon analysis of lymphocyte movement, we optimised distributions which describe the transit times (first passage times of discrete one dimensional and continuous (Brownian three dimensional random walks with drift. The optimal fit is obtained when drift is small, i.e. the ratio of probabilities of migrating forward and backward within the node is close to one. These distributions are qualitatively similar to the inferred empirical distribution, with high variance and strong skew. In contrast, an optimised normal distribution of transit times (symmetrical around mean fitted the data poorly. The results demonstrate that the rapid recirculation of lymphocytes observed at a macro level is compatible with predominantly randomised movement within lymph nodes, and significant probabilities of long transit times. We discuss how this pattern of migration may contribute to facilitating interactions between low frequency T cells and antigen

  1. MO-FG-202-09: Virtual IMRT QA Using Machine Learning: A Multi-Institutional Validation

    Energy Technology Data Exchange (ETDEWEB)

    Valdes, G; Scheuermann, R; Solberg, T [University of Pennsylvania, Philadelphia, PA (United States); Chan, M; Deasy, J [Memorial Sloan-Kettering Cancer Center, New York, NY (United States)

    2016-06-15

    Purpose: To validate a machine learning approach to Virtual IMRT QA for accurately predicting gamma passing rates using different QA devices at different institutions. Methods: A Virtual IMRT QA was constructed using a machine learning algorithm based on 416 IMRT plans, in which QA measurements were performed using diode-array detectors and a 3%local/3mm with 10% threshold. An independent set of 139 IMRT measurements from a different institution, with QA data based on portal dosimetry using the same gamma index and 10% threshold, was used to further test the algorithm. Plans were characterized by 90 different complexity metrics. A weighted poison regression with Lasso regularization was trained to predict passing rates using the complexity metrics as input. Results: In addition to predicting passing rates with 3% accuracy for all composite plans using diode-array detectors, passing rates for portal dosimetry on per-beam basis were predicted with an error <3.5% for 120 IMRT measurements. The remaining measurements (19) had large areas of low CU, where portal dosimetry has larger disagreement with the calculated dose and, as such, large errors were expected. These beams need to be further modeled to correct the under-response in low dose regions. Important features selected by Lasso to predict gamma passing rates were: complete irradiated area outline (CIAO) area, jaw position, fraction of MLC leafs with gaps smaller than 20 mm or 5mm, fraction of area receiving less than 50% of the total CU, fraction of the area receiving dose from penumbra, weighted Average Irregularity Factor, duty cycle among others. Conclusion: We have demonstrated that the Virtual IMRT QA can predict passing rates using different QA devices and across multiple institutions. Prediction of QA passing rates could have profound implications on the current IMRT process.

  2. Content Coding of Psychotherapy Transcripts Using Labeled Topic Models.

    Science.gov (United States)

    Gaut, Garren; Steyvers, Mark; Imel, Zac E; Atkins, David C; Smyth, Padhraic

    2017-03-01

    Psychotherapy represents a broad class of medical interventions received by millions of patients each year. Unlike most medical treatments, its primary mechanisms are linguistic; i.e., the treatment relies directly on a conversation between a patient and provider. However, the evaluation of patient-provider conversation suffers from critical shortcomings, including intensive labor requirements, coder error, nonstandardized coding systems, and inability to scale up to larger data sets. To overcome these shortcomings, psychotherapy analysis needs a reliable and scalable method for summarizing the content of treatment encounters. We used a publicly available psychotherapy corpus from Alexander Street press comprising a large collection of transcripts of patient-provider conversations to compare coding performance for two machine learning methods. We used the labeled latent Dirichlet allocation (L-LDA) model to learn associations between text and codes, to predict codes in psychotherapy sessions, and to localize specific passages of within-session text representative of a session code. We compared the L-LDA model to a baseline lasso regression model using predictive accuracy and model generalizability (measured by calculating the area under the curve (AUC) from the receiver operating characteristic curve). The L-LDA model outperforms the lasso logistic regression model at predicting session-level codes with average AUC scores of 0.79, and 0.70, respectively. For fine-grained level coding, L-LDA and logistic regression are able to identify specific talk-turns representative of symptom codes. However, model performance for talk-turn identification is not yet as reliable as human coders. We conclude that the L-LDA model has the potential to be an objective, scalable method for accurate automated coding of psychotherapy sessions that perform better than comparable discriminative methods at session-level coding and can also predict fine-grained codes.

  3. A unified and comprehensible view of parametric and kernel methods for genomic prediction with application to rice

    Directory of Open Access Journals (Sweden)

    Laval Jacquin

    2016-08-01

    Full Text Available One objective of this study was to provide readers with a clear and unified understanding ofparametric statistical and kernel methods, used for genomic prediction, and to compare some ofthese in the context of rice breeding for quantitative traits. Furthermore, another objective wasto provide a simple and user-friendly R package, named KRMM, which allows users to performRKHS regression with several kernels. After introducing the concept of regularized empiricalrisk minimization, the connections between well-known parametric and kernel methods suchas Ridge regression (i.e. genomic best linear unbiased predictor (GBLUP and reproducingkernel Hilbert space (RKHS regression were reviewed. Ridge regression was then reformulatedso as to show and emphasize the advantage of the kernel trick concept, exploited by kernelmethods in the context of epistatic genetic architectures, over parametric frameworks used byconventional methods. Some parametric and kernel methods; least absolute shrinkage andselection operator (LASSO, GBLUP, support vector machine regression (SVR and RKHSregression were thereupon compared for their genomic predictive ability in the context of ricebreeding using three real data sets. Among the compared methods, RKHS regression and SVRwere often the most accurate methods for prediction followed by GBLUP and LASSO. An Rfunction which allows users to perform RR-BLUP of marker effects, GBLUP and RKHS regression,with a Gaussian, Laplacian, polynomial or ANOVA kernel, in a reasonable computation time hasbeen developed. Moreover, a modified version of this function, which allows users to tune kernelsfor RKHS regression, has also been developed and parallelized for HPC Linux clusters. The corresponding KRMM package and all scripts have been made publicly available.

  4. fastBMA: scalable network inference and transitive reduction.

    Science.gov (United States)

    Hung, Ling-Hong; Shi, Kaiyuan; Wu, Migao; Young, William Chad; Raftery, Adrian E; Yeung, Ka Yee

    2017-10-01

    Inferring genetic networks from genome-wide expression data is extremely demanding computationally. We have developed fastBMA, a distributed, parallel, and scalable implementation of Bayesian model averaging (BMA) for this purpose. fastBMA also includes a computationally efficient module for eliminating redundant indirect edges in the network by mapping the transitive reduction to an easily solved shortest-path problem. We evaluated the performance of fastBMA on synthetic data and experimental genome-wide time series yeast and human datasets. When using a single CPU core, fastBMA is up to 100 times faster than the next fastest method, LASSO, with increased accuracy. It is a memory-efficient, parallel, and distributed application that scales to human genome-wide expression data. A 10 000-gene regulation network can be obtained in a matter of hours using a 32-core cloud cluster (2 nodes of 16 cores). fastBMA is a significant improvement over its predecessor ScanBMA. It is more accurate and orders of magnitude faster than other fast network inference methods such as the 1 based on LASSO. The improved scalability allows it to calculate networks from genome scale data in a reasonable time frame. The transitive reduction method can improve accuracy in denser networks. fastBMA is available as code (M.I.T. license) from GitHub (https://github.com/lhhunghimself/fastBMA), as part of the updated networkBMA Bioconductor package (https://www.bioconductor.org/packages/release/bioc/html/networkBMA.html) and as ready-to-deploy Docker images (https://hub.docker.com/r/biodepot/fastbma/). © The Authors 2017. Published by Oxford University Press.

  5. Eigentumors for prediction of treatment failure in patients with early-stage breast cancer using dynamic contrast-enhanced MRI: a feasibility study

    Science.gov (United States)

    Chan, H. M.; van der Velden, B. H. M.; E Loo, C.; Gilhuijs, K. G. A.

    2017-08-01

    We present a radiomics model to discriminate between patients at low risk and those at high risk of treatment failure at long-term follow-up based on eigentumors: principal components computed from volumes encompassing tumors in washin and washout images of pre-treatment dynamic contrast-enhanced (DCE-) MR images. Eigentumors were computed from the images of 563 patients from the MARGINS study. Subsequently, a least absolute shrinkage selection operator (LASSO) selected candidates from the components that contained 90% of the variance of the data. The model for prediction of survival after treatment (median follow-up time 86 months) was based on logistic regression. Receiver operating characteristic (ROC) analysis was applied and area-under-the-curve (AUC) values were computed as measures of training and cross-validated performances. The discriminating potential of the model was confirmed using Kaplan-Meier survival curves and log-rank tests. From the 322 principal components that explained 90% of the variance of the data, the LASSO selected 28 components. The ROC curves of the model yielded AUC values of 0.88, 0.77 and 0.73, for the training, leave-one-out cross-validated and bootstrapped performances, respectively. The bootstrapped Kaplan-Meier survival curves confirmed significant separation for all tumors (P  <  0.0001). Survival analysis on immunohistochemical subgroups shows significant separation for the estrogen-receptor subtype tumors (P  <  0.0001) and the triple-negative subtype tumors (P  =  0.0039), but not for tumors of the HER2 subtype (P  =  0.41). The results of this retrospective study show the potential of early-stage pre-treatment eigentumors for use in prediction of treatment failure of breast cancer.

  6. MO-FG-202-09: Virtual IMRT QA Using Machine Learning: A Multi-Institutional Validation

    International Nuclear Information System (INIS)

    Valdes, G; Scheuermann, R; Solberg, T; Chan, M; Deasy, J

    2016-01-01

    Purpose: To validate a machine learning approach to Virtual IMRT QA for accurately predicting gamma passing rates using different QA devices at different institutions. Methods: A Virtual IMRT QA was constructed using a machine learning algorithm based on 416 IMRT plans, in which QA measurements were performed using diode-array detectors and a 3%local/3mm with 10% threshold. An independent set of 139 IMRT measurements from a different institution, with QA data based on portal dosimetry using the same gamma index and 10% threshold, was used to further test the algorithm. Plans were characterized by 90 different complexity metrics. A weighted poison regression with Lasso regularization was trained to predict passing rates using the complexity metrics as input. Results: In addition to predicting passing rates with 3% accuracy for all composite plans using diode-array detectors, passing rates for portal dosimetry on per-beam basis were predicted with an error <3.5% for 120 IMRT measurements. The remaining measurements (19) had large areas of low CU, where portal dosimetry has larger disagreement with the calculated dose and, as such, large errors were expected. These beams need to be further modeled to correct the under-response in low dose regions. Important features selected by Lasso to predict gamma passing rates were: complete irradiated area outline (CIAO) area, jaw position, fraction of MLC leafs with gaps smaller than 20 mm or 5mm, fraction of area receiving less than 50% of the total CU, fraction of the area receiving dose from penumbra, weighted Average Irregularity Factor, duty cycle among others. Conclusion: We have demonstrated that the Virtual IMRT QA can predict passing rates using different QA devices and across multiple institutions. Prediction of QA passing rates could have profound implications on the current IMRT process.

  7. Molecular Classification Substitutes for the Prognostic Variables Stage, Age, and MYCN Status in Neuroblastoma Risk Assessment

    Directory of Open Access Journals (Sweden)

    Carolina Rosswog

    2017-12-01

    Full Text Available BACKGROUND: Current risk stratification systems for neuroblastoma patients consider clinical, histopathological, and genetic variables, and additional prognostic markers have been proposed in recent years. We here sought to select highly informative covariates in a multistep strategy based on consecutive Cox regression models, resulting in a risk score that integrates hazard ratios of prognostic variables. METHODS: A cohort of 695 neuroblastoma patients was divided into a discovery set (n = 75 for multigene predictor generation, a training set (n = 411 for risk score development, and a validation set (n = 209. Relevant prognostic variables were identified by stepwise multivariable L1-penalized least absolute shrinkage and selection operator (LASSO Cox regression, followed by backward selection in multivariable Cox regression, and then integrated into a novel risk score. RESULTS: The variables stage, age, MYCN status, and two multigene predictors, NB-th24 and NB-th44, were selected as independent prognostic markers by LASSO Cox regression analysis. Following backward selection, only the multigene predictors were retained in the final model. Integration of these classifiers in a risk scoring system distinguished three patient subgroups that differed substantially in their outcome. The scoring system discriminated patients with diverging outcome in the validation cohort (5-year event-free survival, 84.9 ± 3.4 vs 63.6 ± 14.5 vs 31.0 ± 5.4; P < .001, and its prognostic value was validated by multivariable analysis. CONCLUSION: We here propose a translational strategy for developing risk assessment systems based on hazard ratios of relevant prognostic variables. Our final neuroblastoma risk score comprised two multigene predictors only, supporting the notion that molecular properties of the tumor cells strongly impact clinical courses of neuroblastoma patients.

  8. Molecular Classification Substitutes for the Prognostic Variables Stage, Age, and MYCN Status in Neuroblastoma Risk Assessment.

    Science.gov (United States)

    Rosswog, Carolina; Schmidt, Rene; Oberthuer, André; Juraeva, Dilafruz; Brors, Benedikt; Engesser, Anne; Kahlert, Yvonne; Volland, Ruth; Bartenhagen, Christoph; Simon, Thorsten; Berthold, Frank; Hero, Barbara; Faldum, Andreas; Fischer, Matthias

    2017-12-01

    Current risk stratification systems for neuroblastoma patients consider clinical, histopathological, and genetic variables, and additional prognostic markers have been proposed in recent years. We here sought to select highly informative covariates in a multistep strategy based on consecutive Cox regression models, resulting in a risk score that integrates hazard ratios of prognostic variables. A cohort of 695 neuroblastoma patients was divided into a discovery set (n=75) for multigene predictor generation, a training set (n=411) for risk score development, and a validation set (n=209). Relevant prognostic variables were identified by stepwise multivariable L1-penalized least absolute shrinkage and selection operator (LASSO) Cox regression, followed by backward selection in multivariable Cox regression, and then integrated into a novel risk score. The variables stage, age, MYCN status, and two multigene predictors, NB-th24 and NB-th44, were selected as independent prognostic markers by LASSO Cox regression analysis. Following backward selection, only the multigene predictors were retained in the final model. Integration of these classifiers in a risk scoring system distinguished three patient subgroups that differed substantially in their outcome. The scoring system discriminated patients with diverging outcome in the validation cohort (5-year event-free survival, 84.9±3.4 vs 63.6±14.5 vs 31.0±5.4; P<.001), and its prognostic value was validated by multivariable analysis. We here propose a translational strategy for developing risk assessment systems based on hazard ratios of relevant prognostic variables. Our final neuroblastoma risk score comprised two multigene predictors only, supporting the notion that molecular properties of the tumor cells strongly impact clinical courses of neuroblastoma patients. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  9. Gene expression network reconstruction by convex feature selection when incorporating genetic perturbations.

    Directory of Open Access Journals (Sweden)

    Benjamin A Logsdon

    Full Text Available Cellular gene expression measurements contain regulatory information that can be used to discover novel network relationships. Here, we present a new algorithm for network reconstruction powered by the adaptive lasso, a theoretically and empirically well-behaved method for selecting the regulatory features of a network. Any algorithms designed for network discovery that make use of directed probabilistic graphs require perturbations, produced by either experiments or naturally occurring genetic variation, to successfully infer unique regulatory relationships from gene expression data. Our approach makes use of appropriately selected cis-expression Quantitative Trait Loci (cis-eQTL, which provide a sufficient set of independent perturbations for maximum network resolution. We compare the performance of our network reconstruction algorithm to four other approaches: the PC-algorithm, QTLnet, the QDG algorithm, and the NEO algorithm, all of which have been used to reconstruct directed networks among phenotypes leveraging QTL. We show that the adaptive lasso can outperform these algorithms for networks of ten genes and ten cis-eQTL, and is competitive with the QDG algorithm for networks with thirty genes and thirty cis-eQTL, with rich topologies and hundreds of samples. Using this novel approach, we identify unique sets of directed relationships in Saccharomyces cerevisiae when analyzing genome-wide gene expression data for an intercross between a wild strain and a lab strain. We recover novel putative network relationships between a tyrosine biosynthesis gene (TYR1, and genes involved in endocytosis (RCY1, the spindle checkpoint (BUB2, sulfonate catabolism (JLP1, and cell-cell communication (PRM7. Our algorithm provides a synthesis of feature selection methods and graphical model theory that has the potential to reveal new directed regulatory relationships from the analysis of population level genetic and gene expression data.

  10. Pretreatment 18F-FDG PET Textural Features in Locally Advanced Non–Small Cell Lung Cancer: Secondary Analysis of ACRIN 6668/RTOG 0235

    Science.gov (United States)

    Ohri, Nitin; Duan, Fenghai; Snyder, Bradley S.; Wei, Bo; Machtay, Mitchell; Alavi, Abass; Siegel, Barry A.; Johnson, Douglas W.; Bradley, Jeffrey D.; DeNittis, Albert; Werner-Wasik, Maria; El Naqa, Issam

    2016-01-01

    In a secondary analysis of American College of Radiology Imaging Network (ACRIN) 6668/RTOG 0235, high pretreatment metabolic tumor volume (MTV) on 18F-FDG PET was found to be a poor prognostic factor for patients treated with chemoradiotherapy for locally advanced non–small cell lung cancer (NSCLC). Here we utilize the same dataset to explore whether heterogeneity metrics based on PET textural features can provide additional prognostic information. Methods Patients with locally advanced NSCLC underwent 18F-FDG PET prior to treatment. A gradient-based segmentation tool was used to contour each patient’s primary tumor. MTV, maximum SUV, and 43 textural features were extracted for each tumor. To address over-fitting and high collinearity among PET features, the least absolute shrinkage and selection operator (LASSO) method was applied to identify features that were independent predictors of overall survival (OS) after adjusting for MTV. Recursive binary partitioning in a conditional inference framework was utilized to identify optimal thresholds. Kaplan–Meier curves and log-rank testing were used to compare outcomes among patient groups. Results Two hundred one patients met inclusion criteria. The LASSO procedure identified 1 textural feature (SumMean) as an independent predictor of OS. The optimal cutpoint for MTV was 93.3 cm3, and the optimal Sum-Mean cutpoint for tumors above 93.3 cm3 was 0.018. This grouped patients into three categories: low tumor MTV (n = 155; median OS, 22.6 mo), high tumor MTV and high SumMean (n = 23; median OS, 20.0 mo), and high tumor MTV and low SumMean (n = 23; median OS, 6.2 mo; log-rank P textural PET features in the context of established prognostic factors. We have also identified a promising feature that may have prognostic value in locally advanced NSCLC patients with large tumors who are treated with chemoradiotherapy. Validation studies are warranted. PMID:26912429

  11. A multi-stage intelligent approach based on an ensemble of two-way interaction model for forecasting the global horizontal radiation of India

    International Nuclear Information System (INIS)

    Jiang, He; Dong, Yao; Xiao, Ling

    2017-01-01

    Highlights: • Ensemble learning system is proposed to forecast the global solar radiation. • LASSO is utilized as feature selection method for subset model. • GSO is used to select the weight vector aggregating the response of subset model. • A simple and efficient algorithm is designed based on thresholding function. • Theoretical analysis focusing on error rate is provided. - Abstract: Forecasting of effective solar irradiation has developed a huge interest in recent decades, mainly due to its various applications in grid connect photovoltaic installations. This paper develops and investigates an ensemble learning based multistage intelligent approach to forecast 5 days global horizontal radiation at four given locations of India. The two-way interaction model is considered with purpose of detecting the associated correlation between the features. The main structure of the novel method is the ensemble learning, which is based on Divide and Conquer principle, is applied to enhance the forecasting accuracy and model stability. An efficient feature selection method LASSO is performed in the input space with the regularization parameter selected by Cross-Validation. A weight vector which best represents the importance of each individual model in ensemble system is provided by glowworm swarm optimization. The combination of feature selection and parameter selection are helpful in creating the diversity of the ensemble learning. In order to illustrate the validity of the proposed method, the datasets at four different locations of the India are split into training and test datasets. The results of the real data experiments demonstrate the efficiency and efficacy of the proposed method comparing with other competitors.

  12. Internet-based motivation program for women with eating disorders: eating disorder pathology and depressive mood predict dropout.

    Science.gov (United States)

    von Brachel, Ruth; Hötzel, Katrin; Hirschfeld, Gerrit; Rieger, Elizabeth; Schmidt, Ulrike; Kosfelder, Joachim; Hechler, Tanja; Schulte, Dietmar; Vocks, Silja

    2014-03-31

    One of the main problems of Internet-delivered interventions for a range of disorders is the high dropout rate, yet little is known about the factors associated with this. We recently developed and tested a Web-based 6-session program to enhance motivation to change for women with anorexia nervosa, bulimia nervosa, or related subthreshold eating pathology. The aim of the present study was to identify predictors of dropout from this Web program. A total of 179 women took part in the study. We used survival analyses (Cox regression) to investigate the predictive effect of eating disorder pathology (assessed by the Eating Disorders Examination-Questionnaire; EDE-Q), depressive mood (Hopkins Symptom Checklist), motivation to change (University of Rhode Island Change Assessment Scale; URICA), and participants' age at dropout. To identify predictors, we used the least absolute shrinkage and selection operator (LASSO) method. The dropout rate was 50.8% (91/179) and was equally distributed across the 6 treatment sessions. The LASSO analysis revealed that higher scores on the Shape Concerns subscale of the EDE-Q, a higher frequency of binge eating episodes and vomiting, as well as higher depression scores significantly increased the probability of dropout. However, we did not find any effect of the URICA or age on dropout. Women with more severe eating disorder pathology and depressive mood had a higher likelihood of dropping out from a Web-based motivational enhancement program. Interventions such as ours need to address the specific needs of women with more severe eating disorder pathology and depressive mood and offer them additional support to prevent them from prematurely discontinuing treatment.

  13. Internet-Based Motivation Program for Women With Eating Disorders: Eating Disorder Pathology and Depressive Mood Predict Dropout

    Science.gov (United States)

    Hirschfeld, Gerrit; Rieger, Elizabeth; Schmidt, Ulrike; Kosfelder, Joachim; Hechler, Tanja; Schulte, Dietmar; Vocks, Silja

    2014-01-01

    Background One of the main problems of Internet-delivered interventions for a range of disorders is the high dropout rate, yet little is known about the factors associated with this. We recently developed and tested a Web-based 6-session program to enhance motivation to change for women with anorexia nervosa, bulimia nervosa, or related subthreshold eating pathology. Objective The aim of the present study was to identify predictors of dropout from this Web program. Methods A total of 179 women took part in the study. We used survival analyses (Cox regression) to investigate the predictive effect of eating disorder pathology (assessed by the Eating Disorders Examination-Questionnaire; EDE-Q), depressive mood (Hopkins Symptom Checklist), motivation to change (University of Rhode Island Change Assessment Scale; URICA), and participants’ age at dropout. To identify predictors, we used the least absolute shrinkage and selection operator (LASSO) method. Results The dropout rate was 50.8% (91/179) and was equally distributed across the 6 treatment sessions. The LASSO analysis revealed that higher scores on the Shape Concerns subscale of the EDE-Q, a higher frequency of binge eating episodes and vomiting, as well as higher depression scores significantly increased the probability of dropout. However, we did not find any effect of the URICA or age on dropout. Conclusions Women with more severe eating disorder pathology and depressive mood had a higher likelihood of dropping out from a Web-based motivational enhancement program. Interventions such as ours need to address the specific needs of women with more severe eating disorder pathology and depressive mood and offer