Upscaling NZ-DNDC using a regression based meta-model to estimate direct N2O emissions from New Zealand grazed pastures.

PubMed

Giltrap, Donna L; Ausseil, Anne-Gaëlle E

2016-01-01

The availability of detailed input data frequently limits the application of process-based models at large scale. In this study, we produced simplified meta-models of the simulated nitrous oxide (N2O) emission factors (EF) using NZ-DNDC. Monte Carlo simulations were performed and the results investigated using multiple regression analysis to produce simplified meta-models of EF. These meta-models were then used to estimate direct N2O emissions from grazed pastures in New Zealand. New Zealand EF maps were generated using the meta-models with data from national scale soil maps. Direct emissions of N2O from grazed pasture were calculated by multiplying the EF map with a nitrogen (N) input map. Three meta-models were considered. Model 1 included only the soil organic carbon in the top 30cm (SOC30), Model 2 also included a clay content factor, and Model 3 added the interaction between SOC30 and clay. The median annual national direct N2O emissions from grazed pastures estimated using each model (assuming model errors were purely random) were: 9.6GgN (Model 1), 13.6GgN (Model 2), and 11.9GgN (Model 3). These values corresponded to an average EF of 0.53%, 0.75% and 0.63% respectively, while the corresponding average EF using New Zealand national inventory values was 0.67%. If the model error can be assumed to be independent for each pixel then the 95% confidence interval for the N2O emissions was of the order of ±0.4-0.7%, which is much lower than existing methods. However, spatial correlations in the model errors could invalidate this assumption. Under the extreme assumption that the model error for each pixel was identical the 95% confidence interval was approximately ±100-200%. Therefore further work is needed to assess the degree of spatial correlation in the model errors. Copyright © 2015 Elsevier B.V. All rights reserved.

Multilayer Perceptron for Robust Nonlinear Interval Regression Analysis Using Genetic Algorithms

PubMed Central

2014-01-01

On the basis of fuzzy regression, computational models in intelligence such as neural networks have the capability to be applied to nonlinear interval regression analysis for dealing with uncertain and imprecise data. When training data are not contaminated by outliers, computational models perform well by including almost all given training data in the data interval. Nevertheless, since training data are often corrupted by outliers, robust learning algorithms employed to resist outliers for interval regression analysis have been an interesting area of research. Several approaches involving computational intelligence are effective for resisting outliers, but the required parameters for these approaches are related to whether the collected data contain outliers or not. Since it seems difficult to prespecify the degree of contamination beforehand, this paper uses multilayer perceptron to construct the robust nonlinear interval regression model using the genetic algorithm. Outliers beyond or beneath the data interval will impose slight effect on the determination of data interval. Simulation results demonstrate that the proposed method performs well for contaminated datasets. PMID:25110755

Multilayer perceptron for robust nonlinear interval regression analysis using genetic algorithms.

PubMed

Hu, Yi-Chung

2014-01-01

On the basis of fuzzy regression, computational models in intelligence such as neural networks have the capability to be applied to nonlinear interval regression analysis for dealing with uncertain and imprecise data. When training data are not contaminated by outliers, computational models perform well by including almost all given training data in the data interval. Nevertheless, since training data are often corrupted by outliers, robust learning algorithms employed to resist outliers for interval regression analysis have been an interesting area of research. Several approaches involving computational intelligence are effective for resisting outliers, but the required parameters for these approaches are related to whether the collected data contain outliers or not. Since it seems difficult to prespecify the degree of contamination beforehand, this paper uses multilayer perceptron to construct the robust nonlinear interval regression model using the genetic algorithm. Outliers beyond or beneath the data interval will impose slight effect on the determination of data interval. Simulation results demonstrate that the proposed method performs well for contaminated datasets.

Combination of Eight Alleles at Four Quantitative Trait Loci Determines Grain Length in Rice

PubMed Central

Zeng, Yuxiang; Ji, Zhijuan; Wen, Zhihua; Liang, Yan; Yang, Changdeng

2016-01-01

Grain length is an important quantitative trait in rice (Oryza sativa L.) that influences both grain yield and exterior quality. Although many quantitative trait loci (QTLs) for grain length have been identified, it is still unclear how different alleles from different QTLs regulate grain length coordinately. To explore the mechanisms of QTL combination in the determination of grain length, five mapping populations, including two F2 populations, an F3 population, an F7 recombinant inbred line (RIL) population, and an F8 RIL population, were developed from the cross between the U.S. tropical japonica variety ‘Lemont’ and the Chinese indica variety ‘Yangdao 4’ and grown under different environmental conditions. Four QTLs (qGL-3-1, qGL-3-2, qGL-4, and qGL-7) for grain length were detected using both composite interval mapping and multiple interval mapping methods in the mapping populations. In each locus, there was an allele from one parent that increased grain length and another allele from another parent that decreased it. The eight alleles in the four QTLs were analyzed to determine whether these alleles act additively across loci, and lead to a linear relationship between the predicted breeding value of QTLs and phenotype. Linear regression analysis suggested that the combination of eight alleles determined grain length. Plants carrying more grain length-increasing alleles had longer grain length than those carrying more grain length-decreasing alleles. This trend was consistent in all five mapping populations and demonstrated the regulation of grain length by the four QTLs. Thus, these QTLs are ideal resources for modifying grain length in rice. PMID:26942914

Association Between Serum 25-Hydroxy Vitamin D Levels and Blood Pressure Among Adolescents in Two Resource-Limited Settings in Peru

PubMed Central

Tomaino, Katherine; Romero, Karina M.; Robinson, Colin L.; Baumann, Lauren M.; Hansel, Nadia N.; Pollard, Suzanne L.; Gilman, Robert H.; Mougey, Edward; Lima, John J.

2015-01-01

INTRODUCTION Serum 25-hydroxyvitamin D (25OHD) deficiency (<50 nmol/l or 20ng/ml) has been associated with increased blood pressure (BP) in observational studies. A paucity of data on this relationship is available in Latin American or child populations. This study investigates the association between 25OHD levels and BP in adolescents at risk for vitamin D deficiency in 2 Peruvian settings. METHODS In a population-based study of 1,441 Peruvian adolescents aged 13–15 years, 1,074 (75%) provided a serum blood sample for 25OHD analysis and BP measurements. Relationships between 25OHD and BP metrics were assessed using multiple linear regressions, adjusted for anthropometrics and sociodemographic factors. RESULTS 25OHD deficiency was associated with an elevated diastolic BP (DBP) (1.09mm Hg increase, 95% confidence interval: 0.04 to 2.14; P = 0.04) compared to nondeficient adolescents. Systolic BP (SBP) trended to increase with vitamin D deficiency (1.30mm Hg increase, 95% confidence interval: −0.13 to 2.72; P = 0.08). Mean arterial pressure (MAP) was also greater in adolescents with 25OHD (1.16mm Hg increase, 95% confidence interval: 0.10 to 2.22; P = 0.03). SBP was found to demonstrate a U-shaped relationship with 25OHD, while DBP and MAP demonstrated inverse J-shaped relationships with serum 25OHD status. The association between 25OHD deficiency and BP was not different across study sites (all P ≥ 0.19). DISCUSSION Adolescents deficient in 25OHD demonstrated increased DBP and MAP and a trend toward increased SBP, when compared to nondeficient subjects. 25OHD deficiency early in life was associated with elevated BP metrics, which may predispose risk of hypertension later in adulthood. PMID:25600222

Algorithms and Complexity Results for Genome Mapping Problems.

PubMed

Rajaraman, Ashok; Zanetti, Joao Paulo Pereira; Manuch, Jan; Chauve, Cedric

2017-01-01

Genome mapping algorithms aim at computing an ordering of a set of genomic markers based on local ordering information such as adjacencies and intervals of markers. In most genome mapping models, markers are assumed to occur uniquely in the resulting map. We introduce algorithmic questions that consider repeats, i.e., markers that can have several occurrences in the resulting map. We show that, provided with an upper bound on the copy number of repeated markers and with intervals that span full repeat copies, called repeat spanning intervals, the problem of deciding if a set of adjacencies and repeat spanning intervals admits a genome representation is tractable if the target genome can contain linear and/or circular chromosomal fragments. We also show that extracting a maximum cardinality or weight subset of repeat spanning intervals given a set of adjacencies that admits a genome realization is NP-hard but fixed-parameter tractable in the maximum copy number and the number of adjacent repeats, and tractable if intervals contain a single repeated marker.

Analysis of the Magnitude and Frequency of Peak Discharge and Maximum Observed Peak Discharge in New Mexico and Surrounding Areas

USGS Publications Warehouse

Waltemeyer, Scott D.

2008-01-01

Estimates of the magnitude and frequency of peak discharges are necessary for the reliable design of bridges, culverts, and open-channel hydraulic analysis, and for flood-hazard mapping in New Mexico and surrounding areas. The U.S. Geological Survey, in cooperation with the New Mexico Department of Transportation, updated estimates of peak-discharge magnitude for gaging stations in the region and updated regional equations for estimation of peak discharge and frequency at ungaged sites. Equations were developed for estimating the magnitude of peak discharges for recurrence intervals of 2, 5, 10, 25, 50, 100, and 500 years at ungaged sites by use of data collected through 2004 for 293 gaging stations on unregulated streams that have 10 or more years of record. Peak discharges for selected recurrence intervals were determined at gaging stations by fitting observed data to a log-Pearson Type III distribution with adjustments for a low-discharge threshold and a zero skew coefficient. A low-discharge threshold was applied to frequency analysis of 140 of the 293 gaging stations. This application provides an improved fit of the log-Pearson Type III frequency distribution. Use of the low-discharge threshold generally eliminated the peak discharge by having a recurrence interval of less than 1.4 years in the probability-density function. Within each of the nine regions, logarithms of the maximum peak discharges for selected recurrence intervals were related to logarithms of basin and climatic characteristics by using stepwise ordinary least-squares regression techniques for exploratory data analysis. Generalized least-squares regression techniques, an improved regression procedure that accounts for time and spatial sampling errors, then were applied to the same data used in the ordinary least-squares regression analyses. The average standard error of prediction, which includes average sampling error and average standard error of regression, ranged from 38 to 93 percent (mean value is 62, and median value is 59) for the 100-year flood. The 1996 investigation standard error of prediction for the flood regions ranged from 41 to 96 percent (mean value is 67, and median value is 68) for the 100-year flood that was analyzed by using generalized least-squares regression analysis. Overall, the equations based on generalized least-squares regression techniques are more reliable than those in the 1996 report because of the increased length of record and improved geographic information system (GIS) method to determine basin and climatic characteristics. Flood-frequency estimates can be made for ungaged sites upstream or downstream from gaging stations by using a method that transfers flood-frequency data at the gaging station to the ungaged site by using a drainage-area ratio adjustment equation. The peak discharge for a given recurrence interval at the gaging station, drainage-area ratio, and the drainage-area exponent from the regional regression equation of the respective region is used to transfer the peak discharge for the recurrence interval to the ungaged site. Maximum observed peak discharge as related to drainage area was determined for New Mexico. Extreme events are commonly used in the design and appraisal of bridge crossings and other structures. Bridge-scour evaluations are commonly made by using the 500-year peak discharge for these appraisals. Peak-discharge data collected at 293 gaging stations and 367 miscellaneous sites were used to develop a maximum peak-discharge relation as an alternative method of estimating peak discharge of an extreme event such as a maximum probable flood.

The microcomputer scientific software series 2: general linear model--regression.

Treesearch

Harold M. Rauscher

1983-01-01

The general linear model regression (GLMR) program provides the microcomputer user with a sophisticated regression analysis capability. The output provides a regression ANOVA table, estimators of the regression model coefficients, their confidence intervals, confidence intervals around the predicted Y-values, residuals for plotting, a check for multicollinearity, a...

Zero entropy continuous interval maps and MMLS-MMA property

NASA Astrophysics Data System (ADS)

Jiang, Yunping

2018-06-01

We prove that the flow generated by any continuous interval map with zero topological entropy is minimally mean-attractable and minimally mean-L-stable. One of the consequences is that any oscillating sequence is linearly disjoint from all flows generated by all continuous interval maps with zero topological entropy. In particular, the Möbius function is linearly disjoint from all flows generated by all continuous interval maps with zero topological entropy (Sarnak’s conjecture for continuous interval maps). Another consequence is a non-trivial example of a flow having discrete spectrum. We also define a log-uniform oscillating sequence and show a result in ergodic theory for comparison. This material is based upon work supported by the National Science Foundation. It is also partially supported by a collaboration grant from the Simons Foundation (grant number 523341) and PSC-CUNY awards and a grant from NSFC (grant number 11571122).

Methods for calculating confidence and credible intervals for the residual between-study variance in random effects meta-regression models

PubMed Central

2014-01-01

Background Meta-regression is becoming increasingly used to model study level covariate effects. However this type of statistical analysis presents many difficulties and challenges. Here two methods for calculating confidence intervals for the magnitude of the residual between-study variance in random effects meta-regression models are developed. A further suggestion for calculating credible intervals using informative prior distributions for the residual between-study variance is presented. Methods Two recently proposed and, under the assumptions of the random effects model, exact methods for constructing confidence intervals for the between-study variance in random effects meta-analyses are extended to the meta-regression setting. The use of Generalised Cochran heterogeneity statistics is extended to the meta-regression setting and a Newton-Raphson procedure is developed to implement the Q profile method for meta-analysis and meta-regression. WinBUGS is used to implement informative priors for the residual between-study variance in the context of Bayesian meta-regressions. Results Results are obtained for two contrasting examples, where the first example involves a binary covariate and the second involves a continuous covariate. Intervals for the residual between-study variance are wide for both examples. Conclusions Statistical methods, and R computer software, are available to compute exact confidence intervals for the residual between-study variance under the random effects model for meta-regression. These frequentist methods are almost as easily implemented as their established counterparts for meta-analysis. Bayesian meta-regressions are also easily performed by analysts who are comfortable using WinBUGS. Estimates of the residual between-study variance in random effects meta-regressions should be routinely reported and accompanied by some measure of their uncertainty. Confidence and/or credible intervals are well-suited to this purpose. PMID:25196829

Bootstrap Prediction Intervals in Non-Parametric Regression with Applications to Anomaly Detection

NASA Technical Reports Server (NTRS)

Kumar, Sricharan; Srivistava, Ashok N.

2012-01-01

Prediction intervals provide a measure of the probable interval in which the outputs of a regression model can be expected to occur. Subsequently, these prediction intervals can be used to determine if the observed output is anomalous or not, conditioned on the input. In this paper, a procedure for determining prediction intervals for outputs of nonparametric regression models using bootstrap methods is proposed. Bootstrap methods allow for a non-parametric approach to computing prediction intervals with no specific assumptions about the sampling distribution of the noise or the data. The asymptotic fidelity of the proposed prediction intervals is theoretically proved. Subsequently, the validity of the bootstrap based prediction intervals is illustrated via simulations. Finally, the bootstrap prediction intervals are applied to the problem of anomaly detection on aviation data.

Water resources of the Cook Inlet Basin, Alaska

USGS Publications Warehouse

Freethey, Geoffrey W.; Scully, David R.

1980-01-01

Ground-water and surface-water systems of Cook Inlet basin, Alaska, are analyzed. Geologic and topographic features that control the movement and regional availability of ground water are explained and illustrated. Five aquifer systems beneath the most populous areas are described. Estimates of ground-water yield were determined for the region by using ground-water data for the populated areas and by extrapolating known subsurface conditions and interpreting subsurface conditions from surficial features in the other areas. Area maps of generalized geology, Quaternary sediment thickness, and general availability of ground water are shown. Surface-water resources are summarized by describing how basin characteristics affect the discharge in streams. Seasonal trend of streamflow for three types of streams is described. Regression equations for 4 streamflow characteristics (annual, monthly minimum, and maximum discharge) were obtained by using gaging station streamflow characteristics and 10 basin characteristics. In the 24 regression equations presented, drainage area is the most significant basin characteristic, but 5 others are used. Maps of mean annual unit runoff and minimum unit yield for 7 consecutive days with a recurrence interval of 10 years are shown. Historic discharge data at gaging stations is tabulated and representative low-flow and flood-flow frequency curves are shown. (USGS)

Analysis of the Magnitude and Frequency of Peak Discharges for the Navajo Nation in Arizona, Utah, Colorado, and New Mexico

USGS Publications Warehouse

Waltemeyer, Scott D.

2006-01-01

Estimates of the magnitude and frequency of peak discharges are necessary for the reliable flood-hazard mapping in the Navajo Nation in Arizona, Utah, Colorado, and New Mexico. The Bureau of Indian Affairs, U.S. Army Corps of Engineers, and Navajo Nation requested that the U.S. Geological Survey update estimates of peak discharge magnitude for gaging stations in the region and update regional equations for estimation of peak discharge and frequency at ungaged sites. Equations were developed for estimating the magnitude of peak discharges for recurrence intervals of 2, 5, 10, 25, 50, 100, and 500 years at ungaged sites using data collected through 1999 at 146 gaging stations, an additional 13 years of peak-discharge data since a 1997 investigation, which used gaging-station data through 1986. The equations for estimation of peak discharges at ungaged sites were developed for flood regions 8, 11, high elevation, and 6 and are delineated on the basis of the hydrologic codes from the 1997 investigation. Peak discharges for selected recurrence intervals were determined at gaging stations by fitting observed data to a log-Pearson Type III distribution with adjustments for a low-discharge threshold and a zero skew coefficient. A low-discharge threshold was applied to frequency analysis of 82 of the 146 gaging stations. This application provides an improved fit of the log-Pearson Type III frequency distribution. Use of the low-discharge threshold generally eliminated the peak discharge having a recurrence interval of less than 1.4 years in the probability-density function. Within each region, logarithms of the peak discharges for selected recurrence intervals were related to logarithms of basin and climatic characteristics using stepwise ordinary least-squares regression techniques for exploratory data analysis. Generalized least-squares regression techniques, an improved regression procedure that accounts for time and spatial sampling errors, then was applied to the same data used in the ordinary least-squares regression analyses. The average standard error of prediction for a peak discharge have a recurrence interval of 100-years for region 8 was 53 percent (average) for the 100-year flood. The average standard of prediction, which includes average sampling error and average standard error of regression, ranged from 45 to 83 percent for the 100-year flood. Estimated standard error of prediction for a hybrid method for region 11 was large in the 1997 investigation. No distinction of floods produced from a high-elevation region was presented in the 1997 investigation. Overall, the equations based on generalized least-squares regression techniques are considered to be more reliable than those in the 1997 report because of the increased length of record and improved GIS method. Techniques for transferring flood-frequency relations to ungaged sites on the same stream can be estimated at an ungaged site by a direct application of the regional regression equation or at an ungaged site on a stream that has a gaging station upstream or downstream by using the drainage-area ratio and the drainage-area exponent from the regional regression equation of the respective region.

Weighted regression analysis and interval estimators

Treesearch

Donald W. Seegrist

1974-01-01

A method for deriving the weighted least squares estimators for the parameters of a multiple regression model. Confidence intervals for expected values, and prediction intervals for the means of future samples are given.

Hierarchical tone mapping for high dynamic range image visualization

NASA Astrophysics Data System (ADS)

Qiu, Guoping; Duan, Jiang

2005-07-01

In this paper, we present a computationally efficient, practically easy to use tone mapping techniques for the visualization of high dynamic range (HDR) images in low dynamic range (LDR) reproduction devices. The new method, termed hierarchical nonlinear linear (HNL) tone-mapping operator maps the pixels in two hierarchical steps. The first step allocates appropriate numbers of LDR display levels to different HDR intensity intervals according to the pixel densities of the intervals. The second step linearly maps the HDR intensity intervals to theirs allocated LDR display levels. In the developed HNL scheme, the assignment of LDR display levels to HDR intensity intervals is controlled by a very simple and flexible formula with a single adjustable parameter. We also show that our new operators can be used for the effective enhancement of ordinary images.

Bayesian B-spline mapping for dynamic quantitative traits.

PubMed

Xing, Jun; Li, Jiahan; Yang, Runqing; Zhou, Xiaojing; Xu, Shizhong

2012-04-01

Owing to their ability and flexibility to describe individual gene expression at different time points, random regression (RR) analyses have become a popular procedure for the genetic analysis of dynamic traits whose phenotypes are collected over time. Specifically, when modelling the dynamic patterns of gene expressions in the RR framework, B-splines have been proved successful as an alternative to orthogonal polynomials. In the so-called Bayesian B-spline quantitative trait locus (QTL) mapping, B-splines are used to characterize the patterns of QTL effects and individual-specific time-dependent environmental errors over time, and the Bayesian shrinkage estimation method is employed to estimate model parameters. Extensive simulations demonstrate that (1) in terms of statistical power, Bayesian B-spline mapping outperforms the interval mapping based on the maximum likelihood; (2) for the simulated dataset with complicated growth curve simulated by B-splines, Legendre polynomial-based Bayesian mapping is not capable of identifying the designed QTLs accurately, even when higher-order Legendre polynomials are considered and (3) for the simulated dataset using Legendre polynomials, the Bayesian B-spline mapping can find the same QTLs as those identified by Legendre polynomial analysis. All simulation results support the necessity and flexibility of B-spline in Bayesian mapping of dynamic traits. The proposed method is also applied to a real dataset, where QTLs controlling the growth trajectory of stem diameters in Populus are located.

Spatio-temporal water quality mapping from satellite images using geographically and temporally weighted regression

NASA Astrophysics Data System (ADS)

Chu, Hone-Jay; Kong, Shish-Jeng; Chang, Chih-Hua

2018-03-01

The turbidity (TB) of a water body varies with time and space. Water quality is traditionally estimated via linear regression based on satellite images. However, estimating and mapping water quality require a spatio-temporal nonstationary model, while TB mapping necessitates the use of geographically and temporally weighted regression (GTWR) and geographically weighted regression (GWR) models, both of which are more precise than linear regression. Given the temporal nonstationary models for mapping water quality, GTWR offers the best option for estimating regional water quality. Compared with GWR, GTWR provides highly reliable information for water quality mapping, boasts a relatively high goodness of fit, improves the explanation of variance from 44% to 87%, and shows a sufficient space-time explanatory power. The seasonal patterns of TB and the main spatial patterns of TB variability can be identified using the estimated TB maps from GTWR and by conducting an empirical orthogonal function (EOF) analysis.

Interval data clustering using self-organizing maps based on adaptive Mahalanobis distances.

PubMed

Hajjar, Chantal; Hamdan, Hani

2013-10-01

The self-organizing map is a kind of artificial neural network used to map high dimensional data into a low dimensional space. This paper presents a self-organizing map for interval-valued data based on adaptive Mahalanobis distances in order to do clustering of interval data with topology preservation. Two methods based on the batch training algorithm for the self-organizing maps are proposed. The first method uses a common Mahalanobis distance for all clusters. In the second method, the algorithm starts with a common Mahalanobis distance per cluster and then switches to use a different distance per cluster. This process allows a more adapted clustering for the given data set. The performances of the proposed methods are compared and discussed using artificial and real interval data sets. Copyright © 2013 Elsevier Ltd. All rights reserved.

Methods for estimating selected low-flow frequency statistics for unregulated streams in Kentucky

USGS Publications Warehouse

Martin, Gary R.; Arihood, Leslie D.

2010-01-01

This report provides estimates of, and presents methods for estimating, selected low-flow frequency statistics for unregulated streams in Kentucky including the 30-day mean low flows for recurrence intervals of 2 and 5 years (30Q2 and 30Q5) and the 7-day mean low flows for recurrence intervals of 5, 10, and 20 years (7Q2, 7Q10, and 7Q20). Estimates of these statistics are provided for 121 U.S. Geological Survey streamflow-gaging stations with data through the 2006 climate year, which is the 12-month period ending March 31 of each year. Data were screened to identify the periods of homogeneous, unregulated flows for use in the analyses. Logistic-regression equations are presented for estimating the annual probability of the selected low-flow frequency statistics being equal to zero. Weighted-least-squares regression equations were developed for estimating the magnitude of the nonzero 30Q2, 30Q5, 7Q2, 7Q10, and 7Q20 low flows. Three low-flow regions were defined for estimating the 7-day low-flow frequency statistics. The explicit explanatory variables in the regression equations include total drainage area and the mapped streamflow-variability index measured from a revised statewide coverage of this characteristic. The percentage of the station low-flow statistics correctly classified as zero or nonzero by use of the logistic-regression equations ranged from 87.5 to 93.8 percent. The average standard errors of prediction of the weighted-least-squares regression equations ranged from 108 to 226 percent. The 30Q2 regression equations have the smallest standard errors of prediction, and the 7Q20 regression equations have the largest standard errors of prediction. The regression equations are applicable only to stream sites with low flows unaffected by regulation from reservoirs and local diversions of flow and to drainage basins in specified ranges of basin characteristics. Caution is advised when applying the equations for basins with characteristics near the applicable limits and for basins with karst drainage features.

Interval mapping of high growth (hg), a major locus that increases weight gain in mice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Horvat, S.; Medrano, J.F.

1995-04-01

The high growth locus (hg) causes a major increase in weight gain and body size in mice. As a first step to map-based cloning of hg, we developed a genetic map of the hg-containing region using interval mapping of 403 F{sub 2} from a C57BL/6J-hghg x CAST/EiJ cross. The maximum likelihood position of hg was at the chromosome 10 marker D10Mit41 (LOD = 24.8) in the F{sub 2} females and 1.5 cM distal to D10Mit41 (LOD = 9.56) in the F{sub 2} males with corresponding LOD 2 support intervals of 3.7 and 5.4 cM, respectively. The peak LOD scores weremore » significantly higher than the estimated empirical threshold LOD values. The localization of hg by interval mapping was supported by a test cross of F{sub 2} mice recombinant between the LOD 2 support interval and the flanking marker. The interval mapping and test-cross indicate that hg is not allelic with candidate genes Igf1 or decorin (Dcn), a gene that was mapped close to hg in this study. The hg inheritance was recessive in females, although we could not reject recessive or additive inheritance in males. Possible causes for sex differences in peak LOD scores and for the distortion of transmission ratios observed in F{sub 2} males are discussed. The genetic map of the hg region will facilitate further fine mapping and cloning of hg, and allow searches for a homologous quantitative trait locus affecting growth in humans and domestic animals. 48 refs., 3 figs., 3 tabs.« less

Determination of the 100-year flood plain on Upper Three Runs and selected tributaries, and the Savannah River at the Savannah River site, South Carolina, 1995

USGS Publications Warehouse

Lanier, T.H.

1996-01-01

The 100-year flood plain was determined for Upper Three Runs, its tributaries, and the part of the Savannah River that borders the Savannah River Site. The results are provided in tabular and graphical formats. The 100-year flood-plain maps and flood profiles provide water-resource managers of the Savannah River Site with a technical basis for making flood-plain management decisions that could minimize future flood problems and provide a basis for designing and constructing drainage structures along roadways. A hydrologic analysis was made to estimate the 100-year recurrence- interval flow for Upper Three Runs and its tributaries. The analysis showed that the well-drained, sandy soils in the head waters of Upper Three Runs reduce the high flows in the stream; therefore, the South Carolina upper Coastal Plain regional-rural-regression equation does not apply for Upper Three Runs. Conse- quently, a relation was established for 100-year recurrence-interval flow and drainage area using streamflow data from U.S. Geological Survey gaging stations on Upper Three Runs. This relation was used to compute 100-year recurrence-interval flows at selected points along the stream. The regional regression equations were applicable for the tributaries to Upper Three Runs, because the soil types in the drainage basins of the tributaries resemble those normally occurring in upper Coastal Plain basins. This was verified by analysis of the flood-frequency data collected from U.S. Geological Survey gaging station 02197342 on Fourmile Branch. Cross sections were surveyed throughout each reach, and other pertinent data such as flow resistance and land-use were col- lected. The surveyed cross sections and computed 100-year recurrence-interval flows were used in a step-backwater model to compute the 100-year flood profile for Upper Three Runs and its tributaries. The profiles were used to delineate the 100-year flood plain on topographic maps. The Savannah River forms the southwestern border of the Savannah River Site. Data from previously published reports were used to delineate the 100-year flood plain for the Savannah River from the downstream site boundary at the mouth of Lower Three Runs at river mile 125 to the upstream site boundary at river mile 163.

Mapping soil textural fractions across a large watershed in north-east Florida.

PubMed

Lamsal, S; Mishra, U

2010-08-01

Assessment of regional scale soil spatial variation and mapping their distribution is constrained by sparse data which are collected using field surveys that are labor intensive and cost prohibitive. We explored geostatistical (ordinary kriging-OK), regression (Regression Tree-RT), and hybrid methods (RT plus residual Sequential Gaussian Simulation-SGS) to map soil textural fractions across the Santa Fe River Watershed (3585 km(2)) in north-east Florida. Soil samples collected from four depths (L1: 0-30 cm, L2: 30-60 cm, L3: 60-120 cm, and L4: 120-180 cm) at 141 locations were analyzed for soil textural fractions (sand, silt and clay contents), and combined with textural data (15 profiles) assembled under the Florida Soil Characterization program. Textural fractions in L1 and L2 were autocorrelated, and spatially mapped across the watershed. OK performance was poor, which may be attributed to the sparse sampling. RT model structure varied among textural fractions, and the model explained variations ranged from 25% for L1 silt to 61% for L2 clay content. Regression residuals were simulated using SGS, and the average of simulated residuals were used to approximate regression residual distribution map, which were added to regression trend maps. Independent validation of the prediction maps showed that regression models performed slightly better than OK, and regression combined with average of simulated regression residuals improved predictions beyond the regression model. Sand content >90% in both 0-30 and 30-60 cm covered 80.6% of the watershed area. Copyright 2010 Elsevier Ltd. All rights reserved.

Vegetation Monitoring with Gaussian Processes and Latent Force Models

NASA Astrophysics Data System (ADS)

Camps-Valls, Gustau; Svendsen, Daniel; Martino, Luca; Campos, Manuel; Luengo, David

2017-04-01

Monitoring vegetation by biophysical parameter retrieval from Earth observation data is a challenging problem, where machine learning is currently a key player. Neural networks, kernel methods, and Gaussian Process (GP) regression have excelled in parameter retrieval tasks at both local and global scales. GP regression is based on solid Bayesian statistics, yield efficient and accurate parameter estimates, and provides interesting advantages over competing machine learning approaches such as confidence intervals. However, GP models are hampered by lack of interpretability, that prevented the widespread adoption by a larger community. In this presentation we will summarize some of our latest developments to address this issue. We will review the main characteristics of GPs and their advantages in vegetation monitoring standard applications. Then, three advanced GP models will be introduced. First, we will derive sensitivity maps for the GP predictive function that allows us to obtain feature ranking from the model and to assess the influence of examples in the solution. Second, we will introduce a Joint GP (JGP) model that combines in situ measurements and simulated radiative transfer data in a single GP model. The JGP regression provides more sensible confidence intervals for the predictions, respects the physics of the underlying processes, and allows for transferability across time and space. Finally, a latent force model (LFM) for GP modeling that encodes ordinary differential equations to blend data-driven modeling and physical models of the system is presented. The LFM performs multi-output regression, adapts to the signal characteristics, is able to cope with missing data in the time series, and provides explicit latent functions that allow system analysis and evaluation. Empirical evidence of the performance of these models will be presented through illustrative examples.

Laharz_py: GIS tools for automated mapping of lahar inundation hazard zones

USGS Publications Warehouse

Schilling, Steve P.

2014-01-01

Laharz_py is written in the Python programming language as a suite of tools for use in ArcMap Geographic Information System (GIS). Primarily, Laharz_py is a computational model that uses statistical descriptions of areas inundated by past mass-flow events to forecast areas likely to be inundated by hypothetical future events. The forecasts use physically motivated and statistically calibrated power-law equations that each has a form A = cV2/3, relating mass-flow volume (V) to planimetric or cross-sectional areas (A) inundated by an average flow as it descends a given drainage. Calibration of the equations utilizes logarithmic transformation and linear regression to determine the best-fit values of c. The software uses values of V, an algorithm for idenitifying mass-flow source locations, and digital elevation models of topography to portray forecast hazard zones for lahars, debris flows, or rock avalanches on maps. Laharz_py offers two methods to construct areas of potential inundation for lahars: (1) Selection of a range of plausible V values results in a set of nested hazard zones showing areas likely to be inundated by a range of hypothetical flows; and (2) The user selects a single volume and a confidence interval for the prediction. In either case, Laharz_py calculates the mean expected A and B value from each user-selected value of V. However, for the second case, a single value of V yields two additional results representing the upper and lower values of the confidence interval of prediction. Calculation of these two bounding predictions require the statistically calibrated prediction equations, a user-specified level of confidence, and t-distribution statistics to calculate the standard error of regression, standard error of the mean, and standard error of prediction. The portrayal of results from these two methods on maps compares the range of inundation areas due to prediction uncertainties with uncertainties in selection of V values. The Open-File Report document contains an explanation of how to install and use the software. The Laharz_py software includes an example data set for Mount Rainier, Washington. The second part of the documentation describes how to use all of the Laharz_py tools in an example dataset at Mount Rainier, Washington.

HAPRAP: a haplotype-based iterative method for statistical fine mapping using GWAS summary statistics.

PubMed

Zheng, Jie; Rodriguez, Santiago; Laurin, Charles; Baird, Denis; Trela-Larsen, Lea; Erzurumluoglu, Mesut A; Zheng, Yi; White, Jon; Giambartolomei, Claudia; Zabaneh, Delilah; Morris, Richard; Kumari, Meena; Casas, Juan P; Hingorani, Aroon D; Evans, David M; Gaunt, Tom R; Day, Ian N M

2017-01-01

Fine mapping is a widely used approach for identifying the causal variant(s) at disease-associated loci. Standard methods (e.g. multiple regression) require individual level genotypes. Recent fine mapping methods using summary-level data require the pairwise correlation coefficients ([Formula: see text]) of the variants. However, haplotypes rather than pairwise [Formula: see text], are the true biological representation of linkage disequilibrium (LD) among multiple loci. In this article, we present an empirical iterative method, HAPlotype Regional Association analysis Program (HAPRAP), that enables fine mapping using summary statistics and haplotype information from an individual-level reference panel. Simulations with individual-level genotypes show that the results of HAPRAP and multiple regression are highly consistent. In simulation with summary-level data, we demonstrate that HAPRAP is less sensitive to poor LD estimates. In a parametric simulation using Genetic Investigation of ANthropometric Traits height data, HAPRAP performs well with a small training sample size (N < 2000) while other methods become suboptimal. Moreover, HAPRAP's performance is not affected substantially by single nucleotide polymorphisms (SNPs) with low minor allele frequencies. We applied the method to existing quantitative trait and binary outcome meta-analyses (human height, QTc interval and gallbladder disease); all previous reported association signals were replicated and two additional variants were independently associated with human height. Due to the growing availability of summary level data, the value of HAPRAP is likely to increase markedly for future analyses (e.g. functional prediction and identification of instruments for Mendelian randomization). The HAPRAP package and documentation are available at http://apps.biocompute.org.uk/haprap/ CONTACT: : jie.zheng@bristol.ac.uk or tom.gaunt@bristol.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

A self-trained classification technique for producing 30 m percent-water maps from Landsat data

USGS Publications Warehouse

Rover, Jennifer R.; Wylie, Bruce K.; Ji, Lei

2010-01-01

Small bodies of water can be mapped with moderate-resolution satellite data using methods where water is mapped as subpixel fractions using field measurements or high-resolution images as training datasets. A new method, developed from a regression-tree technique, uses a 30 m Landsat image for training the regression tree that, in turn, is applied to the same image to map subpixel water. The self-trained method was evaluated by comparing the percent-water map with three other maps generated from established percent-water mapping methods: (1) a regression-tree model trained with a 5 m SPOT 5 image, (2) a regression-tree model based on endmembers and (3) a linear unmixing classification technique. The results suggest that subpixel water fractions can be accurately estimated when high-resolution satellite data or intensively interpreted training datasets are not available, which increases our ability to map small water bodies or small changes in lake size at a regional scale.

A new approach to correct the QT interval for changes in heart rate using a nonparametric regression model in beagle dogs.

PubMed

Watanabe, Hiroyuki; Miyazaki, Hiroyasu

2006-01-01

Over- and/or under-correction of QT intervals for changes in heart rate may lead to misleading conclusions and/or masking the potential of a drug to prolong the QT interval. This study examines a nonparametric regression model (Loess Smoother) to adjust the QT interval for differences in heart rate, with an improved fitness over a wide range of heart rates. 240 sets of (QT, RR) observations collected from each of 8 conscious and non-treated beagle dogs were used as the materials for investigation. The fitness of the nonparametric regression model to the QT-RR relationship was compared with four models (individual linear regression, common linear regression, and Bazett's and Fridericia's correlation models) with reference to Akaike's Information Criterion (AIC). Residuals were visually assessed. The bias-corrected AIC of the nonparametric regression model was the best of the models examined in this study. Although the parametric models did not fit, the nonparametric regression model improved the fitting at both fast and slow heart rates. The nonparametric regression model is the more flexible method compared with the parametric method. The mathematical fit for linear regression models was unsatisfactory at both fast and slow heart rates, while the nonparametric regression model showed significant improvement at all heart rates in beagle dogs.

Exploring prediction uncertainty of spatial data in geostatistical and machine learning Approaches

NASA Astrophysics Data System (ADS)

Klump, J. F.; Fouedjio, F.

2017-12-01

Geostatistical methods such as kriging with external drift as well as machine learning techniques such as quantile regression forest have been intensively used for modelling spatial data. In addition to providing predictions for target variables, both approaches are able to deliver a quantification of the uncertainty associated with the prediction at a target location. Geostatistical approaches are, by essence, adequate for providing such prediction uncertainties and their behaviour is well understood. However, they often require significant data pre-processing and rely on assumptions that are rarely met in practice. Machine learning algorithms such as random forest regression, on the other hand, require less data pre-processing and are non-parametric. This makes the application of machine learning algorithms to geostatistical problems an attractive proposition. The objective of this study is to compare kriging with external drift and quantile regression forest with respect to their ability to deliver reliable prediction uncertainties of spatial data. In our comparison we use both simulated and real world datasets. Apart from classical performance indicators, comparisons make use of accuracy plots, probability interval width plots, and the visual examinations of the uncertainty maps provided by the two approaches. By comparing random forest regression to kriging we found that both methods produced comparable maps of estimated values for our variables of interest. However, the measure of uncertainty provided by random forest seems to be quite different to the measure of uncertainty provided by kriging. In particular, the lack of spatial context can give misleading results in areas without ground truth data. These preliminary results raise questions about assessing the risks associated with decisions based on the predictions from geostatistical and machine learning algorithms in a spatial context, e.g. mineral exploration.

[New method of mixed gas infrared spectrum analysis based on SVM].

PubMed

Bai, Peng; Xie, Wen-Jun; Liu, Jun-Hua

2007-07-01

A new method of infrared spectrum analysis based on support vector machine (SVM) for mixture gas was proposed. The kernel function in SVM was used to map the seriously overlapping absorption spectrum into high-dimensional space, and after transformation, the high-dimensional data could be processed in the original space, so the regression calibration model was established, then the regression calibration model with was applied to analyze the concentration of component gas. Meanwhile it was proved that the regression calibration model with SVM also could be used for component recognition of mixture gas. The method was applied to the analysis of different data samples. Some factors such as scan interval, range of the wavelength, kernel function and penalty coefficient C that affect the model were discussed. Experimental results show that the component concentration maximal Mean AE is 0.132%, and the component recognition accuracy is higher than 94%. The problems of overlapping absorption spectrum, using the same method for qualitative and quantitative analysis, and limit number of training sample, were solved. The method could be used in other mixture gas infrared spectrum analyses, promising theoretic and application values.

Targeted Recombinant Progeny: a design for ultra-high resolution mapping of Quantitative Trait Loci in crosses between inbred or pure lines.

PubMed

Heifetz, Eliyahu M; Soller, Morris

2015-07-07

High-resolution mapping of the loci (QTN) responsible for genetic variation in quantitative traits is essential for positional cloning of candidate genes, and for effective marker assisted selection. The confidence interval (QTL) flanking the point estimate of QTN-location is proportional to the number of individuals in the mapping population carrying chromosomes recombinant in the given interval. Consequently, many designs for high resolution QTN mapping are based on increasing the proportion of recombinants in the mapping population. The "Targeted Recombinant Progeny" (TRP) design is a new design for high resolution mapping of a target QTN in crosses between pure, or inbred lines. It is a three-generation procedure generating a large number of recombinant individuals within a QTL previously shown to contain a QTN. This is achieved by having individuals that carry chromosomes recombinant across the target QTL interval as parents of a large mapping population; most of whom will therefore carry recombinant chromosomes targeted to the given QTL. The TRP design is particularly useful for high resolution mapping of QTN that differentiate inbred or pure lines, and hence are not amenable to high resolution mapping by genome-wide association tests. In the absence of residual polygenic variation, population sizes required for achieving given mapping resolution by the TRP-F2 design relative to a standard F2 design ranged from 0.289 for a QTN with standardized allele substitution effect = 0.2, mapped to an initial QTL of 0.2 Morgan to 0.041 for equivalent QTN mapped to an initial QTL of 0.02 M. In the presence of residual polygenic variation, the relative effectiveness of the TRP design ranges from 1.068 to 0.151 for the same initial QTL intervals and QTN effect. Thus even in the presence of polygenic variation, the TRP can still provide major savings. Simulation showed that mapping by TRP should be based on 30-50 markers spanning the initial interval; and on at least 50 or more G2 families representing this number of recombination points,. The TRP design can be an effective procedure for achieving high and ultra-high mapping resolution of a target QTN previously mapped to a known confidence interval (QTL).

A Control Algorithm for Chaotic Physical Systems

DTIC Science & Technology

1991-10-01

revision expands the grid to cover the entire area of any attractor that is present. 5 Map Selection The final choices of the state- space mapping process...interval h?; overrange R0 ; control parameter interval AkO and range [kbro, khigh]; iteration depth. "* State- space mapping : 1. Set up grid by expanding

Association Between Serum 25-Hydroxy Vitamin D Levels and Blood Pressure Among Adolescents in Two Resource-Limited Settings in Peru.

PubMed

Tomaino, Katherine; Romero, Karina M; Robinson, Colin L; Baumann, Lauren M; Hansel, Nadia N; Pollard, Suzanne L; Gilman, Robert H; Mougey, Edward; Lima, John J; Checkley, William

2015-08-01

Serum 25-hydroxyvitamin D (25OHD) deficiency (<50 nmol/l or 20 ng/ml) has been associated with increased blood pressure (BP) in observational studies. A paucity of data on this relationship is available in Latin American or child populations. This study investigates the association between 25OHD levels and BP in adolescents at risk for vitamin D deficiency in 2 Peruvian settings. In a population-based study of 1,441 Peruvian adolescents aged 13-15 years, 1,074 (75%) provided a serum blood sample for 25OHD analysis and BP measurements. Relationships between 25OHD and BP metrics were assessed using multiple linear regressions, adjusted for anthropometrics and sociodemographic factors. 25OHD deficiency was associated with an elevated diastolic BP (DBP) (1.09 mm Hg increase, 95% confidence interval: 0.04 to 2.14; P = 0.04) compared to nondeficient adolescents. Systolic BP (SBP) trended to increase with vitamin D deficiency (1.30 mm Hg increase, 95% confidence interval: -0.13 to 2.72; P = 0.08). Mean arterial pressure (MAP) was also greater in adolescents with 25OHD (1.16 mm Hg increase, 95% confidence interval: 0.10 to 2.22; P = 0.03). SBP was found to demonstrate a U-shaped relationship with 25OHD, while DBP and MAP demonstrated inverse J-shaped relationships with serum 25OHD status. The association between 25OHD deficiency and BP was not different across study sites (all P ≥ 0.19). Adolescents deficient in 25OHD demonstrated increased DBP and MAP and a trend toward increased SBP, when compared to nondeficient subjects. 25OHD deficiency early in life was associated with elevated BP metrics, which may predispose risk of hypertension later in adulthood. © American Journal of Hypertension, Ltd 2015. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Foraminiferal biostratigraphy, paleoenvironmental history, and rates of sedimentation within subsurface Miocene of southern Alabama and adjoining state and Federal Waters Areas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, C.C.

1989-03-01

Miocene sedimentary rocks of the study area consist of a predominantly regressive sequence of clay and quartzose sand deposited on a carbonate platform which dips toward the southwest at 50-100 ft/mi. This clastic wedge ranges in thickness from 1000 ft in central Mobile and Baldwin Counties to a maximum of about 5800 ft in the northeastern portion of the Main Pass area. Analysis of planktonic and benthic foraminifera has resulted in a refined biostratigraphic zonation of these rocks, which indicates that basal Miocene transgressive shale assignable to the Amphistegina B interval zone immediately overlies the upper Oligocene regional carbonate platform.more » Thus, both lower and lower middle Miocene sedimentary rocks are absent throughout the area of investigation. Biostratigraphic analysis of the middle and upper Miocene rocks has resulted in a series of cross sections illustrating the dramatic thickening southwestward into the federal offshore continental shelf and showing the relationships of producing intervals in the Cibicides carstensi and Discorbis ''12'' interval zones. Paleoenvironmental interpretations are illustrated on a series of maps constructed for selected regional biostratigraphic zones. These maps have outlined previously unrecognized late middle and early late Miocene deltaic sedimentation in the southeastern Mobile County and Chandeleur-Viosca Knoll (north) areas. Study of sedimentation rates, which range from less than 25 up to 1370 ft/m.y., further aids in understanding the deltaic and coastal shelf sedimentation of the Miocene within Alabama and adjoining state and federal waters areas.« less

Expression of Proteins Involved in Epithelial-Mesenchymal Transition as Predictors of Metastasis and Survival in Breast Cancer Patients

DTIC Science & Technology

2013-11-01

Ptrend 0.78 0.62 0.75 Unconditional logistic regression was used to estimate odds ratios (OR) and 95 % confidence intervals (CI) for risk of node...Ptrend 0.71 0.67 Unconditional logistic regression was used to estimate odds ratios (OR) and 95 % confidence intervals (CI) for risk of high-grade tumors... logistic regression was used to estimate odds ratios (OR) and 95 % confidence intervals (CI) for the associations between each of the seven SNPs and

Reliability of confidence intervals calculated by bootstrap and classical methods using the FIA 1-ha plot design

Treesearch

H. T. Schreuder; M. S. Williams

2000-01-01

In simulation sampling from forest populations using sample sizes of 20, 40, and 60 plots respectively, confidence intervals based on the bootstrap (accelerated, percentile, and t-distribution based) were calculated and compared with those based on the classical t confidence intervals for mapped populations and subdomains within those populations. A 68.1 ha mapped...

Remote-sensing data processing with the multivariate regression analysis method for iron mineral resource potential mapping: a case study in the Sarvian area, central Iran

NASA Astrophysics Data System (ADS)

Mansouri, Edris; Feizi, Faranak; Jafari Rad, Alireza; Arian, Mehran

2018-03-01

This paper uses multivariate regression to create a mathematical model for iron skarn exploration in the Sarvian area, central Iran, using multivariate regression for mineral prospectivity mapping (MPM). The main target of this paper is to apply multivariate regression analysis (as an MPM method) to map iron outcrops in the northeastern part of the study area in order to discover new iron deposits in other parts of the study area. Two types of multivariate regression models using two linear equations were employed to discover new mineral deposits. This method is one of the reliable methods for processing satellite images. ASTER satellite images (14 bands) were used as unique independent variables (UIVs), and iron outcrops were mapped as dependent variables for MPM. According to the results of the probability value (p value), coefficient of determination value (R2) and adjusted determination coefficient (Radj2), the second regression model (which consistent of multiple UIVs) fitted better than other models. The accuracy of the model was confirmed by iron outcrops map and geological observation. Based on field observation, iron mineralization occurs at the contact of limestone and intrusive rocks (skarn type).

Comparing the efficiency of digital and conventional soil mapping to predict soil types in a semi-arid region in Iran

NASA Astrophysics Data System (ADS)

Zeraatpisheh, Mojtaba; Ayoubi, Shamsollah; Jafari, Azam; Finke, Peter

2017-05-01

The efficiency of different digital and conventional soil mapping approaches to produce categorical maps of soil types is determined by cost, sample size, accuracy and the selected taxonomic level. The efficiency of digital and conventional soil mapping approaches was examined in the semi-arid region of Borujen, central Iran. This research aimed to (i) compare two digital soil mapping approaches including Multinomial logistic regression and random forest, with the conventional soil mapping approach at four soil taxonomic levels (order, suborder, great group and subgroup levels), (ii) validate the predicted soil maps by the same validation data set to determine the best method for producing the soil maps, and (iii) select the best soil taxonomic level by different approaches at three sample sizes (100, 80, and 60 point observations), in two scenarios with and without a geomorphology map as a spatial covariate. In most predicted maps, using both digital soil mapping approaches, the best results were obtained using the combination of terrain attributes and the geomorphology map, although differences between the scenarios with and without the geomorphology map were not significant. Employing the geomorphology map increased map purity and the Kappa index, and led to a decrease in the 'noisiness' of soil maps. Multinomial logistic regression had better performance at higher taxonomic levels (order and suborder levels); however, random forest showed better performance at lower taxonomic levels (great group and subgroup levels). Multinomial logistic regression was less sensitive than random forest to a decrease in the number of training observations. The conventional soil mapping method produced a map with larger minimum polygon size because of traditional cartographic criteria used to make the geological map 1:100,000 (on which the conventional soil mapping map was largely based). Likewise, conventional soil mapping map had also a larger average polygon size that resulted in a lower level of detail. Multinomial logistic regression at the order level (map purity of 0.80), random forest at the suborder (map purity of 0.72) and great group level (map purity of 0.60), and conventional soil mapping at the subgroup level (map purity of 0.48) produced the most accurate maps in the study area. The multinomial logistic regression method was identified as the most effective approach based on a combined index of map purity, map information content, and map production cost. The combined index also showed that smaller sample size led to a preference for the order level, while a larger sample size led to a preference for the great group level.

Mapping the Climate of Puerto Rico, Vieques and Culebra.

Treesearch

CHRISTOPHER DALY; E. H. HELMER; MAYA QUINONES

2003-01-01

Spatially explicit climate data contribute to watershed resource management, mapping vegetation type with satellite imagery, mapping present and hypothetical future ecological zones, and predicting species distributions. The regression based Parameter-elevation Regressions on Independent Slopes Model (PRISM) uses spatial data sets, a knowledge base and expert...

Cerebral blood flow velocity declines before arterial pressure in patients with orthostatic vasovagal presyncope

NASA Technical Reports Server (NTRS)

Dan, Dan; Hoag, Jeffrey B.; Ellenbogen, Kenneth A.; Wood, Mark A.; Eckberg, Dwain L.; Gilligan, David M.

2002-01-01

OBJECTIVES: We studied hemodynamic changes leading to orthostatic vasovagal presyncope to determine whether changes of cerebral artery blood flow velocity precede or follow reductions of arterial pressure. BACKGROUND: Some evidence suggests that disordered cerebral autoregulation contributes to the occurrence of orthostatic vasovagal syncope. We studied cerebral hemodynamics with transcranial Doppler recordings, and we closely examined the temporal sequence of changes of cerebral artery blood flow velocity and systemic arterial pressure in 15 patients who did or did not faint during passive 70 degrees head-up tilt. METHODS: We recorded photoplethysmographic arterial pressure, RR intervals (electrocardiogram) and middle cerebral artery blood flow velocities (mean, total, mean/RR interval; Gosling's pulsatility index; and cerebrovascular resistance [mean cerebral velocity/mean arterial pressure, MAP]). RESULTS: Eight men developed presyncope, and six men and one woman did not. Presyncopal patients reported light-headedness, diaphoresis, or a sensation of fatigue 155 s (range: 25 to 414 s) before any cerebral or systemic hemodynamic change. Average cerebral blood flow velocity (CBFV) changes (defined by an iterative linear regression algorithm) began 67 s (range: 9 to 198 s) before reductions of MAP. Cerebral and systemic hemodynamic measurements remained constant in nonsyncopal patients. CONCLUSIONS: Presyncopal symptoms and CBFV changes precede arterial pressure reductions in patients with orthostatic vasovagal syncope. Therefore, changes of cerebrovascular regulation may contribute to the occurrence of vasovagal reactions.

Acoustic-articulatory mapping in vowels by locally weighted regression

PubMed Central

McGowan, Richard S.; Berger, Michael A.

2009-01-01

A method for mapping between simultaneously measured articulatory and acoustic data is proposed. The method uses principal components analysis on the articulatory and acoustic variables, and mapping between the domains by locally weighted linear regression, or loess [Cleveland, W. S. (1979). J. Am. Stat. Assoc. 74, 829–836]. The latter method permits local variation in the slopes of the linear regression, assuming that the function being approximated is smooth. The methodology is applied to vowels of four speakers in the Wisconsin X-ray Microbeam Speech Production Database, with formant analysis. Results are examined in terms of (1) examples of forward (articulation-to-acoustics) mappings and inverse mappings, (2) distributions of local slopes and constants, (3) examples of correlations among slopes and constants, (4) root-mean-square error, and (5) sensitivity of formant frequencies to articulatory change. It is shown that the results are qualitatively correct and that loess performs better than global regression. The forward mappings show different root-mean-square error properties than the inverse mappings indicating that this method is better suited for the forward mappings than the inverse mappings, at least for the data chosen for the current study. Some preliminary results on sensitivity of the first two formant frequencies to the two most important articulatory principal components are presented. PMID:19813812

Historical shoreline mapping (II): Application of the Digital Shoreline Mapping and Analysis Systems (DSMS/DSAS) to shoreline change mapping in Puerto Rico

USGS Publications Warehouse

Thieler, E. Robert; Danforth, William W.

1994-01-01

A new, state-of-the-art method for mapping historical shorelines from maps and aerial photographs, the Digital Shoreline Mapping System (DSMS), has been developed. The DSMS is a freely available, public domain software package that meets the cartographic and photogrammetric requirements of precise coastal mapping, and provides a means to quantify and analyze different sources of error in the mapping process. The DSMS is also capable of resolving imperfections in aerial photography that commonly are assumed to be nonexistent. The DSMS utilizes commonly available computer hardware and software, and permits the entire shoreline mapping process to be executed rapidly by a single person in a small lab. The DSMS generates output shoreline position data that are compatible with a variety of Geographic Information Systems (GIS). A second suite of programs, the Digital Shoreline Analysis System (DSAS) has been developed to calculate shoreline rates-of-change from a series of shoreline data residing in a GIS. Four rate-of-change statistics are calculated simultaneously (end-point rate, average of rates, linear regression and jackknife) at a user-specified interval along the shoreline using a measurement baseline approach. An example of DSMS and DSAS application using historical maps and air photos of Punta Uvero, Puerto Rico provides a basis for assessing the errors associated with the source materials as well as the accuracy of computed shoreline positions and erosion rates. The maps and photos used here represent a common situation in shoreline mapping: marginal-quality source materials. The maps and photos are near the usable upper limit of scale and accuracy, yet the shoreline positions are still accurate ±9.25 m when all sources of error are considered. This level of accuracy yields a resolution of ±0.51 m/yr for shoreline rates-of-change in this example, and is sufficient to identify the short-term trend (36 years) of shoreline change in the study area.

Correlation of physical and genetic maps of human chromosome 16

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sutherland, G.R.

1991-01-01

This project aimed to divide chromosome 16 into approximately 50 intervals of {approximately}2Mb in size by constructing a series of mouse/human somatic cell hybrids each containing a rearranged chromosome 16. Using these hybrids, DNA probes would be regionally mapped by Southern blot or PCR analysis. Preference would be given to mapping probes which demonstrated polymorphisms for which the CEPH panel of families had been typed. This would allow a correlation of the physical and linkage maps of this chromosome. The aims have been substantially achieved. 49 somatic cell hybrids have been constructed which have allowed definition of 46, and potentiallymore » 57, different physical intervals on the chromosome. 164 loci have been fully mapped into these intervals. A correlation of the physical and genetic maps of the chromosome is in an advanced stage of preparation. The somatic cell hybrids constructed have been widely distributed to groups working on chromosome 16 and other genome projects.« less

Correlation of physical and genetic maps of human chromosome 16. Annual progress report, October 1, 1990--July 31, 1991

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sutherland, G.R.

1991-12-31

This project aimed to divide chromosome 16 into approximately 50 intervals of {approximately}2Mb in size by constructing a series of mouse/human somatic cell hybrids each containing a rearranged chromosome 16. Using these hybrids, DNA probes would be regionally mapped by Southern blot or PCR analysis. Preference would be given to mapping probes which demonstrated polymorphisms for which the CEPH panel of families had been typed. This would allow a correlation of the physical and linkage maps of this chromosome. The aims have been substantially achieved. 49 somatic cell hybrids have been constructed which have allowed definition of 46, and potentiallymore » 57, different physical intervals on the chromosome. 164 loci have been fully mapped into these intervals. A correlation of the physical and genetic maps of the chromosome is in an advanced stage of preparation. The somatic cell hybrids constructed have been widely distributed to groups working on chromosome 16 and other genome projects.« less

Photogrammetric portrayal of Mars topography.

USGS Publications Warehouse

Wu, S.S.C.

1979-01-01

Special photogrammetric techniques have been developed to portray Mars topography, using Mariner and Viking imaging and nonimaging topographic information and earth-based radar data. Topography is represented by the compilation of maps at three scales: global, intermediate, and very large scale. The global map is a synthesis of topographic information obtained from Mariner 9 and earth-based radar, compiled at a scale of 1:25,000,000 with a contour interval of 1 km; it gives a broad quantitative view of the planet. At intermediate scales, Viking Orbiter photographs of various resolutions are used to compile detailed contour maps of a broad spectrum of prominent geologic features; a contour interval as small as 20 m has been obtained from very high resolution orbital photography. Imagery from the Viking lander facsimile cameras permits construction of detailed, very large scale (1:10) topographic maps of the terrain surrounding the two landers; these maps have a contour interval of 1 cm. This paper presents several new detailed topographic maps of Mars.-Author

Photogrammetric portrayal of Mars topography

NASA Technical Reports Server (NTRS)

Wu, S. S. C.

1979-01-01

Special photogrammetric techniques have been developed to portray Mars topography, using Mariner and Viking imaging and nonimaging topographic information and earth-based radar data. Topography is represented by the compilation of maps at three scales: global, intermediate, and very large scale. The global map is a synthesis of topographic information obtained from Mariner 9 and earth-based radar, compiled at a scale of 1:25,000,000 with a contour interval of 1 km; it gives a broad quantitative view of the planet. At intermediate scales, Viking Orbiter photographs of various resolutions are used to compile detailed contour maps of a broad spectrum of prominent geologic features; a contour interval as small as 20 m has been obtained from very high resolution orbital photography. Imagery from the Viking lander facsimile cameras permits construction of detailed, very large scale (1:10) topographic maps of the terrain surrounding the two landers; these maps have a contour interval of 1 cm. This paper presents several new detailed topographic maps of Mars.

Precipitation isoscapes for New Zealand: enhanced temporal detail using precipitation-weighted daily climatology.

PubMed

Baisden, W Troy; Keller, Elizabeth D; Van Hale, Robert; Frew, Russell D; Wassenaar, Leonard I

2016-01-01

Predictive understanding of precipitation δ(2)H and δ(18)O in New Zealand faces unique challenges, including high spatial variability in precipitation amounts, alternation between subtropical and sub-Antarctic precipitation sources, and a compressed latitudinal range of 34 to 47 °S. To map the precipitation isotope ratios across New Zealand, three years of integrated monthly precipitation samples were acquired from >50 stations. Conventional mean-annual precipitation δ(2)H and δ(18)O maps were produced by regressions using geographic and annual climate variables. Incomplete data and short-term variation in climate and precipitation sources limited the utility of this approach. We overcome these difficulties by calculating precipitation-weighted monthly climate parameters using national 5-km-gridded daily climate data. This data plus geographic variables were regressed to predict δ(2)H, δ(18)O, and d-excess at all sites. The procedure yields statistically-valid predictions of the isotope composition of precipitation (long-term average root mean square error (RMSE) for δ(18)O = 0.6 ‰; δ(2)H = 5.5 ‰); and monthly RMSE δ(18)O = 1.9 ‰, δ(2)H = 16 ‰. This approach has substantial benefits for studies that require the isotope composition of precipitation during specific time intervals, and may be further improved by comparison to daily and event-based precipitation samples as well as the use of back-trajectory calculations.

Spatial vulnerability assessments by regression kriging

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Takács, Katalin; Szatmári, Gábor

2016-04-01

Two fairly different complex environmental phenomena, causing natural hazard were mapped based on a combined spatial inference approach. The behaviour is related to various environmental factors and the applied approach enables the inclusion of several, spatially exhaustive auxiliary variables that are available for mapping. Inland excess water (IEW) is an interrelated natural and human induced phenomenon causes several problems in the flat-land regions of Hungary, which cover nearly half of the country. The term 'inland excess water' refers to the occurrence of inundations outside the flood levee that originate from sources differing from flood overflow, it is surplus surface water forming due to the lack of runoff, insufficient absorption capability of soil or the upwelling of groundwater. There is a multiplicity of definitions, which indicate the complexity of processes that govern this phenomenon. Most of the definitions have a common part, namely, that inland excess water is temporary water inundation that occurs in flat-lands due to both precipitation and groundwater emerging on the surface as substantial sources. Radon gas is produced in the radioactive decay chain of uranium, which is an element that is naturally present in soils. Radon is transported mainly by diffusion and convection mechanisms through the soil depending mainly on soil physical and meteorological parameters and can enter and accumulate in the buildings. Health risk originating from indoor radon concentration attributed to natural factors is characterized by geogenic radon potential (GRP). In addition to geology and meteorology, physical soil properties play significant role in the determination of GRP. Identification of areas with high risk requires spatial modelling, that is mapping of specific natural hazards. In both cases external environmental factors determine the behaviour of the target process (occurrence/frequncy of IEW and grade of GRP respectively). Spatial auxiliary information representing IEW or GRP forming environmental factors were taken into account to support the spatial inference of the locally experienced IEW frequency and measured GRP values respectively. An efficient spatial prediction methodology was applied to construct reliable maps, namely regression kriging (RK) using spatially exhaustive auxiliary data on soil, geology, topography, land use and climate. RK divides the spatial inference into two parts. Firstly the deterministic component of the target variable is determined by a regression model. The residuals of the multiple linear regression analysis represent the spatially varying but dependent stochastic component, which are interpolated by kriging. The final map is the sum of the two component predictions. Application of RK also provides the possibility of inherent accuracy assessment. The resulting maps are characterized by global and local measures of its accuracy. Additionally the method enables interval estimation for spatial extension of the areas of predefined risk categories. All of these outputs provide useful contribution to spatial planning, action planning and decision making. Acknowledgement: Our work was partly supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Outcrop-scale fracture trace identification using surface roughness derived from a high-density point cloud

NASA Astrophysics Data System (ADS)

Okyay, U.; Glennie, C. L.; Khan, S.

2017-12-01

Owing to the advent of terrestrial laser scanners (TLS), high-density point cloud data has become increasingly available to the geoscience research community. Research groups have started producing their own point clouds for various applications, gradually shifting their emphasis from obtaining the data towards extracting more and meaningful information from the point clouds. Extracting fracture properties from three-dimensional data in a (semi-)automated manner has been an active area of research in geosciences. Several studies have developed various processing algorithms for extracting only planar surfaces. In comparison, (semi-)automated identification of fracture traces at the outcrop scale, which could be used for mapping fracture distribution have not been investigated frequently. Understanding the spatial distribution and configuration of natural fractures is of particular importance, as they directly influence fluid-flow through the host rock. Surface roughness, typically defined as the deviation of a natural surface from a reference datum, has become an important metric in geoscience research, especially with the increasing density and accuracy of point clouds. In the study presented herein, a surface roughness model was employed to identify fracture traces and their distribution on an ophiolite outcrop in Oman. Surface roughness calculations were performed using orthogonal distance regression over various grid intervals. The results demonstrated that surface roughness could identify outcrop-scale fracture traces from which fracture distribution and density maps can be generated. However, considering outcrop conditions and properties and the purpose of the application, the definition of an adequate grid interval for surface roughness model and selection of threshold values for distribution maps are not straightforward and require user intervention and interpretation.

Regression equations for estimation of annual peak-streamflow frequency for undeveloped watersheds in Texas using an L-moment-based, PRESS-minimized, residual-adjusted approach

USGS Publications Warehouse

Asquith, William H.; Roussel, Meghan C.

2009-01-01

Annual peak-streamflow frequency estimates are needed for flood-plain management; for objective assessment of flood risk; for cost-effective design of dams, levees, and other flood-control structures; and for design of roads, bridges, and culverts. Annual peak-streamflow frequency represents the peak streamflow for nine recurrence intervals of 2, 5, 10, 25, 50, 100, 200, 250, and 500 years. Common methods for estimation of peak-streamflow frequency for ungaged or unmonitored watersheds are regression equations for each recurrence interval developed for one or more regions; such regional equations are the subject of this report. The method is based on analysis of annual peak-streamflow data from U.S. Geological Survey streamflow-gaging stations (stations). Beginning in 2007, the U.S. Geological Survey, in cooperation with the Texas Department of Transportation and in partnership with Texas Tech University, began a 3-year investigation concerning the development of regional equations to estimate annual peak-streamflow frequency for undeveloped watersheds in Texas. The investigation focuses primarily on 638 stations with 8 or more years of data from undeveloped watersheds and other criteria. The general approach is explicitly limited to the use of L-moment statistics, which are used in conjunction with a technique of multi-linear regression referred to as PRESS minimization. The approach used to develop the regional equations, which was refined during the investigation, is referred to as the 'L-moment-based, PRESS-minimized, residual-adjusted approach'. For the approach, seven unique distributions are fit to the sample L-moments of the data for each of 638 stations and trimmed means of the seven results of the distributions for each recurrence interval are used to define the station specific, peak-streamflow frequency. As a first iteration of regression, nine weighted-least-squares, PRESS-minimized, multi-linear regression equations are computed using the watershed characteristics of drainage area, dimensionless main-channel slope, and mean annual precipitation. The residuals of the nine equations are spatially mapped, and residuals for the 10-year recurrence interval are selected for generalization to 1-degree latitude and longitude quadrangles. The generalized residual is referred to as the OmegaEM parameter and represents a generalized terrain and climate index that expresses peak-streamflow potential not otherwise represented in the three watershed characteristics. The OmegaEM parameter was assigned to each station, and using OmegaEM, nine additional regression equations are computed. Because of favorable diagnostics, the OmegaEM equations are expected to be generally reliable estimators of peak-streamflow frequency for undeveloped and ungaged stream locations in Texas. The mean residual standard error, adjusted R-squared, and percentage reduction of PRESS by use of OmegaEM are 0.30log10, 0.86, and -21 percent, respectively. Inclusion of the OmegaEM parameter provides a substantial reduction in the PRESS statistic of the regression equations and removes considerable spatial dependency in regression residuals. Although the OmegaEM parameter requires interpretation on the part of analysts and the potential exists that different analysts could estimate different values for a given watershed, the authors suggest that typical uncertainty in the OmegaEM estimate might be about +or-0.1010. Finally, given the two ensembles of equations reported herein and those in previous reports, hydrologic design engineers and other analysts have several different methods, which represent different analytical tracks, to make comparisons of peak-streamflow frequency estimates for ungaged watersheds in the study area.

Mathematical analysis of the normal anatomy of the aging fovea.

PubMed

Nesmith, Brooke; Gupta, Akash; Strange, Taylor; Schaal, Yuval; Schaal, Shlomit

2014-08-28

To mathematically analyze anatomical changes that occur in the normal fovea during aging. A total of 2912 spectral-domain optical coherence tomography (SD-OCT) normal foveal scans were analyzed. Subjects were healthy individuals, aged 13 to 97 years, with visual acuity ≥20/40 and without evidence of foveal pathology. Using automated symbolic regression software Eureqa (version 0.98), foveal thickness maps of 390 eyes were analyzed using several measurements: parafoveal retinal thickness at 50 μm consecutive intervals, parafoveal maximum retinal thickness at two points lateral to central foveal depression, distance between two points of maximum retinal thickness, maximal foveal slope at two intervals lateral to central foveal depression, and central length of foveal depression. A unique mathematical equation representing the mathematical analog of foveal anatomy was derived for every decade, between 10 and 100 years. The mathematical regression function for normal fovea followed first order sine curve of level 10 complexity for the second decade of life. The mathematical regression function became more complex with normal aging, up to level 43 complexity (0.085 fit; P < 0.05). Young foveas had higher symmetry (0.92 ± 0.10) along midline, whereas aged foveas had significantly less symmetry (0.76 ± 0.27, P < 0.01) along midline and steeper maximal slopes (29 ± 32°, P < 0.01). Normal foveal anatomical configuration changes with age. Normal aged foveas are less symmetric along midline with steeper slopes. Differentiating between normal aging and pathologic changes using SD-OCT scans may allow early diagnosis, follow-up, and better management of the aging population. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

A multifractal analysis of equilibrium measures for conformal expanding maps and Moran-like geometric constructions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pesin, Y.; Weiss, H.

1997-01-01

In this paper we establish the complete multifractal formalism for equilibrium measures for Holder continuous conformal expanding maps and expanding Markov Moran-like geometric constructions. Examples include Markov maps of an interval, beta transformations of an interval, rational maps with hyperbolic Julia sets, and conformal total endomorphisms. We also construct a Holder continuous homeomorphism of a compact metric space with an ergodic invariant measure of positive entropy for which the dimension spectrum is not convex, and hence the multifractal formalism fails.

Predicting health-related quality of life (EQ-5D-5 L) and capability wellbeing (ICECAP-A) in the context of opiate dependence using routine clinical outcome measures: CORE-OM, LDQ and TOP.

PubMed

Peak, Jasmine; Goranitis, Ilias; Day, Ed; Copello, Alex; Freemantle, Nick; Frew, Emma

2018-05-30

Economic evaluation normally requires information to be collected on outcome improvement using utility values. This is often not collected during the treatment of substance use disorders making cost-effectiveness evaluations of therapy difficult. One potential solution is the use of mapping to generate utility values from clinical measures. This study develops and evaluates mapping algorithms that could be used to predict the EuroQol-5D (EQ-5D-5 L) and the ICEpop CAPability measure for Adults (ICECAP-A) from the three commonly used clinical measures; the CORE-OM, the LDQ and the TOP measures. Models were estimated using pilot trial data of heroin users in opiate substitution treatment. In the trial the EQ-5D-5 L, ICECAP-A, CORE-OM, LDQ and TOP were administered at baseline, three and twelve month time intervals. Mapping was conducted using estimation and validation datasets. The normal estimation dataset, which comprised of baseline sample data, used ordinary least squares (OLS) and tobit regression methods. Data from the baseline and three month time periods were combined to create a pooled estimation dataset. Cluster and mixed regression methods were used to map from this dataset. Predictive accuracy of the models was assessed using the root mean square error (RMSE) and the mean absolute error (MAE). Algorithms were validated using sample data from the follow-up time periods. Mapping algorithms can be used to predict the ICECAP-A and the EQ-5D-5 L in the context of opiate dependence. Although both measures can be predicted, the ICECAP-A was better predicted by the clinical measures. There were no advantages of pooling the data. There were 6 chosen mapping algorithms, which had MAE scores ranging from 0.100 to 0.138 and RMSE scores ranging from 0.134 to 0.178. It is possible to predict the scores of the ICECAP-A and the EQ-5D-5 L with the use of mapping. In the context of opiate dependence, these algorithms provide the possibility of generating utility values from clinical measures and thus enabling economic evaluation of alternative therapy options. ISRCTN22608399 . Date of registration: 27/04/2012. Date of first randomisation: 14/08/2012.

The use of regression analysis in determining reference intervals for low hematocrit and thrombocyte count in multiple electrode aggregometry and platelet function analyzer 100 testing of platelet function.

PubMed

Kuiper, Gerhardus J A J M; Houben, Rik; Wetzels, Rick J H; Verhezen, Paul W M; Oerle, Rene van; Ten Cate, Hugo; Henskens, Yvonne M C; Lancé, Marcus D

2017-11-01

Low platelet counts and hematocrit levels hinder whole blood point-of-care testing of platelet function. Thus far, no reference ranges for MEA (multiple electrode aggregometry) and PFA-100 (platelet function analyzer 100) devices exist for low ranges. Through dilution methods of volunteer whole blood, platelet function at low ranges of platelet count and hematocrit levels was assessed on MEA for four agonists and for PFA-100 in two cartridges. Using (multiple) regression analysis, 95% reference intervals were computed for these low ranges. Low platelet counts affected MEA in a positive correlation (all agonists showed r 2 ≥ 0.75) and PFA-100 in an inverse correlation (closure times were prolonged with lower platelet counts). Lowered hematocrit did not affect MEA testing, except for arachidonic acid activation (ASPI), which showed a weak positive correlation (r 2 = 0.14). Closure time on PFA-100 testing was inversely correlated with hematocrit for both cartridges. Regression analysis revealed different 95% reference intervals in comparison with originally established intervals for both MEA and PFA-100 in low platelet or hematocrit conditions. Multiple regression analysis of ASPI and both tests on the PFA-100 for combined low platelet and hematocrit conditions revealed that only PFA-100 testing should be adjusted for both thrombocytopenia and anemia. 95% reference intervals were calculated using multiple regression analysis. However, coefficients of determination of PFA-100 were poor, and some variance remained unexplained. Thus, in this pilot study using (multiple) regression analysis, we could establish reference intervals of platelet function in anemia and thrombocytopenia conditions on PFA-100 and in thrombocytopenia conditions on MEA.

Genetic dissection of quantitative trait locus for ethanol sensitivity in long- and short-sleep mice.

PubMed

Bennett, B; Carosone-Link, P; Beeson, M; Gordon, L; Phares-Zook, N; Johnson, T E

2008-08-01

Interval-specific congenic strains (ISCS) allow fine mapping of a quantitative trait locus (QTL), narrowing its confidence interval by an order of magnitude or more. In earlier work, we mapped four QTL specifying differential ethanol sensitivity, assessed by loss of righting reflex because of ethanol (LORE), in the inbred long-sleep (ILS) and inbred short-sleep (ISS) strains, accounting for approximately 50% of the genetic variance for this trait. Subsequently, we generated reciprocal congenic strains in which each full QTL interval from ILS was bred onto the ISS background and vice versa. An earlier paper reported construction and results of the ISCS on the ISS background; here, we describe this process and report results on the ILS background. We developed multiple ISCS for each Lore QTL in which the QTL interval was broken into a number of smaller intervals. For each of the four QTL regions (chromosomes 1, 2, 11 and 15), we were successful in reducing the intervals significantly. Multiple, positive strains were overlapped to generate a single, reduced interval. Subsequently, this reduced region was overlaid on previous reductions from the ISS background congenics, resulting in substantial reductions in all QTL regions by approximately 75% from the initial mapping study. Genes with sequence or expression polymorphisms in the reduced intervals are potential candidates; evidence for these is presented. Genetic background effects can be important in detection of single QTL; combining this information with the generation of congenics on both backgrounds, as described here, is a powerful approach for fine mapping QTL.

Identification of milling and baking quality QTL in multiple soft wheat mapping populations.

PubMed

Cabrera, Antonio; Guttieri, Mary; Smith, Nathan; Souza, Edward; Sturbaum, Anne; Hua, Duc; Griffey, Carl; Barnett, Marla; Murphy, Paul; Ohm, Herb; Uphaus, Jim; Sorrells, Mark; Heffner, Elliot; Brown-Guedira, Gina; Van Sanford, David; Sneller, Clay

2015-11-01

Two mapping approaches were use to identify and validate milling and baking quality QTL in soft wheat. Two LG were consistently found important for multiple traits and we recommend the use marker-assisted selection on specific markers reported here. Wheat-derived food products require a range of characteristics. Identification and understanding of the genetic components controlling end-use quality of wheat is important for crop improvement. We assessed the underlying genetics controlling specific milling and baking quality parameters of soft wheat including flour yield, softness equivalent, flour protein, sucrose, sodium carbonate, water absorption and lactic acid, solvent retention capacities in a diversity panel and five bi-parental mapping populations. The populations were genotyped with SSR and DArT markers, with markers specific for the 1BL.1RS translocation and sucrose synthase gene. Association analysis and composite interval mapping were performed to identify quantitative trait loci (QTL). High heritability was observed for each of the traits evaluated, trait correlations were consistent over populations, and transgressive segregants were common in all bi-parental populations. A total of 26 regions were identified as potential QTL in the diversity panel and 74 QTL were identified across all five bi-parental mapping populations. Collinearity of QTL from chromosomes 1B and 2B was observed across mapping populations and was consistent with results from the association analysis in the diversity panel. Multiple regression analysis showed the importance of the two 1B and 2B regions and marker-assisted selection for the favorable alleles at these regions should improve quality.

Confidence intervals for distinguishing ordinal and disordinal interactions in multiple regression.

PubMed

Lee, Sunbok; Lei, Man-Kit; Brody, Gene H

2015-06-01

Distinguishing between ordinal and disordinal interaction in multiple regression is useful in testing many interesting theoretical hypotheses. Because the distinction is made based on the location of a crossover point of 2 simple regression lines, confidence intervals of the crossover point can be used to distinguish ordinal and disordinal interactions. This study examined 2 factors that need to be considered in constructing confidence intervals of the crossover point: (a) the assumption about the sampling distribution of the crossover point, and (b) the possibility of abnormally wide confidence intervals for the crossover point. A Monte Carlo simulation study was conducted to compare 6 different methods for constructing confidence intervals of the crossover point in terms of the coverage rate, the proportion of true values that fall to the left or right of the confidence intervals, and the average width of the confidence intervals. The methods include the reparameterization, delta, Fieller, basic bootstrap, percentile bootstrap, and bias-corrected accelerated bootstrap methods. The results of our Monte Carlo simulation study suggest that statistical inference using confidence intervals to distinguish ordinal and disordinal interaction requires sample sizes more than 500 to be able to provide sufficiently narrow confidence intervals to identify the location of the crossover point. (c) 2015 APA, all rights reserved).

Cathepsin B is a novel gender-dependent determinant of cholesterol absorption from the intestine[S

PubMed Central

Wong, Winifred P. S.; Altemus, Jessica B.; Hester, James F.; Chan, Ernest R.; Côté, Jean-François; Serre, David; Sehayek, Ephraim

2013-01-01

We used a mouse C57BL/6J×CASA/Rk intercross to map a locus on chromosome 14 that displayed a gender-dependent effect on cholesterol absorption from the intestine. Studies in congenic animals revealed a complex locus with multiple operating genetic determinants resulting in alternating gender-dependent phenotypic effects. Fine-mapping narrowed the locus to a critical 6.3 Mb interval. Female subcongenics, but not males, of the critical interval displayed a decrease of 33% in cholesterol absorption. RNA-Seq analysis of female subcongenic jejunum revealed that cysteine protease cathepsin B (Ctsb) is a candidate to explain the interval effect. Consistent with the phenotype in critical interval subcongenics, female Ctsb knockout mice, but not males, displayed a decrease of 31% in cholesterol absorption. Although studies in Ctsb knockouts revealed a gender-dependent effect on cholesterol absorption, further fine-mapping dismissed a role for Ctsb in determining the effect of the critical 6.3 Mb interval on cholesterol absorption. PMID:23248330

How to regress and predict in a Bland-Altman plot? Review and contribution based on tolerance intervals and correlated-errors-in-variables models.

PubMed

Francq, Bernard G; Govaerts, Bernadette

2016-06-30

Two main methodologies for assessing equivalence in method-comparison studies are presented separately in the literature. The first one is the well-known and widely applied Bland-Altman approach with its agreement intervals, where two methods are considered interchangeable if their differences are not clinically significant. The second approach is based on errors-in-variables regression in a classical (X,Y) plot and focuses on confidence intervals, whereby two methods are considered equivalent when providing similar measures notwithstanding the random measurement errors. This paper reconciles these two methodologies and shows their similarities and differences using both real data and simulations. A new consistent correlated-errors-in-variables regression is introduced as the errors are shown to be correlated in the Bland-Altman plot. Indeed, the coverage probabilities collapse and the biases soar when this correlation is ignored. Novel tolerance intervals are compared with agreement intervals with or without replicated data, and novel predictive intervals are introduced to predict a single measure in an (X,Y) plot or in a Bland-Atman plot with excellent coverage probabilities. We conclude that the (correlated)-errors-in-variables regressions should not be avoided in method comparison studies, although the Bland-Altman approach is usually applied to avert their complexity. We argue that tolerance or predictive intervals are better alternatives than agreement intervals, and we provide guidelines for practitioners regarding method comparison studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A study of the Herald-Phillipstown fault in the Wabash Valley using drillhole and 3-D seismic reflection data

NASA Astrophysics Data System (ADS)

Kroenke, Samantha E.

In June 2009, a 2.2 square mile 3-D high resolution seismic reflection survey was shot in southeastern Illinois in the Phillipstown Consolidated oilfield. A well was drilled in the 3-D survey area to tie the seismic to the geological data with a synthetic seismogram from the sonic log. The objectives of the 3-D seismic survey were three-fold: (1) To image and interpret faulting of the Herald-Phillipstown Fault using drillhole-based geological and seismic cross-sections and structural contour maps created from the drillhole data and seismic reflection data, (2) To test the effectiveness of imaging the faults by selected seismic attributes, and (3) To compare spectral decomposition amplitude maps with an isochron map and an isopach map of a selected geologic interval (VTG interval). Drillhole and seismic reflection data show that various formation offsets increase near the main Herald-Phillipstown fault, and that the fault and its large offset subsidiary faults penetrate the Precambrian crystalline basement. A broad, northeast-trending 10,000 feet wide graben is consistently observed in the drillhole data. Both shallow and deep formations in the geological cross-sections reveal small horst and graben features within the broad graben created possibly in response to fault reactivations. The HPF faults have been interpreted as originally Precambrian age high-angle, normal faults reactivated with various amounts and types of offset. Evidence for strike-slip movement is also clear on several faults. Changes in the seismic attribute values in the selected interval and along various time slices throughout the whole dataset correlate with the Herald-Phillipstown faults. Overall, seismic attributes could provide a means of mapping large offset faults in areas with limited or absent drillhole data. Results of the spectral decomposition suggest that if the interval velocity is known for a particular formation or interval, high-resolution 3-D seismic reflection surveys could utilize these amplitudes as an alternative seismic interpretation method for estimating formation thicknesses. A VTG isopach map was compared with an isochron map and a spectral decomposition amplitude map. The results reveal that the isochron map strongly correlates with the isopach map as well as the spectral decomposition map. It was also found that thicker areas in the isopach correlated with higher amplitude values in the spectral decomposition amplitude map. Offsets along the faults appear sharper in these amplitudes and isochron maps than in the isopach map, possibly as a result of increased spatial sampling.

Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra

NASA Astrophysics Data System (ADS)

Shan, Jiajia; Wang, Xue; Zhou, Hao; Han, Shuqing; Riza, Dimas Firmanda Al; Kondo, Naoshi

2018-04-01

Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models’ performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.

Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra.

PubMed

Shan, Jiajia; Wang, Xue; Zhou, Hao; Han, Shuqing; Riza, Dimas Firmanda Al; Kondo, Naoshi

2018-03-13

Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models' performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.

Map based navigation for autonomous underwater vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tuohy, S.T.; Leonard, J.J.; Bellingham, J.G.

1995-12-31

In this work, a map based navigation algorithm is developed wherein measured geophysical properties are matched to a priori maps. The objectives is a complete algorithm applicable to a small, power-limited AUV which performs in real time to a required resolution with bounded position error. Interval B-Splines are introduced for the non-linear representation of two-dimensional geophysical parameters that have measurement uncertainty. Fine-scale position determination involves the solution of a system of nonlinear polynomial equations with interval coefficients. This system represents the complete set of possible vehicle locations and is formulated as the intersection of contours established on each map frommore » the simultaneous measurement of associated geophysical parameters. A standard filter mechanisms, based on a bounded interval error model, predicts the position of the vehicle and, therefore, screens extraneous solutions. When multiple solutions are found, a tracking mechanisms is applied until a unique vehicle location is determined.« less

Dynamics of Stability of Orientation Maps Recorded with Optical Imaging.

PubMed

Shumikhina, S I; Bondar, I V; Svinov, M M

2018-03-15

Orientation selectivity is an important feature of visual cortical neurons. Optical imaging of the visual cortex allows for the generation of maps of orientation selectivity that reflect the activity of large populations of neurons. To estimate the statistical significance of effects of experimental manipulations, evaluation of the stability of cortical maps over time is required. Here, we performed optical imaging recordings of the visual cortex of anesthetized adult cats. Monocular stimulation with moving clockwise square-wave gratings that continuously changed orientation and direction was used as the mapping stimulus. Recordings were repeated at various time intervals, from 15 min to 16 h. Quantification of map stability was performed on a pixel-by-pixel basis using several techniques. Map reproducibility showed clear dynamics over time. The highest degree of stability was seen in maps recorded 15-45 min apart. Averaging across all time intervals and all stimulus orientations revealed a mean shift of 2.2 ± 0.1°. There was a significant tendency for larger shifts to occur at longer time intervals. Shifts between 2.8° (mean ± 2SD) and 5° were observed more frequently at oblique orientations, while shifts greater than 5° appeared more frequently at cardinal orientations. Shifts greater than 5° occurred rarely overall (5.4% of cases) and never exceeded 11°. Shifts of 10-10.6° (0.7%) were seen occasionally at time intervals of more than 4 h. Our findings should be considered when evaluating the potential effect of experimental manipulations on orientation selectivity mapping studies. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Regression Equations for Estimating Flood Flows at Selected Recurrence Intervals for Ungaged Streams in Pennsylvania

USGS Publications Warehouse

Roland, Mark A.; Stuckey, Marla H.

2008-01-01

Regression equations were developed for estimating flood flows at selected recurrence intervals for ungaged streams in Pennsylvania with drainage areas less than 2,000 square miles. These equations were developed utilizing peak-flow data from 322 streamflow-gaging stations within Pennsylvania and surrounding states. All stations used in the development of the equations had 10 or more years of record and included active and discontinued continuous-record as well as crest-stage partial-record stations. The state was divided into four regions, and regional regression equations were developed to estimate the 2-, 5-, 10-, 50-, 100-, and 500-year recurrence-interval flood flows. The equations were developed by means of a regression analysis that utilized basin characteristics and flow data associated with the stations. Significant explanatory variables at the 95-percent confidence level for one or more regression equations included the following basin characteristics: drainage area; mean basin elevation; and the percentages of carbonate bedrock, urban area, and storage within a basin. The regression equations can be used to predict the magnitude of flood flows for specified recurrence intervals for most streams in the state; however, they are not valid for streams with drainage areas generally greater than 2,000 square miles or with substantial regulation, diversion, or mining activity within the basin. Estimates of flood-flow magnitude and frequency for streamflow-gaging stations substantially affected by upstream regulation are also presented.

Variability in total ozone associated with baroclinic waves

NASA Technical Reports Server (NTRS)

Mote, Philip W.; Holton, James R.; Wallace, John M.

1991-01-01

One-point regression maps of total ozone formed by regressing the time series of bandpass-filtered geopotential height data have been analyzed against Total Ozone Mapping Spectrometer data. Results obtained reveal a strong signature of baroclinic waves in the ozone variability. The regressed patterns are found to be similar in extent and behavior to the relative vorticity patterns reported by Lim and Wallace (1991).

Characterization of minimal sequences associated with self-similar interval exchange maps

NASA Astrophysics Data System (ADS)

Cobo, Milton; Gutiérrez-Romo, Rodolfo; Maass, Alejandro

2018-04-01

The construction of affine interval exchange maps (IEMs) with wandering intervals that are semi-conjugate to a given self-similar IEM is strongly related to the existence of the so-called minimal sequences associated with local potentials, which are certain elements of the substitution subshift arising from the given IEM. In this article, under the condition called unique representation property, we characterize such minimal sequences for potentials coming from non-real eigenvalues of the substitution matrix. We also give conditions on the slopes of the affine extensions of a self-similar IEM that determine whether it exhibits a wandering interval or not.

Confidence Intervals for Squared Semipartial Correlation Coefficients: The Effect of Nonnormality

ERIC Educational Resources Information Center

Algina, James; Keselman, H. J.; Penfield, Randall D.

2010-01-01

The increase in the squared multiple correlation coefficient ([delta]R[superscript 2]) associated with a variable in a regression equation is a commonly used measure of importance in regression analysis. Algina, Keselman, and Penfield found that intervals based on asymptotic principles were typically very inaccurate, even though the sample size…

USGS Maps

USGS Publications Warehouse

,

1994-01-01

Most USGS topographic maps use brown contours to show the shape and elevation of the terrain. Elevations are usually shown in feet, but on some maps they are in meters. Contour intervals vary, depending mainly on the scale of the map and the type of terrain.

A new computer aided diagnosis system for evaluation of chronic liver disease with ultrasound shear wave elastography imaging.

PubMed

Gatos, Ilias; Tsantis, Stavros; Spiliopoulos, Stavros; Karnabatidis, Dimitris; Theotokas, Ioannis; Zoumpoulis, Pavlos; Loupas, Thanasis; Hazle, John D; Kagadis, George C

2016-03-01

Classify chronic liver disease (CLD) from ultrasound shear-wave elastography (SWE) imaging by means of a computer aided diagnosis (CAD) system. The proposed algorithm employs an inverse mapping technique (red-green-blue to stiffness) to quantify 85 SWE images (54 healthy and 31 with CLD). Texture analysis is then applied involving the automatic calculation of 330 first and second order textural features from every transformed stiffness value map to determine functional features that characterize liver elasticity and describe liver condition for all available stages. Consequently, a stepwise regression analysis feature selection procedure is utilized toward a reduced feature subset that is fed into the support vector machines (SVMs) classification algorithm in the design of the CAD system. With regard to the mapping procedure accuracy, the stiffness map values had an average difference of 0.01 ± 0.001 kPa compared to the quantification results derived from the color-box provided by the built-in software of the ultrasound system. Highest classification accuracy from the SVM model was 87.0% with sensitivity and specificity values of 83.3% and 89.1%, respectively. Receiver operating characteristic curves analysis gave an area under the curve value of 0.85 with [0.77-0.89] confidence interval. The proposed CAD system employing color to stiffness mapping and classification algorithms offered superior results, comparing the already published clinical studies. It could prove to be of value to physicians improving the diagnostic accuracy of CLD and can be employed as a second opinion tool for avoiding unnecessary invasive procedures.

Psychophysical Map Stability in Bilateral Sequential Cochlear Implantation: Comparing Current Audiology Methods to a New Statistical Definition.

PubMed

Domville-Lewis, Chloe; Santa Maria, Peter L; Upson, Gemma; Chester-Browne, Ronel; Atlas, Marcus D

2015-01-01

The purpose of this study was to establish a statistical definition for stability in cochlear implant maps. Once defined, this study aimed to compare the duration taken to achieve a stable map in first and second implants in patients who underwent sequential bilateral cochlear implantation. This article also sought to evaluate a number of factors that potentially affect map stability. A retrospective cohort study of 33 patients with sensorineural hearing loss who received sequential bilateral cochlear implantation (Cochlear, Sydney, Australia), performed by the senior author. Psychophysical parameters of hearing threshold scores, comfort scores, and the dynamic range were measured for the apical, medial, and basal portions of the cochlear implant electrode at a range of intervals postimplantation. Stability was defined statistically as a less than 10% difference in threshold, comfort, and dynamic range scores over three consecutive mapping sessions. A senior cochlear implant audiologist, blinded to implant order and the statistical results, separately analyzed these psychophysical map parameters using current assessment methods. First and second implants were compared for duration to achieve stability, age, gender, the duration of deafness, etiology of deafness, time between the insertion of the first and second implant, and the presence or absence of preoperative hearing aids were evaluated and its relationship to stability. Statistical analysis included performing a two-tailed Student's t tests and least squares regression analysis, with a statistical significance set at p ≤ 0.05. There was a significant positive correlation between the devised statistical definition and the current audiology methods for assessing stability, with a Pearson correlation coefficient r = 0.36 and a least squares regression slope (b) of 0.41, df(58), 95% confidence interval 0.07 to 0.55 (p = 0.004). The average duration from device switch on to stability in the first implant was 87 days using current audiology methods and 81 days using the statistical definition, with no statistically significant difference between assessment methods (p = 0.2). The duration to achieve stability in the second implant was 51 days using current audiology methods and 60 days using the statistical method, and again no difference between the two assessment methods (p = 0.13). There was a significant reduction in the time to achieve stability in second implants for both audiology and statistical methods (p < 0.001 and p = 0.02, respectively). There was a difference in duration to achieve stability based on electrode array region, with basal portions taking longer to stabilize than apical in the first implant (p = 0.02) and both apical and medial segments in second implants (p = 0.004 and p = 0.01, respectively). No factors that were evaluated in this study, including gender, age, etiology of deafness, duration of deafness, time between implant insertion, and the preoperative hearing aid status, were correlated with stability duration in either stability assessment method. Our statistical definition can accurately predict cochlear implant map stability when compared with current audiology practices. Cochlear implants that are implanted second tend to stabilize sooner than the first, which has a significant impact on counseling before a second implant. No factors evaluated affected the duration required to achieve stability in this study.

Fine mapping of the NRC-1 tumor suppressor locus within chromosome 3p12.

PubMed

Zhang, Kun; Lott, Steven T; Jin, Li; Killary, Ann McNeill

2007-08-31

Identification of tumor suppressor genes based on physical mapping exercises has proven to be a challenging endeavor, due to the difficulty of narrowing regions of loss of heterozygosity (LOH), infrequency of homozygous deletions, and the labor-intensive characterization process for screening candidates in a given genomic interval. We previously defined a chromosome 3p12 tumor suppressor locus NRC-1 (Nonpapillary Renal Carcinoma-1) by functional complementation experiments in which renal cell carcinoma microcell hybrids containing introduced normal chromosome 3p fragments were either suppressed or unsuppressed for tumorigenicity following injection into athymic nude mice. We now present the fine-scale physical mapping of NRC-1 using a QPCR-based approach for measuring copy number at sequence tagged sites (STS) which allowed a sub-exon mapping resolution. Using STS-QPCR and a novel statistical algorithm, the NRC-1 locus was narrowed to 4.615-Mb with the distal boundary mapping within a 38-Kb interval between exon 3 and exon 4 of the DUTT1/Robo1 gene, currently the only candidate tumor suppressor gene in the interval. Further mutational screening and gene expression analyses indicate that DUTT1/ROBO1 is not involved in the tumor suppressor activity of NRC-1, suggesting that there are at least two important tumor suppressor genes within the chromosome 3p12 interval.

Regression analysis of case K interval-censored failure time data in the presence of informative censoring.

PubMed

Wang, Peijie; Zhao, Hui; Sun, Jianguo

2016-12-01

Interval-censored failure time data occur in many fields such as demography, economics, medical research, and reliability and many inference procedures on them have been developed (Sun, 2006; Chen, Sun, and Peace, 2012). However, most of the existing approaches assume that the mechanism that yields interval censoring is independent of the failure time of interest and it is clear that this may not be true in practice (Zhang et al., 2007; Ma, Hu, and Sun, 2015). In this article, we consider regression analysis of case K interval-censored failure time data when the censoring mechanism may be related to the failure time of interest. For the problem, an estimated sieve maximum-likelihood approach is proposed for the data arising from the proportional hazards frailty model and for estimation, a two-step procedure is presented. In the addition, the asymptotic properties of the proposed estimators of regression parameters are established and an extensive simulation study suggests that the method works well. Finally, we apply the method to a set of real interval-censored data that motivated this study. © 2016, The International Biometric Society.

Construction of a high-density genetic map using specific length amplified fragment markers and identification of a quantitative trait locus for anthracnose resistance in walnut (Juglans regia L.).

PubMed

Zhu, Yufeng; Yin, Yanfei; Yang, Keqiang; Li, Jihong; Sang, Yalin; Huang, Long; Fan, Shu

2015-08-18

Walnut (Juglans regia, 2n = 32, approximately 606 Mb per 1C genome) is an economically important tree crop. Resistance to anthracnose, caused by Colletotrichum gloeosporioides, is a major objective of walnut genetic improvement in China. The recently developed specific length amplified fragment sequencing (SLAF-seq) is an efficient strategy that can obtain large numbers of markers with sufficient sequence information to construct high-density genetic maps and permits detection of quantitative trait loci (QTLs) for molecular breeding. SLAF-seq generated 161.64 M paired-end reads. 153,820 SLAF markers were obtained, of which 49,174 were polymorphic. 13,635 polymorphic markers were sorted into five segregation types and 2,577 markers of them were used to construct genetic linkage maps: 2,395 of these fell into 16 linkage groups (LGs) for the female map, 448 markers for the male map, and 2,577 markers for the integrated map. Taking into account the size of all LGs, the marker coverage was 2,664.36 cM for the female map, 1,305.58 cM for the male map, and 2,457.82 cM for the integrated map. The average intervals between two adjacent mapped markers were 1.11 cM, 2.91 cM and 0.95 cM for three maps, respectively. 'SNP_only' markers accounted for 89.25% of the markers on the integrated map. Mapping markers contained 5,043 single nucleotide polymorphisms (SNPs) loci, which corresponded to two SNP loci per SLAF marker. According to the integrated map, we used interval mapping (Logarithm of odds, LOD > 3.0) to detect our quantitative trait. One QTL was detected for anthracnose resistance. The interval of this QTL ranged from 165.51 cM to 176.33 cM on LG14, and ten markers in this interval that were above the threshold value were considered to be linked markers to the anthracnose resistance trait. The phenotypic variance explained by each marker ranged from 16.2 to 19.9%, and their LOD scores varied from 3.22 to 4.04. High-density genetic maps for walnut containing 16 LGs were constructed using the SLAF-seq method with an F1 population. One QTL for walnut anthracnose resistance was identified based on the map. The results will aid molecular marker-assisted breeding and walnut resistance genes identification.

Flood-hazard mapping in Honduras in response to Hurricane Mitch

USGS Publications Warehouse

Mastin, M.C.

2002-01-01

The devastation in Honduras due to flooding from Hurricane Mitch in 1998 prompted the U.S. Agency for International Development, through the U.S. Geological Survey, to develop a country-wide systematic approach of flood-hazard mapping and a demonstration of the method at selected sites as part of a reconstruction effort. The design discharge chosen for flood-hazard mapping was the flood with an average return interval of 50 years, and this selection was based on discussions with the U.S. Agency for International Development and the Honduran Public Works and Transportation Ministry. A regression equation for estimating the 50-year flood discharge using drainage area and annual precipitation as the explanatory variables was developed, based on data from 34 long-term gaging sites. This equation, which has a standard error of prediction of 71.3 percent, was used in a geographic information system to estimate the 50-year flood discharge at any location for any river in the country. The flood-hazard mapping method was demonstrated at 15 selected municipalities. High-resolution digital-elevation models of the floodplain were obtained using an airborne laser-terrain mapping system. Field verification of the digital elevation models showed that the digital-elevation models had mean absolute errors ranging from -0.57 to 0.14 meter in the vertical dimension. From these models, water-surface elevation cross sections were obtained and used in a numerical, one-dimensional, steady-flow stepbackwater model to estimate water-surface profiles corresponding to the 50-year flood discharge. From these water-surface profiles, maps of area and depth of inundation were created at the 13 of the 15 selected municipalities. At La Lima only, the area and depth of inundation of the channel capacity in the city was mapped. At Santa Rose de Aguan, no numerical model was created. The 50-year flood and the maps of area and depth of inundation are based on the estimated 50-year storm tide.

Chaotic orbits obeying one isolating integral in a four-dimensional map

NASA Astrophysics Data System (ADS)

Muzzio, J. C.

2018-02-01

We have recently presented strong evidence that chaotic orbits that obey one isolating integral besides energy exist in a toy Hamiltonian model with three degrees of freedom and are bounded by regular orbits that isolate them from the Arnold web. The interval covered by those numerical experiments was equivalent to about one million Hubble times in a galactic context. Here, we use a four-dimensional map to confirm our previous results and to extend that interval 50 times. We show that, at least within that interval, features found in lower dimension Hamiltonian systems and maps are also present in our study, e.g. within the phase space occupied by a chaotic orbit that obeys one integral there are subspaces where that orbit does not enter and are, instead, occupied by regular orbits that, if tori, bound other chaotic orbits obeying one integral and, if cantori, produce stickiness. We argue that the validity of our results might exceed the time intervals covered by the numerical experiments.

Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat—Turkey)

NASA Astrophysics Data System (ADS)

Yilmaz, Işık

2009-06-01

The purpose of this study is to compare the landslide susceptibility mapping methods of frequency ratio (FR), logistic regression and artificial neural networks (ANN) applied in the Kat County (Tokat—Turkey). Digital elevation model (DEM) was first constructed using GIS software. Landslide-related factors such as geology, faults, drainage system, topographical elevation, slope angle, slope aspect, topographic wetness index (TWI) and stream power index (SPI) were used in the landslide susceptibility analyses. Landslide susceptibility maps were produced from the frequency ratio, logistic regression and neural networks models, and they were then compared by means of their validations. The higher accuracies of the susceptibility maps for all three models were obtained from the comparison of the landslide susceptibility maps with the known landslide locations. However, respective area under curve (AUC) values of 0.826, 0.842 and 0.852 for frequency ratio, logistic regression and artificial neural networks showed that the map obtained from ANN model is more accurate than the other models, accuracies of all models can be evaluated relatively similar. The results obtained in this study also showed that the frequency ratio model can be used as a simple tool in assessment of landslide susceptibility when a sufficient number of data were obtained. Input process, calculations and output process are very simple and can be readily understood in the frequency ratio model, however logistic regression and neural networks require the conversion of data to ASCII or other formats. Moreover, it is also very hard to process the large amount of data in the statistical package.

Mapping Regional Impervious Surface Distribution from Night Time Light: The Variability across Global Cities

NASA Astrophysics Data System (ADS)

Lin, M.; Yang, Z.; Park, H.; Qian, S.; Chen, J.; Fan, P.

2017-12-01

Impervious surface area (ISA) has become an important indicator for studying urban environments, but mapping ISA at the regional or global scale is still challenging due to the complexity of impervious surface features. The Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) nighttime light data is (NTL) and Resolution Imaging Spectroradiometer (MODIS) are the major remote sensing data source for regional ISA mapping. A single regression relationship between fractional ISA and NTL or various index derived based on NTL and MODIS vegetation index (NDVI) data was established in many previous studies for regional ISA mapping. However, due to the varying geographical, climatic, and socio-economic characteristics of different cities, the same regression relationship may vary significantly across different cities in the same region in terms of both fitting performance (i.e. R2) and the rate of change (Slope). In this study, we examined the regression relationship between fractional ISA and Vegetation Adjusted Nighttime light Urban Index (VANUI) for 120 randomly selected cities around the world with a multilevel regression model. We found that indeed there is substantial variability of both the R2 (0.68±0.29) and slopes (0.64±0.40) among individual regressions, which suggests that multilevel/hierarchical models are needed for accuracy improvement of future regional ISA mapping .Further analysis also let us find the this substantial variability are affected by climate conditions, socio-economic status, and urban spatial structures. However, all these effects are nonlinear rather than linear, thus could not modeled explicitly in multilevel linear regression models.

Estimating selected low-flow frequency statistics and harmonic-mean flows for ungaged, unregulated streams in Indiana

USGS Publications Warehouse

Martin, Gary R.; Fowler, Kathleen K.; Arihood, Leslie D.

2016-09-06

Information on low-flow characteristics of streams is essential for the management of water resources. This report provides equations for estimating the 1-, 7-, and 30-day mean low flows for a recurrence interval of 10 years and the harmonic-mean flow at ungaged, unregulated stream sites in Indiana. These equations were developed using the low-flow statistics and basin characteristics for 108 continuous-record streamgages in Indiana with at least 10 years of daily mean streamflow data through the 2011 climate year (April 1 through March 31). The equations were developed in cooperation with the Indiana Department of Environmental Management.Regression techniques were used to develop the equations for estimating low-flow frequency statistics and the harmonic-mean flows on the basis of drainage-basin characteristics. A geographic information system was used to measure basin characteristics for selected streamgages. A final set of 25 basin characteristics measured at all the streamgages were evaluated to choose the best predictors of the low-flow statistics.Logistic-regression equations applicable statewide are presented for estimating the probability that selected low-flow frequency statistics equal zero. These equations use the explanatory variables total drainage area, average transmissivity of the full thickness of the unconsolidated deposits within 1,000 feet of the stream network, and latitude of the basin outlet. The percentage of the streamgage low-flow statistics correctly classified as zero or nonzero using the logistic-regression equations ranged from 86.1 to 88.9 percent.Generalized-least-squares regression equations applicable statewide for estimating nonzero low-flow frequency statistics use total drainage area, the average hydraulic conductivity of the top 70 feet of unconsolidated deposits, the slope of the basin, and the index of permeability and thickness of the Quaternary surficial sediments as explanatory variables. The average standard error of prediction of these regression equations ranges from 55.7 to 61.5 percent.Regional weighted-least-squares regression equations were developed for estimating the harmonic-mean flows by dividing the State into three low-flow regions. The Northern region uses total drainage area and the average transmissivity of the entire thickness of unconsolidated deposits as explanatory variables. The Central region uses total drainage area, the average hydraulic conductivity of the entire thickness of unconsolidated deposits, and the index of permeability and thickness of the Quaternary surficial sediments. The Southern region uses total drainage area and the percent of the basin covered by forest. The average standard error of prediction for these equations ranges from 39.3 to 66.7 percent.The regional regression equations are applicable only to stream sites with low flows unaffected by regulation and to stream sites with drainage basin characteristic values within specified limits. Caution is advised when applying the equations for basins with characteristics near the applicable limits and for basins with karst drainage features and for urbanized basins. Extrapolations near and beyond the applicable basin characteristic limits will have unknown errors that may be large. Equations are presented for use in estimating the 90-percent prediction interval of the low-flow statistics estimated by use of the regression equations at a given stream site.The regression equations are to be incorporated into the U.S. Geological Survey StreamStats Web-based application for Indiana. StreamStats allows users to select a stream site on a map and automatically measure the needed basin characteristics and compute the estimated low-flow statistics and associated prediction intervals.

Regional biostratigraphy and paleoenvironmental history of Miocene of onshore and offshore Alabama

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, C.C.

1989-09-01

Subsurface Miocene sediments of coastal Alabama and the adjoining state and federal waters consist of a clastic wedge varying in thickness from less than 1,000 ft in southern Alabama to a maximum of about 6,000 ft in the northeastern portion of the Main Pass area. Relatively deep-water and open-marine transgressive basal Miocene clays and shales unconformably overlie a gently southwestward-dipping late Oligocene-earliest Miocene carbonate platform. Middle and late Miocene sediments consist of a regressive offlapping sequence of sand and shale deposited in varying neritic paleoenvironments. Analysis of planktonic and benthonic foraminifera has resulted in a refined biostratigraphic zonation of thesemore » sediments, permitting the recognition of several regional time-equivalent datum levels, or biohorizons. These biohorizons are shown on a series of subsurface cross sections that show the dramatic southwestward thickening of middle and late Miocene sediments as well as illustrate the relationships of the producing intervals within the Cibicides carstensi and Discorbis 12 interval zones. The paleoenvironmental history of the Miocene has been reconstructed on a series of paleobathymetric maps drawn for selected regional biohorizons. Among other features, these maps have proven the existence and outlined the margins of previously unrecognized shallow-meritic deltaic sediments in southeastern Mobile County and in the Chandeleur and Viosca Knoll (north) areas. Analysis of sedimentation rates, which range from less than 25 to 1,370 ft/m.y., further aids in understanding the coastal shelf, deltaic, and open-marine depositional history of the Miocene of Alabama and the adjoining state and federal waters.« less

Simple estimation procedures for regression analysis of interval-censored failure time data under the proportional hazards model.

PubMed

Sun, Jianguo; Feng, Yanqin; Zhao, Hui

2015-01-01

Interval-censored failure time data occur in many fields including epidemiological and medical studies as well as financial and sociological studies, and many authors have investigated their analysis (Sun, The statistical analysis of interval-censored failure time data, 2006; Zhang, Stat Modeling 9:321-343, 2009). In particular, a number of procedures have been developed for regression analysis of interval-censored data arising from the proportional hazards model (Finkelstein, Biometrics 42:845-854, 1986; Huang, Ann Stat 24:540-568, 1996; Pan, Biometrics 56:199-203, 2000). For most of these procedures, however, one drawback is that they involve estimation of both regression parameters and baseline cumulative hazard function. In this paper, we propose two simple estimation approaches that do not need estimation of the baseline cumulative hazard function. The asymptotic properties of the resulting estimates are given, and an extensive simulation study is conducted and indicates that they work well for practical situations.

StreamStats in Oklahoma - Drainage-Basin Characteristics and Peak-Flow Frequency Statistics for Ungaged Streams

USGS Publications Warehouse

Smith, S. Jerrod; Esralew, Rachel A.

2010-01-01

The USGS Streamflow Statistics (StreamStats) Program was created to make geographic information systems-based estimation of streamflow statistics easier, faster, and more consistent than previously used manual techniques. The StreamStats user interface is a map-based internet application that allows users to easily obtain streamflow statistics, basin characteristics, and other information for user-selected U.S. Geological Survey data-collection stations and ungaged sites of interest. The application relies on the data collected at U.S. Geological Survey streamflow-gaging stations, computer aided computations of drainage-basin characteristics, and published regression equations for several geographic regions comprising the United States. The StreamStats application interface allows the user to (1) obtain information on features in selected map layers, (2) delineate drainage basins for ungaged sites, (3) download drainage-basin polygons to a shapefile, (4) compute selected basin characteristics for delineated drainage basins, (5) estimate selected streamflow statistics for ungaged points on a stream, (6) print map views, (7) retrieve information for U.S. Geological Survey streamflow-gaging stations, and (8) get help on using StreamStats. StreamStats was designed for national application, with each state, territory, or group of states responsible for creating unique geospatial datasets and regression equations to compute selected streamflow statistics. With the cooperation of the Oklahoma Department of Transportation, StreamStats has been implemented for Oklahoma and is available at http://water.usgs.gov/osw/streamstats/. The Oklahoma StreamStats application covers 69 processed hydrologic units and most of the state of Oklahoma. Basin characteristics available for computation include contributing drainage area, contributing drainage area that is unregulated by Natural Resources Conservation Service floodwater retarding structures, mean-annual precipitation at the drainage-basin outlet for the period 1961-1990, 10-85 channel slope (slope between points located at 10 percent and 85 percent of the longest flow-path length upstream from the outlet), and percent impervious area. The Oklahoma StreamStats application interacts with the National Streamflow Statistics database, which contains the peak-flow regression equations in a previously published report. Fourteen peak-flow (flood) frequency statistics are available for computation in the Oklahoma StreamStats application. These statistics include the peak flow at 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals for rural, unregulated streams; and the peak flow at 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals for rural streams that are regulated by Natural Resources Conservation Service floodwater retarding structures. Basin characteristics and streamflow statistics cannot be computed for locations in playa basins (mostly in the Oklahoma Panhandle) and along main stems of the largest river systems in the state, namely the Arkansas, Canadian, Cimarron, Neosho, Red, and Verdigris Rivers, because parts of the drainage areas extend outside of the processed hydrologic units.

Mapping a major QTL responsible for dwarf architecture in Brassica napus using a single-nucleotide polymorphism marker approach.

PubMed

Wang, Yankun; Chen, Wenjing; Chu, Pu; Wan, Shubei; Yang, Mao; Wang, Mingming; Guan, Rongzhan

2016-08-18

Key genes related to plant type traits have played very important roles in the "green revolution" by increasing lodging resistance and elevating the harvest indices of crop cultivars. Although there have been numerous achievements in the development of dwarfism and plant type in Brassica napus breeding, exploring new materials conferring oilseed rape with efficient plant types that provide higher yields is still of significance in breeding, as well as in elucidating the mechanisms underlying plant development. Here, we report a new dwarf architecture with down-curved leaf mutant (Bndwf/dcl1) isolated from an ethyl methanesulphonate (EMS)-mutagenized B. napus line, together with its inheritance and gene mapping, and pleiotropic effects of the mapped locus on plant-type traits. We constructed a high-density single-nucleotide polymorphism (SNP) map using a backcross population derived from the Bndwf/dcl1 mutant and the canola cultivar 'zhongshuang11' ('ZS11') and mapped the dwarf architecture with the down-curved leaf dominant locus, BnDWF/DCL1, in a 6.58-cM interval between SNP marker bins M46180 and M49962 on the linkage group (LG) C05 of B. napus. Further mapping with other materials derived from Bndwf/dcl1 narrowed the interval harbouring BnDWF/DCL1 to 175 kb in length and this interval contained 16 annotated genes. Quantitative trait locus (QTL) mappings with the backcross population for plant type traits, including plant height, branching height, main raceme length and average branching interval, indicated that the mapped QTLs for plant type traits were located at the same position as the BnDWF/DCL1 locus. This study suggests that the BnDWF/DCL1 locus is a major pleiotropic locus/QTL in B. napus, which may reduce plant height, alter plant type traits and change leaf shape, and thus may lead to compact plant architecture. Accordingly, this locus may have substantial breeding potential for increasing planting density.

Effect of increasing the sampling interval to 2 seconds on the radiation dose and accuracy of CT perfusion of the head and neck.

PubMed

Tawfik, Ahmed M; Razek, Ahmed A; Elhawary, Galal; Batouty, Nihal M

2014-01-01

To evaluate the effect of increasing the sampling interval from 1 second (1 image per second) to 2 seconds (1 image every 2 seconds) on computed tomographic (CT) perfusion (CTP) of head and neck tumors. Twenty patients underwent CTP studies of head and neck tumors with images acquired in cine mode for 50 seconds using sampling interval of 1 second. Using deconvolution-based software, analysis of CTP was done with sampling interval of 1 second and then 2 seconds. Perfusion maps representing blood flow, blood volume, mean transit time, and permeability surface area product (PS) were obtained. Quantitative tumor CTP values were compared between the 2 sampling intervals. Two blinded radiologists compared the subjective quality of CTP maps using a 3-point scale between the 2 sampling intervals. Radiation dose parameters were recorded for the 2 sampling interval rates. No significant differences were observed between the means of the 4 perfusion parameters generated using both sampling intervals; all P >0.05. The 95% limits of agreement between the 2 sampling intervals were -65.9 to 48.1) mL/min per 100 g for blood flow, -3.6 to 3.1 mL/100 g for blood volume, -2.9 to 3.8 seconds for mean transit time, and -10.0 to 12.5 mL/min per 100 g for PS. There was no significant difference between the subjective quality scores of CTP maps obtained using the 2 sampling intervals; all P > 0.05. Radiation dose was halved when sampling interval increased from 1 to 2 seconds. Increasing the sampling interval rate to 1 image every 2 seconds does not compromise the image quality and has no significant effect on quantitative perfusion parameters of head and neck tumors. The radiation dose is halved.

Cuntz-Krieger algebras representations from orbits of interval maps

NASA Astrophysics Data System (ADS)

Correia Ramos, C.; Martins, Nuno; Pinto, Paulo R.; Sousa Ramos, J.

2008-05-01

Let f be an expansive Markov interval map with finite transition matrix Af. Then for every point, we yield an irreducible representation of the Cuntz-Krieger algebra and show that two such representations are unitarily equivalent if and only if the points belong to the same generalized orbit. The restriction of each representation to the gauge part of is decomposed into irreducible representations, according to the decomposition of the orbit.

Estimating the magnitude of peak flows for streams in Kentucky for selected recurrence intervals

USGS Publications Warehouse

Hodgkins, Glenn A.; Martin, Gary R.

2003-01-01

This report gives estimates of, and presents techniques for estimating, the magnitude of peak flows for streams in Kentucky for recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years. A flowchart in this report guides the user to the appropriate estimates and (or) estimating techniques for a site on a specific stream. Estimates of peak flows are given for 222 U.S. Geological Survey streamflow-gaging stations in Kentucky. In the development of the peak-flow estimates at gaging stations, a new generalized skew coefficient was calculated for the State. This single statewide value of 0.011 (with a standard error of prediction of 0.520) is more appropriate for Kentucky than the national skew isoline map in Bulletin 17B of the Interagency Advisory Committee on Water Data. Regression equations are presented for estimating the peak flows on ungaged, unregulated streams in rural drainage basins. The equations were developed by use of generalized-least-squares regression procedures at 187 U.S. Geological Survey gaging stations in Kentucky and 51 stations in surrounding States. Kentucky was divided into seven flood regions. Total drainage area is used in the final regression equations as the sole explanatory variable, except in Regions 1 and 4 where main-channel slope also was used. The smallest average standard errors of prediction were in Region 3 (from -13.1 to +15.0 percent) and the largest average standard errors of prediction were in Region 5 (from -37.6 to +60.3 percent). One section of this report describes techniques for estimating peak flows for ungaged sites on gaged, unregulated streams in rural drainage basins. Another section references two previous U.S. Geological Survey reports for peak-flow estimates on ungaged, unregulated, urban streams. Estimating peak flows at ungaged sites on regulated streams is beyond the scope of this report, because peak flows on regulated streams are dependent upon variable human activities.

Developing a predictive tropospheric ozone model for Tabriz

NASA Astrophysics Data System (ADS)

Khatibi, Rahman; Naghipour, Leila; Ghorbani, Mohammad A.; Smith, Michael S.; Karimi, Vahid; Farhoudi, Reza; Delafrouz, Hadi; Arvanaghi, Hadi

2013-04-01

Predictive ozone models are becoming indispensable tools by providing a capability for pollution alerts to serve people who are vulnerable to the risks. We have developed a tropospheric ozone prediction capability for Tabriz, Iran, by using the following five modeling strategies: three regression-type methods: Multiple Linear Regression (MLR), Artificial Neural Networks (ANNs), and Gene Expression Programming (GEP); and two auto-regression-type models: Nonlinear Local Prediction (NLP) to implement chaos theory and Auto-Regressive Integrated Moving Average (ARIMA) models. The regression-type modeling strategies explain the data in terms of: temperature, solar radiation, dew point temperature, and wind speed, by regressing present ozone values to their past values. The ozone time series are available at various time intervals, including hourly intervals, from August 2010 to March 2011. The results for MLR, ANN and GEP models are not overly good but those produced by NLP and ARIMA are promising for the establishing a forecasting capability.

Lesion location associated with balance recovery and gait velocity change after rehabilitation in stroke patients.

PubMed

Moon, Hyun Im; Lee, Hyo Jeong; Yoon, Seo Yeon

2017-06-01

Impaired gait function after stroke contributes strongly to overall patient disability. However, the response to rehabilitation varies between individuals. The aims of this study were to identify predictors of gait velocity change and to elucidate lesion location associated with change of balance and gait function. We reviewed 102 stroke patients. The patients were divided into two groups according to gait ability post-rehabilitation, and we analyzed differences in their characteristics, such as demographic information, lesion factors, and initial balance function. Multivariate regression analyses were performed to examine the predictors of rehabilitation response. Lesion location and volume were measured on brain magnetic resonance images. We generated statistical maps of the lesions related to functional gains in gait and balance using voxel-based lesion symptom mapping (VLSM). The group of patients who regained independent ambulation function showed a smaller lesion size, a shorter duration from stroke onset, and higher initial balance function. In the regression model, gait velocity changes were predicted with the initial Berg balance scale (BBS) and duration post-onset. Absolute BBS changes were also correlated with the duration post-onset and initial BBS, and relative BBS changes were predicted by the baseline BBS. Using VLSM, lesion locations associated with gait velocity changes and balance adjusting for other factors were the insula, internal capsule, and adjacent white matter. Initial balance function as well as the interval between stroke onset and the initiation of therapy might influence balance recovery and gait velocity changes. Damage to the insula and internal capsule also affected gait velocity change after rehabilitation.

African Ancestry Analysis and Admixture Genetic Mapping for Proliferative Diabetic Retinopathy in African Americans.

PubMed

Tandon, Arti; Chen, Ching J; Penman, Alan; Hancock, Heather; James, Maurice; Husain, Deeba; Andreoli, Christopher; Li, Xiaohui; Kuo, Jane Z; Idowu, Omolola; Riche, Daniel; Papavasilieou, Evangelia; Brauner, Stacey; Smith, Sataria O; Hoadley, Suzanne; Richardson, Cole; Kieser, Troy; Vazquez, Vanessa; Chi, Cheryl; Fernandez, Marlene; Harden, Maegan; Cotch, Mary Frances; Siscovick, David; Taylor, Herman A; Wilson, James G; Reich, David; Wong, Tien Y; Klein, Ronald; Klein, Barbara E K; Rotter, Jerome I; Patterson, Nick; Sobrin, Lucia

2015-06-01

To examine the relationship between proportion of African ancestry (PAA) and proliferative diabetic retinopathy (PDR) and to identify genetic loci associated with PDR using admixture mapping in African Americans with type 2 diabetes (T2D). Between 1993 and 2013, 1440 participants enrolled in four different studies had fundus photographs graded using the Early Treatment Diabetic Retinopathy Study scale. Cases (n = 305) had PDR while controls (n = 1135) had nonproliferative diabetic retinopathy (DR) or no DR. Covariates included diabetes duration, hemoglobin A1C, systolic blood pressure, income, and education. Genotyping was performed on the Affymetrix platform. The association between PAA and PDR was evaluated using logistic regression. Genome-wide admixture scanning was performed using ANCESTRYMAP software. In the univariate analysis, PDR was associated with increased PAA (odds ratio [OR] = 1.36, 95% confidence interval [CI] = 1.16-1.59, P = 0.0002). In multivariate regression adjusting for traditional DR risk factors, income and education, the association between PAA and PDR was attenuated and no longer significant (OR = 1.21, 95% CI = 0.59-2.47, P = 0.61). For the admixture analyses, the maximum genome-wide score was 1.44 on chromosome 1. In this largest study of PDR in African Americans with T2D to date, an association between PAA and PDR is not present after adjustment for clinical, demographic, and socioeconomic factors. No genome-wide significant locus (defined as having a locus-genome statistic > 5) was identified with admixture analysis. Further analyses with even larger sample sizes are needed to definitively assess if any admixture signal for DR is present.

Mapping lichen color-groups in western Arctic Alaska using seasonal Landsat composites

NASA Astrophysics Data System (ADS)

Nelson, P.; Macander, M. J.; Swingley, C. S.

2016-12-01

Mapping lichens at a landscape scale has received increased recent interest due to fears that terricolous lichen mats, primary winter caribou forage, may be decreasing across the arctic and boreal zones. However, previous efforts have produced taxonomically coarse, total lichen cover maps or have covered relatively small spatial extents. Here we attempt to map lichens of differing colors as species proxies across northwestern Alaska to produce the finest taxonomic and spatial- grained lichen maps covering the largest spatial extent to date. Lichen community sampling in five western Alaskan National Parks and Preserves from 2007-2012 generated 328 FIA-style 34.7 m radius plots on which species-level macrolichen community structure and abundance was estimated. Species were coded by color and plot lichen cover was aggregated by plot as the sum of the cover of each species in a color group. Ten different lichen color groupings were used for modeling to deduce which colors were most detectable. Reflectance signatures of each plot were extracted from a series of Landsat composites (circa 2000-2010) partitioned into two-week intervals from June 1 to Sept. 15. Median reflectance values for each band in each pixel were selected based on filtering criteria to reduce likelihood of snow cover. Lichen color group cover was regressed against plot reflectance plus additional abiotic predictors in two different data mining algorithms. Brown and grey lichens had the best models explaining approximately 40% of lichen cover in those color groups. Both data mining techniques produced similarly good fitting models. Spatial patterns of lichen color-group cover show distinctly different ecological patterns of these color-group species proxies.

Preliminary Mapping of the Western Corn Rootworm (Diabrotica virgifera virgifera) Genome and Quantitative Trait Locus (QTL) Interval Mapping for Growth

USDA-ARS?s Scientific Manuscript database

Preliminary investigations into the organization of the western corn rootworm (Diabrotica virgifera virgifera; WCR) genome have resulted in low to moderate density gender-specific maps constructed from progeny of a backcrossed, short-diapause WCR family. Maps were based upon variation at microsatel...

Monitoring the dynamics of surface water fraction from MODIS time series in a Mediterranean environment

NASA Astrophysics Data System (ADS)

Li, Linlin; Vrieling, Anton; Skidmore, Andrew; Wang, Tiejun; Turak, Eren

2018-04-01

Detailed spatial information of changes in surface water extent is needed for water management and biodiversity conservation, particularly in drier parts of the globe where small, temporally-variant wetlands prevail. Although global surface water histories are now generated from 30 m Landsat data, for many locations they contain large temporal gaps particularly for longer periods (>10 years) due to revisit intervals and cloud cover. Daily Moderate Resolution Imaging Spectrometer (MODIS) imagery has potential to fill such gaps, but its relatively coarse spatial resolution may not detect small water bodies, which can be of great ecological importance. To address this problem, this study proposes and tests options for estimating the surface water fraction from MODIS 16-day 500 m Bidirectional Reflectance Distribution Function (BRDF) corrected surface reflectance image composites. The spatial extent of two Landsat tiles over Spain were selected as test areas. We obtained a 500 m reference dataset on surface water fraction by spatially aggregating 30 m binary water masks obtained from the Landsat-derived C-version of Function of Mask (CFmask), which themselves were evaluated against high-resolution Google Earth imagery. Twelve regression tree models were developed with two approaches, Random Forest and Cubist, using spectral metrics derived from MODIS data and topographic parameters generated from a 30 m spatial resolution digital elevation model. Results showed that accuracies were higher when we included annual summary statistics of the spectral metrics as predictor variables. Models trained on a single Landsat tile were ineffective in mapping surface water in the other tile, but global models trained with environmental conditions from both tiles can provide accurate results for both study areas. We achieved the highest accuracy with Cubist global model (R2 = 0.91, RMSE = 11.05%, MAE = 7.67%). Our method was not only effective for mapping permanent water fraction, but also in accurately capturing temporal fluctuations of surface water. Based on this good performance, we produced surface water fraction maps at 16-day interval for the 2000-2015 MODIS archive. Our approach is promising for monitoring surface water fraction at high frequency time intervals over much larger regions provided that training data are collected across the spatial domain for which the model will be applied.

Forest type mapping of the Interior West

Treesearch

Bonnie Ruefenacht; Gretchen G. Moisen; Jock A. Blackard

2004-01-01

This paper develops techniques for the mapping of forest types in Arizona, New Mexico, and Wyoming. The methods involve regression-tree modeling using a variety of remote sensing and GIS layers along with Forest Inventory Analysis (FIA) point data. Regression-tree modeling is a fast and efficient technique of estimating variables for large data sets with high accuracy...

Mapping of a dominant rust resistance gene revealed two R genes around the major Rust_QTL in cultivated peanut (Arachis hypogaea L.).

PubMed

Mondal, Suvendu; Badigannavar, Anand M

2018-05-09

A consensus rust QTL was identified within a 1.25 cM map interval of A03 chromosome in cultivated peanut. This map interval contains a TIR-NB-LRR R gene and four pathogenesis-related genes. Disease resistance in plants is manifested due to the specific interaction between the R gene product and its cognate avirulence gene product (AVR) in the pathogen. Puccinia arachidis Speg. causes rust disease and inflicts economic damages to peanut. Till now, no experimental evidence is known for the action of R gene in peanut for rust resistance. A fine mapping approach towards the development of closely linked markers for rust resistance gene was undertaken in this study. Phenotyping of an RIL population at five environments for field rust score and subsequent QTL analysis has identified a 1.25 cM map interval that harbored a consensus major Rust_QTL in A03 chromosome. This Rust_QTL is flanked by two SSR markers: FRS72 and SSR_GO340445. Both the markers clearly identified strong association of the mapped region with rust reaction in both resistant and susceptible genotypes from a collection of 95 cultivated peanut germplasm. This 1.25 cM map interval contained 331.7 kb in the physical map of A. duranensis and had a TIR-NB-LRR category R gene (Aradu.Z87JB) and four glucan endo-1,3 β glucosidase genes (Aradu.RKA6 M, Aradu.T44NR, Aradu.IWV86 and Aradu.VG51Q). Another resistance gene analog was also found in the vicinity of mapped Rust_QTL. The sequence between SSR markers, FRS72 and FRS49, contains an LRR-PK (Aradu.JG217) which is equivalent to RHG4 in soybean. Probably, the protein kinase domain in AhRHG4 acts as an integrated decoy for the cognate AVR from Puccinia arachidis and helps the TIR-NB-LRR R-protein to initiate a controlled program cell death in resistant peanut plants.

Retrieval and Mapping of Heavy Metal Concentration in Soil Using Time Series Landsat 8 Imagery

NASA Astrophysics Data System (ADS)

Fang, Y.; Xu, L.; Peng, J.; Wang, H.; Wong, A.; Clausi, D. A.

2018-04-01

Heavy metal pollution is a critical global environmental problem which has always been a concern. Traditional approach to obtain heavy metal concentration relying on field sampling and lab testing is expensive and time consuming. Although many related studies use spectrometers data to build relational model between heavy metal concentration and spectra information, and then use the model to perform prediction using the hyperspectral imagery, this manner can hardly quickly and accurately map soil metal concentration of an area due to the discrepancies between spectrometers data and remote sensing imagery. Taking the advantage of easy accessibility of Landsat 8 data, this study utilizes Landsat 8 imagery to retrieve soil Cu concentration and mapping its distribution in the study area. To enlarge the spectral information for more accurate retrieval and mapping, 11 single date Landsat 8 imagery from 2013-2017 are selected to form a time series imagery. Three regression methods, partial least square regression (PLSR), artificial neural network (ANN) and support vector regression (SVR) are used to model construction. By comparing these models unbiasedly, the best model are selected to mapping Cu concentration distribution. The produced distribution map shows a good spatial autocorrelation and consistency with the mining area locations.

Collapse susceptibility mapping in karstified gypsum terrain (Sivas basin - Turkey) by conditional probability, logistic regression, artificial neural network models

NASA Astrophysics Data System (ADS)

Yilmaz, Isik; Keskin, Inan; Marschalko, Marian; Bednarik, Martin

2010-05-01

This study compares the GIS based collapse susceptibility mapping methods such as; conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) applied in gypsum rock masses in Sivas basin (Turkey). Digital Elevation Model (DEM) was first constructed using GIS software. Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index- TWI, stream power index- SPI, Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from CP, LR and ANN models, and they were then compared by means of their validations. Area Under Curve (AUC) values obtained from all three methodologies showed that the map obtained from ANN model looks like more accurate than the other models, and the results also showed that the artificial neural networks is a usefull tool in preparation of collapse susceptibility map and highly compatible with GIS operating features. Key words: Collapse; doline; susceptibility map; gypsum; GIS; conditional probability; logistic regression; artificial neural networks.

Mapping of the locus for autosomal dominant amelogenesis imperfecta (AIH2) to a 4-Mb YAC contig on chromosome 4q11-q21

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaerrman, C.; Holmgren, G.; Forsman, K.

1997-01-15

Amelogenesis imperfecta (Al) is a clinically and genetically heterogeneous group of inherited enamel defects. We recently mapped a locus for autosomal dominant local hypoplastic amelogenesis imperfecta (AIH2) to the long arm of chromosome 4. The disease gene was localized to a 17.6-cM region between the markers D4S392 and D4S395. The albumin gene (ALB), located in the same interval, was a candidate gene for autosomal dominant AI (ADAI) since albumin has a potential role in enamel maturation. Here we describe refined mapping of the AIH2 locus and the construction of marker maps by radiation hybrid mapping and yeast artificial chromosome (YAC)-basedmore » sequence tagged site-content mapping. A radiation hybrid map consisting of 11 microsatellite markers in the 5-cM interval between D4S409 and D4S1558 was constructed. Recombinant haplotypes in six Swedish ADAI families suggest that the disease gene is located in the interval between D4S2421 and ALB. ALB is therefore not likely to be the disease-causing gene. Affected members in all six families share the same allele haplotypes, indicating a common ancestral mutation in all families. The AIH2 critical region is less than 4 cM and spans a physical distance of approximately 4 Mb as judged from radiation hybrid maps. A YAC contig over the AIH2 critical region including several potential candidate genes was constructed. 35 refs., 4 figs., 1 tab.« less

Molecular mapping of chromosomes 17 and X

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barker, D.F.

1991-01-15

Progress toward the construction of high density genetic maps of chromosomes 17 and X has been made by isolating and characterizing a relatively large set of polymorphic probes for each chromosome and using these probes to construct genetic maps. We have mapped the same polymorphic probes against a series of chromosome breakpoints on X and 17. The probes could be assigned to over 30 physical intervals on the X chromosome and 7 intervals on 17. In many cases, this process resulted in improved characterization of the relative locations of the breakpoints with respect to each other and the definition ofmore » new physical intervals. The strategy for isolation of the polymorphic clones utilized chromosome specific libraries of 1--15 kb segments from each of the two chromosomes. From these libraries, clones were screened for those detecting restriction fragment length polymorphisms. The markers were further characterized, the chromosomal assignments confirmed and in most cases segments of the original probes were subcloned into plasmids to produce probes with improved signal to noise ratios for use in the genetic marker studies. The linkage studies utilize the CEPH reference families and other well-characterized families in our collection which have been used for genetic disease linkage work. Preliminary maps and maps of portions of specific regions of 17 and X are provided. We have nearly completed a map of the 1 megabase Mycoplasma arthritidis genome by applying these techniques to a lambda phage library of its genome. We have found bit mapping to be an efficient means to organize a contiguous set of overlapping clones from a larger genome.« less

Molecular mapping of chromosomes 17 and X. Progress report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barker, D.F.

1991-01-15

Progress toward the construction of high density genetic maps of chromosomes 17 and X has been made by isolating and characterizing a relatively large set of polymorphic probes for each chromosome and using these probes to construct genetic maps. We have mapped the same polymorphic probes against a series of chromosome breakpoints on X and 17. The probes could be assigned to over 30 physical intervals on the X chromosome and 7 intervals on 17. In many cases, this process resulted in improved characterization of the relative locations of the breakpoints with respect to each other and the definition ofmore » new physical intervals. The strategy for isolation of the polymorphic clones utilized chromosome specific libraries of 1--15 kb segments from each of the two chromosomes. From these libraries, clones were screened for those detecting restriction fragment length polymorphisms. The markers were further characterized, the chromosomal assignments confirmed and in most cases segments of the original probes were subcloned into plasmids to produce probes with improved signal to noise ratios for use in the genetic marker studies. The linkage studies utilize the CEPH reference families and other well-characterized families in our collection which have been used for genetic disease linkage work. Preliminary maps and maps of portions of specific regions of 17 and X are provided. We have nearly completed a map of the 1 megabase Mycoplasma arthritidis genome by applying these techniques to a lambda phage library of its genome. We have found bit mapping to be an efficient means to organize a contiguous set of overlapping@ clones from a larger genome.« less

Contactless magnetocardiographic mapping in anesthetized Wistar rats: evidence of age-related changes of cardiac electrical activity.

PubMed

Brisinda, Donatella; Caristo, Maria Emiliana; Fenici, Riccardo

2006-07-01

Magnetocardiography (MCG) is the recording of the magnetic field (MF) generated by cardiac electrophysiological activity. Because it is a contactless method, MCG is ideal for noninvasive cardiac mapping of small experimental animals. The aim of this study was to assess age-related changes of cardiac intervals and ventricular repolarization (VR) maps in intact rats by means of MCG mapping. Twenty-four adult Wistar rats (12 male and 12 female) were studied, under anesthesia, with the same unshielded 36-channel MCG instrumentation used for clinical recordings. Two sets of measurements were obtained from each animal: 1) at 5 mo of age (297.5 +/- 21 g body wt) and 2) at 14 mo of age (516.8 +/- 180 g body wt). RR and PR intervals, QRS segment, and QTpeak, QTend, JTpeak, JTend, and Tpeak-end were measured from MCG waveforms. MCG imaging was automatically obtained as MF maps and as inverse localization of cardiac sources with equivalent current dipole and effective magnetic dipole models. After 300 s of continuous recording were averaged, the signal-to-noise ratio was adequate for study of atrial and ventricular MF maps and for three-dimensional localization of the underlying cardiac sources. Clear-cut age-related differences in VR duration were demonstrated by significantly longer QTend, JTend, and Tpeak-end in older Wistar rats. Reproducible multisite noninvasive cardiac mapping of anesthetized rats is simpler with MCG methodology than with ECG recording. In addition, MCG mapping provides new information based on quantitative analysis of MF and equivalent sources. In this study, statistically significant age-dependent variations in VR intervals were found.

Active, capable, and potentially active faults - a paleoseismic perspective

USGS Publications Warehouse

Machette, M.N.

2000-01-01

Maps of faults (geologically defined source zones) may portray seismic hazards in a wide range of completeness depending on which types of faults are shown. Three fault terms - active, capable, and potential - are used in a variety of ways for different reasons or applications. Nevertheless, to be useful for seismic-hazards analysis, fault maps should encompass a time interval that includes several earthquake cycles. For example, if the common recurrence in an area is 20,000-50,000 years, then maps should include faults that are 50,000-100,000 years old (two to five typical earthquake cycles), thus allowing for temporal variability in slip rate and recurrence intervals. Conversely, in more active areas such as plate boundaries, maps showing faults that are <10,000 years old should include those with at least 2 to as many as 20 paleoearthquakes. For the International Lithosphere Programs' Task Group II-2 Project on Major Active Faults of the World our maps and database will show five age categories and four slip rate categories that allow one to select differing time spans and activity rates for seismic-hazard analysis depending on tectonic regime. The maps are accompanied by a database that describes evidence for Quaternary faulting, geomorphic expression, and paleoseismic parameters (slip rate, recurrence interval and time of most recent surface faulting). These maps and databases provide an inventory of faults that would be defined as active, capable, and potentially active for seismic-hazard assessments.

A gentle introduction to quantile regression for ecologists

USGS Publications Warehouse

Cade, B.S.; Noon, B.R.

2003-01-01

Quantile regression is a way to estimate the conditional quantiles of a response variable distribution in the linear model that provides a more complete view of possible causal relationships between variables in ecological processes. Typically, all the factors that affect ecological processes are not measured and included in the statistical models used to investigate relationships between variables associated with those processes. As a consequence, there may be a weak or no predictive relationship between the mean of the response variable (y) distribution and the measured predictive factors (X). Yet there may be stronger, useful predictive relationships with other parts of the response variable distribution. This primer relates quantile regression estimates to prediction intervals in parametric error distribution regression models (eg least squares), and discusses the ordering characteristics, interval nature, sampling variation, weighting, and interpretation of the estimates for homogeneous and heterogeneous regression models.

Atlas of interoccurrence intervals for selected thresholds of daily precipitation in Texas

USGS Publications Warehouse

Asquith, William H.; Roussel, Meghan C.

2003-01-01

A Poisson process model is used to define the distribution of interoccurrence intervals of daily precipitation in Texas. A precipitation interoccurrence interval is the time period between two successive rainfall events. Rainfall events are defined as daily precipitation equaling or exceeding a specified depth threshold. Ten precipitation thresholds are considered: 0.05, 0.10, 0.25, 0.50, 0.75, 1.0, 1.5, 2.0, 2.5, and 3.0 inches. Site-specific mean interoccurrence interval and ancillary statistics are presented for each threshold and for each of 1,306 National Weather Service daily precipitation gages. Maps depicting the spatial variation across Texas of the mean interoccurrence interval for each threshold are presented. The percent change from the statewide standard deviation of the interoccurrence intervals to the root-mean-square error ranges from a magnitude minimum of (negative) -24 to a magnitude maximum of -60 percent for the 0.05- and 2.0-inch thresholds, respectively. Because of the substantial negative percent change, the maps are considered more reliable estimators of the mean interoccurrence interval for most locations in Texas than the statewide mean values.

A reconnaissance method for delineation of tracts for regional-scale mineral-resource assessment based on geologic-map data

USGS Publications Warehouse

Raines, G.L.; Mihalasky, M.J.

2002-01-01

The U.S. Geological Survey (USGS) is proposing to conduct a global mineral-resource assessment using geologic maps, significant deposits, and exploration history as minimal data requirements. Using a geologic map and locations of significant pluton-related deposits, the pluton-related-deposit tract maps from the USGS national mineral-resource assessment have been reproduced with GIS-based analysis and modeling techniques. Agreement, kappa, and Jaccard's C correlation statistics between the expert USGS and calculated tract maps of 87%, 40%, and 28%, respectively, have been achieved using a combination of weights-of-evidence and weighted logistic regression methods. Between the experts' and calculated maps, the ranking of states measured by total permissive area correlates at 84%. The disagreement between the experts and calculated results can be explained primarily by tracts defined by geophysical evidence not considered in the calculations, generalization of tracts by the experts, differences in map scales, and the experts' inclusion of large tracts that are arguably not permissive. This analysis shows that tracts for regional mineral-resource assessment approximating those delineated by USGS experts can be calculated using weights of evidence and weighted logistic regression, a geologic map, and the location of significant deposits. Weights of evidence and weighted logistic regression applied to a global geologic map could provide quickly a useful reconnaissance definition of tracts for mineral assessment that is tied to the data and is reproducible. ?? 2002 International Association for Mathematical Geology.

The role of human and mouse Y chromosome genes in male infertility.

PubMed

Affara, N A; Mitchell, M J

2000-11-01

It was suggested by Ronald Fisher in 1931 that genes involved in benefit to the male (including spermatogenesis genes) would accumulate on the Y chromosome. The analysis of mouse Y chromosome deletions and the discovery of microdeletions of the human Y chromosome associated with diverse defective spermatogenic phenotypes has revealed the presence of intervals containing one or more genes controlling male germ cell differentiation. These intervals have been mapped, cloned and examined in detail for functional genes. This review discusses the genes mapping to critical spermatogenesis intervals and the evidence indicating which are the most likely candidates underlying Y-linked male infertility.

Genetic mapping and QTL analysis for body weight in Jian carp ( Cyprinus carpio var. Jian) compared with mirror carp ( Cyprinus carpio L.)

NASA Astrophysics Data System (ADS)

Gu, Ying; Lu, Cuiyun; Zhang, Xiaofeng; Li, Chao; Yu, Juhua; Sun, Xiaowen

2015-05-01

We report the genetic linkage map of Jian carp ( Cyprinus carpio var. Jian). An F1 population comprising 94 Jian carp individuals was mapped using 254 microsatellite markers. The genetic map spanned 1 381.592 cM and comprised 44 linkage groups, with an average marker distance of 6.58 cM. We identified eight quantitative trait loci (QTLs) for body weight (BW) in seven linkage groups, explaining 12.6% to 17.3% of the phenotypic variance. Comparative mapping was performed between Jian carp and mirror carp ( Cyprinus carpio L.), which both have 50 chromosomes. One hundred and ninety-eight Jian carp marker loci were found in common with the mirror carp map, with 186 (93.94%) showing synteny. All 44 Jian carp linkage groups could be one-to-one aligned to the 44 mirror carp linkage groups, mostly sharing two or more common loci. Three QTLs for BW in Jian carp were conserved in mirror carp. QTL comparison suggested that the QTL confidence interval in mirror carp was more precise than the homologous interval in Jian carp, which was contained within the QTL interval in Jian carp. The syntenic relationship and consensus QTLs between the two varieties provide a foundation for genomic research and genetic breeding in common carp.

Improving estimates of streamflow characteristics using LANDSAT-1 (ERTS-1) imagery. [Delmarva Peninsula

NASA Technical Reports Server (NTRS)

Hollyday, E. F. (Principal Investigator)

1975-01-01

The author has identified the following significant results. Streamflow characteristics in the Delmarva Peninsula derived from the records of daily discharge of 20 gaged basins are representative of the full range in flow conditions and include all of those commonly used for design or planning purposes. They include annual flood peaks with recurrence intervals of 2, 5, 10, 25, and 50 years, mean annual discharge, standard deviation of the mean annual discharge, mean monthly discharges, standard deviation of the mean monthly discharges, low-flow characteristics, flood volume characteristics, and the discharge equalled or exceeded 50 percent of the time. Streamflow and basin characteristics were related by a technique of multiple regression using a digital computer. A control group of equations was computed using basin characteristics derived from maps and climatological records. An experimental group of equations was computed using basin characteristics derived from LANDSAT imagery as well as from maps and climatological records. Based on a reduction in standard error of estimate equal to or greater than 10 percent, the equations for 12 stream flow characteristics were substantially improved by adding to the analyses basin characteristics derived from LANDSAT imagery.

Associations between Mycobacterium paratuberculosis sero-status, milk quality parameters, and reproduction in dairy cows.

PubMed

Pesqueira, María N; Factor, Camino; Mato, Ivan; Sanjuán, María L; Macias, Laura; Eiras, Carmen; Arnaiz, Ignacio; Camino, Fernando; Yus, Eduardo; Diéguez, Francisco J

2015-01-01

The objective of this study was to investigate the influence of Mycobocterium avium subsp. paratuberculosis (MAP) sero-status of dairy cows on different milk production variables and reproductive traits. The study was carried out on 40 herds from the region of Galicia (North-West Spain). These herds were randomly selected from a larger group that had taken part in a voluntary paratuberculosis control program since 2005, which involves regular serum sampling of every adult animal to run antibody-ELISA tests. Milk production and reproductive data were obtained from the "Dairy Herd Improvement Program (DHIP) of Galicia". All the gathered data were processed following a linear regression model. Results indicated that there was no significant effect of MAP sero-status on individual milk production variables. However, a significant difference was observed at the calving-to-first-insemination interval, with an average increase of 14 days in positive animals compared to negatives. It has to be taken into consideration that the paratuberculosis status was only defined by the serological status. Since para tb-infected animals may have antbodies or may not, para tb-positive animals can also be included in the sero-negative group of animals, which may bias the results.

Predictive landslide susceptibility mapping using spatial information in the Pechabun area of Thailand

NASA Astrophysics Data System (ADS)

Oh, Hyun-Joo; Lee, Saro; Chotikasathien, Wisut; Kim, Chang Hwan; Kwon, Ju Hyoung

2009-04-01

For predictive landslide susceptibility mapping, this study applied and verified probability model, the frequency ratio and statistical model, logistic regression at Pechabun, Thailand, using a geographic information system (GIS) and remote sensing. Landslide locations were identified in the study area from interpretation of aerial photographs and field surveys, and maps of the topography, geology and land cover were constructed to spatial database. The factors that influence landslide occurrence, such as slope gradient, slope aspect and curvature of topography and distance from drainage were calculated from the topographic database. Lithology and distance from fault were extracted and calculated from the geology database. Land cover was classified from Landsat TM satellite image. The frequency ratio and logistic regression coefficient were overlaid for landslide susceptibility mapping as each factor’s ratings. Then the landslide susceptibility map was verified and compared using the existing landslide location. As the verification results, the frequency ratio model showed 76.39% and logistic regression model showed 70.42% in prediction accuracy. The method can be used to reduce hazards associated with landslides and to plan land cover.

Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia

NASA Astrophysics Data System (ADS)

Pradhan, Biswajeet

2010-05-01

This paper presents the results of the cross-validation of a multivariate logistic regression model using remote sensing data and GIS for landslide hazard analysis on the Penang, Cameron, and Selangor areas in Malaysia. Landslide locations in the study areas were identified by interpreting aerial photographs and satellite images, supported by field surveys. SPOT 5 and Landsat TM satellite imagery were used to map landcover and vegetation index, respectively. Maps of topography, soil type, lineaments and land cover were constructed from the spatial datasets. Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed. Then the landslide hazard was analysed using the multivariate logistic regression coefficients derived not only from the data for the respective area but also using the logistic regression coefficients calculated from each of the other two areas (nine hazard maps in all) as a cross-validation of the model. For verification of the model, the results of the analyses were then compared with the field-verified landslide locations. Among the three cases of the application of logistic regression coefficient in the same study area, the case of Selangor based on the Selangor logistic regression coefficients showed the highest accuracy (94%), where as Penang based on the Penang coefficients showed the lowest accuracy (86%). Similarly, among the six cases from the cross application of logistic regression coefficient in other two areas, the case of Selangor based on logistic coefficient of Cameron showed highest (90%) prediction accuracy where as the case of Penang based on the Selangor logistic regression coefficients showed the lowest accuracy (79%). Qualitatively, the cross application model yields reasonable results which can be used for preliminary landslide hazard mapping.

Sequential Processing and the Matching-Stimulus Interval Effect in ERP Components: An Exploration of the Mechanism Using Multiple Regression

PubMed Central

Steiner, Genevieve Z.; Barry, Robert J.; Gonsalvez, Craig J.

2016-01-01

In oddball tasks, increasing the time between stimuli within a particular condition (target-to-target interval, TTI; nontarget-to-nontarget interval, NNI) systematically enhances N1, P2, and P300 event-related potential (ERP) component amplitudes. This study examined the mechanism underpinning these effects in ERP components recorded from 28 adults who completed a conventional three-tone oddball task. Bivariate correlations, partial correlations and multiple regression explored component changes due to preceding ERP component amplitudes and intervals found within the stimulus series, rather than constraining the task with experimentally constructed intervals, which has been adequately explored in prior studies. Multiple regression showed that for targets, N1 and TTI predicted N2, TTI predicted P3a and P3b, and Processing Negativity (PN), P3b, and TTI predicted reaction time. For rare nontargets, P1 predicted N1, NNI predicted N2, and N1 predicted Slow Wave (SW). Findings show that the mechanism is operating on separate stages of stimulus-processing, suggestive of either increased activation within a number of stimulus-specific pathways, or very long component generator recovery cycles. These results demonstrate the extent to which matching-stimulus intervals influence ERP component amplitudes and behavior in a three-tone oddball task, and should be taken into account when designing similar studies. PMID:27445774

Sequential Processing and the Matching-Stimulus Interval Effect in ERP Components: An Exploration of the Mechanism Using Multiple Regression.

PubMed

Steiner, Genevieve Z; Barry, Robert J; Gonsalvez, Craig J

2016-01-01

In oddball tasks, increasing the time between stimuli within a particular condition (target-to-target interval, TTI; nontarget-to-nontarget interval, NNI) systematically enhances N1, P2, and P300 event-related potential (ERP) component amplitudes. This study examined the mechanism underpinning these effects in ERP components recorded from 28 adults who completed a conventional three-tone oddball task. Bivariate correlations, partial correlations and multiple regression explored component changes due to preceding ERP component amplitudes and intervals found within the stimulus series, rather than constraining the task with experimentally constructed intervals, which has been adequately explored in prior studies. Multiple regression showed that for targets, N1 and TTI predicted N2, TTI predicted P3a and P3b, and Processing Negativity (PN), P3b, and TTI predicted reaction time. For rare nontargets, P1 predicted N1, NNI predicted N2, and N1 predicted Slow Wave (SW). Findings show that the mechanism is operating on separate stages of stimulus-processing, suggestive of either increased activation within a number of stimulus-specific pathways, or very long component generator recovery cycles. These results demonstrate the extent to which matching-stimulus intervals influence ERP component amplitudes and behavior in a three-tone oddball task, and should be taken into account when designing similar studies.

An ultra-high-density bin map facilitates high-throughput QTL mapping of horticultural traits in pepper (Capsicum annuum).

PubMed

Han, Koeun; Jeong, Hee-Jin; Yang, Hee-Bum; Kang, Sung-Min; Kwon, Jin-Kyung; Kim, Seungill; Choi, Doil; Kang, Byoung-Cheorl

2016-04-01

Most agricultural traits are controlled by quantitative trait loci (QTLs); however, there are few studies on QTL mapping of horticultural traits in pepper (Capsicum spp.) due to the lack of high-density molecular maps and the sequence information. In this study, an ultra-high-density map and 120 recombinant inbred lines (RILs) derived from a cross between C. annuum'Perennial' and C. annuum'Dempsey' were used for QTL mapping of horticultural traits. Parental lines and RILs were resequenced at 18× and 1× coverage, respectively. Using a sliding window approach, an ultra-high-density bin map containing 2,578 bins was constructed. The total map length of the map was 1,372 cM, and the average interval between bins was 0.53 cM. A total of 86 significant QTLs controlling 17 horticultural traits were detected. Among these, 32 QTLs controlling 13 traits were major QTLs. Our research shows that the construction of bin maps using low-coverage sequence is a powerful method for QTL mapping, and that the short intervals between bins are helpful for fine-mapping of QTLs. Furthermore, bin maps can be used to improve the quality of reference genomes by elucidating the genetic order of unordered regions and anchoring unassigned scaffolds to linkage groups. © The Author 2016. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Approximating prediction uncertainty for random forest regression models

Treesearch

John W. Coulston; Christine E. Blinn; Valerie A. Thomas; Randolph H. Wynne

2016-01-01

Machine learning approaches such as random forest have increased for the spatial modeling and mapping of continuous variables. Random forest is a non-parametric ensemble approach, and unlike traditional regression approaches there is no direct quantification of prediction error. Understanding prediction uncertainty is important when using model-based continuous maps as...

Construction of High-Density Genetic Linkage Maps and Mapping of Growth-Related Quantitative Trail Loci in the Japanese Flounder (Paralichthys olivaceus)

PubMed Central

Niu, Yuze; Gao, Fengtao; Zhao, Yongwei; Zhang, Jing; Sun, Jian; Shao, Changwei; Liao, Xiaolin; Wang, Lei; Tian, Yongsheng; Chen, Songlin

2012-01-01

High-density genetic linkage maps were constructed for the Japanese flounder (Paralichthys olivaceus). A total of 1624 microsatellite markers were polymorphic in the reference family. Linkage analysis using JoinMap 4.0 resulted in the mapping of 1487 markers to 24 linkage groups, a result which was consistent with the 24 chromosomes seen in chromosome spreads. The female map was composed of 1257 markers, covering a total of 1663.8 cM with an average interval 1.35 cM between markers. The male map consisted of 1224 markers, spanning 1726.5 cM, with an average interval of 1.44 cM. The genome length in the Japanese flounder was estimated to be 1730.3 cM for the females and 1798.0 cM for the males, a coverage of 96.2% for the female and 96.0% for the male map. The mean recombination at common intervals throughout the genome revealed a slight difference between sexes, i.e. 1.07 times higher in the male than female. High-density genetic linkage maps are very useful for marker-assisted selection (MAS) programs for economically valuable traits in this species and for further evolutionary studies in flatfish and vertebrate species. Furthermore, four quantiative trait loci (QTL) associated with growth traits were mapped on the genetic map. One QTL was identified for body weight on LG 14 f, which explained 14.85% of the total variation of the body weight. Three QTL were identified for body width on LG14f and LG14m, accounting for 16.75%, 13.62% and 13.65% of the total variation in body width, respectively. The additive effects were evident as negative values. There were four QTL for growth traits clustered on LG14, which should prove to be very useful for improving growth traits using molecular MAS. PMID:23209734

A novel candidate gene for mouse and human preaxial polydactyly with altered expression in limbs of Hemimelic extra-toes mutant mice.

PubMed

Clark, R M; Marker, P C; Kingsley, D M

2000-07-01

Polydactyly is a common malformation of vertebrate limbs. In humans a major locus for nonsyndromic pre-axial polydactyly (PPD) has been mapped previously to 7q36. The mouse Hemimelic extra-toes (Hx) mutation maps to a homologous chromosome segment and has been proposed to affect a homologous gene. To understand the molecular changes underlying PPD, we used a positional cloning approach to identify the gene or genes disrupted by the Hx mutation and a closely linked limb mutation, Hammertoe (Hm). High resolution genetic mapping identified a small candidate interval for the mouse mutations located 1.2 cM distal to the Shh locus. The nonrecombinant interval was completely cloned in bacterial artificial chromosomes and searched for genes using a combination of exon trapping, sample sequencing, and mapping of known genes. Two novel genes, Lmbr1 and Lmbr2, are entirely within the candidate interval we defined genetically. The open reading frame of both genes is intact in mutant mice, but the expression of the Lmbr1 gene is dramatically altered in developing limbs of Hx mutant mice. The correspondence between the spatial and temporal changes in Lmbr1 expression and the embryonic onset of the Hx mutant phenotype suggests that the mouse Hx mutation may be a regulatory allele of Lmbr1. The human ortholog of Lmbr1 maps within the recently described interval for human PPD, strengthening the possibility that both mouse and human limb abnormalities are due to defects in the same highly conserved gene.

PMICALC: an R code-based software for estimating post-mortem interval (PMI) compatible with Windows, Mac and Linux operating systems.

PubMed

Muñoz-Barús, José I; Rodríguez-Calvo, María Sol; Suárez-Peñaranda, José M; Vieira, Duarte N; Cadarso-Suárez, Carmen; Febrero-Bande, Manuel

2010-01-30

In legal medicine the correct determination of the time of death is of utmost importance. Recent advances in estimating post-mortem interval (PMI) have made use of vitreous humour chemistry in conjunction with Linear Regression, but the results are questionable. In this paper we present PMICALC, an R code-based freeware package which estimates PMI in cadavers of recent death by measuring the concentrations of potassium ([K+]), hypoxanthine ([Hx]) and urea ([U]) in the vitreous humor using two different regression models: Additive Models (AM) and Support Vector Machine (SVM), which offer more flexibility than the previously used Linear Regression. The results from both models are better than those published to date and can give numerical expression of PMI with confidence intervals and graphic support within 20 min. The program also takes into account the cause of death. 2009 Elsevier Ireland Ltd. All rights reserved.

Random Forests (RFs) for Estimation, Uncertainty Prediction and Interpretation of Monthly Solar Potential

NASA Astrophysics Data System (ADS)

Assouline, Dan; Mohajeri, Nahid; Scartezzini, Jean-Louis

2017-04-01

Solar energy is clean, widely available, and arguably the most promising renewable energy resource. Taking full advantage of solar power, however, requires a deep understanding of its patterns and dependencies in space and time. The recent advances in Machine Learning brought powerful algorithms to estimate the spatio-temporal variations of solar irradiance (the power per unit area received from the Sun, W/m2), using local weather and terrain information. Such algorithms include Deep Learning (e.g. Artificial Neural Networks), or kernel methods (e.g. Support Vector Machines). However, most of these methods have some disadvantages, as they: (i) are complex to tune, (ii) are mainly used as a black box and offering no interpretation on the variables contributions, (iii) often do not provide uncertainty predictions (Assouline et al., 2016). To provide a reasonable solar mapping with good accuracy, these gaps would ideally need to be filled. We present here simple steps using one ensemble learning algorithm namely, Random Forests (Breiman, 2001) to (i) estimate monthly solar potential with good accuracy, (ii) provide information on the contribution of each feature in the estimation, and (iii) offer prediction intervals for each point estimate. We have selected Switzerland as an example. Using a Digital Elevation Model (DEM) along with monthly solar irradiance time series and weather data, we build monthly solar maps for Global Horizontal Irradiance (GHI), Diffuse Horizontal Irradiance (GHI), and Extraterrestrial Irradiance (EI). The weather data include monthly values for temperature, precipitation, sunshine duration, and cloud cover. In order to explain the impact of each feature on the solar irradiance of each point estimate, we extend the contribution method (Kuz'min et al., 2011) to a regression setting. Contribution maps for all features can then be computed for each solar map. This provides precious information on the spatial variation of the features impact all across Switzerland maps. Finally, as RFs are based on bootstrap samples of the training data, they can produce prediction intervals by looking at the trees estimates distribution, instead of taking the mean estimate. To do so, a simple idea is to grow all trees fully so that each leaf has exactly one value, that is, a training sample value. Then, for each point estimate, we compute percentiles of the trees estimates data to build a prediction interval. Two issues arise from this process: (i) growing the trees fully is not always possible, and (ii) there is a risk of over-fitting. We show how to solve them. These steps can be used for any type of environmental mapping so as to extract useful information on uncertainty and feature impact interpretation. References -Assouline, D., Mohajeri, N., & Scartezzini, J. L. (2017). Quantifying rooftop photovoltaic solar energy potential: A machine learning approach. Solar Energy, 141, 278-296. -Breiman, L. (2001). Random forests. Machine learning, 45(1), 5-32. -Kuz'min, V. E., Polishchuk, P. G., Artemenko, A. G., & Andronati, S. A. (2011). Interpretation of QSAR models based on random forest methods. Molecular Informatics, 30(6-7), 593-603.

Optical mapping and its potential for large-scale sequencing projects.

PubMed

Aston, C; Mishra, B; Schwartz, D C

1999-07-01

Physical mapping has been rediscovered as an important component of large-scale sequencing projects. Restriction maps provide landmark sequences at defined intervals, and high-resolution restriction maps can be assembled from ensembles of single molecules by optical means. Such optical maps can be constructed from both large-insert clones and genomic DNA, and are used as a scaffold for accurately aligning sequence contigs generated by shotgun sequencing.

Decomposition Technique for Remaining Useful Life Prediction

NASA Technical Reports Server (NTRS)

Saha, Bhaskar (Inventor); Goebel, Kai F. (Inventor); Saxena, Abhinav (Inventor); Celaya, Jose R. (Inventor)

2014-01-01

The prognostic tool disclosed here decomposes the problem of estimating the remaining useful life (RUL) of a component or sub-system into two separate regression problems: the feature-to-damage mapping and the operational conditions-to-damage-rate mapping. These maps are initially generated in off-line mode. One or more regression algorithms are used to generate each of these maps from measurements (and features derived from these), operational conditions, and ground truth information. This decomposition technique allows for the explicit quantification and management of different sources of uncertainty present in the process. Next, the maps are used in an on-line mode where run-time data (sensor measurements and operational conditions) are used in conjunction with the maps generated in off-line mode to estimate both current damage state as well as future damage accumulation. Remaining life is computed by subtracting the instance when the extrapolated damage reaches the failure threshold from the instance when the prediction is made.

Systolic time interval v heart rate regression equations using atropine: reproducibility studies.

PubMed Central

Kelman, A W; Sumner, D J; Whiting, B

1981-01-01

1. Systolic time intervals (STI) were recorded in six normal male subjects over a period of 3 weeks. On one day per week, each subject received incremental doses of atropine intravenously to increase heart rate, allowing the determination of individual STI v HR regression equations. On the other days STI were recorded with the subjects resting, in the supine position. 2. There were highly significant regression relationships between heart rate and both LVET and QS2, but not between heart rate and PEP. 3. The regression relationships showed little intra-subject variability, but a large degree of inter-subject variability: they proved adequate to correct the STI for the daily fluctuations in heart rate. 4. Administration of small doses of atropine intravenously provides a satisfactory and convenient method of deriving individual STI v HR regression equations which can be applied over a period of weeks. PMID:7248136

Systolic time interval v heart rate regression equations using atropine: reproducibility studies.

PubMed

Kelman, A W; Sumner, D J; Whiting, B

1981-07-01

1. Systolic time intervals (STI) were recorded in six normal male subjects over a period of 3 weeks. On one day per week, each subject received incremental doses of atropine intravenously to increase heart rate, allowing the determination of individual STI v HR regression equations. On the other days STI were recorded with the subjects resting, in the supine position. 2. There were highly significant regression relationships between heart rate and both LVET and QS2, but not between heart rate and PEP. 3. The regression relationships showed little intra-subject variability, but a large degree of inter-subject variability: they proved adequate to correct the STI for the daily fluctuations in heart rate. 4. Administration of small doses of atropine intravenously provides a satisfactory and convenient method of deriving individual STI v HR regression equations which can be applied over a period of weeks.

High-resolution genetic linkage mapping, high-temperature tolerance and growth-related quantitative trait locus (QTL) identification in Marsupenaeus japonicus.

PubMed

Lu, Xia; Luan, Sheng; Hu, Long Yang; Mao, Yong; Tao, Ye; Zhong, Sheng Ping; Kong, Jie

2016-06-01

The Kuruma prawn, Marsupenaeus japonicus, is one of the most promising marine invertebrates in the industry in Asia, Europe and Australia. However, the increasing global temperatures result in considerable economic losses in M. japonicus farming. In the present study, to select genetically improved animals for the sustainable development of the Kuruma prawn industry, a high-resolution genetic linkage map and quantitative trait locus (QTL) identification were performed using the RAD technology. The maternal map contained 5849 SNP markers and spanned 3127.23 cM, with an average marker interval of 0.535 cM. Instead, the paternal map contained 3927 SNP markers and spanned 3326.19 cM, with an average marker interval of 0.847 cM. The consensus map contained 9289 SNP markers and spanned 3610.90 cM, with an average marker interval of 0.388 cM and coverage of 99.06 % of the genome. The markers were grouped into 41 linkage groups in the maps. Significantly, negative correlation was detected between high-temperature tolerance (UTT) and body weight (BW). The QTL mapping revealed 129 significant QTL loci for UTT and four significant QTL loci for BW at the genome-wide significance threshold. Among these QTLs, 129 overlapped with linked SNPs, and the remaining four were located in regions between contiguous SNPs. They explained the total phenotypic variance ranging from 8.9 to 12.4 %. Because of a significantly negative correlation between growth and high-temperature tolerance, we demonstrate that this high-resolution linkage map and QTLs would be useful for further marker-assisted selection in the genetic improvement of M. japonicus.

Average variograms to guide soil sampling

NASA Astrophysics Data System (ADS)

Kerry, R.; Oliver, M. A.

2004-10-01

To manage land in a site-specific way for agriculture requires detailed maps of the variation in the soil properties of interest. To predict accurately for mapping, the interval at which the soil is sampled should relate to the scale of spatial variation. A variogram can be used to guide sampling in two ways. A sampling interval of less than half the range of spatial dependence can be used, or the variogram can be used with the kriging equations to determine an optimal sampling interval to achieve a given tolerable error. A variogram might not be available for the site, but if the variograms of several soil properties were available on a similar parent material and or particular topographic positions an average variogram could be calculated from these. Averages of the variogram ranges and standardized average variograms from four different parent materials in southern England were used to suggest suitable sampling intervals for future surveys in similar pedological settings based on half the variogram range. The standardized average variograms were also used to determine optimal sampling intervals using the kriging equations. Similar sampling intervals were suggested by each method and the maps of predictions based on data at different grid spacings were evaluated for the different parent materials. Variograms of loss on ignition (LOI) taken from the literature for other sites in southern England with similar parent materials had ranges close to the average for a given parent material showing the possible wider application of such averages to guide sampling.

Comparison of regression and geostatistical methods for mapping Leaf Area Index (LAI) with Landsat ETM+ data over a boreal forest.

Treesearch

Mercedes Berterretche; Andrew T. Hudak; Warren B. Cohen; Thomas K. Maiersperger; Stith T. Gower; Jennifer Dungan

2005-01-01

This study compared aspatial and spatial methods of using remote sensing and field data to predict maximum growing season leaf area index (LAI) maps in a boreal forest in Manitoba, Canada. The methods tested were orthogonal regression analysis (reduced major axis, RMA) and two geostatistical techniques: kriging with an external drift (KED) and sequential Gaussian...

New machine learning tools for predictive vegetation mapping after climate change: Bagging and Random Forest perform better than Regression Tree Analysis

Treesearch

L.R. Iverson; A.M. Prasad; A. Liaw

2004-01-01

More and better machine learning tools are becoming available for landscape ecologists to aid in understanding species-environment relationships and to map probable species occurrence now and potentially into the future. To thal end, we evaluated three statistical models: Regression Tree Analybib (RTA), Bagging Trees (BT) and Random Forest (RF) for their utility in...

Regression modeling and mapping of coniferous forest basal area and tree density from discrete-return lidar and multispectral data

Treesearch

Andrew T. Hudak; Nicholas L. Crookston; Jeffrey S. Evans; Michael K. Falkowski; Alistair M. S. Smith; Paul E. Gessler; Penelope Morgan

2006-01-01

We compared the utility of discrete-return light detection and ranging (lidar) data and multispectral satellite imagery, and their integration, for modeling and mapping basal area and tree density across two diverse coniferous forest landscapes in north-central Idaho. We applied multiple linear regression models subset from a suite of 26 predictor variables derived...

The association between short interpregnancy interval and preterm birth in Louisiana: a comparison of methods.

PubMed

Howard, Elizabeth J; Harville, Emily; Kissinger, Patricia; Xiong, Xu

2013-07-01

There is growing interest in the application of propensity scores (PS) in epidemiologic studies, especially within the field of reproductive epidemiology. This retrospective cohort study assesses the impact of a short interpregnancy interval (IPI) on preterm birth and compares the results of the conventional logistic regression analysis with analyses utilizing a PS. The study included 96,378 singleton infants from Louisiana birth certificate data (1995-2007). Five regression models designed for methods comparison are presented. Ten percent (10.17 %) of all births were preterm; 26.83 % of births were from a short IPI. The PS-adjusted model produced a more conservative estimate of the exposure variable compared to the conventional logistic regression method (β-coefficient: 0.21 vs. 0.43), as well as a smaller standard error (0.024 vs. 0.028), odds ratio and 95 % confidence intervals [1.15 (1.09, 1.20) vs. 1.23 (1.17, 1.30)]. The inclusion of more covariate and interaction terms in the PS did not change the estimates of the exposure variable. This analysis indicates that PS-adjusted regression may be appropriate for validation of conventional methods in a large dataset with a fairly common outcome. PS's may be beneficial in producing more precise estimates, especially for models with many confounders and effect modifiers and where conventional adjustment with logistic regression is unsatisfactory. Short intervals between pregnancies are associated with preterm birth in this population, according to either technique. Birth spacing is an issue that women have some control over. Educational interventions, including birth control, should be applied during prenatal visits and following delivery.

Hierarchical cluster-based partial least squares regression (HC-PLSR) is an efficient tool for metamodelling of nonlinear dynamic models.

PubMed

Tøndel, Kristin; Indahl, Ulf G; Gjuvsland, Arne B; Vik, Jon Olav; Hunter, Peter; Omholt, Stig W; Martens, Harald

2011-06-01

Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs) to variation in features of the trajectories of the state variables (outputs) throughout the entire biologically relevant input space. A sufficiently accurate mapping can be exploited both instrumentally and epistemically. Multivariate regression methodology is a commonly used approach for emulating dynamic models. However, when the input-output relations are highly nonlinear or non-monotone, a standard linear regression approach is prone to give suboptimal results. We therefore hypothesised that a more accurate mapping can be obtained by locally linear or locally polynomial regression. We present here a new method for local regression modelling, Hierarchical Cluster-based PLS regression (HC-PLSR), where fuzzy C-means clustering is used to separate the data set into parts according to the structure of the response surface. We compare the metamodelling performance of HC-PLSR with polynomial partial least squares regression (PLSR) and ordinary least squares (OLS) regression on various systems: six different gene regulatory network models with various types of feedback, a deterministic mathematical model of the mammalian circadian clock and a model of the mouse ventricular myocyte function. Our results indicate that multivariate regression is well suited for emulating dynamic models in systems biology. The hierarchical approach turned out to be superior to both polynomial PLSR and OLS regression in all three test cases. The advantage, in terms of explained variance and prediction accuracy, was largest in systems with highly nonlinear functional relationships and in systems with positive feedback loops. HC-PLSR is a promising approach for metamodelling in systems biology, especially for highly nonlinear or non-monotone parameter to phenotype maps. The algorithm can be flexibly adjusted to suit the complexity of the dynamic model behaviour, inviting automation in the metamodelling of complex systems.

Hierarchical Cluster-based Partial Least Squares Regression (HC-PLSR) is an efficient tool for metamodelling of nonlinear dynamic models

PubMed Central

2011-01-01

Background Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs) to variation in features of the trajectories of the state variables (outputs) throughout the entire biologically relevant input space. A sufficiently accurate mapping can be exploited both instrumentally and epistemically. Multivariate regression methodology is a commonly used approach for emulating dynamic models. However, when the input-output relations are highly nonlinear or non-monotone, a standard linear regression approach is prone to give suboptimal results. We therefore hypothesised that a more accurate mapping can be obtained by locally linear or locally polynomial regression. We present here a new method for local regression modelling, Hierarchical Cluster-based PLS regression (HC-PLSR), where fuzzy C-means clustering is used to separate the data set into parts according to the structure of the response surface. We compare the metamodelling performance of HC-PLSR with polynomial partial least squares regression (PLSR) and ordinary least squares (OLS) regression on various systems: six different gene regulatory network models with various types of feedback, a deterministic mathematical model of the mammalian circadian clock and a model of the mouse ventricular myocyte function. Results Our results indicate that multivariate regression is well suited for emulating dynamic models in systems biology. The hierarchical approach turned out to be superior to both polynomial PLSR and OLS regression in all three test cases. The advantage, in terms of explained variance and prediction accuracy, was largest in systems with highly nonlinear functional relationships and in systems with positive feedback loops. Conclusions HC-PLSR is a promising approach for metamodelling in systems biology, especially for highly nonlinear or non-monotone parameter to phenotype maps. The algorithm can be flexibly adjusted to suit the complexity of the dynamic model behaviour, inviting automation in the metamodelling of complex systems. PMID:21627852

Modelling and mapping the topsoil organic carbon content for Tanzania

NASA Astrophysics Data System (ADS)

Kempen, Bas; Kaaya, Abel; Ngonyani Mhaiki, Consolatha; Kiluvia, Shani; Ruiperez-Gonzalez, Maria; Batjes, Niels; Dalsgaard, Soren

2014-05-01

Soil organic carbon (SOC), held in soil organic matter, is a key indicator of soil health and plays an important role in the global carbon cycle. The soil can act as a net source or sink of carbon depending on land use and management. Deforestation and forest degradation lead to the release of vast amounts of carbon from the soil in the form of greenhouse gasses, especially in tropical countries. Tanzania has a high deforestation rate: it is estimated that the country loses 1.1% of its total forested area annually. During 2010-2013 Tanzania has been a pilot country under the UN-REDD programme. This programme has supported Tanzania in its initial efforts towards reducing greenhouse gas emission from forest degradation and deforestation and towards preserving soil carbon stocks. Formulation and implementation of the national REDD strategy requires detailed information on the five carbon pools among these the SOC pool. The spatial distribution of SOC contents and stocks was not available for Tanzania. The initial aim of this research, was therefore to develop high-resolution maps of the SOC content for the country. The mapping exercise was carried out in a collaborative effort with four Tanzanian institutes and data from the Africa Soil Information Service initiative (AfSIS). The mapping exercise was provided with over 3200 field observations on SOC from four sources; this is the most comprehensive soil dataset collected in Tanzania so far. The main source of soil samples was the National Forest Monitoring and Assessment (NAFORMA). The carbon maps were generated by means of digital soil mapping using regression-kriging. Maps at 250 m spatial resolution were developed for four depth layers: 0-10 cm, 10-20 cm, 20-30 cm, and 0-30 cm. A total of 37 environmental GIS data layers were prepared for use as covariates in the regression model. These included vegetation indices, terrain parameters, surface temperature, spectral reflectances, a land cover map and a small-scale Soil and Terrain (SOTER) map. Prediction uncertainty was quantified by the 90% prediction interval and the predictions were validated by cross-validation. The SOTER map proved to be the best predictor of SOC content, followed by the terrain parameters, mid-infrared reflectance, surface temperature, several vegetation indices, and the land cover map. The maps show that the SOC content decreases with depth, which is typically observed in soils. For the 0-10 cm layer the average predicted SOC content is 1.31%, for the 10-20 cm layer this is 0.93%, for the 20-30cm layer 0.72%, and for the 0-30cm layer 1.00%. The mean absolute error of the 0-10cm layer was 0.54%, that of the 10-20cm layer 0.38%, that of the 20-30cm layer 0.31%, and that of the 0-30cm layer 0.34%. The R2-value of the 0-10 cm layer was 0.47, that of the 10-20cm layer 0.49, that of the 20-30cm layer 0.44, and that of the 0-30cm layer 0.59. The next step will be the development of maps of SOC stock and key properties that are of interest for soil fertility management such as pH and the textural fractions.

Identifying Strategies Programs Adopt to Meet Healthy Eating and Physical Activity Standards in Afterschool Programs.

PubMed

Weaver, Robert G; Moore, Justin B; Turner-McGrievy, Brie; Saunders, Ruth; Beighle, Aaron; Khan, M Mahmud; Chandler, Jessica; Brazendale, Keith; Randell, Allison; Webster, Collin; Beets, Michael W

2017-08-01

The YMCA of USA has adopted Healthy Eating and Physical Activity (HEPA) Standards for its afterschool programs (ASPs). Little is known about strategies YMCA ASPs are implementing to achieve Standards and these strategies' effectiveness. (1) Identify strategies implemented in YMCA ASPs and (2) evaluate the relationship between strategy implementation and meeting Standards. HEPA was measured via accelerometer (moderate-to-vigorous-physical-activity [MVPA]) and direct observation (snacks served) in 20 ASPs. Strategies were identified and mapped onto a capacity building framework ( Strategies To Enhance Practice [STEPs]). Mixed-effects regression estimated increases in HEPA outcomes as implementation increased. Model-implied estimates were calculated for high (i.e., highest implementation score achieved), moderate (median implementation score across programs), and low (lowest implementation score achieved) implementation for both HEPA separately. Programs implemented a variety of strategies identified in STEPs. For every 1-point increase in implementation score 1.45% (95% confidence interval = 0.33% to 2.55%, p ≤ .001) more girls accumulated 30 min/day of MVPA and fruits and/or vegetables were served on 0.11 more days (95% confidence interval = 0.11-0.45, p ≤ .01). Relationships between implementation and other HEPA outcomes did not reach statistical significance. Still regression estimates indicated that desserts are served on 1.94 fewer days (i.e., 0.40 vs. 2.34) in the highest implementing program than the lowest implementing program and water is served 0.73 more days (i.e., 2.37 vs. 1.64). Adopting HEPA Standards at the national level does not lead to changes in routine practice in all programs. Practical strategies that programs could adopt to more fully comply with the HEPA Standards are identified.

Cosinor-based rhythmometry

PubMed Central

2014-01-01

A brief overview is provided of cosinor-based techniques for the analysis of time series in chronobiology. Conceived as a regression problem, the method is applicable to non-equidistant data, a major advantage. Another dividend is the feasibility of deriving confidence intervals for parameters of rhythmic components of known periods, readily drawn from the least squares procedure, stressing the importance of prior (external) information. Originally developed for the analysis of short and sparse data series, the extended cosinor has been further developed for the analysis of long time series, focusing both on rhythm detection and parameter estimation. Attention is given to the assumptions underlying the use of the cosinor and ways to determine whether they are satisfied. In particular, ways of dealing with non-stationary data are presented. Examples illustrate the use of the different cosinor-based methods, extending their application from the study of circadian rhythms to the mapping of broad time structures (chronomes). PMID:24725531

Fine Mapping of Resistance Genes from Five Brown Stem Rot Resistance Sources in Soybean.

PubMed

Rincker, Keith; Hartman, Glen L; Diers, Brian W

2016-03-01

Brown stem rot (BSR) of soybean [ (L.) Merr.] caused by (Allington & Chamb.) T.C. Harr. & McNew can be controlled effectively with genetic host resistance. Three BSR resistance genes , , and , have been identified and mapped to a large region on chromosome 16. Marker-assisted selection (MAS) will be more efficient and gene cloning will be facilitated with a narrowed genomic interval containing an gene. The objective of this study was to fine map the positions of genes from five sources. Mapping populations were developed by crossing the resistant sources 'Bell', PI 84946-2, PI 437833, PI 437970, L84-5873, and PI 86150 with either the susceptible cultivar Colfax or Century 84. Plants identified as having a recombination event near genes were selected and individually harvested to create recombinant lines. Progeny from recombinant lines were tested in a root-dip assay and evaluated for foliar and stem BSR symptom development. Overall, 4878 plants were screened for recombination, and progeny from 52 recombinant plants were evaluated with simple-sequence repeat (SSR) genetic markers and assessed for symptom development. Brown stem rot resistance was mapped to intervals ranging from 0.34 to 0.04 Mb in the different sources. In all sources, resistance was fine mapped to intervals inclusive of BARCSOYSSR_16_1114 and BARCSOYSSR_16_1115, which provides further evidence that one locus provides BSR resistance in soybean. Copyright © 2016 Crop Science Society of America.

Genetic linkage map of a wild genome: genomic structure, recombination and sexual dimorphism in bighorn sheep

PubMed Central

2010-01-01

Background The construction of genetic linkage maps in free-living populations is a promising tool for the study of evolution. However, such maps are rare because it is difficult to develop both wild pedigrees and corresponding sets of molecular markers that are sufficiently large. We took advantage of two long-term field studies of pedigreed individuals and genomic resources originally developed for domestic sheep (Ovis aries) to construct a linkage map for bighorn sheep, Ovis canadensis. We then assessed variability in genomic structure and recombination rates between bighorn sheep populations and sheep species. Results Bighorn sheep population-specific maps differed slightly in contiguity but were otherwise very similar in terms of genomic structure and recombination rates. The joint analysis of the two pedigrees resulted in a highly contiguous map composed of 247 microsatellite markers distributed along all 26 autosomes and the X chromosome. The map is estimated to cover about 84% of the bighorn sheep genome and contains 240 unique positions spanning a sex-averaged distance of 3051 cM with an average inter-marker distance of 14.3 cM. Marker synteny, order, sex-averaged interval lengths and sex-averaged total map lengths were all very similar between sheep species. However, in contrast to domestic sheep, but consistent with the usual pattern for a placental mammal, recombination rates in bighorn sheep were significantly greater in females than in males (~12% difference), resulting in an autosomal female map of 3166 cM and an autosomal male map of 2831 cM. Despite differing genome-wide patterns of heterochiasmy between the sheep species, sexual dimorphism in recombination rates was correlated between orthologous intervals. Conclusions We have developed a first-generation bighorn sheep linkage map that will facilitate future studies of the genetic architecture of trait variation in this species. While domestication has been hypothesized to be responsible for the elevated mean recombination rate observed in domestic sheep, our results suggest that it is a characteristic of Ovis species. However, domestication may have played a role in altering patterns of heterochiasmy. Finally, we found that interval-specific patterns of sexual dimorphism were preserved among closely related Ovis species, possibly due to the conserved position of these intervals relative to the centromeres and telomeres. This study exemplifies how transferring genomic resources from domesticated species to close wild relative can benefit evolutionary ecologists while providing insights into the evolution of genomic structure and recombination rates of domesticated species. PMID:20920197

Preliminary genetic linkage map of the abalone Haliotis diversicolor Reeve

NASA Astrophysics Data System (ADS)

Shi, Yaohua; Guo, Ximing; Gu, Zhifeng; Wang, Aimin; Wang, Yan

2010-05-01

Haliotis diversicolor Reeve is one of the most important mollusks cultured in South China. Preliminary genetic linkage maps were constructed with amplified fragment length polymorphism (AFLP) markers. A total of 2 596 AFLP markers were obtained from 28 primer combinations in two parents and 78 offsprings. Among them, 412 markers (15.9%) were polymorphic and segregated in the mapping family. Chi-square tests showed that 151 (84.4%) markers segregated according to the expected 1:1 Mendelian ratio ( P<0.05) in the female parent, and 200 (85.8%) in the male parent. For the female map, 179 markers were used for linkage analysis and 90 markers were assigned to 17 linkage groups with an average interval length of 25.7 cm. For the male map, 233 markers were used and 94 were mapped into 18 linkage groups, with an average interval of 25.0 cm. The estimated genome length was 2 773.0 cm for the female and 2 817.1 cm for the male map. The observed length of the linkage map was 1 875.2 cm and 1 896.5 cm for the female and male maps, respectively. When doublets were considered, the map length increased to 2 152.8 cm for the female and 2 032.7 cm for the male map, corresponding to genome coverage of 77.6% and 72.2%, respectively.

Techniques for estimating flood-peak discharges of rural, unregulated streams in Ohio

USGS Publications Warehouse

Koltun, G.F.

2003-01-01

Regional equations for estimating 2-, 5-, 10-, 25-, 50-, 100-, and 500-year flood-peak discharges at ungaged sites on rural, unregulated streams in Ohio were developed by means of ordinary and generalized least-squares (GLS) regression techniques. One-variable, simple equations and three-variable, full-model equations were developed on the basis of selected basin characteristics and flood-frequency estimates determined for 305 streamflow-gaging stations in Ohio and adjacent states. The average standard errors of prediction ranged from about 39 to 49 percent for the simple equations, and from about 34 to 41 percent for the full-model equations. Flood-frequency estimates determined by means of log-Pearson Type III analyses are reported along with weighted flood-frequency estimates, computed as a function of the log-Pearson Type III estimates and the regression estimates. Values of explanatory variables used in the regression models were determined from digital spatial data sets by means of a geographic information system (GIS), with the exception of drainage area, which was determined by digitizing the area within basin boundaries manually delineated on topographic maps. Use of GIS-based explanatory variables represents a major departure in methodology from that described in previous reports on estimating flood-frequency characteristics of Ohio streams. Examples are presented illustrating application of the regression equations to ungaged sites on ungaged and gaged streams. A method is provided to adjust regression estimates for ungaged sites by use of weighted and regression estimates for a gaged site on the same stream. A region-of-influence method, which employs a computer program to estimate flood-frequency characteristics for ungaged sites based on data from gaged sites with similar characteristics, was also tested and compared to the GLS full-model equations. For all recurrence intervals, the GLS full-model equations had superior prediction accuracy relative to the simple equations and therefore are recommended for use.

Quantile regression models of animal habitat relationships

USGS Publications Warehouse

Cade, Brian S.

2003-01-01

Typically, all factors that limit an organism are not measured and included in statistical models used to investigate relationships with their environment. If important unmeasured variables interact multiplicatively with the measured variables, the statistical models often will have heterogeneous response distributions with unequal variances. Quantile regression is an approach for estimating the conditional quantiles of a response variable distribution in the linear model, providing a more complete view of possible causal relationships between variables in ecological processes. Chapter 1 introduces quantile regression and discusses the ordering characteristics, interval nature, sampling variation, weighting, and interpretation of estimates for homogeneous and heterogeneous regression models. Chapter 2 evaluates performance of quantile rankscore tests used for hypothesis testing and constructing confidence intervals for linear quantile regression estimates (0 ≤ τ ≤ 1). A permutation F test maintained better Type I errors than the Chi-square T test for models with smaller n, greater number of parameters p, and more extreme quantiles τ. Both versions of the test required weighting to maintain correct Type I errors when there was heterogeneity under the alternative model. An example application related trout densities to stream channel width:depth. Chapter 3 evaluates a drop in dispersion, F-ratio like permutation test for hypothesis testing and constructing confidence intervals for linear quantile regression estimates (0 ≤ τ ≤ 1). Chapter 4 simulates from a large (N = 10,000) finite population representing grid areas on a landscape to demonstrate various forms of hidden bias that might occur when the effect of a measured habitat variable on some animal was confounded with the effect of another unmeasured variable (spatially and not spatially structured). Depending on whether interactions of the measured habitat and unmeasured variable were negative (interference interactions) or positive (facilitation interactions), either upper (τ > 0.5) or lower (τ < 0.5) quantile regression parameters were less biased than mean rate parameters. Sampling (n = 20 - 300) simulations demonstrated that confidence intervals constructed by inverting rankscore tests provided valid coverage of these biased parameters. Quantile regression was used to estimate effects of physical habitat resources on a bivalve mussel (Macomona liliana) in a New Zealand harbor by modeling the spatial trend surface as a cubic polynomial of location coordinates.

`VIS/NIR mapping of TOC and extent of organic soils in the Nørre Å valley

NASA Astrophysics Data System (ADS)

Knadel, M.; Greve, M. H.; Thomsen, A.

2009-04-01

Organic soils represent a substantial pool of carbon in Denmark. The need for carbon stock assessment calls for more rapid and effective mapping methods to be developed. The aim of this study was to compare traditional soil mapping with maps produced from the results of a mobile VIS/NIR system and to evaluate the ability to estimate TOC and map the area of organic soils. The Veris mobile VIS/NIR spectroscopy system was compared to traditional manual sampling. The system is developed for in-situ near surface measurements of soil carbon content. It measures diffuse reflectance in the 350 nm-2200 nm region. The system consists of two spectrophotometers mounted on a toolbar and pulled by a tractor. Optical measurements are made through a sapphire window at the bottom of the shank. The shank was pulled at a depth of 5-7 cm at a speed of 4-5 km/hr. 20-25 spectra per second with 8 nm resolution were acquired by the spectrometers. Measurements were made on 10-12 m spaced transects. The system also acquired soil electrical conductivity (EC) for two soil depths: shallow EC-SH (0- 31 cm) and deep conductivity EC-DP (0- 91 cm). The conductivity was recorded together with GPS coordinates and spectral data for further construction of the calibration models. Two maps of organic soils in the Nørre Å valley (Central Jutland) were generated: (i) based on a conventional 25 m grid with 162 sampling points and laboratory analysis of TOC, (ii) based on in-situ VIS/NIR measurements supported by chemometrics. Before regression analysis, spectral information was compressed by calculating principal components. The outliers were determined by a mahalanobis distance equation and removed. Clustering using a fuzzy c- means algorithm was conducted. Within each cluster a location with the minimal spatial variability was selected. A map of 15 representative sample locations was proposed. The interpolation of the spectra into a single spectrum was performed using a Gaussian kernel weighting function. Spectra obtained near a sampled location were averaged. The collected spectra were correlated to TOC of the 15 representative samples using multivariate regression techniques (Unscrambler 9.7; Camo ASA, Oslo, Norway). Two types of calibrations were performed: using only spectra and using spectra together with the auxiliary data (EC-SH and EC-DP). These calibration equations were computed using PLS regression, segmented cross-validation method on centred data (using the raw spectral data, log 1/R). Six different spectra pre-treatments were conducted: (1) only spectra, (2) Savitsky-Golay smoothing over 11 wavelength points and transformation to a (3) 1'st and (4) 2'nd Savitzky and Golay derivative algorithm with a derivative interval of 21 wavelength points, (5) with or (6) without smoothing. The best treatment was considered to be the one with the lowest Root Mean Square Error of Prediction (RMSEP), the highest r2 between the VIS/NIR-predicted and measured values in the calibration model and the lowest mean deviation of predicted TOC values. The best calibration model was obtained with the mathematical pre-treatment's including smoothing, calculating the 2'nd derivative and outlier removal. The two TOC maps were compared after interpolation using kriging. They showed a similar pattern in the TOC distribution. Despite the unfavourable field conditions the VIS/NIR system performed well in both low and high TOC areas. Water content in places exceeding field capacity in the lower parts of the investigated field did not seriously degrade measurements. The present study represents the first attempt to apply the mobile Veris VIS/NIR system to the mapping of TOC of peat soils in Denmark. The result from this study show that a mobile VIS/NIR system can be applied to cost effective TOC mapping of mineral and organic soils with highly varying water content. Key words: VIS/NIR spectroscopy, organic soils, TOC

GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models.

PubMed

Chen, Wei; Li, Hui; Hou, Enke; Wang, Shengquan; Wang, Guirong; Panahi, Mahdi; Li, Tao; Peng, Tao; Guo, Chen; Niu, Chao; Xiao, Lele; Wang, Jiale; Xie, Xiaoshen; Ahmad, Baharin Bin

2018-09-01

The aim of the current study was to produce groundwater spring potential maps using novel ensemble weights-of-evidence (WoE) with logistic regression (LR) and functional tree (FT) models. First, a total of 66 springs were identified by field surveys, out of which 70% of the spring locations were used for training the models and 30% of the spring locations were employed for the validation process. Second, a total of 14 affecting factors including aspect, altitude, slope, plan curvature, profile curvature, stream power index (SPI), topographic wetness index (TWI), sediment transport index (STI), lithology, normalized difference vegetation index (NDVI), land use, soil, distance to roads, and distance to streams was used to analyze the spatial relationship between these affecting factors and spring occurrences. Multicollinearity analysis and feature selection of the correlation attribute evaluation (CAE) method were employed to optimize the affecting factors. Subsequently, the novel ensembles of the WoE, LR, and FT models were constructed using the training dataset. Finally, the receiver operating characteristic (ROC) curves, standard error, confidence interval (CI) at 95%, and significance level P were employed to validate and compare the performance of three models. Overall, all three models performed well for groundwater spring potential evaluation. The prediction capability of the FT model, with the highest AUC values, the smallest standard errors, the narrowest CIs, and the smallest P values for the training and validation datasets, is better compared to those of other models. The groundwater spring potential maps can be adopted for the management of water resources and land use by planners and engineers. Copyright © 2018 Elsevier B.V. All rights reserved.

African Ancestry Analysis and Admixture Genetic Mapping for Proliferative Diabetic Retinopathy in African Americans

PubMed Central

Tandon, Arti; Chen, Ching J.; Penman, Alan; Hancock, Heather; James, Maurice; Husain, Deeba; Andreoli, Christopher; Li, Xiaohui; Kuo, Jane Z.; Idowu, Omolola; Riche, Daniel; Papavasilieou, Evangelia; Brauner, Stacey; Smith, Sataria O.; Hoadley, Suzanne; Richardson, Cole; Kieser, Troy; Vazquez, Vanessa; Chi, Cheryl; Fernandez, Marlene; Harden, Maegan; Cotch, Mary Frances; Siscovick, David; Taylor, Herman A.; Wilson, James G.; Reich, David; Wong, Tien Y.; Klein, Ronald; Klein, Barbara E. K.; Rotter, Jerome I.; Patterson, Nick; Sobrin, Lucia

2015-01-01

Purpose. To examine the relationship between proportion of African ancestry (PAA) and proliferative diabetic retinopathy (PDR) and to identify genetic loci associated with PDR using admixture mapping in African Americans with type 2 diabetes (T2D). Methods. Between 1993 and 2013, 1440 participants enrolled in four different studies had fundus photographs graded using the Early Treatment Diabetic Retinopathy Study scale. Cases (n = 305) had PDR while controls (n = 1135) had nonproliferative diabetic retinopathy (DR) or no DR. Covariates included diabetes duration, hemoglobin A1C, systolic blood pressure, income, and education. Genotyping was performed on the Affymetrix platform. The association between PAA and PDR was evaluated using logistic regression. Genome-wide admixture scanning was performed using ANCESTRYMAP software. Results. In the univariate analysis, PDR was associated with increased PAA (odds ratio [OR] = 1.36, 95% confidence interval [CI] = 1.16–1.59, P = 0.0002). In multivariate regression adjusting for traditional DR risk factors, income and education, the association between PAA and PDR was attenuated and no longer significant (OR = 1.21, 95% CI = 0.59–2.47, P = 0.61). For the admixture analyses, the maximum genome-wide score was 1.44 on chromosome 1. Conclusions. In this largest study of PDR in African Americans with T2D to date, an association between PAA and PDR is not present after adjustment for clinical, demographic, and socioeconomic factors. No genome-wide significant locus (defined as having a locus-genome statistic > 5) was identified with admixture analysis. Further analyses with even larger sample sizes are needed to definitively assess if any admixture signal for DR is present. PMID:26098467

GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran.

PubMed

Naghibi, Seyed Amir; Pourghasemi, Hamid Reza; Dixon, Barnali

2016-01-01

Groundwater is considered one of the most valuable fresh water resources. The main objective of this study was to produce groundwater spring potential maps in the Koohrang Watershed, Chaharmahal-e-Bakhtiari Province, Iran, using three machine learning models: boosted regression tree (BRT), classification and regression tree (CART), and random forest (RF). Thirteen hydrological-geological-physiographical (HGP) factors that influence locations of springs were considered in this research. These factors include slope degree, slope aspect, altitude, topographic wetness index (TWI), slope length (LS), plan curvature, profile curvature, distance to rivers, distance to faults, lithology, land use, drainage density, and fault density. Subsequently, groundwater spring potential was modeled and mapped using CART, RF, and BRT algorithms. The predicted results from the three models were validated using the receiver operating characteristics curve (ROC). From 864 springs identified, 605 (≈70 %) locations were used for the spring potential mapping, while the remaining 259 (≈30 %) springs were used for the model validation. The area under the curve (AUC) for the BRT model was calculated as 0.8103 and for CART and RF the AUC were 0.7870 and 0.7119, respectively. Therefore, it was concluded that the BRT model produced the best prediction results while predicting locations of springs followed by CART and RF models, respectively. Geospatially integrated BRT, CART, and RF methods proved to be useful in generating the spring potential map (SPM) with reasonable accuracy.

DAM - detection and mapping

NASA Technical Reports Server (NTRS)

1977-01-01

Integrated set of manual procedures, computer programs, and graphic devices processes multispectral scanner data from orbiting Landsat into precisely registered and formatted maps of surface water and other resources at variety of scales, sheet formats, and tick intervals.

A population of deletion mutants and an integrated mapping and Exome-seq pipeline for gene discovery in maize

USDA-ARS?s Scientific Manuscript database

To better understand maize endosperm filling and maturation, we developed a novel functional genomics platform that combined Bulked Segregant RNA and Exome sequencing (BSREx-seq) to map causative mutations and identify candidate genes within mapping intervals. Using gamma-irradiation of B73 maize to...

The effects of intravenous anesthetics on QT interval during anesthetic induction with sevoflurane.

PubMed

Terao, Yoshiaki; Higashijima, Ushio; Toyoda, Tomomi; Ichinomiya, Taiga; Fukusaki, Makoto; Hara, Tetsuya

2016-12-01

Sevoflurane is known to prolong the QT interval. This study aimed to determine the effect of the interaction between intravenous anesthetics and sevoflurane on the QT interval. The study included 48 patients who underwent lumbar spine surgery. Patients received 3 μg/kg fentanyl and were then randomly allocated to either Group T, in which they received 5 mg/kg thiamylal, or Group P, in which they received 1.5 mg/kg propofol, at 2 min after administration of fentanyl injection for anesthetic induction. Vecuronium (1.5 mg/kg) and sevoflurane (3 % inhaled concentration) were administered immediately after loss of consciousness and tracheal intubation was performed 3 min after vecuronium injection. Heart rate (HR), mean arterial pressure (MAP), bispectral index score (BIS), and the heart rate-corrected QT (QTc) interval on a 12-lead electrocardiogram were recorded immediately before fentanyl administration (T1), 2 min after fentanyl injection (T2), immediately before intubation (T3), and 2 min after intubation (T4). There were no significant differences between the two groups in baseline patient characteristics. BIS and MAP significantly decreased after anesthesia induction in both groups. At T3, MAP in Group T was higher than in Group P, while HR had reduced in both groups. The QTc interval was prolonged after anesthesia induction in Group T, but did not change at any time point in Group P. The QTc interval after anesthesia induction in Group T was longer than in Group P. We concluded that an injection of propofol could counteract QTc interval prolongation associated with sevoflurane anesthesia induction.

Shaded seafloor relief, backscatter strength, and surficial geology; German Bank, Scotian Shelf, offshore Nova Scotia

USGS Publications Warehouse

Todd, B.J.; Valentine, Page C.

2010-01-01

This map is part of a three-map series of German Bank, located on the Scotian Shelf off southern Nova Scotia.  This map is the product of a number of surveys (1997-2003) that used a multibeam sonar system to map 5321 km2 of the seafloor.  Other surveys collected geological data for scientific interpretation.  This map sheet shows the seafloor topography of German Bank in shaded-relief view and seafloor depth (coded by colour) at a scale of 1:1000,000.  Topographic contours generated from the multibeam data are shown (in white) on the colour-coded multibeam topography at a depth interval of 20 m.  Bathymetic contours (in blue) outside the multibeam survey area, presented at a depth interval of 10 m, are from the Natural Resource Map series (Canadian Hydrographic Service, 1967, 1971a, 1971b, 1972). Sheet 2 shows coloured backscatter strength in shaded-relief view.  Sheet 3 shows seafloor topography in shaded-relief view with colour-coded surficial geological units.

A multitemporal (1979-2009) land-use/land-cover dataset of the binational Santa Cruz Watershed

USGS Publications Warehouse

2011-01-01

Trends derived from multitemporal land-cover data can be used to make informed land management decisions and to help managers model future change scenarios. We developed a multitemporal land-use/land-cover dataset for the binational Santa Cruz watershed of southern Arizona, United States, and northern Sonora, Mexico by creating a series of land-cover maps at decadal intervals (1979, 1989, 1999, and 2009) using Landsat Multispectral Scanner and Thematic Mapper data and a classification and regression tree classifier. The classification model exploited phenological changes of different land-cover spectral signatures through the use of biseasonal imagery collected during the (dry) early summer and (wet) late summer following rains from the North American monsoon. Landsat images were corrected to remove atmospheric influences, and the data were converted from raw digital numbers to surface reflectance values. The 14-class land-cover classification scheme is based on the 2001 National Land Cover Database with a focus on "Developed" land-use classes and riverine "Forest" and "Wetlands" cover classes required for specific watershed models. The classification procedure included the creation of several image-derived and topographic variables, including digital elevation model derivatives, image variance, and multitemporal Kauth-Thomas transformations. The accuracy of the land-cover maps was assessed using a random-stratified sampling design, reference aerial photography, and digital imagery. This showed high accuracy results, with kappa values (the statistical measure of agreement between map and reference data) ranging from 0.80 to 0.85.

Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99

USGS Publications Warehouse

Conrads, Paul; Petkewich, Matthew D.; O'Reilly, Andrew M.; Telis, Pamela A.

2015-01-01

To hindcast and fill data records, 214 empirical models were developed—189 are linear regression models and 25 are artificial neural network models. The coefficient of determination (R2) for 163 of the models is greater than 0.80 and the median percent model error (root mean square error divided by the range of the measured data) is 5 percent. To evaluate the performance of the hindcast models as a group, contour maps of modeled water-level surfaces at 2-centimeter (cm) intervals were generated using the hindcasted data. The 2-cm contour maps were examined for selected days to verify that water surfaces from the EDEN model are consistent with the input data. The biweekly 2-cm contour maps did show a higher number of issues during days in 1990 as compared to days after 1990. May 1990 had the lowest water levels in the Everglades of the 21-year dataset used for the hindcasting study. To hindcast these record low conditions in 1990, many of the hindcast models would require large extrapolations beyond the range of the predictive quality of the models. For these reasons, it was decided to limit the hindcasted data to the period January 1, 1991, to December 31, 1999. Overall, the hindcasted and gap-filled data are assumed to provide reasonable estimates of station-specific water-level data for an extended historical period to inform research and natural resource management in the Everglades.

Does Availability of Worksite Supports for Physical Activity Differ by Industry and Occupation?

PubMed

Dodson, Elizabeth A; Hipp, J Aaron; Lee, Jung Ae; Yang, Lin; Marx, Christine M; Tabak, Rachel G; Brownson, Ross C

2018-03-01

To explore combinations of worksite supports (WSS) for physical activity (PA) that may assist employees in meeting PA recommendations and to investigate how availability of WSS differs across industries and occupations. Cross-sectional. Several Missouri metropolitan areas. Adults employed >20 h/wk outside the home. Survey utilized existing self-reported measures (eg, presence of WSS for PA) and the International Physical Activity Questionnaire. Logistic regression was conducted for 2 outcome variables: leisure and transportation PA. Independent variables included 16 WSS. Of particular interest were interaction effects between WSS variables. Analyses were stratified by 5 occupation and 7 industry types. Overall, 2013 people completed the survey (46% response rate). Often, availability of 1 WSS did not increase the likelihood of meeting PA recommendations, but several pairs of WSS did. For example, in business occupations, the odds of meeting PA recommendations through transportation PA increased when employees had access to showers and incentives to bike/walk (odds ratio [OR] = 1.6; 95% confidence interval [CI] = 1.16-2.22); showers and maps (OR = 1.25; 1.02-1.55); maps and incentives to bike/walk (OR = 1.48; 1.04-2.12). Various combinations of WSS may increase the likelihood that employees will meet PA recommendations. Many are of low or no cost, including flexible time for exercise and maps of worksite-adjacent walk/bike routes. Findings may be instructive for employers seeking to improve employee health through worksite PA.

A candidate region for Nevoid Basal Cell Carcinoma Syndrome defined by genetic and physical mapping

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wainwright, B.; Negus, K.; Berkman, J.

1994-09-01

Nevoid Basal Cell Carcinoma Syndrome (NBCCS, or Gorlin`s syndrome) is a cancer predisposition syndrome charcterized by multiple basal cell carcinomas (BCCs) and diverse developmental defects. The gene responsible for NBCCS, which is most likely to be a tumor suppressor gene, has previously been mapped to 9q22.3-q31 in a 12 cM interval between the microsatellite marker loci D9S12 and D9S109. Combined multipoint and haplotype analyses of Australian pedigrees has further refined the localization to a 2 cM interval between markers D9S196 and D9S180. Our loss of heterozygosity (LOH) studies from sporadic (n= 58) and familial (n=41) BCCs indicate that 50% havemore » deletions within the NBCCS candidate region. All LOH is consistent with the genetic mapping of the NBCCS locus. Additionally, one sporadic tumor indicates that the smallest region of overlap in the deletions is within the interval D9S287 (proximal) and D9S180 (distal). A series of YAC clones from within this region has been mapped by FISH to examine chimerism. These clones, which have been mapped with respect to one another, form a contig which encompasses the candidate region from D9S196 to D9S180.« less

Characterization of a Thermo-Inducible Chlorophyll-Deficient Mutant in Barley.

PubMed

Wang, Rong; Yang, Fei; Zhang, Xiao-Qi; Wu, Dianxin; Tan, Cong; Westcott, Sharon; Broughton, Sue; Li, Chengdao; Zhang, Wenying; Xu, Yanhao

2017-01-01

Leaf color is an important trait for not only controlling crop yield but also monitoring plant status under temperature stress. In this study, a thermo-inducible chlorophyll-deficient mutant, named V-V-Y, was identified from a gamma-radiated population of the barley variety Vlamingh. The leaves of the mutant were green under normal growing temperature but turned yellowish under high temperature in the glasshouse experiment. The ratio of chlorophyll a and chlorophyll b in the mutant declined much faster in the first 7-9 days under heat treatment. The leaves of V-V-Y turned yellowish but took longer to senesce under heat stress in the field experiment. Genetic analysis indicated that a single nuclear gene controlled the mutant trait. The mutant gene ( vvy ) was mapped to the long arm of chromosome 4H between SNP markers 1_0269 and 1_1531 with a genetic distance of 2.2 cM and a physical interval of 9.85 Mb. A QTL for grain yield was mapped to the same interval and explained 10.4% of the yield variation with a LOD score of 4. This QTL is coincident with the vvy gene interval that is responsible for the thermo-inducible chlorophyll-deficient trait. Fine mapping, based on the barley reference genome sequence, further narrowed the vvy gene to a physical interval of 0.428 Mb with 11 annotated genes. This is the first report of fine mapping a thermo-inducible chlorophyll-deficient gene in barley.

Predicting Ambulance Time of Arrival to the Emergency Department Using Global Positioning System and Google Maps

PubMed Central

Fleischman, Ross J.; Lundquist, Mark; Jui, Jonathan; Newgard, Craig D.; Warden, Craig

2014-01-01

Objective To derive and validate a model that accurately predicts ambulance arrival time that could be implemented as a Google Maps web application. Methods This was a retrospective study of all scene transports in Multnomah County, Oregon, from January 1 through December 31, 2008. Scene and destination hospital addresses were converted to coordinates. ArcGIS Network Analyst was used to estimate transport times based on street network speed limits. We then created a linear regression model to improve the accuracy of these street network estimates using weather, patient characteristics, use of lights and sirens, daylight, and rush-hour intervals. The model was derived from a 50% sample and validated on the remainder. Significance of the covariates was determined by p < 0.05 for a t-test of the model coefficients. Accuracy was quantified by the proportion of estimates that were within 5 minutes of the actual transport times recorded by computer-aided dispatch. We then built a Google Maps-based web application to demonstrate application in real-world EMS operations. Results There were 48,308 included transports. Street network estimates of transport time were accurate within 5 minutes of actual transport time less than 16% of the time. Actual transport times were longer during daylight and rush-hour intervals and shorter with use of lights and sirens. Age under 18 years, gender, wet weather, and trauma system entry were not significant predictors of transport time. Our model predicted arrival time within 5 minutes 73% of the time. For lights and sirens transports, accuracy was within 5 minutes 77% of the time. Accuracy was identical in the validation dataset. Lights and sirens saved an average of 3.1 minutes for transports under 8.8 minutes, and 5.3 minutes for longer transports. Conclusions An estimate of transport time based only on a street network significantly underestimated transport times. A simple model incorporating few variables can predict ambulance time of arrival to the emergency department with good accuracy. This model could be linked to global positioning system data and an automated Google Maps web application to optimize emergency department resource use. Use of lights and sirens had a significant effect on transport times. PMID:23865736

Producing landslide susceptibility maps by utilizing machine learning methods. The case of Finikas catchment basin, North Peloponnese, Greece.

NASA Astrophysics Data System (ADS)

Tsangaratos, Paraskevas; Ilia, Ioanna; Loupasakis, Constantinos; Papadakis, Michalis; Karimalis, Antonios

2017-04-01

The main objective of the present study was to apply two machine learning methods for the production of a landslide susceptibility map in the Finikas catchment basin, located in North Peloponnese, Greece and to compare their results. Specifically, Logistic Regression and Random Forest were utilized, based on a database of 40 sites classified into two categories, non-landslide and landslide areas that were separated into a training dataset (70% of the total data) and a validation dataset (remaining 30%). The identification of the areas was established by analyzing airborne imagery, extensive field investigation and the examination of previous research studies. Six landslide related variables were analyzed, namely: lithology, elevation, slope, aspect, distance to rivers and distance to faults. Within the Finikas catchment basin most of the reported landslides were located along the road network and within the residential complexes, classified as rotational and translational slides, and rockfalls, mainly caused due to the physical conditions and the general geotechnical behavior of the geological formation that cover the area. Each landslide susceptibility map was reclassified by applying the Geometric Interval classification technique into five classes, namely: very low susceptibility, low susceptibility, moderate susceptibility, high susceptibility, and very high susceptibility. The comparison and validation of the outcomes of each model were achieved using statistical evaluation measures, the receiving operating characteristic and the area under the success and predictive rate curves. The computation process was carried out using RStudio an integrated development environment for R language and ArcGIS 10.1 for compiling the data and producing the landslide susceptibility maps. From the outcomes of the Logistic Regression analysis it was induced that the highest b coefficient is allocated to lithology and slope, which was 2.8423 and 1.5841, respectively. From the estimation of the mean decrease in Gini coefficient performed during the application of Random Forest and the mean decrease in accuracy the most important variable is slope followed by lithology, aspect, elevation, distance from river network, and distance from faults, while the most used variables during the training phase were the variable aspect (21.45%), slope (20.53%) and lithology (19.84%). The outcomes of the analysis are consistent with previous studies concerning the area of research, which have indicated the high influence of lithology and slope in the manifestation of landslides. High percentage of landslide occurrence has been observed in Plio-Pleistocene sediments, flysch formations, and Cretaceous limestone. Also the presences of landslides have been associated with the degree of weathering and fragmentation, the orientation of the discontinuities surfaces and the intense morphological relief. The most accurate model was Random Forest which identified correctly 92.00% of the instances during the training phase, followed by the Logistic Regression 89.00%. The same pattern of accuracy was calculated during the validation phase, in which the Random Forest achieved a classification accuracy of 93.00%, while the Logistic Regression model achieved an accuracy of 91.00%. In conclusion, the outcomes of the study could be a useful cartographic product to local authorities and government agencies during the implementation of successful decision-making and land use planning strategies. Keywords: Landslide Susceptibility, Logistic Regression, Random Forest, GIS, Greece.

Potential confounding in the association between short birth intervals and increased neonatal, infant, and child mortality

PubMed Central

Perin, Jamie; Walker, Neff

2015-01-01

Background Recent steep declines in child mortality have been attributed in part to increased use of contraceptives and the resulting change in fertility behaviour, including an increase in the time between births. Previous observational studies have documented strong associations between short birth spacing and an increase in the risk of neonatal, infant, and under-five mortality, compared to births with longer preceding birth intervals. In this analysis, we compare two methods to estimate the association between short birth intervals and mortality risk to better inform modelling efforts linking family planning and mortality in children. Objectives Our goal was to estimate the mortality risk for neonates, infants, and young children by preceding birth space using household survey data, controlling for mother-level factors and to compare the results to those from previous analyses with survey data. Design We assessed the potential for confounding when estimating the relative mortality risk by preceding birth interval and estimated mortality risk by birth interval in four categories: less than 18 months, 18–23 months, 24–35 months, and 36 months or longer. We estimated the relative risks among women who were 35 and older at the time of the survey with two methods: in a Cox proportional hazards regression adjusting for potential confounders and also by stratifying Cox regression by mother, to control for all factors that remain constant over a woman's childbearing years. We estimated the overall effects for birth spacing in a meta-analysis with random survey effects. Results We identified several factors known for their associations with neonatal, infant, and child mortality that are also associated with preceding birth interval. When estimating the effect of birth spacing on mortality, we found that regression adjustment for these factors does not substantially change the risk ratio for short birth intervals compared to an unadjusted mortality ratio. For birth intervals less than 18 months, standard regression adjustment for confounding factors estimated a risk ratio for neonatal mortality of 2.28 (95% confidence interval: 2.18–2.37). This same effect estimated within mother is 1.57 (95% confidence interval: 1.52–1.63), a decline of almost one-third in the effect on neonatal mortality. Conclusions Neonatal, infant, and child mortality are strongly and significantly related to preceding birth interval, where births within a short interval of time after the previous birth have increased mortality. Previous analyses have demonstrated this relationship on average across all births; however, women who have short spaces between births are different from women with long spaces. Among women 35 years and older where a comparison of birth spaces within mother is possible, we find a much reduced although still significant effect of short birth spaces on child mortality. PMID:26562139

Potential confounding in the association between short birth intervals and increased neonatal, infant, and child mortality.

PubMed

Perin, Jamie; Walker, Neff

2015-01-01

Recent steep declines in child mortality have been attributed in part to increased use of contraceptives and the resulting change in fertility behaviour, including an increase in the time between births. Previous observational studies have documented strong associations between short birth spacing and an increase in the risk of neonatal, infant, and under-five mortality, compared to births with longer preceding birth intervals. In this analysis, we compare two methods to estimate the association between short birth intervals and mortality risk to better inform modelling efforts linking family planning and mortality in children. Our goal was to estimate the mortality risk for neonates, infants, and young children by preceding birth space using household survey data, controlling for mother-level factors and to compare the results to those from previous analyses with survey data. We assessed the potential for confounding when estimating the relative mortality risk by preceding birth interval and estimated mortality risk by birth interval in four categories: less than 18 months, 18-23 months, 24-35 months, and 36 months or longer. We estimated the relative risks among women who were 35 and older at the time of the survey with two methods: in a Cox proportional hazards regression adjusting for potential confounders and also by stratifying Cox regression by mother, to control for all factors that remain constant over a woman's childbearing years. We estimated the overall effects for birth spacing in a meta-analysis with random survey effects. We identified several factors known for their associations with neonatal, infant, and child mortality that are also associated with preceding birth interval. When estimating the effect of birth spacing on mortality, we found that regression adjustment for these factors does not substantially change the risk ratio for short birth intervals compared to an unadjusted mortality ratio. For birth intervals less than 18 months, standard regression adjustment for confounding factors estimated a risk ratio for neonatal mortality of 2.28 (95% confidence interval: 2.18-2.37). This same effect estimated within mother is 1.57 (95% confidence interval: 1.52-1.63), a decline of almost one-third in the effect on neonatal mortality. Neonatal, infant, and child mortality are strongly and significantly related to preceding birth interval, where births within a short interval of time after the previous birth have increased mortality. Previous analyses have demonstrated this relationship on average across all births; however, women who have short spaces between births are different from women with long spaces. Among women 35 years and older where a comparison of birth spaces within mother is possible, we find a much reduced although still significant effect of short birth spaces on child mortality.

Digital soil mapping using remote sensing indices, terrain attributes, and vegetation features in the rangelands of northeastern Iran.

PubMed

Mahmoudabadi, Ebrahim; Karimi, Alireza; Haghnia, Gholam Hosain; Sepehr, Adel

2017-09-11

Digital soil mapping has been introduced as a viable alternative to the traditional mapping methods due to being fast and cost-effective. The objective of the present study was to investigate the capability of the vegetation features and spectral indices as auxiliary variables in digital soil mapping models to predict soil properties. A region with an area of 1225 ha located in Bajgiran rangelands, Khorasan Razavi province, northeastern Iran, was chosen. A total of 137 sampling sites, each containing 3-5 plots with 10-m interval distance along a transect established based on randomized-systematic method, were investigated. In each plot, plant species names and numbers as well as vegetation cover percentage (VCP) were recorded, and finally one composite soil sample was taken from each transect at each site (137 soil samples in total). Terrain attributes were derived from a digital elevation model, different bands and spectral indices were obtained from the Landsat7 ETM+ images, and vegetation features were calculated in the plots, all of which were used as auxiliary variables to predict soil properties using artificial neural network, gene expression programming, and multivariate linear regression models. According to R 2 RMSE and MBE values, artificial neutral network was obtained as the most accurate soil properties prediction function used in scorpan model. Vegetation features and indices were more effective than remotely sensed data and terrain attributes in predicting soil properties including calcium carbonate equivalent, clay, bulk density, total nitrogen, carbon, sand, silt, and saturated moisture capacity. It was also shown that vegetation indices including NDVI, SAVI, MSAVI, SARVI, RDVI, and DVI were more effective in estimating the majority of soil properties compared to separate bands and even some soil spectral indices.

Detection of anomalous crop condition and soil variability mapping using a 26 year Landsat record and the Palmer crop moisture index

NASA Astrophysics Data System (ADS)

Venteris, E. R.; Tagestad, J. D.; Downs, J. L.; Murray, C. J.

2015-07-01

Cost-effective and reliable vegetation monitoring methods are needed for applications ranging from traditional agronomic mapping, to verifying the safety of geologic injection activities. A particular challenge is defining baseline crop conditions and subsequent anomalies from long term imagery records (Landsat) in the face of large spatiotemporal variability. We develop a new method for defining baseline crop response (near peak growth) using the normalized difference vegetation index (NDVI) from 26 years (1986-2011) of Landsat data for 400 km2 surrounding a planned geologic carbon sequestration site near Jacksonville, Illinois. The normal score transform (yNDVI) was applied on a field by field basis to accentuate spatial patterns and level differences due to planting times. We tested crop type and soil moisture (Palmer crop moisture index (CMI)) as predictors of expected crop condition. Spatial patterns in yNDVI were similar between corn and soybeans - the two major crops. Linear regressions between yNDVI and the cumulative CMI (CCMI) exposed complex interactions between crop condition, field location (topography and soils), and annual moisture. Wet toposequence positions (depressions) were negatively correlated to CCMI and dry positions (crests) positively correlated. However, only 21% of the landscape showed a statistically significant (p < 0.05) linear relationship. To map anomalous crop conditions, we defined a tolerance interval based on yNDVI statistics. Tested on an independent image (2013), 63 of 1483 possible fields showed unusual crop condition. While the method is not directly suitable for crop health assessment, the spatial patterns in correlation between yNDVI and CCMI have potential applications for pest damage detection and edaphological soil mapping, especially in the developing world.

Relationship between long-term exposure to low-level arsenic in drinking water and the prevalence of abnormal blood pressure.

PubMed

Zhang, Chuanwu; Mao, Guangyun; He, Suxia; Yang, Zuopeng; Yang, Wei; Zhang, Xiaojing; Qiu, Wenting; Ta, Na; Cao, Li; Yang, Hui; Guo, Xiaojuan

2013-11-15

Arsenic increases the risk and incidence of cardiovascular disease. To explore the impact of long-term exposure to low-level arsenic in drinking water on blood pressure including pulse pressure (PP) and mean arterial blood pressure (MAP), a cross-sectional study was conducted in 2010 in which the blood pressure of 405 villagers was measured, who had been drinking water with an inorganic arsenic content <50 μg/L. A multivariate logistic regression model was used to estimate odds ratios and 95% confidence intervals. After adjusting for age, gender, Body Mass Index (BMI), alcohol consumption and smoking, the odds ratios showed a 1.45-fold (95%CI: 0.63-3.35) increase in the group with >30-50 years of arsenic exposure and a 2.95-fold (95%CI: 1.31-6.67) increase in the group with >50 years exposure. Furthermore, the odds ratio for prevalence of abnormal PP and MAP were 1.06 (95%CI: 0.24-4.66) and 0.87 (95%CI: 0.36-2.14) in the group with >30-50 years of exposure, and were 2.46 (95%CI: 0.87-6.97) and 3.75 (95%CI: 1.61-8.71) for the group with >50 years exposure, compared to the group with arsenic exposure ≤ 30 years respectively. Significant trends for Hypertension (p<0.0001), PP (p<0.0001) and MAP (p=0.0016) were found. The prevalence of hypertension and abnormal PP as well as MAP is marked among a low-level arsenic exposure population, and significantly increases with the duration of arsenic exposure. Copyright © 2012 Elsevier B.V. All rights reserved.

Application of laboratory reflectance spectroscopy to target and map expansive soils: example of the western Loiret, France

NASA Astrophysics Data System (ADS)

Hohmann, Audrey; Dufréchou, Grégory; Grandjean, Gilles; Bourguignon, Anne

2014-05-01

Swelling soils contain clay minerals that change volume with water content and cause extensive and expensive damage on infrastructures. Based on spatial distribution of infrastructure damages and existing geological maps, the Bureau de Recherches Géologiques et Minières (BRGM, i.e. the French Geological Survey) published in 2010 a 1:50 000 swelling hazard map of France, indexing the territory to low, moderate, or high swelling risk. This study aims to use SWIR (1100-2500 nm) reflectance spectra of soils acquired under laboratory controlled conditions to estimate the swelling potential of soils and improve the swelling risk map of France. 332 samples were collected at the W of Orléans (France) in various geological formations and swelling risk areas. Comparisons of swelling potential of soil samples and swelling risk areas of the map show several inconsistent associations that confirm the necessity to redraw the actual swelling risk map of France. New swelling risk maps of the sampling area were produce from soil samples using three interpolation methods. Maps produce using kriging and Natural neighbour interpolation methods did not permit to show discrete lithological units, introduced unsupported swelling risk zones, and did not appear useful to refine swelling risk map of France. Voronoi polygon was also used to produce map where swelling potential estimated from each samples were extrapolated to a polygon and all polygons were thus supported by field information. From methods tested here, Voronoi polygon appears thus the most adapted method to produce expansive soils maps. However, size of polygon is highly dependent of the samples spacing and samples may not be representative of the entire polygon. More samples are thus needed to provide reliable map at the scale of the sampling area. Soils were also sampled along two sections with a sampling interval of ca. 260 m and ca. 50 m. Sample interval of 50 m appears more adapted for mapping of smallest lithological units. The presence of several samples close to themselves indicating the same swelling potential is a good indication of the presence of a zone with constant swelling potential. Combination of Voronoi method and sampling interval of ca. 50 m appear adapted to produce local swelling potential maps in areas where doubt remain or where infrastructure damages attributed to expansive soils are knew.

Maternal steroid therapy for fetuses with second-degree immune-mediated congenital atrioventricular block: a systematic review and meta-analysis.

PubMed

Ciardulli, Andrea; D'Antonio, Francesco; Magro-Malosso, Elena R; Manzoli, Lamberto; Anisman, Paul; Saccone, Gabriele; Berghella, Vincenzo

2018-03-07

To explore the effect of maternal fluorinated steroid therapy on fetuses affected by second-degree immune-mediated congenital atrioventricular block. Studies reporting the outcome of fetuses with second-degree immune-mediated congenital atrioventricular block diagnosed on prenatal ultrasound and treated with fluorinated steroids compared with those not treated were included. The primary outcome was the overall progression of congenital atrioventricular block to either continuous or intermittent third-degree congenital atrioventricular block at birth. Meta-analyses of proportions using random effect model and meta-analyses using individual data random-effect logistic regression were used. Five studies (71 fetuses) were included. The progression rate to congenital atrioventricular block at birth in fetuses treated with steroids was 52% (95% confidence interval 23-79) and in fetuses not receiving steroid therapy 73% (95% confidence interval 39-94). The overall rate of regression to either first-degree, intermittent first-/second-degree or sinus rhythm in fetuses treated with steroids was 25% (95% confidence interval 12-41) compared with 23% (95% confidence interval 8-44) in those not treated. Stable (constant) second-degree congenital atrioventricular block at birth was present in 11% (95% confidence interval 2-27) of cases in the treated group and in none of the newborns in the untreated group, whereas complete regression to sinus rhythm occurred in 21% (95% confidence interval 6-42) of fetuses receiving steroids vs. 9% (95% confidence interval 0-41) of those untreated. There is still limited evidence as to the benefit of administered fluorinated steroids in terms of affecting outcome of fetuses with second-degree immune-mediated congenital atrioventricular block. © 2018 Nordic Federation of Societies of Obstetrics and Gynecology.

A new algorithm for segmentation of cardiac quiescent phases and cardiac time intervals using seismocardiography

NASA Astrophysics Data System (ADS)

Jafari Tadi, Mojtaba; Koivisto, Tero; Pänkäälä, Mikko; Paasio, Ari; Knuutila, Timo; Teräs, Mika; Hänninen, Pekka

2015-03-01

Systolic time intervals (STI) have significant diagnostic values for a clinical assessment of the left ventricle in adults. This study was conducted to explore the feasibility of using seismocardiography (SCG) to measure the systolic timings of the cardiac cycle accurately. An algorithm was developed for the automatic localization of the cardiac events (e.g. the opening and closing moments of the aortic and mitral valves). Synchronously acquired SCG and electrocardiography (ECG) enabled an accurate beat to beat estimation of the electromechanical systole (QS2), pre-ejection period (PEP) index and left ventricular ejection time (LVET) index. The performance of the algorithm was evaluated on a healthy test group with no evidence of cardiovascular disease (CVD). STI values were corrected based on Weissler's regression method in order to assess the correlation between the heart rate and STIs. One can see from the results that STIs correlate poorly with the heart rate (HR) on this test group. An algorithm was developed to visualize the quiescent phases of the cardiac cycle. A color map displaying the magnitude of SCG accelerations for multiple heartbeats visualizes the average cardiac motions and thereby helps to identify quiescent phases. High correlation between the heart rate and the duration of the cardiac quiescent phases was observed.

Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion

NASA Astrophysics Data System (ADS)

Jokar Arsanjani, Jamal; Helbich, Marco; Kainz, Wolfgang; Darvishi Boloorani, Ali

2013-04-01

This research analyses the suburban expansion in the metropolitan area of Tehran, Iran. A hybrid model consisting of logistic regression model, Markov chain (MC), and cellular automata (CA) was designed to improve the performance of the standard logistic regression model. Environmental and socio-economic variables dealing with urban sprawl were operationalised to create a probability surface of spatiotemporal states of built-up land use for the years 2006, 2016, and 2026. For validation, the model was evaluated by means of relative operating characteristic values for different sets of variables. The approach was calibrated for 2006 by cross comparing of actual and simulated land use maps. The achieved outcomes represent a match of 89% between simulated and actual maps of 2006, which was satisfactory to approve the calibration process. Thereafter, the calibrated hybrid approach was implemented for forthcoming years. Finally, future land use maps for 2016 and 2026 were predicted by means of this hybrid approach. The simulated maps illustrate a new wave of suburban development in the vicinity of Tehran at the western border of the metropolis during the next decades.

Mathematical models application for mapping soils spatial distribution on the example of the farm from the North of Udmurt Republic of Russia

NASA Astrophysics Data System (ADS)

Dokuchaev, P. M.; Meshalkina, J. L.; Yaroslavtsev, A. M.

2018-01-01

Comparative analysis of soils geospatial modeling using multinomial logistic regression, decision trees, random forest, regression trees and support vector machines algorithms was conducted. The visual interpretation of the digital maps obtained and their comparison with the existing map, as well as the quantitative assessment of the individual soil groups detection overall accuracy and of the models kappa showed that multiple logistic regression, support vector method, and random forest models application with spatial prediction of the conditional soil groups distribution can be reliably used for mapping of the study area. It has shown the most accurate detection for sod-podzolics soils (Phaeozems Albic) lightly eroded and moderately eroded soils. In second place, according to the mean overall accuracy of the prediction, there are sod-podzolics soils - non-eroded and warp one, as well as sod-gley soils (Umbrisols Gleyic) and alluvial soils (Fluvisols Dystric, Umbric). Heavy eroded sod-podzolics and gray forest soils (Phaeozems Albic) were detected by methods of automatic classification worst of all.

Evaluating the perennial stream using logistic regression in central Taiwan

NASA Astrophysics Data System (ADS)

Ruljigaljig, T.; Cheng, Y. S.; Lin, H. I.; Lee, C. H.; Yu, T. T.

2014-12-01

This study produces a perennial stream head potential map, based on a logistic regression method with a Geographic Information System (GIS). Perennial stream initiation locations, indicates the location of the groundwater and surface contact, were identified in the study area from field survey. The perennial stream potential map in central Taiwan was constructed using the relationship between perennial stream and their causative factors, such as Catchment area, slope gradient, aspect, elevation, groundwater recharge and precipitation. Here, the field surveys of 272 streams were determined in the study area. The areas under the curve for logistic regression methods were calculated as 0.87. The results illustrate the importance of catchment area and groundwater recharge as key factors within the model. The results obtained from the model within the GIS were then used to produce a map of perennial stream and estimate the location of perennial stream head.

Estimating Gestational Age With Sonography: Regression-Derived Formula Versus the Fetal Biometric Average.

PubMed

Cawyer, Chase R; Anderson, Sarah B; Szychowski, Jeff M; Neely, Cherry; Owen, John

2018-03-01

To compare the accuracy of a new regression-derived formula developed from the National Fetal Growth Studies data to the common alternative method that uses the average of the gestational ages (GAs) calculated for each fetal biometric measurement (biparietal diameter, head circumference, abdominal circumference, and femur length). This retrospective cross-sectional study identified nonanomalous singleton pregnancies that had a crown-rump length plus at least 1 additional sonographic examination with complete fetal biometric measurements. With the use of the crown-rump length to establish the referent estimated date of delivery, each method's (National Institute of Child Health and Human Development regression versus Hadlock average [Radiology 1984; 152:497-501]), error at every examination was computed. Error, defined as the difference between the crown-rump length-derived GA and each method's predicted GA (weeks), was compared in 3 GA intervals: 1 (14 weeks-20 weeks 6 days), 2 (21 weeks-28 weeks 6 days), and 3 (≥29 weeks). In addition, the proportion of each method's examinations that had errors outside prespecified (±) day ranges was computed by using odds ratios. A total of 16,904 sonograms were identified. The overall and prespecified GA range subset mean errors were significantly smaller for the regression compared to the average (P < .01), and the regression had significantly lower odds of observing examinations outside the specified range of error in GA intervals 2 (odds ratio, 1.15; 95% confidence interval, 1.01-1.31) and 3 (odds ratio, 1.24; 95% confidence interval, 1.17-1.32) than the average method. In a contemporary unselected population of women dated by a crown-rump length-derived GA, the National Institute of Child Health and Human Development regression formula produced fewer estimates outside a prespecified margin of error than the commonly used Hadlock average; the differences were most pronounced for GA estimates at 29 weeks and later. © 2017 by the American Institute of Ultrasound in Medicine.

Isopach map of interval between top of the Pictured Cliffs Sandstone and the Huerfanito Bentonite bed of the Lewis Shale, La Plata County, Colorado, and Rio Arriba and San Juan counties, New Mexico

USGS Publications Warehouse

Sandberg, D.T.

1986-01-01

Data used for the isopach map are mostly from interpretation of geophysical logs of oil and gas wells, southeast of the outcrop in parts of the Cortez, Durango, Farmington, and Navajo Reservoir 1: 100,000-scale quadrangles, Colorado and New Mexico. Cross sections A-A’ and B-B' give examples of geophysical logs that show some of the variations in the isopach interval.

Predicting birth weight with conditionally linear transformation models.

PubMed

Möst, Lisa; Schmid, Matthias; Faschingbauer, Florian; Hothorn, Torsten

2016-12-01

Low and high birth weight (BW) are important risk factors for neonatal morbidity and mortality. Gynecologists must therefore accurately predict BW before delivery. Most prediction formulas for BW are based on prenatal ultrasound measurements carried out within one week prior to birth. Although successfully used in clinical practice, these formulas focus on point predictions of BW but do not systematically quantify uncertainty of the predictions, i.e. they result in estimates of the conditional mean of BW but do not deliver prediction intervals. To overcome this problem, we introduce conditionally linear transformation models (CLTMs) to predict BW. Instead of focusing only on the conditional mean, CLTMs model the whole conditional distribution function of BW given prenatal ultrasound parameters. Consequently, the CLTM approach delivers both point predictions of BW and fetus-specific prediction intervals. Prediction intervals constitute an easy-to-interpret measure of prediction accuracy and allow identification of fetuses subject to high prediction uncertainty. Using a data set of 8712 deliveries at the Perinatal Centre at the University Clinic Erlangen (Germany), we analyzed variants of CLTMs and compared them to standard linear regression estimation techniques used in the past and to quantile regression approaches. The best-performing CLTM variant was competitive with quantile regression and linear regression approaches in terms of conditional coverage and average length of the prediction intervals. We propose that CLTMs be used because they are able to account for possible heteroscedasticity, kurtosis, and skewness of the distribution of BWs. © The Author(s) 2014.

Visualizing the Logistic Map with a Microcontroller

ERIC Educational Resources Information Center

Serna, Juan D.; Joshi, Amitabh

2012-01-01

The logistic map is one of the simplest nonlinear dynamical systems that clearly exhibits the route to chaos. In this paper, we explore the evolution of the logistic map using an open-source microcontroller connected to an array of light-emitting diodes (LEDs). We divide the one-dimensional domain interval [0,1] into ten equal parts, an associate…

Use of single nucleotide polymorphisms (SNP) to fine-map quantitative trait loci (QTL) in swine

USDA-ARS?s Scientific Manuscript database

Mapping quantitative trait loci (QTL) in swine at the US Meat Animal Research Center has relied heavily on linkage mapping in either F2 or Backcross families. QTL identified in the initial scans typically have very broad confidence intervals and further refinement of the QTL’s position is needed bef...

Newer classification and regression tree techniques: Bagging and Random Forests for ecological prediction

Treesearch

Anantha M. Prasad; Louis R. Iverson; Andy Liaw; Andy Liaw

2006-01-01

We evaluated four statistical models - Regression Tree Analysis (RTA), Bagging Trees (BT), Random Forests (RF), and Multivariate Adaptive Regression Splines (MARS) - for predictive vegetation mapping under current and future climate scenarios according to the Canadian Climate Centre global circulation model.

An ultra-high density linkage map and QTL mapping for sex and growth-related traits of common carp (Cyprinus carpio)

PubMed Central

Peng, Wenzhu; Xu, Jian; Zhang, Yan; Feng, Jianxin; Dong, Chuanju; Jiang, Likun; Feng, Jingyan; Chen, Baohua; Gong, Yiwen; Chen, Lin; Xu, Peng

2016-01-01

High density genetic linkage maps are essential for QTL fine mapping, comparative genomics and high quality genome sequence assembly. In this study, we constructed a high-density and high-resolution genetic linkage map with 28,194 SNP markers on 14,146 distinct loci for common carp based on high-throughput genotyping with the carp 250 K single nucleotide polymorphism (SNP) array in a mapping family. The genetic length of the consensus map was 10,595.94 cM with an average locus interval of 0.75 cM and an average marker interval of 0.38 cM. Comparative genomic analysis revealed high level of conserved syntenies between common carp and the closely related model species zebrafish and medaka. The genome scaffolds were anchored to the high-density linkage map, spanning 1,357 Mb of common carp reference genome. QTL mapping and association analysis identified 22 QTLs for growth-related traits and 7 QTLs for sex dimorphism. Candidate genes underlying growth-related traits were identified, including important regulators such as KISS2, IGF1, SMTLB, NPFFR1 and CPE. Candidate genes associated with sex dimorphism were also identified including 3KSR and DMRT2b. The high-density and high-resolution genetic linkage map provides an important tool for QTL fine mapping and positional cloning of economically important traits, and improving common carp genome assembly. PMID:27225429

Assessing landslide susceptibility by statistical data analysis and GIS: the case of Daunia (Apulian Apennines, Italy)

NASA Astrophysics Data System (ADS)

Ceppi, C.; Mancini, F.; Ritrovato, G.

2009-04-01

This study aim at the landslide susceptibility mapping within an area of the Daunia (Apulian Apennines, Italy) by a multivariate statistical method and data manipulation in a Geographical Information System (GIS) environment. Among the variety of existing statistical data analysis techniques, the logistic regression was chosen to produce a susceptibility map all over an area where small settlements are historically threatened by landslide phenomena. By logistic regression a best fitting between the presence or absence of landslide (dependent variable) and the set of independent variables is performed on the basis of a maximum likelihood criterion, bringing to the estimation of regression coefficients. The reliability of such analysis is therefore due to the ability to quantify the proneness to landslide occurrences by the probability level produced by the analysis. The inventory of dependent and independent variables were managed in a GIS, where geometric properties and attributes have been translated into raster cells in order to proceed with the logistic regression by means of SPSS (Statistical Package for the Social Sciences) package. A landslide inventory was used to produce the bivariate dependent variable whereas the independent set of variable concerned with slope, aspect, elevation, curvature, drained area, lithology and land use after their reductions to dummy variables. The effect of independent parameters on landslide occurrence was assessed by the corresponding coefficient in the logistic regression function, highlighting a major role played by the land use variable in determining occurrence and distribution of phenomena. Once the outcomes of the logistic regression are determined, data are re-introduced in the GIS to produce a map reporting the proneness to landslide as predicted level of probability. As validation of results and regression model a cell-by-cell comparison between the susceptibility map and the initial inventory of landslide events was performed and an agreement at 75% level achieved.

An analysis of first-time blood donors return behaviour using regression models.

PubMed

Kheiri, S; Alibeigi, Z

2015-08-01

Blood products have a vital role in saving many patients' lives. The aim of this study was to analyse blood donor return behaviour. Using a cross-sectional follow-up design of 5-year duration, 864 first-time donors who had donated blood were selected using a systematic sampling. The behaviours of donors via three response variables, return to donation, frequency of return to donation and the time interval between donations, were analysed based on logistic regression, negative binomial regression and Cox's shared frailty model for recurrent events respectively. Successful return to donation rated at 49·1% and the deferral rate was 13·3%. There was a significant reverse relationship between the frequency of return to donation and the time interval between donations. Sex, body weight and job had an effect on return to donation; weight and frequency of donation during the first year had a direct effect on the total frequency of donations. Age, weight and job had a significant effect on the time intervals between donations. Aging decreases the chances of return to donation and increases the time interval between donations. Body weight affects the three response variables, i.e. the higher the weight, the more the chances of return to donation and the shorter the time interval between donations. There is a positive correlation between the frequency of donations in the first year and the total number of return to donations. Also, the shorter the time interval between donations is, the higher the frequency of donations. © 2015 British Blood Transfusion Society.

Immobilization of Cellulase from Bacillus subtilis UniMAP-KB01 on Multi-walled Carbon Nanotubes for Biofuel Production

NASA Astrophysics Data System (ADS)

Naresh, Sandrasekaran; Hoong Shuit, Siew; Kunasundari, Balakrishnan; Hoo Peng, Yong; Qi, Hwa Ng; Teoh, Yi Peng

2018-03-01

Bacillus subtilis UniMAP-KB01, a cellulase producer was isolated from Malaysian mangrove soil. Through morphological identification it was observed that the B. subtilis appears to be in rod shaped and identified as a gram positive bacterium. Growth profile of isolated B. subtilis was established by measuring optical density (OD) at 600 nm for every 1 hour intervals. Polymath software was employed to plot the growth profile and the non-linear plot established gave the precision value of linear regression, R2 of 0.9602, root mean square deviation (RMSD) of 0.0176 and variance of 0.0025. The hydrolysis capacity testing revealed the cellulolytic index of 2.83 ± 0.46 after stained with Gram’s Iodine. The harvested crude enzyme after 24 hours incubation in carboxymethylcellulose (CMC) broth at 45°C and 100 RPM, was tested for enzyme activity. Through Filter Paper Assay (FPA), the cellulase activity was calculated to be 0.05 U/mL. The hydrolysis capacity testing and FPA shown an acceptable value for thermophilic bacterial enzyme activity. Thus, this isolated strain reasoned to be potential for producing thermostable cellulase which will be immobilized onto multi-walled carbon nanotubes and the cellulolytic activity will be characterized for biofuel production.

A simple linear regression method for quantitative trait loci linkage analysis with censored observations.

PubMed

Anderson, Carl A; McRae, Allan F; Visscher, Peter M

2006-07-01

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.

Examination of Parameters Affecting the House Prices by Multiple Regression Analysis and its Contributions to Earthquake-Based Urban Transformation

NASA Astrophysics Data System (ADS)

Denli, H. H.; Durmus, B.

2016-12-01

The purpose of this study is to examine the factors which may affect the apartment prices with multiple linear regression analysis models and visualize the results by value maps. The study is focused on a county of Istanbul - Turkey. Totally 390 apartments around the county Umraniye are evaluated due to their physical and locational conditions. The identification of factors affecting the price of apartments in the county with a population of approximately 600k is expected to provide a significant contribution to the apartment market.Physical factors are selected as the age, number of rooms, size, floor numbers of the building and the floor that the apartment is positioned in. Positional factors are selected as the distances to the nearest hospital, school, park and police station. Totally ten physical and locational parameters are examined by regression analysis.After the regression analysis has been performed, value maps are composed from the parameters age, price and price per square meters. The most significant of the composed maps is the price per square meters map. Results show that the location of the apartment has the most influence to the square meter price information of the apartment. A different practice is developed from the composed maps by searching the ability of using price per square meters map in urban transformation practices. By marking the buildings older than 15 years in the price per square meters map, a different and new interpretation has been made to determine the buildings, to which should be given priority during an urban transformation in the county.This county is very close to the North Anatolian Fault zone and is under the threat of earthquakes. By marking the apartments older than 15 years on the price per square meters map, both older and expensive square meters apartments list can be gathered. By the help of this list, the priority could be given to the selected higher valued old apartments to support the economy of the country during an earthquake loss. We may call this urban transformation as earthquake-based urban transformation.

Comparison of methods for the prediction of human clearance from hepatocyte intrinsic clearance for a set of reference compounds and an external evaluation set.

PubMed

Yamagata, Tetsuo; Zanelli, Ugo; Gallemann, Dieter; Perrin, Dominique; Dolgos, Hugues; Petersson, Carl

2017-09-01

1. We compared direct scaling, regression model equation and the so-called "Poulin et al." methods to scale clearance (CL) from in vitro intrinsic clearance (CL int ) measured in human hepatocytes using two sets of compounds. One reference set comprised of 20 compounds with known elimination pathways and one external evaluation set based on 17 compounds development in Merck (MS). 2. A 90% prospective confidence interval was calculated using the reference set. This interval was found relevant for the regression equation method. The three outliers identified were justified on the basis of their elimination mechanism. 3. The direct scaling method showed a systematic underestimation of clearance in both the reference and evaluation sets. The "Poulin et al." and the regression equation methods showed no obvious bias in either the reference or evaluation sets. 4. The regression model equation was slightly superior to the "Poulin et al." method in the reference set and showed a better absolute average fold error (AAFE) of value 1.3 compared to 1.6. A larger difference was observed in the evaluation set were the regression method and "Poulin et al." resulted in an AAFE of 1.7 and 2.6, respectively (removing the three compounds with known issues mentioned above). A similar pattern was observed for the correlation coefficient. Based on these data we suggest the regression equation method combined with a prospective confidence interval as the first choice for the extrapolation of human in vivo hepatic metabolic clearance from in vitro systems.

Using a binary logistic regression method and GIS for evaluating and mapping the groundwater spring potential in the Sultan Mountains (Aksehir, Turkey)

NASA Astrophysics Data System (ADS)

Ozdemir, Adnan

2011-07-01

SummaryThe purpose of this study is to produce a groundwater spring potential map of the Sultan Mountains in central Turkey, based on a logistic regression method within a Geographic Information System (GIS) environment. Using field surveys, the locations of the springs (440 springs) were determined in the study area. In this study, 17 spring-related factors were used in the analysis: geology, relative permeability, land use/land cover, precipitation, elevation, slope, aspect, total curvature, plan curvature, profile curvature, wetness index, stream power index, sediment transport capacity index, distance to drainage, distance to fault, drainage density, and fault density map. The coefficients of the predictor variables were estimated using binary logistic regression analysis and were used to calculate the groundwater spring potential for the entire study area. The accuracy of the final spring potential map was evaluated based on the observed springs. The accuracy of the model was evaluated by calculating the relative operating characteristics. The area value of the relative operating characteristic curve model was found to be 0.82. These results indicate that the model is a good estimator of the spring potential in the study area. The spring potential map shows that the areas of very low, low, moderate and high groundwater spring potential classes are 105.586 km 2 (28.99%), 74.271 km 2 (19.906%), 101.203 km 2 (27.14%), and 90.05 km 2 (24.671%), respectively. The interpretations of the potential map showed that stream power index, relative permeability of lithologies, geology, elevation, aspect, wetness index, plan curvature, and drainage density play major roles in spring occurrence and distribution in the Sultan Mountains. The logistic regression approach has not yet been used to delineate groundwater potential zones. In this study, the logistic regression method was used to locate potential zones for groundwater springs in the Sultan Mountains. The evolved model was found to be in strong agreement with the available groundwater spring test data. Hence, this method can be used routinely in groundwater exploration under favourable conditions.

Fragile--Handle with Care: Regression Analyses That Include Categorical Data.

ERIC Educational Resources Information Center

Brown, Diane Peacock

In education and the social sciences, problems of interest to researchers and users of research often involve variables that do not meet the assumptions of regression in the area of an equal interval scale relative to a zero point. Various coding schemes exist that allow the use of regression while still answering the researcher's questions of…

Economic benefits of reducing fire-related sediment in southwestern fire-prone ecosystems

Treesearch

John Loomis; Pete Wohlgemuth; Armando González-Cabán; Don English

2003-01-01

A multiple regression analysis of fire interval and resulting sediment yield (controlling for relief ratio, rainfall, etc.) indicates that reducing the fire interval from the current average 22 years to a prescribed fire interval of 5 years would reduce sediment yield by 2 million cubic meters in the 86.2 square kilometer southern California watershed adjacent to and...

Mapping soil texture targeting predefined depth range or synthetizing from standard layers?

NASA Astrophysics Data System (ADS)

Laborczi, Annamária; Dezső Kaposi, András; Szatmári, Gábor; Takács, Katalin; Pásztor, László

2017-04-01

There are increasing demands nowadays on spatial soil information in order to support environmental related and land use management decisions. Physical soil properties, especially particle size distribution play important role in this context. A few of the requirements can be satisfied by the sand-, silt-, and clay content maps compiled according to global standards such as GlobalSoilMap (GSM) or Soil Grids. Soil texture classes (e. g. according to USDA classification) can be derived from these three fraction data, in this way texture map can be compiled based on the proper separate maps. Soil texture class as well as fraction information represent direct input of crop-, meteorological- and hydrological models. The model inputs frequently require maps representing soil features of 0-30 cm depth, which is covered by three consecutive depth intervals according to standard specifications: 0-5 cm, 5-15 cm, 15-30 cm. Becoming GSM and SoilGrids the most detailed freely available spatial soil data sources, the common model users (e. g. meteorologists, agronomists, or hydrologists) would produce input map from (the weighted mean of) these three layers. However, if the basic soil data and proper knowledge is obtainable, a soil texture map targeting directly the 0-30 cm layer could be independently compiled. In our work we compared Hungary's soil texture maps compiled using the same reference and auxiliary data and inference methods but for differing layer distribution. We produced the 0-30 cm clay, silt and sand map as well as the maps for the three standard layers (0-5 cm, 5-15 cm, 15-30 cm). Maps of sand, silt and clay percentage were computed through regression kriging (RK) applying Additive Log-Ratio (alr) transformation. In addition to the Hungarian Soil Information and Monitoring System as reference soil data, digital elevation model and its derived components, soil physical property maps, remotely sensed images, land use -, geological-, as well as meteorological data were applied as auxiliary variables. We compared the directly compiled and the synthetized clay-, sand content, and texture class maps by different tools. In addition to pairwise comparison of basic statistical features (histograms, scatter plots), we examined the spatial distribution of the differences. We quantified the taxonomical distances of the textural classes, in order to investigate the differences of the map-pairs. We concluded that the directly computed and the synthetized maps show various differences. In the case of clay-, and sand content maps, the map-pairs have to be considered statistically different. On the other hand, the differences of the texture class maps are not significant. However, in all cases, the differences rather concern the extreme ranges and categories. Using of synthetized maps can intensify extremities by error propagation in models and scenarios. Based on our results, we suggest the usage of the directly composed maps.

Assessment of risk factors for cerebral oxygen desaturation during neonatal and infant general anesthesia: an observational, prospective study.

PubMed

Razlevice, Ilona; Rugyte, Danguole C; Strumylaite, Loreta; Macas, Andrius

2016-10-28

Cerebral oxygen saturation (rSO 2 c) decrease from baseline greater than 20 % during infant cardiac surgery was associated with postoperative neurologic changes and neurodevelopmental impairment at 1 year of age. So far, there is no sufficient evidence to support the routine monitoring of rSO 2 c during general surgical procedures in children. We aimed to find out the frequency of cerebral desaturation 20 % or more from baseline and to identify possible predictors of change in cerebral oxygen saturation during neonatal and infant general surgery. Forty-four infants up to 3 months of age were recruited. Before induction of anesthesia, two pediatric cerebral sensors were placed bilaterally to the forehead region and monitoring of regional cerebral saturation of oxygen was started and continued throughout the surgery. Simultaneously, mean arterial blood pressure (MAP), pulse oximetry (SpO 2 ), heart rate (HR), endtidal CO 2 , expired fraction of sevoflurane and rectal temperature were recorded. The main outcome measure was rSO 2 c value drop-off ≥20 % from baseline. Mann-Whitney U-test, chi-squared test, simple and multiple linear regression models were used for statistical analysis. Forty-three infants were analyzed. Drop-off ≥20 % in rSO 2 c from baseline occurred in 8 (18.6 %) patients. There were no differences in basal rSO 2 c, SpO 2 , HR, endtidal CO 2 , expired fraction of sevoflurane and rectal temperature between patients with and without desaturation 20 % or more from baseline. But the two groups differed with regard to gestation, preoperative mechanical ventilation and the use of vasoactive medications and red blood cell transfusions during surgery. Simple linear regression model showed, that gestation, age, preoperative mechanical ventilation and mean arterial pressure corresponding to minimal rSO 2 c value during anesthesia (MAP minrSO2c ) were associated with a change in rSO 2 c values. Multiple regression model including all above mentioned variables, revealed that only MAP minrSO2c was predictive for a change in rSO 2 c values (β (95 % confidence interval) -0.28 (-0.52-(-0.04)) p = 0.02). Cerebral oxygen desaturation ≥20 % from baseline occurred in almost one fifth of patients. Although different perioperative factors can predispose to cerebral oxygenation changes, arterial blood pressure seems to be the most important. Gestation as another possible risk factor needs further investigation. The international registration number NCT02423369 . Retrospectively registered on April 2015.

Evaluation of using digital gravity field models for zoning map creation

NASA Astrophysics Data System (ADS)

Loginov, Dmitry

2018-05-01

At the present time the digital cartographic models of geophysical fields are taking a special significance into geo-physical mapping. One of the important directions to their application is the creation of zoning maps, which allow taking into account the morphology of geophysical field in the implementation automated choice of contour intervals. The purpose of this work is the comparative evaluation of various digital models in the creation of integrated gravity field zoning map. For comparison were chosen the digital model of gravity field of Russia, created by the analog map with scale of 1 : 2 500 000, and the open global model of gravity field of the Earth - WGM2012. As a result of experimental works the four integrated gravity field zoning maps were obtained with using raw and processed data on each gravity field model. The study demonstrates the possibility of open data use to create integrated zoning maps with the condition to eliminate noise component of model by processing in specialized software systems. In this case, for solving problem of contour intervals automated choice the open digital models aren't inferior to regional models of gravity field, created for individual countries. This fact allows asserting about universality and independence of integrated zoning maps creation regardless of detail of a digital cartographic model of geo-physical fields.

Techniques for Estimating the Magnitude and Frequency of Peak Flows on Small Streams in Minnesota Based on Data through Water Year 2005

USGS Publications Warehouse

Lorenz, David L.; Sanocki, Chris A.; Kocian, Matthew J.

2010-01-01

Knowledge of the peak flow of floods of a given recurrence interval is essential for regulation and planning of water resources and for design of bridges, culverts, and dams along Minnesota's rivers and streams. Statistical techniques are needed to estimate peak flow at ungaged sites because long-term streamflow records are available at relatively few places. Because of the need to have up-to-date peak-flow frequency information in order to estimate peak flows at ungaged sites, the U.S. Geological Survey (USGS) conducted a peak-flow frequency study in cooperation with the Minnesota Department of Transportation and the Minnesota Pollution Control Agency. Estimates of peak-flow magnitudes for 1.5-, 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals are presented for 330 streamflow-gaging stations in Minnesota and adjacent areas in Iowa and South Dakota based on data through water year 2005. The peak-flow frequency information was subsequently used in regression analyses to develop equations relating peak flows for selected recurrence intervals to various basin and climatic characteristics. Two statistically derived techniques-regional regression equation and region of influence regression-can be used to estimate peak flow on ungaged streams smaller than 3,000 square miles in Minnesota. Regional regression equations were developed for selected recurrence intervals in each of six regions in Minnesota: A (northwestern), B (north central and east central), C (northeastern), D (west central and south central), E (southwestern), and F (southeastern). The regression equations can be used to estimate peak flows at ungaged sites. The region of influence regression technique dynamically selects streamflow-gaging stations with characteristics similar to a site of interest. Thus, the region of influence regression technique allows use of a potentially unique set of gaging stations for estimating peak flow at each site of interest. Two methods of selecting streamflow-gaging stations, similarity and proximity, can be used for the region of influence regression technique. The regional regression equation technique is the preferred technique as an estimate of peak flow in all six regions for ungaged sites. The region of influence regression technique is not appropriate for regions C, E, and F because the interrelations of some characteristics of those regions do not agree with the interrelations throughout the rest of the State. Both the similarity and proximity methods for the region of influence technique can be used in the other regions (A, B, and D) to provide additional estimates of peak flow. The peak-flow-frequency estimates and basin characteristics for selected streamflow-gaging stations and regional peak-flow regression equations are included in this report.

Construction of a high-density genetic map and lint percentage and cottonseed nutrient trait QTL identification in upland cotton (Gossypium hirsutum L.).

PubMed

Liu, Dexin; Liu, Fang; Shan, Xiaoru; Zhang, Jian; Tang, Shiyi; Fang, Xiaomei; Liu, Xueying; Wang, Wenwen; Tan, Zhaoyun; Teng, Zhonghua; Zhang, Zhengsheng; Liu, Dajun

2015-10-01

Upland cotton plays a critical role not only in the textile industry, but also in the production of important secondary metabolites, such as oil and proteins. Construction of a high-density linkage map and identifying yield and seed trait quantitative trail loci (QTL) are prerequisites for molecular marker-assisted selective breeding projects. Here, we update a high-density upland cotton genetic map from recombinant inbred lines. A total of 25,313 SSR primer pairs were screened for polymorphism between Yumian 1 and T586, and 1712 SSR primer pairs were used to genotype the mapping population and construct a map. An additional 1166 loci have been added to our previously published map with 509 SSR markers. The updated genetic map spans a total recombinant length of 3338.2 cM and contains 1675 SSR loci and nine morphological markers, with an average interval of 1.98 cM between adjacent markers. Green lint (Lg) mapped on chromosome 15 in a previous report is mapped in an interval of 2.6 cM on chromosome 21. Based on the map and phenotypic data from multiple environments, 79 lint percentage and seed nutrient trait QTL are detected. These include 8 lint percentage, 13 crude protein, 15 crude oil, 8 linoleic, 10 oleic, 13 palmitic, and 12 stearic acid content QTL. They explain 3.5-62.7 % of the phenotypic variation observed. Four morphological markers identified have a major impact on lint percentage and cottonseed nutrients traits. In this study, our genetic map provides new sights into the tetraploid cotton genome. Furthermore, the stable QTL and morphological markers could be used for fine-mapping and map-based cloning.

A 2.5-Mb contig constructed from Angus, Longhorn and horned Hereford DNA spanning the polled interval on bovine chromosome 1.

PubMed

Wunderlich, K R; Abbey, C A; Clayton, D R; Song, Y; Schein, J E; Georges, M; Coppieters, W; Adelson, D L; Taylor, J F; Davis, S L; Gill, C A

2006-12-01

The polled locus has been mapped by genetic linkage analysis to the proximal region of bovine chromosome 1. As an intermediate step in our efforts to identify the polled locus and the underlying causative mutation for the polled phenotype, we have constructed a BAC-based physical map of the interval containing the polled locus. Clones containing genes and markers in the critical interval were isolated from the TAMBT (constructed from Angus and Longhorn genomic DNA) and CHORI-240 (constructed from horned Hereford genomic DNA) BAC libraries and ordered based on fingerprinting and the presence or absence of 80 STS markers. A single contig spanning 2.5 Mb was assembled. Comparison of the physical order of STSs to the corresponding region of human chromosome 21 revealed the same order of genes within the polled critical interval. This contig of overlapping BAC clones from horned and polled breeds is a useful resource for SNP discovery and characterization of positional candidate genes.

The concept of psychological regression: metaphors, mapping, Queen Square, and Tavistock Square.

PubMed

Mercer, Jean

2011-05-01

The term "regression" refers to events in which an individual changes from his or her present level of maturity and regains mental and behavioral characteristics shown at an earlier point in development. This definition has remained constant for over a century, but the implications of the concept have changed systematically from a perspective in which regression was considered pathological, to a current view in which regression may be seen as a positive step in psychotherapy or as a part of normal development. The concept of regression, famously employed by Sigmund Freud and others in his circle, derived from ideas suggested by Herbert Spencer and by John Hughlings Jackson. By the 1940s and '50s, the regression concept was applied by Winnicott and others in treatment of disturbed children and in adult psychotherapy. In addition, behavioral regression came to be seen as a part of a normal developmental trajectory, with a focus on expectable variability. The present article examines historical changes in the regression concept in terms of mapping to biomedical or other metaphors, in terms of a movement from earlier nativism toward an increased environmentalism in psychology, and with respect to other historical factors such as wartime events. The role of dominant metaphors in shifting perspectives on regression is described.

High-resolution mapping of the 11q13 amplicon and identification of a gene, TAOS1, that is amplified and overexpressed in oral cancer cells

PubMed Central

Huang, Xin; Gollin, Susanne M.; Raja, Siva; Godfrey, Tony E.

2002-01-01

Amplification of chromosomal band 11q13 is a common event in human cancer. It has been reported in about 45% of head and neck carcinomas and in other cancers including esophageal, breast, liver, lung, and bladder cancer. To understand the mechanism of 11q13 amplification and to identify the potential oncogene(s) driving it, we have fine-mapped the structure of the amplicon in oral squamous cell carcinoma cell lines and localized the proximal and distal breakpoints. A 5-Mb physical map of the region has been prepared from which sequence is available. We quantified copy number of sequence-tagged site markers at 42–550 kb intervals along the length of the amplicon and defined the amplicon core and breakpoints by using TaqMan-based quantitative microsatellite analysis. The core of the amplicon maps to a 1.5-Mb region. The proximal breakpoint localizes to two intervals between sequence-tagged site markers, 550 kb and 160 kb in size, and the distal breakpoint maps to a 250 kb interval. The cyclin D1 gene maps to the amplicon core, as do two new expressed sequence tag clusters. We have analyzed one of these expressed sequence tag clusters and now report that it contains a previously uncharacterized gene, TAOS1 (tumor amplified and overexpressed sequence 1), which is both amplified and overexpressed in oral cancer cells. The data suggest that TAOS1 may be an amplification-dependent candidate oncogene with a role in the development and/or progression of human tumors, including oral squamous cell carcinomas. The approach described here should be useful for characterizing amplified genomic regions in a wide variety of tumors. PMID:12172009

Technical note: Instantaneous sampling intervals validated from continuous video observation for behavioral recording of feedlot lambs.

PubMed

Pullin, A N; Pairis-Garcia, M D; Campbell, B J; Campler, M R; Proudfoot, K L

2017-11-01

When considering methodologies for collecting behavioral data, continuous sampling provides the most complete and accurate data set whereas instantaneous sampling can provide similar results and also increase the efficiency of data collection. However, instantaneous time intervals require validation to ensure accurate estimation of the data. Therefore, the objective of this study was to validate scan sampling intervals for lambs housed in a feedlot environment. Feeding, lying, standing, drinking, locomotion, and oral manipulation were measured on 18 crossbred lambs housed in an indoor feedlot facility for 14 h (0600-2000 h). Data from continuous sampling were compared with data from instantaneous scan sampling intervals of 5, 10, 15, and 20 min using a linear regression analysis. Three criteria determined if a time interval accurately estimated behaviors: 1) ≥ 0.90, 2) slope not statistically different from 1 ( > 0.05), and 3) intercept not statistically different from 0 ( > 0.05). Estimations for lying behavior were accurate up to 20-min intervals, whereas feeding and standing behaviors were accurate only at 5-min intervals (i.e., met all 3 regression criteria). Drinking, locomotion, and oral manipulation demonstrated poor associations () for all tested intervals. The results from this study suggest that a 5-min instantaneous sampling interval will accurately estimate lying, feeding, and standing behaviors for lambs housed in a feedlot, whereas continuous sampling is recommended for the remaining behaviors. This methodology will contribute toward the efficiency, accuracy, and transparency of future behavioral data collection in lamb behavior research.

Paleogeography and the Late Cretaceous of the Western Interior of middle North America; coal distribution and sediment accumulation

USGS Publications Warehouse

Roberts, Laura N. Robinson; Kirschbaum, Mark A.

1995-01-01

A synthesis of Late Cretaceous paleogeography of the Western Interior from Mexico to southwestern Canada emphasizes the areal distribution of peat-forming environments during six biostratigraphically constrained time intervals. Isopach maps of strata for each interval reveal the locations and magnitude of major depocenters. The paleogeographic framework provides insight into the relative importance of tectonism, eustasy, and climate on the accumulation of thick peats and their preservation as coals. A total of 123 basin summaries and their data provide the ground truth for construction of the isopach and paleogeographic maps.

Theoretical evaluation of accuracy in position and size of brain activity obtained by near-infrared topography

NASA Astrophysics Data System (ADS)

Kawaguchi, Hiroshi; Hayashi, Toshiyuki; Kato, Toshinori; Okada, Eiji

2004-06-01

Near-infrared (NIR) topography can obtain a topographical distribution of the activated region in the brain cortex. Near-infrared light is strongly scattered in the head, and the volume of tissue sampled by a source-detector pair on the head surface is broadly distributed in the brain. This scattering effect results in poor resolution and contrast in the topographic image of the brain activity. In this study, a one-dimensional distribution of absorption change in a head model is calculated by mapping and reconstruction methods to evaluate the effect of the image reconstruction algorithm and the interval of measurement points for topographic imaging on the accuracy of the topographic image. The light propagation in the head model is predicted by Monte Carlo simulation to obtain the spatial sensitivity profile for a source-detector pair. The measurement points are one-dimensionally arranged on the surface of the model, and the distance between adjacent measurement points is varied from 4 mm to 28 mm. Small intervals of the measurement points improve the topographic image calculated by both the mapping and reconstruction methods. In the conventional mapping method, the limit of the spatial resolution depends upon the interval of the measurement points and spatial sensitivity profile for source-detector pairs. The reconstruction method has advantages over the mapping method which improve the results of one-dimensional analysis when the interval of measurement points is less than 12 mm. The effect of overlapping of spatial sensitivity profiles indicates that the reconstruction method may be effective to improve the spatial resolution of a two-dimensional reconstruction of topographic image obtained with larger interval of measurement points. Near-infrared topography with the reconstruction method potentially obtains an accurate distribution of absorption change in the brain even if the size of absorption change is less than 10 mm.

Musical training generalises across modalities and reveals efficient and adaptive mechanisms for reproducing temporal intervals.

PubMed

Aagten-Murphy, David; Cappagli, Giulia; Burr, David

2014-03-01

Expert musicians are able to time their actions accurately and consistently during a musical performance. We investigated how musical expertise influences the ability to reproduce auditory intervals and how this generalises across different techniques and sensory modalities. We first compared various reproduction strategies and interval length, to examine the effects in general and to optimise experimental conditions for testing the effect of music, and found that the effects were robust and consistent across different paradigms. Focussing on a 'ready-set-go' paradigm subjects reproduced time intervals drawn from distributions varying in total length (176, 352 or 704 ms) or in the number of discrete intervals within the total length (3, 5, 11 or 21 discrete intervals). Overall, Musicians performed more veridical than Non-Musicians, and all subjects reproduced auditory-defined intervals more accurately than visually-defined intervals. However, Non-Musicians, particularly with visual stimuli, consistently exhibited a substantial and systematic regression towards the mean interval. When subjects judged intervals from distributions of longer total length they tended to regress more towards the mean, while the ability to discriminate between discrete intervals within the distribution had little influence on subject error. These results are consistent with a Bayesian model that minimizes reproduction errors by incorporating a central tendency prior weighted by the subject's own temporal precision relative to the current distribution of intervals. Finally a strong correlation was observed between all durations of formal musical training and total reproduction errors in both modalities (accounting for 30% of the variance). Taken together these results demonstrate that formal musical training improves temporal reproduction, and that this improvement transfers from audition to vision. They further demonstrate the flexibility of sensorimotor mechanisms in adapting to different task conditions to minimise temporal estimation errors. © 2013.

Estimating the magnitude of annual peak discharges with recurrence intervals between 1.1 and 3.0 years for rural, unregulated streams in West Virginia

USGS Publications Warehouse

Wiley, Jeffrey B.; Atkins, John T.; Newell, Dawn A.

2002-01-01

Multiple and simple least-squares regression models for the log10-transformed 1.5- and 2-year recurrence intervals of peak discharges with independent variables describing the basin characteristics (log10-transformed and untransformed) for 236 streamflow-gaging stations were evaluated, and the regression residuals were plotted as areal distributions that defined three regions in West Virginia designated as East, North, and South. Regional equations for the 1.1-, 1.2-, 1.3-, 1.4-, 1.5-, 1.6-, 1.7-, 1.8-, 1.9-, 2.0-, 2.5-, and 3-year recurrence intervals of peak discharges were determined by generalized least-squares regression. Log10-transformed drainage area was the most significant independent variable for all regions. Equations developed in this study are applicable only to rural, unregulated streams within the boundaries of West Virginia. The accuracies of estimating equations are quantified by measuring the average prediction error (from 27.4 to 52.4 percent) and equivalent years of record (from 1.1 to 3.4 years).

SPSS macros to compare any two fitted values from a regression model.

PubMed

Weaver, Bruce; Dubois, Sacha

2012-12-01

In regression models with first-order terms only, the coefficient for a given variable is typically interpreted as the change in the fitted value of Y for a one-unit increase in that variable, with all other variables held constant. Therefore, each regression coefficient represents the difference between two fitted values of Y. But the coefficients represent only a fraction of the possible fitted value comparisons that might be of interest to researchers. For many fitted value comparisons that are not captured by any of the regression coefficients, common statistical software packages do not provide the standard errors needed to compute confidence intervals or carry out statistical tests-particularly in more complex models that include interactions, polynomial terms, or regression splines. We describe two SPSS macros that implement a matrix algebra method for comparing any two fitted values from a regression model. The !OLScomp and !MLEcomp macros are for use with models fitted via ordinary least squares and maximum likelihood estimation, respectively. The output from the macros includes the standard error of the difference between the two fitted values, a 95% confidence interval for the difference, and a corresponding statistical test with its p-value.

Evaluation of three statistical prediction models for forensic age prediction based on DNA methylation.

PubMed

Smeers, Inge; Decorte, Ronny; Van de Voorde, Wim; Bekaert, Bram

2018-05-01

DNA methylation is a promising biomarker for forensic age prediction. A challenge that has emerged in recent studies is the fact that prediction errors become larger with increasing age due to interindividual differences in epigenetic ageing rates. This phenomenon of non-constant variance or heteroscedasticity violates an assumption of the often used method of ordinary least squares (OLS) regression. The aim of this study was to evaluate alternative statistical methods that do take heteroscedasticity into account in order to provide more accurate, age-dependent prediction intervals. A weighted least squares (WLS) regression is proposed as well as a quantile regression model. Their performances were compared against an OLS regression model based on the same dataset. Both models provided age-dependent prediction intervals which account for the increasing variance with age, but WLS regression performed better in terms of success rate in the current dataset. However, quantile regression might be a preferred method when dealing with a variance that is not only non-constant, but also not normally distributed. Ultimately the choice of which model to use should depend on the observed characteristics of the data. Copyright © 2018 Elsevier B.V. All rights reserved.

Estimation of Monthly Near Surface Air Temperature Using Geographically Weighted Regression in China

NASA Astrophysics Data System (ADS)

Wang, M. M.; He, G. J.; Zhang, Z. M.; Zhang, Z. J.; Liu, X. G.

2018-04-01

Near surface air temperature (NSAT) is a primary descriptor of terrestrial environment conditions. The availability of NSAT with high spatial resolution is deemed necessary for several applications such as hydrology, meteorology and ecology. In this study, a regression-based NSAT mapping method is proposed. This method is combined remote sensing variables with geographical variables, and uses geographically weighted regression to estimate NSAT. The altitude was selected as geographical variable; and the remote sensing variables include land surface temperature (LST) and Normalized Difference vegetation index (NDVI). The performance of the proposed method was assessed by predict monthly minimum, mean, and maximum NSAT from point station measurements in China, a domain with a large area, complex topography, and highly variable station density, and the NSAT maps were validated against the meteorology observations. Validation results with meteorological data show the proposed method achieved an accuracy of 1.58 °C. It is concluded that the proposed method for mapping NSAT is very operational and has good precision.

Linear Regression Quantile Mapping (RQM) - A new approach to bias correction with consistent quantile trends

NASA Astrophysics Data System (ADS)

Passow, Christian; Donner, Reik

2017-04-01

Quantile mapping (QM) is an established concept that allows to correct systematic biases in multiple quantiles of the distribution of a climatic observable. It shows remarkable results in correcting biases in historical simulations through observational data and outperforms simpler correction methods which relate only to the mean or variance. Since it has been shown that bias correction of future predictions or scenario runs with basic QM can result in misleading trends in the projection, adjusted, trend preserving, versions of QM were introduced in the form of detrended quantile mapping (DQM) and quantile delta mapping (QDM) (Cannon, 2015, 2016). Still, all previous versions and applications of QM based bias correction rely on the assumption of time-independent quantiles over the investigated period, which can be misleading in the context of a changing climate. Here, we propose a novel combination of linear quantile regression (QR) with the classical QM method to introduce a consistent, time-dependent and trend preserving approach of bias correction for historical and future projections. Since QR is a regression method, it is possible to estimate quantiles in the same resolution as the given data and include trends or other dependencies. We demonstrate the performance of the new method of linear regression quantile mapping (RQM) in correcting biases of temperature and precipitation products from historical runs (1959 - 2005) of the COSMO model in climate mode (CCLM) from the Euro-CORDEX ensemble relative to gridded E-OBS data of the same spatial and temporal resolution. A thorough comparison with established bias correction methods highlights the strengths and potential weaknesses of the new RQM approach. References: A.J. Cannon, S.R. Sorbie, T.Q. Murdock: Bias Correction of GCM Precipitation by Quantile Mapping - How Well Do Methods Preserve Changes in Quantiles and Extremes? Journal of Climate, 28, 6038, 2015 A.J. Cannon: Multivariate Bias Correction of Climate Model Outputs - Matching Marginal Distributions and Inter-variable Dependence Structure. Journal of Climate, 29, 7045, 2016

Carbon emissions risk map from deforestation in the tropical Amazon

NASA Astrophysics Data System (ADS)

Ometto, J.; Soler, L. S.; Assis, T. D.; Oliveira, P. V.; Aguiar, A. P.

2011-12-01

Assis, Pedro Valle This work aims to estimate the carbon emissions from tropical deforestation in the Brazilian Amazon associated to the risk assessment of future land use change. The emissions are estimated by incorporating temporal deforestation dynamics, accounting for the biophysical and socioeconomic heterogeneity in the region, as well secondary forest growth dynamic in abandoned areas. The land cover change model that supported the risk assessment of deforestation, was run based on linear regressions. This method takes into account spatial heterogeneity of deforestation as the spatial variables adopted to fit the final regression model comprise: environmental aspects, economic attractiveness, accessibility and land tenure structure. After fitting a suitable regression models for each land cover category, the potential of each cell to be deforested (25x25km and 5x5 km of resolution) in the near future was used to calculate the risk assessment of land cover change. The carbon emissions model combines high-resolution new forest clear-cut mapping and four alternative sources of spatial information on biomass distribution for different vegetation types. The risk assessment map of CO2 emissions, was obtained by crossing the simulation results of the historical land cover changes to a map of aboveground biomass contained in the remaining forest. This final map represents the risk of CO2 emissions at 25x25km and 5x5 km until 2020, under a scenario of carbon emission reduction target.

Entrainment and high-density three-dimensional mapping in right atrial macroreentry provide critical complementary information: Entrainment may unmask "visual reentry" as passive.

PubMed

Pathik, Bhupesh; Lee, Geoffrey; Nalliah, Chrishan; Joseph, Stephen; Morton, Joseph B; Sparks, Paul B; Sanders, Prashanthan; Kistler, Peter M; Kalman, Jonathan M

2017-10-01

With the recent advent of high-density (HD) 3-dimensional (3D) mapping, the utility of entrainment is uncertain. However, the limitations of visual representation and interpretation of these high-resolution 3D maps are unclear. The purpose of this study was to determine the strengths and limitations of both HD 3D mapping and entrainment mapping during mapping of right atrial macroreentry. Fifteen patients were studied. The number and type of circuits accounting for ≥90% of the tachycardia cycle length using HD 3D mapping were verified using systematic entrainment mapping. Entrainment sites with an unexpectedly long postpacing interval despite proximity to the active circuit were evaluated. Based on HD 3D mapping, 27 circuits were observed: 12 peritricuspid, 2 upper loop reentry, 10 lower loop reentry, and 3 lateral wall circuits. With entrainment, 17 of the 27 circuits were active: all 12 peritricuspid and 2 upper loop reentry. However, lower loop reentry was confirmed in only 3 of 10, and none of the 3 lateral wall circuits were present. Mean percentage of tachycardia cycle length covered by active circuits was 98% ± 1% vs 97% ± 2% for passive circuits (P = .09). None of the 345 entrainment runs terminated tachycardia or changed tachycardia mechanism. In 8 of 15 patients, 13 examples of unexpectedly long postpacing interval were observed at entrainment sites located distal to localized zones of slow conduction seen on HD 3D mapping. Using HD 3D mapping, "visual reentry" may be due to passive circuitous propagation rather than a critical reentrant circuit. HD 3D mapping provides new insights into regional conduction and helps explain unusual entrainment phenomena. Copyright © 2017 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Endocrine events during the periestrous period and the subsequent estrous cycle in ewes after estrus synchronization.

PubMed

Menegatos, J; Chadio, S; Kalogiannis, T; Kouskoura, T; Kouimtzis, S

2003-04-01

The aim of the present study was to investigate the endocrinology of the periestrus period and that of the subsequent estrous cycle in ewes synchronized during the breeding season. Animals were treated for 14 days with either MAP intravaginal sponges or subcutaneous progesterone implants, followed by administration of 500 IU PMSG at the time of withdrawal. The time to estrus occurrence following progestagen withdrawal differed significantly between groups (45.3+/-2.7h for the MAP and 21.5+/-1.2h for the implant group, P<0.001). Estradiol levels around estrus did not differ between groups, but a significant difference was detected for the interval from peak estradiol to estrus, with a shorter interval for the implant group (26.7+/-0.7 and 2.7+/-0.9h, P<0.001). Progesterone implants shortened the interval from removal to LH surge, compared to the MAP group (31.2+/-4.4 and 56.5+/-3.6h, respectively, P<0.05). An earlier response was also observed for the interval from estradiol peak to LH peak in the implant group (12.1+/-3.3 and 37+/-2h, respectively, P<0.005), but no difference was observed for the interval from estrus to LH surge. Progesterone levels, particularly during the Days 6 to 10 of the subsequent estrous cycle were significantly higher (P<0.05) in the implant group. It is concluded that the kind of progesterone treatment may affect the time of estrus and the LH peak as well as the progesterone levels of the subsequent cycle.

Risk factors for low birth weight according to the multiple logistic regression model. A retrospective cohort study in José María Morelos municipality, Quintana Roo, Mexico.

PubMed

Franco Monsreal, José; Tun Cobos, Miriam Del Ruby; Hernández Gómez, José Ricardo; Serralta Peraza, Lidia Esther Del Socorro

2018-01-17

Low birth weight has been an enigma for science over time. There have been many researches on its causes and its effects. Low birth weight is an indicator that predicts the probability of a child surviving. In fact, there is an exponential relationship between weight deficit, gestational age, and perinatal mortality. Multiple logistic regression is one of the most expressive and versatile statistical instruments available for the analysis of data in both clinical and epidemiology settings, as well as in public health. To assess in a multivariate fashion the importance of 17 independent variables in low birth weight (dependent variable) of children born in the Mayan municipality of José María Morelos, Quintana Roo, Mexico. Analytical observational epidemiological cohort study with retrospective temporality. Births that met the inclusion criteria occurred in the "Hospital Integral Jose Maria Morelos" of the Ministry of Health corresponding to the Maya municipality of Jose Maria Morelos during the period from August 1, 2014 to July 31, 2015. The total number of newborns recorded was 1,147; 84 of which (7.32%) had low birth weight. To estimate the independent association between the explanatory variables (potential risk factors) and the response variable, a multiple logistic regression analysis was performed using the IBM SPSS Statistics 22 software. In ascending numerical order values of odds ratio > 1 indicated the positive contribution of explanatory variables or possible risk factors: "unmarried" marital status (1.076, 95% confidence interval: 0.550 to 2.104); age at menarche ≤ 12 years (1.08, 95% confidence interval: 0.64 to 1.84); history of abortion(s) (1.14, 95% confidence interval: 0.44 to 2.93); maternal weight < 50 kg (1.51, 95% confidence interval: 0.83 to 2.76); number of prenatal consultations ≤ 5 (1.86, 95% confidence interval: 0.94 to 3.66); maternal age ≥ 36 years (3.5, 95% confidence interval: 0.40 to 30.47); maternal age ≤ 19 years (3.59, 95% confidence interval: 0.43 to 29.87); number of deliveries = 1 (3.86, 95% confidence interval: 0.33 to 44.85); personal pathological history (4.78, 95% confidence interval: 2.16 to 10.59); pathological obstetric history (5.01, 95% confidence interval: 1.66 to 15.18); maternal height < 150 cm (5.16, 95% confidence interval: 3.08 to 8.65); number of births ≥ 5 (5.99, 95% confidence interval: 0.51 to 69.99); and smoking (15.63, 95% confidence interval: 1.07 to 227.97). Four of the independent variables (personal pathological history, obstetric pathological history, maternal stature <150 centimeters and smoking) showed a significant positive contribution, thus they can be considered as clear risk factors for low birth weight. The use of the logistic regression model in the Mayan municipality of José María Morelos, will allow estimating the probability of low birth weight for each pregnant woman in the future, which will be useful for the health authorities of the region.

SNP Marker Integration and QTL Analysis of 12 Agronomic and Morphological Traits in F8 RILs of Pepper (Capsicum annuum L.)

PubMed Central

Lu, Fu-Hao; Kwon, Soon-Wook; Yoon, Min-Young; Kim, Ki-Taek; Cho, Myeong-Cheoul; Yoon, Moo-Kyung; Park, Yong-Jin

2012-01-01

Red pepper, Capsicum annuum L., has been attracting geneticists’ and breeders’ attention as one of the important agronomic crops. This study was to integrate 41 SNP markers newly developed from comparative transcriptomes into a previous linkage map, and map 12 agronomic and morphological traits into the integrated map. A total of 39 markers found precise position and were assigned to 13 linkage groups (LGs) as well as the unassigned LGe, leading to total 458 molecular markers present in this genetic map. Linkage mapping was supported by the physical mapping to tomato and potato genomes using BLAST retrieving, revealing at least two-thirds of the markers mapped to the corresponding LGs. A sum of 23 quantitative trait loci from 11 traits was detected using the composite interval mapping algorithm. A consistent interval between a035_1 and a170_1 on LG5 was detected as a main-effect locus among the resistance QTLs to Phytophthora capsici at high-, intermediate- and low-level tests, and interactions between the QTLs for high-level resistance test were found. Considering the epistatic effect, those QTLs could explain up to 98.25% of the phenotype variations of resistance. Moreover, 17 QTLs for another eight traits were found to locate on LG3, 4, and 12 mostly with varying phenotypic contribution. Furthermore, the locus for corolla color was mapped to LG10 as a marker. The integrated map and the QTLs identified would be helpful for current genetics research and crop breeding, especially in the Solanaceae family. PMID:22684870

Construction of a high-density genetic map by specific locus amplified fragment sequencing (SLAF-seq) and its application to Quantitative Trait Loci (QTL) analysis for boll weight in upland cotton (Gossypium hirsutum.).

PubMed

Zhang, Zhen; Shang, Haihong; Shi, Yuzhen; Huang, Long; Li, Junwen; Ge, Qun; Gong, Juwu; Liu, Aiying; Chen, Tingting; Wang, Dan; Wang, Yanling; Palanga, Koffi Kibalou; Muhammad, Jamshed; Li, Weijie; Lu, Quanwei; Deng, Xiaoying; Tan, Yunna; Song, Weiwu; Cai, Juan; Li, Pengtao; Rashid, Harun or; Gong, Wankui; Yuan, Youlu

2016-04-11

Upland Cotton (Gossypium hirsutum) is one of the most important worldwide crops it provides natural high-quality fiber for the industrial production and everyday use. Next-generation sequencing is a powerful method to identify single nucleotide polymorphism markers on a large scale for the construction of a high-density genetic map for quantitative trait loci mapping. In this research, a recombinant inbred lines population developed from two upland cotton cultivars 0-153 and sGK9708 was used to construct a high-density genetic map through the specific locus amplified fragment sequencing method. The high-density genetic map harbored 5521 single nucleotide polymorphism markers which covered a total distance of 3259.37 cM with an average marker interval of 0.78 cM without gaps larger than 10 cM. In total 18 quantitative trait loci of boll weight were identified as stable quantitative trait loci and were detected in at least three out of 11 environments and explained 4.15-16.70 % of the observed phenotypic variation. In total, 344 candidate genes were identified within the confidence intervals of these stable quantitative trait loci based on the cotton genome sequence. These genes were categorized based on their function through gene ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis and eukaryotic orthologous groups analysis. This research reported the first high-density genetic map for Upland Cotton (Gossypium hirsutum) with a recombinant inbred line population using single nucleotide polymorphism markers developed by specific locus amplified fragment sequencing. We also identified quantitative trait loci of boll weight across 11 environments and identified candidate genes within the quantitative trait loci confidence intervals. The results of this research would provide useful information for the next-step work including fine mapping, gene functional analysis, pyramiding breeding of functional genes as well as marker-assisted selection.

The Topography Tub Learning Activity

NASA Astrophysics Data System (ADS)

Glesener, G. B.

2014-12-01

Understanding the basic elements of a topographic map (i.e. contour lines and intervals) is just a small part of learning how to use this abstract representational system as a resource in geologic mapping. Interpretation of a topographic map and matching its features with real-world structures requires that the system is utilized for visualizing the shapes of these structures and their spatial orientation. To enrich students' skills in visualizing topography from topographic maps a spatial training activity has been developed that uses 3D objects of various shapes and sizes, a sighting tool, a plastic basin, water, and transparencies. In the first part of the activity, the student is asked to draw a topographic map of one of the 3D objects. Next, the student places the object into a plastic tub in which water is added to specified intervals of height. The shoreline at each interval is used to reference the location of the contour line the student draws on a plastic inkjet transparency directly above the object. A key part of this activity is the use of a sighting tool by the student to assist in keeping the pencil mark directly above the shoreline. It (1) ensures the accurate positioning of the contour line and (2) gives the learner experience with using a sight before going out into the field. Finally, after the student finishes drawing the contour lines onto the transparency, the student can compare and contrast the two maps in order to discover where improvements in their visualization of the contours can be made. The teacher and/or peers can also make suggestions on ways to improve. A number of objects with various shapes and sizes are used in this exercise to produce contour lines representing the different types of topography the student may encounter while field mapping. The intended outcome from using this visualization training activity is improvement in performance of visualizing topography as the student moves between the topographic representation and corresponding topography in the field.

Progressive myoclonus epilepsy EPM1 locus maps to a 175-kb interval in distal 21q

DOE Office of Scientific and Technical Information (OSTI.GOV)

Virtaneva, K.; Miao, J.; Traeskelin, A.L.

1996-06-01

The EPM1 locus responsible for progressive myoclonus epilepsy of Unverricht-Lundborg type (MIM 254800) maps to a region in distal chromosome 21q where positional cloning has been hampered by the lack of physical and genetic mapping resolution. We here report the use of a recently constituted contig of cosmid, BAC, and P1 clones that allowed new polymorphic markers to be positioned. These were typed in 53 unrelated disease families from an isolated Finnish population in which a putative single ancestral EPM1 mutation has segregated for an estimated 100 generations. By thus exploiting historical recombinations in haplotype analysis, EPM1 could be assignedmore » to the {approximately}175-kb interval between the markers D21S2040 and D21S1259. 26 refs., 2 figs., 4 tabs.« less

Fine-Scale Mapping of the 5q11.2 Breast Cancer Locus Reveals at Least Three Independent Risk Variants Regulating MAP3K1

PubMed Central

Glubb, Dylan M.; Maranian, Mel J.; Michailidou, Kyriaki; Pooley, Karen A.; Meyer, Kerstin B.; Kar, Siddhartha; Carlebur, Saskia; O’Reilly, Martin; Betts, Joshua A.; Hillman, Kristine M.; Kaufmann, Susanne; Beesley, Jonathan; Canisius, Sander; Hopper, John L.; Southey, Melissa C.; Tsimiklis, Helen; Apicella, Carmel; Schmidt, Marjanka K.; Broeks, Annegien; Hogervorst, Frans B.; van der Schoot, C. Ellen; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Fasching, Peter A.; Ruebner, Matthias; Ekici, Arif B.; Beckmann, Matthias W.; Peto, Julian; dos-Santos-Silva, Isabel; Fletcher, Olivia; Johnson, Nichola; Pharoah, Paul D.P.; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Sawyer, Elinor J.; Tomlinson, Ian; Kerin, Michael J.; Miller, Nicola; Burwinkel, Barbara; Marme, Frederik; Yang, Rongxi; Surowy, Harald; Guénel, Pascal; Truong, Thérèse; Menegaux, Florence; Sanchez, Marie; Bojesen, Stig E.; Nordestgaard, Børge G.; Nielsen, Sune F.; Flyger, Henrik; González-Neira, Anna; Benitez, Javier; Zamora, M. Pilar; Arias Perez, Jose Ignacio; Anton-Culver, Hoda; Neuhausen, Susan L.; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Meindl, Alfons; Schmutzler, Rita K.; Brauch, Hiltrud; Ko, Yon-Dschun; Brüning, Thomas; Nevanlinna, Heli; Muranen, Taru A.; Aittomäki, Kristiina; Blomqvist, Carl; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Tanaka, Hideo; Dörk, Thilo; Bogdanova, Natalia V.; Helbig, Sonja; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M.; Wu, Anna H.; Tseng, Chiu-chen; Van Den Berg, David; Stram, Daniel O.; Lambrechts, Diether; Zhao, Hui; Weltens, Caroline; van Limbergen, Erik; Chang-Claude, Jenny; Flesch-Janys, Dieter; Rudolph, Anja; Seibold, Petra; Radice, Paolo; Peterlongo, Paolo; Barile, Monica; Capra, Fabio; Couch, Fergus J.; Olson, Janet E.; Hallberg, Emily; Vachon, Celine; Giles, Graham G.; Milne, Roger L.; McLean, Catriona; Haiman, Christopher A.; Henderson, Brian E.; Schumacher, Fredrick; Le Marchand, Loic; Simard, Jacques; Goldberg, Mark S.; Labrèche, France; Dumont, Martine; Teo, Soo Hwang; Yip, Cheng Har; See, Mee-Hoong; Cornes, Belinda; Cheng, Ching-Yu; Ikram, M. Kamran; Kristensen, Vessela; Zheng, Wei; Halverson, Sandra L.; Shrubsole, Martha; Long, Jirong; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Kauppila, Saila; Andrulis, Irene L.; Knight, Julia A.; Glendon, Gord; Tchatchou, Sandrine; Devilee, Peter; Tollenaar, Robert A.E.M.; Seynaeve, Caroline; Van Asperen, Christi J.; García-Closas, Montserrat; Figueroa, Jonine; Chanock, Stephen J.; Lissowska, Jolanta; Czene, Kamila; Klevebring, Daniel; Darabi, Hatef; Eriksson, Mikael; Hooning, Maartje J.; Hollestelle, Antoinette; Martens, John W.M.; Collée, J. Margriet; Hall, Per; Li, Jingmei; Humphreys, Keith; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Cox, Angela; Cross, Simon S.; Reed, Malcolm W.R.; Blot, William; Signorello, Lisa B.; Cai, Qiuyin; Shah, Mitul; Ghoussaini, Maya; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K.; Noh, Dong-Young; Hartman, Mikael; Miao, Hui; Lim, Wei Yen; Tang, Anthony; Hamann, Ute; Torres, Diana; Jakubowska, Anna; Lubinski, Jan; Jaworska, Katarzyna; Durda, Katarzyna; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; McKay, James; Olswold, Curtis; Slager, Susan; Toland, Amanda E.; Yannoukakos, Drakoulis; Shen, Chen-Yang; Wu, Pei-Ei; Yu, Jyh-Cherng; Hou, Ming-Feng; Swerdlow, Anthony; Ashworth, Alan; Orr, Nick; Jones, Michael; Pita, Guillermo; Alonso, M. Rosario; Álvarez, Nuria; Herrero, Daniel; Tessier, Daniel C.; Vincent, Daniel; Bacot, Francois; Luccarini, Craig; Baynes, Caroline; Ahmed, Shahana; Healey, Catherine S.; Brown, Melissa A.; Ponder, Bruce A.J.; Chenevix-Trench, Georgia; Thompson, Deborah J.; Edwards, Stacey L.; Easton, Douglas F.; Dunning, Alison M.; French, Juliet D.

2015-01-01

Genome-wide association studies (GWASs) have revealed SNP rs889312 on 5q11.2 to be associated with breast cancer risk in women of European ancestry. In an attempt to identify the biologically relevant variants, we analyzed 909 genetic variants across 5q11.2 in 103,991 breast cancer individuals and control individuals from 52 studies in the Breast Cancer Association Consortium. Multiple logistic regression analyses identified three independent risk signals: the strongest associations were with 15 correlated variants (iCHAV1), where the minor allele of the best candidate, rs62355902, associated with significantly increased risks of both estrogen-receptor-positive (ER+: odds ratio [OR] = 1.24, 95% confidence interval [CI] = 1.21–1.27, ptrend = 5.7 × 10−44) and estrogen-receptor-negative (ER−: OR = 1.10, 95% CI = 1.05–1.15, ptrend = 3.0 × 10−4) tumors. After adjustment for rs62355902, we found evidence of association of a further 173 variants (iCHAV2) containing three subsets with a range of effects (the strongest was rs113317823 [pcond = 1.61 × 10−5]) and five variants composing iCHAV3 (lead rs11949391; ER+: OR = 0.90, 95% CI = 0.87–0.93, pcond = 1.4 × 10−4). Twenty-six percent of the prioritized candidate variants coincided with four putative regulatory elements that interact with the MAP3K1 promoter through chromatin looping and affect MAP3K1 promoter activity. Functional analysis indicated that the cancer risk alleles of four candidates (rs74345699 and rs62355900 [iCHAV1], rs16886397 [iCHAV2a], and rs17432750 [iCHAV3]) increased MAP3K1 transcriptional activity. Chromatin immunoprecipitation analysis revealed diminished GATA3 binding to the minor (cancer-protective) allele of rs17432750, indicating a mechanism for its action. We propose that the cancer risk alleles act to increase MAP3K1 expression in vivo and might promote breast cancer cell survival. PMID:25529635

Fine-scale mapping of the 5q11.2 breast cancer locus reveals at least three independent risk variants regulating MAP3K1.

PubMed

Glubb, Dylan M; Maranian, Mel J; Michailidou, Kyriaki; Pooley, Karen A; Meyer, Kerstin B; Kar, Siddhartha; Carlebur, Saskia; O'Reilly, Martin; Betts, Joshua A; Hillman, Kristine M; Kaufmann, Susanne; Beesley, Jonathan; Canisius, Sander; Hopper, John L; Southey, Melissa C; Tsimiklis, Helen; Apicella, Carmel; Schmidt, Marjanka K; Broeks, Annegien; Hogervorst, Frans B; van der Schoot, C Ellen; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Fasching, Peter A; Ruebner, Matthias; Ekici, Arif B; Beckmann, Matthias W; Peto, Julian; dos-Santos-Silva, Isabel; Fletcher, Olivia; Johnson, Nichola; Pharoah, Paul D P; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Sawyer, Elinor J; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Burwinkel, Barbara; Marme, Frederik; Yang, Rongxi; Surowy, Harald; Guénel, Pascal; Truong, Thérèse; Menegaux, Florence; Sanchez, Marie; Bojesen, Stig E; Nordestgaard, Børge G; Nielsen, Sune F; Flyger, Henrik; González-Neira, Anna; Benitez, Javier; Zamora, M Pilar; Arias Perez, Jose Ignacio; Anton-Culver, Hoda; Neuhausen, Susan L; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Meindl, Alfons; Schmutzler, Rita K; Brauch, Hiltrud; Ko, Yon-Dschun; Brüning, Thomas; Nevanlinna, Heli; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Tanaka, Hideo; Dörk, Thilo; Bogdanova, Natalia V; Helbig, Sonja; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Wu, Anna H; Tseng, Chiu-chen; Van Den Berg, David; Stram, Daniel O; Lambrechts, Diether; Zhao, Hui; Weltens, Caroline; van Limbergen, Erik; Chang-Claude, Jenny; Flesch-Janys, Dieter; Rudolph, Anja; Seibold, Petra; Radice, Paolo; Peterlongo, Paolo; Barile, Monica; Capra, Fabio; Couch, Fergus J; Olson, Janet E; Hallberg, Emily; Vachon, Celine; Giles, Graham G; Milne, Roger L; McLean, Catriona; Haiman, Christopher A; Henderson, Brian E; Schumacher, Fredrick; Le Marchand, Loic; Simard, Jacques; Goldberg, Mark S; Labrèche, France; Dumont, Martine; Teo, Soo Hwang; Yip, Cheng Har; See, Mee-Hoong; Cornes, Belinda; Cheng, Ching-Yu; Ikram, M Kamran; Kristensen, Vessela; Zheng, Wei; Halverson, Sandra L; Shrubsole, Martha; Long, Jirong; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Kauppila, Saila; Andrulis, Irene L; Knight, Julia A; Glendon, Gord; Tchatchou, Sandrine; Devilee, Peter; Tollenaar, Robert A E M; Seynaeve, Caroline; Van Asperen, Christi J; García-Closas, Montserrat; Figueroa, Jonine; Chanock, Stephen J; Lissowska, Jolanta; Czene, Kamila; Klevebring, Daniel; Darabi, Hatef; Eriksson, Mikael; Hooning, Maartje J; Hollestelle, Antoinette; Martens, John W M; Collée, J Margriet; Hall, Per; Li, Jingmei; Humphreys, Keith; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Cox, Angela; Cross, Simon S; Reed, Malcolm W R; Blot, William; Signorello, Lisa B; Cai, Qiuyin; Shah, Mitul; Ghoussaini, Maya; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K; Noh, Dong-Young; Hartman, Mikael; Miao, Hui; Lim, Wei Yen; Tang, Anthony; Hamann, Ute; Torres, Diana; Jakubowska, Anna; Lubinski, Jan; Jaworska, Katarzyna; Durda, Katarzyna; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; McKay, James; Olswold, Curtis; Slager, Susan; Toland, Amanda E; Yannoukakos, Drakoulis; Shen, Chen-Yang; Wu, Pei-Ei; Yu, Jyh-Cherng; Hou, Ming-Feng; Swerdlow, Anthony; Ashworth, Alan; Orr, Nick; Jones, Michael; Pita, Guillermo; Alonso, M Rosario; Álvarez, Nuria; Herrero, Daniel; Tessier, Daniel C; Vincent, Daniel; Bacot, Francois; Luccarini, Craig; Baynes, Caroline; Ahmed, Shahana; Healey, Catherine S; Brown, Melissa A; Ponder, Bruce A J; Chenevix-Trench, Georgia; Thompson, Deborah J; Edwards, Stacey L; Easton, Douglas F; Dunning, Alison M; French, Juliet D

2015-01-08

Genome-wide association studies (GWASs) have revealed SNP rs889312 on 5q11.2 to be associated with breast cancer risk in women of European ancestry. In an attempt to identify the biologically relevant variants, we analyzed 909 genetic variants across 5q11.2 in 103,991 breast cancer individuals and control individuals from 52 studies in the Breast Cancer Association Consortium. Multiple logistic regression analyses identified three independent risk signals: the strongest associations were with 15 correlated variants (iCHAV1), where the minor allele of the best candidate, rs62355902, associated with significantly increased risks of both estrogen-receptor-positive (ER(+): odds ratio [OR] = 1.24, 95% confidence interval [CI] = 1.21-1.27, ptrend = 5.7 × 10(-44)) and estrogen-receptor-negative (ER(-): OR = 1.10, 95% CI = 1.05-1.15, ptrend = 3.0 × 10(-4)) tumors. After adjustment for rs62355902, we found evidence of association of a further 173 variants (iCHAV2) containing three subsets with a range of effects (the strongest was rs113317823 [pcond = 1.61 × 10(-5)]) and five variants composing iCHAV3 (lead rs11949391; ER(+): OR = 0.90, 95% CI = 0.87-0.93, pcond = 1.4 × 10(-4)). Twenty-six percent of the prioritized candidate variants coincided with four putative regulatory elements that interact with the MAP3K1 promoter through chromatin looping and affect MAP3K1 promoter activity. Functional analysis indicated that the cancer risk alleles of four candidates (rs74345699 and rs62355900 [iCHAV1], rs16886397 [iCHAV2a], and rs17432750 [iCHAV3]) increased MAP3K1 transcriptional activity. Chromatin immunoprecipitation analysis revealed diminished GATA3 binding to the minor (cancer-protective) allele of rs17432750, indicating a mechanism for its action. We propose that the cancer risk alleles act to increase MAP3K1 expression in vivo and might promote breast cancer cell survival. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

AbsIDconvert: An absolute approach for converting genetic identifiers at different granularities

PubMed Central

2012-01-01

Background High-throughput molecular biology techniques yield vast amounts of data, often by detecting small portions of ribonucleotides corresponding to specific identifiers. Existing bioinformatic methodologies categorize and compare these elements using inferred descriptive annotation given this sequence information irrespective of the fact that it may not be representative of the identifier as a whole. Results All annotations, no matter the granularity, can be aligned to genomic sequences and therefore annotated by genomic intervals. We have developed AbsIDconvert, a methodology for converting between genomic identifiers by first mapping them onto a common universal coordinate system using an interval tree which is subsequently queried for overlapping identifiers. AbsIDconvert has many potential uses, including gene identifier conversion, identification of features within a genomic region, and cross-species comparisons. The utility is demonstrated in three case studies: 1) comparative genomic study mapping plasmodium gene sequences to corresponding human and mosquito transcriptional regions; 2) cross-species study of Incyte clone sequences; and 3) analysis of human Ensembl transcripts mapped by Affymetrix®; and Agilent microarray probes. AbsIDconvert currently supports ID conversion of 53 species for a given list of input identifiers, genomic sequence, or genome intervals. Conclusion AbsIDconvert provides an efficient and reliable mechanism for conversion between identifier domains of interest. The flexibility of this tool allows for custom definition identifier domains contingent upon the availability and determination of a genomic mapping interval. As the genomes and the sequences for genetic elements are further refined, this tool will become increasingly useful and accurate. AbsIDconvert is freely available as a web application or downloadable as a virtual machine at: http://bioinformatics.louisville.edu/abid/. PMID:22967011

Use of ocean color scanner data in water quality mapping

NASA Technical Reports Server (NTRS)

Khorram, S.

1981-01-01

Remotely sensed data, in combination with in situ data, are used in assessing water quality parameters within the San Francisco Bay-Delta. The parameters include suspended solids, chlorophyll, and turbidity. Regression models are developed between each of the water quality parameter measurements and the Ocean Color Scanner (OCS) data. The models are then extended to the entire study area for mapping water quality parameters. The results include a series of color-coded maps, each pertaining to one of the water quality parameters, and the statistical analysis of the OCS data and regression models. It is found that concurrently collected OCS data and surface truth measurements are highly useful in mapping the selected water quality parameters and locating areas having relatively high biological activity. In addition, it is found to be virtually impossible, at least within this test site, to locate such areas on U-2 color and color-infrared photography.

Procedural Documentation and Accuracy Assessment of Bathymetric Maps and Area/Capacity Tables for Small Reservoirs

USGS Publications Warehouse

Wilson, Gary L.; Richards, Joseph M.

2006-01-01

Because of the increasing use and importance of lakes for water supply to communities, a repeatable and reliable procedure to determine lake bathymetry and capacity is needed. A method to determine the accuracy of the procedure will help ensure proper collection and use of the data and resulting products. It is important to clearly define the intended products and desired accuracy before conducting the bathymetric survey to ensure proper data collection. A survey-grade echo sounder and differential global positioning system receivers were used to collect water-depth and position data in December 2003 at Sugar Creek Lake near Moberly, Missouri. Data were collected along planned transects, with an additional set of quality-assurance data collected for use in accuracy computations. All collected data were imported into a geographic information system database. A bathymetric surface model, contour map, and area/capacity tables were created from the geographic information system database. An accuracy assessment was completed on the collected data, bathymetric surface model, area/capacity table, and contour map products. Using established vertical accuracy standards, the accuracy of the collected data, bathymetric surface model, and contour map product was 0.67 foot, 0.91 foot, and 1.51 feet at the 95 percent confidence level. By comparing results from different transect intervals with the quality-assurance transect data, it was determined that a transect interval of 1 percent of the longitudinal length of Sugar Creek Lake produced nearly as good results as 0.5 percent transect interval for the bathymetric surface model, area/capacity table, and contour map products.

Operating room-to-incision interval and neonatal outcome in emergency caesarean section: a retrospective 5-year cohort study.

PubMed

Palmer, E; Ciechanowicz, S; Reeve, A; Harris, S; Wong, D J N; Sultan, P

2018-07-01

We conducted a 5-year retrospective cohort study on women undergoing caesarean section to investigate factors influencing the operating room-to-incision interval. Time-to-event analysis was performed for category-1 caesarean section using a Cox proportional hazards regression model. Covariates included: anaesthetic technique; body mass index; age; parity; time of delivery; and gestational age. Binary logistic regression was performed for 5-min Apgar score ≥ 7. There were 677 women who underwent category-1 caesarean section and who met the entry criteria. Unadjusted median (IQR [range]) operating room-to-incision intervals were: epidural top-up 11 (7-17 [0-87]) min; general anaesthesia 6 (4-11 [0-69]) min; spinal 13 (10-20 [0-83]) min; and combined spinal-epidural 24 (13-35 [0-75]) min. Cox regression showed general anaesthesia to be the most rapid method with a hazard ratio (95%CI) of 1.97 (1.60-2.44; p < 0.0001), followed by epidural top-up (reference group), spinal anaesthesia 0.79 (0.65-0.96; p = 0.02) and combined spinal-epidural 0.48 (0.35-0.67; p < 0.0001). Underweight and overweight body mass indexes were associated with longer operating room-to-incision intervals. General anaesthesia was associated with fewer 5-min Apgar scores ≥ 7 with an odds ratio (95%CI) of 0.28 (0.11-0.68; p < 0.01). There was no difference in neonatal outcomes between the first and fifth quintiles for operating room-to-incision intervals. General anaesthesia is associated with the most rapid operating room-to-incision interval for category-1 caesarean section, but is also associated with worse short term neonatal outcomes. Longer operating room-to-incision intervals were not associated with worse neonatal outcomes. © 2018 The Association of Anaesthetists of Great Britain and Ireland.

Power law behavior of RR-interval variability in healthy middle-aged persons, patients with recent acute myocardial infarction, and patients with heart transplants

NASA Technical Reports Server (NTRS)

Bigger, J. T. Jr; Steinman, R. C.; Rolnitzky, L. M.; Fleiss, J. L.; Albrecht, P.; Cohen, R. J.

1996-01-01

BACKGROUND. The purposes of the present study were (1) to establish normal values for the regression of log(power) on log(frequency) for, RR-interval fluctuations in healthy middle-aged persons, (2) to determine the effects of myocardial infarction on the regression of log(power) on log(frequency), (3) to determine the effect of cardiac denervation on the regression of log(power) on log(frequency), and (4) to assess the ability of power law regression parameters to predict death after myocardial infarction. METHODS AND RESULTS. We studied three groups: (1) 715 patients with recent myocardial infarction; (2) 274 healthy persons age and sex matched to the infarct sample; and (3) 19 patients with heart transplants. Twenty-four-hour RR-interval power spectra were computed using fast Fourier transforms and log(power) was regressed on log(frequency) between 10(-4) and 10(-2) Hz. There was a power law relation between log(power) and log(frequency). That is, the function described a descending straight line that had a slope of approximately -1 in healthy subjects. For the myocardial infarction group, the regression line for log(power) on log(frequency) was shifted downward and had a steeper negative slope (-1.15). The transplant (denervated) group showed a larger downward shift in the regression line and a much steeper negative slope (-2.08). The correlation between traditional power spectral bands and slope was weak, and that with log(power) at 10(-4) Hz was only moderate. Slope and log(power) at 10(-4) Hz were used to predict mortality and were compared with the predictive value of traditional power spectral bands. Slope and log(power) at 10(-4) Hz were excellent predictors of all-cause mortality or arrhythmic death. To optimize the prediction of death, we calculated a log(power) intercept that was uncorrelated with the slope of the power law regression line. We found that the combination of slope and zero-correlation log(power) was an outstanding predictor, with a relative risk of > 10, and was better than any combination of the traditional power spectral bands. The combination of slope and log(power) at 10(-4) Hz also was an excellent predictor of death after myocardial infarction. CONCLUSIONS. Myocardial infarction or denervation of the heart causes a steeper slope and decreased height of the power law regression relation between log(power) and log(frequency) of RR-interval fluctuations. Individually and, especially, combined, the power law regression parameters are excellent predictors of death of any cause or arrhythmic death and predict these outcomes better than the traditional power spectral bands.

Weighted analysis methods for mapped plot forest inventory data: Tables, regressions, maps and graphs

Treesearch

Paul C. Van Deusen; Linda S. Heath

2010-01-01

Weighted estimation methods for analysis of mapped plot forest inventory data are discussed. The appropriate weighting scheme can vary depending on the type of analysis and graphical display. Both statistical issues and user expectations need to be considered in these methods. A weighting scheme is proposed that balances statistical considerations and the logical...

Forest/non-forest mapping using inventory data and satellite imagery

Treesearch

Ronald E. McRoberts

2002-01-01

For two study areas in Minnesota, USA, one heavily forested and one sparsely forested, maps of predicted proportion forest area were created using Landsat Thematic Mapper imagery, forest inventory plot data, and two prediction techniques, logistic regression and a k-Nearest Neighbours technique. The maps were used to increase the precision of forest area estimates by...

Accurate estimation of short read mapping quality for next-generation genome sequencing

PubMed Central

Ruffalo, Matthew; Koyutürk, Mehmet; Ray, Soumya; LaFramboise, Thomas

2012-01-01

Motivation: Several software tools specialize in the alignment of short next-generation sequencing reads to a reference sequence. Some of these tools report a mapping quality score for each alignment—in principle, this quality score tells researchers the likelihood that the alignment is correct. However, the reported mapping quality often correlates weakly with actual accuracy and the qualities of many mappings are underestimated, encouraging the researchers to discard correct mappings. Further, these low-quality mappings tend to correlate with variations in the genome (both single nucleotide and structural), and such mappings are important in accurately identifying genomic variants. Approach: We develop a machine learning tool, LoQuM (LOgistic regression tool for calibrating the Quality of short read mappings, to assign reliable mapping quality scores to mappings of Illumina reads returned by any alignment tool. LoQuM uses statistics on the read (base quality scores reported by the sequencer) and the alignment (number of matches, mismatches and deletions, mapping quality score returned by the alignment tool, if available, and number of mappings) as features for classification and uses simulated reads to learn a logistic regression model that relates these features to actual mapping quality. Results: We test the predictions of LoQuM on an independent dataset generated by the ART short read simulation software and observe that LoQuM can ‘resurrect’ many mappings that are assigned zero quality scores by the alignment tools and are therefore likely to be discarded by researchers. We also observe that the recalibration of mapping quality scores greatly enhances the precision of called single nucleotide polymorphisms. Availability: LoQuM is available as open source at http://compbio.case.edu/loqum/. Contact: matthew.ruffalo@case.edu. PMID:22962451

Topographic map of the Coronae Montes region of Mars - MTM 500k -35/087E OMKTT

USGS Publications Warehouse

Rosiek, Mark R.; Redding, Bonnie L.; Galuszca, Donna M.

2005-01-01

This map is part of a series of topographic maps of areas of special scientific interest on Mars. The topography was compiled photogrammetrically using Viking Orbiter stereo image pairs. The contour interval is 250 m. Horizontal and vertical control was established using the USGS Mars Digital Image Model 2.0 (MDIM 2.0) and data from the Mars Orbiter Laser Altimeter (MOLA).

Topographic Map of the Northeast Ascraeus Mons Region of Mars - MTM 500k 15/257E OMKT

USGS Publications Warehouse

,

2004-01-01

This map is part of a series of topographic maps of areas of special scientific interest on Mars. The topography was compiled photogrammetically using Viking Orbiter stereo image pairs. The contour interval is 250 meters. Horizontal and vertical control was established using the USGS Mars Digital Image Model 2.0 (MDIM 2.0) and data from the Mars Orbiter Laser Altimeter (MOLA).

Topographic Map of the Northwest Ascraeus Mons Region of Mars - MTM 500k 15/252E OMKT

USGS Publications Warehouse

,

2004-01-01

This map is part of a series of topographic maps of areas of special scientific interest on Mars. The topography was compiled photogrammetically using Viking Orbiter stereo image pairs. The contour interval is 250 meters. Horizontal and vertical control was established using the USGS Mars Digital Image Model 2.0 (MDIM 2.0) and data from the Mars Orbiter Laser Altimeter (MOLA).

Topographic Map of the Southeast Ascraeus Mons Region of Mars - MTM 500k 10/257E OMKT

USGS Publications Warehouse

,

2004-01-01

This map is part of a series of topographic maps of areas of special scientific interest on Mars. The topography was compiled photogrammetically using Viking Orbiter stereo image pairs. The contour interval is 250 meters. Horizontal and vertical control was established using the USGS Mars Digital Image Model 2.0 (MDIM 2.0) and data from the Mars Orbiter Laser Altimeter (MOLA).

Topographic Map of the Southwest Ascraeus Mons Region of Mars - MTM 500k 10/252E OMKT

USGS Publications Warehouse

,

2004-01-01

This map is part of a series of topographic maps of areas of special scientific interest on Mars. The topography was compiled photogrammetically using Viking Orbiter stereo image pairs. The contour interval is 250 meters. Horizontal and vertical control was established using the USGS Mars Digital Image Model 2.0 (MDIM 2.0) and data from the Mars Orbiter Laser Altimeter (MOLA).

Detecting long-duration cloud contamination in hyper-temporal NDVI imagery

NASA Astrophysics Data System (ADS)

Ali, Amjad; de Bie, C. A. J. M.; Skidmore, A. K.

2013-10-01

Cloud contamination impacts on the quality of hyper-temporal NDVI imagery and its subsequent interpretation. Short-duration cloud impacts are easily removed by using quality flags and an upper envelope filter, but long-duration cloud contamination of NDVI imagery remains. In this paper, an approach that goes beyond the use of quality flags and upper envelope filtering is tested to detect when and where long-duration clouds are responsible for unreliable NDVI readings, so that a user can flag those data as missing. The study is based on MODIS Terra and the combined Terra-Aqua 16-day NDVI product for the south of Ghana, where persistent cloud cover occurs throughout the year. The combined product could be assumed to have less cloud contamination, since it is based on two images per day. Short-duration cloud effects were removed from the two products through using the adaptive Savitzky-Golay filter. Then for each 'cleaned' product an unsupervised classified map was prepared using the ISODATA algorithm, and, by class, plots were prepared to depict changes over time of the means and the standard deviations in NDVI values. By comparing plots of similar classes, long-duration cloud contamination appeared to display a decline in mean NDVI below the lower limit 95% confidence interval with a coinciding increase in standard deviation above the upper limit 95% confidence interval. Regression analysis was carried out per NDVI class in two randomly selected groups in order to statistically test standard deviation values related to long-duration cloud contamination. A decline in seasonal NDVI values (growing season) were below the lower limit of 95% confidence interval as well as a concurrent increase in standard deviation values above the upper limit of the 95% confidence interval were noted in 34 NDVI classes. The regression analysis results showed that differences in NDVI class values between the Terra and the Terra-Aqua imagery were significantly correlated (p < 0.05) with the corresponding standard deviation values of the Terra imagery in case of all NDVI classes of two selected NDVI groups. The method successfully detects long-duration cloud contamination that results in unreliable NDVI values. The approach offers scientists interested in time series analysis a method of masking by area (class) the periods when pre-cleaned NDVI values remain affected by clouds. The approach requires no additional data for execution purposes but involves unsupervised classification of the imagery to carry out the evaluation of class-specific mean NDVI and standard deviation values over time.

Thorough statistical comparison of machine learning regression models and their ensembles for sub-pixel imperviousness and imperviousness change mapping

NASA Astrophysics Data System (ADS)

Drzewiecki, Wojciech

2017-12-01

We evaluated the performance of nine machine learning regression algorithms and their ensembles for sub-pixel estimation of impervious areas coverages from Landsat imagery. The accuracy of imperviousness mapping in individual time points was assessed based on RMSE, MAE and R2. These measures were also used for the assessment of imperviousness change intensity estimations. The applicability for detection of relevant changes in impervious areas coverages at sub-pixel level was evaluated using overall accuracy, F-measure and ROC Area Under Curve. The results proved that Cubist algorithm may be advised for Landsat-based mapping of imperviousness for single dates. Stochastic gradient boosting of regression trees (GBM) may be also considered for this purpose. However, Random Forest algorithm is endorsed for both imperviousness change detection and mapping of its intensity. In all applications the heterogeneous model ensembles performed at least as well as the best individual models or better. They may be recommended for improving the quality of sub-pixel imperviousness and imperviousness change mapping. The study revealed also limitations of the investigated methodology for detection of subtle changes of imperviousness inside the pixel. None of the tested approaches was able to reliably classify changed and non-changed pixels if the relevant change threshold was set as one or three percent. Also for fi ve percent change threshold most of algorithms did not ensure that the accuracy of change map is higher than the accuracy of random classifi er. For the threshold of relevant change set as ten percent all approaches performed satisfactory.

Monopole and dipole estimation for multi-frequency sky maps by linear regression

NASA Astrophysics Data System (ADS)

Wehus, I. K.; Fuskeland, U.; Eriksen, H. K.; Banday, A. J.; Dickinson, C.; Ghosh, T.; Górski, K. M.; Lawrence, C. R.; Leahy, J. P.; Maino, D.; Reich, P.; Reich, W.

2017-01-01

We describe a simple but efficient method for deriving a consistent set of monopole and dipole corrections for multi-frequency sky map data sets, allowing robust parametric component separation with the same data set. The computational core of this method is linear regression between pairs of frequency maps, often called T-T plots. Individual contributions from monopole and dipole terms are determined by performing the regression locally in patches on the sky, while the degeneracy between different frequencies is lifted whenever the dominant foreground component exhibits a significant spatial spectral index variation. Based on this method, we present two different, but each internally consistent, sets of monopole and dipole coefficients for the nine-year WMAP, Planck 2013, SFD 100 μm, Haslam 408 MHz and Reich & Reich 1420 MHz maps. The two sets have been derived with different analysis assumptions and data selection, and provide an estimate of residual systematic uncertainties. In general, our values are in good agreement with previously published results. Among the most notable results are a relative dipole between the WMAP and Planck experiments of 10-15μK (depending on frequency), an estimate of the 408 MHz map monopole of 8.9 ± 1.3 K, and a non-zero dipole in the 1420 MHz map of 0.15 ± 0.03 K pointing towards Galactic coordinates (l,b) = (308°,-36°) ± 14°. These values represent the sum of any instrumental and data processing offsets, as well as any Galactic or extra-Galactic component that is spectrally uniform over the full sky.

A high-resolution genetic, physical, and comparative gene map of the doublefoot (Dbf) region of mouse chromosome 1 and the region of conserved synteny on human chromosome 2q35.

PubMed

Hayes, C; Rump, A; Cadman, M R; Harrison, M; Evans, E P; Lyon, M F; Morriss-Kay, G M; Rosenthal, A; Brown, S D

2001-12-01

The mouse doublefoot (Dbf) mutant exhibits preaxial polydactyly in association with craniofacial defects. This mutation has previously been mapped to mouse chromosome 1. We have used a positional cloning strategy, coupled with a comparative sequencing approach using available human draft sequence, to identify putative candidates for the Dbf gene in the mouse and in homologous human region. We have constructed a high-resolution genetic map of the region, localizing the mutation to a 0.4-cM (+/-0.0061) interval on mouse chromosome 1. Furthermore, we have constructed contiguous BAC/PAC clone maps across the mouse and human Dbf region. Using existing markers and additional sequence tagged sites, which we have generated, we have anchored the physical map to the genetic map. Through the comparative sequencing of these clones we have identified 35 genes within this interval, indicating that the region is gene-rich. From this we have identified several genes that are known to be differentially expressed in the developing mid-gestation mouse embryo, some in the developing embryonic limb buds. These genes include those encoding known developmental signaling molecules such as WNT proteins and IHH, and we provide evidence that these genes are candidates for the Dbf mutation.

Reliable prediction intervals with regression neural networks.

PubMed

Papadopoulos, Harris; Haralambous, Haris

2011-10-01

This paper proposes an extension to conventional regression neural networks (NNs) for replacing the point predictions they produce with prediction intervals that satisfy a required level of confidence. Our approach follows a novel machine learning framework, called Conformal Prediction (CP), for assigning reliable confidence measures to predictions without assuming anything more than that the data are independent and identically distributed (i.i.d.). We evaluate the proposed method on four benchmark datasets and on the problem of predicting Total Electron Content (TEC), which is an important parameter in trans-ionospheric links; for the latter we use a dataset of more than 60000 TEC measurements collected over a period of 11 years. Our experimental results show that the prediction intervals produced by our method are both well calibrated and tight enough to be useful in practice. Copyright © 2011 Elsevier Ltd. All rights reserved.

CT-1-CP-induced ventricular electrical remodeling in mice.

PubMed

Chen, Shu-fen; Wei, Tao-zhi; Rao, Li-ya; Xu, Ming-guang; Dong, Zhan-ling

2015-02-01

The chronic effects of carboxyl-terminal polypeptide of Cardiotrophin-1 (CT-1-CP) on ventricular electrical remodeling were investigated. CT-1-CP, which contains 16 amino acids in sequence of the C-terminal of Cardiotrophin-1, was selected and synthesized, and then administered to Kunming mice (aged 5 weeks) by intraperitoneal injection (500 ng·g⁻¹·day⁻¹) (4 groups, n=10 and female: male=1:1 in each group) for 1, 2, 3 and 4 weeks, respectively. The control group (n=10, female: male=1:1) was injected by physiological saline for 4 weeks. The epicardial monophasic action potential (MAP) was recorded by using a contact-type MAP electrode placed vertically on the left ventricular (LV) epicardium surface, and the electrocardiogram (ECG) signal in lead II was monitored synchronously. ECG intervals (RR, PR, QRS and QT) and the amplitude of MAP (Am), the maximum upstroke velocity (Vmax), as well as action potential durations (APDs) at different repolarization levels (APD30, APD50, APD70, and APD90) of MAP were determined and analyzed in detail. There were no significant differences in RR and P intervals between CT-1-CP-treated groups and control group, but the PR segment and the QRS complex were greater in the former than in the latter (F=2.681 and 5.462 respectively, P<0.05). Though QT interval and the corrected QT interval (QTc) were shorter in CT-1-CP-treated groups than in control group, the QT dispersion (QTd) of them was greater in the latter than in the former (F=3.090, P<0.05) and increased with the time. The ECG monitoring synchronously with the MAP showed that the compression of MAP electrode on the left ventricular epicardium induced performance similar to myocardium ischemia. As compared with those before chest-opening, the PR segment and QT intervals remained basically unchanged in control group, but prolonged significantly in all CT-1-CP-treated groups and the prolongation of QT intervals increased gradually along with the time of exposure to CT-1-CP. The QRS complex had no significant change in control group, one-week and three-week CT-1-CP-treated groups, but prolonged significantly in two-week and four-week CT-1-CP-treated groups. Interestingly, the QTd after chest-opening was significantly greater than that before chest-opening in control group (t=5.242, P<0.01), but decreased along with the time in CT-1-CP-treated groups. The mean MAP amplitude, Vmax and APD were greater in CT-1-CP-treated groups than those in control group, and became more obvious along with the time. The APD in four CT-1-CP-treat groups was prolonged mainly in middle to final repolarization phase. The difference among these groups became significant in middle phase (APD50) (F=6.076, P<0.01) and increased furthermore in late and final phases (APD70: F=10.054; APD90: F=18.691, P<0.01) along with the time of injection of CT-1-CP. The chronic action of CT-1-CP might induce the adapting alteration in cardiac conductivity and ventricular repolarization. The amplitude and the Vmax of the anterior LV epicardial MAP increased obviously, and the APD prolonged mainly in late and final phase of repolarization.

Translation of Bernstein Coefficients Under an Affine Mapping of the Unit Interval

NASA Technical Reports Server (NTRS)

Alford, John A., II

2012-01-01

We derive an expression connecting the coefficients of a polynomial expanded in the Bernstein basis to the coefficients of an equivalent expansion of the polynomial under an affine mapping of the domain. The expression may be useful in the calculation of bounds for multi-variate polynomials.

Quantitative genetic bases of anthocyanin variation in grape (Vitis vinifera L. ssp. sativa) berry: a quantitative trait locus to quantitative trait nucleotide integrated study.

PubMed

Fournier-Level, Alexandre; Le Cunff, Loïc; Gomez, Camila; Doligez, Agnès; Ageorges, Agnès; Roux, Catherine; Bertrand, Yves; Souquet, Jean-Marc; Cheynier, Véronique; This, Patrice

2009-11-01

The combination of QTL mapping studies of synthetic lines and association mapping studies of natural diversity represents an opportunity to throw light on the genetically based variation of quantitative traits. With the positional information provided through quantitative trait locus (QTL) mapping, which often leads to wide intervals encompassing numerous genes, it is now feasible to directly target candidate genes that are likely to be responsible for the observed variation in completely sequenced genomes and to test their effects through association genetics. This approach was performed in grape, a newly sequenced genome, to decipher the genetic architecture of anthocyanin content. Grapes may be either white or colored, ranging from the lightest pink to the darkest purple tones according to the amount of anthocyanin accumulated in the berry skin, which is a crucial trait for both wine quality and human nutrition. Although the determinism of the white phenotype has been fully identified, the genetic bases of the quantitative variation of anthocyanin content in berry skin remain unclear. A single QTL responsible for up to 62% of the variation in the anthocyanin content was mapped on a Syrah x Grenache F(1) pseudo-testcross. Among the 68 unigenes identified in the grape genome within the QTL interval, a cluster of four Myb-type genes was selected on the basis of physiological evidence (VvMybA1, VvMybA2, VvMybA3, and VvMybA4). From a core collection of natural resources (141 individuals), 32 polymorphisms revealed significant association, and extended linkage disequilibrium was observed. Using a multivariate regression method, we demonstrated that five polymorphisms in VvMybA genes except VvMybA4 (one retrotransposon, three single nucleotide polymorphisms and one 2-bp insertion/deletion) accounted for 84% of the observed variation. All these polymorphisms led to either structural changes in the MYB proteins or differences in the VvMybAs promoters. We concluded that the continuous variation in anthocyanin content in grape was explained mainly by a single gene cluster of three VvMybA genes. The use of natural diversity helped to reduce one QTL to a set of five quantitative trait nucleotides and gave a clear picture of how isogenes combined their effects to shape grape color. Such analysis also illustrates how isogenes combine their effect to shape a complex quantitative trait and enables the definition of markers directly targeted for upcoming breeding programs.

Geologic and hydrostratigraphic map of the Anhalt, Fischer, and Spring Branch 7.5-minute quadrangles, Blanco, Comal, and Kendall Counties, Texas

USGS Publications Warehouse

Clark, Allan K.; Robert R. Morris,

2015-01-01

The hydrostratigraphic units of the Edwards and Trinity aquifers have been mapped and described herein using a classification system developed by Choquette and Pray (1970), which is based on porosity types being fabric or not-fabric selective. The naming of hydrostratigraphic units is also based on preexisting names and topographic or historical features that occur in outcrop. The only hydrostratigraphic unit of the Edwards aquifer present in the study area is VIII hydrostratigraphic unit. The mapped hydrostratigraphic units of the upper Trinity aquifer are, from top to bottom: the cavernous, Camp Bullis, upper evaporite, fossiliferous, and lower evaporite and they are interval equivalent to the upper member of the Glen Rose Limestone. The middle Trinity aquifer (interval equivalent to the lower member of the Glen Rose Limestone) contains, from top to bottom: the Bulverde, Little Blanco, Twin Sisters, Doeppenschmidt, Rust, and Honey Creek hydrostratigraphic units. The lower part of the middle Trinity aquifer is formed by the Hensell, Cow Creek, and Hammett hydrostratigraphic units which are interval equivalent to the Hensell Sand Member, the Cow Creek Limestone, and the Hammett Shale Member, respectively, of the Pearsall Formation.

A novel autosomal recessive non-syndromic hearing impairment locus (DFNB47) maps to chromosome 2p25.1-p24.3.

PubMed

Hassan, Muhammad Jawad; Santos, Regie Lyn P; Rafiq, Muhammad Arshad; Chahrour, Maria H; Pham, Thanh L; Wajid, Muhammad; Hijab, Nadine; Wambangco, Michael; Lee, Kwanghyuk; Ansar, Muhammad; Yan, Kai; Ahmad, Wasim; Leal, Suzanne M

2006-01-01

Hereditary hearing impairment (HI) displays extensive genetic heterogeneity. Autosomal recessive (AR) forms of prelingual HI account for approximately 75% of cases with a genetic etiology. A novel AR non-syndromic HI locus (DFNB47) was mapped to chromosome 2p25.1-p24.3, in two distantly related Pakistani kindreds. Genome scan and fine mapping were carried out using microsatellite markers. Multipoint linkage analysis resulted in a maximum LOD score of 4.7 at markers D2S1400 and D2S262. The three-unit support interval was bounded by D2S330 and D2S131. The region of homozygosity was found within the three-unit support interval and flanked by markers D2S2952 and D2S131, which corresponds to 13.2 cM according to the Rutgers combined linkage-physical map. This region contains 5.3 Mb according to the sequence-based physical map. Three candidate genes, KCNF1, ID2 and ATP6V1C2 were sequenced, and were found to be negative for functional sequence variants.

A novel autosomal recessive non-syndromic hearing impairment locus (DFNB47) maps to chromosome 2p25.1-p24.3

PubMed Central

Hassan, Muhammad Jawad; Santos, Regie Lyn P.; Rafiq, Muhammad Arshad; Chahrour, Maria H.; Pham, Thanh L.; Wajid, Muhammad; Hijab, Nadine; Wambangco, Michael; Lee, Kwanghyuk; Ansar, Muhammad; Yan, Kai; Ahmad, Wasim; Leal, Suzanne M.

2010-01-01

Hereditary hearing impairment (HI) displays extensive genetic heterogeneity. Autosomal recessive (AR) forms of prelingual HI account for ~75% of cases with a genetic etiology. A novel AR non-syndromic HI locus (DFNB47) was mapped to chromosome 2p25.1-p24.3, in two distantly related Pakistani kindreds. Genome scan and fine mapping were carried out using microsatellite markers. Multipoint linkage analysis resulted in a maximum LOD score of 4.7 at markers D2S1400 and D2S262. The three-unit support interval was bounded by D2S330 and D2S131. The region of homozygosity was found within the three-unit support interval and flanked by markers D2S2952 and D2S131, which corresponds to 13.2 cM according to the Rutgers combined linkage-physical map. This region contains 5.3 Mb according to the sequence-based physical map. Three candidate genes, KCNF1, ID2 and ATP6V1C2 were sequenced, and were found to be negative for functional sequence variants. PMID:16261342

A high-resolution map of the Grp1 locus on chromosome V of potato harbouring broad-spectrum resistance to the cyst nematode species Globodera pallida and Globodera rostochiensis.

PubMed

Finkers-Tomczak, Anna; Danan, Sarah; van Dijk, Thijs; Beyene, Amelework; Bouwman, Liesbeth; Overmars, Hein; van Eck, Herman; Goverse, Aska; Bakker, Jaap; Bakker, Erin

2009-06-01

The Grp1 locus confers broad-spectrum resistance to the potato cyst nematode species Globodera pallida and Globodera rostochiensis and is located in the GP21-GP179 interval on the short arm of chromosome V of potato. A high-resolution map has been developed using the diploid mapping population RHAM026, comprising 1,536 genotypes. The flanking markers GP21 and GP179 have been used to screen the 1,536 genotypes for recombination events. Interval mapping of the resistances to G. pallida Pa2 and G. rostochiensis Ro5 resulted in two nearly identical LOD graphs with the highest LOD score just north of marker TG432. Detailed analysis of the 44 recombinant genotypes showed that G. pallida and G. rostochiensis resistance could not be separated and map to the same location between marker SPUD838 and TG432. It is suggested that the quantitative resistance to both nematode species at the Grp1 locus is mediated by one or more tightly linked R genes that might belong to the NBS-LRR class.

Geographically weighted regression and geostatistical techniques to construct the geogenic radon potential map of the Lazio region: A methodological proposal for the European Atlas of Natural Radiation.

PubMed

Ciotoli, G; Voltaggio, M; Tuccimei, P; Soligo, M; Pasculli, A; Beaubien, S E; Bigi, S

2017-01-01

In many countries, assessment programmes are carried out to identify areas where people may be exposed to high radon levels. These programmes often involve detailed mapping, followed by spatial interpolation and extrapolation of the results based on the correlation of indoor radon values with other parameters (e.g., lithology, permeability and airborne total gamma radiation) to optimise the radon hazard maps at the municipal and/or regional scale. In the present work, Geographical Weighted Regression and geostatistics are used to estimate the Geogenic Radon Potential (GRP) of the Lazio Region, assuming that the radon risk only depends on the geological and environmental characteristics of the study area. A wide geodatabase has been organised including about 8000 samples of soil-gas radon, as well as other proxy variables, such as radium and uranium content of homogeneous geological units, rock permeability, and faults and topography often associated with radon production/migration in the shallow environment. All these data have been processed in a Geographic Information System (GIS) using geospatial analysis and geostatistics to produce base thematic maps in a 1000 m × 1000 m grid format. Global Ordinary Least Squared (OLS) regression and local Geographical Weighted Regression (GWR) have been applied and compared assuming that the relationships between radon activities and the environmental variables are not spatially stationary, but vary locally according to the GRP. The spatial regression model has been elaborated considering soil-gas radon concentrations as the response variable and developing proxy variables as predictors through the use of a training dataset. Then a validation procedure was used to predict soil-gas radon values using a test dataset. Finally, the predicted values were interpolated using the kriging algorithm to obtain the GRP map of the Lazio region. The map shows some high GRP areas corresponding to the volcanic terrains (central-northern sector of Lazio region) and to faulted and fractured carbonate rocks (central-southern and eastern sectors of the Lazio region). This typical local variability of autocorrelated phenomena can only be taken into account by using local methods for spatial data analysis. The constructed GRP map can be a useful tool to implement radon policies at both the national and local levels, providing critical data for land use and planning purposes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Bootstrap investigation of the stability of a Cox regression model.

PubMed

Altman, D G; Andersen, P K

1989-07-01

We describe a bootstrap investigation of the stability of a Cox proportional hazards regression model resulting from the analysis of a clinical trial of azathioprine versus placebo in patients with primary biliary cirrhosis. We have considered stability to refer both to the choice of variables included in the model and, more importantly, to the predictive ability of the model. In stepwise Cox regression analyses of 100 bootstrap samples using 17 candidate variables, the most frequently selected variables were those selected in the original analysis, and no other important variable was identified. Thus there was no reason to doubt the model obtained in the original analysis. For each patient in the trial, bootstrap confidence intervals were constructed for the estimated probability of surviving two years. It is shown graphically that these intervals are markedly wider than those obtained from the original model.

Prioritization of Candidate Genes in QTL Regions for Physiological and Biochemical Traits Underlying Drought Response in Barley (Hordeum vulgare L.)

PubMed Central

Gudys, Kornelia; Guzy-Wrobelska, Justyna; Janiak, Agnieszka; Dziurka, Michał A.; Ostrowska, Agnieszka; Hura, Katarzyna; Jurczyk, Barbara; Żmuda, Katarzyna; Grzybkowska, Daria; Śróbka, Joanna; Urban, Wojciech; Biesaga-Koscielniak, Jolanta; Filek, Maria; Koscielniak, Janusz; Mikołajczak, Krzysztof; Ogrodowicz, Piotr; Krystkowiak, Karolina; Kuczyńska, Anetta; Krajewski, Paweł; Szarejko, Iwona

2018-01-01

Drought is one of the most adverse abiotic factors limiting growth and productivity of crops. Among them is barley, ranked fourth cereal worldwide in terms of harvested acreage and production. Plants have evolved various mechanisms to cope with water deficit at different biological levels, but there is an enormous challenge to decipher genes responsible for particular complex phenotypic traits, in order to develop drought tolerant crops. This work presents a comprehensive approach for elucidation of molecular mechanisms of drought tolerance in barley at the seedling stage of development. The study includes mapping of QTLs for physiological and biochemical traits associated with drought tolerance on a high-density function map, projection of QTL confidence intervals on barley physical map, and the retrievement of positional candidate genes (CGs), followed by their prioritization based on Gene Ontology (GO) enrichment analysis. A total of 64 QTLs for 25 physiological and biochemical traits that describe plant water status, photosynthetic efficiency, osmoprotectant and hormone content, as well as antioxidant activity, were positioned on a consensus map, constructed using RIL populations developed from the crosses between European and Syrian genotypes. The map contained a total of 875 SNP, SSR and CGs, spanning 941.86 cM with resolution of 1.1 cM. For the first time, QTLs for ethylene, glucose, sucrose, maltose, raffinose, α-tocopherol, γ-tocotrienol content, and catalase activity, have been mapped in barley. Based on overlapping confidence intervals of QTLs, 11 hotspots were identified that enclosed more than 60% of mapped QTLs. Genetic and physical map integration allowed the identification of 1,101 positional CGs within the confidence intervals of drought response-specific QTLs. Prioritization resulted in the designation of 143 CGs, among them were genes encoding antioxidants, carboxylic acid biosynthesis enzymes, heat shock proteins, small auxin up-regulated RNAs, nitric oxide synthase, ATP sulfurylases, and proteins involved in regulation of flowering time. This global approach may be proposed for identification of new CGs that underlies QTLs responsible for complex traits. PMID:29946328

Nationwide Multicenter Reference Interval Study for 28 Common Biochemical Analytes in China.

PubMed

Xia, Liangyu; Chen, Ming; Liu, Min; Tao, Zhihua; Li, Shijun; Wang, Liang; Cheng, Xinqi; Qin, Xuzhen; Han, Jianhua; Li, Pengchang; Hou, Li'an; Yu, Songlin; Ichihara, Kiyoshi; Qiu, Ling

2016-03-01

A nationwide multicenter study was conducted in the China to explore sources of variation of reference values and establish reference intervals for 28 common biochemical analytes, as a part of the International Federation of Clinical Chemistry and Laboratory Medicine, Committee on Reference Intervals and Decision Limits (IFCC/C-RIDL) global study on reference values. A total of 3148 apparently healthy volunteers were recruited in 6 cities covering a wide area in China. Blood samples were tested in 2 central laboratories using Beckman Coulter AU5800 chemistry analyzers. Certified reference materials and value-assigned serum panel were used for standardization of test results. Multiple regression analysis was performed to explore sources of variation. Need for partition of reference intervals was evaluated based on 3-level nested ANOVA. After secondary exclusion using the latent abnormal values exclusion method, reference intervals were derived by a parametric method using the modified Box-Cox formula. Test results of 20 analytes were made traceable to reference measurement procedures. By the ANOVA, significant sex-related and age-related differences were observed in 12 and 12 analytes, respectively. A small regional difference was observed in the results for albumin, glucose, and sodium. Multiple regression analysis revealed BMI-related changes in results of 9 analytes for man and 6 for woman. Reference intervals of 28 analytes were computed with 17 analytes partitioned by sex and/or age. In conclusion, reference intervals of 28 common chemistry analytes applicable to Chinese Han population were established by use of the latest methodology. Reference intervals of 20 analytes traceable to reference measurement procedures can be used as common reference intervals, whereas others can be used as the assay system-specific reference intervals in China.

Nationwide Multicenter Reference Interval Study for 28 Common Biochemical Analytes in China

PubMed Central

Xia, Liangyu; Chen, Ming; Liu, Min; Tao, Zhihua; Li, Shijun; Wang, Liang; Cheng, Xinqi; Qin, Xuzhen; Han, Jianhua; Li, Pengchang; Hou, Li’an; Yu, Songlin; Ichihara, Kiyoshi; Qiu, Ling

2016-01-01

Abstract A nationwide multicenter study was conducted in the China to explore sources of variation of reference values and establish reference intervals for 28 common biochemical analytes, as a part of the International Federation of Clinical Chemistry and Laboratory Medicine, Committee on Reference Intervals and Decision Limits (IFCC/C-RIDL) global study on reference values. A total of 3148 apparently healthy volunteers were recruited in 6 cities covering a wide area in China. Blood samples were tested in 2 central laboratories using Beckman Coulter AU5800 chemistry analyzers. Certified reference materials and value-assigned serum panel were used for standardization of test results. Multiple regression analysis was performed to explore sources of variation. Need for partition of reference intervals was evaluated based on 3-level nested ANOVA. After secondary exclusion using the latent abnormal values exclusion method, reference intervals were derived by a parametric method using the modified Box–Cox formula. Test results of 20 analytes were made traceable to reference measurement procedures. By the ANOVA, significant sex-related and age-related differences were observed in 12 and 12 analytes, respectively. A small regional difference was observed in the results for albumin, glucose, and sodium. Multiple regression analysis revealed BMI-related changes in results of 9 analytes for man and 6 for woman. Reference intervals of 28 analytes were computed with 17 analytes partitioned by sex and/or age. In conclusion, reference intervals of 28 common chemistry analytes applicable to Chinese Han population were established by use of the latest methodology. Reference intervals of 20 analytes traceable to reference measurement procedures can be used as common reference intervals, whereas others can be used as the assay system-specific reference intervals in China. PMID:26945390

Characterization of the collagen component of cartilage repair tissue of the talus with quantitative MRI: comparison of T2 relaxation time measurements with a diffusion-weighted double-echo steady-state sequence (dwDESS).

PubMed

Kretzschmar, M; Bieri, O; Miska, M; Wiewiorski, M; Hainc, N; Valderrabano, V; Studler, U

2015-04-01

The purpose of this study was to characterize the collagen component of repair tissue (RT) of the talus after autologous matrix-induced chondrogenesis (AMIC) using quantitative T2 and diffusion-weighted imaging. Mean T2 values and diffusion coefficients of AMIC-RT and normal cartilage of the talus of 25 patients with posttraumatic osteochondral lesions and AMIC repair were compared in a cross-sectional design using partially spoiled steady-state free precession (pSSFP) for T2 quantification, and diffusion-weighted double-echo steady-state (dwDESS) for diffusion measurement. RT and cartilage were graded with modified Noyes and MOCART scores on morphological sequences. An association between follow-up interval and quantitative MRI measures was assessed using multivariate regression, after stratifying the cohort according to time interval between surgery and MRI. Mean T2 of the AMIC-RT and cartilage were 43.1 ms and 39.1 ms, respectively (p = 0.26). Mean diffusivity of the RT (1.76 μm(2)/ms) was significantly higher compared to normal cartilage (1.46 μm(2)/ms) (p = 0.0092). No correlation was found between morphological and quantitative parameters. RT diffusivity was lowest in the subgroup with follow-up >28 months (p = 0.027). Compared to T2-mapping, dwDESS demonstrated greater sensitivity in detecting differences in the collagen matrix between AMIC-RT and cartilage. Decreased diffusivity in patients with longer follow-up times may indicate an increased matrix organization of RT. • MRI is used to assess morphology of the repair tissue during follow-up. • Quantitative MRI allows an estimation of biochemical properties of the repair tissue. • Differences between repair tissue and cartilage were more significant with dwDESS than T2 mapping.

Germplasm-regression-combined (GRC) marker-trait association identification in plant breeding: a challenge for plant biotechnological breeding under soil water deficit conditions.

PubMed

Ruan, Cheng-Jiang; Xu, Xue-Xuan; Shao, Hong-Bo; Jaleel, Cheruth Abdul

2010-09-01

In the past 20 years, the major effort in plant breeding has changed from quantitative to molecular genetics with emphasis on quantitative trait loci (QTL) identification and marker assisted selection (MAS). However, results have been modest. This has been due to several factors including absence of tight linkage QTL, non-availability of mapping populations, and substantial time needed to develop such populations. To overcome these limitations, and as an alternative to planned populations, molecular marker-trait associations have been identified by the combination between germplasm and the regression technique. In the present preview, the authors (1) survey the successful applications of germplasm-regression-combined (GRC) molecular marker-trait association identification in plants; (2) describe how to do the GRC analysis and its differences from mapping QTL based on a linkage map reconstructed from the planned populations; (3) consider the factors that affect the GRC association identification, including selections of optimal germplasm and molecular markers and testing of identification efficiency of markers associated with traits; and (4) finally discuss the future prospects of GRC marker-trait association analysis used in plant MAS/QTL breeding programs, especially in long-juvenile woody plants when no other genetic information such as linkage maps and QTL are available.

Probabilistic change mapping from airborne LiDAR for post-disaster damage assessment

NASA Astrophysics Data System (ADS)

Jalobeanu, A.; Runyon, S. C.; Kruse, F. A.

2013-12-01

When both pre- and post-event LiDAR point clouds are available, change detection can be performed to identify areas that were most affected by a disaster event, and to obtain a map of quantitative changes in terms of height differences. In the case of earthquakes in built-up areas for instance, first responders can use a LiDAR change map to help prioritize search and recovery efforts. The main challenge consists of producing reliable change maps, robust to collection conditions, free of processing artifacts (due for instance to triangulation or gridding), and taking into account the various sources of uncertainty. Indeed, datasets acquired within a few years interval are often of different point density (sometimes an order of magnitude higher for recent data), different acquisition geometries, and very likely suffer from georeferencing errors and geometric discrepancies. All these differences might not be important for producing maps from each dataset separately, but they are crucial when performing change detection. We have developed a novel technique for the estimation of uncertainty maps from the LiDAR point clouds, using Bayesian inference, treating all variables as random. The main principle is to grid all points on a common grid before attempting any comparison, as working directly with point clouds is cumbersome and time consuming. A non-parametric approach based on local linear regression was implemented, assuming a locally linear model for the surface. This enabled us to derive error bars on gridded elevations, and then elevation differences. In this way, a map of statistically significant changes could be computed - whereas a deterministic approach would not allow testing of the significance of differences between the two datasets. This approach allowed us to take into account not only the observation noise (due to ranging, position and attitude errors) but also the intrinsic roughness of the observed surfaces occurring when scanning vegetation. As only elevation differences above a predefined noise level are accounted for (according to a specified confidence interval related to the allowable false alarm rate) the change detection is robust to all these sources of noise. To first validate the approach, we built small-scale models and scanned them using a terrestrial laser scanner to establish 'ground truth'. Changes were manually applied to the models then new scans were performed and analyzed. Additionally, two airborne datasets of the Monterey Peninsula, California, were processed and analyzed. The first one was acquired during 2010 (with relatively low point density, 1-3 pts/m2), and the second one was acquired during 2012 (with up to 30 pts/m2). To perform the comparison, a new point cloud registration technique was developed and the data were registered to a common 1 m grid. The goal was to correct systematic shifts due to GPS and INS errors, and focus on the actual height differences regardless of the absolute planimetric accuracy of the datasets. Though no major disaster event occurred between the two acquisition dates, sparse changes were detected and interpreted mostly as construction and natural landscape evolution.

An LPV Adaptive Observer for Updating a Map Applied to an MAF Sensor in a Diesel Engine.

PubMed

Liu, Zhiyuan; Wang, Changhui

2015-10-23

In this paper, a new method for mass air flow (MAF) sensor error compensation and an online updating error map (or lookup table) due to installation and aging in a diesel engine is developed. Since the MAF sensor error is dependent on the engine operating point, the error model is represented as a two-dimensional (2D) map with two inputs, fuel mass injection quantity and engine speed. Meanwhile, the 2D map representing the MAF sensor error is described as a piecewise bilinear interpolation model, which can be written as a dot product between the regression vector and parameter vector using a membership function. With the combination of the 2D map regression model and the diesel engine air path system, an LPV adaptive observer with low computational load is designed to estimate states and parameters jointly. The convergence of the proposed algorithm is proven under the conditions of persistent excitation and given inequalities. The observer is validated against the simulation data from engine software enDYNA provided by Tesis. The results demonstrate that the operating point-dependent error of the MAF sensor can be approximated acceptably by the 2D map from the proposed method.

Modeling Relationships Between Flight Crew Demographics and Perceptions of Interval Management

NASA Technical Reports Server (NTRS)

Remy, Benjamin; Wilson, Sara R.

2016-01-01

The Interval Management Alternative Clearances (IMAC) human-in-the-loop simulation experiment was conducted to assess interval management system performance and participants' acceptability and workload while performing three interval management clearance types. Twenty-four subject pilots and eight subject controllers flew ten high-density arrival scenarios into Denver International Airport during two weeks of data collection. This analysis examined the possible relationships between subject pilot demographics on reported perceptions of interval management in IMAC. Multiple linear regression models were created with a new software tool to predict subject pilot questionnaire item responses from demographic information. General patterns were noted across models that may indicate flight crew demographics influence perceptions of interval management.

Association of angiotensin-converting-enzyme gene polymorphism with the depressor response to mild exercise therapy in patients with mild to moderate essential hypertension.

PubMed

Zhang, B; Sakai, T; Miura, S; Kiyonaga, A; Tanaka, H; Shindo, M; Saku, K

2002-10-01

We studied the association of angiotensin I-converting enzyme (ACE) gene polymorphism with the depressor response to exercise therapy in 64 Japanese subjects with mild to moderate essential hypertension. Each subject performed 10 weeks of mild (lactate threshold intensity: approximately 50% maximum oxygen consumption) exercise therapy on a bicycle ergometer. Systolic blood pressure (SPB), diastolic blood pressure (DPB), and mean arterial pressure (MAP) were significantly decreased by exercise therapy in subjects with the ACE-II and ID genotypes but not in DD subjects. The time-by-genotype interaction effects were significant for DBP and MAP. According to a multiple logistic regression analysis, the age- and baseline plasma renin activity-adjusted relative risk (odds ratio) for the lack of a depressor response conferred by the D allele (assuming an additive effect) was 2.72 [95% confidence interval (CI), 1.07-6.91; p = 0.034]; for DD genotypes, as compared with the DI and II genotypes (assuming that the D allele is recessive), it was 11.7 (95% CI, 2.25-60.6; p = 0.003). ACE gene I/D polymorphism is associated with the depressor response of essential hypertensives to mild exercise therapy, which suggests that genetic features may underlie, at least in part, the heterogeneity of the depressor response in essential hypertensives to mild exercise therapy.

Predicting Culex pipiens/restuans population dynamics by interval lagged weather data

PubMed Central

2013-01-01

Background Culex pipiens/restuans mosquitoes are important vectors for a variety of arthropod borne viral infections. In this study, the associations between 20 years of mosquito capture data and the time lagged environmental quantities daytime length, temperature, precipitation, relative humidity and wind speed were used to generate a predictive model for the population dynamics of this vector species. Methods Mosquito population in the study area was represented by averaged time series of mosquitos counts captured at 6 sites in Cook County (Illinois, USA). Cross-correlation maps (CCMs) were compiled to investigate the association between mosquito abundances and environmental quantities. The results obtained from the CCMs were incorporated into a Poisson regression to generate a predictive model. To optimize the predictive model the time lags obtained from the CCMs were adjusted using a genetic algorithm. Results CCMs for weekly data showed a highly positive correlation of mosquito abundances with daytime length 4 to 5 weeks prior to capture (quantified by a Spearman rank order correlation of rS = 0.898) and with temperature during 2 weeks prior to capture (rS = 0.870). Maximal negative correlations were found for wind speed averaged over 3 week prior to capture (rS = −0.621). Cx. pipiens/restuans population dynamics was predicted by integrating the CCM results in Poisson regression models. They were used to simulate the average seasonal cycle of the mosquito abundance. Verification with observations resulted in a correlation of rS = 0.899 for daily and rS = 0.917 for weekly data. Applying the optimized models to the entire 20-years time series also resulted in a suitable fit with rS = 0.876 for daily and rS = 0.899 for weekly data. Conclusions The study demonstrates the application of interval lagged weather data to predict mosquito abundances with a feasible accuracy, especially when related to weekly Cx. pipiens/restuans populations. PMID:23634763

A YAC contig spanning the dominant retinitis pigmentosa locus (RP9) on chromosome 7p

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keen, T.J.; Inglehearn, C.F.; Patel, R.J.

1995-08-10

The dominant retinitis pigmentosa locus RP9 has previously been localized to 7p13-p15, in the interval D7S526-D7S484. We now report refinement of the locus to the interval D7S795-D7S484 and YAC contig of approximately 4.8 Mb spanning this region and extending both distally and proximally from it. The contig was constructed by STS content mapping and physically orders 29 STSs in 28 YAC clones. The order of polymorphic markers in the contig is consistent with a genetic map that has been assembled using haplotype data from the CEPH pedigrees. This contig will provide a primary resource for the construction of a transcriptionalmore » map of this region and for the identification of the defective gene causing this form of adRP. 27 refs., 3 figs., 1 tab.« less

Linkage Disequilibrium Mapping in Domestic Dog Breeds Narrows the Progressive Rod-Cone Degeneration (prcd) Interval and Identifies Ancestral Disease Transmitting Chromosome

PubMed Central

Goldstein, Orly; Zangerl, Barbara; Pearce-Kelling, Sue; Sidjanin, Duska J.; Kijas, James W.; Felix, Jeanette; Acland, Gregory M; Aguirre, Gustavo D.

2014-01-01

Canine progressive rod-cone degeneration (prcd) is a retinal disease previously mapped to a broad, gene-rich centromeric region of canine chromosome 9. As allelic disorders are present in multiple breeds, we used linkage disequilibrium (LD) to narrow the ∼6.4 Mb interval candidate region. Multiple dog breeds, each representing genetically isolated populations, were typed for SNPs and other polymorphisms identified from BACs. The candidate region was initially localized to a 1.5 Mb zero recombination interval between growth factor receptor-bound protein 2 (GRB2) and SEC14-like 1 (SEC14L). A fine-scale haplotype of the region was developed which reduced the LD interval to 106 Kb, and identified a conserved haplotype of 98 polymorphisms present in all prcd-affected chromosomes from 14 different dog breeds. The findings strongly suggest that a common ancestor transmitted the prcd disease allele to many of the modern dog breeds, and demonstrate the power of LD approach in the canine model. PMID:16859891

Prediction of hearing outcomes by multiple regression analysis in patients with idiopathic sudden sensorineural hearing loss.

PubMed

Suzuki, Hideaki; Tabata, Takahisa; Koizumi, Hiroki; Hohchi, Nobusuke; Takeuchi, Shoko; Kitamura, Takuro; Fujino, Yoshihisa; Ohbuchi, Toyoaki

2014-12-01

This study aimed to create a multiple regression model for predicting hearing outcomes of idiopathic sudden sensorineural hearing loss (ISSNHL). The participants were 205 consecutive patients (205 ears) with ISSNHL (hearing level ≥ 40 dB, interval between onset and treatment ≤ 30 days). They received systemic steroid administration combined with intratympanic steroid injection. Data were examined by simple and multiple regression analyses. Three hearing indices (percentage hearing improvement, hearing gain, and posttreatment hearing level [HLpost]) and 7 prognostic factors (age, days from onset to treatment, initial hearing level, initial hearing level at low frequencies, initial hearing level at high frequencies, presence of vertigo, and contralateral hearing level) were included in the multiple regression analysis as dependent and explanatory variables, respectively. In the simple regression analysis, the percentage hearing improvement, hearing gain, and HLpost showed significant correlation with 2, 5, and 6 of the 7 prognostic factors, respectively. The multiple correlation coefficients were 0.396, 0.503, and 0.714 for the percentage hearing improvement, hearing gain, and HLpost, respectively. Predicted values of HLpost calculated by the multiple regression equation were reliable with 70% probability with a 40-dB-width prediction interval. Prediction of HLpost by the multiple regression model may be useful to estimate the hearing prognosis of ISSNHL. © The Author(s) 2014.

Semiparametric regression analysis of interval-censored competing risks data.

PubMed

Mao, Lu; Lin, Dan-Yu; Zeng, Donglin

2017-09-01

Interval-censored competing risks data arise when each study subject may experience an event or failure from one of several causes and the failure time is not observed directly but rather is known to lie in an interval between two examinations. We formulate the effects of possibly time-varying (external) covariates on the cumulative incidence or sub-distribution function of competing risks (i.e., the marginal probability of failure from a specific cause) through a broad class of semiparametric regression models that captures both proportional and non-proportional hazards structures for the sub-distribution. We allow each subject to have an arbitrary number of examinations and accommodate missing information on the cause of failure. We consider nonparametric maximum likelihood estimation and devise a fast and stable EM-type algorithm for its computation. We then establish the consistency, asymptotic normality, and semiparametric efficiency of the resulting estimators for the regression parameters by appealing to modern empirical process theory. In addition, we show through extensive simulation studies that the proposed methods perform well in realistic situations. Finally, we provide an application to a study on HIV-1 infection with different viral subtypes. © 2017, The International Biometric Society.

The Montana experience

NASA Technical Reports Server (NTRS)

Dundas, T. R.

1981-01-01

The development and capabilities of the Montana geodata system are discussed. The system is entirely dependent on the state's central data processing facility which serves all agencies and is therefore restricted to batch mode processing. The computer graphics equipment is briefly described along with its application to state lands and township mapping and the production of water quality interval maps.

Flood characteristics of streams in Owyhee County, Idaho

USGS Publications Warehouse

Riggs, H.C.; Harenberg, W.A.

1976-01-01

Channel-width measurements were used to estimate annual peaks with a recurrence interval of 10 years at 79 sites in Owyhee County, Idaho, and adjacent areas. These discharges and those from 33 gaging stations are plotted on a map of the area. The map will allow the user to interpolate between sites. (Woodard-USGS)

49 CFR Appendix C to Part 195 - Guidance for Implementation of an Integrity Management Program

Code of Federal Regulations, 2014 CFR

2014-10-01

... get this information from topographical maps such as U.S. Geological Survey quadrangle maps. (2... risk.)—Risk Value=3 Close interval survey: (yes/no)—no—Risk Value =5 Internal Inspection tool used..., including a summary of performance improvements, both qualitative and quantitative, to an operator's...

49 CFR Appendix C to Part 195 - Guidance for Implementation of an Integrity Management Program

Code of Federal Regulations, 2011 CFR

2011-10-01

... get this information from topographical maps such as U.S. Geological Survey quadrangle maps. (2... risk.)—Risk Value=3 Close interval survey: (yes/no)—no—Risk Value =5 Internal Inspection tool used..., including a summary of performance improvements, both qualitative and quantitative, to an operator's...

49 CFR Appendix C to Part 195 - Guidance for Implementation of an Integrity Management Program

Code of Federal Regulations, 2012 CFR

2012-10-01

... get this information from topographical maps such as U.S. Geological Survey quadrangle maps. (2... risk.)—Risk Value=3 Close interval survey: (yes/no)—no—Risk Value =5 Internal Inspection tool used..., including a summary of performance improvements, both qualitative and quantitative, to an operator's...

49 CFR Appendix C to Part 195 - Guidance for Implementation of an Integrity Management Program

Code of Federal Regulations, 2013 CFR

2013-10-01

... get this information from topographical maps such as U.S. Geological Survey quadrangle maps. (2... risk.)—Risk Value=3 Close interval survey: (yes/no)—no—Risk Value =5 Internal Inspection tool used..., including a summary of performance improvements, both qualitative and quantitative, to an operator's...

An integrated genetic and physical map of the autosomal recessive polycystic kidney disease region

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lens, X.M.; Onuchic, L.F.; Daoust, M.

1997-05-01

Autosomal recessive polycystic kidney disease is one of the most common hereditary renal cystic diseases in children. Genetic studies have recently assigned the only known locus for this disorder, PKHD1, to chromosome 6p21-p12. We have generated a YAC contig that spans {approximately}5 cM of this region, defined by the markers D6S1253-D6S295, and have mapped 43 sequence-tagged sites (STS) within this interval. This set includes 20 novel STSs, which define 12 unique positions in the region, and three ESTs. A minimal set of two YACs spans the segment D6S465-D6S466, which contains PKHD1, and estimates of their sizes based on information inmore » public databases suggest that the size of the critical region is <3.1 Mb. Twenty-eight STSs map to this interval, giving an average STS density of <1/150 kb. These resources will be useful for establishing a complete trancription map of the PKHD1 region. 10 refs., 1 fig., 1 tab.« less

Complex oolite reservoirs in Ste. Genevieve limestone (Mississippian) at Folsomville field, Warrick County, Indiana

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zuppann, C.W.

1989-09-01

Correlation of productive zones at the Folsomville field is difficult because lithology in the upper part of the Ste. Genevieve Limestone, which contains oolite bodies, is both laterally and vertically variable. The problem is further complicated by significant thickness variations of this interval that result in juxtaposed positions of porosity zones when geophysical logs are correlated side by side. Subsurface slice mapping, now an infrequently used method of subsurface analysis, can resolve complex geometries of oolite bodies and account for seemingly incongruous patterns of hydrocarbon production. Any mappable parameter can be envisioned in three dimensions by using the slice-map method.more » Net porosity and lithofacies slice maps, constructed at 2-ft intervals beneath a persistent stratigraphic marker near the top of the Ste. Genevieve Limestone, describe the stratigraphic geometries of oolite reservoirs at the Folsomville field. Integrating fluid content and well-production histories with the slice maps allows patterns of hydrocarbon production to be deciphered, a procedure that should provide a valuable guide in designing the most effect enhanced recovery program for the field.« less

Contour maps of lunar remanent magnetic fields

NASA Technical Reports Server (NTRS)

Hood, L. L.; Russell, C. T.; Coleman, P. J., Jr.

1981-01-01

The 2605 usable orbits of Apollo 15 and 16 subsatellite magnetometer data have been reexamined for intervals suitable for analysis of crustal magnetic anomalies. To minimize plasma-related disturbances, segments from 274 of these orbits were selected from times when the moon was either in a lobe of the geomagnetic tail or in the solar wind with the subsatellites in the lunar wake. External field contributions which remained in the selected intervals were minimized by (1) quadratic detrending of individual orbit segments with lengths much greater than anomaly wavelengths and (2) two-dimensional filtering with minimum passed wavelengths less than or equal to anomaly wavelengths. Improvements in coverage, accuracy, and resolution of previously published anomaly maps produced from these data are obtained. In addition to improved maps of the Reiner Gamma and Van de Graaff-Aitken anomalies studied previously, a third region of relatively high-amplitude anomalies centered near the crater Gerasimovich on the southeastern far side has been mapped. Both the Van de Graaff-Aitken region and the Gerasimovich region are marked by the general occurrence of extensive groups of Reiner Gamma-type swirls.

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, genetic homogeneity, and mapping of the locus within a 2-cM interval

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ducros, A.; Alamowitch, S.; Nagy, T.

1996-01-01

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is a recently identified autosomal dominant cerebral arteriopathy characterized by the recurrence of subcortical infarcts leading to dementia. A genetic linkage analysis conducted in two large families recently allowed us to map the affected gene on chromosome 19 in a 12-cM interval bracketed by D19S221 and D19S215. In the present study, these first 2 families and 13 additional ones, including a total of 199 potentially informative meiosis, have been genotyped with eight polymorphic markers located between D19S221 and D19S215. All families were linked to chromosome 19. The highest combined lodmore » score (Z{sub max} = 37.24 at {theta} = .01) was obtained with marker D19S841, a new CA{sub n} microsatellite marker that we isolated from chromosome 19 cosmids. The recombinant events observed within these families were used to refine the genetic mapping of CADASIL within a 2-cM interval that is now bracketed by D19S226 and D19S199 on 19p13.1. These data strongly suggest the genetic homogeneity of this recently identified condition and establish the value of its clinical and neuroimaging diagnostic criteria. Besides their importance for the ongoing positional cloning of the CADASIL gene, these data help to refine the genetic mapping of CADASIL relative to familial hemiplegic migraine and hereditary paroxysmal cerebellar ataxia, conditions that we both mapped within the same chromosome 19 region. 35 refs., 5 figs., 2 tabs.« less

Fine mapping and candidate gene analysis of qFL-chr1, a fiber length QTL in cotton.

PubMed

Xu, Peng; Gao, Jin; Cao, Zhibin; Chee, Peng W; Guo, Qi; Xu, Zhenzhen; Paterson, Andrew H; Zhang, Xianggui; Shen, Xinlian

2017-06-01

A fiber length QTL, qFL-chr1, was fine mapped to a 0.9 cM interval of cotton chromosome 1. Two positional candidate genes showed positive correlation between gene expression level and fiber length. Prior analysis of a backcross-self mapping population derived from a cross between Gossypium hirsutum L. and G. barbadense L. revealed a QTL on chromosome 1 associated with increased fiber length (qFL-chr1), which was confirmed in three independent populations of near-isogenic introgression lines (NIILs). Here, a single NIIL, R01-40-08, was used to develop a large population segregating for the target region. Twenty-two PCR-based polymorphic markers used to genotype 1672 BC 4 F 2 plants identified 432 recombinants containing breakpoints in the target region. Substitution mapping using 141 informative recombinants narrowed the position of qFL-chr1 to a 1.0-cM interval between SSR markers MUSS084 and CIR018. To exclude possible effects of non-target introgressions on fiber length, different heterozygous BC 4 F 3 plants introgressed between SSR markers NAU3384 and CGR5144 were selected to develop sub-NILs. The qFL-chr1 was further mapped at 0.9-cM interval between MUSS422 and CIR018 by comparisons of sub-NIL phenotype, and increased fiber length by ~1 mm. The 2.38-Mb region between MUSS422 and CIR018 in G. barbadense contained 19 annotated genes. Expression levels of two of these genes, GOBAR07705 (encoding 1-aminocyclopropane-1-carboxylate synthase) and GOBAR25992 (encoding amino acid permease), were positively correlated with fiber length in a small F 2 population, supporting these genes as candidates for qFL-chr1.

Landslide Hazard Mapping in Rwanda Using Logistic Regression

NASA Astrophysics Data System (ADS)

Piller, A.; Anderson, E.; Ballard, H.

2015-12-01

Landslides in the United States cause more than $1 billion in damages and 50 deaths per year (USGS 2014). Globally, figures are much more grave, yet monitoring, mapping and forecasting of these hazards are less than adequate. Seventy-five percent of the population of Rwanda earns a living from farming, mostly subsistence. Loss of farmland, housing, or life, to landslides is a very real hazard. Landslides in Rwanda have an impact at the economic, social, and environmental level. In a developing nation that faces challenges in tracking, cataloging, and predicting the numerous landslides that occur each year, satellite imagery and spatial analysis allow for remote study. We have focused on the development of a landslide inventory and a statistical methodology for assessing landslide hazards. Using logistic regression on approximately 30 test variables (i.e. slope, soil type, land cover, etc.) and a sample of over 200 landslides, we determine which variables are statistically most relevant to landslide occurrence in Rwanda. A preliminary predictive hazard map for Rwanda has been produced, using the variables selected from the logistic regression analysis.

GIS-based rare events logistic regression for mineral prospectivity mapping

NASA Astrophysics Data System (ADS)

Xiong, Yihui; Zuo, Renguang

2018-02-01

Mineralization is a special type of singularity event, and can be considered as a rare event, because within a specific study area the number of prospective locations (1s) are considerably fewer than the number of non-prospective locations (0s). In this study, GIS-based rare events logistic regression (RELR) was used to map the mineral prospectivity in the southwestern Fujian Province, China. An odds ratio was used to measure the relative importance of the evidence variables with respect to mineralization. The results suggest that formations, granites, and skarn alterations, followed by faults and aeromagnetic anomaly are the most important indicators for the formation of Fe-related mineralization in the study area. The prediction rate and the area under the curve (AUC) values show that areas with higher probability have a strong spatial relationship with the known mineral deposits. Comparing the results with original logistic regression (OLR) demonstrates that the GIS-based RELR performs better than OLR. The prospectivity map obtained in this study benefits the search for skarn Fe-related mineralization in the study area.

Determinants of physical activity in America: a first characterization of physical activity profile using the National Health and Nutrition Examination Survey (NHANES).

PubMed

Kao, Ming-Chih Jeffrey; Jarosz, Renata; Goldin, Michael; Patel, Amy; Smuck, Matthew

2014-10-01

To develop and implement methodologies for characterizing accelerometry-derived patterns of physical activity (PA) in the United States in relation to demographics, anthropometrics, behaviors, and comorbidities using the National Health and Nutrition Examination Survey (NHANES) dataset. Retrospective analysis of nationally representative database. Computer-generated modeling in silico. A total of 6329 adults in the United States from the NHANES 2003-2004 database. To discover subtle multivariate signal in the dynamic and noisy accelerometry data, we developed a novel approach, termed discretized multiple adaptive regression and implemented the algorithm in SAS 9.2 (SAS Institute, Cary, NC). Demographic, anthropometric, comorbidity, and behavioral variables. The intensity of PA decreased with both increased age and increased body mass index. Both greater education and greater income correlate with increased activity over short durations and reduced activity intensity over long durations. Numerous predictors demonstrated effects within activity ranges that may be masked by use of the standard activity intensity intervals. These include age, one of the most robust variables, where we discovered decreasing activities inside the moderate activity range. It also includes gender, where women compared with men have increased proportions of active times up to the center of light activity range, and income greater than $45,000, where a complex effect is seen with little correspondence to existing cut-points. The results presented in this study suggest that the method of multiple regression and heat map visualization can generate insights otherwise hidden in large datasets such as NHANES. A review of the provided heat maps reveals the trends discussed previously involving demographic, anthropometric, comorbidity, and behavioral variables. It also demonstrates the power of accelerometry to expose alterations in PA. Ultimately, this study provides a US population-based norm to use in future studies of PA. Copyright © 2014 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

Machado Joseph disease maps to the same region of chromosome 14 as the spinocerebellar ataxia type 3 locus.

PubMed Central

Twist, E C; Casaubon, L K; Ruttledge, M H; Rao, V S; Macleod, P M; Radvany, J; Zhao, Z; Rosenberg, R N; Farrer, L A; Rouleau, G A

1995-01-01

Machado Joseph disease (MJD) is an autosomal dominantly inherited neuro-degenerative disorder primarily affecting the motor system. It can be divided into three phenotypes based on the variable combination of a range of clinical symptoms including pyramidal and extra-pyramidal features, cerebellar deficits, and distal muscle atrophy. MJD is thought to be caused by mutation of a single gene which has recently been mapped, using genetic linkage analysis, to a 29 cM region on chromosome 14q24.3-q32 in five Japanese families. A second disorder, spinocerebellar ataxia type 3 (SCA3), which has clinical symptoms similar to MJD, has also been linked to the same region of chromosome 14q in two French families. In order to narrow down the region of chromosome 14 which contains the MJD locus and to determine if this region overlaps with the predisposing locus for SCA3, we have performed genetic linkage analysis in seven MJD families, six of Portuguese/Azorean origin and one of Brazilian origin, using nine microsatellite markers mapped to 14q24.3-q32. Our results localise the MJD locus in these families to an 11 cM interval flanked by the markers D14S68 and AFM343vf1. In addition we show that this 11 cM interval maps within the 15 cM interval containing the SCA3 locus, suggesting that these diseases are allelic. PMID:7897622

Geospatial Predictive Modelling for Climate Mapping of Selected Severe Weather Phenomena Over Poland: A Methodological Approach

NASA Astrophysics Data System (ADS)

Walawender, Ewelina; Walawender, Jakub P.; Ustrnul, Zbigniew

2017-02-01

The main purpose of the study is to introduce methods for mapping the spatial distribution of the occurrence of selected atmospheric phenomena (thunderstorms, fog, glaze and rime) over Poland from 1966 to 2010 (45 years). Limited in situ observations as well the discontinuous and location-dependent nature of these phenomena make traditional interpolation inappropriate. Spatially continuous maps were created with the use of geospatial predictive modelling techniques. For each given phenomenon, an algorithm identifying its favourable meteorological and environmental conditions was created on the basis of observations recorded at 61 weather stations in Poland. Annual frequency maps presenting the probability of a day with a thunderstorm, fog, glaze or rime were created with the use of a modelled, gridded dataset by implementing predefined algorithms. Relevant explanatory variables were derived from NCEP/NCAR reanalysis and downscaled with the use of a Regional Climate Model. The resulting maps of favourable meteorological conditions were found to be valuable and representative on the country scale but at different correlation ( r) strength against in situ data (from r = 0.84 for thunderstorms to r = 0.15 for fog). A weak correlation between gridded estimates of fog occurrence and observations data indicated the very local nature of this phenomenon. For this reason, additional environmental predictors of fog occurrence were also examined. Topographic parameters derived from the SRTM elevation model and reclassified CORINE Land Cover data were used as the external, explanatory variables for the multiple linear regression kriging used to obtain the final map. The regression model explained 89 % of annual frequency of fog variability in the study area. Regression residuals were interpolated via simple kriging.

Landslide susceptibility mapping for a part of North Anatolian Fault Zone (Northeast Turkey) using logistic regression model

NASA Astrophysics Data System (ADS)

Demir, Gökhan; aytekin, mustafa; banu ikizler, sabriye; angın, zekai

2013-04-01

The North Anatolian Fault is know as one of the most active and destructive fault zone which produced many earthquakes with high magnitudes. Along this fault zone, the morphology and the lithological features are prone to landsliding. However, many earthquake induced landslides were recorded by several studies along this fault zone, and these landslides caused both injuiries and live losts. Therefore, a detailed landslide susceptibility assessment for this area is indispancable. In this context, a landslide susceptibility assessment for the 1445 km2 area in the Kelkit River valley a part of North Anatolian Fault zone (Eastern Black Sea region of Turkey) was intended with this study, and the results of this study are summarized here. For this purpose, geographical information system (GIS) and a bivariate statistical model were used. Initially, Landslide inventory maps are prepared by using landslide data determined by field surveys and landslide data taken from General Directorate of Mineral Research and Exploration. The landslide conditioning factors are considered to be lithology, slope gradient, slope aspect, topographical elevation, distance to streams, distance to roads and distance to faults, drainage density and fault density. ArcGIS package was used to manipulate and analyze all the collected data Logistic regression method was applied to create a landslide susceptibility map. Landslide susceptibility maps were divided into five susceptibility regions such as very low, low, moderate, high and very high. The result of the analysis was verified using the inventoried landslide locations and compared with the produced probability model. For this purpose, Area Under Curvature (AUC) approach was applied, and a AUC value was obtained. Based on this AUC value, the obtained landslide susceptibility map was concluded as satisfactory. Keywords: North Anatolian Fault Zone, Landslide susceptibility map, Geographical Information Systems, Logistic Regression Analysis.

Confidence Intervals for Assessing Heterogeneity in Generalized Linear Mixed Models

ERIC Educational Resources Information Center

Wagler, Amy E.

2014-01-01

Generalized linear mixed models are frequently applied to data with clustered categorical outcomes. The effect of clustering on the response is often difficult to practically assess partly because it is reported on a scale on which comparisons with regression parameters are difficult to make. This article proposes confidence intervals for…

Cigarette smoke chemistry market maps under Massachusetts Department of Public Health smoking conditions.

PubMed

Morton, Michael J; Laffoon, Susan W

2008-06-01

This study extends the market mapping concept introduced by Counts et al. (Counts, M.E., Hsu, F.S., Tewes, F.J., 2006. Development of a commercial cigarette "market map" comparison methodology for evaluating new or non-conventional cigarettes. Regul. Toxicol. Pharmacol. 46, 225-242) to include both temporal cigarette and testing variation and also machine smoking with more intense puffing parameters, as defined by the Massachusetts Department of Public Health (MDPH). The study was conducted over a two year period and involved a total of 23 different commercial cigarette brands from the U.S. marketplace. Market mapping prediction intervals were developed for 40 mainstream cigarette smoke constituents and the potential utility of the market map as a comparison tool for new brands was demonstrated. The over-time character of the data allowed for the variance structure of the smoke constituents to be more completely characterized than is possible with one-time sample data. The variance was partitioned among brand-to-brand differences, temporal differences, and the remaining residual variation using a mixed random and fixed effects model. It was shown that a conventional weighted least squares model typically gave similar prediction intervals to those of the more complicated mixed model. For most constituents there was less difference in the prediction intervals calculated from over-time samples and those calculated from one-time samples than had been anticipated. One-time sample maps may be adequate for many purposes if the user is aware of their limitations. Cigarette tobacco fillers were analyzed for nitrate, nicotine, tobacco-specific nitrosamines, ammonia, chlorogenic acid, and reducing sugars. The filler information was used to improve predicting relationships for several of the smoke constituents, and it was concluded that the effects of filler chemistry on smoke chemistry were partial explanations of the observed brand-to-brand variation.

Mapping epibenthic assemblages and their relations to sedimentary features in shallow-water, high-energy environments

NASA Astrophysics Data System (ADS)

Sisson, John D.; Shimeta, Jeff; Zimmer, Cheryl Ann; Traykovski, Peter

2002-03-01

Knowledge of spatial relationships among benthic biota and sedimentary features in shallow-water (<30 m) high-energy environments has been severely limited by sampling technology. We describe and report tests of a SCUBA-diving mapping method specifically for this region. Underwater acoustic location is used to achieve meter-scale resolution over kilometer-scale regions of the sea floor. A triad of acoustic transponders is bottom-mounted at known positions, 300-500 m apart. Transported by underwater personal vehicles, SCUBA-divers map the bed using hand-held acoustic receivers that record ranges to the transponders. The mean error of acoustic fixes was 2.4±1.2 m in a 0.5 km×1.0 km test area. Dense assemblages of epibenthic animals were mapped relative to sediment texture and bedforms off the exposed south coast of Martha's Vineyard Island, Massachusetts, USA. Surveys one month apart within a 0.6 km×0.6 km area (8-12 m depth) revealed 100-m-scale patches of the tube worm Spiophanes bombyx (⩽30,000 m -2) in fine sand and of the sand dollar Echinarachnius parma (⩽55 m -2) in coarse sand. Raised mud patches that, together with fine sand, occurred in two shore-perpendicular belts are likely exposed, ancient marsh deposits. Depth gradients of sand-ripple geometry indicated that ripples in deeper areas were not in equilibrium with wave conditions monitored during surveys; i.e., they were relict ripples. Thus, sand dollars in some areas may have had >1 month to rework surficial sands since their transformation by physical processes. Linear regressions of ripple characteristics against sand dollar or tube worm densities were not significant, although such relationships would be highly dependent on temporal scale. The survey method described here can be used at more frequent intervals to explore such interactions between epibenthic animals and sediment-transport dynamics.

Estimating Forest Canopy Heights and Aboveground Biomass with Simulated ICESat-2 Data

NASA Astrophysics Data System (ADS)

Malambo, L.; Narine, L.; Popescu, S. C.; Neuenschwander, A. L.; Sheridan, R.

2016-12-01

The Ice, Cloud and Land Elevation Satellite (ICESat) 2 is scheduled for launch in 2017 and one of its overall science objectives will be to measure vegetation heights, which can be used to estimate and monitor aboveground biomass (AGB) over large spatial scales. This study serves to develop a methodology for utilizing vegetation data collected by ICESat-2 that will be on a five-year mission from 2017, for mapping forest canopy heights and estimating aboveground forest biomass (AGB). The specific objectives are to, (1) simulate ICESat-2 photon-counting lidar (PCL) data, (2) utilize simulated PCL data to estimate forest canopy heights and propose a methodology for upscaling PCL height measurements to obtain spatially contiguous coverage and, (3) estimate and map AGB using simulated PCL data. The laser pulse from ICESat-2 will be divided into three pairs of beams spaced approximately 3 km apart, with footprints measuring approximately 14 m in diameter and with 70 cm along-track intervals. Using existing airborne lidar data (ALS) for Sam Houston National Forest (SHNF) and known ICESat-2 beam locations, footprints are generated along beam locations and PCL data are then simulated from discrete return lidar points within each footprint. By applying data processing algorithms, photons are classified into top of canopy points and ground surface elevation points to yield tree canopy height values within each ICESat-2 footprint. AGB is then estimated using simple linear regression that utilizes AGB from a biomass map generated with ALS data for SHNF and simulated PCL height metrics for 100 m segments along ICESat-2 tracks. Two approaches also investigated for upscaling AGB estimates to provide wall-to-wall coverage of AGB are (1) co-kriging and (2) Random Forest. Height and AGB maps, which are the outcomes of this study, will demonstrate how data acquired by ICESat-2 can be used to measure forest parameters and in extension, estimate forest carbon for climate change initiatives.

Evaluation of indirect blood pressure monitoring in awake and anesthetized red-tailed hawks (Buteo jamaicensis): effects of cuff size, cuff placement, and monitoring equipment.

PubMed

Zehnder, Ashley M; Hawkins, Michelle G; Pascoe, Peter J; Kass, Philip H

2009-09-01

To compare Doppler and oscillometric methods of indirect arterial blood pressure (IBP) with direct arterial measurements in anesthetized and awake red-tailed hawks. Prospective, randomized, blinded study. Six, sex unknown, adult red-tailed hawks. Birds were anesthetized and IBP measurements were obtained by oscillometry (IBP-O) and Doppler (IBP-D) on the pectoral and pelvic limbs using three cuffs of different width based on limb circumference: cuff 1 (20-30% of circumference), cuff 2 (30-40%), and cuff 3 (40-50%). Direct arterial pressure measurements were obtained from the contralateral superficial ulnar artery. Indirect blood pressure measurements were compared to direct systolic arterial pressure (SAP) and mean arterial pressure (MAP) during normotension and induced states of hypotension and hypertension. Measurements were also obtained in awake, restrained birds. Three-way anova, linear regression and Bland-Altman analyses were used to evaluate the IBP-D data. Results are reported as mean bias (95% confidence intervals). The IBP-O monitor reported errors during 54% of the measurements. Indirect blood pressure Doppler measurements were most accurate with cuff 3 and were comparable to MAP with a bias of 2 (-9, 13 mmHg). However, this cuff consistently underestimated SAP with a bias of 33 (19, 48 mmHg). Variability in the readings within and among birds was high. There was no significant difference between sites of cuff placement. Awake birds had SAP, MAP and diastolic arterial pressure that were 56, 43, and 38 mmHg higher than anesthetized birds. Indirect blood pressure (oscillometric) measurements were unreliable in red-tailed hawks. Indirect blood pressure (Doppler) measurements were closer to MAP measurements than SAP measurements. There was slightly better agreement with the use of cuff 3 on either the pectoral or pelvic limbs. Awake, restrained birds have significantly higher arterial pressures than those under sevoflurane anesthesia.

Fire risk in California

NASA Astrophysics Data System (ADS)

Peterson, Seth Howard

Fire is an integral part of ecosystems in the western United States. Decades of fire suppression have led to (unnaturally) large accumulations of fuel in some forest communities, such as the lower elevation forests of the Sierra Nevada. Urban sprawl into fire prone chaparral vegetation in southern California has put human lives at risk and the decreased fire return intervals have put the vegetation community at risk of type conversion. This research examines the factors affecting fire risk in two of the dominant landscapes in the state of California, chaparral and inland coniferous forests. Live fuel moisture (LFM) is important for fire ignition, spread rate, and intensity in chaparral. LFM maps were generated for Los Angeles County by developing and then inverting robust cross-validated regression equations from time series field data and vegetation indices (VIs) and phenological metrics from MODIS data. Fire fuels, including understory fuels which are not visible to remote sensing instruments, were mapped in Yosemite National Park using the random forests decision tree algorithm and climatic, topographic, remotely sensed, and fire history variables. Combining the disparate data sources served to improve classification accuracies. The models were inverted to produce maps of fuel models and fuel amounts, and these showed that fire fuel amounts are highest in the low elevation forests that have been most affected by fire suppression impacting the natural fire regime. Wildland fires in chaparral commonly burn in late summer or fall when LFM is near its annual low, however, the Jesusita Fire burned in early May of 2009, when LFM was still relatively high. The HFire fire spread model was used to simulate the growth of the Jesusita Fire using LFM maps derived from imagery acquired at the time of the fire and imagery acquired in late August to determine how much different the fire would have been if it had occurred later in the year. Simulated fires were 1.5 times larger, and the fire reached the wildland urban interface three hours earlier, when using August LFM.

Stroke Location Is an Independent Predictor of Cognitive Outcome.

PubMed

Munsch, Fanny; Sagnier, Sharmila; Asselineau, Julien; Bigourdan, Antoine; Guttmann, Charles R; Debruxelles, Sabrina; Poli, Mathilde; Renou, Pauline; Perez, Paul; Dousset, Vincent; Sibon, Igor; Tourdias, Thomas

2016-01-01

On top of functional outcome, accurate prediction of cognitive outcome for stroke patients is an unmet need with major implications for clinical management. We investigated whether stroke location may contribute independent prognostic value to multifactorial predictive models of functional and cognitive outcomes. Four hundred twenty-eight consecutive patients with ischemic stroke were prospectively assessed with magnetic resonance imaging at 24 to 72 hours and at 3 months for functional outcome using the modified Rankin Scale and cognitive outcome using the Montreal Cognitive Assessment (MoCA). Statistical maps of functional and cognitive eloquent regions were derived from the first 215 patients (development sample) using voxel-based lesion-symptom mapping. We used multivariate logistic regression models to study the influence of stroke location (number of eloquent voxels from voxel-based lesion-symptom mapping maps), age, initial National Institutes of Health Stroke Scale and stroke volume on modified Rankin Scale and MoCA. The second part of our cohort was used as an independent replication sample. In univariate analyses, stroke location, age, initial National Institutes of Health Stroke Scale, and stroke volume were all predictive of poor modified Rankin Scale and MoCA. In multivariable analyses, stroke location remained the strongest independent predictor of MoCA and significantly improved the prediction compared with using only age, initial National Institutes of Health Stroke Scale, and stroke volume (area under the curve increased from 0.697-0.771; difference=0.073; 95% confidence interval, 0.008-0.155). In contrast, stroke location did not persist as independent predictor of modified Rankin Scale that was mainly driven by initial National Institutes of Health Stroke Scale (area under the curve going from 0.840 to 0.835). Similar results were obtained in the replication sample. Stroke location is an independent predictor of cognitive outcome (MoCA) at 3 months post stroke. © 2015 American Heart Association, Inc.

Identification of stable QTLs for seed oil content by combined linkage and association mapping in Brassica napus.

PubMed

Sun, Fengming; Liu, Jing; Hua, Wei; Sun, Xingchao; Wang, Xinfa; Wang, Hanzhong

2016-11-01

Seed oil content is an important agricultural trait in rapeseed breeding. Although numerous quantitative trait locus (QTL) have been identified, most of them cannot be applied in practical breeding mainly due to environmental instability or large confidence intervals. The purpose of this study was to identify and validate high quality and more stable QTLs by combining linkage mapping and genome-wide association study (GWAS). For linkage mapping, we constructed two F 2 populations from crosses of high-oil content (∼50%) lines 6F313 and 61616 with a low-oil content (∼40%) line 51070. Two high density linkage maps spanned 1987cM (1659 bins) and 1856cM (1746 bins), respectively. For GWAS, we developed more than 34,000 high-quality SNP markers based on 227 accessions. Finally, 40 QTLs and 29 associations were established by linkage and association mapping in different environments. After merging the results, 32 consensus QTLs were obtained and 7 of them were identified by both mapping methods. Seven overlapping QTLs covered an average confidence interval of 183kb and explained the phenotypic variation of 10.23 to 24.45%. We further developed allele-specific PCR primers to identify each of the seven QTLs. These stable QTLs should be useful in gene cloning and practical breeding application. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Fine genetic mapping of spot blotch resistance gene Sb3 in wheat (Triticum aestivum).

PubMed

Lu, Ping; Liang, Yong; Li, Delin; Wang, Zhengzhong; Li, Wenbin; Wang, Guoxin; Wang, Yong; Zhou, Shenghui; Wu, Qiuhong; Xie, Jingzhong; Zhang, Deyun; Chen, Yongxing; Li, Miaomiao; Zhang, Yan; Sun, Qixin; Han, Chenggui; Liu, Zhiyong

2016-03-01

Spot blotch disease resistance gene Sb3 was mapped to a 0.15 centimorgan (cM) genetic interval spanning a 602 kb physical genomic region on chromosome 3BS. Wheat spot blotch disease, caused by B. sorokiniana, is a devastating disease that can cause severe yield losses. Although inoculum levels can be reduced by planting disease-free seed, treatment of plants with fungicides and crop rotation, genetic resistance is likely to be a robust, economical and environmentally friendly tool in the control of spot blotch. The winter wheat line 621-7-1 confers immune resistance against B. sorokiniana. Genetic analysis indicates that the spot blotch resistance of 621-7-1 is controlled by a single dominant gene, provisionally designated Sb3. Bulked segregant analysis (BSA) and simple sequence repeat (SSR) mapping showed that Sb3 is located on chromosome arm 3BS linked with markers Xbarc133 and Xbarc147. Seven and twelve new polymorphic markers were developed from the Chinese Spring 3BS shotgun survey sequence contigs and 3BS reference sequences, respectively. Finally, Sb3 was mapped in a 0.15 cM genetic interval spanning a 602 kb physical genomic region of Chinese Spring chromosome 3BS. The genetic and physical maps of Sb3 provide a framework for map-based cloning and marker-assisted selection (MAS) of the spot blotch resistance.

Fine-Mapping of the 1p11.2 Breast Cancer Susceptibility Locus

PubMed Central

Horne, Hisani N.; Chung, Charles C.; Zhang, Han; Yu, Kai; Prokunina-Olsson, Ludmila; Michailidou, Kyriaki; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Hopper, John L.; Southey, Melissa C.; Schmidt, Marjanka K.; Broeks, Annegien; Muir, Kenneth; Lophatananon, Artitaya; Fasching, Peter A.; Beckmann, Matthias W.; Fletcher, Olivia; Johnson, Nichola; Sawyer, Elinor J.; Tomlinson, Ian; Burwinkel, Barbara; Marme, Frederik; Guénel, Pascal; Truong, Thérèse; Bojesen, Stig E.; Flyger, Henrik; Benitez, Javier; González-Neira, Anna; Anton-Culver, Hoda; Neuhausen, Susan L.; Brenner, Hermann; Arndt, Volker; Meindl, Alfons; Schmutzler, Rita K.; Brauch, Hiltrud; Hamann, Ute; Nevanlinna, Heli; Khan, Sofia; Matsuo, Keitaro; Iwata, Hiroji; Dörk, Thilo; Bogdanova, Natalia V.; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kosma, Veli-Matti; Chenevix-Trench, Georgia; Wu, Anna H.; ven den Berg, David; Smeets, Ann; Zhao, Hui; Chang-Claude, Jenny; Rudolph, Anja; Radice, Paolo; Barile, Monica; Couch, Fergus J.; Vachon, Celine; Giles, Graham G.; Milne, Roger L.; Haiman, Christopher A.; Marchand, Loic Le; Goldberg, Mark S.; Teo, Soo H.; Taib, Nur A. M.; Kristensen, Vessela; Borresen-Dale, Anne-Lise; Zheng, Wei; Shrubsole, Martha; Winqvist, Robert; Jukkola-Vuorinen, Arja; Andrulis, Irene L.; Knight, Julia A.; Devilee, Peter; Seynaeve, Caroline; García-Closas, Montserrat; Czene, Kamila; Darabi, Hatef; Hollestelle, Antoinette; Martens, John W. M.; Li, Jingmei; Lu, Wei; Shu, Xiao-Ou; Cox, Angela; Cross, Simon S.; Blot, William; Cai, Qiuyin; Shah, Mitul; Luccarini, Craig; Baynes, Caroline; Harrington, Patricia; Kang, Daehee; Choi, Ji-Yeob; Hartman, Mikael; Chia, Kee Seng; Kabisch, Maria; Torres, Diana; Jakubowska, Anna; Lubinski, Jan; Sangrajrang, Suleeporn; Brennan, Paul; Slager, Susan; Yannoukakos, Drakoulis; Shen, Chen-Yang; Hou, Ming-Feng; Swerdlow, Anthony; Orr, Nick; Simard, Jacques; Hall, Per; Pharoah, Paul D. P.

2016-01-01

The Cancer Genetic Markers of Susceptibility genome-wide association study (GWAS) originally identified a single nucleotide polymorphism (SNP) rs11249433 at 1p11.2 associated with breast cancer risk. To fine-map this locus, we genotyped 92 SNPs in a 900kb region (120,505,799–121,481,132) flanking rs11249433 in 45,276 breast cancer cases and 48,998 controls of European, Asian and African ancestry from 50 studies in the Breast Cancer Association Consortium. Genotyping was done using iCOGS, a custom-built array. Due to the complicated nature of the region on chr1p11.2: 120,300,000–120,505,798, that lies near the centromere and contains seven duplicated genomic segments, we restricted analyses to 429 SNPs excluding the duplicated regions (42 genotyped and 387 imputed). Per-allelic associations with breast cancer risk were estimated using logistic regression models adjusting for study and ancestry-specific principal components. The strongest association observed was with the original identified index SNP rs11249433 (minor allele frequency (MAF) 0.402; per-allele odds ratio (OR) = 1.10, 95% confidence interval (CI) 1.08–1.13, P = 1.49 x 10-21). The association for rs11249433 was limited to ER-positive breast cancers (test for heterogeneity P≤8.41 x 10-5). Additional analyses by other tumor characteristics showed stronger associations with moderately/well differentiated tumors and tumors of lobular histology. Although no significant eQTL associations were observed, in silico analyses showed that rs11249433 was located in a region that is likely a weak enhancer/promoter. Fine-mapping analysis of the 1p11.2 breast cancer susceptibility locus confirms this region to be limited to risk to cancers that are ER-positive. PMID:27556229

Fine-Mapping of the 1p11.2 Breast Cancer Susceptibility Locus.

PubMed

Horne, Hisani N; Chung, Charles C; Zhang, Han; Yu, Kai; Prokunina-Olsson, Ludmila; Michailidou, Kyriaki; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Hopper, John L; Southey, Melissa C; Schmidt, Marjanka K; Broeks, Annegien; Muir, Kenneth; Lophatananon, Artitaya; Fasching, Peter A; Beckmann, Matthias W; Fletcher, Olivia; Johnson, Nichola; Sawyer, Elinor J; Tomlinson, Ian; Burwinkel, Barbara; Marme, Frederik; Guénel, Pascal; Truong, Thérèse; Bojesen, Stig E; Flyger, Henrik; Benitez, Javier; González-Neira, Anna; Anton-Culver, Hoda; Neuhausen, Susan L; Brenner, Hermann; Arndt, Volker; Meindl, Alfons; Schmutzler, Rita K; Brauch, Hiltrud; Hamann, Ute; Nevanlinna, Heli; Khan, Sofia; Matsuo, Keitaro; Iwata, Hiroji; Dörk, Thilo; Bogdanova, Natalia V; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kosma, Veli-Matti; Chenevix-Trench, Georgia; Wu, Anna H; Ven den Berg, David; Smeets, Ann; Zhao, Hui; Chang-Claude, Jenny; Rudolph, Anja; Radice, Paolo; Barile, Monica; Couch, Fergus J; Vachon, Celine; Giles, Graham G; Milne, Roger L; Haiman, Christopher A; Marchand, Loic Le; Goldberg, Mark S; Teo, Soo H; Taib, Nur A M; Kristensen, Vessela; Borresen-Dale, Anne-Lise; Zheng, Wei; Shrubsole, Martha; Winqvist, Robert; Jukkola-Vuorinen, Arja; Andrulis, Irene L; Knight, Julia A; Devilee, Peter; Seynaeve, Caroline; García-Closas, Montserrat; Czene, Kamila; Darabi, Hatef; Hollestelle, Antoinette; Martens, John W M; Li, Jingmei; Lu, Wei; Shu, Xiao-Ou; Cox, Angela; Cross, Simon S; Blot, William; Cai, Qiuyin; Shah, Mitul; Luccarini, Craig; Baynes, Caroline; Harrington, Patricia; Kang, Daehee; Choi, Ji-Yeob; Hartman, Mikael; Chia, Kee Seng; Kabisch, Maria; Torres, Diana; Jakubowska, Anna; Lubinski, Jan; Sangrajrang, Suleeporn; Brennan, Paul; Slager, Susan; Yannoukakos, Drakoulis; Shen, Chen-Yang; Hou, Ming-Feng; Swerdlow, Anthony; Orr, Nick; Simard, Jacques; Hall, Per; Pharoah, Paul D P; Easton, Douglas F; Chanock, Stephen J; Dunning, Alison M; Figueroa, Jonine D

2016-01-01

The Cancer Genetic Markers of Susceptibility genome-wide association study (GWAS) originally identified a single nucleotide polymorphism (SNP) rs11249433 at 1p11.2 associated with breast cancer risk. To fine-map this locus, we genotyped 92 SNPs in a 900kb region (120,505,799-121,481,132) flanking rs11249433 in 45,276 breast cancer cases and 48,998 controls of European, Asian and African ancestry from 50 studies in the Breast Cancer Association Consortium. Genotyping was done using iCOGS, a custom-built array. Due to the complicated nature of the region on chr1p11.2: 120,300,000-120,505,798, that lies near the centromere and contains seven duplicated genomic segments, we restricted analyses to 429 SNPs excluding the duplicated regions (42 genotyped and 387 imputed). Per-allelic associations with breast cancer risk were estimated using logistic regression models adjusting for study and ancestry-specific principal components. The strongest association observed was with the original identified index SNP rs11249433 (minor allele frequency (MAF) 0.402; per-allele odds ratio (OR) = 1.10, 95% confidence interval (CI) 1.08-1.13, P = 1.49 x 10-21). The association for rs11249433 was limited to ER-positive breast cancers (test for heterogeneity P≤8.41 x 10-5). Additional analyses by other tumor characteristics showed stronger associations with moderately/well differentiated tumors and tumors of lobular histology. Although no significant eQTL associations were observed, in silico analyses showed that rs11249433 was located in a region that is likely a weak enhancer/promoter. Fine-mapping analysis of the 1p11.2 breast cancer susceptibility locus confirms this region to be limited to risk to cancers that are ER-positive.

T1 mapping and survival in systemic light-chain amyloidosis

PubMed Central

Banypersad, Sanjay M.; Fontana, Marianna; Maestrini, Viviana; Sado, Daniel M.; Captur, Gabriella; Petrie, Aviva; Piechnik, Stefan K.; Whelan, Carol J.; Herrey, Anna S.; Gillmore, Julian D.; Lachmann, Helen J.; Wechalekar, Ashutosh D.; Hawkins, Philip N.; Moon, James C.

2015-01-01

Aims To assess the prognostic value of myocardial pre-contrast T1 and extracellular volume (ECV) in systemic amyloid light-chain (AL) amyloidosis using cardiovascular magnetic resonance (CMR) T1 mapping. Methods and results One hundred patients underwent CMR and T1 mapping pre- and post-contrast. Myocardial ECV was calculated at contrast equilibrium (ECVi) and 15 min post-bolus (ECVb). Fifty-four healthy volunteers served as controls. Patients were followed up for a median duration of 23 months and survival analyses were performed. Mean ECVi was raised in amyloid (0.44 ± 0.12) as was ECVb (mean 0.44 ± 0.12) compared with healthy volunteers (0.25 ± 0.02), P < 0.001. Native pre-contrast T1 was raised in amyloid (mean 1080 ± 87 ms vs. 954 ± 34 ms, P < 0.001). All three correlated with pre-test probability of cardiac involvement, cardiac biomarkers, and systolic and diastolic dysfunction. During follow-up, 25 deaths occurred. An ECVi of >0.45 carried a hazard ratio (HR) for death of 3.84 [95% confidence interval (CI): 1.53–9.61], P = 0.004 and pre-contrast T1 of >1044 ms = HR 5.39 (95% CI: 1.24–23.4), P = 0.02. Extracellular volume after primed infusion and ECVb performed similarly. Isolated post-contrast T1 was non-predictive. In Cox regression models, ECVi was independently predictive of mortality (HR = 4.41, 95% CI: 1.35–14.4) after adjusting for E:E′, ejection fraction, diastolic dysfunction grade, and NT-proBNP. Conclusion Myocardial ECV (bolus or infusion technique) and pre-contrast T1 are biomarkers for cardiac AL amyloid and they predict mortality in systemic amyloidosis. PMID:25411195

Conflation and integration of archived geologic maps and associated uncertainties

USGS Publications Warehouse

Shoberg, Thomas G.

2016-01-01

Old, archived geologic maps are often available with little or no associated metadata. This creates special problems in terms of extracting their data to use with a modern database. This research focuses on some problems and uncertainties associated with conflating older geologic maps in regions where modern geologic maps are, as yet, non-existent as well as vertically integrating the conflated maps with layers of modern GIS data (in this case, The National Map of the U.S. Geological Survey). Ste. Genevieve County, Missouri was chosen as the test area. It is covered by six archived geologic maps constructed in the years between 1928 and 1994. Conflating these maps results in a map that is internally consistent with these six maps, is digitally integrated with hydrography, elevation and orthoimagery data, and has a 95% confidence interval useful for further data set integration.

Comparison of Sub-Pixel Classification Approaches for Crop-Specific Mapping

EPA Science Inventory

This paper examined two non-linear models, Multilayer Perceptron (MLP) regression and Regression Tree (RT), for estimating sub-pixel crop proportions using time-series MODIS-NDVI data. The sub-pixel proportions were estimated for three major crop types including corn, soybean, a...

Mapping of the DLQI scores to EQ-5D utility values using ordinal logistic regression.

PubMed

Ali, Faraz Mahmood; Kay, Richard; Finlay, Andrew Y; Piguet, Vincent; Kupfer, Joerg; Dalgard, Florence; Salek, M Sam

2017-11-01

The Dermatology Life Quality Index (DLQI) and the European Quality of Life-5 Dimension (EQ-5D) are separate measures that may be used to gather health-related quality of life (HRQoL) information from patients. The EQ-5D is a generic measure from which health utility estimates can be derived, whereas the DLQI is a specialty-specific measure to assess HRQoL. To reduce the burden of multiple measures being administered and to enable a more disease-specific calculation of health utility estimates, we explored an established mathematical technique known as ordinal logistic regression (OLR) to develop an appropriate model to map DLQI data to EQ-5D-based health utility estimates. Retrospective data from 4010 patients were randomly divided five times into two groups for the derivation and testing of the mapping model. Split-half cross-validation was utilized resulting in a total of ten ordinal logistic regression models for each of the five EQ-5D dimensions against age, sex, and all ten items of the DLQI. Using Monte Carlo simulation, predicted health utility estimates were derived and compared against those observed. This method was repeated for both OLR and a previously tested mapping methodology based on linear regression. The model was shown to be highly predictive and its repeated fitting demonstrated a stable model using OLR as well as linear regression. The mean differences between OLR-predicted health utility estimates and observed health utility estimates ranged from 0.0024 to 0.0239 across the ten modeling exercises, with an average overall difference of 0.0120 (a 1.6% underestimate, not of clinical importance). This modeling framework developed in this study will enable researchers to calculate EQ-5D health utility estimates from a specialty-specific study population, reducing patient and economic burden.

Robust Head-Pose Estimation Based on Partially-Latent Mixture of Linear Regressions.

PubMed

Drouard, Vincent; Horaud, Radu; Deleforge, Antoine; Ba, Sileye; Evangelidis, Georgios

2017-03-01

Head-pose estimation has many applications, such as social event analysis, human-robot and human-computer interaction, driving assistance, and so forth. Head-pose estimation is challenging, because it must cope with changing illumination conditions, variabilities in face orientation and in appearance, partial occlusions of facial landmarks, as well as bounding-box-to-face alignment errors. We propose to use a mixture of linear regressions with partially-latent output. This regression method learns to map high-dimensional feature vectors (extracted from bounding boxes of faces) onto the joint space of head-pose angles and bounding-box shifts, such that they are robustly predicted in the presence of unobservable phenomena. We describe in detail the mapping method that combines the merits of unsupervised manifold learning techniques and of mixtures of regressions. We validate our method with three publicly available data sets and we thoroughly benchmark four variants of the proposed algorithm with several state-of-the-art head-pose estimation methods.

Scalable Regression Tree Learning on Hadoop using OpenPlanet

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yin, Wei; Simmhan, Yogesh; Prasanna, Viktor

As scientific and engineering domains attempt to effectively analyze the deluge of data arriving from sensors and instruments, machine learning is becoming a key data mining tool to build prediction models. Regression tree is a popular learning model that combines decision trees and linear regression to forecast numerical target variables based on a set of input features. Map Reduce is well suited for addressing such data intensive learning applications, and a proprietary regression tree algorithm, PLANET, using MapReduce has been proposed earlier. In this paper, we describe an open source implement of this algorithm, OpenPlanet, on the Hadoop framework usingmore » a hybrid approach. Further, we evaluate the performance of OpenPlanet using realworld datasets from the Smart Power Grid domain to perform energy use forecasting, and propose tuning strategies of Hadoop parameters to improve the performance of the default configuration by 75% for a training dataset of 17 million tuples on a 64-core Hadoop cluster on FutureGrid.« less

A Comparison of Regional and SiteSpecific Volume Estimation Equations

Treesearch

Joe P. McClure; Jana Anderson; Hans T. Schreuder

1987-01-01

Regression equations for volume by region and site class were examined for lobiolly pine. The regressions for the Coastal Plain and Piedmont regions had significantly different slopes. The results shared important practical differences in percentage of confidence intervals containing the true total volume and in percentage of estimates within a specific proportion of...

Quantile regression reveals hidden bias and uncertainty in habitat models

Treesearch

Brian S. Cade; Barry R. Noon; Curtis H. Flather

2005-01-01

We simulated the effects of missing information on statistical distributions of animal response that covaried with measured predictors of habitat to evaluate the utility and performance of quantile regression for providing more useful intervals of uncertainty in habitat relationships. These procedures were evaulated for conditions in which heterogeneity and hidden bias...

3D-Digital soil property mapping by geoadditive models

NASA Astrophysics Data System (ADS)

Papritz, Andreas

2016-04-01

In many digital soil mapping (DSM) applications, soil properties must be predicted not only for a single but for multiple soil depth intervals. In the GlobalSoilMap project, as an example, predictions are computed for the 0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm, 100-200 cm depth intervals (Arrouays et al., 2014). Legacy soil data are often used for DSM. It is common for such datasets that soil properties were measured for soil horizons or for layers at varying soil depth and with non-constant thickness (support). This poses problems for DSM: One strategy is to harmonize the soil data to common depth prior to the analyses (e.g. Bishop et al., 1999) and conduct the statistical analyses for each depth interval independently. The disadvantage of this approach is that the predictions for different depths are computed independently from each other so that the predicted depth profiles may be unrealistic. Furthermore, the error induced by the harmonization to common depth is ignored in this approach (Orton et al. 2016). A better strategy is therefore to process all soil data jointly without prior harmonization by a 3D-analysis that takes soil depth and geographical position explicitly into account. Usually, the non-constant support of the data is then ignored, but Orton et al. (2016) presented recently a geostatistical approach that accounts for non-constant support of soil data and relies on restricted maximum likelihood estimation (REML) of a linear geostatistical model with a separable, heteroscedastic, zonal anisotropic auto-covariance function and area-to-point kriging (Kyriakidis, 2004.) Although this model is theoretically coherent and elegant, estimating its many parameters by REML and selecting covariates for the spatial mean function is a formidable task. A simpler approach might be to use geoadditive models (Kammann and Wand, 2003; Wand, 2003) for 3D-analyses of soil data. geoAM extend the scope of the linear model with spatially correlated errors to account for nonlinear effects of covariates by fitting componentwise smooth, nonlinear functions to the covariates (additive terms). REML estimation of model parameters and computing best linear unbiased predictions (BLUP) builds in the geoAM framework on the fact that both geostatistical and additive models can be parametrized as linear mixed models Wand, 2003. For 3D-DSM analysis of soil data, it is natural to model depth profiles of soil properties by additive terms of soil depth. Including interactions between these additive terms and covariates of the spatial mean function allows to model spatially varying depth profiles. Furthermore, with suitable choice of the basis functions of the additive term (e.g. polynomial regression splines), non-constant support of the soil data can be taken into account. Finally, boosting (Bühlmann and Hothorn, 2007) can be used for selecting covariates for the spatial mean function. The presentation will detail the geoAM approach and present an example of geoAM for 3D-analysis of legacy soil data. Arrouays, D., McBratney, A. B., Minasny, B., Hempel, J. W., Heuvelink, G. B. M., MacMillan, R. A., Hartemink, A. E., Lagacherie, P., and McKenzie, N. J. (2014). The GlobalSoilMap project specifications. In GlobalSoilMap Basis of the global spatial soil information system, pages 9-12. CRC Press. Bishop, T., McBratney, A., and Laslett, G. (1999). Modelling soil attribute depth functions with equal-area quadratic smoothing splines. Geoderma, 91(1-2), 27-45. Bühlmann, P. and Hothorn, T. (2007). Boosting algorithms: Regularization, prediction and model fitting. Statistical Science, 22(4), 477-505. Kammann, E. E. and Wand, M. P. (2003). Geoadditive models. Journal of the Royal Statistical Society. Series C: Applied Statistics, 52(1), 1-18. Kyriakidis, P. (2004). A geostatistical framework for area-to-point spatial interpolation. Geographical Analysis, 36(3), 259-289. Orton, T., Pringle, M., and Bishop, T. (2016). A one-step approach for modelling and mapping soil properties based on profile data sampled over varying depth intervals. Geoderma, 262, 174-186. Wand, M. P. (2003). Smoothing and mixed models. Computational Statistics, 18(2), 223-249.

Advancing the quantification of humid tropical forest cover loss with multi-resolution optical remote sensing data: Sampling & wall-to-wall mapping

NASA Astrophysics Data System (ADS)

Broich, Mark

Humid tropical forest cover loss is threatening the sustainability of ecosystem goods and services as vast forest areas are rapidly cleared for industrial scale agriculture and tree plantations. Despite the importance of humid tropical forest in the provision of ecosystem services and economic development opportunities, the spatial and temporal distribution of forest cover loss across large areas is not well quantified. Here I improve the quantification of humid tropical forest cover loss using two remote sensing-based methods: sampling and wall-to-wall mapping. In all of the presented studies, the integration of coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data enable advances in quantifying forest cover loss in the humid tropics. Imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used as the source of coarse spatial resolution, high temporal resolution data and imagery from the Landsat Enhanced Thematic Mapper Plus (ETM+) sensor are used as the source of moderate spatial, low temporal resolution data. In a first study, I compare the precision of different sampling designs for the Brazilian Amazon using the annual deforestation maps derived by the Brazilian Space Agency for reference. I show that sampling designs can provide reliable deforestation estimates; furthermore, sampling designs guided by MODIS data can provide more efficient estimates than the systematic design used for the United Nations Food and Agricultural Organization Forest Resource Assessment 2010. Sampling approaches, such as the one demonstrated, are viable in regions where data limitations, such as cloud contamination, limit exhaustive mapping methods. Cloud-contaminated regions experiencing high rates of change include Insular Southeast Asia, specifically Indonesia and Malaysia. Due to persistent cloud cover, forest cover loss in Indonesia has only been mapped at a 5-10 year interval using photo interpretation of single best Landsat images. Such an approach does not provide timely results, and cloud cover reduces the utility of map outputs. In a second study, I develop a method to exhaustively mine the recently opened Landsat archive for cloud-free observations and automatically map forest cover loss for Sumatra and Kalimantan for the 2000-2005 interval. In a comparison with a reference dataset consisting of 64 Landsat sample blocks, I show that my method, using per pixel time-series, provides more accurate forest cover loss maps for multiyear intervals than approaches using image composites. In a third study, I disaggregate Landsat-mapped forest cover loss, mapped over a multiyear interval, by year using annual forest cover loss maps generated from coarse spatial, high temporal resolution MODIS imagery. I further disaggregate and analyze forest cover loss by forest land use, and provinces. Forest cover loss trends show high spatial and temporal variability. These results underline the importance of annual mapping for the quantification of forest cover loss in Indonesia, specifically in the light of the developing Reducing Emissions from Deforestation and Forest Degradation in Developing Countries policy framework (REDD). All three studies highlight the advances in quantifying forest cover loss in the humid tropics made by integrating coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data. The three methods presented can be combined into an integrated monitoring strategy.

Spatiotemporal Modeling for Fine-Scale Maps of Regional Malaria Endemicity and Its Implications for Transitional Complexities in a Routine Surveillance Network in Western Cambodia

PubMed Central

Okami, Suguru; Kohtake, Naohiko

2017-01-01

Due to the associated and substantial efforts of many stakeholders involved in malaria containment, the disease burden of malaria has dramatically decreased in many malaria-endemic countries in recent years. Some decades after the past efforts of the global malaria eradication program, malaria elimination has again featured on the global health agenda. While risk distribution modeling and a mapping approach are effective tools to assist with the efficient allocation of limited health-care resources, these methods need some adjustment and reexamination in accordance with changes occurring in relation to malaria elimination. Limited available data, fine-scale data inaccessibility (for example, household or individual case data), and the lack of reliable data due to inefficiencies within the routine surveillance system, make it difficult to create reliable risk maps for decision-makers or health-care practitioners in the field. Furthermore, the risk of malaria may dynamically change due to various factors such as the progress of containment interventions and environmental changes. To address the complex and dynamic nature of situations in low-to-moderate malaria transmission settings, we built a spatiotemporal model of a standardized morbidity ratio (SMR) of malaria incidence, calculated through annual parasite incidence, using routinely reported surveillance data in combination with environmental indices such as remote sensing data, and the non-environmental regional containment status, to create fine-scale risk maps. A hierarchical Bayesian frame was employed to fit the transitioning malaria risk data onto the map. The model was set to estimate the SMRs of every study location at specific time intervals within its uncertainty range. Using the spatial interpolation of estimated SMRs at village level, we created fine-scale maps of two provinces in western Cambodia at specific time intervals. The maps presented different patterns of malaria risk distribution at specific time intervals. Moreover, the visualized weights estimated using the risk model, and the structure of the routine surveillance network, represent the transitional complexities emerging from ever-changing regional endemic situations. PMID:29034229

Long-time uncertainty propagation using generalized polynomial chaos and flow map composition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luchtenburg, Dirk M., E-mail: dluchten@cooper.edu; Brunton, Steven L.; Rowley, Clarence W.

2014-10-01

We present an efficient and accurate method for long-time uncertainty propagation in dynamical systems. Uncertain initial conditions and parameters are both addressed. The method approximates the intermediate short-time flow maps by spectral polynomial bases, as in the generalized polynomial chaos (gPC) method, and uses flow map composition to construct the long-time flow map. In contrast to the gPC method, this approach has spectral error convergence for both short and long integration times. The short-time flow map is characterized by small stretching and folding of the associated trajectories and hence can be well represented by a relatively low-degree basis. The compositionmore » of these low-degree polynomial bases then accurately describes the uncertainty behavior for long integration times. The key to the method is that the degree of the resulting polynomial approximation increases exponentially in the number of time intervals, while the number of polynomial coefficients either remains constant (for an autonomous system) or increases linearly in the number of time intervals (for a non-autonomous system). The findings are illustrated on several numerical examples including a nonlinear ordinary differential equation (ODE) with an uncertain initial condition, a linear ODE with an uncertain model parameter, and a two-dimensional, non-autonomous double gyre flow.« less

Mixing rates and limit theorems for random intermittent maps

NASA Astrophysics Data System (ADS)

Bahsoun, Wael; Bose, Christopher

2016-04-01

We study random transformations built from intermittent maps on the unit interval that share a common neutral fixed point. We focus mainly on random selections of Pomeu-Manneville-type maps {{T}α} using the full parameter range 0<α <∞ , in general. We derive a number of results around a common theme that illustrates in detail how the constituent map that is fastest mixing (i.e. smallest α) combined with details of the randomizing process, determines the asymptotic properties of the random transformation. Our key result (theorem 1.1) establishes sharp estimates on the position of return time intervals for the quenched dynamics. The main applications of this estimate are to limit laws (in particular, CLT and stable laws, depending on the parameters chosen in the range 0<α <1 ) for the associated skew product; these are detailed in theorem 3.2. Since our estimates in theorem 1.1 also hold for 1≤slant α <∞ we study a second class of random transformations derived from piecewise affine Gaspard-Wang maps, prove existence of an infinite (σ-finite) invariant measure and study the corresponding correlation asymptotics. To the best of our knowledge, this latter kind of result is completely new in the setting of random transformations.

A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications

PubMed Central

Austin, Peter C.

2017-01-01

Summary Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health, education and sociology. We describe three families of regression models for the analysis of multilevel survival data. First, Cox proportional hazards models with mixed effects incorporate cluster-specific random effects that modify the baseline hazard function. Second, piecewise exponential survival models partition the duration of follow-up into mutually exclusive intervals and fit a model that assumes that the hazard function is constant within each interval. This is equivalent to a Poisson regression model that incorporates the duration of exposure within each interval. By incorporating cluster-specific random effects, generalised linear mixed models can be used to analyse these data. Third, after partitioning the duration of follow-up into mutually exclusive intervals, one can use discrete time survival models that use a complementary log–log generalised linear model to model the occurrence of the outcome of interest within each interval. Random effects can be incorporated to account for within-cluster homogeneity in outcomes. We illustrate the application of these methods using data consisting of patients hospitalised with a heart attack. We illustrate the application of these methods using three statistical programming languages (R, SAS and Stata). PMID:29307954

A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications.

PubMed

Austin, Peter C

2017-08-01

Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health, education and sociology. We describe three families of regression models for the analysis of multilevel survival data. First, Cox proportional hazards models with mixed effects incorporate cluster-specific random effects that modify the baseline hazard function. Second, piecewise exponential survival models partition the duration of follow-up into mutually exclusive intervals and fit a model that assumes that the hazard function is constant within each interval. This is equivalent to a Poisson regression model that incorporates the duration of exposure within each interval. By incorporating cluster-specific random effects, generalised linear mixed models can be used to analyse these data. Third, after partitioning the duration of follow-up into mutually exclusive intervals, one can use discrete time survival models that use a complementary log-log generalised linear model to model the occurrence of the outcome of interest within each interval. Random effects can be incorporated to account for within-cluster homogeneity in outcomes. We illustrate the application of these methods using data consisting of patients hospitalised with a heart attack. We illustrate the application of these methods using three statistical programming languages (R, SAS and Stata).

A novel locus for Usher syndrome type I, USH1G, maps to chromosome 17q24-25.

PubMed

Mustapha, Mirna; Chouery, Eliane; Torchard-Pagnez, Delphine; Nouaille, Sylvie; Khrais, Awni; Sayegh, Fouad N; Mégarbané, André; Loiselet, Jacques; Lathrop, Mark; Petit, Christine; Weil, Dominique

2002-04-01

Usher syndrome (USH) is an autosomal recessive disorder associated with sensorineural hearing impairment and progressive visual loss attributable to retinitis pigmentosa. This syndrome is both clinically and genetically heterogeneous. Three clinical types have been described of which type I (USH1) is the most severe. Six USH1 loci have been identified. We report a Palestinian consanguineous family from Jordan with three affected children. In view of the combination of profound hearing loss, vestibular dysfunction, and retinitis pigmentosa in the patients, we classified the disease as USH1. Linkage analysis excluded the involvement of any of the known USH1 loci. A genome-wide screening allowed us to map this novel locus, USH1G, in a 23-cM interval on chromosome 17q24-25. The USH1G interval overlaps the intervals for two dominant forms of isolated hearing loss, namely DFNA20 and DFNA26. Since several examples have been reported of syndromic and isolated forms of deafness being allelic, USH1G, DFNA20, and DFNA26 might result from alterations of the same gene. Finally, a mouse mutant, jackson shaker ( js), with deafness and circling behavior has been mapped to the murine homologous region on chromosome 11.

Mapping and Modelling the Geographical Distribution and Environmental Limits of Podoconiosis in Ethiopia

PubMed Central

Deribe, Kebede; Cano, Jorge; Newport, Melanie J.; Golding, Nick; Pullan, Rachel L.; Sime, Heven; Gebretsadik, Abeba; Assefa, Ashenafi; Kebede, Amha; Hailu, Asrat; Rebollo, Maria P.; Shafi, Oumer; Bockarie, Moses J.; Aseffa, Abraham; Hay, Simon I.; Reithinger, Richard; Enquselassie, Fikre; Davey, Gail; Brooker, Simon J.

2015-01-01

Background Ethiopia is assumed to have the highest burden of podoconiosis globally, but the geographical distribution and environmental limits and correlates are yet to be fully investigated. In this paper we use data from a nationwide survey to address these issues. Methodology Our analyses are based on data arising from the integrated mapping of podoconiosis and lymphatic filariasis (LF) conducted in 2013, supplemented by data from an earlier mapping of LF in western Ethiopia in 2008–2010. The integrated mapping used woreda (district) health offices’ reports of podoconiosis and LF to guide selection of survey sites. A suite of environmental and climatic data and boosted regression tree (BRT) modelling was used to investigate environmental limits and predict the probability of podoconiosis occurrence. Principal Findings Data were available for 141,238 individuals from 1,442 communities in 775 districts from all nine regional states and two city administrations of Ethiopia. In 41.9% of surveyed districts no cases of podoconiosis were identified, with all districts in Affar, Dire Dawa, Somali and Gambella regional states lacking the disease. The disease was most common, with lymphoedema positivity rate exceeding 5%, in the central highlands of Ethiopia, in Amhara, Oromia and Southern Nations, Nationalities and Peoples regional states. BRT modelling indicated that the probability of podoconiosis occurrence increased with increasing altitude, precipitation and silt fraction of soil and decreased with population density and clay content. Based on the BRT model, we estimate that in 2010, 34.9 (95% confidence interval [CI]: 20.2–51.7) million people (i.e. 43.8%; 95% CI: 25.3–64.8% of Ethiopia’s national population) lived in areas environmentally suitable for the occurrence of podoconiosis. Conclusions Podoconiosis is more widespread in Ethiopia than previously estimated, but occurs in distinct geographical regions that are tied to identifiable environmental factors. The resultant maps can be used to guide programme planning and implementation and estimate disease burden in Ethiopia. This work provides a framework with which the geographical limits of podoconiosis could be delineated at a continental scale. PMID:26222887

Learning Inverse Rig Mappings by Nonlinear Regression.

PubMed

Holden, Daniel; Saito, Jun; Komura, Taku

2017-03-01

We present a framework to design inverse rig-functions-functions that map low level representations of a character's pose such as joint positions or surface geometry to the representation used by animators called the animation rig. Animators design scenes using an animation rig, a framework widely adopted in animation production which allows animators to design character poses and geometry via intuitive parameters and interfaces. Yet most state-of-the-art computer animation techniques control characters through raw, low level representations such as joint angles, joint positions, or vertex coordinates. This difference often stops the adoption of state-of-the-art techniques in animation production. Our framework solves this issue by learning a mapping between the low level representations of the pose and the animation rig. We use nonlinear regression techniques, learning from example animation sequences designed by the animators. When new motions are provided in the skeleton space, the learned mapping is used to estimate the rig controls that reproduce such a motion. We introduce two nonlinear functions for producing such a mapping: Gaussian process regression and feedforward neural networks. The appropriate solution depends on the nature of the rig and the amount of data available for training. We show our framework applied to various examples including articulated biped characters, quadruped characters, facial animation rigs, and deformable characters. With our system, animators have the freedom to apply any motion synthesis algorithm to arbitrary rigging and animation pipelines for immediate editing. This greatly improves the productivity of 3D animation, while retaining the flexibility and creativity of artistic input.

Advanced microwave soil moisture studies. [Big Sioux River Basin, Iowa

NASA Technical Reports Server (NTRS)

Dalsted, K. J.; Harlan, J. C.

1983-01-01

Comparisons of low level L-band brightness temperature (TB) and thermal infrared (TIR) data as well as the following data sets: soil map and land cover data; direct soil moisture measurement; and a computer generated contour map were statistically evaluated using regression analysis and linear discriminant analysis. Regression analysis of footprint data shows that statistical groupings of ground variables (soil features and land cover) hold promise for qualitative assessment of soil moisture and for reducing variance within the sampling space. Dry conditions appear to be more conductive to producing meaningful statistics than wet conditions. Regression analysis using field averaged TB and TIR data did not approach the higher sq R values obtained using within-field variations. The linear discriminant analysis indicates some capacity to distinguish categories with the results being somewhat better on a field basis than a footprint basis.

Inconsistencies in Numerical Simulations of Dynamical Systems Using Interval Arithmetic

NASA Astrophysics Data System (ADS)

Nepomuceno, Erivelton G.; Peixoto, Márcia L. C.; Martins, Samir A. M.; Rodrigues, Heitor M.; Perc, Matjaž

Over the past few decades, interval arithmetic has been attracting widespread interest from the scientific community. With the expansion of computing power, scientific computing is encountering a noteworthy shift from floating-point arithmetic toward increased use of interval arithmetic. Notwithstanding the significant reliability of interval arithmetic, this paper presents a theoretical inconsistency in a simulation of dynamical systems using a well-known implementation of arithmetic interval. We have observed that two natural interval extensions present an empty intersection during a finite time range, which is contrary to the fundamental theorem of interval analysis. We have proposed a procedure to at least partially overcome this problem, based on the union of the two generated pseudo-orbits. This paper also shows a successful case of interval arithmetic application in the reduction of interval width size on the simulation of discrete map. The implications of our findings on the reliability of scientific computing using interval arithmetic have been properly addressed using two numerical examples.

An LPV Adaptive Observer for Updating a Map Applied to an MAF Sensor in a Diesel Engine

PubMed Central

Liu, Zhiyuan; Wang, Changhui

2015-01-01

In this paper, a new method for mass air flow (MAF) sensor error compensation and an online updating error map (or lookup table) due to installation and aging in a diesel engine is developed. Since the MAF sensor error is dependent on the engine operating point, the error model is represented as a two-dimensional (2D) map with two inputs, fuel mass injection quantity and engine speed. Meanwhile, the 2D map representing the MAF sensor error is described as a piecewise bilinear interpolation model, which can be written as a dot product between the regression vector and parameter vector using a membership function. With the combination of the 2D map regression model and the diesel engine air path system, an LPV adaptive observer with low computational load is designed to estimate states and parameters jointly. The convergence of the proposed algorithm is proven under the conditions of persistent excitation and given inequalities. The observer is validated against the simulation data from engine software enDYNA provided by Tesis. The results demonstrate that the operating point-dependent error of the MAF sensor can be approximated acceptably by the 2D map from the proposed method. PMID:26512675

Selection of vegetation indices for mapping the sugarcane condition around the oil and gas field of North West Java Basin, Indonesia

NASA Astrophysics Data System (ADS)

Muji Susantoro, Tri; Wikantika, Ketut; Saepuloh, Asep; Handoyo Harsolumakso, Agus

2018-05-01

Selection of vegetation indices in plant mapping is needed to provide the best information of plant conditions. The methods used in this research are the standard deviation and the linear regression. This research tried to determine the vegetation indices used for mapping the sugarcane conditions around oil and gas fields. The data used in this study is Landsat 8 OLI/TIRS. The standard deviation analysis on the 23 vegetation indices with 27 samples has resulted in the six highest standard deviations of vegetation indices, termed as GRVI, SR, NLI, SIPI, GEMI and LAI. The standard deviation values are 0.47; 0.43; 0.30; 0.17; 0.16 and 0.13. Regression correlation analysis on the 23 vegetation indices with 280 samples has resulted in the six vegetation indices, termed as NDVI, ENDVI, GDVI, VARI, LAI and SIPI. This was performed based on regression correlation with the lowest value R2 than 0,8. The combined analysis of the standard deviation and the regression correlation has obtained the five vegetation indices, termed as NDVI, ENDVI, GDVI, LAI and SIPI. The results of the analysis of both methods show that a combination of two methods needs to be done to produce a good analysis of sugarcane conditions. It has been clarified through field surveys and showed good results for the prediction of microseepages.

The solar wind effect on cosmic rays and solar activity

NASA Technical Reports Server (NTRS)

Fujimoto, K.; Kojima, H.; Murakami, K.

1985-01-01

The relation of cosmic ray intensity to solar wind velocity is investigated, using neutron monitor data from Kiel and Deep River. The analysis shows that the regression coefficient of the average intensity for a time interval to the corresponding average velocity is negative and that the absolute effect increases monotonously with the interval of averaging, tau, that is, from -0.5% per 100km/s for tau = 1 day to -1.1% per 100km/s for tau = 27 days. For tau 27 days the coefficient becomes almost constant independently of the value of tau. The analysis also shows that this tau-dependence of the regression coefficiently is varying with the solar activity.

Generative Topographic Mapping of Conformational Space.

PubMed

Horvath, Dragos; Baskin, Igor; Marcou, Gilles; Varnek, Alexandre

2017-10-01

Herein, Generative Topographic Mapping (GTM) was challenged to produce planar projections of the high-dimensional conformational space of complex molecules (the 1LE1 peptide). GTM is a probability-based mapping strategy, and its capacity to support property prediction models serves to objectively assess map quality (in terms of regression statistics). The properties to predict were total, non-bonded and contact energies, surface area and fingerprint darkness. Map building and selection was controlled by a previously introduced evolutionary strategy allowed to choose the best-suited conformational descriptors, options including classical terms and novel atom-centric autocorrellograms. The latter condensate interatomic distance patterns into descriptors of rather low dimensionality, yet precise enough to differentiate between close favorable contacts and atom clashes. A subset of 20 K conformers of the 1LE1 peptide, randomly selected from a pool of 2 M geometries (generated by the S4MPLE tool) was employed for map building and cross-validation of property regression models. The GTM build-up challenge reached robust three-fold cross-validated determination coefficients of Q 2 =0.7…0.8, for all modeled properties. Mapping of the full 2 M conformer set produced intuitive and information-rich property landscapes. Functional and folding subspaces appear as well-separated zones, even though RMSD with respect to the PDB structure was never used as a selection criterion of the maps. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Topographic map of part of the Kasei Valles and Sacra Fossae regions of Mars - MTM 500k 20/287E OMKT

USGS Publications Warehouse

Rosiek, Mark R.; Redding, Bonnie L.; Galuszca, Donna M.

2005-01-01

This map is part of a series of topographic maps of areas of special scientific interest on Mars. The topography was compiled photogrammetrically using Viking Orbiter stereo image pairs and photoclinometry from a Viking Orbiter image. The contour interval is 250 m. Horizontal and vertical control was established using the USGS Mars Digital Image Model 2.0 (MDIM 2.0) and data from the Mars Orbiter Laser Altimeter (MOLA).

Topographic map of Golden Gate Estates, Collier County, Florida

USGS Publications Warehouse

Jurado, Antonio

1981-01-01

Construction of canals related to land development in the Golden Gate Estates area of Collier County, Fla., has altered the natural drainage pattern of the watershed. The area of approximately 300 square miles was topographically mapped with a contour interval of 0.5 foot to assist in determining the effects of canal construction on the surface-water and ground-water resources in the watershed. The topographic map was prepared at a scale of 1:48,000 using aerial photography and ground-control points. (USGS)

Regression equations to estimate seasonal flow duration, n-day high-flow frequency, and n-day low-flow frequency at sites in North Dakota using data through water year 2009

USGS Publications Warehouse

Williams-Sether, Tara; Gross, Tara A.

2016-02-09

Seasonal mean daily flow data from 119 U.S. Geological Survey streamflow-gaging stations in North Dakota; the surrounding states of Montana, Minnesota, and South Dakota; and the Canadian provinces of Manitoba and Saskatchewan with 10 or more years of unregulated flow record were used to develop regression equations for flow duration, n-day high flow and n-day low flow using ordinary least-squares and Tobit regression techniques. Regression equations were developed for seasonal flow durations at the 10th, 25th, 50th, 75th, and 90th percent exceedances; the 1-, 7-, and 30-day seasonal mean high flows for the 10-, 25-, and 50-year recurrence intervals; and the 1-, 7-, and 30-day seasonal mean low flows for the 2-, 5-, and 10-year recurrence intervals. Basin and climatic characteristics determined to be significant explanatory variables in one or more regression equations included drainage area, percentage of basin drainage area that drains to isolated lakes and ponds, ruggedness number, stream length, basin compactness ratio, minimum basin elevation, precipitation, slope ratio, stream slope, and soil permeability. The adjusted coefficient of determination for the n-day high-flow regression equations ranged from 55.87 to 94.53 percent. The Chi2 values for the duration regression equations ranged from 13.49 to 117.94, whereas the Chi2 values for the n-day low-flow regression equations ranged from 4.20 to 49.68.

A regression approach to the mapping of bio-physical characteristics of surface sediment using in situ and airborne hyperspectral acquisitions

NASA Astrophysics Data System (ADS)

Ibrahim, Elsy; Kim, Wonkook; Crawford, Melba; Monbaliu, Jaak

2017-02-01

Remote sensing has been successfully utilized to distinguish and quantify sediment properties in the intertidal environment. Classification approaches of imagery are popular and powerful yet can lead to site- and case-specific results. Such specificity creates challenges for temporal studies. Thus, this paper investigates the use of regression models to quantify sediment properties instead of classifying them. Two regression approaches, namely multiple regression (MR) and support vector regression (SVR), are used in this study for the retrieval of bio-physical variables of intertidal surface sediment of the IJzermonding, a Belgian nature reserve. In the regression analysis, mud content, chlorophyll a concentration, organic matter content, and soil moisture are estimated using radiometric variables of two airborne sensors, namely airborne hyperspectral sensor (AHS) and airborne prism experiment (APEX) and and using field hyperspectral acquisitions by analytical spectral device (ASD). The performance of the two regression approaches is best for the estimation of moisture content. SVR attains the highest accuracy without feature reduction while MR achieves good results when feature reduction is carried out. Sediment property maps are successfully obtained using the models and hyperspectral imagery where SVR used with all bands achieves the best performance. The study also involves the extraction of weights identifying the contribution of each band of the images in the quantification of each sediment property when MR and principal component analysis are used.

Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings.

PubMed

Choi, Jae-Seok; Kim, Munchurl

2017-03-01

Super-resolution (SR) has become more vital, because of its capability to generate high-quality ultra-high definition (UHD) high-resolution (HR) images from low-resolution (LR) input images. Conventional SR methods entail high computational complexity, which makes them difficult to be implemented for up-scaling of full-high-definition input images into UHD-resolution images. Nevertheless, our previous super-interpolation (SI) method showed a good compromise between Peak-Signal-to-Noise Ratio (PSNR) performances and computational complexity. However, since SI only utilizes simple linear mappings, it may fail to precisely reconstruct HR patches with complex texture. In this paper, we present a novel SR method, which inherits the large-to-small patch conversion scheme from SI but uses global regression based on local linear mappings (GLM). Thus, our new SR method is called GLM-SI. In GLM-SI, each LR input patch is divided into 25 overlapped subpatches. Next, based on the local properties of these subpatches, 25 different local linear mappings are applied to the current LR input patch to generate 25 HR patch candidates, which are then regressed into one final HR patch using a global regressor. The local linear mappings are learned cluster-wise in our off-line training phase. The main contribution of this paper is as follows: Previously, linear-mapping-based conventional SR methods, including SI only used one simple yet coarse linear mapping to each patch to reconstruct its HR version. On the contrary, for each LR input patch, our GLM-SI is the first to apply a combination of multiple local linear mappings, where each local linear mapping is found according to local properties of the current LR patch. Therefore, it can better approximate nonlinear LR-to-HR mappings for HR patches with complex texture. Experiment results show that the proposed GLM-SI method outperforms most of the state-of-the-art methods, and shows comparable PSNR performance with much lower computational complexity when compared with a super-resolution method based on convolutional neural nets (SRCNN15). Compared with the previous SI method that is limited with a scale factor of 2, GLM-SI shows superior performance with average 0.79 dB higher in PSNR, and can be used for scale factors of 3 or higher.

Spatial Representation in Blind Children. 3: Effects of Individual Differences.

ERIC Educational Resources Information Center

Fletcher, Janet F.

1981-01-01

Data from a study of spatial representation in blind children were subjected to two stepwise regression analyses to determine the relationships between several subject related variables and responses to "map" (cognitive map) and "route" (sequential memory) questions about the position of furniture in a recently explored room. (Author/SBH)

EFFECTS OF IMPROVED PRECIPITATION ESTIMATES ON AUTOMATED RUNOFF MAPPING: EASTERN UNITED STATES

EPA Science Inventory

We evaluated maps of runoff created by means of two automated procedures. We implemented each procedure using precipitation estimates of both 5-km and 10-km resolution from PRISM (Parameter-elevation Regressions on Independent Slopes Model). Our goal was to determine if using the...

Genomic Dissection of Leaf Angle in Maize (Zea mays L.) Using a Four-Way Cross Mapping Population.

PubMed

Ding, Junqiang; Zhang, Luyan; Chen, Jiafa; Li, Xiantang; Li, Yongming; Cheng, Hongliang; Huang, Rongrong; Zhou, Bo; Li, Zhimin; Wang, Jiankang; Wu, Jianyu

2015-01-01

Increasing grain yield by the selection for optimal plant architecture has been the key focus in modern maize breeding. As a result, leaf angle, an important determinant of plant architecture, has been significantly improved to adapt to the ever-increasing plant density in maize production over the past several decades. To extend our understanding on the genetic mechanisms of leaf angle in maize, we developed the first four-way cross mapping population, consisting of 277 lines derived from four maize inbred lines with varied leaf angles. The four-way cross mapping population together with the four parental lines were evaluated for leaf angle in two environments. In this study, we reported linkage maps built in the population and quantitative trait loci (QTL) on leaf angle detected by inclusive composite interval mapping (ICIM). ICIM applies a two-step strategy to effectively separate the cofactor selection from the interval mapping, which controls the background additive and dominant effects at the same time. A total of 14 leaf angle QTL were identified, four of which were further validated in near-isogenic lines (NILs). Seven of the 14 leaf angle QTL were found to overlap with the published leaf angle QTL or genes, and the remaining QTL were unique to the four-way population. This study represents the first example of QTL mapping using a four-way cross population in maize, and demonstrates that the use of specially designed four-way cross is effective in uncovering the basis of complex and polygenetic trait like leaf angle in maize.

Genomic Dissection of Leaf Angle in Maize (Zea mays L.) Using a Four-Way Cross Mapping Population

PubMed Central

Li, Xiantang; Li, Yongming; Cheng, Hongliang; Huang, Rongrong; Zhou, Bo; Li, Zhimin; Wang, Jiankang; Wu, Jianyu

2015-01-01

Increasing grain yield by the selection for optimal plant architecture has been the key focus in modern maize breeding. As a result, leaf angle, an important determinant of plant architecture, has been significantly improved to adapt to the ever-increasing plant density in maize production over the past several decades. To extend our understanding on the genetic mechanisms of leaf angle in maize, we developed the first four-way cross mapping population, consisting of 277 lines derived from four maize inbred lines with varied leaf angles. The four-way cross mapping population together with the four parental lines were evaluated for leaf angle in two environments. In this study, we reported linkage maps built in the population and quantitative trait loci (QTL) on leaf angle detected by inclusive composite interval mapping (ICIM). ICIM applies a two-step strategy to effectively separate the cofactor selection from the interval mapping, which controls the background additive and dominant effects at the same time. A total of 14 leaf angle QTL were identified, four of which were further validated in near-isogenic lines (NILs). Seven of the 14 leaf angle QTL were found to overlap with the published leaf angle QTL or genes, and the remaining QTL were unique to the four-way population. This study represents the first example of QTL mapping using a four-way cross population in maize, and demonstrates that the use of specially designed four-way cross is effective in uncovering the basis of complex and polygenetic trait like leaf angle in maize. PMID:26509792

Genetic mapping and predictive testing for multiple endocrine neoplasia type 1 (MEN1)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pandit, S.D.; Read, C.; Liu, L.

1994-09-01

Multiple endocrine neoplasia type 1 (MEN1) is an autosomal dominant disorder with an estimated prevalance of 20-200 per million persons. It is characterized by the combined occurence of tumors involving two or more endocrine glands, namely the parathyroid glands, the endocrine pancreas and the anterior pituitary. This disorder affects virtually all age groups with an average range of 20-60 years. Linkage analysis mapped the MEN1 locus to 11q13 near the human muscle glycogen phosphorylase (PYGM) locus. Additional genetic mapping and deletion analysis studies have refined the region containing the MEN1 locus to a 3 cM interval flanked by markers PYGMmore » and D11S146/D11S97, a physical distance of approximately 1.5 Mb. We have identified 8 large families segregating MEN1 (71 affected from a population of 389 individuals). A high resolution reference map for the 11q13 region has been constructed using four new microsatellite markers, the CEPH reference (40 family) pedigree resource, and the CRI-MAP program package. Subsequent analyses using the LINKAGE program package and 8 MEN 1 families placed the MEN1 locus within the context of the microsatellite map. This map was used to develop a linkage-based predictive test. These markers have also been used to further refine the interval containing the MEN1 locus from the study of chromosome deletions (loss of heterozygosity, LOH studies) in paired sets of tumor and germline DNA from 87 MEN 1 affected individuals.« less

EnviroAtlas - Austin, TX - Proximity to Parks

EPA Pesticide Factsheets

This EnviroAtlas dataset shows the approximate walking distance from a park entrance at any given location within the EnviroAtlas community boundary. The zones are estimated in 1/4 km intervals up to 1km then in 1km intervals up to 5km. Park entrances were included in this analysis if they were within 5km of the community boundary. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Hailey-Hailey disease maps to a 5 cM interval on chromosome 3q21-q24.

PubMed

Richard, G; Korge, B P; Wright, A R; Mazzanti, C; Harth, W; Annicchiarico-Petruzzelli, M; Compton, J G; Bale, S J

1995-09-01

Hailey-Hailey disease (HHD) is a rare autosomal dominant genodermatosis characterized by disturbed keratinocyte adhesion. The disease has recently been mapped to a 14 cM region on chromosome 3q. We have further refined the location of the HHD gene by linkage analysis in six HHD families from Germany and Italy using 11 polymorphic microsatellite markers and found no evidence for genetic heterogeneity. We observed complete cosegregation between HHD and marker D3S1587, with a maximal lod score of 4.54. Detailed haplotype analyses allowed us to narrow the interval containing the HHD locus to 5 cM, flanked by D3S1589 and D3S1290.

Readiness of Primary Care Practices for Medical Home Certification

PubMed Central

Clark, Sarah J.; Sakshaug, Joseph W.; Chen, Lena M.; Hollingsworth, John M.

2013-01-01

OBJECTIVES: To assess the prevalence of medical home infrastructure among primary care practices for children and identify practice characteristics associated with medical home infrastructure. METHODS: Cross-sectional analysis of restricted data files from 2007 and 2008 of the National Ambulatory Medical Care Survey. We mapped survey items to the 2011 National Committee on Quality Assurance’s Patient-Centered Medical home standards. Points were awarded for each “passed” element based on National Committee for Quality Assurance scoring, and we then calculated the percentage of the total possible points met for each practice. We used multivariate linear regression to assess associations between practice characteristics and the percentage of medical home infrastructure points attained. RESULTS: On average, pediatric practices attained 38% (95% confidence interval 34%–41%) of medical home infrastructure points, and family/general practices attained 36% (95% confidence interval 33%–38%). Practices scored higher on medical home elements related to direct patient care (eg, providing comprehensive health assessments) and lower in areas highly dependent on health information technology (eg, computerized prescriptions, test ordering, laboratory result viewing, or quality of care measurement and reporting). In multivariate analyses, smaller practice size was significantly associated with lower infrastructure scores. Practice ownership, urban versus rural location, and proportion of visits covered by public insurers were not consistently associated with a practice’s infrastructure score. CONCLUSIONS: Medical home programs need effective approaches to support practice transformation in the small practices that provide the vast majority of the primary care for children in the United States. PMID:23382438

Rapid performance modeling and parameter regression of geodynamic models

NASA Astrophysics Data System (ADS)

Brown, J.; Duplyakin, D.

2016-12-01

Geodynamic models run in a parallel environment have many parameters with complicated effects on performance and scientifically-relevant functionals. Manually choosing an efficient machine configuration and mapping out the parameter space requires a great deal of expert knowledge and time-consuming experiments. We propose an active learning technique based on Gaussion Process Regression to automatically select experiments to map out the performance landscape with respect to scientific and machine parameters. The resulting performance model is then used to select optimal experiments for improving the accuracy of a reduced order model per unit of computational cost. We present the framework and evaluate its quality and capability using popular lithospheric dynamics models.

Multi-species Management Using Modeling and Decision Theory Applications to Integrated Natural Resources Management Planning

DTIC Science & Technology

2008-06-01

or just habitat area . They used linear interpolation to derive maps for each time step in the population model and population dynamics were...Metapopulation Map ............................................................................................................... 20  Figure 12. Habitat...Stephen’s kangaroo rat (SKR). In some areas of coastal sage scrub habitat short fire return intervals make the habitat suitable for the SKR while

Estimating equivalence with quantile regression

USGS Publications Warehouse

Cade, B.S.

2011-01-01

Equivalence testing and corresponding confidence interval estimates are used to provide more enlightened statistical statements about parameter estimates by relating them to intervals of effect sizes deemed to be of scientific or practical importance rather than just to an effect size of zero. Equivalence tests and confidence interval estimates are based on a null hypothesis that a parameter estimate is either outside (inequivalence hypothesis) or inside (equivalence hypothesis) an equivalence region, depending on the question of interest and assignment of risk. The former approach, often referred to as bioequivalence testing, is often used in regulatory settings because it reverses the burden of proof compared to a standard test of significance, following a precautionary principle for environmental protection. Unfortunately, many applications of equivalence testing focus on establishing average equivalence by estimating differences in means of distributions that do not have homogeneous variances. I discuss how to compare equivalence across quantiles of distributions using confidence intervals on quantile regression estimates that detect differences in heterogeneous distributions missed by focusing on means. I used one-tailed confidence intervals based on inequivalence hypotheses in a two-group treatment-control design for estimating bioequivalence of arsenic concentrations in soils at an old ammunition testing site and bioequivalence of vegetation biomass at a reclaimed mining site. Two-tailed confidence intervals based both on inequivalence and equivalence hypotheses were used to examine quantile equivalence for negligible trends over time for a continuous exponential model of amphibian abundance. ?? 2011 by the Ecological Society of America.

Analysis of 133 meioses places the genes for nevoid basal cell carcinoma (gorlin) syndrome and fanconi anemia group C in a 2.6-cM interval and contributes to the fine map of 9q22.3

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farndon, P.A.; Hardy, C.; Kilpatrick, M.W.

1994-09-15

Four disease genes (NBCCS, ESS1, XPAC, FACC) map to 9q22.3-q31. A fine map of this region was produced by linkage and haplotype analysis using 12 DNA markers. The gene for nevoid basal cell carcinoma syndrome (NBCCS, Gorlin) has an important role in congenital malformations and carcinogenesis. Phase-known recombinants in a study of 133 meioses place NBCCS between (D9S12/D9S151) and D9S176. Haplotype analysis in a two-generation family suggests that NBCCS lies in a smaller interval of 2.6 cM centromeric to D9S287. These flanking markers will be useful clinically for gene tracking. Recombinants also map FACC (Fanconi anemia, group C) to themore » same region, between (D9S12/D9S151) and D9S287. The recombination rate between (D9S12/D9S151) and D9S53 in males is 8.3% and 13.2% in females, giving a sex-specific male:female ratio of 1:1.6 and a sex-averaged map distance of 10.4 cM. No double recombinants were detected, in agreement with the apparently complete level of interference predicted from the male chiasmata map. 19 refs., 2 figs., 1 tab.« less

Tactile mapping system: a novel imaging technology for surface topography and elasticity of tissues or organs.

PubMed

Oie, Tomonori; Suzuki, Hisato; Fukuda, Toru; Murayama, Yoshinobu; Omata, Sadao; Kanda, Keiichi; Nakayama, Yasuhide

2009-11-01

: We demonstrated that the tactile mapping system (TMS) has a high degree of spatial precision in the distribution mapping of surface elasticity of tissues or organs. : Samples used were a circumferential section of a small-caliber porcine artery (diameter: ∼3 mm) and an elasticity test pattern with a line and space configuration for the distribution mapping of elasticity, prepared by regional micropatterning of a 14-μm thick gelatin hydrogel coating on a polyurethane sheet. Surface topography and elasticity in normal saline were simultaneously investigated by TMS using a probe with a diameter of 5 or 12 μm, a spatial interval of 1 to 5 μm, and an indentation depth of 4 μm. : In the test pattern, a spatial resolution in TMS of <5 μm was acquired under water with a minimal probe diameter and spatial interval of the probe movement. TMS was used for the distribution mapping of surface elasticity in a flat, circumferential section (thickness: ∼0.5 mm) of a porcine artery, and the concentric layers of the vascular wall, including the collagen-rich and elastin-rich layers, could be clearly differentiated in terms of surface elasticity at the spatial resolution of <2 μm. : TMS is a simple and inexpensive technique for the distribution mapping of the surface elasticity in vascular tissues at the spatial resolution <2 μm. TMS has the ability to analyze a complex structure of the tissue samples under normal saline.

Arrhythmic hazard map for a 3D whole-ventricles model under multiple ion channel block.

PubMed

Okada, Jun-Ichi; Yoshinaga, Takashi; Kurokawa, Junko; Washio, Takumi; Furukawa, Tetsushi; Sawada, Kohei; Sugiura, Seiryo; Hisada, Toshiaki

2018-05-10

To date, proposed in silico models for preclinical cardiac safety testing are limited in their predictability and usability. We previously reported a multi-scale heart simulation that accurately predicts arrhythmogenic risk for benchmark drugs. We extend this approach and report the first comprehensive hazard map of drug-induced arrhythmia based on the exhaustive in silico electrocardiogram (ECG) database of drug effects, developed using a petaflop computer. A total of 9075 electrocardiograms constitute the five-dimensional hazard map, with coordinates representing the extent of the block of each of the five ionic currents (rapid delayed rectifier potassium current (IKr), fast (INa) and late (INa,L) components of the sodium current, L-type calcium current (ICa,L) and slow delayed rectifier current (IKs)), involved in arrhythmogenesis. Results of the evaluation of arrhythmogenic risk based on this hazard map agreed well with the risk assessments reported in three references. ECG database also suggested that the interval between the J-point and the T-wave peak is a superior index of arrhythmogenicity compared to other ECG biomarkers including the QT interval. Because concentration-dependent effects on electrocardiograms of any drug can be traced on this map based on in vitro current assay data, its arrhythmogenic risk can be evaluated without performing costly and potentially risky human electrophysiological assays. Hence, the map serves as a novel tool for use in pharmaceutical research and development. This article is protected by copyright. All rights reserved.

Considerations of solar wind dynamics in mapping of Jupiter's auroral features to magnetospheric sources

NASA Astrophysics Data System (ADS)

Gyalay, S.; Vogt, M.; Withers, P.

2015-12-01

Previous studies have mapped locations from the magnetic equator to the ionosphere in order to understand how auroral features relate to magnetospheric sources. Vogt et al. (2011) in particular mapped equatorial regions to the ionosphere by using a method of flux equivalence—requiring that the magnetic flux in a specified region at the equator is equal to the magnetic flux in the region to which it maps in the ionosphere. This is preferred to methods relying on tracing field lines from global Jovian magnetic field models, which are inaccurate beyond 30 Jupiter radii from the planet. That previous study produced a two-dimensional model—accounting for changes with radial distance and local time—of the normal component of the magnetic field in the equatorial region. However, this two-dimensional fit—which aggregated all equatorial data from Pioneer 10, Pioneer 11, Voyager 1, Voyager 2, Ulysses, and Galileo—did not account for temporal variability resulting from changing solar wind conditions. Building off of that project, this study aims to map the Jovian aurora to the magnetosphere for two separate cases: with a nominal magnetosphere, and with a magnetosphere compressed by high solar wind dynamic pressure. Using the Michigan Solar Wind Model (mSWiM) to predict the solar wind conditions upstream of Jupiter, intervals of high solar wind dynamic pressure were separated from intervals of low solar wind dynamic pressure—thus creating two datasets of magnetometer measurements to be used for two separate 2D fits, and two separate mappings.

Electric charge requirements of pediatric cochlear implant recipients enrolled in the Childhood Development After Cochlear Implantation study.

PubMed

Zwolan, Teresa A; O'Sullivan, Mary Beth; Fink, Nancy E; Niparko, John K

2008-02-01

To evaluate mapping characteristics of children with cochlear implants who are enrolled in the Childhood Development After Cochlear Implantation (CDACI) multicenter study. Longitudinal evaluation during 24 months of speech processor maps of children with cochlear implants prospectively enrolled in the study. Six tertiary referral centers. One hundred eighty-eight children enrolled in the CDACI study who were 5 years old or younger at the time of enrollment. Of these children, 184 received unilateral implants, and 4 received simultaneous bilateral implants. Children attended regular mapping sessions at their implant clinic as part of the study protocol. Maps were examined for each subject at 4 different time intervals: at device activation and 6, 12, and 24 months postactivation. Mean C/M levels (in charge per phase) were compared for 4 different time intervals, for 3 different devices, for 6 different implant centers, and for children with normal and abnormal cochleae. All 3 types of implant devices demonstrate significant increases in C/M levels between device activation and the 24-month appointment. Significant differences in mean C/M levels were noted between devices. Children with cochlear anomalies demonstrate significantly greater C/M levels than children with normal cochleae. The CDACI study has enabled us to evaluate the mapping characteristics of pediatric patients who use 3 different devices and were implanted at a variety of implant centers. Analysis of such data enables us to better understand the mapping characteristics of children with cochlear implants.

Statistical procedures for determination and verification of minimum reporting levels for drinking water methods.

PubMed

Winslow, Stephen D; Pepich, Barry V; Martin, John J; Hallberg, George R; Munch, David J; Frebis, Christopher P; Hedrick, Elizabeth J; Krop, Richard A

2006-01-01

The United States Environmental Protection Agency's Office of Ground Water and Drinking Water has developed a single-laboratory quantitation procedure: the lowest concentration minimum reporting level (LCMRL). The LCMRL is the lowest true concentration for which future recovery is predicted to fall, with high confidence (99%), between 50% and 150%. The procedure takes into account precision and accuracy. Multiple concentration replicates are processed through the entire analytical method and the data are plotted as measured sample concentration (y-axis) versus true concentration (x-axis). If the data support an assumption of constant variance over the concentration range, an ordinary least-squares regression line is drawn; otherwise, a variance-weighted least-squares regression is used. Prediction interval lines of 99% confidence are drawn about the regression. At the points where the prediction interval lines intersect with data quality objective lines of 50% and 150% recovery, lines are dropped to the x-axis. The higher of the two values is the LCMRL. The LCMRL procedure is flexible because the data quality objectives (50-150%) and the prediction interval confidence (99%) can be varied to suit program needs. The LCMRL determination is performed during method development only. A simpler procedure for verification of data quality objectives at a given minimum reporting level (MRL) is also presented. The verification procedure requires a single set of seven samples taken through the entire method procedure. If the calculated prediction interval is contained within data quality recovery limits (50-150%), the laboratory performance at the MRL is verified.

[Evaluation of estimation of prevalence ratio using bayesian log-binomial regression model].

PubMed

Gao, W L; Lin, H; Liu, X N; Ren, X W; Li, J S; Shen, X P; Zhu, S L

2017-03-10

To evaluate the estimation of prevalence ratio ( PR ) by using bayesian log-binomial regression model and its application, we estimated the PR of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea in their infants by using bayesian log-binomial regression model in Openbugs software. The results showed that caregivers' recognition of infant' s risk signs of diarrhea was associated significantly with a 13% increase of medical care-seeking. Meanwhile, we compared the differences in PR 's point estimation and its interval estimation of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea and convergence of three models (model 1: not adjusting for the covariates; model 2: adjusting for duration of caregivers' education, model 3: adjusting for distance between village and township and child month-age based on model 2) between bayesian log-binomial regression model and conventional log-binomial regression model. The results showed that all three bayesian log-binomial regression models were convergence and the estimated PRs were 1.130(95 %CI : 1.005-1.265), 1.128(95 %CI : 1.001-1.264) and 1.132(95 %CI : 1.004-1.267), respectively. Conventional log-binomial regression model 1 and model 2 were convergence and their PRs were 1.130(95 % CI : 1.055-1.206) and 1.126(95 % CI : 1.051-1.203), respectively, but the model 3 was misconvergence, so COPY method was used to estimate PR , which was 1.125 (95 %CI : 1.051-1.200). In addition, the point estimation and interval estimation of PRs from three bayesian log-binomial regression models differed slightly from those of PRs from conventional log-binomial regression model, but they had a good consistency in estimating PR . Therefore, bayesian log-binomial regression model can effectively estimate PR with less misconvergence and have more advantages in application compared with conventional log-binomial regression model.

Complete Bouguer gravity anomaly map of the state of Colorado

USGS Publications Warehouse

Abrams, Gerda A.

1993-01-01

The Bouguer gravity anomaly map is part of a folio of maps of Colorado cosponsored by the National Mineral Resources Assessment Program (NAMRAP) and the National Geologic Mapping Program (COGEOMAP) and was produced to assist in studies of the mineral resource potential and tectonic setting of the State. Previous compilations of about 12,000 gravity stations by Behrendt and Bajwa (1974a,b) are updated by this map. The data was reduced at a 2.67 g/cm3 and the grid contoured at 3 mGal intervals. This map will aid in the mineral resource assessment by indicating buried intrusive complexes, volcanic fields, major faults and shear zones, and sedimentary basins; helping to identify concealed geologic units; and identifying localities that might be hydrothermically altered or mineralized.

Proarrhythmia risk prediction using human induced pluripotent stem cell-derived cardiomyocytes.

PubMed

Yamazaki, Daiju; Kitaguchi, Takashi; Ishimura, Masakazu; Taniguchi, Tomohiko; Yamanishi, Atsuhiro; Saji, Daisuke; Takahashi, Etsushi; Oguchi, Masao; Moriyama, Yuta; Maeda, Sanae; Miyamoto, Kaori; Morimura, Kaoru; Ohnaka, Hiroki; Tashibu, Hiroyuki; Sekino, Yuko; Miyamoto, Norimasa; Kanda, Yasunari

2018-04-01

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are expected to become a useful tool for proarrhythmia risk prediction in the non-clinical drug development phase. Several features including electrophysiological properties, ion channel expression profile and drug responses were investigated using commercially available hiPSC-CMs, such as iCell-CMs and Cor.4U-CMs. Although drug-induced arrhythmia has been extensively examined by microelectrode array (MEA) assays in iCell-CMs, it has not been fully understood an availability of Cor.4U-CMs for proarrhythmia risk. Here, we evaluated the predictivity of proarrhythmia risk using Cor.4U-CMs. MEA assay revealed linear regression between inter-spike interval and field potential duration (FPD). The hERG inhibitor E-4031 induced reverse-use dependent FPD prolongation. We next evaluated the proarrhythmia risk prediction by a two-dimensional map, which we have previously proposed. We determined the relative torsade de pointes risk score, based on the extent of FPD with Fridericia's correction (FPDcF) change and early afterdepolarization occurrence, and calculated the margins normalized to free effective therapeutic plasma concentrations. The drugs were classified into three risk groups using the two-dimensional map. This risk-categorization system showed high concordance with the torsadogenic information obtained by a public database CredibleMeds. Taken together, these results indicate that Cor.4U-CMs can be used for drug-induced proarrhythmia risk prediction. Copyright © 2018 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

Modeling α- and β-diversity in a tropical forest from remotely sensed and spatial data

NASA Astrophysics Data System (ADS)

Hernández-Stefanoni, J. Luis; Gallardo-Cruz, J. Alberto; Meave, Jorge A.; Rocchini, Duccio; Bello-Pineda, Javier; López-Martínez, J. Omar

2012-10-01

Comprehensive information on species distribution and species composition patterns of plant communities is required for effective conservation and management of biodiversity. Remote sensing offers an inexpensive means of attaining complete spatial coverage for large areas, at regular time intervals, and can therefore be extremely useful for estimating both species richness and spatial variation of species composition (α- and β-diversity). An essential step to map such attributes is to identify and understand their main drivers. We used remotely sensed data as a surrogate of plant productivity and habitat structure variables for explaining α- and β-diversity, and evaluated the relative roles of productivity-habitat structure and spatial variables in explaining observed patterns of α- and β-diversity by using a Principal Coordinates of Neighbor Matrices analysis. We also examined the relationship between remotely sensed and field data, in order to map α- and β-diversity at the landscape-level in the Yucatan Peninsula, using a regression kriging procedure. These two procedures integrate the relationship of species richness and spatial species turnover both with remotely sensed data and spatial structure. The empirical models so obtained can be used to predict species richness and variation in species composition, and they can be regarded as valuable tools not only for identifying areas with high local species richness (α-diversity), but also areas with high species turnover (β-diversity). Ultimately, information obtained in this way can help maximize the number of species preserved in a landscape.

Determinants and consequences of short birth interval in rural Bangladesh: a cross-sectional study.

PubMed

de Jonge, Hendrik C C; Azad, Kishwar; Seward, Nadine; Kuddus, Abdul; Shaha, Sanjit; Beard, James; Costello, Anthony; Houweling, Tanja A J; Fottrell, Ed

2014-12-24

Short birth intervals are known to have negative effects on pregnancy outcomes. We analysed data from a large population surveillance system in rural Bangladesh to identify predictors of short birth interval and determine consequences of short intervals on pregnancy outcomes. The study was conducted in three districts of Bangladesh - Bogra, Moulavibazar and Faridpur (population 282,643, 54,668 women of reproductive age). We used data between January 2010 and June 2011 from a key informant surveillance system that recorded all births, deaths and stillbirths. Short birth interval was defined as an interval between consecutive births of less than 33 months. Initially, risk factors of a short birth interval were determined using a multivariate mixed effects logistic regression model. Independent risk factors were selected using a priori knowledge from literature review. An adjusted mixed effects logistic regression model was then used to determine the effect of up to 21-, 21-32-, 33-44- and 45-month and higher birth-to-birth intervals on pregnancy outcomes controlling for confounders selected through a directed acyclic graph. We analysed 5,571 second or higher order deliveries. Average birth interval was 55 months and 1368/5571 women (24.6%) had a short birth interval (<33 months). Younger women (AOR 1.11 95% CI 1.08-1.15 per year increase in age), women who started their reproductive life later (AOR 0.95, 0.92-0.98 per year) and those who achieve higher order parities were less likely to experience short birth intervals (AOR 0.28, 0.19-0.41 parity 4 compared to 1). Women who were socioeconomically disadvantaged were more likely to experience a short birth interval (AOR 1.42, 1.22-1.65) and a previous adverse outcome was an important determinant of interval (AOR 2.10, 1.83-2.40). Very short birth intervals of less than 21 months were associated with increased stillbirth rate (AOR 2.13, 95% CI 1.28-3.53) and neonatal mortality (AOR 2.28 95% CI 1.28-4.05). Birth spacing remains a reproductive health problem in Bangladesh. Disadvantaged women are more likely to experience short birth intervals and to have increased perinatal deaths. Research into causal pathways and strategies to improve spacing between pregnancies should be intensified.

Genetics and fine mapping of a purple leaf gene, BoPr, in ornamental kale (Brassica oleracea L. var. acephala).

PubMed

Liu, Xiao-Ping; Gao, Bao-Zhen; Han, Feng-Qing; Fang, Zhi-Yuan; Yang, Li-Mei; Zhuang, Mu; Lv, Hong-Hao; Liu, Yu-Mei; Li, Zhan-Sheng; Cai, Cheng-Cheng; Yu, Hai-Long; Li, Zhi-Yuan; Zhang, Yang-Yong

2017-03-14

Due to its variegated and colorful leaves, ornamental kale (Brassica oleracea L. var. acephala) has become a popular ornamental plant. In this study, we report the fine mapping and analysis of a candidate purple leaf gene using a backcross population and an F 2 population derived from two parental lines: W1827 (with white leaves) and P1835 (with purple leaves). Genetic analysis indicated that the purple leaf trait is controlled by a single dominant gene, which we named BoPr. Using markers developed based on the reference genome '02-12', the BoPr gene was preliminarily mapped to a 280-kb interval of chromosome C09, with flanking markers M17 and BoID4714 at genetic distances of 4.3 cM and 1.5 cM, respectively. The recombination rate within this interval is almost 12 times higher than the usual level, which could be caused by assembly error for reference genome '02-12' at this interval. Primers were designed based on 'TO1000', another B. oleracea reference genome. Among the newly designed InDel markers, BRID485 and BRID490 were found to be the closest to BoPr, flanking the gene at genetic distances of 0.1 cM and 0.2 cM, respectively; the interval between the two markers is 44.8 kb (reference genome 'TO1000'). Seven annotated genes are located within the 44.8 kb genomic region, of which only Bo9g058630 shows high homology to AT5G42800 (dihydroflavonol reductase), which was identified as a candidate gene for BoPr. Blast analysis revealed that this 44.8 kb interval is located on an unanchored scaffold (Scaffold000035_P2) of '02-12', confirming the existence of assembly error at the interval between M17 and BoID4714 for reference genome '02-12'. This study identified a candidate gene for BoPr and lays a foundation for the cloning and functional analysis of this gene.

Geographic Distribution of Healthy Resources and Adverse Pregnancy Outcomes.

PubMed

Young, Christopher; Laurent, Olivier; Chung, Judith H; Wu, Jun

2016-08-01

Objective To determine the risk of gestational diabetes (GDM) and preeclampsia associated with various community resources. Methods An ecological study was performed in Los Angeles and Orange counties in California. Fast food restaurants, supermarkets, grocery stores, gyms, health clubs and green space were identified using Google © Maps Extractor and through the Southern California Association of Government. California Birth Certificate data was used to identify cases of GDM and preeclampsia. Unadjusted and adjusted risk ratios were calculated using negative binomial regression. Results There were 9692 cases of GDM and 6288 cases of preeclampsia corresponding to incidences of 2.5 and 1.4 % respectively. The adjusted risk of GDM was reduced in zip codes with greater concentration of grocery stores [relative risk (RR) 0.95, 95 % confidence interval (CI) 0.92-0.99] and supermarkets (RR 0.94, 95 % CI 0.90-0.98). There were no significant relationships between preeclampsia and the concentration of fast food restaurants, grocery store, supermarkets or the amount of green space. Conclusion The distribution of community resources has a significant association with the risk of developing GDM but not preeclampsia.

Genetic Regulation of Hypothalamic Cocaine and Amphetamine-Regulated Transcript (CART) in BxD Inbred Mice

PubMed Central

Hawks, Brian W.; Li, Wei; Garlow, Steven J.

2009-01-01

Cocaine-Amphetamine Regulated Transcript (CART) peptides are implicated in a wide range of behaviors including in the reinforcing properties of psychostimulants, feeding and energy balance and stress and anxiety responses. We conducted a complex trait analysis to examine natural variation in the regulation of CART transcript abundance (CARTta) in the hypothalamus. CART transcript abundance was measured in total hypothalamic RNA from 26 BxD recombinant inbred (RI) mouse strains and in the C57BL/6 (B6) and DBA/2J (D2) progenitor strains. The strain distribution pattern for CARTta was continuous across the RI panel, which is consistent with this being a quantitative trait. Marker regression and interval mapping revealed significant quantitative trait loci (QTL) on mouse chromosome 4 (around 58.2cM) and chromosome 11 (between 20–36cM) that influence CARTta and account for 31% of the between strain variance in this phenotype. There are numerous candidate genes and QTL in these chromosomal regions that may indicate shared genetic regulation between CART expression and other neurobiological processes referable to known actions of this neuropeptide. PMID:18199428

Low-flow frequency analyses for streams in west-central Florida

USGS Publications Warehouse

Hammett, K.M.

1985-01-01

The log-Pearson type III distribution was used for defining low-flow frequency at 116 continuous-record streamflow stations in west-central Florida. Frequency distributions were calculated for 1, 3, 7, 14, 30, 60, 90, 120, and 183 consecutive-day periods for recurrence intervals of 2, 5, 10, and 20 years. Discharge measurements at more than 100 low-flow partial-record stations and miscellaneous discharge-measurement stations were correlated with concurrent daily mean discharge at continuous-record stations. Estimates of the 7-day, 2-year; 7-day, 10-year; 30-day, 2-year; and 30-day, 10-year discharges were made for most of the low-flow partial-record and miscellaneous discharge-measurement stations based on those correlations. Multiple linear-regression analysis was used in an attempt to mathematically relate low-flow frequency data to basin characteristics. The resulting equations showed an apparent bias and were considered unsatisfactory for use in estimating low-flow characteristics. Maps of the 7-day, 10-year and 30-day, 10-year low flows are presented. Techniques that can be used to estimate low-flow characteristics at an ungaged site are also provided. (USGS)

Procedure for locating 10 km UTM grid on Alabama County general highway maps

NASA Technical Reports Server (NTRS)

Paludan, C. T. N.

1975-01-01

Each county highway map has a geographic grid of degrees and tens of minutes in both longitude and latitude in the margins and within the map as intersection crosses. These will be used to locate the universal transverse mercator (UTM) grid at 10 km intervals. Since the maps used may have stretched or shrunk in height and/or width, interpolation should be done between the 10 min intersections when possible. A table of UTM coordinates of 10 min intersections is required and included. In Alabama, all eastings are referred to a false easting of 500,000 m at 87 deg W longitude (central meridian, CM).

Mapping Soil pH Buffering Capacity of Selected Fields

NASA Technical Reports Server (NTRS)

Weaver, A. R.; Kissel, D. E.; Chen, F.; West, L. T.; Adkins, W.; Rickman, D.; Luvall, J. C.

2003-01-01

Soil pH buffering capacity, since it varies spatially within crop production fields, may be used to define sampling zones to assess lime requirement, or for modeling changes in soil pH when acid forming fertilizers or manures are added to a field. Our objective was to develop a procedure to map this soil property. One hundred thirty six soil samples (0 to 15 cm depth) from three Georgia Coastal Plain fields were titrated with calcium hydroxide to characterize differences in pH buffering capacity of the soils. Since the relationship between soil pH and added calcium hydroxide was approximately linear for all samples up to pH 6.5, the slope values of these linear relationships for all soils were regressed on the organic C and clay contents of the 136 soil samples using multiple linear regression. The equation that fit the data best was b (slope of pH vs. lime added) = 0.00029 - 0.00003 * % clay + 0.00135 * % O/C, r(exp 2) = 0.68. This equation was applied within geographic information system (GIS) software to create maps of soil pH buffering capacity for the three fields. When the mapped values of the pH buffering capacity were compared with measured values for a total of 18 locations in the three fields, there was good general agreement. A regression of directly measured pH buffering capacities on mapped pH buffering capacities at the field locations for these samples gave an r(exp 2) of 0.88 with a slope of 1.04 for a group of soils that varied approximately tenfold in their pH buffering capacities.

Learning-based subject-specific estimation of dynamic maps of cortical morphology at missing time points in longitudinal infant studies.

PubMed

Meng, Yu; Li, Gang; Gao, Yaozong; Lin, Weili; Shen, Dinggang

2016-11-01

Longitudinal neuroimaging analysis of the dynamic brain development in infants has received increasing attention recently. Many studies expect a complete longitudinal dataset in order to accurately chart the brain developmental trajectories. However, in practice, a large portion of subjects in longitudinal studies often have missing data at certain time points, due to various reasons such as the absence of scan or poor image quality. To make better use of these incomplete longitudinal data, in this paper, we propose a novel machine learning-based method to estimate the subject-specific, vertex-wise cortical morphological attributes at the missing time points in longitudinal infant studies. Specifically, we develop a customized regression forest, named dynamically assembled regression forest (DARF), as the core regression tool. DARF ensures the spatial smoothness of the estimated maps for vertex-wise cortical morphological attributes and also greatly reduces the computational cost. By employing a pairwise estimation followed by a joint refinement, our method is able to fully exploit the available information from both subjects with complete scans and subjects with missing scans for estimation of the missing cortical attribute maps. The proposed method has been applied to estimating the dynamic cortical thickness maps at missing time points in an incomplete longitudinal infant dataset, which includes 31 healthy infant subjects, each having up to five time points in the first postnatal year. The experimental results indicate that our proposed framework can accurately estimate the subject-specific vertex-wise cortical thickness maps at missing time points, with the average error less than 0.23 mm. Hum Brain Mapp 37:4129-4147, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Durbin-Watson partial least-squares regression applied to MIR data on adulteration with edible oils of different origins.

PubMed

Jović, Ozren

2016-12-15

A novel method for quantitative prediction and variable-selection on spectroscopic data, called Durbin-Watson partial least-squares regression (dwPLS), is proposed in this paper. The idea is to inspect serial correlation in infrared data that is known to consist of highly correlated neighbouring variables. The method selects only those variables whose intervals have a lower Durbin-Watson statistic (dw) than a certain optimal cutoff. For each interval, dw is calculated on a vector of regression coefficients. Adulteration of cold-pressed linseed oil (L), a well-known nutrient beneficial to health, is studied in this work by its being mixed with cheaper oils: rapeseed oil (R), sesame oil (Se) and sunflower oil (Su). The samples for each botanical origin of oil vary with respect to producer, content and geographic origin. The results obtained indicate that MIR-ATR, combined with dwPLS could be implemented to quantitative determination of edible-oil adulteration. Copyright © 2016 Elsevier Ltd. All rights reserved.

Energy expenditure estimation during daily military routine with body-fixed sensors.

PubMed

Wyss, Thomas; Mäder, Urs

2011-05-01

The purpose of this study was to develop and validate an algorithm for estimating energy expenditure during the daily military routine on the basis of data collected using body-fixed sensors. First, 8 volunteers completed isolated physical activities according to an established protocol, and the resulting data were used to develop activity-class-specific multiple linear regressions for physical activity energy expenditure on the basis of hip acceleration, heart rate, and body mass as independent variables. Second, the validity of these linear regressions was tested during the daily military routine using indirect calorimetry (n = 12). Volunteers' mean estimated energy expenditure did not significantly differ from the energy expenditure measured with indirect calorimetry (p = 0.898, 95% confidence interval = -1.97 to 1.75 kJ/min). We conclude that the developed activity-class-specific multiple linear regressions applied to the acceleration and heart rate data allow estimation of energy expenditure in 1-minute intervals during daily military routine, with accuracy equal to indirect calorimetry.

A baseline-free procedure for transformation models under interval censorship.

PubMed

Gu, Ming Gao; Sun, Liuquan; Zuo, Guoxin

2005-12-01

An important property of Cox regression model is that the estimation of regression parameters using the partial likelihood procedure does not depend on its baseline survival function. We call such a procedure baseline-free. Using marginal likelihood, we show that an baseline-free procedure can be derived for a class of general transformation models under interval censoring framework. The baseline-free procedure results a simplified and stable computation algorithm for some complicated and important semiparametric models, such as frailty models and heteroscedastic hazard/rank regression models, where the estimation procedures so far available involve estimation of the infinite dimensional baseline function. A detailed computational algorithm using Markov Chain Monte Carlo stochastic approximation is presented. The proposed procedure is demonstrated through extensive simulation studies, showing the validity of asymptotic consistency and normality. We also illustrate the procedure with a real data set from a study of breast cancer. A heuristic argument showing that the score function is a mean zero martingale is provided.

A fully traits-based approach to modeling global vegetation distribution.

PubMed

van Bodegom, Peter M; Douma, Jacob C; Verheijen, Lieneke M

2014-09-23

Dynamic Global Vegetation Models (DGVMs) are indispensable for our understanding of climate change impacts. The application of traits in DGVMs is increasingly refined. However, a comprehensive analysis of the direct impacts of trait variation on global vegetation distribution does not yet exist. Here, we present such analysis as proof of principle. We run regressions of trait observations for leaf mass per area, stem-specific density, and seed mass from a global database against multiple environmental drivers, making use of findings of global trait convergence. This analysis explained up to 52% of the global variation of traits. Global trait maps, generated by coupling the regression equations to gridded soil and climate maps, showed up to orders of magnitude variation in trait values. Subsequently, nine vegetation types were characterized by the trait combinations that they possess using Gaussian mixture density functions. The trait maps were input to these functions to determine global occurrence probabilities for each vegetation type. We prepared vegetation maps, assuming that the most probable (and thus, most suited) vegetation type at each location will be realized. This fully traits-based vegetation map predicted 42% of the observed vegetation distribution correctly. Our results indicate that a major proportion of the predictive ability of DGVMs with respect to vegetation distribution can be attained by three traits alone if traits like stem-specific density and seed mass are included. We envision that our traits-based approach, our observation-driven trait maps, and our vegetation maps may inspire a new generation of powerful traits-based DGVMs.

Low-flow characteristics of streams in Virginia

USGS Publications Warehouse

Hayes, Donald C.

1991-01-01

Streamflow data were collected and low-flow characteristics computed for 715 gaged sites in Virginia Annual minimum average 7-consecutive-day flows range from 0 to 2,195 cubic feet per second for a 2-year recurrence interval and from 0 to 1,423 cubic feet per second for a 10-year recurrence interval. Drainage areas range from 0.17 to 7,320 square miles. Existing and discontinued gaged sites are separated into three types: long-term continuous-record sites, short-term continuous-record sites, and partial-record sites. Low-flow characteristics for long-term continuous-record sites are determined from frequency curves of annual minimum average 7-consecutive-day flows . Low-flow characteristics for short-term continuous-record sites are estimated by relating daily mean base-flow discharge values at a short-term site to concurrent daily mean discharge values at nearby long-term continuous-record sites having similar basin characteristics . Low-flow characteristics for partial-record sites are estimated by relating base-flow measurements to daily mean discharge values at long-term continuous-record sites. Information from the continuous-record sites and partial-record sites in Virginia are used to develop two techniques for estimating low-flow characteristics at ungaged sites. A flow-routing method is developed to estimate low-flow values at ungaged sites on gaged streams. Regional regression equations are developed for estimating low-flow values at ungaged sites on ungaged streams. The flow-routing method consists of transferring low-flow characteristics from a gaged site, either upstream or downstream, to a desired ungaged site. A simple drainage-area proration is used to transfer values when there are no major tributaries between the gaged and ungaged sites. Standard errors of estimate for108 test sites are 19 percent of the mean for estimates of low-flow characteristics having a 2-year recurrence interval and 52 percent of the mean for estimates of low-flow characteristics having a 10-year recurrence interval . A more complex transfer method must be used when major tributaries enter the stream between the gaged and ungaged sites. Twenty-four stream networks are analyzed, and predictions are made for 84 sites. Standard errors of estimate are 15 percent of the mean for estimates of low-flow characteristics having a 2-year recurrence interval and 22 percent of the mean for estimates of low-flow characteristics having a 10-year recurrence interval. Regional regression equations were developed for estimating low-flow values at ungaged sites on ungaged streams. The State was divided into eight regions on the basis of physiography and geographic grouping of the residuals computed in regression analyses . Basin characteristics that were significant in the regression analysis were drainage area, rock type, and strip-mined area. Standard errors of prediction range from 60 to139 percent for estimates of low-flow characteristics having a 2-year recurrence interval and 90 percent to 172 percent for estimates of low-flow characteristics having a 10-year recurrence interval.

Marine Air Penetration: The Effect of Synoptic-scale Change on Regional Climate

NASA Astrophysics Data System (ADS)

Wang, M.; Ullrich, P. A.

2016-12-01

Marine air penetration (MAP) around the California San Francisco Bay Delta region has a pronounced impact on local temperature and air quality, and is highly correlated with inland wind penetration and hence wind power generation. Observational MAP criteria are defined based on the 900hPa across-shore wind speed greater than or equal to 3m/s at the Oakland radiosonde station, and a surface temperature difference greater than or equal to 7 degrees Celsius between two California Irrigation Management Information System (CIMIS) stations at Fresno, CA and Lodi, CA. This choice reflects marine cooling of Lodi, and was found to be highly correlated with inland specific humidity and breeze front activity. The observational MAP criteria were tuned based on small biases from Climate Forecast System Reanalysis (CFSR) to selected MAP days from CFSR, to identify synoptic-scale indicators associated with MAP events. A multivariate logistic regression model was constructed based on the selected five synoptic indicators from CFSR and demonstrated good model performance. Two synoptic-scale patterns were identified and analyzed out of the 32 categories from the regression model, suggesting a strong influence from the off-shore trough and the inland thermal ridge on MAP events. Future projection of MAP events included the 21st century Coupled Model Intercomparison Project Phase 5 (CMIP5), and Variable resolution in the Community Earth System Model (VR-CESM). Both showed no statistically significant trend associated with MAP events through the end of this century under both Representative Concentration Pathways (RCP) 2.6 and RCP 8.5.

Fine Mapping of QUICK ROOTING 1 and 2, Quantitative Trait Loci Increasing Root Length in Rice.

PubMed

Kitomi, Yuka; Nakao, Emari; Kawai, Sawako; Kanno, Noriko; Ando, Tsuyu; Fukuoka, Shuichi; Irie, Kenji; Uga, Yusaku

2018-02-02

The volume that the root system can occupy is associated with the efficiency of water and nutrient uptake from soil. Genetic improvement of root length, which is a limiting factor for root distribution, is necessary for increasing crop production. In this report, we describe identification of two quantitative trait loci (QTLs) for maximal root length, QUICK ROOTING 1 ( QRO1 ) on chromosome 2 and QRO2 on chromosome 6, in cultivated rice ( Oryza sativa L.). We measured the maximal root length in 26 lines carrying chromosome segments from the long-rooted upland rice cultivar Kinandang Patong in the genetic background of the short-rooted lowland cultivar IR64. Five lines had longer roots than IR64. By rough mapping of the target regions in BC 4 F 2 populations, we detected putative QTLs for maximal root length on chromosomes 2, 6, and 8. To fine-map these QTLs, we used BC 4 F 3 recombinant homozygous lines. QRO1 was mapped between markers RM5651 and RM6107, which delimit a 1.7-Mb interval on chromosome 2, and QRO2 was mapped between markers RM20495 and RM3430-1, which delimit an 884-kb interval on chromosome 6. Both QTLs may be promising gene resources for improving root system architecture in rice. Copyright © 2018 Kitomi et al.

Total body weight loss of ≥ 10 % is associated with improved hepatic fibrosis in patients with nonalcoholic steatohepatitis.

PubMed

Glass, Lisa M; Dickson, Rolland C; Anderson, Joseph C; Suriawinata, Arief A; Putra, Juan; Berk, Brian S; Toor, Arifa

2015-04-01

Given the rising epidemics of obesity and metabolic syndrome, nonalcoholic steatohepatitis (NASH) is now the most common cause of liver disease in the developed world. Effective treatment for NASH, either to reverse or prevent the progression of hepatic fibrosis, is currently lacking. To define the predictors associated with improved hepatic fibrosis in NASH patients undergoing serial liver biopsies at prolonged biopsy interval. This is a cohort study of 45 NASH patients undergoing serial liver biopsies for clinical monitoring in a tertiary care setting. Biopsies were scored using the NASH Clinical Research Network guidelines. Fibrosis regression was defined as improvement in fibrosis score ≥1 stage. Univariate analysis utilized Fisher's exact or Student's t test. Multivariate regression models determined independent predictors for regression of fibrosis. Forty-five NASH patients with biopsies collected at a mean interval of 4.6 years (±1.4) were included. The mean initial fibrosis stage was 1.96, two patients had cirrhosis and 12 patients (26.7 %) underwent bariatric surgery. There was a significantly higher rate of fibrosis regression among patients who lost ≥10 % total body weight (TBW) (63.2 vs. 9.1 %; p = 0.001) and who underwent bariatric surgery (47.4 vs. 4.5 %; p = 0.003). Factors such as age, gender, glucose intolerance, elevated ferritin, and A1AT heterozygosity did not influence fibrosis regression. On multivariate analysis, only weight loss of ≥10 % TBW predicted fibrosis regression [OR 8.14 (CI 1.08-61.17)]. Results indicate that regression of fibrosis in NASH is possible, even in advanced stages. Weight loss of ≥10 % TBW predicts fibrosis regression.

Comparing the performance of various digital soil mapping approaches to map physical soil properties

NASA Astrophysics Data System (ADS)

Laborczi, Annamária; Takács, Katalin; Pásztor, László

2015-04-01

Spatial information on physical soil properties is intensely expected, in order to support environmental related and land use management decisions. One of the most widely used properties to characterize soils physically is particle size distribution (PSD), which determines soil water management and cultivability. According to their size, different particles can be categorized as clay, silt, or sand. The size intervals are defined by national or international textural classification systems. The relative percentage of sand, silt, and clay in the soil constitutes textural classes, which are also specified miscellaneously in various national and/or specialty systems. The most commonly used is the classification system of the United States Department of Agriculture (USDA). Soil texture information is essential input data in meteorological, hydrological and agricultural prediction modelling. Although Hungary has a great deal of legacy soil maps and other relevant soil information, it often occurs, that maps do not exist on a certain characteristic with the required thematic and/or spatial representation. The recent developments in digital soil mapping (DSM), however, provide wide opportunities for the elaboration of object specific soil maps (OSSM) with predefined parameters (resolution, accuracy, reliability etc.). Due to the simultaneous richness of available Hungarian legacy soil data, spatial inference methods and auxiliary environmental information, there is a high versatility of possible approaches for the compilation of a given soil map. This suggests the opportunity of optimization. For the creation of an OSSM one might intend to identify the optimum set of soil data, method and auxiliary co-variables optimized for the resources (data costs, computation requirements etc.). We started comprehensive analysis of the effects of the various DSM components on the accuracy of the output maps on pilot areas. The aim of this study is to compare and evaluate different digital soil mapping methods and sets of ancillary variables for producing the most accurate spatial prediction of texture classes in a given area of interest. Both legacy and recently collected data on PSD were used as reference information. The predictor variable data set consisted of digital elevation model and its derivatives, lithology, land use maps as well as various bands and indices of satellite images. Two conceptionally different approaches can be applied in the mapping process. Textural classification can be realized after particle size data were spatially extended by proper geostatistical method. Alternatively, the textural classification is carried out first, followed by the spatial extension through suitable data mining method. According to the first approach, maps of sand, silt and clay percentage have been computed through regression kriging (RK). Since the three maps are compositional (their sum must be 100%), we applied Additive Log-Ratio (alr) transformation, instead of kriging them independently. Finally, the texture class map has been compiled according to the USDA categories from the three maps. Different combinations of reference and training soil data and auxiliary covariables resulted several different maps. On the basis of the other way, the PSD were classified firstly into the USDA categories, then the texture class maps were compiled directly by data mining methods (classification trees and random forests). The various results were compared to each other as well as to the RK maps. The performance of the different methods and data sets has been examined by testing the accuracy of the geostatistically computed and the directly classified results to assess the most predictive and accurate method. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Regression Analyses on the Butterfly Ballot Effect: A Statistical Perspective of the US 2000 Election

ERIC Educational Resources Information Center

Wu, Dane W.

2002-01-01

The year 2000 US presidential election between Al Gore and George Bush has been the most intriguing and controversial one in American history. The state of Florida was the trigger for the controversy, mainly, due to the use of the misleading "butterfly ballot". Using prediction (or confidence) intervals for least squares regression lines…

Advances in data processing for open-path Fourier transform infrared spectrometry of greenhouse gases.

PubMed

Shao, Limin; Griffiths, Peter R; Leytem, April B

2010-10-01

The automated quantification of three greenhouse gases, ammonia, methane, and nitrous oxide, in the vicinity of a large dairy farm by open-path Fourier transform infrared (OP/FT-IR) spectrometry at intervals of 5 min is demonstrated. Spectral pretreatment, including the automated detection and correction of the effect of interrupting the infrared beam, is by a moving object, and the automated correction for the nonlinear detector response is applied to the measured interferograms. Two ways of obtaining quantitative data from OP/FT-IR data are described. The first, which is installed in a recently acquired commercial OP/FT-IR spectrometer, is based on classical least-squares (CLS) regression, and the second is based on partial least-squares (PLS) regression. It is shown that CLS regression only gives accurate results if the absorption features of the analytes are located in very short spectral intervals where lines due to atmospheric water vapor are absent or very weak; of the three analytes examined, only ammonia fell into this category. On the other hand, PLS regression works allowed what appeared to be accurate results to be obtained for all three analytes.

Three-Dimensional Mapping of Soil Chemical Characteristics at Micrometric Scale by Combining 2D SEM-EDX Data and 3D X-Ray CT Images.

PubMed

Hapca, Simona; Baveye, Philippe C; Wilson, Clare; Lark, Richard Murray; Otten, Wilfred

2015-01-01

There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R2 value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented in this study can be easily adapted and applied to other types of data such as bacterial or fungal population densities for the 3D characterization of microbial distribution.

Three-Dimensional Mapping of Soil Chemical Characteristics at Micrometric Scale by Combining 2D SEM-EDX Data and 3D X-Ray CT Images

PubMed Central

Hapca, Simona; Baveye, Philippe C.; Wilson, Clare; Lark, Richard Murray; Otten, Wilfred

2015-01-01

There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R2 value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented in this study can be easily adapted and applied to other types of data such as bacterial or fungal population densities for the 3D characterization of microbial distribution. PMID:26372473

Atlas of depth-duration frequency of precipitation annual maxima for Texas

USGS Publications Warehouse

Asquith, William H.; Roussel, Meghan C.

2004-01-01

Ninety-six maps depicting the spatial variation of the depth-duration frequency of precipitation annual maxima for Texas are presented. The recurrence intervals represented are 2, 5, 10, 25, 50, 100, 250, and 500 years. The storm durations represented are 15 and 30 minutes; 1, 2, 3, 6, and 12 hours; and 1, 2, 3, 5, and 7 days. The maps were derived using geographically referenced parameter maps of probability distributions used in previously published research by the U.S. Geological Survey to model the magnitude and frequency of precipitation annual maxima for Texas. The maps in this report apply that research and update depth-duration frequency of precipitation maps available in earlier studies done by the National Weather Service.

Replication of long-bone length QTL in the F9-F10 LG,SM advanced intercross.

PubMed

Norgard, Elizabeth A; Jarvis, Joseph P; Roseman, Charles C; Maxwell, Taylor J; Kenney-Hunt, Jane P; Samocha, Kaitlin E; Pletscher, L Susan; Wang, Bing; Fawcett, Gloria L; Leatherwood, Christopher J; Wolf, Jason B; Cheverud, James M

2009-04-01

Quantitative trait locus (QTL) mapping techniques are frequently used to identify genomic regions associated with variation in phenotypes of interest. However, the F(2) intercross and congenic strain populations usually employed have limited genetic resolution resulting in relatively large confidence intervals that greatly inhibit functional confirmation of statistical results. Here we use the increased resolution of the combined F(9) and F(10) generations (n = 1455) of the LG,SM advanced intercross to fine-map previously identified QTL associated with the lengths of the humerus, ulna, femur, and tibia. We detected 81 QTL affecting long-bone lengths. Of these, 49 were previously identified in the combined F(2)-F(3) population of this intercross, while 32 represent novel contributors to trait variance. Pleiotropy analysis suggests that most QTL affect three to four long bones or serially homologous limb segments. We also identified 72 epistatic interactions involving 38 QTL and 88 novel regions. This analysis shows that using later generations of an advanced intercross greatly facilitates fine-mapping of confidence intervals, resolving three F(2)-F(3) QTL into multiple linked loci and narrowing confidence intervals of other loci, as well as allowing identification of additional QTL. Further characterization of the biological bases of these QTL will help provide a better understanding of the genetics of small variations in long-bone length.

An easy-to-use technique to characterize cardiodynamics from first-return maps on ΔRR-intervals

NASA Astrophysics Data System (ADS)

Fresnel, Emeline; Yacoub, Emad; Freitas, Ubiratan; Kerfourn, Adrien; Messager, Valérie; Mallet, Eric; Muir, Jean-François; Letellier, Christophe

2015-08-01

Heart rate variability analysis using 24-h Holter monitoring is frequently performed to assess the cardiovascular status of a patient. The present retrospective study is based on the beat-to-beat interval variations or ΔRR, which offer a better view of the underlying structures governing the cardiodynamics than the common RR-intervals. By investigating data for three groups of adults (with normal sinus rhythm, congestive heart failure, and atrial fibrillation, respectively), we showed that the first-return maps built on ΔRR can be classified according to three structures: (i) a moderate central disk, (ii) a reduced central disk with well-defined segments, and (iii) a large triangular shape. These three very different structures can be distinguished by computing a Shannon entropy based on a symbolic dynamics and an asymmetry coefficient, here introduced to quantify the balance between accelerations and decelerations in the cardiac rhythm. The probability P111111 of successive heart beats without large beat-to-beat fluctuations allows to assess the regularity of the cardiodynamics. A characteristic time scale, corresponding to the partition inducing the largest Shannon entropy, was also introduced to quantify the ability of the heart to modulate its rhythm: it was significantly different for the three structures of first-return maps. A blind validation was performed to validate the technique.

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PubMed

Kropat, Georg; Bochud, Francois; Jaboyedoff, Michel; Laedermann, Jean-Pascal; Murith, Christophe; Palacios Gruson, Martha; Baechler, Sébastien

2015-09-01

According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information. Copyright © 2015 Elsevier Ltd. All rights reserved.

High-resolution Mapping of Forest Carbon Stocks in the Colombian Amazon

NASA Astrophysics Data System (ADS)

Asner, G. P.; Clark, J. K.; Mascaro, J.; Galindo García, G. A.; Chadwick, K. D.; Navarrete Encinales, D. A.; Paez-Acosta, G.; Cabrera Montenegro, E.; Kennedy-Bowdoin, T.; Duque, Á.; Balaji, A.; von Hildebrand, P.; Maatoug, L.; Bernal, J. F. Phillips; Knapp, D. E.; García Dávila, M. C.; Jacobson, J.; Ordóñez, M. F.

2012-03-01

High-resolution mapping of tropical forest carbon stocks can assist forest management and improve implementation of large-scale carbon retention and enhancement programs. Previous high-resolution approaches have relied on field plot and/or Light Detection and Ranging (LiDAR) samples of aboveground carbon density, which are typically upscaled to larger geographic areas using stratification maps. Such efforts often rely on detailed vegetation maps to stratify the region for sampling, but existing tropical forest maps are often too coarse and field plots too sparse for high resolution carbon assessments. We developed a top-down approach for high-resolution carbon mapping in a 16.5 million ha region (>40 %) of the Colombian Amazon - a remote landscape seldom documented. We report on three advances for large-scale carbon mapping: (i) employing a universal approach to airborne LiDAR-calibration with limited field data; (ii) quantifying environmental controls over carbon densities; and (iii) developing stratification- and regression-based approaches for scaling up to regions outside of LiDAR coverage. We found that carbon stocks are predicted by a combination of satellite-derived elevation, fractional canopy cover and terrain ruggedness, allowing upscaling of the LiDAR samples to the full 16.5 million ha region. LiDAR-derived carbon mapping samples had 14.6 % uncertainty at 1 ha resolution, and regional maps based on stratification and regression approaches had 25.6 % and 29.6 % uncertainty, respectively, in any given hectare. High-resolution approaches with reported local-scale uncertainties will provide the most confidence for monitoring changes in tropical forest carbon stocks. Improved confidence will allow resource managers and decision-makers to more rapidly and effectively implement actions that better conserve and utilize forests in tropical regions.

A YAC contig encompassing the chromosome 7p locus for autosomal dominant retinitis pigmentosa

DOE Office of Scientific and Technical Information (OSTI.GOV)

Inglehearn, C.F.; Keen, T.J.; Ratel, R.

1994-09-01

Retinitis pigmentosa is an inherited retinal degeneration characterized by night blindness and loss of peripheral vision, often leading to complete blindness. The autosomal dominant form (adRP) maps to at least six different loci, including the rhodopsin and peripherin/Rds genes and four loci identified only by linkage analysis on chromosomes 7p, 7q, 8cen and 19q. The 7p locus was reported by this laboratory in a large English family, with a lod score of 16.5. Several new genetic markers have been tested in the family and this locus has now been refined to an interval of approximately 1 cM between markers D7S795more » and D7S484 in the 7p13-15 region. In order to clone the gene for adRP, we have used microsatellites and STSs from the region to identify over 80 YACs, from four different libraries, which map to this interval. End clones from key YACs were isolated for the generation of additional STSs. Eleven microsatellite markers between D7S435 (distal) and D7S484 (proximal) have been ordered by a combination of both physical and genetic mapping. In this way we have now obtained a YAC contig spanning approximately 3 megabases of chromosome 7p within which the adRP gene must lie. One gene (aquaporin) and one chromosome 7 brain EST have been placed on the contig but both map distal to the region of interest. Sixteen other ESTs and three further known 7p genes mapping in the region have been excluded. We are now attempting to build a cosmid contig in the defined interval and identify further expressed sequences from both YACs and cosmids to test as candidates for the adRP gene.« less

Floods of 1971 and 1972 on Glover Creek and Little River in southeastern Oklahoma

USGS Publications Warehouse

Thomas, Wilbert O.; Corley, Robert K.

1973-01-01

Heavy rains of December 9-10, 1971, and Oct. 30-31, 1972, caused outstanding floods on Glover Creek and Little River in McCurtain County in southeastern Oklahoma. This report presents hydrologic data that document the extent of flooding, flood profiles, and frequency of flooding on reaches of both streams. The data presented provide a technical basis for formulating effective flood-plain zoning that will minimize existing and future flood problems. The report also can be useful for locating waste-disposal and water-treatment facilities, and for the development of recreational areas. The area studied includes the reach of Little River on the Garvin and Idabel 7 1/2-minute quadrangles (sheet 1) and the reach of Glover Creek on the southwest quarter of the Golden 15-minute quadrangle (sheet 2). The flood boundaries delineated on the maps are the limits of flooding during the December 1971 and October 1972 floods. Any attempt to delineate the flood boundaries on streams in the study area other than Glover Creek and Little River was considered to be beyond the scope of this report. The general procedure used in defining the flood boundaries was to construct the flood profiles from high-water marks obtained by field surveys and by records at three stream-gaging stations (two on Little River and one on Glover Creek.). The extent of flooding was delineated on the topographic maps by using the flood profiles to define the flood elevations at various points along the channel and locating the elevations on the map by interpolating between contours (lines of equal ground elevation). In addition, flood boundaries were defined in places by field survey, aerial photographs, and information from local residents. The accuracy of the flood boundaries is consistent with the scale and contour interval of the maps (1 inch = 2,000 feet; contour interval 10 and 20 feet), which means the flood boundaries are drawn as accurately as possible on maps having 10- and 20-foot contour intervals.

The gene for pancreatic polypeptide (PPY) and the anonymous marker D17S78 are within 45 kb of each other on chromosome 17q21

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chandrasekharappa, S.C.; King, S.E.; Lee, Y.H.

1994-05-15

A gene for early-onset breast and ovarian cancer (BRCA1) has been localized to a small region of chromosome 17q21. A combination of genetic linkage studies, radiation-reduced hybrid analysis, and physical mapping by FISH has identified several genes/markers that lie in this interval. Among these are the gene encoding pancreatic polypeptide (PPY) and a polymorphic marker at locus D17S78. Efforts to construct a physical map of this region by isolating a large number of yeast artificial chromosome (YAC) and cosmid clones demonstrate that PPY and D17S78 are present within the same cosmid clone, and therefore no farther than 45 kb apart.more » This observation takes on particular significance since it excludes a recently described BRCA1 candidate gene from the interval defined by meiotic mapping. Although PPY and D17S78 were found to be no farther than 45 kb apart, identification of a smaller fragment that hybridizes to both probes would indicate that these two are much closer. The probe p131 and the gene PPY were previously mapped to 17q21-q23 and to the proximal long arm of chromosome 17, respectively. The demonstration of the close proximity of these markers should allow them to be treated as a single locus in terms of long-range genomic mapping of this region, and the genomic clones isolated should serve as useful resources for the identification of the BRCA1 gene. Analysis of a large number of a familial and spordic breast and ovarian cancers has identified frequent loss of heterozygosity near the BRCA1 locus. A recent report has suggested the responsible interval lies just telomeric to PPY, and a suggested candidate gene (MCD) for BRCA1 was found to be somatically rearranged in two of several hundred sporadic breast tumors.« less

Preliminary Geologic Map of the Big Pine Mountain Quadrangle, California

USGS Publications Warehouse

Vedder, J.G.; McLean, Hugh; Stanley, R.G.

1995-01-01

Reconnaissance geologic mapping of the San Rafael Primitive Area (now the San Rafael Wilderness) by Gower and others (1966) and Vedder an others (1967) showed s number of stratigraphic and structural ambiguities. To help resolve some of those problems, additional field work was done on parts of the Big Pine Moutain quadrangle during short intervals in 1981 and 1984, and 1990-1994.

Multinomial Logistic Regression Predicted Probability Map To Visualize The Influence Of Socio-Economic Factors On Breast Cancer Occurrence in Southern Karnataka

NASA Astrophysics Data System (ADS)

Madhu, B.; Ashok, N. C.; Balasubramanian, S.

2014-11-01

Multinomial logistic regression analysis was used to develop statistical model that can predict the probability of breast cancer in Southern Karnataka using the breast cancer occurrence data during 2007-2011. Independent socio-economic variables describing the breast cancer occurrence like age, education, occupation, parity, type of family, health insurance coverage, residential locality and socioeconomic status of each case was obtained. The models were developed as follows: i) Spatial visualization of the Urban- rural distribution of breast cancer cases that were obtained from the Bharat Hospital and Institute of Oncology. ii) Socio-economic risk factors describing the breast cancer occurrences were complied for each case. These data were then analysed using multinomial logistic regression analysis in a SPSS statistical software and relations between the occurrence of breast cancer across the socio-economic status and the influence of other socio-economic variables were evaluated and multinomial logistic regression models were constructed. iii) the model that best predicted the occurrence of breast cancer were identified. This multivariate logistic regression model has been entered into a geographic information system and maps showing the predicted probability of breast cancer occurrence in Southern Karnataka was created. This study demonstrates that Multinomial logistic regression is a valuable tool for developing models that predict the probability of breast cancer Occurrence in Southern Karnataka.

A Narrow Quantitative Trait Locus in C. elegans Coordinately Affects Longevity, Thermotolerance, and Resistance to Paraquat

PubMed Central

Vertino, Anthony; Ayyadevara, Srinivas; Thaden, John J.; Reis, Robert J. Shmookler

2011-01-01

By linkage mapping of quantitative trait loci, we previously identified at least 11 natural genetic variants that significantly modulate Caenorhabditis elegans life-span (LS), many of which would have eluded discovery by knock-down or mutation screens. A region on chromosome IV between markers stP13 and stP35 had striking effects on longevity in three inter-strain crosses (each P < 10−9). In order to define the limits of that interval, we have now constructed two independent lines by marker-based selection during 20 backcross generations, isolating the stP13–stP35 interval from strain Bergerac-BO in a CL2a background. These congenic lines differed significantly from CL2a in LS, assayed in two environments (each P < 0.001). We then screened for exchange of flanking markers to isolate recombinants that partition this region, because fine-mapping the boundaries for overlapping heteroallelic spans can greatly narrow the implicated interval. Recombinants carrying the CL2a allele at stP35 were consistently long-lived compared to those retaining the Bergerac-BO allele (P < 0.001), and more resistant to temperature elevation and paraquat (each ∼1.7-fold, P < 0.0001), but gained little protection from ultraviolet or peroxide stresses. Two rounds of recombinant screening, followed by fine-mapping of break-points and survival testing, narrowed the interval to 0.18 Mb (13.35–13.53 Mb) containing 26 putative genes and six small-nuclear RNAs – a manageable number of targets for functional assessment. PMID:22303358

Cultivar-Based Introgression Mapping Reveals Wild Species-Derived Pm-0, the Major Powdery Mildew Resistance Locus in Squash.

PubMed

Holdsworth, William L; LaPlant, Kyle E; Bell, Duane C; Jahn, Molly M; Mazourek, Michael

2016-01-01

Powdery mildew is a major fungal disease on squash and pumpkin (Cucurbita spp.) in the US and throughout the world. Genetic resistance to the disease is not known to occur naturally within Cucurbita pepo and only infrequently in Cucurbita moschata, but has been achieved in both species through the introgression of a major resistance gene from the wild species Cucurbita okeechobeensis subsp. martinezii. At present, this gene, Pm-0, is used extensively in breeding, and is found in nearly all powdery mildew-resistant C. pepo and C. moschata commercial cultivars. In this study, we mapped C. okeechobeensis subsp. martinezii-derived single nucleotide polymorphism (SNP) alleles in a set of taxonomically and morphologically diverse and resistant C. pepo and C. moschata cultivars bred at Cornell University that, by common possession of Pm-0, form a shared-trait introgression panel. High marker density was achieved using genotyping-by-sequencing, which yielded over 50,000 de novo SNP markers in each of the three Cucurbita species genotyped. A single 516.4 kb wild-derived introgression was present in all of the resistant cultivars and absent in a diverse set of heirlooms that predated the Pm-0 introgression. The contribution of this interval to powdery mildew resistance was confirmed by association mapping in a C. pepo cultivar panel that included the Cornell lines, heirlooms, and 68 additional C. pepo cultivars and with an independent F2 population derived from C. okeechobeensis subsp. martinezii x C. moschata. The interval was refined to a final candidate interval of 76.4 kb and CAPS markers were developed inside this interval to facilitate marker-assisted selection.

Cultivar-Based Introgression Mapping Reveals Wild Species-Derived Pm-0, the Major Powdery Mildew Resistance Locus in Squash

PubMed Central

Holdsworth, William L.; LaPlant, Kyle E.; Bell, Duane C.; Jahn, Molly M.; Mazourek, Michael

2016-01-01

Powdery mildew is a major fungal disease on squash and pumpkin (Cucurbita spp.) in the US and throughout the world. Genetic resistance to the disease is not known to occur naturally within Cucurbita pepo and only infrequently in Cucurbita moschata, but has been achieved in both species through the introgression of a major resistance gene from the wild species Cucurbita okeechobeensis subsp. martinezii. At present, this gene, Pm-0, is used extensively in breeding, and is found in nearly all powdery mildew-resistant C. pepo and C. moschata commercial cultivars. In this study, we mapped C. okeechobeensis subsp. martinezii-derived single nucleotide polymorphism (SNP) alleles in a set of taxonomically and morphologically diverse and resistant C. pepo and C. moschata cultivars bred at Cornell University that, by common possession of Pm-0, form a shared-trait introgression panel. High marker density was achieved using genotyping-by-sequencing, which yielded over 50,000 de novo SNP markers in each of the three Cucurbita species genotyped. A single 516.4 kb wild-derived introgression was present in all of the resistant cultivars and absent in a diverse set of heirlooms that predated the Pm-0 introgression. The contribution of this interval to powdery mildew resistance was confirmed by association mapping in a C. pepo cultivar panel that included the Cornell lines, heirlooms, and 68 additional C. pepo cultivars and with an independent F2 population derived from C. okeechobeensis subsp. martinezii x C. moschata. The interval was refined to a final candidate interval of 76.4 kb and CAPS markers were developed inside this interval to facilitate marker-assisted selection. PMID:27936008

The impact of change in albumin assay on reference intervals, prevalence of 'hypoalbuminaemia' and albumin prescriptions.

PubMed

Coley-Grant, Deon; Herbert, Mike; Cornes, Michael P; Barlow, Ian M; Ford, Clare; Gama, Rousseau

2016-01-01

We studied the impact on reference intervals, classification of patients with hypoalbuminaemia and albumin infusion prescriptions on changing from a bromocresol green (BCG) to a bromocresol purple (BCP) serum albumin assay. Passing-Bablok regression analysis and Bland-Altman plot were used to compare Abbott BCP and Roche BCG methods. Linear regression analysis was used to compare in-house and an external laboratory Abbott BCP serum albumin results. Reference intervals for Abbott BCP serum albumin were derived in two different laboratories using pathology data from adult patients in primary care. Prescriptions for 20% albumin infusions were compared one year before and one year after changing the albumin method. Abbott BCP assay had a negative bias of approximately 6 g/L compared with Roche BCG method.There was good agreement (y = 1.04 x - 1.03; R(2 )= 0.9933) between in-house and external laboratory Abbott BCP results. Reference intervals for the serum albumin Abbott BCP assay were 31-45 g/L, different to those recommended by Pathology Harmony and the manufacturers (35-50 g/L). Following the change in method there was a large increase in the number of patients classified as hypoalbuminaemic using Pathology Harmony references intervals (32%) but not when retrospectively compared to locally derived reference intervals (16%) compared with the previous year (12%). The method change was associated with a 44.6% increase in albumin prescriptions. This equated to an annual increase in expenditure of £35,234. We suggest that serum albumin reference intervals be method specific to prevent misclassification of albumin status in patients. Change in albumin methodology may have significant impact on hospital resources. © The Author(s) 2015.

Fifty-year flood-inundation maps for Comayagua, Hondura

USGS Publications Warehouse

Kresch, David L.; Mastin, Mark C.; Olsen, T.D.

2002-01-01

After the devastating floods caused by Hurricane Mitch in 1998, maps of the areas and depths of the 50-year-flood inundation at 15 municipalities in Honduras were prepared as a tool for agencies involved in reconstruction and planning. This report, which is one in a series of 15, presents maps of areas in the municipality of Comayagua that would be inundated by 50-year floods on Rio Humuya and Rio Majada. Geographic Information System (GIS) coverages of the flood inundation are available on a computer in the municipality of Comayagua as part of the Municipal GIS project and on the Internet at the Flood Hazard Mapping Web page (http://mitchnts1.cr.usgs.gov/projects/floodhazard.html). These coverages allow users to view the flood inundation in much more detail than is possible using the maps in this report. Water-surface elevations for 50-year-floods on Rio Humuya and Rio Majada at Comayagua were estimated using HEC-RAS, a one-dimensional, steady-flow, step-backwater computer program. The channel and floodplain cross sections used in HEC-RAS were developed from an airborne light-detection-and-ranging (LIDAR) topographic survey of the area. The 50-year-flood discharge for Rio Humuya at Comayagua, 1,400 cubic meters per second, was estimated using a regression equation that relates the 50-year-flood discharge to drainage area and mean annual precipitation. The reasonableness of the regression discharge was evaluated by comparing it with drainage-area-adjusted 50-year-flood discharges estimated for three long-term Rio Humuya stream-gaging stations. The drainage-area-adjusted 50-year-flood discharges estimated from the gage records ranged from 946 to 1,365 cubic meters per second. Because the regression equation discharge agrees closely with the high end of the range of discharges estimated from the gaging-station records, it was used for the hydraulic modeling to ensure that the resulting 50-year-flood water-surface elevations would not be underestimated. The 50-year-flood discharge for Rio Majada at Comayagua (230 cubic meters per second) was estimated using the regression equation because there are no long-term gaging-stations on this river from which to estimate the discharge.

Linkage map of the honey bee, Apis mellifera, based on RAPD markers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hunt, G.J.; Page, R.E. Jr.

A linkage map was constructed for the honey bee based on the segregation of 365 random amplified polymorphic DNA (RAPD) markers in haploid male progeny of a single female bee. The X locus for sex determination and genes for black body color and malate dehydrogenase were mapped to separate linkage groups. RAPD markers were very efficient for mapping, with an average of about 2.8 loci mapped for each 10-nucleotide primer that was used in polymerase chain reactions. The mean interval size between markers on the map was 9.1 cM. The map covered 3110 cM of linked markers on 26 linkagemore » groups. We estimate the total genome size to be {approximately}3450 cM. The size of the map indicated a very high recombination rate for the honey bee. The relationship of physical to genetic distance was estimated at 52 kb/cM, suggesting that map-based cloning of genes will be feasible for this species. 71 refs., 6 figs., 1 tab.« less

Caribou distribution during the post-calving period in relation to infrastructure in the Prudhoe Bay oil field, Alaska

USGS Publications Warehouse

Cronin, Matthew A.; Amstrup, Steven C.; Durner, George M.; Noel, Lynn E.; McDonald, Trent L.; Ballard, Warren B.

1998-01-01

There is concern that caribou (Rangifer tarandus) may avoid roads and facilities (i.e., infrastructure) in the Prudhoe Bay oil field (PBOF) in northern Alaska, and that this avoidance can have negative effects on the animals. We quantified the relationship between caribou distribution and PBOF infrastructure during the post-calving period (mid-June to mid-August) with aerial surveys from 1990 to 1995. We conducted four to eight surveys per year with complete coverage of the PBOF. We identified active oil field infrastructure and used a geographic information system (GIS) to construct ten 1 km wide concentric intervals surrounding the infrastructure. We tested whether caribou distribution is related to distance from infrastructure with a chi-squared habitat utilization-availability analysis and log-linear regression. We considered bulls, calves, and total caribou of all sex/age classes separately. The habitat utilization-availability analysis indicated there was no consistent trend of attraction to or avoidance of infrastructure. Caribou frequently were more abundant than expected in the intervals close to infrastructure, and this trend was more pronounced for bulls and for total caribou of all sex/age classes than for calves. Log-linear regression (with Poisson error structure) of numbers of caribou and distance from infrastructure were also done, with and without combining data into the 1 km distance intervals. The analysis without intervals revealed no relationship between caribou distribution and distance from oil field infrastructure, or between caribou distribution and Julian date, year, or distance from the Beaufort Sea coast. The log-linear regression with caribou combined into distance intervals showed the density of bulls and total caribou of all sex/age classes declined with distance from infrastructure. Our results indicate that during the post-calving period: 1) caribou distribution is largely unrelated to distance from infrastructure; 2) caribou regularly use habitats in the PBOF; 3) caribou often occur close to infrastructure; and 4) caribou do not appear to avoid oil field infrastructure.

Fine genetic mapping of the gene for nevoid basal cell carcinoma syndrome

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wicking, C.; Berkman, J.; Wainwright, B.

1994-08-01

Nevoid basal cell carcinoma syndrome (NBCCS, or Gorlin syndrome) is a cancer predisposition syndrome characterized by multiple basal cell carcinomas and diverse developmental defects. The gene responsible for NBCCS, which is most likely to be a tumor suppressor gene, has previously been mapped to 9q22.3-q31 in a 12-cM interval between the microsatellite marker loci D9S12.1 and D9S109. Combined multipoint and haplotype analyses of additional polymorphisms in this region in our collection of Australasian pedigrees have further refined the localization of the gene to between the markers D9S196 and D9S180, an interval reported to be approximately 2 cM. 27 refs., 4more » figs., 1 tab.« less

Evaluation of confidence intervals for a steady-state leaky aquifer model

USGS Publications Warehouse

Christensen, S.; Cooley, R.L.

1999-01-01

The fact that dependent variables of groundwater models are generally nonlinear functions of model parameters is shown to be a potentially significant factor in calculating accurate confidence intervals for both model parameters and functions of the parameters, such as the values of dependent variables calculated by the model. The Lagrangian method of Vecchia and Cooley [Vecchia, A.V. and Cooley, R.L., Water Resources Research, 1987, 23(7), 1237-1250] was used to calculate nonlinear Scheffe-type confidence intervals for the parameters and the simulated heads of a steady-state groundwater flow model covering 450 km2 of a leaky aquifer. The nonlinear confidence intervals are compared to corresponding linear intervals. As suggested by the significant nonlinearity of the regression model, linear confidence intervals are often not accurate. The commonly made assumption that widths of linear confidence intervals always underestimate the actual (nonlinear) widths was not correct. Results show that nonlinear effects can cause the nonlinear intervals to be asymmetric and either larger or smaller than the linear approximations. Prior information on transmissivities helps reduce the size of the confidence intervals, with the most notable effects occurring for the parameters on which there is prior information and for head values in parameter zones for which there is prior information on the parameters.The fact that dependent variables of groundwater models are generally nonlinear functions of model parameters is shown to be a potentially significant factor in calculating accurate confidence intervals for both model parameters and functions of the parameters, such as the values of dependent variables calculated by the model. The Lagrangian method of Vecchia and Cooley was used to calculate nonlinear Scheffe-type confidence intervals for the parameters and the simulated heads of a steady-state groundwater flow model covering 450 km2 of a leaky aquifer. The nonlinear confidence intervals are compared to corresponding linear intervals. As suggested by the significant nonlinearity of the regression model, linear confidence intervals are often not accurate. The commonly made assumption that widths of linear confidence intervals always underestimate the actual (nonlinear) widths was not correct. Results show that nonlinear effects can cause the nonlinear intervals to be asymmetric and either larger or smaller than the linear approximations. Prior information on transmissivities helps reduce the size of the confidence intervals, with the most notable effects occurring for the parameters on which there is prior information and for head values in parameter zones for which there is prior information on the parameters.

Linking in situ LAI and fine resolution remote sensing data to map reference LAI over cropland and grassland using geostatistical regression method

NASA Astrophysics Data System (ADS)

He, Yaqian; Bo, Yanchen; Chai, Leilei; Liu, Xiaolong; Li, Aihua

2016-08-01

Leaf Area Index (LAI) is an important parameter of vegetation structure. A number of moderate resolution LAI products have been produced in urgent need of large scale vegetation monitoring. High resolution LAI reference maps are necessary to validate these LAI products. This study used a geostatistical regression (GR) method to estimate LAI reference maps by linking in situ LAI and Landsat TM/ETM+ and SPOT-HRV data over two cropland and two grassland sites. To explore the discrepancies of employing different vegetation indices (VIs) on estimating LAI reference maps, this study established the GR models for different VIs, including difference vegetation index (DVI), normalized difference vegetation index (NDVI), and ratio vegetation index (RVI). To further assess the performance of the GR model, the results from the GR and Reduced Major Axis (RMA) models were compared. The results show that the performance of the GR model varies between the cropland and grassland sites. At the cropland sites, the GR model based on DVI provides the best estimation, while at the grassland sites, the GR model based on DVI performs poorly. Compared to the RMA model, the GR model improves the accuracy of reference LAI maps in terms of root mean square errors (RMSE) and bias.

Successful gas hydrate prospecting using 3D seismic - A case study for the Mt. Elbert prospect, Milne Point, North Slope Alaska

USGS Publications Warehouse

Inks, T.L.; Agena, W.F.

2008-01-01

In February 2007, the Mt. Elbert Prospect stratigraphic test well, Milne Point, North Slope Alaska encountered thick methane gas hydrate intervals, as predicted by 3D seismic interpretation and modeling. Methane gas hydrate-saturated sediment was found in two intervals, totaling more than 100 ft., identified and mapped based on seismic character and wavelet modeling.

An Investigation of the Standard Errors of Expected A Posteriori Ability Estimates.

ERIC Educational Resources Information Center

De Ayala, R. J.; And Others

Expected a posteriori has a number of advantages over maximum likelihood estimation or maximum a posteriori (MAP) estimation methods. These include ability estimates (thetas) for all response patterns, less regression towards the mean than MAP ability estimates, and a lower average squared error. R. D. Bock and R. J. Mislevy (1982) state that the…

Comparing Forest/Nonforest Classifications of Landsat TM Imagery for Stratifying FIA Estimates of Forest Land Area

Treesearch

Mark D. Nelson; Ronald E. McRoberts; Greg C. Liknes; Geoffrey R. Holden

2005-01-01

Landsat Thematic Mapper (TM) satellite imagery and Forest Inventory and Analysis (FIA) plot data were used to construct forest/nonforest maps of Mapping Zone 41, National Land Cover Dataset 2000 (NLCD 2000). Stratification approaches resulting from Maximum Likelihood, Fuzzy Convolution, Logistic Regression, and k-Nearest Neighbors classification/prediction methods were...

Regression and Geostatistical Techniques: Considerations and Observations from Experiences in NE-FIA

Treesearch

Rachel Riemann; Andrew Lister

2005-01-01

Maps of forest variables improve our understanding of the forest resource by allowing us to view and analyze it spatially. The USDA Forest Service's Northeastern Forest Inventory and Analysis unit (NE-FIA) has used geostatistical techniques, particularly stochastic simulation, to produce maps and spatial data sets of FIA variables. That work underscores the...

The effects of forest fragmentation on forest stand attributes

Treesearch

Ronald E. McRoberts; Greg C. Liknes

2002-01-01

For two study areas in Minnesota, USA, one heavily forested and one sparsely forested, maps of predicted proportion forest area were created using Landsat Thematic Mapper imagery, forest inventory plot data, and a logistic regression model. The maps were used to estimate quantitative indices of forest fragmentation. Correlations between the values of the indices and...

An application of quantile random forests for predictive mapping of forest attributes

Treesearch

E.A. Freeman; G.G. Moisen

2015-01-01

Increasingly, random forest models are used in predictive mapping of forest attributes. Traditional random forests output the mean prediction from the random trees. Quantile regression forests (QRF) is an extension of random forests developed by Nicolai Meinshausen that provides non-parametric estimates of the median predicted value as well as prediction quantiles. It...

The regression discontinuity design showed to be a valid alternative to a randomized controlled trial for estimating treatment effects.

PubMed

Maas, Iris L; Nolte, Sandra; Walter, Otto B; Berger, Thomas; Hautzinger, Martin; Hohagen, Fritz; Lutz, Wolfgang; Meyer, Björn; Schröder, Johanna; Späth, Christina; Klein, Jan Philipp; Moritz, Steffen; Rose, Matthias

2017-02-01

To compare treatment effect estimates obtained from a regression discontinuity (RD) design with results from an actual randomized controlled trial (RCT). Data from an RCT (EVIDENT), which studied the effect of an Internet intervention on depressive symptoms measured with the Patient Health Questionnaire (PHQ-9), were used to perform an RD analysis, in which treatment allocation was determined by a cutoff value at baseline (PHQ-9 = 10). A linear regression model was fitted to the data, selecting participants above the cutoff who had received the intervention (n = 317) and control participants below the cutoff (n = 187). Outcome was PHQ-9 sum score 12 weeks after baseline. Robustness of the effect estimate was studied; the estimate was compared with the RCT treatment effect. The final regression model showed a regression coefficient of -2.29 [95% confidence interval (CI): -3.72 to -.85] compared with a treatment effect found in the RCT of -1.57 (95% CI: -2.07 to -1.07). Although the estimates obtained from two designs are not equal, their confidence intervals overlap, suggesting that an RD design can be a valid alternative for RCTs. This finding is particularly important for situations where an RCT may not be feasible or ethical as is often the case in clinical research settings. Copyright © 2016 Elsevier Inc. All rights reserved.

Locally linear regression for pose-invariant face recognition.

PubMed

Chai, Xiujuan; Shan, Shiguang; Chen, Xilin; Gao, Wen

2007-07-01

The variation of facial appearance due to the viewpoint (/pose) degrades face recognition systems considerably, which is one of the bottlenecks in face recognition. One of the possible solutions is generating virtual frontal view from any given nonfrontal view to obtain a virtual gallery/probe face. Following this idea, this paper proposes a simple, but efficient, novel locally linear regression (LLR) method, which generates the virtual frontal view from a given nonfrontal face image. We first justify the basic assumption of the paper that there exists an approximate linear mapping between a nonfrontal face image and its frontal counterpart. Then, by formulating the estimation of the linear mapping as a prediction problem, we present the regression-based solution, i.e., globally linear regression. To improve the prediction accuracy in the case of coarse alignment, LLR is further proposed. In LLR, we first perform dense sampling in the nonfrontal face image to obtain many overlapped local patches. Then, the linear regression technique is applied to each small patch for the prediction of its virtual frontal patch. Through the combination of all these patches, the virtual frontal view is generated. The experimental results on the CMU PIE database show distinct advantage of the proposed method over Eigen light-field method.

Evaluation and prediction of shrub cover in coastal Oregon forests (USA)

Treesearch

Becky K. Kerns; Janet L. Ohmann

2004-01-01

We used data from regional forest inventories and research programs, coupled with mapped climatic and topographic information, to explore relationships and develop multiple linear regression (MLR) and regression tree models for total and deciduous shrub cover in the Oregon coastal province. Results from both types of models indicate that forest structure variables were...

Subpixel urban land cover estimation: comparing cubist, random forests, and support vector regression

Treesearch

Jeffrey T. Walton

2008-01-01

Three machine learning subpixel estimation methods (Cubist, Random Forests, and support vector regression) were applied to estimate urban cover. Urban forest canopy cover and impervious surface cover were estimated from Landsat-7 ETM+ imagery using a higher resolution cover map resampled to 30 m as training and reference data. Three different band combinations (...

Interval ridge regression (iRR) as a fast and robust method for quantitative prediction and variable selection applied to edible oil adulteration.

PubMed

Jović, Ozren; Smrečki, Neven; Popović, Zora

2016-04-01

A novel quantitative prediction and variable selection method called interval ridge regression (iRR) is studied in this work. The method is performed on six data sets of FTIR, two data sets of UV-vis and one data set of DSC. The obtained results show that models built with ridge regression on optimal variables selected with iRR significantly outperfom models built with ridge regression on all variables in both calibration (6 out of 9 cases) and validation (2 out of 9 cases). In this study, iRR is also compared with interval partial least squares regression (iPLS). iRR outperfomed iPLS in validation (insignificantly in 6 out of 9 cases and significantly in one out of 9 cases for p<0.05). Also, iRR can be a fast alternative to iPLS, especially in case of unknown degree of complexity of analyzed system, i.e. if upper limit of number of latent variables is not easily estimated for iPLS. Adulteration of hempseed (H) oil, a well known health beneficial nutrient, is studied in this work by mixing it with cheap and widely used oils such as soybean (So) oil, rapeseed (R) oil and sunflower (Su) oil. Binary mixture sets of hempseed oil with these three oils (HSo, HR and HSu) and a ternary mixture set of H oil, R oil and Su oil (HRSu) were considered. The obtained accuracy indicates that using iRR on FTIR and UV-vis data, each particular oil can be very successfully quantified (in all 8 cases RMSEP<1.2%). This means that FTIR-ATR coupled with iRR can very rapidly and effectively determine the level of adulteration in the adulterated hempseed oil (R(2)>0.99). Copyright © 2015 Elsevier B.V. All rights reserved.

Slow wave contraction frequency plateaus in the small intestine are composed of discrete waves of interval increase associated with dislocations.

PubMed

Parsons, Sean P; Huizinga, Jan D

2018-06-03

What is the central question of this study? What is the nature of slow wave driven contraction frequency gradients in the small intestine? What is the main finding and its importance? Frequency plateaus are composed of discrete waves of increased interval, each wave associated with a contraction dislocation. Smooth frequency gradients are generated by localised neural modulation of wave frequency, leading to functionally important wave turbulence. Both patterns are emergent properties of a network of coupled oscillators, the interstitial cells of Cajal. A gut-wide network of interstitial cells of Cajal (ICC) generate electrical oscillations (slow waves) that orchestrate waves of muscle contraction. In the small intestine there is a gradient in slow wave frequency from high at the duodenum to low at the terminal ileum. Time-averaged measurements of frequency have suggested either a smooth or stepped (plateaued) gradient. We measured individual contraction intervals from diameter maps of the mouse small intestine to create interval maps (IMaps). IMaps showed that each frequency plateau was composed of discrete waves of increased interval. Each interval wave originated at a terminating contraction wave, a "dislocation", at the plateau's proximal boundary. In a model chain of coupled phase oscillators, interval wave frequency increased as coupling decreased or as the natural frequency gradient or noise increased. Injuring the intestine at a proximal point to destroy coupling, suppressed distal steps which then reappeared with gap junction block by carbenoxolone. This lent further support to our previous hypothesis that lines of dislocations were fixed by points of low coupling strength. Dislocations induced by electrical field pulses in the intestine and by equivalent phase shift in the model, were associated with interval waves. When the enteric nervous system was active, IMaps showed a chaotic, turbulent pattern of interval change with no frequency steps or plateaus. This probably resulted from local, stochastic release of neurotransmitters. Plateaus, dislocations, interval waves and wave turbulence arise from a dynamic interplay between natural frequency and coupling in the ICC network. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Quantitative retrieving forest ecological parameters based on remote sensing in Liping County of China

NASA Astrophysics Data System (ADS)

Tian, Qingjiu; Chen, Jing M.; Zheng, Guang; Xia, Xueqi; Chen, Junying

2006-09-01

Forest ecosystem is an important component of terrestrial ecosystem and plays an important role in global changes. Aboveground biomass (AGB) of forest ecosystem is an important factor in global carbon cycle studies. The purpose of this study was to retrieve the yearly Net Primary Productivity (NPP) of forest from the 8-days-interval MODIS-LAI images of a year and produce a yearly NPP distribution map. The LAI, DBH (diameter at breast height), tree height, and tree age field were measured in different 80 plots for Chinese fir, Masson pine, bamboo, broadleaf, mix forest in Liping County. Based on the DEM image and Landsat TM images acquired on May 14th, 2000, the geometric correction and terrain correction were taken. In addition, the "6S"model was used to gain the surface reflectance image. Then the correlation between Leaf Area Index (LAI) and Reduced Simple Ratio (RSR) was built. Combined with the Landcover map, forest stand map, the LAI, aboveground biomass, tree age map were produced respectively. After that, the 8-days- interval LAI images of a year, meteorology data, soil data, forest stand image and Landcover image were inputted into the BEPS model to get the NPP spatial distribution. At last, the yearly NPP spatial distribution map with 30m spatial resolution was produced. The values in those forest ecological parameters distribution maps were quite consistent with those of field measurements. So it's possible, feasible and time-saving to estimate forest ecological parameters at a large scale by using remote sensing.

Flood profiles for lower Brooker Creek, west-central Florida

USGS Publications Warehouse

Murphy, W.R.

1978-01-01

Flood heights are computed for a range of recurrence intervals for a 12.6 mile reach of Brooker Creek, beginning at the mouth at Lake Tarpon. A Geological Survey step-backwater computer program, E431, was used in these analyses using: (1) Stream and valley cross-section geometry and roughness data; (2) Recurrence interval flood-peak discharges; (3) Recurrence interval starting elevations; (4) Gaging station stage-discharge relations. Flood heights may be plotted versus distance above stream mouth and connected to construct flood profiles. They may also be used to indicate areas of inundation on detailed topographic maps.

Re-evaluation of link between interpregnancy interval and adverse birth outcomes: retrospective cohort study matching two intervals per mother

PubMed Central

Pereira, Gavin; Jacoby, Peter; de Klerk, Nicholas; Stanley, Fiona J

2014-01-01

Objective To re-evaluate the causal effect of interpregnancy interval on adverse birth outcomes, on the basis that previous studies relying on between mother comparisons may have inadequately adjusted for confounding by maternal risk factors. Design Retrospective cohort study using conditional logistic regression (matching two intervals per mother so each mother acts as her own control) to model the incidence of adverse birth outcomes as a function of interpregnancy interval; additional unconditional logistic regression with adjustment for confounders enabled comparison with the unmatched design of previous studies. Setting Perth, Western Australia, 1980-2010. Participants 40 441 mothers who each delivered three liveborn singleton neonates. Main outcome measures Preterm birth (<37 weeks), small for gestational age birth (<10th centile of birth weight by sex and gestational age), and low birth weight (<2500 g). Results Within mother analysis of interpregnancy intervals indicated a much weaker effect of short intervals on the odds of preterm birth and low birth weight compared with estimates generated using a traditional between mother analysis. The traditional unmatched design estimated an adjusted odds ratio for an interpregnancy interval of 0-5 months (relative to the reference category of 18-23 months) of 1.41 (95% confidence interval 1.31 to 1.51) for preterm birth, 1.26 (1.15 to 1.37) for low birth weight, and 0.98 (0.92 to 1.06) for small for gestational age birth. In comparison, the matched design showed a much weaker effect of short interpregnancy interval on preterm birth (odds ratio 1.07, 0.86 to 1.34) and low birth weight (1.03, 0.79 to 1.34), and the effect for small for gestational age birth remained small (1.08, 0.87 to 1.34). Both the unmatched and matched models estimated a high odds of small for gestational age birth and low birth weight for long interpregnancy intervals (longer than 59 months), but the estimated effect of long interpregnancy intervals on the odds of preterm birth was much weaker in the matched model than in the unmatched model. Conclusion This study questions the causal effect of short interpregnancy intervals on adverse birth outcomes and points to the possibility of unmeasured or inadequately specified maternal factors in previous studies. PMID:25056260

Prediction of the distillation temperatures of crude oils using ¹H NMR and support vector regression with estimated confidence intervals.

PubMed

Filgueiras, Paulo R; Terra, Luciana A; Castro, Eustáquio V R; Oliveira, Lize M S L; Dias, Júlio C M; Poppi, Ronei J

2015-09-01

This paper aims to estimate the temperature equivalent to 10% (T10%), 50% (T50%) and 90% (T90%) of distilled volume in crude oils using (1)H NMR and support vector regression (SVR). Confidence intervals for the predicted values were calculated using a boosting-type ensemble method in a procedure called ensemble support vector regression (eSVR). The estimated confidence intervals obtained by eSVR were compared with previously accepted calculations from partial least squares (PLS) models and a boosting-type ensemble applied in the PLS method (ePLS). By using the proposed boosting strategy, it was possible to identify outliers in the T10% property dataset. The eSVR procedure improved the accuracy of the distillation temperature predictions in relation to standard PLS, ePLS and SVR. For T10%, a root mean square error of prediction (RMSEP) of 11.6°C was obtained in comparison with 15.6°C for PLS, 15.1°C for ePLS and 28.4°C for SVR. The RMSEPs for T50% were 24.2°C, 23.4°C, 22.8°C and 14.4°C for PLS, ePLS, SVR and eSVR, respectively. For T90%, the values of RMSEP were 39.0°C, 39.9°C and 39.9°C for PLS, ePLS, SVR and eSVR, respectively. The confidence intervals calculated by the proposed boosting methodology presented acceptable values for the three properties analyzed; however, they were lower than those calculated by the standard methodology for PLS. Copyright © 2015 Elsevier B.V. All rights reserved.

Mapping the Structure-Function Relationship in Glaucoma and Healthy Patients Measured with Spectralis OCT and Humphrey Perimetry

PubMed Central

Muñoz–Negrete, Francisco J.; Oblanca, Noelia; Rebolleda, Gema

2018-01-01

Purpose To study the structure-function relationship in glaucoma and healthy patients assessed with Spectralis OCT and Humphrey perimetry using new statistical approaches. Materials and Methods Eighty-five eyes were prospectively selected and divided into 2 groups: glaucoma (44) and healthy patients (41). Three different statistical approaches were carried out: (1) factor analysis of the threshold sensitivities (dB) (automated perimetry) and the macular thickness (μm) (Spectralis OCT), subsequently applying Pearson's correlation to the obtained regions, (2) nonparametric regression analysis relating the values in each pair of regions that showed significant correlation, and (3) nonparametric spatial regressions using three models designed for the purpose of this study. Results In the glaucoma group, a map that relates structural and functional damage was drawn. The strongest correlation with visual fields was observed in the peripheral nasal region of both superior and inferior hemigrids (r = 0.602 and r = 0.458, resp.). The estimated functions obtained with the nonparametric regressions provided the mean sensitivity that corresponds to each given macular thickness. These functions allowed for accurate characterization of the structure-function relationship. Conclusions Both maps and point-to-point functions obtained linking structure and function damage contribute to a better understanding of this relationship and may help in the future to improve glaucoma diagnosis. PMID:29850196

The slick hair coat locus maps to chromosome 20 in Senepol-derived cattle.

PubMed

Mariasegaram, M; Chase, C C; Chaparro, J X; Olson, T A; Brenneman, R A; Niedz, R P

2007-02-01

The ability to maintain normal temperatures during heat stress is an important attribute for cattle in the subtropics and tropics. Previous studies have shown that Senepol cattle and their crosses with Holstein, Charolais and Angus animals are as heat tolerant as Brahman cattle. This has been attributed to the slick hair coat of Senepol cattle, which is thought to be controlled by a single dominant gene. In this study, a genome scan using a DNA-pooling strategy indicated that the slick locus is most likely on bovine chromosome 20 (BTA20). Interval mapping confirmed the BTA20 assignment and refined the location of the locus. In total, 14 microsatellite markers were individually genotyped in two pedigrees consisting of slick and normal-haired cattle (n = 36), representing both dairy and beef breeds. The maximum LOD score was 9.4 for a 4.4-cM support interval between markers DIK2416 and BM4107. By using additional microsatellite markers in this region, and genotyping in six more pedigrees (n = 86), the slick locus was further localized to the DIK4835 - DIK2930 interval.

Recombination rate variation in mice from an isolated island.

PubMed

Wang, Richard J; Gray, Melissa M; Parmenter, Michelle D; Broman, Karl W; Payseur, Bret A

2017-01-01

Recombination rate is a heritable trait that varies among individuals. Despite the major impact of recombination rate on patterns of genetic diversity and the efficacy of selection, natural variation in this phenotype remains poorly characterized. We present a comparison of genetic maps, sampling 1212 meioses, from a unique population of wild house mice (Mus musculus domesticus) that recently colonized remote Gough Island. Crosses to a mainland reference strain (WSB/EiJ) reveal pervasive variation in recombination rate among Gough Island mice, including subchromosomal intervals spanning up to 28% of the genome. In spite of this high level of polymorphism, the genomewide recombination rate does not significantly vary. In general, we find that recombination rate varies more when measured in smaller genomic intervals. Using the current standard genetic map of the laboratory mouse to polarize intervals with divergent recombination rates, we infer that the majority of evolutionary change occurred in one of the two tested lines of Gough Island mice. Our results confirm that natural populations harbour a high level of recombination rate polymorphism and highlight the disparities in recombination rate evolution across genomic scales. © 2016 John Wiley & Sons Ltd.

Recombination rate variation in mice from an isolated island

PubMed Central

Wang, Richard J.; Gray, Melissa M.; Parmenter, Michelle D.; Broman, Karl W.; Payseur, Bret A.

2016-01-01

Recombination rate is a heritable trait that varies among individuals. Despite the major impact of recombination rate on patterns of genetic diversity and the efficacy of selection, natural variation in this phenotype remains poorly characterized. We present a comparison of genetic maps, sampling 1,212 meioses, from a unique population of wild house mice (Mus musculus domesticus) that recently colonized remote Gough Island. Crosses to a mainland reference strain (WSB/EiJ) reveal pervasive variation in recombination rate among Gough Island mice, including sub-chromosomal intervals spanning up to 28% of the genome. In spite of this high level of polymorphism, the genome-wide recombination rate does not significantly vary. In general, we find that recombination rate varies more when measured in smaller genomic intervals. Using the current standard genetic map of the laboratory mouse to polarize intervals with divergent recombination rates, we infer that the majority of evolutionary change occurred in one of the two tested lines of Gough Island mice. Our results confirm that natural populations harbor a high level of recombination rate polymorphism and highlight the disparities in recombination rate evolution across genomic scales. PMID:27864900

Mapping the spatio-temporal evolution of irrigation in the Coastal Plain of Georgia, USA

Treesearch

Marcus D. Williams; Christie M.S. Hawley; Marguerite Madden; J. Marshall Shepherd

2017-01-01

This study maps the spatial and temporal evolution of acres irrigated in the Coastal Plain of Georgia over a 38 year period. The goal of this analysis is to create a time-series of irrigated areas in the Coastal Plain of Georgia at a sub-county level. From 1976 through 2013, Landsat images were obtained and sampled at four year intervals to manually...

Identification of a key recombinant narrows the CADASIL gene region to 8 cM and argues against allelism of CADASIL and familial hemiplegic migraine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dichgans, M.; Mayer, M.; Straube, A.

1996-02-15

This article reports on new information regarding the genetic mapping of the human CADASIL gene region. Previously, the gene had been mapped to human chromosome 19q12. Using the identification of a chromosomal crossover, the region has been refined to an 8-cM interval. 11 refs., 2 figs., 1 tab.

Non-Markovianity of Gaussian Channels.

PubMed

Torre, G; Roga, W; Illuminati, F

2015-08-14

We introduce a necessary and sufficient criterion for the non-Markovianity of Gaussian quantum dynamical maps based on the violation of divisibility. The criterion is derived by defining a general vectorial representation of the covariance matrix which is then exploited to determine the condition for the complete positivity of partial maps associated with arbitrary time intervals. Such construction does not rely on the Choi-Jamiolkowski representation and does not require optimization over states.

Inter-Pregnancy Intervals and Maternal Morbidity: New Evidence from Rwanda.

PubMed

Habimana-Kabano, Ignace; Broekhuis, Annelet; Hooimeijer, Pieter

2015-09-01

The effects of short and long pregnancy intervals on maternal morbidity have hardly been investigated. This research analyses these effects using logistic regression in two steps. First, data from the Rwanda Demographic and Health Survey 2010 are used to study delivery referrals to District hospitals. Second, Kibagabaga District Hospital's maternity records are used to study the effect of inter-pregnancy intervals on maternal morbidity. The results show that both short and long intervals lead to higher odds of being referred because of pregnancy or delivery complications. Once admitted, short intervals were not associated with higher levels of maternal morbidity. Long intervals are associated with higher risks of third trimester bleeding, premature rupture of membrane and lower limb edema, while a higher age at conception is associated with lower risks. Poor women from rural areas and with limited health insurance are less often admitted to a hospital, which might bias the results.

Common y-intercept and single compound regressions of gas-particle partitioning data vs 1/T

NASA Astrophysics Data System (ADS)

Pankow, James F.

Confidence intervals are placed around the log Kp vs 1/ T correlation equations obtained using simple linear regressions (SLR) with the gas-particle partitioning data set of Yamasaki et al. [(1982) Env. Sci. Technol.16, 189-194]. The compounds and groups of compounds studied include the polycylic aromatic hydrocarbons phenanthrene + anthracene, me-phenanthrene + me-anthracene, fluoranthene, pyrene, benzo[ a]fluorene + benzo[ b]fluorene, chrysene + benz[ a]anthracene + triphenylene, benzo[ b]fluoranthene + benzo[ k]fluoranthene, and benzo[ a]pyrene + benzo[ e]pyrene (note: me = methyl). For any given compound, at equilibrium, the partition coefficient Kp equals ( F/ TSP)/ A where F is the particulate-matter associated concentration (ng m -3), A is the gas-phase concentration (ng m -3), and TSP is the concentration of particulate matter (μg m -3). At temperatures more than 10°C from the mean sampling temperature of 17°C, the confidence intervals are quite wide. Since theory predicts that similar compounds sorbing on the same particulate matter should possess very similar y-intercepts, the data set was also fitted using a special common y-intercept regression (CYIR). For most of the compounds, the CYIR equations fell inside of the SLR 95% confidence intervals. The CYIR y-intercept value is -18.48, and is reasonably close to the type of value that can be predicted for PAH compounds. The set of CYIR regression equations is probably more reliable than the set of SLR equations. For example, the CYIR-derived desorption enthalpies are much more highly correlated with vaporization enthalpies than are the SLR-derived desorption enthalpies. It is recommended that the CYIR approach be considered whenever analysing temperature-dependent gas-particle partitioning data.

A difference in systolic blood pressure between arms is a novel predictor of the development and progression of diabetic nephropathy in patients with type 2 diabetes.

PubMed

Okada, Hiroshi; Fukui, Michiaki; Tanaka, Muhei; Matsumoto, Shinobu; Iwase, Hiroya; Kobayashi, Kanae; Asano, Mai; Yamazaki, Masahiro; Hasegawa, Goji; Nakamura, Naoto

2013-10-01

Recent studies have suggested that a difference in systolic blood pressure (SBP) between arms is associated with both vascular disease and mortality. The aim of this study was to investigate the relationship between a difference in SBP between arms and change in urinary albumin excretion or development of albuminuria in patients with type 2 diabetes. We measured SBP in 408 consecutive patients with type 2 diabetes, and calculated a difference in SBP between arms. We performed follow-up study to assess change in urinary albumin excretion or development of albuminuria, mean interval of which was 4.6 ± 1.7 years. We then evaluated the relationship of a difference in SBP between arms to diabetic nephropathy using multiple regression analysis and multiple Cox regression model. Multiple regression analyses demonstrated that a difference in SBP between arms was independently associated with change in urinary albumin excretion (β = 0.1869, P = 0.0010). Adjusted Cox regression analyses demonstrated that a difference in SBP between arms was associated with an increased hazard of development of albuminuria; hazard ratio was 1.215 (95% confidence interval 1.077-1.376). Moreover, the risk of development of albuminuria was increased in patients with a difference in SBP of equal to or more than 10 mmHg between arms; hazard ratio was 4.168 (95% confidence interval 1.478-11.70). A difference in SBP between arms could be a novel predictor of the development and progression of diabetic nephropathy in patients with type 2 diabetes. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Relationship of nutrition and physical activity behaviors and fitness measures to academic performance for sixth graders in a midwest city school district.

PubMed

Edwards, Jane U; Mauch, Lois; Winkelman, Mark R

2011-02-01

To support curriculum and policy, a midwest city school district assessed the association of selected categories of nutrition and physical activity (NUTR/PA) behaviors, fitness measures, and body mass index (BMI) with academic performance (AP) for 800 sixth graders. Students completed an adapted Youth Risk Behavior Surveillance Survey (NUTR/PA behaviors), fitness assessments (mile run, curl-ups, push-ups, height, and weight) with results matched to standardized scores (Measures of Academic Progress [MAP]), meal price status, and gender. Differences in mean MAP scores (math and reading) were compared by selected categories of each variable utilizing 1-way analysis of variance. Associations were determined by stepwise multiple regression utilizing mean MAP scores (for math and for reading) as the dependent variable and NUTR/PA behaviors, fitness, and BMI categories as independent variables. Significance was set at α = 0.05. Higher MAP math scores were associated with NUTR (more milk and breakfast; less 100% fruit juice and sweetened beverages [SB]) and PA (increased vigorous PA and sports teams; reduced television), and fitness (higher mile run performance). Higher MAP reading scores were associated with NUTR (fewer SB) and PA (increased vigorous PA, reduced television). Regression analysis indicated about 11.1% of the variation in the mean MAP math scores and 6.7% of the mean MAP reading scores could be accounted for by selected NUTR/PA behaviors, fitness, meal price status, and gender. Many positive NUTR/PA behaviors and fitness measures were associated with higher MAP scores supporting the school district focus on healthy lifestyles. Additional factors, including meal price status and gender, contribute to AP. © 2011, Fargo Public School.

Nonlinear-regression flow model of the Gulf Coast aquifer systems in the south-central United States

USGS Publications Warehouse

Kuiper, L.K.

1994-01-01

A multiple-regression methodology was used to help answer questions concerning model reliability, and to calibrate a time-dependent variable-density ground-water flow model of the gulf coast aquifer systems in the south-central United States. More than 40 regression models with 2 to 31 regressions parameters are used and detailed results are presented for 12 of the models. More than 3,000 values for grid-element volume-averaged head and hydraulic conductivity are used for the regression model observations. Calculated prediction interval half widths, though perhaps inaccurate due to a lack of normality of the residuals, are the smallest for models with only four regression parameters. In addition, the root-mean weighted residual decreases very little with an increase in the number of regression parameters. The various models showed considerable overlap between the prediction inter- vals for shallow head and hydraulic conductivity. Approximate 95-percent prediction interval half widths for volume-averaged freshwater head exceed 108 feet; for volume-averaged base 10 logarithm hydraulic conductivity, they exceed 0.89. All of the models are unreliable for the prediction of head and ground-water flow in the deeper parts of the aquifer systems, including the amount of flow coming from the underlying geopressured zone. Truncating the domain of solution of one model to exclude that part of the system having a ground-water density greater than 1.005 grams per cubic centimeter or to exclude that part of the systems below a depth of 3,000 feet, and setting the density to that of freshwater does not appreciably change the results for head and ground-water flow, except for locations close to the truncation surface.

Interpregnancy Interval and Adverse Pregnancy Outcomes: An Analysis of Successive Pregnancies.

PubMed

Hanley, Gillian E; Hutcheon, Jennifer A; Kinniburgh, Brooke A; Lee, Lily

2017-03-01

To examine the association between interpregnancy interval and maternal-neonate health when matching women to their successive pregnancies to control for differences in maternal risk factors and compare these results with traditional unmatched designs. We conducted a retrospective cohort study of 38,178 women with three or more deliveries (two or greater interpregnancy intervals) between 2000 and 2015 in British Columbia, Canada. We examined interpregnancy interval (0-5, 6-11, 12-17, 18-23 [reference], 24-59, and 60 months or greater) in relation to neonatal outcomes (preterm birth [less than 37 weeks of gestation], small-for-gestational-age birth [less than the 10th centile], use of neonatal intensive care, low birth weight [less than 2,500 g]) and maternal outcomes (gestational diabetes, beginning the subsequent pregnancy obese [body mass index 30 or greater], and preeclampsia-eclampsia). We used conditional logistic regression to compare interpregnancy intervals within the same mother and unconditional (unmatched) logistic regression to enable comparison with prior research. Analyses using the traditional unmatched design showed significantly increased risks associated with short interpregnancy intervals (eg, there were 232 preterm births [12.8%] in 0-5 months compared with 501 [8.2%] in the 18-23 months reference group; adjusted odds ratio [OR] for preterm birth 1.53, 95% confidence interval [CI] 1.35-1.73). However, these risks were eliminated in within-woman matched analyses (adjusted OR for preterm birth 0.85, 95% CI 0.71-1.02). Matched results indicated that short interpregnancy intervals were significantly associated with increased risk of gestational diabetes (adjusted OR 1.35, 95% CI 1.02-1.80 for 0-5 months) and beginning the subsequent pregnancy obese (adjusted OR 1.61, 95% CI 1.05-2.45 for 0-5 months and adjusted OR 1.43, 95% CI 1.10-1.87 for 6-11 months). Previously reported associations between short interpregnancy intervals and adverse neonatal outcomes may not be causal. However, short interpregnancy interval is associated with increased risk of gestational diabetes and beginning a subsequent pregnancy obese.

Methods for estimating low-flow statistics for Massachusetts streams

USGS Publications Warehouse

Ries, Kernell G.; Friesz, Paul J.

2000-01-01

Methods and computer software are described in this report for determining flow duration, low-flow frequency statistics, and August median flows. These low-flow statistics can be estimated for unregulated streams in Massachusetts using different methods depending on whether the location of interest is at a streamgaging station, a low-flow partial-record station, or an ungaged site where no data are available. Low-flow statistics for streamgaging stations can be estimated using standard U.S. Geological Survey methods described in the report. The MOVE.1 mathematical method and a graphical correlation method can be used to estimate low-flow statistics for low-flow partial-record stations. The MOVE.1 method is recommended when the relation between measured flows at a partial-record station and daily mean flows at a nearby, hydrologically similar streamgaging station is linear, and the graphical method is recommended when the relation is curved. Equations are presented for computing the variance and equivalent years of record for estimates of low-flow statistics for low-flow partial-record stations when either a single or multiple index stations are used to determine the estimates. The drainage-area ratio method or regression equations can be used to estimate low-flow statistics for ungaged sites where no data are available. The drainage-area ratio method is generally as accurate as or more accurate than regression estimates when the drainage-area ratio for an ungaged site is between 0.3 and 1.5 times the drainage area of the index data-collection site. Regression equations were developed to estimate the natural, long-term 99-, 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, and 50-percent duration flows; the 7-day, 2-year and the 7-day, 10-year low flows; and the August median flow for ungaged sites in Massachusetts. Streamflow statistics and basin characteristics for 87 to 133 streamgaging stations and low-flow partial-record stations were used to develop the equations. The streamgaging stations had from 2 to 81 years of record, with a mean record length of 37 years. The low-flow partial-record stations had from 8 to 36 streamflow measurements, with a median of 14 measurements. All basin characteristics were determined from digital map data. The basin characteristics that were statistically significant in most of the final regression equations were drainage area, the area of stratified-drift deposits per unit of stream length plus 0.1, mean basin slope, and an indicator variable that was 0 in the eastern region and 1 in the western region of Massachusetts. The equations were developed by use of weighted-least-squares regression analyses, with weights assigned proportional to the years of record and inversely proportional to the variances of the streamflow statistics for the stations. Standard errors of prediction ranged from 70.7 to 17.5 percent for the equations to predict the 7-day, 10-year low flow and 50-percent duration flow, respectively. The equations are not applicable for use in the Southeast Coastal region of the State, or where basin characteristics for the selected ungaged site are outside the ranges of those for the stations used in the regression analyses. A World Wide Web application was developed that provides streamflow statistics for data collection stations from a data base and for ungaged sites by measuring the necessary basin characteristics for the site and solving the regression equations. Output provided by the Web application for ungaged sites includes a map of the drainage-basin boundary determined for the site, the measured basin characteristics, the estimated streamflow statistics, and 90-percent prediction intervals for the estimates. An equation is provided for combining regression and correlation estimates to obtain improved estimates of the streamflow statistics for low-flow partial-record stations. An equation is also provided for combining regression and drainage-area ratio estimates to obtain improved e

Earth before life.

PubMed

Marzban, Caren; Viswanathan, Raju; Yurtsever, Ulvi

2014-01-09

A recent study argued, based on data on functional genome size of major phyla, that there is evidence life may have originated significantly prior to the formation of the Earth. Here a more refined regression analysis is performed in which 1) measurement error is systematically taken into account, and 2) interval estimates (e.g., confidence or prediction intervals) are produced. It is shown that such models for which the interval estimate for the time origin of the genome includes the age of the Earth are consistent with observed data. The appearance of life after the formation of the Earth is consistent with the data set under examination.

[Association of cardiovascular autonomic neuropathy and prolonged QT interval with cardiovascular morbidity and mortality in patients with type 2 diabetes mellitus].

PubMed

Ticse Aguirre, Ray; Villena, Jaime E

2011-03-01

In order to evaluate the relationship between cardiovascular autonomic neuropathy and corrected QT interval (QTc) with cardiovascular morbidity and mortality in patients with type 2 diabetes mellitus, we followed up for 5 years 67 patients attending the outpatient Endocrinology Service. 82% completed follow-up and cardiovascular events occurred in 16 patients. We found that long QTc interval was the only variable significantly associated with cardiovascular morbidity and mortality in the multiple logistic regression analysis (RR: 13.56, 95% CI: 2.01-91.36) (p = 0.0074).

Mapping mesoscale variability of the Azores Current using TOPEX/POSEIDON and ERS 1 altimetry, together with hydrographic and Lagrangian measurements

NASA Astrophysics Data System (ADS)

Hernandez, Fabrice; Le Traon, Pierre-Yves; Morrow, Rosemary

1995-12-01

The SEMAPHORE mesoscale air/sea experiment was conducted in the Azores-Madeira region from July to November 1993. TOPEX/POSEIDON (T/P) and ERS 1 were flying simultaneously at that time. The main purposes of this paper are to evaluate the estimation of the oceanic mesoscale circulation from the two different sets of altimetric data (T/P and ERS 1) and to compare the results with in situ measurements provided by the SEMAPHORE hydrographic surveys and surface drifters (three expendable bathytermograph conductivity-temperature-depth surveys in a 500-km2 box and a set of 47 Lagrangian surface drifters drogued at 150 m). Comparisons are carried out through the maps obtained by objective analysis from the four data sets. The mapping accuracy of T/P, ERS 1, T/P and ERS 1 combined, and in situ data is investigated, as well as the sensitivity of the mapping to the correlation functions used. There is a good qualitative agreement between altimetric maps and corresponding drifter and hydrographic maps for the three hydrographic surveys. Correlations are about 0.8, and the regression fit is about 0.6-0.7; the lower values are due to the smooth climatology used to reference the altimetric maps. The correlation for time differences is better, with regression lines not significantly different from 1, especially when ERS 1 and T/P are combined. T/P mapping is almost as good as ERS 1 mapping, which was rather unexpected since the ERS 1 space-time sampling is better suited for the mesoscale. This may reflect the fact that the signal mapped by the hydrography and drifters does not contain the high frequency/wavenumber components. T/P and ERS 1 combined provide better results, although the improvement is not as large as expected, probably for the same reason.

Lunar Silicon Abundance determined by Kaguya Gamma-ray Spectrometer and Chandrayaan-1 Moon Mineralogy Mapper

NASA Astrophysics Data System (ADS)

Kim, Kyeong; Berezhnoy, Alexey; Wöhler, Christian; Grumpe, Arne; Rodriguez, Alexis; Hasebe, Nobuyuki; Van Gasselt, Stephan

2016-07-01

Using Kaguya GRS data, we investigated Si distribution on the Moon, based on study of the 4934 keV Si gamma ray peak caused by interaction between thermal neutrons and lunar Si-28 atoms. A Si peak analysis for a grid of 10 degrees in longitude and latitude was accomplished by the IRAP Aquarius program followed by a correction for altitude and thermal neutron density. A spectral parameter based regression model of the Si distribution was built for latitudes between 60°S and 60°N based on the continuum slopes, band depths, widths and minimum wavelengths of the absorption bands near 1 μμm and 2 μμm. Based on these regression models a nearly global cpm (counts per minute) map of Si with a resolution of 20 pixels per degree was constructed. The construction of a nearly global map of lunar Si abundances has been achieved by a combination of regression-based analysis of KGRS cpm data and M ^{3} spectral reflectance data, it has been calibrated with respect to returned sample-based wt% values. The Si abundances estimated with our method systematically exceed those of the LP GRS Si data set but are consistent with typical Si abundances of lunar basalt samples (in the maria) and feldspathic mineral samples (in the highlands). Our Si map shows that the Si abundance values on the Moon are typically between 17 and 28 wt%. The obtained Si map will provide an important aspect in both understanding the distribution of minerals and the evolution of the lunar surface since its formation.

Sodium Velocity Maps on Mercury

NASA Technical Reports Server (NTRS)

Potter, A. E.; Killen, R. M.

2011-01-01

The objective of the current work was to measure two-dimensional maps of sodium velocities on the Mercury surface and examine the maps for evidence of sources or sinks of sodium on the surface. The McMath-Pierce Solar Telescope and the Stellar Spectrograph were used to measure Mercury spectra that were sampled at 7 milliAngstrom intervals. Observations were made each day during the period October 5-9, 2010. The dawn terminator was in view during that time. The velocity shift of the centroid of the Mercury emission line was measured relative to the solar sodium Fraunhofer line corrected for radial velocity of the Earth. The difference between the observed and calculated velocity shift was taken to be the velocity vector of the sodium relative to Earth. For each position of the spectrograph slit, a line of velocities across the planet was measured. Then, the spectrograph slit was stepped over the surface of Mercury at 1 arc second intervals. The position of Mercury was stabilized by an adaptive optics system. The collection of lines were assembled into an images of surface reflection, sodium emission intensities, and Earthward velocities over the surface of Mercury. The velocity map shows patches of higher velocity in the southern hemisphere, suggesting the existence of sodium sources there. The peak earthward velocity occurs in the equatorial region, and extends to the terminator. Since this was a dawn terminator, this might be an indication of dawn evaporation of sodium. Leblanc et al. (2008) have published a velocity map that is similar.

Automated mapping of the ocean floor using the theory of intrinsic random functions of order k

USGS Publications Warehouse

David, M.; Crozel, D.; Robb, James M.

1986-01-01

High-quality contour maps can be computer drawn from single track echo-sounding data by combining Universal Kriging and the theory of intrinsic random function of order K (IRFK). These methods interpolate values among the closely spaced points that lie along relatively widely spaced lines. The technique provides a variance which can be contoured as a quantitative measure of map precision. The technique can be used to evaluate alternative survey trackline configurations and data collection intervals, and can be applied to other types of oceanographic data. ?? 1986 D. Reidel Publishing Company.

Assessing the Effects of Forest Fragmentation Using Satellite Imagery and Forest Inventory Data

Treesearch

Ronald E. McRoberts; Greg C. Liknes

2005-01-01

For a study area in the North Central region of the USA, maps of predicted proportion forest area were created using Landsat Thematic Mapper imagery, forest inventory plot data, and a logistic regression model. The maps were used to estimate quantitative indices of forest fragmentation. Correlations between the values of the indices and forest attributes observed on...

Lithologic mapping of silicate rocks using TIMS

NASA Technical Reports Server (NTRS)

Gillespie, A. R.

1986-01-01

Common rock-forming minerals have thermal infrared spectral features that are measured in the laboratory to infer composition. An airborne Daedalus scanner (TIMS) that collects six channels of thermal infrared radiance data (8 to 12 microns), may be used to measure these same features for rock identification. Previously, false-color composite pictures made from channels 1, 3, and 5 and emittance spectra for small areas on these images were used to make lithologic maps. Central wavelength, standard deviation, and amplitude of normal curves regressed on the emittance spectra are related to compositional information for crystalline igneous silicate rocks. As expected, the central wavelength varies systematically with silica content and with modal quartz content. Standard deviation is less sensitive to compositional changes, but large values may result from mixed admixture of vegetation. Compression of the six TIMS channels to three image channels made from the regressed parameters may be effective in improving geologic mapping from TIMS data, and these synthetic images may form a basis for the remote assessment of rock composition.

Analysis of the quality of image data acquired by the LANDSAT-4 Thematic Mapper and Multispectral Scanners

NASA Technical Reports Server (NTRS)

Colwell, R. N. (Principal Investigator)

1984-01-01

The geometric quality of TM film and digital products is evaluated by making selective photomeasurements and by measuring the coordinates of known features on both the TM products and map products. These paired observations are related using a standard linear least squares regression approach. Using regression equations and coefficients developed from 225 (TM film product) and 20 (TM digital product) control points, map coordinates of test points are predicted. The residual error vectors and analysis of variance (ANOVA) were performed on the east and north residual using nine image segments (blocks) as treatments. Based on the root mean square error of the 223 (TM film product) and 22 (TM digital product) test points, users of TM data expect the planimetric accuracy of mapped points to be within 91 meters and within 117 meters for the film products, and to be within 12 meters and within 14 meters for the digital products.

Using the Quantile Mapping to improve a weather generator

NASA Astrophysics Data System (ADS)

Chen, Y.; Themessl, M.; Gobiet, A.

2012-04-01

We developed a weather generator (WG) by using statistical and stochastic methods, among them are quantile mapping (QM), Monte-Carlo, auto-regression, empirical orthogonal function (EOF). One of the important steps in the WG is using QM, through which all the variables, no matter what distribution they originally are, are transformed into normal distributed variables. Therefore, the WG can work on normally distributed variables, which greatly facilitates the treatment of random numbers in the WG. Monte-Carlo and auto-regression are used to generate the realization; EOFs are employed for preserving spatial relationships and the relationships between different meteorological variables. We have established a complete model named WGQM (weather generator and quantile mapping), which can be applied flexibly to generate daily or hourly time series. For example, with 30-year daily (hourly) data and 100-year monthly (daily) data as input, the 100-year daily (hourly) data would be relatively reasonably produced. Some evaluation experiments with WGQM have been carried out in the area of Austria and the evaluation results will be presented.

Developing Empirical Lightning Cessation Forecast Guidance for the Cape Canaveral Air Force Station and Kennedy Space Center

NASA Technical Reports Server (NTRS)

Stano, Geoffrey T.; Fuelberg, Henry E.; Roeder, William P.

2010-01-01

This research addresses the 45th Weather Squadron's (45WS) need for improved guidance regarding lightning cessation at Cape Canaveral Air Force Station and Kennedy Space Center (KSC). KSC's Lightning Detection and Ranging (LDAR) network was the primary observational tool to investigate both cloud-to-ground and intracloud lightning. Five statistical and empirical schemes were created from LDAR, sounding, and radar parameters derived from 116 storms. Four of the five schemes were unsuitable for operational use since lightning advisories would be canceled prematurely, leading to safety risks to personnel. These include a correlation and regression tree analysis, three variants of multiple linear regression, event time trending, and the time delay between the greatest height of the maximum dBZ value to the last flash. These schemes failed to adequately forecast the maximum interval, the greatest time between any two flashes in the storm. The majority of storms had a maximum interval less than 10 min, which biased the schemes toward small values. Success was achieved with the percentile method (PM) by separating the maximum interval into percentiles for the 100 dependent storms.

Modeling stream fish distributions using interval-censored detection times.

PubMed

Ferreira, Mário; Filipe, Ana Filipa; Bardos, David C; Magalhães, Maria Filomena; Beja, Pedro

2016-08-01

Controlling for imperfect detection is important for developing species distribution models (SDMs). Occupancy-detection models based on the time needed to detect a species can be used to address this problem, but this is hindered when times to detection are not known precisely. Here, we extend the time-to-detection model to deal with detections recorded in time intervals and illustrate the method using a case study on stream fish distribution modeling. We collected electrofishing samples of six fish species across a Mediterranean watershed in Northeast Portugal. Based on a Bayesian hierarchical framework, we modeled the probability of water presence in stream channels, and the probability of species occupancy conditional on water presence, in relation to environmental and spatial variables. We also modeled time-to-first detection conditional on occupancy in relation to local factors, using modified interval-censored exponential survival models. Posterior distributions of occupancy probabilities derived from the models were used to produce species distribution maps. Simulations indicated that the modified time-to-detection model provided unbiased parameter estimates despite interval-censoring. There was a tendency for spatial variation in detection rates to be primarily influenced by depth and, to a lesser extent, stream width. Species occupancies were consistently affected by stream order, elevation, and annual precipitation. Bayesian P-values and AUCs indicated that all models had adequate fit and high discrimination ability, respectively. Mapping of predicted occupancy probabilities showed widespread distribution by most species, but uncertainty was generally higher in tributaries and upper reaches. The interval-censored time-to-detection model provides a practical solution to model occupancy-detection when detections are recorded in time intervals. This modeling framework is useful for developing SDMs while controlling for variation in detection rates, as it uses simple data that can be readily collected by field ecologists.

Impact of Risk Factors on Different Interval Cancer Subtypes in a Population-Based Breast Cancer Screening Programme

PubMed Central

Blanch, Jordi; Sala, Maria; Ibáñez, Josefa; Domingo, Laia; Fernandez, Belén; Otegi, Arantza; Barata, Teresa; Zubizarreta, Raquel; Ferrer, Joana; Castells, Xavier; Rué, Montserrat; Salas, Dolores

2014-01-01

Background Interval cancers are primary breast cancers diagnosed in women after a negative screening test and before the next screening invitation. Our aim was to evaluate risk factors for interval cancer and their subtypes and to compare the risk factors identified with those associated with incident screen-detected cancers. Methods We analyzed data from 645,764 women participating in the Spanish breast cancer screening program from 2000–2006 and followed-up until 2009. A total of 5,309 screen-detected and 1,653 interval cancers were diagnosed. Among the latter, 1,012 could be classified on the basis of findings in screening and diagnostic mammograms, consisting of 489 true interval cancers (48.2%), 235 false-negatives (23.2%), 172 minimal-signs (17.2%) and 114 occult tumors (11.3%). Information on the screening protocol and women's characteristics were obtained from the screening program registry. Cause-specific Cox regression models were used to estimate the hazard ratios (HR) of risks factors for interval cancer and incident screen-detected cancer. A multinomial regression model, using screen-detected tumors as a reference group, was used to assess the effect of breast density and other factors on the occurrence of interval cancer subtypes. Results A previous false-positive was the main risk factor for interval cancer (HR = 2.71, 95%CI: 2.28–3.23); this risk was higher for false-negatives (HR = 8.79, 95%CI: 6.24–12.40) than for true interval cancer (HR = 2.26, 95%CI: 1.59–3.21). A family history of breast cancer was associated with true intervals (HR = 2.11, 95%CI: 1.60–2.78), previous benign biopsy with a false-negatives (HR = 1.83, 95%CI: 1.23–2.71). High breast density was mainly associated with occult tumors (RRR = 4.92, 95%CI: 2.58–9.38), followed by true intervals (RRR = 1.67, 95%CI: 1.18–2.36) and false-negatives (RRR = 1.58, 95%CI: 1.00–2.49). Conclusion The role of women's characteristics differs among interval cancer subtypes. This information could be useful to improve effectiveness of breast cancer screening programmes and to better classify subgroups of women with different risks of developing cancer. PMID:25333936

Non-Parametric Blur Map Regression for Depth of Field Extension.

PubMed

D'Andres, Laurent; Salvador, Jordi; Kochale, Axel; Susstrunk, Sabine

2016-04-01

Real camera systems have a limited depth of field (DOF) which may cause an image to be degraded due to visible misfocus or too shallow DOF. In this paper, we present a blind deblurring pipeline able to restore such images by slightly extending their DOF and recovering sharpness in regions slightly out of focus. To address this severely ill-posed problem, our algorithm relies first on the estimation of the spatially varying defocus blur. Drawing on local frequency image features, a machine learning approach based on the recently introduced regression tree fields is used to train a model able to regress a coherent defocus blur map of the image, labeling each pixel by the scale of a defocus point spread function. A non-blind spatially varying deblurring algorithm is then used to properly extend the DOF of the image. The good performance of our algorithm is assessed both quantitatively, using realistic ground truth data obtained with a novel approach based on a plenoptic camera, and qualitatively with real images.

Linkage mapping of beta 2 EEG waves via non-parametric regression.

PubMed

Ghosh, Saurabh; Begleiter, Henri; Porjesz, Bernice; Chorlian, David B; Edenberg, Howard J; Foroud, Tatiana; Goate, Alison; Reich, Theodore

2003-04-01

Parametric linkage methods for analyzing quantitative trait loci are sensitive to violations in trait distributional assumptions. Non-parametric methods are relatively more robust. In this article, we modify the non-parametric regression procedure proposed by Ghosh and Majumder [2000: Am J Hum Genet 66:1046-1061] to map Beta 2 EEG waves using genome-wide data generated in the COGA project. Significant linkage findings are obtained on chromosomes 1, 4, 5, and 15 with findings at multiple regions on chromosomes 4 and 15. We analyze the data both with and without incorporating alcoholism as a covariate. We also test for epistatic interactions between regions of the genome exhibiting significant linkage with the EEG phenotypes and find evidence of epistatic interactions between a region each on chromosome 1 and chromosome 4 with one region on chromosome 15. While regressing out the effect of alcoholism does not affect the linkage findings, the epistatic interactions become statistically insignificant. Copyright 2003 Wiley-Liss, Inc.

Use of Myocardial T1 Mapping at 3.0 T to Differentiate Anderson-Fabry Disease from Hypertrophic Cardiomyopathy.

PubMed

Karur, Gauri R; Robison, Sean; Iwanochko, Robert M; Morel, Chantal F; Crean, Andrew M; Thavendiranathan, Paaladinesh; Nguyen, Elsie T; Mathur, Shobhit; Wasim, Syed; Hanneman, Kate

2018-04-24

Purpose To compare left ventricular (LV) and right ventricular (RV) 3.0-T cardiac magnetic resonance (MR) imaging T1 values in Anderson-Fabry disease (AFD) and hypertrophic cardiomyopathy (HCM) and evaluate the diagnostic value of native T1 values beyond age, sex, and conventional imaging features. Materials and Methods For this prospective study, 30 patients with gene-positive AFD (37% male; mean age ± standard deviation, 45.0 years ± 14.1) and 30 patients with HCM (57% male; mean age, 49.3 years ± 13.5) were prospectively recruited between June 2016 and September 2017 to undergo cardiac MR imaging T1 mapping with a modified Look-Locker inversion recovery (MOLLI) acquisition scheme at 3.0 T (repetition time msec/echo time msec, 280/1.12; section thickness, 8 mm). LV and RV T1 values were evaluated. Statistical analysis included independent samples t test, receiver operating characteristic curve analysis, multivariable logistic regression, and likelihood ratio test. Results Septal LV, global LV, and RV native T1 values were significantly lower in AFD compared with those in HCM (1161 msec ± 47 vs 1296 msec ± 55, respectively [P < .001]; 1192 msec ± 52 vs 1268 msec ± 55 [P < .001]; and 1221 msec ± 54 vs 1271 msec ± 37 [P = .001], respectively). A septal LV native T1 cutoff point of 1220 msec or lower distinguished AFD from HCM with sensitivity of 97%, specificity of 93%, and accuracy of 95%. Septal LV native T1 values differentiated AFD from HCM after adjustment for age, sex, and conventional imaging features (odds ratio, 0.94; 95% confidence interval: 0.91, 0.98; P = < .001). In a nested logistic regression model with age, sex, and conventional imaging features, model fit was significantly improved by the addition of septal LV native T1 values (χ 2 [df = 1] = 33.4; P < .001). Conclusion Cardiac MR imaging native T1 values at 3.0 T are significantly lower in patients with AFD compared with those with HCM and provide independent and incremental diagnostic value beyond age, sex, and conventional imaging features. © RSNA, 2018.

Admixture mapping of pelvic organ prolapse in African Americans from the Women’s Health Initiative Hormone Therapy trial

PubMed Central

Hartmann, Katherine E.; Aldrich, Melinda C.; Ward, Renee M.; Wu, Jennifer M.; Park, Amy J.; Graff, Mariaelisa; Qi, Lihong; Nassir, Rami; Wallace, Robert B.; O'Sullivan, Mary J.; North, Kari E.; Velez Edwards, Digna R.; Edwards, Todd L.

2017-01-01

Evidence suggests European American (EA) women have two- to five-fold increased odds of having pelvic organ prolapse (POP) when compared with African American (AA) women. However, the role of genetic ancestry in relation to POP risk is not clear. Here we evaluate the association between genetic ancestry and POP in AA women from the Women’s Health Initiative Hormone Therapy trial. Women with grade 1 or higher classification, and grade 2 or higher classification for uterine prolapse, cystocele or rectocele at baseline or during follow-up were considered to have any POP (N = 805) and moderate/severe POP (N = 156), respectively. Women with at least two pelvic exams with no indication for POP served as controls (N = 344). We performed case-only, and case-control admixture-mapping analyses using multiple logistic regression while adjusting for age, BMI, parity and global ancestry. We evaluated the association between global ancestry and POP using multiple logistic regression. European ancestry at the individual level was not associated with POP risk. Case-only and case-control local ancestry analyses identified two ancestry-specific loci that may be associated with POP. One locus (Chromosome 15q26.2) achieved empirically-estimated statistical significance and was associated with decreased POP odds (considering grade ≥2 POP) with each unit increase in European ancestry (OR: 0.35; 95% CI: 0.30, 0.57; p-value = 1.48x10-5). This region includes RGMA, a potent regulator of the BMP family of genes. The second locus (Chromosome 1q42.1-q42.3) was associated with increased POP odds with each unit increase in European ancestry (Odds ratio [OR]: 1.69; 95% confidence interval [CI]: 1.28, 2.22; p-value = 1.93x10-4). Although this region did not reach statistical significance after considering multiple comparisons, it includes potentially relevant genes including TBCE, and ACTA1. Unique non-overlapping European and African ancestry-specific susceptibility loci may be associated with increased POP risk. PMID:28582460

Intensity Maps Production Using Real-Time Joint Streaming Data Processing From Social and Physical Sensors

NASA Astrophysics Data System (ADS)

Kropivnitskaya, Y. Y.; Tiampo, K. F.; Qin, J.; Bauer, M.

2015-12-01

Intensity is one of the most useful measures of earthquake hazard, as it quantifies the strength of shaking produced at a given distance from the epicenter. Today, there are several data sources that could be used to determine intensity level which can be divided into two main categories. The first category is represented by social data sources, in which the intensity values are collected by interviewing people who experienced the earthquake-induced shaking. In this case, specially developed questionnaires can be used in addition to personal observations published on social networks such as Twitter. These observations are assigned to the appropriate intensity level by correlating specific details and descriptions to the Modified Mercalli Scale. The second category of data sources is represented by observations from different physical sensors installed with the specific purpose of obtaining an instrumentally-derived intensity level. These are usually based on a regression of recorded peak acceleration and/or velocity amplitudes. This approach relates the recorded ground motions to the expected felt and damage distribution through empirical relationships. The goal of this work is to implement and evaluate streaming data processing separately and jointly from both social and physical sensors in order to produce near real-time intensity maps and compare and analyze their quality and evolution through 10-minute time intervals immediately following an earthquake. Results are shown for the case study of the M6.0 2014 South Napa, CA earthquake that occurred on August 24, 2014. The using of innovative streaming and pipelining computing paradigms through IBM InfoSphere Streams platform made it possible to read input data in real-time for low-latency computing of combined intensity level and production of combined intensity maps in near-real time. The results compare three types of intensity maps created based on physical, social and combined data sources. Here we correlate the count and density of Tweets with intensity level and show the importance of processing combined data sources at the earliest time stages after earthquake happens. This method can supplement existing approaches of intensity level detection, especially in the regions with high number of Twitter users and low density of seismic networks.

Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA

USGS Publications Warehouse

Ohlmacher, G.C.; Davis, J.C.

2003-01-01

Landslides in the hilly terrain along the Kansas and Missouri rivers in northeastern Kansas have caused millions of dollars in property damage during the last decade. To address this problem, a statistical method called multiple logistic regression has been used to create a landslide-hazard map for Atchison, Kansas, and surrounding areas. Data included digitized geology, slopes, and landslides, manipulated using ArcView GIS. Logistic regression relates predictor variables to the occurrence or nonoccurrence of landslides within geographic cells and uses the relationship to produce a map showing the probability of future landslides, given local slopes and geologic units. Results indicated that slope is the most important variable for estimating landslide hazard in the study area. Geologic units consisting mostly of shale, siltstone, and sandstone were most susceptible to landslides. Soil type and aspect ratio were considered but excluded from the final analysis because these variables did not significantly add to the predictive power of the logistic regression. Soil types were highly correlated with the geologic units, and no significant relationships existed between landslides and slope aspect. ?? 2003 Elsevier Science B.V. All rights reserved.

A subharmonic dynamical bifurcation during in vitro epileptiform activity

NASA Astrophysics Data System (ADS)

Perez Velazquez, Jose L.; Khosravani, Houman

2004-06-01

Epileptic seizures are considered to result from a sudden change in the synchronization of firing neurons in brain neural networks. We have used an in vitro model of status epilepticus (SE) to characterize dynamical regimes underlying the observed seizure-like activity. Time intervals between spikes or bursts were used as the variable to construct first-return interpeak or interburst interval plots, for studying neuronal population activity during the transition to seizure, as well as within seizures. Return maps constructed for a brief epoch before seizures were used for approximating the local system dynamics during that time window. Analysis of the first-return maps suggests that intermittency is a dynamical regime underlying the observed epileptic activity. This type of analysis may be useful for understanding the collective dynamics of neuronal populations in the normal and pathological brain.

The gene for autosomal dominant cerebellar ataxia with pigmentary macular dystrophy maps to chromosome 3p12-p21.1.

PubMed

Benomar, A; Krols, L; Stevanin, G; Cancel, G; LeGuern, E; David, G; Ouhabi, H; Martin, J J; Dürr, A; Zaim, A

1995-05-01

Autosomal dominant cerebellar ataxia with pigmentary macular dystrophy (ADCA type II) is a rare neurodegenerative disorder with marked anticipation. We have mapped the ADCA type II locus to chromosome 3 by linkage analysis in a genome-wide search and found no evidence for genetic heterogeneity among four families of different geographic origins. Haplotype reconstruction initially restricted the locus to the 33 cM interval flanked by D3S1300 and D3S1276 located at 3p12-p21.1. Combined multipoint analysis, using the Zmax-1 method, further reduced the candidate interval to an 8 cM region around D3S1285. Our results show that ADCA type II is a genetically homogenous disorder, independent of the heterogeneous group of type I cerebellar ataxias.

Fine mapping and identification of a novel locus qGL12.2 control grain length in wild rice (Oryza rufipogon Griff.).

PubMed

Qi, Lan; Ding, Yingbin; Zheng, Xiaoming; Xu, Rui; Zhang, Lizhen; Wang, Yanyan; Wang, Xiaoning; Zhang, Lifang; Cheng, Yunlian; Qiao, Weihua; Yang, Qingwen

2018-04-19

A wild rice QTL qGL12.2 for grain length was fine mapped to an 82-kb interval in chromosome 12 containing six candidate genes and none was reported previously. Grain length is an important trait for yield and commercial value in rice. Wild rice seeds have a very slender shape and have many desirable genes that have been lost in cultivated rice during domestication. In this study, we identified a quantitative trait locus, qGL12.2, which controls grain length in wild rice. First, a wild rice chromosome segment substitution line, CSSL41, was selected that has longer glume and grains than does the Oryza sativa indica cultivar, 9311. Next, an F 2 population was constructed from a cross between CSSL41 and 9311. Using the next-generation sequencing combined with bulked-segregant analysis and F 3 recombinants analysis, qGL12.2 was finally fine mapped to an 82-kb interval in chromosome 12. Six candidate genes were found, and no reported grain length genes were found in this interval. Using scanning electron microscopy, we found that CSSL41 cells are significantly longer than those of 9311, but there is no difference in cell widths. These data suggest that qGL12.2 is a novel gene that controls grain cell length in wild rice. Our study provides a new genetic resource for rice breeding and a starting point for functional characterization of the wild rice GL gene.

Fine Mapping and Transcriptome Analysis Reveal Candidate Genes Associated with Hybrid Lethality in Cabbage (Brassica Oleracea).

PubMed

Xiao, Zhiliang; Hu, Yang; Zhang, Xiaoli; Xue, Yuqian; Fang, Zhiyuan; Yang, Limei; Zhang, Yangyong; Liu, Yumei; Li, Zhansheng; Liu, Xing; Liu, Zezhou; Lv, Honghao; Zhuang, Mu

2017-06-05

Hybrid lethality is a deleterious phenotype that is vital to species evolution. We previously reported hybrid lethality in cabbage ( Brassica oleracea ) and performed preliminary mapping of related genes. In the present study, the fine mapping of hybrid lethal genes revealed that BoHL1 was located on chromosome C1 between BoHLTO124 and BoHLTO130, with an interval of 101 kb. BoHL2 was confirmed to be between insertion-deletion (InDels) markers HL234 and HL235 on C4, with a marker interval of 70 kb. Twenty-eight and nine annotated genes were found within the two intervals of BoHL1 and BoHL2 , respectively. We also applied RNA-Seq to analyze hybrid lethality in cabbage. In the region of BoHL1 , seven differentially expressed genes (DEGs) and five resistance (R)-related genes (two in common, i.e., Bo1g153320 and Bo1g153380 ) were found, whereas in the region of BoHL2 , two DEGs and four R-related genes (two in common, i.e., Bo4g173780 and Bo4g173810 ) were found. Along with studies in which R genes were frequently involved in hybrid lethality in other plants, these interesting R-DEGs may be good candidates associated with hybrid lethality. We also used SNP/InDel analyses and quantitative real-time PCR to confirm the results. This work provides new insight into the mechanisms of hybrid lethality in cabbage.

Estimating the magnitude of peak flows at selected recurrence intervals for streams in Idaho

USGS Publications Warehouse

Berenbrock, Charles

2002-01-01

The region-of-influence method is not recommended for use in determining flood-frequency estimates for ungaged sites in Idaho because the results, overall, are less accurate and the calculations are more complex than those of regional regression equations. The regional regression equations were considered to be the primary method of estimating the magnitude and frequency of peak flows for ungaged sites in Idaho.

Normality of Residuals Is a Continuous Variable, and Does Seem to Influence the Trustworthiness of Confidence Intervals: A Response to, and Appreciation of, Williams, Grajales, and Kurkiewicz (2013)

ERIC Educational Resources Information Center

Osborne, Jason W.

2013-01-01

Osborne and Waters (2002) focused on checking some of the assumptions of multiple linear regression. In a critique of that paper, Williams, Grajales, and Kurkiewicz correctly clarify that regression models estimated using ordinary least squares require the assumption of normally distributed errors, but not the assumption of normally distributed…

Conformal Regression for Quantitative Structure-Activity Relationship Modeling-Quantifying Prediction Uncertainty.

PubMed

Svensson, Fredrik; Aniceto, Natalia; Norinder, Ulf; Cortes-Ciriano, Isidro; Spjuth, Ola; Carlsson, Lars; Bender, Andreas

2018-05-29

Making predictions with an associated confidence is highly desirable as it facilitates decision making and resource prioritization. Conformal regression is a machine learning framework that allows the user to define the required confidence and delivers predictions that are guaranteed to be correct to the selected extent. In this study, we apply conformal regression to model molecular properties and bioactivity values and investigate different ways to scale the resultant prediction intervals to create as efficient (i.e., narrow) regressors as possible. Different algorithms to estimate the prediction uncertainty were used to normalize the prediction ranges, and the different approaches were evaluated on 29 publicly available data sets. Our results show that the most efficient conformal regressors are obtained when using the natural exponential of the ensemble standard deviation from the underlying random forest to scale the prediction intervals, but other approaches were almost as efficient. This approach afforded an average prediction range of 1.65 pIC50 units at the 80% confidence level when applied to bioactivity modeling. The choice of nonconformity function has a pronounced impact on the average prediction range with a difference of close to one log unit in bioactivity between the tightest and widest prediction range. Overall, conformal regression is a robust approach to generate bioactivity predictions with associated confidence.

Motion of Major Ice Shelf Fronts in Antarctica from Slant Range Analysis of Radar Altimeter Data, 1978 - 1998

NASA Technical Reports Server (NTRS)

Zwally, H. J.; Beckley, M. A.; Brenner, A. C.; Giovinetto, M. B.; Koblinsky, Chester J. (Technical Monitor)

2001-01-01

Slant range analysis of radar altimeter data from the Seasat, Geosat, ERS-1 and ERS-2 databases are used to determine barrier location at particular times, and estimate barrier motion (km/yr) for major Antarctic ice shelves. The barrier locations, which are the seaward edges or fronts of floating ice shelves, advance with time as the ice flows from the grounded ice sheets and retreat whenever icebergs calve from the fronts. The analysis covers various multiyear intervals from 1978 to 1998, supplemented by barrier location maps produced elsewhere for 1977 and 1986. Barrier motion is estimated as the ratio between mean annual ice shelf area change for a particular interval, and the length of the discharge periphery. This value is positive if the barrier location progresses seaward, or negative if the barrier location regresses (break-back). Either positive or negative values are lower limit estimates because the method does not detect relatively small area changes due to calving or surge events. The findings are discussed in the context of the three ice shelves that lie in large embayments (the Filchner-Ronne, Amery, and Ross), and marginal ice shelves characterized by relatively short distances between main segments of grounding line and barrier (those in the Queen Maud Land sector between 10.1 deg. W and 32.5 deg. E, and the West and Shackleton ice shelves). All the ice shelves included in the study account for approximately three-fourths of the total ice shelf area of Antarctica, and discharge approximately two-thirds of the total grounded ice area.

A rapid integrated bioactivity evaluation system based on near-infrared spectroscopy for quality control of Flos Chrysanthemi.

PubMed

Ding, Guoyu; Li, Baiqing; Han, Yanqi; Liu, Aina; Zhang, Jingru; Peng, Jiamin; Jiang, Min; Hou, Yuanyuan; Bai, Gang

2016-11-30

For quality control of herbal medicines or functional foods, integral activity evaluation has become more popular in recent studies. The majority of researchers focus on the relationship between chromatography/mass spectroscopy and bioactivity, but the connection with spectrum-activity is easily ignored. In this paper, the near infrared reflection spectra (NIRS) of Flos Chrysanthemi samples were collected as a representative spectrum technology, and corresponding anti-inflammation activities were utilized to illustrate the spectrum-activity study. HPLC/Q-TOF-MS identification and heat map clustering were used to select the quality markers (Q-marker) from five cultivars of Flos Chrysanthemi. Using boxplot analysis and the interval limits of detection (LODs) theory, six crucial markers, namely, chlorogenic acid, 3,5-dicaffeoylquinic acid, 1,5-dicaffeoylquinic acid, luteoloside, apigenin-7-O-β-d-glucoside, and luteolin-7-O-6-malonylglucoside were screened out. Then partial least squares regression (PLSR) calibration models combined with synergy interval partial least squares (siPLS) and 12 different spectral pretreatment methods were developed for the parameters optimization of these Q-markers in Flos Chrysanthemi powder. After comparing the relationship between Q-marker contents and anti-inflammation activity via three machine learning approaches and PLSR, back-propagation neural network (BP-ANN) displayed a more excellent non-linear fitting effect, as its R for new batches reached 0.89. These results indicated that the integrated NIRS and bioactive strategy was suitable for fast quality management in Flos Chrysanthemi, and also applied to other botanical food quality control. Copyright © 2016 Elsevier B.V. All rights reserved.

Patterns of Progressive Ganglion Cell-Inner Plexiform Layer Thinning in Glaucoma Detected by OCT.

PubMed

Shin, Joong Won; Sung, Kyung Rim; Park, Sun-Won

2018-04-25

To investigate the spatial characteristics and patterns of progressive macular ganglion cell-inner plexiform layer (GCIPL) thinning in glaucomatous eyes assessed by OCT Guided Progression Analysis (GPA). Longitudinal, retrospective, observational study. Two hundred ninety-two eyes of 192 patients with primary open-angle glaucoma with a mean follow-up of 6.0 years (range, 3.2-8.1 years) were included. Macular GCIPL imaging and visual field (VF) examination were performed at 6-month intervals for 3 years or more. Progressive GCIPL thinning was evaluated by a Cirrus HD-OCT (Carl Zeiss Meditec, Dublin, CA) GPA device. Spatial characteristics of progressive GCIPL thinning were assessed by the GCIPL thickness change map. The pattern of progressive GCIPL thinning was evaluated by comparing the baseline GCIPL thickness deviation map and the final GCIPL thickness change map. Visual field progression was determined by Early Manifest Glaucoma Trial criteria and linear regression of the VF index. Spatial characteristics and patterns of progressive GCIPL thinning. Seventy-two eyes of 62 participants (24.7% [72/292]) showed progressive GCIPL thinning in the GCIPL thickness change map. Progressive GCIPL thinning was detected most frequently (25.0%) at 2.08 mm from the fovea, and it extended in an arcuate shape in the inferotemporal region (250°-339°). Compared with the baseline GCIPL defects, the progressive GCIPL thinning extended toward the fovea and optic disc. The most common pattern of progressive GCIPL thinning was widening of GCIPL defects (42 eyes [58.3%]), followed by deepening of GCIPL defects (19 eyes [26.4%]) and newly developed GCIPL defects (15 eyes [20.8%]). Visual field progression was accompanied by progressive GCIPL thinning in 41 of 72 eyes (56.9%). Progressive GCIPL thinning preceded (61.0% [25/41]) or occurred concomitantly with (21.9% [9/41]) VF progression. The use of OCT GPA maps offers an effective approach to evaluate the topographic patterns of progressive GCIPL thinning in glaucomatous eyes. Progression of GCIPL thinning occurred before apparent progression on standard automated perimetry in most glaucomatous eyes. Understanding specific patterns and sequences of macular damage may provide important insights in the monitoring of glaucomatous progression. Copyright © 2018 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Sex preference and third birth intervals in a traditional Indian society.

PubMed

Nath, D C; Land, K C

1994-07-01

The traditional preference for sons may be the main hindrance to India's current population policy of two children per family. In this study, the effects of various sociodemographic covariates, particularly sex preference, on the length of the third birth interval are examined for the scheduled caste population in Assam, India. Life table and hazards regression techniques are applied to retrospective sample data. The analysis shows that couples having two surviving sons are less likely to have a third child than those without a surviving son and those with only one surviving son. Age at first marriage, length of preceding birth intervals, age of mother, and household income have strong effects on the length of the third birth interval.

Harmonization of forest disturbance datasets of the conterminous USA from 1986 to 2011

USGS Publications Warehouse

Soulard, Christopher E.; Acevedo, William; Cohen, Warren B.; Yang, Zhiqiang; Stehman, Stephen V.; Taylor, Janis L.

2017-01-01

Several spatial forest disturbance datasets exist for the conterminous USA. The major problem with forest disturbance mapping is that variability between map products leads to uncertainty regarding the actual rate of disturbance. In this article, harmonized maps were produced from multiple data sources (i.e., Global Forest Change, LANDFIRE Vegetation Disturbance, National Land Cover Database, Vegetation Change Tracker, and Web-Enabled Landsat Data). The harmonization process involved fitting common class ontologies and determining spatial congruency to produce forest disturbance maps for four time intervals (1986–1992, 1992–2001, 2001–2006, and 2006–2011). Pixels mapped as disturbed for two or more datasets were labeled as disturbed in the harmonized maps. The primary advantage gained by harmonization was improvement in commission error rates relative to the individual disturbance products. Disturbance omission errors were high for both harmonized and individual forest disturbance maps due to underlying limitations in mapping subtle disturbances with Landsat classification algorithms. To enhance the value of the harmonized disturbance products, we used fire perimeter maps to add information on the cause of disturbance.

Harmonization of forest disturbance datasets of the conterminous USA from 1986 to 2011.

PubMed

Soulard, Christopher E; Acevedo, William; Cohen, Warren B; Yang, Zhiqiang; Stehman, Stephen V; Taylor, Janis L

2017-04-01

Several spatial forest disturbance datasets exist for the conterminous USA. The major problem with forest disturbance mapping is that variability between map products leads to uncertainty regarding the actual rate of disturbance. In this article, harmonized maps were produced from multiple data sources (i.e., Global Forest Change, LANDFIRE Vegetation Disturbance, National Land Cover Database, Vegetation Change Tracker, and Web-Enabled Landsat Data). The harmonization process involved fitting common class ontologies and determining spatial congruency to produce forest disturbance maps for four time intervals (1986-1992, 1992-2001, 2001-2006, and 2006-2011). Pixels mapped as disturbed for two or more datasets were labeled as disturbed in the harmonized maps. The primary advantage gained by harmonization was improvement in commission error rates relative to the individual disturbance products. Disturbance omission errors were high for both harmonized and individual forest disturbance maps due to underlying limitations in mapping subtle disturbances with Landsat classification algorithms. To enhance the value of the harmonized disturbance products, we used fire perimeter maps to add information on the cause of disturbance.

Widespread Miocene deep-sea hiatuses: coincidence with periods of global cooling.

USGS Publications Warehouse

Barron, J.A.; Keller, G.

1982-01-01

High-resolution biostratigraphic analyses of Miocene deep-sea cores reveal eight intervals of widespread hiatuses in the world ocean. In complete sections these hiatuses correspond to intervals of cool faunal and floral assemblages, rapid enrichment of delta 18O, and sea-level regressions. These factors suggest that Miocene deep-sea hiatuses result from an increased intensity of circulation and corrosiveness of bottom currents during periods of increased polar refrigeration.-Authors

High prevalence of refractive errors in a rural population: 'Nooravaran Salamat' Mobile Eye Clinic experience.

PubMed

Hashemi, Hassan; Rezvan, Farhad; Ostadimoghaddam, Hadi; Abdollahi, Majid; Hashemi, Maryam; Khabazkhoob, Mehdi

2013-01-01

The prevalence of myopia and hyperopia and determinants were determined in a rural population of Iran. Population-based cross-sectional study. Using random cluster sampling, 13 of the 83 villages of Khaf County in the north east of Iran were selected. Data from 2001 people over the age of 15 years were analysed. Visual acuity measurement, non-cycloplegic refraction and eye examinations were done at the Mobile Eye Clinic. The prevalence of myopia and hyperopia based on spherical equivalent worse than -0.5 dioptre and +0.5 dioptre, respectively. The prevalence of myopia, hyperopia and anisometropia in the total study sample was 28% (95% confidence interval: 25.9-30.2), 19.2% (95% confidence interval: 17.3-21.1), and 11.5% (95% confidence interval: 10.0-13.1), respectively. In the over 40 population, the prevalence of myopia and hyperopia was 32.5% (95% confidence interval: 28.9-36.1) and 27.9% (95% confidence interval: 24.5-31.3), respectively. In the multiple regression model for this group, myopia strongly correlated with cataract (odds ratio = 1.98 and 95% confidence interval: 1.33-2.93), and hyperopia only correlated with age (P < 0.001). The prevalence of high myopia and high hyperopia was 1.5% and 4.6%. In the multiple regression model, anisometropia significantly correlated with age (odds ratio = 1.04) and cataract (odds ratio = 5.2) (P < 0.001). The prevalence of myopia and anisometropia was higher than that in previous studies in urban population of Iran, especially in the elderly. Cataract was the only variable that correlated with myopia and anisometropia. © 2013 The Authors. Clinical and Experimental Ophthalmology © 2013 Royal Australian and New Zealand College of Ophthalmologists.

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China

PubMed Central

Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

2016-01-01

In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%–19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides. PMID:27187430

A batch sliding window method for local singularity mapping and its application for geochemical anomaly identification

NASA Astrophysics Data System (ADS)

Xiao, Fan; Chen, Zhijun; Chen, Jianguo; Zhou, Yongzhang

2016-05-01

In this study, a novel batch sliding window (BSW) based singularity mapping approach was proposed. Compared to the traditional sliding window (SW) technique with disadvantages of the empirical predetermination of a fixed maximum window size and outliers sensitivity of least-squares (LS) linear regression method, the BSW based singularity mapping approach can automatically determine the optimal size of the largest window for each estimated position, and utilizes robust linear regression (RLR) which is insensitive to outlier values. In the case study, tin geochemical data in Gejiu, Yunnan, have been processed by BSW based singularity mapping approach. The results show that the BSW approach can improve the accuracy of the calculation of singularity exponent values due to the determination of the optimal maximum window size. The utilization of RLR method in the BSW approach can smoothen the distribution of singularity index values with few or even without much high fluctuate values looking like noise points that usually make a singularity map much roughly and discontinuously. Furthermore, the student's t-statistic diagram indicates a strong spatial correlation between high geochemical anomaly and known tin polymetallic deposits. The target areas within high tin geochemical anomaly could probably have much higher potential for the exploration of new tin polymetallic deposits than other areas, particularly for the areas that show strong tin geochemical anomalies whereas no tin polymetallic deposits have been found in them.

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China.

PubMed

Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

2016-05-11

In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%-19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides.

Quantitative maps of geomagnetic perturbation vectors during substorm onset and recovery

PubMed Central

Pothier, N M; Weimer, D R; Moore, W B

2015-01-01

We have produced the first series of spherical harmonic, numerical maps of the time-dependent surface perturbations in the Earth's magnetic field following the onset of substorms. Data from 124 ground magnetometer stations in the Northern Hemisphere at geomagnetic latitudes above 33° were used. Ground station data averaged over 5 min intervals covering 8 years (1998–2005) were used to construct pseudo auroral upper, auroral lower, and auroral electrojet (AU*, AL*, and AE*) indices. These indices were used to generate a list of substorms that extended from 1998 to 2005, through a combination of automated processing and visual checks. Events were sorted by interplanetary magnetic field (IMF) orientation (at the Advanced Composition Explorer (ACE) satellite), dipole tilt angle, and substorm magnitude. Within each category, the events were aligned on substorm onset. A spherical cap harmonic analysis was used to obtain a least error fit of the substorm disturbance patterns at 5 min intervals up to 90 min after onset. The fits obtained at onset time were subtracted from all subsequent fits, for each group of substorm events. Maps of the three vector components of the averaged magnetic perturbations were constructed to show the effects of substorm currents. These maps are produced for several specific ranges of values for the peak |AL*| index, IMF orientation, and dipole tilt angle. We demonstrate an influence of the dipole tilt angle on the response to substorms. Our results indicate that there are downward currents poleward and upward currents just equatorward of the peak in the substorms' westward electrojet. Key Points Show quantitative maps of ground geomagnetic perturbations due to substorms Three vector components mapped as function of time during onset and recovery Compare/contrast results for different tilt angle and sign of IMF Y-component PMID:26167445

An eceriferum locus, cer-zv, is associated with a defect in cutin responsible for water retention in barley (Hordeum vulgare) leaves.

PubMed

Li, Chao; Wang, Aidong; Ma, Xiaoying; Pourkheirandish, Mohammad; Sakuma, Shun; Wang, Ning; Ning, Shunzong; Nevo, Eviatar; Nawrath, Christiane; Komatsuda, Takao; Chen, Guoxiong

2013-03-01

Drought limits plant growth and threatens crop productivity. A barley (Hordeum vulgare) ethylene imine-induced monogenic recessive mutant cer-zv, which is sensitive to drought, was characterized and genetically mapped in the present study. Detached leaves of cer-zv lost 34.2 % of their initial weight after 1 h of dehydration. The transpiration was much higher in cer-zv leaves than in wild-type leaves under both light and dark conditions. The stomata of cer-zv leaves functioned normally, but the cuticle of cer-zv leaves showed increased permeability to ethanol and toluidine blue dye. There was a 50-90 % reduction in four major cutin monomers, but no reduction in wax loads was found in the cer-zv mutant as compared with the wild type. Two F(2) mapping populations were established by the crosses of 23-19 × cer-zv and cer-zv × OUH602. More polymorphisms were found in EST sequences between cer-zv and OUH602 than between cer-zv and 23-19. cer-zv was located in a pericentromeric region on chromosome 4H in a 10.8 cM interval in the 23-19 × cer-zv map based on 186 gametes tested and a 1.7 cM interval in the cer-zv × OUH602 map based on 176 gametes tested. It co-segregated with EST marker AK251484 in both maps. The results indicated that the cer-zv mutant is defective in cutin, which might be responsible for the increased transpiration rate and drought sensitivity, and that the F(2) of cer-zv × OUH602 might better facilitate high resolution mapping of cer-zv.

Genetic mapping of QTL for the sizes of eight consecutive leaves below the tassel in maize (Zea mays L.).

PubMed

Yang, Cong; Tang, Dengguo; Qu, Jingtao; Zhang, Ling; Zhang, Lei; Chen, Zhengjie; Liu, Jian

2016-11-01

A set of RIL population was used to detect QTL associated with the sizes of eight consecutive leaves, across different environments, and ten QTL clusters were identified as main QTLs. One of the important parameters of the maize leaf architecture that affects light penetration into the canopy, leaf size, has long attracted breeders' attention for optimizing the plant type of maize and for maximizing the grain yield (GY). In this study, we used 253 RIL lines derived from a cross between B73 and SICAU1212 to investigate the leaf widths (LWs), leaf lengths (LLs), and leaf areas (LAs) of eight consecutive leaves of maize below the tassel and GY across different environments and to identify quantitative traits loci (QTLs) controlling the above-mentioned traits, using inclusive interval mapping for single-environment analysis plus a mixed-model-based composite interval mapping for joint analysis. A total of 171 and 159 putative QTLs were detected through these two mapping methods, respectively. Single-environment mapping revealed that 39 stable QTLs explained more than 10 % of the phenotypic variance, and 35 of the 39 QTLs were also detected by joint analysis. In addition, joint analysis showed that nine of the 159 QTLs exhibited significant QTL × environment interaction and 15 significant epistatic interactions were identified. Approximately 47.17 % of the QTLs for leaf architectural traits in joint analysis were concentrated in ten main chromosomal regions, namely, bins 1.07, 2.02, 3.06, 4.09, 5.01, 5.02, 5.03-5.04, 5.07, 6.07, and 8.05. This study should provide a basis for further fine-mapping of these main genetic regions and improvement of maize leaf architecture.

Real-Time Two-Dimensional Mapping of Relative Local Surface Temperatures with a Thin-Film Sensor Array

PubMed Central

Li, Gang; Wang, Zhenhai; Mao, Xinyu; Zhang, Yinghuang; Huo, Xiaoye; Liu, Haixiao; Xu, Shengyong

2016-01-01

Dynamic mapping of an object’s local temperature distribution may offer valuable information for failure analysis, system control and improvement. In this letter we present a computerized measurement system which is equipped with a hybrid, low-noise mechanical-electrical multiplexer for real-time two-dimensional (2D) mapping of surface temperatures. We demonstrate the performance of the system on a device embedded with 32 pieces of built-in Cr-Pt thin-film thermocouples arranged in a 4 × 8 matrix. The system can display a continuous 2D mapping movie of relative temperatures with a time interval around 1 s. This technique may find applications in a variety of practical devices and systems. PMID:27347969

Epidemiologic Evaluation of Measurement Data in the Presence of Detection Limits

PubMed Central

Lubin, Jay H.; Colt, Joanne S.; Camann, David; Davis, Scott; Cerhan, James R.; Severson, Richard K.; Bernstein, Leslie; Hartge, Patricia

2004-01-01

Quantitative measurements of environmental factors greatly improve the quality of epidemiologic studies but can pose challenges because of the presence of upper or lower detection limits or interfering compounds, which do not allow for precise measured values. We consider the regression of an environmental measurement (dependent variable) on several covariates (independent variables). Various strategies are commonly employed to impute values for interval-measured data, including assignment of one-half the detection limit to nondetected values or of “fill-in” values randomly selected from an appropriate distribution. On the basis of a limited simulation study, we found that the former approach can be biased unless the percentage of measurements below detection limits is small (5–10%). The fill-in approach generally produces unbiased parameter estimates but may produce biased variance estimates and thereby distort inference when 30% or more of the data are below detection limits. Truncated data methods (e.g., Tobit regression) and multiple imputation offer two unbiased approaches for analyzing measurement data with detection limits. If interest resides solely on regression parameters, then Tobit regression can be used. If individualized values for measurements below detection limits are needed for additional analysis, such as relative risk regression or graphical display, then multiple imputation produces unbiased estimates and nominal confidence intervals unless the proportion of missing data is extreme. We illustrate various approaches using measurements of pesticide residues in carpet dust in control subjects from a case–control study of non-Hodgkin lymphoma. PMID:15579415

Photogrammetry of the Viking Lander imagery

NASA Technical Reports Server (NTRS)

Wu, S. S. C.; Schafer, F. J.

1982-01-01

The problem of photogrammetric mapping which uses Viking Lander photography as its basis is solved in two ways: (1) by converting the azimuth and elevation scanning imagery to the equivalent of a frame picture, using computerized rectification; and (2) by interfacing a high-speed, general-purpose computer to the analytical plotter employed, so that all correction computations can be performed in real time during the model-orientation and map-compilation process. Both the efficiency of the Viking Lander cameras and the validity of the rectification method have been established by a series of pre-mission tests which compared the accuracy of terrestrial maps compiled by this method with maps made from aerial photographs. In addition, 1:10-scale topographic maps of Viking Lander sites 1 and 2 having a contour interval of 1.0 cm have been made to test the rectification method.

Korean coastal water depth/sediment and land cover mapping (1:25,000) by computer analysis of LANDSAT imagery

NASA Technical Reports Server (NTRS)

Park, K. Y.; Miller, L. D.

1978-01-01

Computer analysis was applied to single date LANDSAT MSS imagery of a sample coastal area near Seoul, Korea equivalent to a 1:50,000 topographic map. Supervised image processing yielded a test classification map from this sample image containing 12 classes: 5 water depth/sediment classes, 2 shoreline/tidal classes, and 5 coastal land cover classes at a scale of 1:25,000 and with a training set accuracy of 76%. Unsupervised image classification was applied to a subportion of the site analyzed and produced classification maps comparable in results in a spatial sense. The results of this test indicated that it is feasible to produce such quantitative maps for detailed study of dynamic coastal processes given a LANDSAT image data base at sufficiently frequent time intervals.

Genetic ancestry is associated with colorectal adenomas and adenocarcinomas in Latino populations.

PubMed

Hernandez-Suarez, Gustavo; Sanabria, Maria Carolina; Serrano, Marta; Herran, Oscar F; Perez, Jesus; Plata, Jose L; Zabaleta, Jovanny; Tenesa, Albert

2014-10-01

Colorectal cancer rates in Latin American countries are less than half of those observed in the United States. Latin Americans are the resultant of generations of an admixture of Native American, European, and African individuals. The potential role of genetic admixture in colorectal carcinogenesis has not been examined. We evaluate the association of genetic ancestry with colorectal neoplasms in 190 adenocarcinomas, 113 sporadic adenomas and 243 age- and sex-matched controls enrolled in a multicentric case-control study in Colombia. Individual ancestral genetic fractions were estimated using the STRUCTURE software, based on allele frequencies and assuming three distinct population origins. We used the Illumina Cancer Panel to genotype 1,421 sparse single-nucleotide polymorphisms (SNPs), and Northern and Western European ancestry, LWJ and Han Chinese in Beijing, China populations from the HapMap project as references. A total of 678 autosomal SNPs overlapped with the HapMap data set SNPs and were used for ancestry estimations. African mean ancestry fraction was higher in adenomas (0.13, 95% confidence interval (95% CI)=0.11-0.15) and cancer cases (0.14, 95% CI=0.12-0.16) compared with controls (0.11, 95% CI=0.10-0.12). Conditional logistic regression analysis, controlling for known risk factors, showed a positive association of African ancestry per 10% increase with both colorectal adenoma (odds ratio (OR)=1.12, 95% CI=0.97-1.30) and adenocarcinoma (OR=1.19, 95% CI=1.05-1.35). In conclusion, increased African ancestry (or variants linked to it) contributes to the increased susceptibility of colorectal cancer in admixed Latin American population.

Geographic disparities of asthma prevalence in south-western United States of America.

PubMed

Chien, Lung-Chang; Alamgir, Hasanat

2014-11-01

Asthma is one of the most prevalent chronic diseases in the United States of America (USA), and many of its risk factors have so far been investigated and identified; however, evidence is limited on how spatial disparities impact the disease. The purpose of this study was to provide scientific evidence on the location influence on asthma in the four states of southwestern USA (California, Arizona, New Mexico and Texas) which, together, include 360 counties. The Behavioral Risk Factor Surveillance System database for these four states covering the period of 2000 to 2011 was used in this analysis, and a Bayesian structured additive regression model was applied to analyse by a geographical information system. After adjusting for individual characteristics, socioeconomic status and health behaviour, this study found higher odds associated with asthma and a likely cluster around the Bay Area in California, while lower odds appeared in several counties around the larger cities of Texas, such as Dallas, Houston and San Antonio. The significance map shows 43 of 360 counties (11.9%) to be high-risk areas for asthma. The level of geographical disparities demonstrates that the county risk of asthma prevalence varies significantly and can be about 19.9% (95% confidence interval: 15.3-25.8) higher or lower than the overall asthma prevalence. We provide an efficient method to utilise and interpret the existing surveillance data on asthma. Visualisation by maps may help deliver future interventions on targeted areas and vulnerable populations to reduce geographical disparities in the burden of asthma.

Soil Organic Carbon Estimation and Mapping Using "on-the-go" VisNIR Spectroscopy

NASA Astrophysics Data System (ADS)

Brown, D. J.; Bricklemyer, R. S.; Christy, C.

2007-12-01

Soil organic carbon (SOC) and other soil properties related to carbon sequestration (eg. soil clay content and mineralogy) vary spatially across landscapes. To cost effectively capture this variability, new technologies, such as Visible and Near Infrared (VisNIR) spectroscopy, have been applied to soils for rapid, accurate, and inexpensive estimation of SOC and other soil properties. For this study, we evaluated an "on the go" VisNIR sensor developed by Veris Technologies, Inc. (Salinas, KS) for mapping SOC, soil clay content and mineralogy. The Veris spectrometer spanned 350 to 2224 nm with 8 nm spectral resolution, and 25 spectra were integrated every 2 seconds resulting in 3 -5 m scanning distances on the ground. The unit was mounted to a mobile sensor platform pulled by a tractor, and scanned soils at an average depth of 10 cm through a quartz-sapphire window. We scanned eight 16.2 ha (40 ac) wheat fields in north central Montana (USA), with 15 m transect intervals. Using random sampling with spatial inhibition, 100 soil samples from 0-10 cm depths were extracted along scanned transects from each field and were analyzed for SOC. Neat, sieved (<2 mm) soil sample materials were also scanned in the lab using an Analytical Spectral Devices (ASD, Boulder, CO, USA) Fieldspec Pro FR spectroradiometer with a spectral range of 350-2500 and spectral resolution of 2-10 nm. The analyzed samples were used to calibrate and validate a number of partial least squares regression (PLSR) VisNIR models to compare on-the-go scanning vs. higher spectral resolution laboratory spectroscopy vs. standard SOC measurement methods.

Abnormal early diastolic intraventricular flow 'kinetic energy index' assessed by vector flow mapping in patients with elevated filling pressure.

PubMed

Nogami, Yoshie; Ishizu, Tomoko; Atsumi, Akiko; Yamamoto, Masayoshi; Kawamura, Ryo; Seo, Yoshihiro; Aonuma, Kazutaka

2013-03-01

Recently developed vector flow mapping (VFM) enables evaluation of local flow dynamics without angle dependency. This study used VFM to evaluate quantitatively the index of intraventricular haemodynamic kinetic energy in patients with left ventricular (LV) diastolic dysfunction and to compare those with normal subjects. We studied 25 patients with estimated high left atrial (LA) pressure (pseudonormal: PN group) and 36 normal subjects (control group). Left ventricle was divided into basal, mid, and apical segments. Intraventricular haemodynamic energy was evaluated in the dimension of speed, and it was defined as the kinetic energy index. We calculated this index and created time-energy index curves. The time interval from electrocardiogram (ECG) R wave to peak index was measured, and time differences of the peak index between basal and other segments were defined as ΔT-mid and ΔT-apex. In both groups, early diastolic peak kinetic energy index in mid and apical segments was significantly lower than that in the basal segment. Time to peak index did not differ in apex, mid, and basal segments in the control group but was significantly longer in the apex than that in the basal segment in the PN group. ΔT-mid and ΔT-apex were significantly larger in the PN group than the control group. Multiple regression analysis showed sphericity index, E/E' to be significant independent variables determining ΔT apex. Retarded apical kinetic energy fluid dynamics were detected using VFM and were closely associated with LV spherical remodelling in patients with high LA pressure.

Molecular characterisation of resistance against potato wart races 1, 2, 6 and 18 in a tetraploid population of potato (Solanum tuberosum subsp. tuberosum).

PubMed

Groth, Jennifer; Song, Yesu; Kellermann, Adolf; Schwarzfischer, Andrea

2013-05-01

Potato wart is caused by the obligate biotrophic fungus Synchytrium endobioticum, which is subject to quarantine regulations due to the production of long persisting spores in the soil and the lack of effective fungicides. The objective of this study was to identify quantitative trait loci (QTL) for resistance against potato wart races (R) 1, 2, 6 and 18 in a tetraploid potato population developed by crossing cv. Saturna (resistant to R1) with cv. Panda (resistant to R1, R2, R6, R18). A total of 92 progenies were used for phenotyping and genotyping. Resistance tests were performed for races 1 and 18 in 2 years and for races 2 and 6 in 1 year on 10 to 20 eyepieces per genotype. Based on amplified fragment length polymorphism (AFLP) and simple sequence repeat (SSR) markers, linkage maps were established for the female and male parent, respectively. Single marker analysis followed by a multiple regression analysis revealed initial marker-trait associations. The interval mapping routine of TetraploidMap was applied for QTL analysis. A major QTL for resistance against race 1 explaining between 46 % and 56 % of the phenotypic variation was identified near Sen1, a known resistance locus for potato wart race 1 on chromosome XI. Other resistance QTL were detected on chromosomes I (to R2), II (to R6, 18), VI (to R1, 2, 6, 18), VII (to R2, 6, 18), VIII (to R1, 2, 6, 18), X (to R2, 6, 18), XI (to R2, 6, 18) and on an unknown linkage group (to R18) explaining minor to moderate effects of the phenotypic variation. Resistance QTL against different potato wart races often overlapped, particularly concerning races 2, 6 and 18. Overall, this study gives a valuable insight into the complex inheritance of resistance against potato wart.

How Statistics "Excel" Online.

ERIC Educational Resources Information Center

Chao, Faith; Davis, James

2000-01-01

Discusses the use of Microsoft Excel software and provides examples of its use in an online statistics course at Golden Gate University in the areas of randomness and probability, sampling distributions, confidence intervals, and regression analysis. (LRW)

Analyzing big data with the hybrid interval regression methods.

PubMed

Huang, Chia-Hui; Yang, Keng-Chieh; Kao, Han-Ying

2014-01-01

Big data is a new trend at present, forcing the significant impacts on information technologies. In big data applications, one of the most concerned issues is dealing with large-scale data sets that often require computation resources provided by public cloud services. How to analyze big data efficiently becomes a big challenge. In this paper, we collaborate interval regression with the smooth support vector machine (SSVM) to analyze big data. Recently, the smooth support vector machine (SSVM) was proposed as an alternative of the standard SVM that has been proved more efficient than the traditional SVM in processing large-scale data. In addition the soft margin method is proposed to modify the excursion of separation margin and to be effective in the gray zone that the distribution of data becomes hard to be described and the separation margin between classes.

Analyzing Big Data with the Hybrid Interval Regression Methods

PubMed Central

Kao, Han-Ying

2014-01-01

Big data is a new trend at present, forcing the significant impacts on information technologies. In big data applications, one of the most concerned issues is dealing with large-scale data sets that often require computation resources provided by public cloud services. How to analyze big data efficiently becomes a big challenge. In this paper, we collaborate interval regression with the smooth support vector machine (SSVM) to analyze big data. Recently, the smooth support vector machine (SSVM) was proposed as an alternative of the standard SVM that has been proved more efficient than the traditional SVM in processing large-scale data. In addition the soft margin method is proposed to modify the excursion of separation margin and to be effective in the gray zone that the distribution of data becomes hard to be described and the separation margin between classes. PMID:25143968

Use of microcomputer in mapping depth of stratigraphic horizons in National Petroleum Reserve in Alaska

USGS Publications Warehouse

Payne, Thomas G.

1982-01-01

REGIONAL MAPPER is a menu-driven system in the BASIC language for computing and plotting (1) time, depth, and average velocity to geologic horizons, (2) interval time, thickness, and interval velocity of stratigraphic intervals, and (3) subcropping and onlapping intervals at unconformities. The system consists of three programs: FILER, TRAVERSER, and PLOTTER. A control point is a shot point with velocity analysis or a shot point at or near a well with velocity check-shot survey. Reflection time to and code number of seismic horizons are filed by digitizing tablet from record sections. TRAVERSER starts at a point of geologic control and, in traversing to another, parallels seismic events, records loss of horizons by onlap and truncation, and stores reflection time for geologic horizons at traversed shot points. TRAVERSER is basically a phantoming procedure. Permafrost thickness and velocity variations, buried canyons with low-velocity fill, and error in seismically derived velocity cause velocity anomalies that complicate depth mapping. Two depths to the top of the pebble is based shale are computed for each control point. One depth, designated Zs on seismically derived velocity. The other (Zw) is based on interval velocity interpolated linearly between wells and multiplied by interval time (isochron) to give interval thickness. Z w is computed for all geologic horizons by downward summation of interval thickness. Unknown true depth (Z) to the pebble shale may be expressed as Z = Zs + es and Z = Zw + ew where the e terms represent error. Equating the two expressions gives the depth difference D = Zs + Zw = ew + es A plot of D for the top of the pebble shale is readily contourable but smoothing is required to produce a reasonably simple surface. Seismically derived velocity used in computing Zs includes the effect of velocity anomalies but is subject to some large randomly distributed errors resulting in depth errors (es). Well-derived velocity used in computing Zw does not include the effect of velocity anomalies, but the error (ew) should reflect these anomalies and should be contourable (non-random). The D surface as contoured with smoothing is assumed to represent ew, that is, the depth effect of variations in permafrost thickness and velocity and buried canyon depth. Estimated depth (Zest) to each geologic horizon is the sum of Z w for that horizon and a constant e w as contoured for the pebble shale, which is the first highly continuous seismic horizon below the zone of anomalous velocity. Results of this 'depthing' procedure are compared with those of Tetra Tech, Inc., the subcontractor responsible for geologic and geophysical interpretation and mapping.

Regression equations for estimating flood flows for the 2-, 10-, 25-, 50-, 100-, and 500-Year recurrence intervals in Connecticut

USGS Publications Warehouse

Ahearn, Elizabeth A.

2004-01-01

Multiple linear-regression equations were developed to estimate the magnitudes of floods in Connecticut for recurrence intervals ranging from 2 to 500 years. The equations can be used for nonurban, unregulated stream sites in Connecticut with drainage areas ranging from about 2 to 715 square miles. Flood-frequency data and hydrologic characteristics from 70 streamflow-gaging stations and the upstream drainage basins were used to develop the equations. The hydrologic characteristics?drainage area, mean basin elevation, and 24-hour rainfall?are used in the equations to estimate the magnitude of floods. Average standard errors of prediction for the equations are 31.8, 32.7, 34.4, 35.9, 37.6 and 45.0 percent for the 2-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals, respectively. Simplified equations using only one hydrologic characteristic?drainage area?also were developed. The regression analysis is based on generalized least-squares regression techniques. Observed flows (log-Pearson Type III analysis of the annual maximum flows) from five streamflow-gaging stations in urban basins in Connecticut were compared to flows estimated from national three-parameter and seven-parameter urban regression equations. The comparison shows that the three- and seven- parameter equations used in conjunction with the new statewide equations generally provide reasonable estimates of flood flows for urban sites in Connecticut, although a national urban flood-frequency study indicated that the three-parameter equations significantly underestimated flood flows in many regions of the country. Verification of the accuracy of the three-parameter or seven-parameter national regression equations using new data from Connecticut stations was beyond the scope of this study. A technique for calculating flood flows at streamflow-gaging stations using a weighted average also is described. Two estimates of flood flows?one estimate based on the log-Pearson Type III analyses of the annual maximum flows at the gaging station, and the other estimate from the regression equation?are weighted together based on the years of record at the gaging station and the equivalent years of record value determined from the regression. Weighted averages of flood flows for the 2-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals are tabulated for the 70 streamflow-gaging stations used in the regression analysis. Generally, weighted averages give the most accurate estimate of flood flows at gaging stations. An evaluation of the Connecticut's streamflow-gaging network was performed to determine whether the spatial coverage and range of geographic and hydrologic conditions are adequately represented for transferring flood characteristics from gaged to ungaged sites. Fifty-one of 54 stations in the current (2004) network support one or more flood needs of federal, state, and local agencies. Twenty-five of 54 stations in the current network are considered high-priority stations by the U.S. Geological Survey because of their contribution to the longterm understanding of floods, and their application for regionalflood analysis. Enhancements to the network to improve overall effectiveness for regionalization can be made by increasing the spatial coverage of gaging stations, establishing stations in regions of the state that are not well-represented, and adding stations in basins with drainage area sizes not represented. Additionally, the usefulness of the network for characterizing floods can be maintained and improved by continuing operation at the current stations because flood flows can be more accurately estimated at stations with continuous, long-term record.

High-resolution precipitation mapping in a mountainous watershed: ground truth for evaluating uncertainty in a national precipitation dataset

Treesearch

Christopher Daly; Melissa E. Slater; Joshua A. Roberti; Stephanie H. Laseter; Lloyd W. Swift

2017-01-01

A 69-station, densely spaced rain gauge network was maintained over the period 1951–1958 in the Coweeta Hydrologic Laboratory, located in the southern Appalachians in western North Carolina, USA. This unique dataset was used to develop the first digital seasonal and annual precipitation maps for the Coweeta basin, using elevation regression functions and...

Use of Forest Inventory and Analysis information in wildlife habitat modeling: a process for linking multiple scales

Treesearch

Thomas C. Edwards; Gretchen G. Moisen; Tracey S. Frescino; Joshua L. Lawler

2002-01-01

We describe our collective efforts to develop and apply methods for using FIA data to model forest resources and wildlife habitat. Our work demonstrates how flexible regression techniques, such as generalized additive models, can be linked with spatially explicit environmental information for the mapping of forest type and structure. We illustrate how these maps of...

Estimation of the stand ages of tropical secondary forests after shifting cultivation based on the combination of WorldView-2 and time-series Landsat images

NASA Astrophysics Data System (ADS)

Fujiki, Shogoro; Okada, Kei-ichi; Nishio, Shogo; Kitayama, Kanehiro

2016-09-01

We developed a new method to estimate stand ages of secondary vegetation in the Bornean montane zone, where local people conduct traditional shifting cultivation and protected areas are surrounded by patches of recovering secondary vegetation of various ages. Identifying stand ages at the landscape level is critical to improve conservation policies. We combined a high-resolution satellite image (WorldView-2) with time-series Landsat images. We extracted stand ages (the time elapsed since the most recent slash and burn) from a change-detection analysis with Landsat time-series images and superimposed the derived stand ages on the segments classified by object-based image analysis using WorldView-2. We regarded stand ages as a response variable, and object-based metrics as independent variables, to develop regression models that explain stand ages. Subsequently, we classified the vegetation of the target area into six age units and one rubber plantation unit (1-3 yr, 3-5 yr, 5-7 yr, 7-30 yr, 30-50 yr, >50 yr and 'rubber plantation') using regression models and linear discriminant analyses. Validation demonstrated an accuracy of 84.3%. Our approach is particularly effective in classifying highly dynamic pioneer vegetation younger than 7 years into 2-yr intervals, suggesting that rapid changes in vegetation canopies can be detected with high accuracy. The combination of a spectral time-series analysis and object-based metrics based on high-resolution imagery enabled the classification of dynamic vegetation under intensive shifting cultivation and yielded an informative land cover map based on stand ages.

[Winter wheat area estimation with MODIS-NDVI time series based on parcel].

PubMed

Li, Le; Zhang, Jin-shui; Zhu, Wen-quan; Hu, Tan-gao; Hou, Dong

2011-05-01

Several attributes of MODIS (moderate resolution imaging spectrometer) data, especially the short temporal intervals and the global coverage, provide an extremely efficient way to map cropland and monitor its seasonal change. However, the reliability of their measurement results is challenged because of the limited spatial resolution. The parcel data has clear geo-location and obvious boundary information of cropland. Also, the spectral differences and the complexity of mixed pixels are weak in parcels. All of these make that area estimation based on parcels presents more advantage than on pixels. In the present study, winter wheat area estimation based on MODIS-NDVI time series has been performed with the support of cultivated land parcel in Tongzhou, Beijing. In order to extract the regional winter wheat acreage, multiple regression methods were used to simulate the stable regression relationship between MODIS-NDVI time series data and TM samples in parcels. Through this way, the consistency of the extraction results from MODIS and TM can stably reach up to 96% when the amount of samples accounts for 15% of the whole area. The results shows that the use of parcel data can effectively improve the error in recognition results in MODIS-NDVI based multi-series data caused by the low spatial resolution. Therefore, with combination of moderate and low resolution data, the winter wheat area estimation became available in large-scale region which lacks completed medium resolution images or has images covered with clouds. Meanwhile, it carried out the preliminary experiments for other crop area estimation.

Subpixel Snow Cover Mapping from MODIS Data by Nonparametric Regression Splines

NASA Astrophysics Data System (ADS)

Akyurek, Z.; Kuter, S.; Weber, G. W.

2016-12-01

Spatial extent of snow cover is often considered as one of the key parameters in climatological, hydrological and ecological modeling due to its energy storage, high reflectance in the visible and NIR regions of the electromagnetic spectrum, significant heat capacity and insulating properties. A significant challenge in snow mapping by remote sensing (RS) is the trade-off between the temporal and spatial resolution of satellite imageries. In order to tackle this issue, machine learning-based subpixel snow mapping methods, like Artificial Neural Networks (ANNs), from low or moderate resolution images have been proposed. Multivariate Adaptive Regression Splines (MARS) is a nonparametric regression tool that can build flexible models for high dimensional and complex nonlinear data. Although MARS is not often employed in RS, it has various successful implementations such as estimation of vertical total electron content in ionosphere, atmospheric correction and classification of satellite images. This study is the first attempt in RS to evaluate the applicability of MARS for subpixel snow cover mapping from MODIS data. Total 16 MODIS-Landsat ETM+ image pairs taken over European Alps between March 2000 and April 2003 were used in the study. MODIS top-of-atmospheric reflectance, NDSI, NDVI and land cover classes were used as predictor variables. Cloud-covered, cloud shadow, water and bad-quality pixels were excluded from further analysis by a spatial mask. MARS models were trained and validated by using reference fractional snow cover (FSC) maps generated from higher spatial resolution Landsat ETM+ binary snow cover maps. A multilayer feed-forward ANN with one hidden layer trained with backpropagation was also developed. The mutual comparison of obtained MARS and ANN models was accomplished on independent test areas. The MARS model performed better than the ANN model with an average RMSE of 0.1288 over the independent test areas; whereas the average RMSE of the ANN model was 0.1500. MARS estimates for low FSC values (i.e., FSC<0.3) were better than that of ANN. Both ANN and MARS tended to overestimate medium FSC values (i.e., 0.30.7).

Regression of left ventricular hypertrophy and microalbuminuria changes during antihypertensive treatment.

PubMed

Rodilla, Enrique; Pascual, Jose Maria; Costa, Jose Antonio; Martin, Joaquin; Gonzalez, Carmen; Redon, Josep

2013-08-01

The objective of the present study was to assess the regression of left ventricular hypertrophy (LVH) during antihypertensive treatment, and its relationship with the changes in microalbuminuria. One hundred and sixty-eight previously untreated patients with echocardiographic LVH, 46 (27%) with microalbuminuria, were followed during a median period of 13 months (range 6-23 months) and treated with lifestyle changes and antihypertensive drugs. Twenty-four-hour ambulatory blood pressure monitoring, echocardiography and urinary albumin excretion were assessed at the beginning and at the end of the study period. Left ventricular mass index (LVMI) was reduced from 137 [interquartile interval (IQI), 129-154] to 121 (IQI, 104-137) g/m (P < 0.001). Eighty-nine patients (53%) had a reduction in LVMI of at least 17.8 g/m, and an LVH regression rate of 43.8 per 100 patient-years [95% confidence interval (CI) 35.2-53.9]. The main factor related to LVH regression was the reduction in SBP24 h [multivariate odds ratio (ORm) 4.49; 95% CI 1.73-11.63; P = 0.005, highest tertile compared with lower tertiles]. Male sex (ORm 0.39; 95% CI 0.17-0.90; P = 0.04) and baseline glomerular filtration rate less than 90 ml/min per 1.73 m (ORm 0.39; 95% CI 0.17-0.90; P = 0.03) were associated with a lower probability of LVH regression. Patients with microalbuminuria regression (urinary albumin excretion reduction >50%) had the same odds of achieving regression of LVH as patients with normoalbuminuria (ORm 1.1; 95% CI 0.38-3.25; P = 0.85). However, those with microalbuminuria at baseline, who did not regress, had less probability of achieving LVH regression than the normoalbuminuric patients (OR 0.26; 95% CI 0.07-0.90; P = 0.03) even when adjusted for age, sex, initial LVMI, GFR, blood pressure and angiotensin-converting enzyme inhibitor (ACE-I) or angiotensin receptor blocker (ARB) treatment during the follow-up. Patients who do not have a significant reduction in microalbuminuria have less chance of achieving LVH regression, independent of blood pressure reduction.

Soil sail content estimation in the yellow river delta with satellite hyperspectral data

USGS Publications Warehouse

Weng, Yongling; Gong, Peng; Zhu, Zhi-Liang

2008-01-01

Soil salinization is one of the most common land degradation processes and is a severe environmental hazard. The primary objective of this study is to investigate the potential of predicting salt content in soils with hyperspectral data acquired with EO-1 Hyperion. Both partial least-squares regression (PLSR) and conventional multiple linear regression (MLR), such as stepwise regression (SWR), were tested as the prediction model. PLSR is commonly used to overcome the problem caused by high-dimensional and correlated predictors. Chemical analysis of 95 samples collected from the top layer of soils in the Yellow River delta area shows that salt content was high on average, and the dominant chemicals in the saline soil were NaCl and MgCl2. Multivariate models were established between soil contents and hyperspectral data. Our results indicate that the PLSR technique with laboratory spectral data has a strong prediction capacity. Spectral bands at 1487-1527, 1971-1991, 2032-2092, and 2163-2355 nm possessed large absolute values of regression coefficients, with the largest coefficient at 2203 nm. We obtained a root mean squared error (RMSE) for calibration (with 61 samples) of RMSEC = 0.753 (R2 = 0.893) and a root mean squared error for validation (with 30 samples) of RMSEV = 0.574. The prediction model was applied on a pixel-by-pixel basis to a Hyperion reflectance image to yield a quantitative surface distribution map of soil salt content. The result was validated successfully from 38 sampling points. We obtained an RMSE estimate of 1.037 (R2 = 0.784) for the soil salt content map derived by the PLSR model. The salinity map derived from the SWR model shows that the predicted value is higher than the true value. These results demonstrate that the PLSR method is a more suitable technique than stepwise regression for quantitative estimation of soil salt content in a large area. ?? 2008 CASI.

Geology of the offshore Southeast Georgia Embayment, U.S. Atlantic continental margin, based on multichannel seismic reflection profiles

USGS Publications Warehouse

Buffler, Richard T.; Watkins, Joel S.; Dillon, William P.

1979-01-01

The sedimentary section is divided into three major seismic intervals. The intervals are separated by unconformities and can be mapped regionally. The oldest interval ranges in age from Early Cretaceous through middle Late Cretaceous, although it may contain Jurassic rocks where it thickens beneath the Blake Plateau. It probably consists of continental to nearshore clastic rocks where it onlaps basement and grades seaward to a restricted carbonate platform facies (dolomite-evaporite). The middle interval (Upper Cretaceous) is characterized by prograding clinoforms interpreted as open marine slope deposits. This interval represents a Late Cretaceous shift of the carbonate shelf margin from the Blake Escarpment shoreward to about its present location, probably due to a combination of co tinued subsidence, an overall Late Cretaceous rise in sea level, and strong currents across the Blake Plateau. The youngest (Cenozoic) interval represents a continued seaward progradation of the continental shelf and slope. Cenozoic sedimentation on the Blake Plateau was much abbreviated owing mainly to strong currents.

Spatial patterns of high Aedes aegypti oviposition activity in northwestern Argentina.

PubMed

Estallo, Elizabet Lilia; Más, Guillermo; Vergara-Cid, Carolina; Lanfri, Mario Alberto; Ludueña-Almeida, Francisco; Scavuzzo, Carlos Marcelo; Introini, María Virginia; Zaidenberg, Mario; Almirón, Walter Ricardo

2013-01-01

In Argentina, dengue has affected mainly the Northern provinces, including Salta. The objective of this study was to analyze the spatial patterns of high Aedes aegypti oviposition activity in San Ramón de la Nueva Orán, northwestern Argentina. The location of clusters as hot spot areas should help control programs to identify priority areas and allocate their resources more effectively. Oviposition activity was detected in Orán City (Salta province) using ovitraps, weekly replaced (October 2005-2007). Spatial autocorrelation was measured with Moran's Index and depicted through cluster maps to identify hot spots. Total egg numbers were spatially interpolated and a classified map with Ae. aegypti high oviposition activity areas was performed. Potential breeding and resting (PBR) sites were geo-referenced. A logistic regression analysis of interpolated egg numbers and PBR location was performed to generate a predictive mapping of mosquito oviposition activity. Both cluster maps and predictive map were consistent, identifying in central and southern areas of the city high Ae. aegypti oviposition activity. A logistic regression model was successfully developed to predict Ae. aegypti oviposition activity based on distance to PBR sites, with tire dumps having the strongest association with mosquito oviposition activity. A predictive map reflecting probability of oviposition activity was produced. The predictive map delimitated an area of maximum probability of Ae. aegypti oviposition activity in the south of Orán city where tire dumps predominate. The overall fit of the model was acceptable (ROC=0.77), obtaining 99% of sensitivity and 75.29% of specificity. Distance to tire dumps is inversely associated with high mosquito activity, allowing us to identify hot spots. These methodologies are useful for prevention, surveillance, and control of tropical vector borne diseases and might assist National Health Ministry to focus resources more effectively.

Mapping the EORTC QLQ-C30 onto the EQ-5D-3L: assessing the external validity of existing mapping algorithms.

PubMed

Doble, Brett; Lorgelly, Paula

2016-04-01

To determine the external validity of existing mapping algorithms for predicting EQ-5D-3L utility values from EORTC QLQ-C30 responses and to establish their generalizability in different types of cancer. A main analysis (pooled) sample of 3560 observations (1727 patients) and two disease severity patient samples (496 and 93 patients) with repeated observations over time from Cancer 2015 were used to validate the existing algorithms. Errors were calculated between observed and predicted EQ-5D-3L utility values using a single pooled sample and ten pooled tumour type-specific samples. Predictive accuracy was assessed using mean absolute error (MAE) and standardized root-mean-squared error (RMSE). The association between observed and predicted EQ-5D utility values and other covariates across the distribution was tested using quantile regression. Quality-adjusted life years (QALYs) were calculated using observed and predicted values to test responsiveness. Ten 'preferred' mapping algorithms were identified. Two algorithms estimated via response mapping and ordinary least-squares regression using dummy variables performed well on number of validation criteria, including accurate prediction of the best and worst QLQ-C30 health states, predicted values within the EQ-5D tariff range, relatively small MAEs and RMSEs, and minimal differences between estimated QALYs. Comparison of predictive accuracy across ten tumour type-specific samples highlighted that algorithms are relatively insensitive to grouping by tumour type and affected more by differences in disease severity. Two of the 'preferred' mapping algorithms suggest more accurate predictions, but limitations exist. We recommend extensive scenario analyses if mapped utilities are used in cost-utility analyses.

Estimating cavity tree and snag abundance using negative binomial regression models and nearest neighbor imputation methods

Treesearch

Bianca N.I. Eskelson; Hailemariam Temesgen; Tara M. Barrett

2009-01-01

Cavity tree and snag abundance data are highly variable and contain many zero observations. We predict cavity tree and snag abundance from variables that are readily available from forest cover maps or remotely sensed data using negative binomial (NB), zero-inflated NB, and zero-altered NB (ZANB) regression models as well as nearest neighbor (NN) imputation methods....

Fast metabolite identification with Input Output Kernel Regression.

PubMed

Brouard, Céline; Shen, Huibin; Dührkop, Kai; d'Alché-Buc, Florence; Böcker, Sebastian; Rousu, Juho

2016-06-15

An important problematic of metabolomics is to identify metabolites using tandem mass spectrometry data. Machine learning methods have been proposed recently to solve this problem by predicting molecular fingerprint vectors and matching these fingerprints against existing molecular structure databases. In this work we propose to address the metabolite identification problem using a structured output prediction approach. This type of approach is not limited to vector output space and can handle structured output space such as the molecule space. We use the Input Output Kernel Regression method to learn the mapping between tandem mass spectra and molecular structures. The principle of this method is to encode the similarities in the input (spectra) space and the similarities in the output (molecule) space using two kernel functions. This method approximates the spectra-molecule mapping in two phases. The first phase corresponds to a regression problem from the input space to the feature space associated to the output kernel. The second phase is a preimage problem, consisting in mapping back the predicted output feature vectors to the molecule space. We show that our approach achieves state-of-the-art accuracy in metabolite identification. Moreover, our method has the advantage of decreasing the running times for the training step and the test step by several orders of magnitude over the preceding methods. celine.brouard@aalto.fi Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Fast metabolite identification with Input Output Kernel Regression

PubMed Central

Brouard, Céline; Shen, Huibin; Dührkop, Kai; d'Alché-Buc, Florence; Böcker, Sebastian; Rousu, Juho

2016-01-01

Motivation: An important problematic of metabolomics is to identify metabolites using tandem mass spectrometry data. Machine learning methods have been proposed recently to solve this problem by predicting molecular fingerprint vectors and matching these fingerprints against existing molecular structure databases. In this work we propose to address the metabolite identification problem using a structured output prediction approach. This type of approach is not limited to vector output space and can handle structured output space such as the molecule space. Results: We use the Input Output Kernel Regression method to learn the mapping between tandem mass spectra and molecular structures. The principle of this method is to encode the similarities in the input (spectra) space and the similarities in the output (molecule) space using two kernel functions. This method approximates the spectra-molecule mapping in two phases. The first phase corresponds to a regression problem from the input space to the feature space associated to the output kernel. The second phase is a preimage problem, consisting in mapping back the predicted output feature vectors to the molecule space. We show that our approach achieves state-of-the-art accuracy in metabolite identification. Moreover, our method has the advantage of decreasing the running times for the training step and the test step by several orders of magnitude over the preceding methods. Availability and implementation: Contact: celine.brouard@aalto.fi Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307628

QTLs for Seed Vigor-Related Traits Identified in Maize Seeds Germinated under Artificial Aging Conditions

PubMed Central

Han, Zanping; Ku, Lixia; Zhang, Zhenzhen; Zhang, Jun; Guo, ShuLei; Liu, Haiying; Zhao, Ruifang; Ren, Zhenzhen; Zhang, Liangkun; Su, Huihui; Dong, Lei; Chen, Yanhui

2014-01-01

High seed vigor is important for agricultural production due to the associated potential for increased growth and productivity. However, a better understanding of the underlying molecular mechanisms is required because the genetic basis for seed vigor remains unknown. We used single-nucleotide polymorphism (SNP) markers to map quantitative trait loci (QTLs) for four seed vigor traits in two connected recombinant inbred line (RIL) maize populations under four treatment conditions during seed germination. Sixty-five QTLs distributed between the two populations were identified and a meta-analysis was used to integrate genetic maps. Sixty-one initially identified QTLs were integrated into 18 meta-QTLs (mQTLs). Initial QTLs with contribution to phenotypic variation values of R2>10% were integrated into mQTLs. Twenty-three candidate genes for association with seed vigor traits coincided with 13 mQTLs. The candidate genes had functions in the glycolytic pathway and in protein metabolism. QTLs with major effects (R2>10%) were identified under at least one treatment condition for mQTL2, mQTL3-2, and mQTL3-4. Candidate genes included a calcium-dependent protein kinase gene (302810918) involved in signal transduction that mapped in the mQTL3-2 interval associated with germination energy (GE) and germination percentage (GP), and an hsp20/alpha crystallin family protein gene (At5g51440) that mapped in the mQTL3-4 interval associated with GE and GP. Two initial QTLs with a major effect under at least two treatment conditions were identified for mQTL5-2. A cucumisin-like Ser protease gene (At5g67360) mapped in the mQTL5-2 interval associated with GP. The chromosome regions for mQTL2, mQTL3-2, mQTL3-4, and mQTL5-2 may be hot spots for QTLs related to seed vigor traits. The mQTLs and candidate genes identified in this study provide valuable information for the identification of additional quantitative trait genes. PMID:24651614

QTLs for seed vigor-related traits identified in maize seeds germinated under artificial aging conditions.

PubMed

Han, Zanping; Ku, Lixia; Zhang, Zhenzhen; Zhang, Jun; Guo, Shulei; Liu, Haiying; Zhao, Ruifang; Ren, Zhenzhen; Zhang, Liangkun; Su, Huihui; Dong, Lei; Chen, Yanhui

2014-01-01

High seed vigor is important for agricultural production due to the associated potential for increased growth and productivity. However, a better understanding of the underlying molecular mechanisms is required because the genetic basis for seed vigor remains unknown. We used single-nucleotide polymorphism (SNP) markers to map quantitative trait loci (QTLs) for four seed vigor traits in two connected recombinant inbred line (RIL) maize populations under four treatment conditions during seed germination. Sixty-five QTLs distributed between the two populations were identified and a meta-analysis was used to integrate genetic maps. Sixty-one initially identified QTLs were integrated into 18 meta-QTLs (mQTLs). Initial QTLs with contribution to phenotypic variation values of R(2)>10% were integrated into mQTLs. Twenty-three candidate genes for association with seed vigor traits coincided with 13 mQTLs. The candidate genes had functions in the glycolytic pathway and in protein metabolism. QTLs with major effects (R(2)>10%) were identified under at least one treatment condition for mQTL2, mQTL3-2, and mQTL3-4. Candidate genes included a calcium-dependent protein kinase gene (302810918) involved in signal transduction that mapped in the mQTL3-2 interval associated with germination energy (GE) and germination percentage (GP), and an hsp20/alpha crystallin family protein gene (At5g51440) that mapped in the mQTL3-4 interval associated with GE and GP. Two initial QTLs with a major effect under at least two treatment conditions were identified for mQTL5-2. A cucumisin-like Ser protease gene (At5g67360) mapped in the mQTL5-2 interval associated with GP. The chromosome regions for mQTL2, mQTL3-2, mQTL3-4, and mQTL5-2 may be hot spots for QTLs related to seed vigor traits. The mQTLs and candidate genes identified in this study provide valuable information for the identification of additional quantitative trait genes.

Multiple interval QTL mapping and searching for PSTOL1 homologs associated with root morphology, biomass accumulation and phosphorus content in maize seedlings under low-P.

PubMed

Azevedo, Gabriel C; Cheavegatti-Gianotto, Adriana; Negri, Bárbara F; Hufnagel, Bárbara; E Silva, Luciano da Costa; Magalhaes, Jurandir V; Garcia, Antonio Augusto F; Lana, Ubiraci G P; de Sousa, Sylvia M; Guimaraes, Claudia T

2015-07-07

Modifications in root morphology are important strategies to maximize soil exploitation under phosphorus starvation in plants. Here, we used two multiple interval models to map QTLs related to root traits, biomass accumulation and P content in a maize RIL population cultivated in nutrient solution. In addition, we searched for putative maize homologs to PSTOL1, a gene responsible to enhance early root growth, P uptake and grain yield in rice and sorghum. Based on path analysis, root surface area was the root morphology component that most strongly contributed to total dry weight and to P content in maize seedling under low-P availability. Multiple interval mapping models for single (MIM) and multiple traits (MT-MIM) were combined and revealed 13 genomic regions significantly associated with the target traits in a complementary way. The phenotypic variances explained by all QTLs and their epistatic interactions using MT-MIM (23.4 to 35.5 %) were higher than in previous studies, and presented superior statistical power. Some of these QTLs were coincident with QTLs for root morphology traits and grain yield previously mapped, whereas others harbored ZmPSTOL candidate genes, which shared more than 55 % of amino acid sequence identity and a conserved serine/threonine kinase domain with OsPSTOL1. Additionally, four ZmPSTOL candidate genes co-localized with QTLs for root morphology, biomass accumulation and/or P content were preferentially expressed in roots of the parental lines that contributed the alleles enhancing the respective phenotypes. QTL mapping strategies adopted in this study revealed complementary results for single and multiple traits with high accuracy. Some QTLs, mainly the ones that were also associated with yield performance in other studies, can be good targets for marker-assisted selection to improve P-use efficiency in maize. Based on the co-localization with QTLs, the protein domain conservation and the coincidence of gene expression, we selected novel maize genes as putative homologs to PSTOL1 that will require further validation studies.

Contig Maps and Genomic Sequencing Identify Candidate Genes in the Usher 1C Locus

PubMed Central

Higgins, Michael J.; Day, Colleen D.; Smilinich, Nancy J.; Ni, L.; Cooper, Paul R.; Nowak, Norma J.; Davies, Chris; de Jong, Pieter J.; Hejtmancik, Fielding; Evans, Glen A.; Smith, Richard J.H.; Shows, Thomas B.

1998-01-01

Usher syndrome 1C (USH1C) is a congenital condition manifesting profound hearing loss, the absence of vestibular function, and eventual retinal degeneration. The USH1C locus has been mapped genetically to a 2- to 3-cM interval in 11p14–15.1 between D11S899 and D11S861. In an effort to identify the USH1C disease gene we have isolated the region between these markers in yeast artificial chromosomes (YACs) using a combination of STS content mapping and Alu–PCR hybridization. The YAC contig is ∼3.5 Mb and has located several other loci within this interval, resulting in the order CEN-LDHA-SAA1-TPH-D11S1310-(D11S1888/KCNC1)-MYOD1-D11S902D11S921-D11S1890-TEL. Subsequent haplotyping and homozygosity analysis refined the location of the disease gene to a 400-kb interval between D11S902 and D11S1890 with all affected individuals being homozygous for the internal marker D11S921. To facilitate gene identification, the critical region has been converted into P1 artificial chromosome (PAC) clones using sequence-tagged sites (STSs) mapped to the YAC contig, Alu–PCR products generated from the YACs, and PAC end probes. A contig of >50 PAC clones has been assembled between D11S1310 and D11S1890, confirming the order of markers used in haplotyping. Three PAC clones representing nearly two-thirds of the USH1C critical region have been sequenced. PowerBLAST analysis identified six clusters of expressed sequence tags (ESTs), two known genes (BIR,SUR1) mapped previously to this region, and a previously characterized but unmapped gene NEFA (DNA binding/EF hand/acidic amino-acid-rich). GRAIL analysis identified 11 CpG islands and 73 exons of excellent quality. These data allowed the construction of a transcription map for the USH1C critical region, consisting of three known genes and six or more novel transcripts. Based on their map location, these loci represent candidate disease loci for USH1C. The NEFA gene was assessed as the USH1C locus by the sequencing of an amplified NEFA cDNA from an USH1C patient; however, no mutations were detected. [The sequence data described in this paper have been submitted to GenBank under accession numbers AC000406–AC000407.] PMID:9445488

Prehospital management and fluid resuscitation in hypotensive trauma patients admitted to Karolinska University Hospital in Stockholm.

PubMed

Talving, Peep; Pålstedt, Joakim; Riddez, Louis

2005-01-01

Few previous studies have been conducted on the prehospital management of hypotensive trauma patients in Stockholm County. The aim of this study was to describe the prehospital management of hypotensive trauma patients admitted to the largest trauma center in Sweden, and to assess whether prehospital trauma life support (PHTLS) guidelines have been implemented regarding prehospital time intervals and fluid therapy. In addition, the effects of the age, type of injury, injury severity, prehospital time interval, blood pressure, and fluid therapy on outcome were investigated. This is a retrospective, descriptive study on consecutive, hypotensive trauma patients (systolic blood pressure < or = 90 mmHg on the scene of injury) admitted to Karolinska University Hospital in Stockholm, Sweden, during 2001-2003. The reported values are medians with interquartile ranges. Basic demographics, prehospital time intervals and interventions, injury severity scores (ISS), type and volumes of prehospital fluid resuscitation, and 30-day mortality were abstracted. The effects of the patient's age, gender, prehospital time interval, type of injury, injury severity, on-scene and emergency department blood pressure, and resuscitation fluid volumes on mortality were analyzed using the exact logistic regression model. In 102 (71 male) adult patients (age > or = 15 years) recruited, the median age was 35.5 years (range: 27-55 years) and 77 patients (75%) had suffered blunt injury. The predominant trauma mechanisms were falls between levels (24%) and motor vehicle crashes (22%) with an ISS of 28.5 (range: 16-50). The on-scene time interval was 19 minutes (range: 12-24 minutes). Fluid therapy was initiated at the scene of injury in the majority of patients (73%) regardless of the type of injury (77 blunt [75%] / 25 penetrating [25%]) or injury severity (ISS: 0-20; 21-40; 41-75). Age (odds ratio (OR) = 1.04), male gender (OR = 3.2), ISS 21-40 (OR = 13.6), and ISS >40 (OR = 43.6) were the significant factors affecting outcome in the exact logistic regression analysis. The time interval at the scene of injury exceeded PHTLS guidelines. The vast majority of the hypotensive trauma patients were fluid-resuscitated on-scene regardless of the type, mechanism, or severity of injury. A predefined fluid resuscitation regimen is not employed in hypotensive trauma victims with different types of injuries. The outcome was worsened by male gender, progressive age, and ISS > 20 in the exact multiple regression analysis.

Detecting spatio-temporal changes in agricultural land use in Heilongjiang province, China using MODIS time-series data and a random forest regression model

NASA Astrophysics Data System (ADS)

Hu, Q.; Friedl, M. A.; Wu, W.

2017-12-01

Accurate and timely information regarding the spatial distribution of crop types and their changes is essential for acreage surveys, yield estimation, water management, and agricultural production decision-making. In recent years, increasing population, dietary shifts and climate change have driven drastic changes in China's agricultural land use. However, no maps are currently available that document the spatial and temporal patterns of these agricultural land use changes. Because of its short revisit period, rich spectral bands and global coverage, MODIS time series data has been shown to have great potential for detecting the seasonal dynamics of different crop types. However, its inherently coarse spatial resolution limits the accuracy with which crops can be identified from MODIS in regions with small fields or complex agricultural landscapes. To evaluate this more carefully and specifically understand the strengths and weaknesses of MODIS data for crop-type mapping, we used MODIS time-series imagery to map the sub-pixel fractional crop area for four major crop types (rice, corn, soybean and wheat) at 500-m spatial resolution for Heilongjiang province, one of the most important grain-production regions in China where recent agricultural land use change has been rapid and pronounced. To do this, a random forest regression (RF-g) model was constructed to estimate the percentage of each sub-pixel crop type in 2006, 2011 and 2016. Crop type maps generated through expert visual interpretation of high spatial resolution images (i.e., Landsat and SPOT data) were used to calibrate the regression model. Five different time series of vegetation indices (155 features) derived from different spectral channels of MODIS land surface reflectance (MOD09A1) data were used as candidate features for the RF-g model. An out-of-bag strategy and backward elimination approach was applied to select the optimal spectra-temporal feature subset for each crop type. The resulting crop maps were assessed in two ways: (1) wall-to-wall pixel comparison with corresponding high spatial resolution reference maps; and (2) county-level comparison with census data. Based on these derived maps, changes in crop type, total area, and spatial patterns of change in Heilongjiang province during 2006-2016 were analyzed.

Comparison of two landslide susceptibility assessments in the Champagne-Ardenne region (France)

NASA Astrophysics Data System (ADS)

Den Eeckhaut, M. Van; Marre, A.; Poesen, J.

2010-02-01

The vineyards of the Montagne de Reims are mostly planted on steep south-oriented cuesta fronts receiving a maximum of sun radiation. Due to the location of the vineyards on steep hillslopes, the viticultural activity is threatened by slope failures. This study attempts to better understand the spatial patterns of landslide susceptibility in the Champagne-Ardenne region by comparing a heuristic (qualitative) and a statistical (quantitative) model in a 1120 km² study area. The heuristic landslide susceptibility model was adopted from the Bureau de Recherches Géologiques et Minières, the GEGEAA - Reims University and the Comité Interprofessionnel du Vin de Champagne. In this model, expert knowledge of the region was used to assign weights to all slope classes and lithologies present in the area, but the final susceptibility map was never evaluated with the location of mapped landslides. For the statistical landslide susceptibility assessment, logistic regression was applied to a dataset of 291 'old' (Holocene) landslides. The robustness of the logistic regression model was evaluated and ROC curves were used for model calibration and validation. With regard to the variables assumed to be important environmental factors controlling landslides, the two models are in agreement. They both indicate that present and future landslides are mainly controlled by slope gradient and lithology. However, the comparison of the two landslide susceptibility maps through (1) an evaluation with the location of mapped 'old' landslides and through (2) a temporal validation with spatial data of 'recent' (1960-1999; n = 48) and 'very recent' (2000-2008; n = 46) landslides showed a better prediction capacity for the statistical model produced in this study compared to the heuristic model. In total, the statistically-derived landslide susceptibility map succeeded in correctly classifying 81.0% of the 'old' and 91.6% of the 'recent' and 'very recent' landslides. On the susceptibility map derived from the heuristic model, on the other hand, only 54.6% of the 'old' and 64.0% of the 'recent' and 'very recent' landslides were correctly classified as unstable. Hence, the landslide susceptibility map obtained from logistic regression is a better tool for regional landslide susceptibility analysis in the study area of the Montagne de Reims. The accurate classification of zones with very high and high susceptibility allows delineating zones where viticulturists should be informed and where implementation of precaution measures is needed to secure slope stability.

Harmonization of Multiple Forest Disturbance Data to Create a 1986-2011 Database for the Conterminous United States

NASA Astrophysics Data System (ADS)

Soulard, C. E.; Acevedo, W.; Yang, Z.; Cohen, W. B.; Stehman, S. V.; Taylor, J. L.

2015-12-01

A wide range of spatial forest disturbance data exist for the conterminous United States, yet inconsistencies between map products arise because of differing programmatic objectives and methodologies. Researchers on the Land Change Research Project (LCRP) are working to assess spatial agreement, characterize uncertainties, and resolve discrepancies between these national level datasets, in regard to forest disturbance. Disturbance maps from the Global Forest Change (GFC), Landfire Vegetation Disturbance (LVD), National Land Cover Dataset (NLCD), Vegetation Change Tracker (VCT), Web-enabled Landsat Data (WELD), and Monitoring Trends in Burn Severity (MTBS) were harmonized using a pixel-based data fusion process. The harmonization process reconciled forest harvesting, forest fire, and remaining forest disturbance across four intervals (1986-1992, 1992-2001, 2001-2006, and 2006-2011) by relying on convergence of evidence across all datasets available for each interval. Pixels with high agreement across datasets were retained, while moderate-to-low agreement pixels were visually assessed and either manually edited using reference imagery or discarded from the final disturbance map(s). National results show that annual rates of forest harvest and overall fire have increased over the past 25 years. Overall, this study shows that leveraging the best elements of readily-available data improves forest loss monitoring relative to using a single dataset to monitor forest change, particularly by reducing commission errors.

Mapping the spatial pattern of temperate forest above ground biomass by integrating airborne lidar with Radarsat-2 imagery via geostatistical models

NASA Astrophysics Data System (ADS)

Li, Wang; Niu, Zheng; Gao, Shuai; Wang, Cheng

2014-11-01

Light Detection and Ranging (LiDAR) and Synthetic Aperture Radar (SAR) are two competitive active remote sensing techniques in forest above ground biomass estimation, which is important for forest management and global climate change study. This study aims to further explore their capabilities in temperate forest above ground biomass (AGB) estimation by emphasizing the spatial auto-correlation of variables obtained from these two remote sensing tools, which is a usually overlooked aspect in remote sensing applications to vegetation studies. Remote sensing variables including airborne LiDAR metrics, backscattering coefficient for different SAR polarizations and their ratio variables for Radarsat-2 imagery were calculated. First, simple linear regression models (SLR) was established between the field-estimated above ground biomass and the remote sensing variables. Pearson's correlation coefficient (R2) was used to find which LiDAR metric showed the most significant correlation with the regression residuals and could be selected as co-variable in regression co-kriging (RCoKrig). Second, regression co-kriging was conducted by choosing the regression residuals as dependent variable and the LiDAR metric (Hmean) with highest R2 as co-variable. Third, above ground biomass over the study area was estimated using SLR model and RCoKrig model, respectively. The results for these two models were validated using the same ground points. Results showed that both of these two methods achieved satisfactory prediction accuracy, while regression co-kriging showed the lower estimation error. It is proved that regression co-kriging model is feasible and effective in mapping the spatial pattern of AGB in the temperate forest using Radarsat-2 data calibrated by airborne LiDAR metrics.

Mapping hurricane rita inland storm tide

USGS Publications Warehouse

Berenbrock, C.; Mason, R.R.; Blanchard, S.F.

2009-01-01

Flood-inundation data are most useful for decision makers when presented in the context of maps of affected communities and (or) areas. But because the data are scarce and rarely cover the full extent of the flooding, interpolation and extrapolation of the information are needed. Many geographic information systems provide various interpolation tools, but these tools often ignore the effects of the topographic and hydraulic features that influence flooding. A barrier mapping method was developed to improve maps of storm tide produced by Hurricane Rita. Maps were developed for the maximum storm tide and at 3-h intervals from midnight (00:00 hours) through noon (12:00 hours) on 24 September 2005. The improved maps depict storm-tide elevations and the extent of flooding. The extent of storm-tide inundation from the improved maximum storm-tide map was compared with the extent of flood inundation from a map prepared by the Federal Emergency Management Agency (FEMA). The boundaries from these two maps generally compared quite well especially along the Calcasieu River. Also a cross-section profile that parallels the Louisiana coast was developed from the maximum storm-tide map and included FEMA high-water marks. ?? 2009 Blackwell Publishing Ltd.

Mapping Hurricane Rita inland storm tide

USGS Publications Warehouse

Berenbrock, Charles; Mason, Jr., Robert R.; Blanchard, Stephen F.; Simonovic, Slobodan P.

2009-01-01

Flood-inundation data are most useful for decision makers when presented in the context of maps of effected communities and (or) areas. But because the data are scarce and rarely cover the full extent of the flooding, interpolation and extrapolation of the information are needed. Many geographic information systems (GIS) provide various interpolation tools, but these tools often ignore the effects of the topographic and hydraulic features that influence flooding. A barrier mapping method was developed to improve maps of storm tide produced by Hurricane Rita. Maps were developed for the maximum storm tide and at 3-hour intervals from midnight (0000 hour) through noon (1200 hour) on September 24, 2005. The improved maps depict storm-tide elevations and the extent of flooding. The extent of storm-tide inundation from the improved maximum storm-tide map was compared to the extent of flood-inundation from a map prepared by the Federal Emergency Management Agency (FEMA). The boundaries from these two maps generally compared quite well especially along the Calcasieu River. Also a cross-section profile that parallels the Louisiana coast was developed from the maximum storm-tide map and included FEMA high-water marks.

Integrated consensus genetic and physical maps of flax (Linum usitatissimum L.).

PubMed

Cloutier, Sylvie; Ragupathy, Raja; Miranda, Evelyn; Radovanovic, Natasa; Reimer, Elsa; Walichnowski, Andrzej; Ward, Kerry; Rowland, Gordon; Duguid, Scott; Banik, Mitali

2012-12-01

Three linkage maps of flax (Linum usitatissimum L.) were constructed from populations CDC Bethune/Macbeth, E1747/Viking and SP2047/UGG5-5 containing between 385 and 469 mapped markers each. The first consensus map of flax was constructed incorporating 770 markers based on 371 shared markers including 114 that were shared by all three populations and 257 shared between any two populations. The 15 linkage group map corresponds to the haploid number of chromosomes of this species. The marker order of the consensus map was largely collinear in all three individual maps but a few local inversions and marker rearrangements spanning short intervals were observed. Segregation distortion was present in all linkage groups which contained 1-52 markers displaying non-Mendelian segregation. The total length of the consensus genetic map is 1,551 cM with a mean marker density of 2.0 cM. A total of 670 markers were anchored to 204 of the 416 fingerprinted contigs of the physical map corresponding to ~274 Mb or 74 % of the estimated flax genome size of 370 Mb. This high resolution consensus map will be a resource for comparative genomics, genome organization, evolution studies and anchoring of the whole genome shotgun sequence.

Does blood transfusion affect intermediate survival after coronary artery bypass surgery?

PubMed

Mikkola, R; Heikkinen, J; Lahtinen, J; Paone, R; Juvonen, T; Biancari, F

2013-01-01

The aim of this study was to investigate the impact of transfusion of blood products on intermediate outcome after coronary artery bypass surgery. Complete data on perioperative blood transfusion in patients undergoing coronary artery bypass surgery were available from 2001 patients who were operated at our institution. Transfusion of any blood product (relative risk = 1.678, 95% confidence interval = 1.087-2.590) was an independent predictor of all-cause mortality. The additive effect of each blood product on all-cause mortality (relative risk = 1.401, 95% confidence interval = 1.203-1.630) and cardiac mortality (relative risk = 1.553, 95% confidence interval = 1.273-1.895) was evident when the sum of each blood product was included in the regression models. However, when single blood products were included in the regression model, transfusion of fresh frozen plasma/Octaplas® was the only blood product associated with increased risk of all-cause mortality (relative risk = 1.692, 95% confidence interval = 1.222-2.344) and cardiac mortality (relative risk = 2.125, 95% confidence interval = 1.414-3.194). The effect of blood product transfusion was particularly evident during the first three postoperative months. Since follow-up was truncated at 3 months, transfusion of any blood product was a significant predictor of all-cause mortality (relative risk = 2.998, 95% confidence interval = 1.053-0.537). Analysis of patients who survived or had at least 3 months of potential follow-up showed that transfusion of any blood product was not associated with a significantly increased risk of intermediate all-cause mortality (relative risk = 1.430, 95% confidence interval = 0.880-2.323). Transfusion of any blood product is associated with a significant risk of all-cause and cardiac mortality after coronary artery bypass surgery. Such a risk seems to be limited to the early postoperative period and diminishes later on. Among blood products, perioperative use of fresh frozen plasma or Octaplas seems to be the main determinant of mortality.

Quantitative imaging biomarkers: Effect of sample size and bias on confidence interval coverage.

PubMed

Obuchowski, Nancy A; Bullen, Jennifer

2017-01-01

Introduction Quantitative imaging biomarkers (QIBs) are being increasingly used in medical practice and clinical trials. An essential first step in the adoption of a quantitative imaging biomarker is the characterization of its technical performance, i.e. precision and bias, through one or more performance studies. Then, given the technical performance, a confidence interval for a new patient's true biomarker value can be constructed. Estimating bias and precision can be problematic because rarely are both estimated in the same study, precision studies are usually quite small, and bias cannot be measured when there is no reference standard. Methods A Monte Carlo simulation study was conducted to assess factors affecting nominal coverage of confidence intervals for a new patient's quantitative imaging biomarker measurement and for change in the quantitative imaging biomarker over time. Factors considered include sample size for estimating bias and precision, effect of fixed and non-proportional bias, clustered data, and absence of a reference standard. Results Technical performance studies of a quantitative imaging biomarker should include at least 35 test-retest subjects to estimate precision and 65 cases to estimate bias. Confidence intervals for a new patient's quantitative imaging biomarker measurement constructed under the no-bias assumption provide nominal coverage as long as the fixed bias is <12%. For confidence intervals of the true change over time, linearity must hold and the slope of the regression of the measurements vs. true values should be between 0.95 and 1.05. The regression slope can be assessed adequately as long as fixed multiples of the measurand can be generated. Even small non-proportional bias greatly reduces confidence interval coverage. Multiple lesions in the same subject can be treated as independent when estimating precision. Conclusion Technical performance studies of quantitative imaging biomarkers require moderate sample sizes in order to provide robust estimates of bias and precision for constructing confidence intervals for new patients. Assumptions of linearity and non-proportional bias should be assessed thoroughly.

Annual regression-based estimates of evapotranspiration for the contiguous United States based on climate, remote sensing, and stream gage data

NASA Astrophysics Data System (ADS)

Reitz, M. D.; Sanford, W. E.; Senay, G. B.; Cazenas, J.

2015-12-01

Evapotranspiration (ET) is a key quantity in the hydrologic cycle, accounting for ~70% of precipitation across the contiguous United States (CONUS). However, it is a challenge to estimate, due to difficulty in making direct measurements and gaps in our theoretical understanding. Here we present a new data-driven, ~1km2 resolution map of long-term average actual evapotranspiration rates across the CONUS. The new ET map is a function of the USGS Landsat-derived National Land Cover Database (NLCD), precipitation, temperature, and daily average temperature range (from the PRISM climate dataset), and is calibrated to long-term water balance data from 679 watersheds. It is unique from previously presented ET maps in that (1) it was co-developed with estimates of runoff and recharge; (2) the regression equation was chosen from among many tested, previously published and newly proposed functional forms for its optimal description of long-term water balance ET data; (3) it has values over open-water areas that are derived from separate mass-transfer and humidity equations; and (4) the data include additional precipitation representing amounts converted from 2005 USGS water-use census irrigation data. The regression equation is calibrated using data from 2000-2013, but can also be applied to individual years with their corresponding input datasets. Comparisons among this new map, the more detailed remote-sensing-based estimates of MOD16 and SSEBop, and AmeriFlux ET tower measurements shows encouraging consistency, and indicates that the empirical ET estimate approach presented here produces closer agreement with independent flux tower data for annual average actual ET than other more complex remote sensing approaches.

Reproductive and Birth Outcomes in Haiti Before and After the 2010 Earthquake.

PubMed

Harville, Emily W; Do, Mai

2016-02-01

We aimed to examine the relationship between exposure to the 2010 Haiti earthquake and pregnancy wantedness, interpregnancy interval, and birth weight. From the nationally representative Haiti 2012 Demographic and Health Survey, information on "size of child at birth" (too small or not) was available for 7280 singleton births in the previous 5 years, whereas information on birth weight was available for 1607 births. Pregnancy wantedness, short (<1 year) interpregnancy interval, and maternal-reported birth weight were compared before and after the earthquake and by level of damage. Multiple logistic regression and linear regression analyses were conducted. Post-earthquake births were less likely to be wanted and more likely to be born after a short interpregnancy interval. Earthquake exposure was associated with increased likelihood of a child being born too small: timing of birth (after earthquake vs. before earthquake, adjusted odds ratio [aOR]: 1.27, 95% confidence interval [CI]: 1.12-1.45), region (hardest-hit vs. rest of country; aOR: 1.43, 95% CI: 1.14- 1.80), and house damage (aOR: 1.27 95% CI: 1.02-1.58). Mean birth weight was 150 to 300 g lower in those exposed to the earthquake. Experience with the earthquake was associated with worse reproductive and birth outcomes, which underscores the need to provide reproductive health services as part of relief efforts.

High-resolution mapping and genetic characterization of the Lazy-2 gravitropic mutant of tomato

NASA Technical Reports Server (NTRS)

Behringer, F. J.; Lomax, T. L.

1999-01-01

Mutation of the Lazy-2 (Lz-2) gene in tomato (Lycopersicon esculentum mill.) produces a phytochrome-dependent reversal of shoot gravitropism, providing a unique genetic resource for investigating how signals from light modulate gravitropism. We mapped the Lz-2 gene using RFLPs and a PCR-based technique to assess the feasibility of positional cloning. Analysis of a 1338 plant backcross population between L. esculentum and L. pennellii placed Lz-2 within a 1.2 cM interval on chromosome 5, 0.4 cM from TG504-CT201A interval. The inabililty to resolve these markers indicates that Lz-2 resides in a centromeric region in which recombination is highly suppressed. Lazy-2 is tightly linked to but does not encode the gene for ACC4, an enzyme involved in ethylene biosynthesis. We also observed that Lz-2 is partially dominant under certain conditions and stages of development.