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EPA Science Inventory

An exact expression is given for the jackknife estimate of the number of species in a community and its variance when one uses quadrat sampling procedures. The jackknife estimate is a function of the number of species that occur in one and only one quadrat. The variance of the nu...


Confidence Intervals for Random Forests: The Jackknife and the Infinitesimal Jackknife  

PubMed Central

We study the variability of predictions made by bagged learners and random forests, and show how to estimate standard errors for these methods. Our work builds on variance estimates for bagging proposed by Efron (1992, 2013) that are based on the jackknife and the infinitesimal jackknife (IJ). In practice, bagged predictors are computed using a finite number B of bootstrap replicates, and working with a large B can be computationally expensive. Direct applications of jackknife and IJ estimators to bagging require B = ?(n1.5) bootstrap replicates to converge, where n is the size of the training set. We propose improved versions that only require B = ?(n) replicates. Moreover, we show that the IJ estimator requires 1.7 times less bootstrap replicates than the jackknife to achieve a given accuracy. Finally, we study the sampling distributions of the jackknife and IJ variance estimates themselves. We illustrate our findings with multiple experiments and simulation studies.

Wager, Stefan; Hastie, Trevor; Efron, Bradley



The Infinitesimal Jackknife with Exploratory Factor Analysis  

ERIC Educational Resources Information Center

The infinitesimal jackknife, a nonparametric method for estimating standard errors, has been used to obtain standard error estimates in covariance structure analysis. In this article, we adapt it for obtaining standard errors for rotated factor loadings and factor correlations in exploratory factor analysis with sample correlation matrices. Both…

Zhang, Guangjian; Preacher, Kristopher J.; Jennrich, Robert I.



Reduced Bias Autocorrelation Estimation: Three Jackknife Methods.  

ERIC Educational Resources Information Center

Effectiveness of jackknife methods in reducing bias in estimation of the log-1 autocorrelation parameter p1 was evaluated through a Monte Carlo study using sample sizes ranging from 6 to 500. These estimates appear less biased in the small sample case than many that have been investigated recently. (SLD)

Huitema, Bradley E.; McKean, Joseph W.



Tests for the Jackknife Autocorrelation Estimator "r(Q2)."  

ERIC Educational Resources Information Center

Two tests for the jackknife autocorrelation estimator r(Q2) are evaluated. It is shown that a test based on the conventional approach for estimating the standard error of a jackknife estimator leads to unacceptable Type I error. An alternative approach is proposed that leads to a more satisfactory test when n>20. (Author/SLD)

Huitema, Bradley E.; McKean, Joseph W.



A Simple Model for the Determination of Jackknifing  

Microsoft Academic Search

Jackknifing is uncontrolled braking of a truck-trailer combination which causes the trailer rotates relative to tractor and as a result extends to adjacent lanes, causing in many cases sever accidents. In this paper a simple two dimensional model is presented. The model includes parameters such as truck's and trailer's dimensions, coefficients of friction, masses, location of the load on the

Oren Masory; Grainer Thomas


A comment on the 'jack-knife' technique for analysing enzyme-kinetic data.  

PubMed Central

The use of the 'jack-knife' technique in the analysis of enzyme-kinetic data [Cornish-Bowden & Wong (1978] Biochem. J. 175, 969--976) is examined. The method can give parameter estimates that appear to be incorrect. PMID:486158

Duggleby, R G



The jackknife as an approach for uncertainty assessment in gamma spectrometric measurements of uranium isotope ratios  

Microsoft Academic Search

The jackknife as an approach for uncertainty estimation in gamma spectrometric uranium isotope ratio measurements was evaluated. Five different materials ranging from depleted uranium (DU) to high enriched uranium (HEU) were measured using gamma spectrometry. High resolution inductively coupled plasma mass spectrometry (ICP-SFMS) was used as a reference method for comparing the results obtained with the gamma spectrometric method. The

H. Ramebäck; A. Vesterlund; A. Tovedal; U. Nygren; L. Wallberg; E. Holm; C. Ekberg; G. Skarnemark



The jackknife as an approach for uncertainty assessment in gamma spectrometric measurements of uranium isotope ratios  

NASA Astrophysics Data System (ADS)

The jackknife as an approach for uncertainty estimation in gamma spectrometric uranium isotope ratio measurements was evaluated. Five different materials ranging from depleted uranium (DU) to high enriched uranium (HEU) were measured using gamma spectrometry. High resolution inductively coupled plasma mass spectrometry (ICP-SFMS) was used as a reference method for comparing the results obtained with the gamma spectrometric method. The relative combined uncertainty in the gamma spectrometric measurements of the 238U/ 235U isotope ratio using the jackknife was about 10-20% ( k = 2), which proved to be fit-for-purpose in order to distinguish between different uranium categories. Moreover, the enrichment of 235U in HEU could be measured with an uncertainty of 1-2%.

Ramebäck, H.; Vesterlund, A.; Tovedal, A.; Nygren, U.; Wallberg, L.; Holm, E.; Ekberg, C.; Skarnemark, G.



Modified Jack-knife estimation of parameter uncertainty in bilinear modelling by partial least squares regression (PLSR)  

Microsoft Academic Search

A method for assessing the uncertainty of the individual bilinear model parameters from two-block regression modelling by multivariate partial least squares regression (PLSR) is presented. The method is based on the so-called “Jack-knife” resampling, comparing the perturbed model parameter estimates from cross-validation with the estimates from the full model. The conventional jack-knifing from ordinary least squares regression is modified in

Harald Martens; Magni Martens



The efficiency of different search strategies in estimating parsimony jackknife, bootstrap, and Bremer support  

PubMed Central

Background For parsimony analyses, the most common way to estimate confidence is by resampling plans (nonparametric bootstrap, jackknife), and Bremer support (Decay indices). The recent literature reveals that parameter settings that are quite commonly employed are not those that are recommended by theoretical considerations and by previous empirical studies. The optimal search strategy to be applied during resampling was previously addressed solely via standard search strategies available in PAUP*. The question of a compromise between search extensiveness and improved support accuracy for Bremer support received even less attention. A set of experiments was conducted on different datasets to find an empirical cut-off point at which increased search extensiveness does not significantly change Bremer support and jackknife or bootstrap proportions any more. Results For the number of replicates needed for accurate estimates of support in resampling plans, a diagram is provided that helps to address the question whether apparently different support values really differ significantly. It is shown that the use of random addition cycles and parsimony ratchet iterations during bootstrapping does not translate into higher support, nor does any extension of the search extensiveness beyond the rather moderate effort of TBR (tree bisection and reconnection branch swapping) plus saving one tree per replicate. Instead, in case of very large matrices, saving more than one shortest tree per iteration and using a strict consensus tree of these yields decreased support compared to saving only one tree. This can be interpreted as a small risk of overestimating support but should be more than compensated by other factors that counteract an enhanced type I error. With regard to Bremer support, a rule of thumb can be derived stating that not much is gained relative to the surplus computational effort when searches are extended beyond 20 ratchet iterations per constrained node, at least not for datasets that fall within the size range found in the current literature. Conclusion In view of these results, calculating bootstrap or jackknife proportions with narrow confidence intervals even for very large datasets can be achieved with less expense than often thought. In particular, iterated bootstrap methods that aim at reducing statistical bias inherent to these proportions are more feasible when the individual bootstrap searches require less time. PMID:16255783

Müller, Kai F



Use of the Multinomial Jackknife and Bootstrap in Generalized Nonlinear Canonical Correlation Analysis. Research Report 87-4.  

ERIC Educational Resources Information Center

The estimation of mean and standard errors of the eigenvalues and category quantifications in generalized non-linear canonical correlation analysis (OVERALS) is discussed. Starting points are the delta method equations. The jackknife and bootstrap methods are compared for providing finite difference approximations to the derivatives. Examining the…

van der Burg, Eeke; de Leeuw, Jan


Using the jackknife for estimation in log link Bernoulli regression models.  


Bernoulli (or binomial) regression using a generalized linear model with a log link function, where the exponentiated regression parameters have interpretation as relative risks, is often more appropriate than logistic regression for prospective studies with common outcomes. In particular, many researchers regard relative risks to be more intuitively interpretable than odds ratios. However, for the log link, when the outcome is very prevalent, the likelihood may not have a unique maximum. To circumvent this problem, a 'COPY method' has been proposed, which is equivalent to creating for each subject an additional observation with the same covariates except the response variable has the outcome values interchanged (1's changed to 0's and 0's changed to 1's). The original response is given weight close to 1, while the new observation is given a positive weight close to 0; this approach always leads to convergence of the maximum likelihood algorithm, except for problems with convergence due to multicollinearity among covariates. Even though this method produces a unique maximum, when the outcome is very prevalent, and/or the sample size is relatively small, the COPY method can yield biased estimates. Here, we propose using the jackknife as a bias-reduction approach for the COPY method. The proposed method is motivated by a study of patients undergoing colorectal cancer surgery. Copyright © 2014 John Wiley & Sons, Ltd. PMID:25388125

Lipsitz, Stuart R; Fitzmaurice, Garrett M; Arriaga, Alex; Sinha, Debajyoti; Gawande, Atul A



Water-soluble jack-knife prawn extract inhibits 5-hydroxytryptamine-induced vasoconstriction and platelet aggregation in humans.  


Coronary artery spasm plays an important role in the pathogenesis of various ischemic heart diseases or serious arrhythmia. The aim of this study is to look for functional foods which have physiologically active substances preventing 5-hydroxytryptamine (5-HT)-related vasospastic diseases including peri- and postoperative ischemic complications of coronary artery bypass grafting (CABG) from ocean resources in Japanese coastal waters. First, we evaluated the effect of water-soluble ocean resource extracts on the response to 5-HT in HEK293 cells which have forcibly expressed cyan fluorescent protein-fused 5-HT2A receptors (5-HT2A-CFP). Among 5 different water-soluble extracts of ocean resources, the crude water-soluble jack-knife prawn extract (WJPE) significantly reduced maximal Ca(2+) influx induced by 0.1 ?M 5-HT in a concentration-dependent manner. The Crude WJPE significantly inhibited, in a concentration-dependent manner, 5-HT-induced constriction of human saphenous vein. 5-HT released from activated platelets plays a crucial roles in the constriction of coronary artery. Next the WJPE was purified for applying the experiment of 5-HT-induced human platelet aggregation. The purified WJPE significantly inhibited 5-HT-induced human platelet aggregation also in a concentration-dependent manner. Based on our findings, jack-knife prawn could be one of a functional food with health-promoting benefits for most people with vasospastic diseases including patients who have gone CABG. PMID:25464143

Gamoh, Shuji; Kanai, Tasuku; Tanaka-Totoribe, Naoko; Ohkura, Masamichi; Kuwabara, Masachika; Nakamura, Eisaku; Yokota, Atsuko; Yamasaki, Tetsuo; Watanabe, Akiko; Hayashi, Masahiro; Fujimoto, Shouichi; Yamamoto, Ryuichi



Power spectral estimates using two-dimensional Morlet-fan wavelets with emphasis on the long wavelengths: jackknife errors, bandwidth resolution and orthogonality properties  

NASA Astrophysics Data System (ADS)

We present a method for estimating the errors on local and global wavelet power spectra using the jackknife approach to error estimation, and compare results with jackknifed multitaper (MT) spectrum estimates. We test the methods on both synthetic and real data, the latter being free air gravity over the Congo Basin. To satisfy the independence requirement of the jackknife we investigate the orthogonality properties of the 2-D Morlet wavelet. Although Morlet wavelets are non-orthogonal, we show that careful selection of parameters can yield approximate orthogonality in space and azimuth. We also find that, when computed via the Fourier transform, the continuous wavelet transform (CWT) contains errors at very long wavelengths due to the discretization of large-scale wavelets in the Fourier domain. We hence recommend the use of convolution in the space-domain at these scales, even though this is computationally more expensive. Finally, in providing an investigation into the bandwidth resolution of CWT and MT spectra and errors at long wavelengths, we show that the Morlet wavelet is superior in this regard to Slepian tapers. Wavelets with higher bandwidth resolution deliver smaller spectral error estimates, in contrast to the MT method, where tapers with higher bandwidth resolution deliver larger errors. This results in the fan-WT having better spectral estimation properties at long wavelengths than Slepian MTs.

Kirby, J. F.; Swain, C. J.



Is It Useful and Safe to Maintain the Sitting Position During Only One Minute before Position Change to the Jack-knife Position?  

PubMed Central

Background Conventional spinal saddle block is performed with the patient in a sitting position, keeping the patient sitting for between 3 to 10 min after injection of a drug. This amount of time, however, is long enough to cause prolonged postoperative urinary retention. The trend in this block is to lower the dose of local anesthetics, providing a selective segmental block; however, an optimal dose and method are needed for adequate anesthesia in variable situations. Therefore, in this study, we evaluated the question of whether only 1 min of sitting after drug injection would be sufficient and safe for minor anorectal surgery. Methods Two hundred and sixteen patients undergoing minor anorectal surgery under spinal anesthesia remained sitting for 1 min after completion of subarachnoid administration of 1 ml of a 0.5% hyperbaric bupivacaine solution (5 mg). They were then placed in the jack-knife position. After surgery, analgesia levels were assessed using loss of cold sensation in the supine position. The next day, urination and 11-point numeric rating scale (NRS) for postoperative pain were assessed. Results None of the patients required additional analgesics during surgical manipulation. Postoperative sensory levels were T10 [T8-T12] in patients, and no significant differences were observed between sex (P = 0.857), height (P = 0.065), obesity (P = 0.873), or age (P = 0.138). Urinary retention developed in only 7 patients (3.2%). In this group, NRS was 5.0 ± 2.4 (P = 0.014). Conclusions The one-minute sitting position for spinal saddle block before the jack-knife position is a safe method for use with minor anorectal surgery and can reduce development of postoperative urinary retention. PMID:20830265

Park, Soo Young; Park, Jong Cook



ROCView: prototype software for data collection in jackknife alternative free-response receiver operating characteristic analysis  

PubMed Central

ROCView has been developed as an image display and response capture (IDRC) solution to image display and consistent recording of reader responses in relation to the free-response receiver operating characteristic paradigm. A web-based solution to IDRC for observer response studies allows observations to be completed from any location, assuming that display performance and viewing conditions are consistent with the study being completed. The simplistic functionality of the software allows observations to be completed without supervision. ROCView can display images from multiple modalities, in a randomised order if required. Following registration, observers are prompted to begin their image evaluation. All data are recorded via mouse clicks, one to localise (mark) and one to score confidence (rate) using either an ordinal or continuous rating scale. Up to nine “mark-rating” pairs can be made per image. Unmarked images are given a default score of zero. Upon completion of the study, both true-positive and false-positive reports can be downloaded and adapted for analysis. ROCView has the potential to be a useful tool in the assessment of modality performance difference for a range of imaging methods. PMID:22573294

Thompson, J; Hogg, P; Thompson, S; Manning, D; Szczepura, K



46 CFR 160.043-1 - Applicable specification and plan.  

Code of Federal Regulations, 2010 CFR

...SPECIFICATIONS AND APPROVAL LIFESAVING EQUIPMENT Jackknife (With Can Opener) for Merchant Vessels § 160.043-1 Applicable specification...Guard: Dwg. No. 160.043-1(b), Jackknife (With Can Opener). (c) Copies on file. A copy of the above...



535Biochem. J. (1980) 185, 535-536 Printed in Great Britain  

E-print Network

535Biochem. J. (1980) 185, 535-536 Printed in Great Britain Validity ofthe Jack-knife TechniqueBiochem. J. (1979) 181, 255-2561 that estimates of kinetic parameters by the jack-knife technique [Cornish-Bowden & Wong, 1978) that the jack- knife technique (Tukey, 1958; Miller, 1974) might provide a valuable


Nonparametric Confidence Interval Estimators for Heritability and Expected Selection Response  

PubMed Central

Statistical methods have not been described for comparing estimates of family-mean heritability (H) or expected selection response (R), nor have consistently valid methods been described for estimating R intervals. Nonparametric methods, e.g., delete-one jackknifing, may be used to estimate variances, intervals, and hypothesis test statistics in estimation problems where parametric methods are unsuitable, nonrobust, or undefinable. Our objective was to evaluate normal-approximation jackknife interval estimators for H and R using Monte Carlo simulation. Simulations were done using normally distributed within-family effects and normally, uniformly, and exponentially distributed between-family effects. Realized coverage probabilities for jackknife interval (2) and parametric interval (5) for H were not significantly different from stated probabilities when between-family effects were normally distributed. Coverages for jackknife intervals (3) and (4) for R were not significantly different from stated coverages when between-family effects were normally distributed. Coverages for interval (3) for R were occasionally significantly less than stated when between-family effects were uniformly or exponentially distributed. Coverages for interval (2) for H were occasionally significantly less than stated when between-family effects were exponentially distributed. Thus, intervals (3) and (4) for R and (2) for H were robust. Means of analysis of variance estimates of R were often significantly less than parametric values when the number of families evaluated was 60 or less. Means of analysis of variance estimates of H were consistently significantly less than parametric values. Means of jackknife estimates of H calculated from log transformed point estimates and R calculated from untransformed or log transformed point estimates were not significantly different from parametric values. Thus, jackknife estimators of H and R were unbiased. Delete-one jackknifing is a robust, versatile, and effective statistical method when applied to estimation problems involving variance functions. Jackknifing is especially valuable in hypothesis test estimation problems where the objective is comparing estimates from different populations. PMID:17246496

Knapp, S. J.; Bridges-Jr, W. C.; Yang, M. H.



1. ABSTRACT We show results from joint TES-OMI retrievals for  

E-print Network

the Trinidad Head sonde station (41N, 124.1W). Other available corroborative data (not currently utilized interest is near the planetary boundary layer. Trinidad Head sonde 10-8 10-7 10-6 10-5 O3 (VMR) 1000.0 100 to jackknife Trinidad Head sonde provides a check of results in conjunction with surface ozone sites


46 CFR 160.043-2 - Type.  

Code of Federal Regulations, 2010 CFR

...SPECIFICATIONS AND APPROVAL LIFESAVING EQUIPMENT Jackknife (With Can Opener) for Merchant Vessels § 160.043-2 Type. (a...which consists of a one-bladed knife fitted with a can opener and a shackle to which a lanyard is attached, all made...



Vehicle System Dynamics, 32 (1999), pp.389408 0042-3114/99/3204-389$15.00 Swets & Zeitlinger  

E-print Network

Vehicle System Dynamics, 32 (1999), pp.389­408 0042-3114/99/3204-389$15.00 ©Swets & Zeitlinger Worst-Case Vehicle Evaluation Methodology-- Examples on Truck Rollover/Jackknifing and Active Yaw Control Systems WEN-HOU MA* AND HUEI PENG SUMMARY A worst-case vehicle evaluation methodology is presented

Peng, Huei


ANOVA Tests of Homogeneity of Variance When n's Are Unequal.  

ERIC Educational Resources Information Center

Stability of Type I error rates and power are investigated for three forms of the Box test and two forms of the jackknife test with equal and unequal sample sizes under conditions of normality and nonnormality. The Box test is shown to be robust to violations of the assumption of normality when sampling is from leptokurtic populations. The…

Martin, Charles G.; Games, Paul A.


Parameter Estimation and Bias Correction for Diffusion Cheng Yong Tang and Song Xi Chen  

E-print Network

Parameter Estimation and Bias Correction for Diffusion Processes Cheng Yong Tang and Song Xi Chen, Continuous-time models, Diffusion Processes, Jackknife, Parameter estimation. Cheng Yong Tang Department. © Cheng Yong Tang. Views expressed herein are those of the author and do not necessarily reflect the views

Chaudhuri, Sanjay


Resampling methods revisited: advancing the understanding and applications in educational research  

Microsoft Academic Search

Resampling methods including randomization test, cross?validation, the jackknife and the bootstrap are widely employed in the research areas of natural science, engineering and medicine, but they lack appreciation in educational research. The purpose of the present review is to revisit and highlight the key principles and developments of resampling methods to advance the understanding and applications of resampling methods in

Haiyan Bai; Wei Pan




Microsoft Academic Search

A distance measure for populations diverging by drift only is based on the coancestry coefficient 0, and three estimators of the distance Si@= -h(l - 0) are constructed for multiallelic, multilocus data. Simulations of a monoecious population mating at random showed that a weighted ratio of single-locus estimators performed better than an unweighted average or a least squares estimator. Jackknifing




Bootstrap Methods Department of Statistics, Wharton School  

E-print Network

in postmenopausal women in the US? Small Sample · 20 postmenopausal women - sample of "typical" patients - collection of clinics · Osteoporosis measured by hip x-ray - converted to a "t-score" - "young normal" has well - Jackknife samples are too close - Fails for the median · Closely related to bootstrap - Type

Stine, Robert A.


The use and misuse of statistics in space physics  

NASA Technical Reports Server (NTRS)

This paper presents several statistical techniques most commonly used in space physics, including Fourier analysis, linear correlation, auto- and cross-correlation, power spectral density and superimposed epoch analysis, and presents tests to assess the significance of the results. New techniques such as bootstrapping and jackknifing are presented. When no test of significance is in common usage, a plausible test is suggested.

Reiff, Patricia H.



Statistical Inference for Regression Models with Covariate Measurement Error and Auxiliary Information  

PubMed Central

We consider statistical inference on a regression model in which some covariables are measured with errors together with an auxiliary variable. The proposed estimation for the regression coefficients is based on some estimating equations. This new method alleates some drawbacks of previously proposed estimations. This includes the requirment of undersmoothing the regressor functions over the auxiliary variable, the restriction on other covariables which can be observed exactly, among others. The large sample properties of the proposed estimator are established. We further propose a jackknife estimation, which consists of deleting one estimating equation (instead of one obervation) at a time. We show that the jackknife estimator of the regression coefficients and the estimating equations based estimator are asymptotically equivalent. Simulations show that the jackknife estimator has smaller biases when sample size is small or moderate. In addition, the jackknife estimation can also provide a consistent estimator of the asymptotic covariance matrix, which is robust to the heteroscedasticity. We illustrate these methods by applying them to a real data set from marketing science. PMID:22199460

You, Jinhong; Zhou, Haibo



Geographic variation in the G matrices of wild populations of the barn swallow  

Microsoft Academic Search

In this paper, we present an analysis of genetic variation in three wild populations of the barn swallow, Hirundo rustica. We estimated the P, E, and G matrices for six linear morphological measurements and tested for variation among populations using the Flury hierarchical method and the jackknife followed by MANOVA method. Because of nonpositive-definite matrices, we had to employ ‘bending’

D A Roff; T Mousseau; A P Møller; F de Lope; N Saino



Interannual variability and intraannual stability of the otolith shape in European anchovy Engraulis encrasicolus (L.) in the Bay of Biscay  

Microsoft Academic Search

recruitment of 2000. The classification success of the discriminant analysis indicated a strong separation between year groups (P < 0? 001), overall, 98% of individuals were correctly classified. Results from both jackknife and Cohen's kappa procedures confirmed the high rates of classification success obtained by the discriminant analysis (99 and 97%, respectively). Stability in the intraannual shape analysis leads to

C. Gonzalez-Salas; P. Lenfant



Robust Tests for the Equality of Variances  

Microsoft Academic Search

Alternative formulations of Levene's test statistic for equality of variances are found to be robust under nonnormality. These statistics use more robust estimators of central location in place of the mean. They are compared with the unmodified Levene's statistic, a jackknife procedure, and a ? test suggested by Layard which are all found to be less robust under nonnormality.

Morton B. Brown; Alan B. Forsythe



Life table and consumption capacity of corn earworm, Helicoverpa armigera, fed asparagus, Asparagus officinalis.  


The life table and consumption rate of Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) reared on asparagus, Asparagus officinalis L. (Asparagales: Asparagaceae) were studied under laboratory conditions to assess their interaction. Development, survival, fecundity, and consumption data were analyzed by the age-stage, twosex life table. This study indicated that asparagus is a natural host of H. armigera. However, the poor nutritional content in asparagus foliage and the poor fitness of H. armigera that fed on asparagus indicated that asparagus is a suboptimal host in comparison to hybrid sweet corn. The uncertainty associated with life table parameters was estimated by using jackknife and bootstrap techniques, and the results were compared for statistical inference. The intrinsic rate of increase (r), finite rate of increase (?), net reproductive rate (R0), and mean generation time (T) were estimated by the jackknife technique to be 0.0780 day(-1), 1.0811 day(-1), 67.4 offspring, and 54.8 days, respectively, while those estimated by the bootstrap technique were 0.0752 day(-1), 1.0781 day(-1), 68.0 offspring, and 55.3 days, respectively. The net consumption rate of H. armigera, as estimated by the jackknife and bootstrap technique, was 1183.02 and 1132.9 mg per individual, respectively. The frequency distribution of sample means obtained by the jackknife technique failed the normality test, while the bootstrap results fit the normal distribution well. By contrast, the relationship between the mean fecundity and the net reproductive rate, as estimated by the bootstrap technique, was slightly inconsistent with the relationship found by mathematical proof. The application of the jackknife and bootstrap techniques in estimating population parameters requires further examination. PMID:25373181

Jha, Ratna Kumar; Tuan, Shu-Jen; Chi, Hsin; Tang, Li-Cheng



Growth estimation of mangrove cockle Anadara tuberculosa (Mollusca: Bivalvia): application and evaluation of length-based methods.  


Growth is one of the key processes in the dynamic of exploited resources, since it provides part of the information required for structured population models. Growth of mangrove cockle, Anadara tuberculosa was estimated through length-based methods (ELEFAN I y NSLCA) and using diverse shell length intervals (SLI). The variability of L(infinity), k and phi prime (phi') estimates and the effect of each sample were quantified by jackknife techniques. Results showed the same L(infinity) estimates from ELEFAN I and NSLCA across each SLI used, and all L(infinity) were within the expected range. On the contrary, k estimates differed between methods. Jackknife estimations uncovered the tendency of ELEFAN I to overestimate k with increases in SLI, and allowed the identification of differences in uncertainty (PE and CV) between both methods. The average values of phi' derived from NSCLA1.5 and length-age sources were similar and corresponded to ranges reported by other authors. Estimates of L(infinity), k and (phi' from NSCLA1.5 were 85.97 mm, 0.124/year and 2.953 with jackknife and 86.36mm de L(infinity), 0.110/year de k and 2.914 de phi' without jackknife, respectively. Based on the observed evidence and according to the biology of the species, NSCLA is suggested to be used with jackknife and a SLI of 1.5 mm as an ad hoc approach to estimate the growth parameters of mangrove cockle. PMID:21513195

Flores, Luis A



A note on bias and mean squared error in steady-state quantile estimation  

NASA Astrophysics Data System (ADS)

When using a batch means methodology for estimation of a nonlinear function of a steady-state mean from the output of simulation experiments, it has been shown that a jackknife estimator may reduce the bias and mean squared error (mse) compared to the classical estimator, whereas the average of the classical estimators from the batches (the batch means estimator) has a worse performance from the point of view of bias and mse. In this paper we show that, under reasonable assumptions, the performance of the jackknife, classical and batch means estimators for the estimation of quantiles of the steady-state distribution exhibit similar properties as in the case of the estimation of a nonlinear function of a steady-state mean. We present some experimental results from the simulation of the waiting time in queue for an M/M/1 system under heavy traffic.

Muñoz, David F.; Ramírez-López, Adán



Inferring Phylogenetic Networks from Gene Order Data  

PubMed Central

Existing algorithms allow us to infer phylogenetic networks from sequences (DNA, protein or binary), sets of trees, and distance matrices, but there are no methods to build them using the gene order data as an input. Here we describe several methods to build split networks from the gene order data, perform simulation studies, and use our methods for analyzing and interpreting different real gene order datasets. All proposed methods are based on intermediate data, which can be generated from genome structures under study and used as an input for network construction algorithms. Three intermediates are used: set of jackknife trees, distance matrix, and binary encoding. According to simulations and case studies, the best intermediates are jackknife trees and distance matrix (when used with Neighbor-Net algorithm). Binary encoding can also be useful, but only when the methods mentioned above cannot be used. PMID:24069602

Morozov, Alexey Anatolievich; Galachyants, Yuri Pavlovich; Likhoshway, Yelena Valentinovna



Abstract Submitted for the DPP97 Meeting of  

E-print Network

­ideal systematic errors from machine­to­machine and regime­to­regime variability. Cross­validation statistical tests such as the jackknife are used to estimate these uncertainties for the present ITER design solve these problems. 1 This work supported by DoE Contract DE­AC02­76CH03073. Prefer Oral Session X

Hammett, Greg


Estimation of the size of a closed population when capture probabilities vary among animals  

USGS Publications Warehouse

A model which allows capture probabilities to vary by individuals is introduced for multiple recapture studies n closed populations. The set of individual capture probabilities is modelled as a random sample from an arbitrary probability distribution over the unit interval. We show that the capture frequencies are a sufficient statistic. A nonparametric estimator of population size is developed based on the generalized jackknife; this estimator is found to be a linear combination of the capture frequencies. Finally, tests of underlying assumptions are presented.

Burnham, K.P.; Overton, W.S.



Attoyac Bayou Bacterial Source Tracking Report  

E-print Network

iv List Of Tables Table 1. Texas E. coli BST Library (ver. 5-13, cross-library validation) composition and rates of correct classification (RCCs) by Jackknife analysis of ERIC-RP composite data sets using an 80% similarity cutoff and three... v List of Acronyms ARCC Average Rate of Correct Classification BST Bacterial Source Tracking DNA Deoxyribonucleic Acid E. coli Escherichia coli ERIC Enterobacterial Repetitive Intergenic Consensus Sequence mTEC Modified...

Martin, E.; Gentry, T.; Gregory, L.; Wagner, K.



Phylogeny of the Prolecithophora (Platyhelminthes) Inferred from 18S rDNA Sequences  

Microsoft Academic Search

Complete nuclear 18S rDNA sequences from 14 species of the Prolecithophora were obtained and used, in combination with literature data, to generate the first parsimony-based hypothesis of the phylogeny of the order Prolecithophora (Platyhelminthes). Bootstrap, parsimony jack-knife, and Bremer support values were computed and compared. The monophyly of the Prolecithophora sensu stricto and the family Plagiostomidae is strongly supported. The

Michael Norén; Ulf Jondelius



Resampling Methods: Concepts, Applications, and Justification  

NSDL National Science Digital Library

Created by Chong Hu Yu for Cisco Systems, this journal article is a summary of resampling methods such as the jackknife, bootstrap, and permutation tests. It summarizes the tests, describes various software to perform the tests, and has a list of references. The author provides an introduction, resampling methods, software for, the rationale of supporting, criticisms of resampling, a conclusion and references. This is a expansive resource which goes very in-depth into the study of resampling methods.

Yu, Chong Hu


Ability of the cognitive behavioral driver's inventory to distinguish malingerers from brain-damaged subjects  

Microsoft Academic Search

The Cognitive Behavioral Driver's Inventory (CBDI) was analyzed for its ability to discriminate brain-damaged patients from intact subjects who feigned brain-damage. In a sample of 251 neurologically impaired patients and 48 malingering volunteers, the computer-administered distinguished most malingerers from genuine patients. A jackknifed count revealed that the CBDI had 90% sensitivity for detecting malingerers, and 98% specificity for detecting non-malingering

Odie L. Bracy



Angiosperm phylogeny inferred from 18S rDNA, rbcL , and atpB sequences  

Microsoft Academic Search

A phylogenetic analysis of a combined data set for 560 angiosperms and seven outgroups based on three genes, 18S rDNA (1855 bp), rbcL (1428 bp), and atpB (1450 bp) representing a total of 4733 bp is presented. Parsimony analysis was expedited by use of a new computer program, the RATCHET. Parsimony jackknifing was performed to assess the support of clades.




Catch-per-unit-effort: which estimator is best?  


In this paper we examine the accuracy and precision of three indices of catch-per-unit-effort (CPUE). We carried out simulations, generating catch data according to six probability distributions (normal, Poisson, lognormal, gamma, delta and negative binomial), three variance structures (constant, proportional to effort and proportional to the squared effort) and their magnitudes (tail weight). The Jackknife approach of the index is recommended, whenever catch is proportional to effort or even under small deviations from proportionality assumption, when a ratio estimator is to be applied and little is known about the underlying behaviour of variables, as is the case for most fishery studies. PMID:20737116

Petrere Jr, M; Giacomini, H C; De Marco Jr, P



An improved statistical method for the racial classification of man by means of palatal rugae.  


A classification of human ruga pattern disclosed interracial differences between six population groups. The conventional statistical procedures of linear and quadratic discriminant function and nearest neighbour-point-method delivered overall correct classification figures of 49.2, 45.3 and 29.1 per cent respectively. The jackknife-classification matrix for the kernel-function method delivered an overall percentage correctly classified of 61.1 per cent with an individual group figure range correctly classified of 37-100 per cent. Although computationally elaborate, this technique has led to new insights into the data compared with parametric methods. PMID:3478034

Thomas, C J; Kotze, T J; Van der Merwe, C A



The Purley train crash mechanism: injuries and prevention.  

PubMed Central

On the afternoon of Saturday 4th March 1989 two trains, both bound for London Victoria Station, collided. Part of the rear train rolled down a steep railway embankment and jack-knifed against a tree. The mechanism of the crash and the injuries sustained by the 55 victims who were seen in the A&E Department of the Mayday University Hospital are described. Improvements in signalling technology and design of rolling stock which may reduce both the risk of collision and severity of injury in future accidents are discussed. Images Fig. 1 PMID:1388485

Fothergill, N J; Ebbs, S R; Reese, A; Partridge, R J; Mowbray, M; Southcott, R D; Hashemi, K



Ongoing Estimation of the Epidemic Parameters of a Stochastic, Spatial, Discrete-Time Model for a 1983–84 Avian Influenza Epidemic  

PubMed Central

SUMMARY We formulate a stochastic, spatial, discrete-time model of viral “Susceptible, Exposed, Infectious, Recovered” animal epidemics and apply it to an avian influenza epidemic in Pennsylvania in 1983–84. Using weekly data for the number of newly infectious cases collected during the epidemic, we find estimates for the latent period of the virus and the values of two parameters within the transmission kernel of the model. These data are then jackknifed on a progressive weekly basis to show how our estimates can be applied to an ongoing epidemic to generate continually improving values of certain epidemic parameters. PMID:21500633

Rorres, C.; Pelletier, S. T. K.; Bruhn, M. C.; Smith, G.



Systematics analyses on nucleon isovector observables in 2+1-flavor dynamical domain-wall lattice QCD near physical mass  

E-print Network

Analyses on possible systematics in some isovector nucleon observables in the RBC+UKQCD 2+1-flavor dynamical domain-wall fermion (DWF) lattice-QCD are presented. The vector charge, axial charge, quark momentum and helicity fractions, and transversity are discussed using mainly the Iwasaki\\(\\times\\)DSDR ensemble at pion mass of 170 MeV. No autocorrelation issue is observed in the vector charge and quark momentum and helicity fractions. Blocked Jack-knife analyses expose significant growth of estimated error for the axial charge with increasing block sizes that are similar to or larger than the known autocorrelation time of the gauge-field topological charge. Similar growth is seen in the transversity. These two observables, however, do not seem correlated with the topological charge.

Shigemi Ohta



A Method for WD40 Repeat Detection and Secondary Structure Prediction  

PubMed Central

WD40-repeat proteins (WD40s), as one of the largest protein families in eukaryotes, play vital roles in assembling protein-protein/DNA/RNA complexes. WD40s fold into similar ?-propeller structures despite diversified sequences. A program WDSP (WD40 repeat protein Structure Predictor) has been developed to accurately identify WD40 repeats and predict their secondary structures. The method is designed specifically for WD40 proteins by incorporating both local residue information and non-local family-specific structural features. It overcomes the problem of highly diversified protein sequences and variable loops. In addition, WDSP achieves a better prediction in identifying multiple WD40-domain proteins by taking the global combination of repeats into consideration. In secondary structure prediction, the average Q3 accuracy of WDSP in jack-knife test reaches 93.7%. A disease related protein LRRK2 was used as a representive example to demonstrate the structure prediction. PMID:23776530

Wang, Yang; Jiang, Fan; Zhuo, Zhu; Wu, Xian-Hui; Wu, Yun-Dong



A new brachycladiid species (Digenea) from Gervais' beaked whale Mesoplodon europaeus in north-western Atlantic waters.  


A new species of the digenean family Brachycladiidae Odhner, 1905 is described from the bile ducts of a Gervais' beaked whale Mesoplodon europaeus Gervais (Ziphiidae) stranded on the North Atlantic coast of Florida. These parasites were assigned to Brachycladium Looss, 1899 and differed from other species of the genus in the relative size of the oral and ventral suckers, the form and size of the eggs and their extremely small body size. A canonical discriminant analysis was used to examine differences between these specimens and the smallest available individuals of B. atlanticum (Abril, Balbuena and Raga, 1991) Gibson, 2005, considered the morphologically closest species. The overall results exhibited significant differences between the two samples and a jack-knife classification showed that 96.2% of the specimens were correctly classified to their group. In view of evidence from morphological data, the specimens from M. europaeus are considered as new to science and are designated as Brachycladium parvulum n. sp. PMID:25119367

Fraija-Fernández, Natalia; Aznar, Francisco J; Raga, Juan A; Gibson, David; Fernández, Mercedes



Sample variance and Lyman ? forest transmission statistics  

NASA Astrophysics Data System (ADS)

We compare the observed probability distribution function (PDF) of the transmission in the H i Lyman ? forest, measured from the Ultraviolet and Visual Echelle Spectrograph (UVES) `Large Programme' sample at redshifts z = [2, 2.5, 3], to results from the gimic cosmological simulations. Our measured values for the mean transmission and its PDF are in good agreement with published results. Errors on statistics measured from high-resolution data are typically estimated using bootstrap or jackknife resampling techniques after splitting the spectra into chunks. We demonstrate that these methods tend to underestimate the sample variance unless the chunk size is much larger than is commonly the case. We therefore estimate the sample variance from the simulations. We conclude that observed and simulated transmission statistics are in good agreement; in particular, we do not require the temperature-density relation to be `inverted'.

Rollinde, E.; Theuns, T.; Schaye, J.; Pâris, I.; Petitjean, P.



Identification of mitochondrial proteins of malaria parasite using analysis of variance.  


As a parasitic protozoan, Plasmodium falciparum (P. falciparum) can cause malaria. The mitochondrial proteins of malaria parasite play important roles in the discovery of anti-malarial drug targets. Thus, accurate identification of mitochondrial proteins of malaria parasite is a key step for understanding their functions and finding potential drug targets. In this work, we developed a sequence-based method to identify the mitochondrial proteins of malaria parasite. At first, we extended adjoining dipeptide composition to g-gap dipeptide composition for discretely formulating the protein sequences. Subsequently, the analysis of variance (ANOVA) combined with incremental feature selection (IFS) was used to pick out the optimal features. Finally, the jackknife cross-validation was used to evaluate the performance of the proposed model. Evaluation results showed that the maximum accuracy of 97.1 % could be achieved by using 101 optimal 5-gap dipeptides. The comparison with previous methods demonstrated that our method was accurate and efficient. PMID:25385313

Ding, Hui; Li, Dongmei



A status report on free-response analysis  

PubMed Central

The purpose of this paper is to summarise recent progress in free-response receiver operating characteristic (FROC) methodology. These are: (1) jackknife alternative FROC analysis including recent extensions and alternative methods; (2) the search-model simulator that enables validation and objective comparison of different methods of analysing the data; (3) case-based analysis that has the potential of greater clinical relevance than conventional free-response analysis; (4) a method for collectively analysing the multiple lesion types in an image (e.g. microcalcifications, masses and architectural distortions); (5) a method for sample-size estimation for FROC studies; and (6) a method for determining an objective proximity criterion, namely how close must a mark be to a true lesion in order to credit the observer for a true localisation. FROC analysis is being increasingly used to evaluate the imaging systems and understanding of recent progress should help researchers conduct better FROC studies. PMID:20085898

Chakraborty, D. P.



Prediction of Cancer Drugs by Chemical-Chemical Interactions  

PubMed Central

Cancer, which is a leading cause of death worldwide, places a big burden on health-care system. In this study, an order-prediction model was built to predict a series of cancer drug indications based on chemical-chemical interactions. According to the confidence scores of their interactions, the order from the most likely cancer to the least one was obtained for each query drug. The 1st order prediction accuracy of the training dataset was 55.93%, evaluated by Jackknife test, while it was 55.56% and 59.09% on a validation test dataset and an independent test dataset, respectively. The proposed method outperformed a popular method based on molecular descriptors. Moreover, it was verified that some drugs were effective to the ‘wrong’ predicted indications, indicating that some ‘wrong’ drug indications were actually correct indications. Encouraged by the promising results, the method may become a useful tool to the prediction of drugs indications. PMID:24498372

Li, Hai-Peng; Feng, Kai-Yan; Chen, Lei; Zheng, Ming-Yue; Cai, Yu-Dong



A New Multi-label Classifier in Identifying the Functional Types of Human Membrane Proteins.  


Membrane proteins were found to be involved in various cellular processes performing various important functions, which are mainly associated to their type. Given a membrane protein sequence, how can we identify its type(s)? Particularly, how can we deal with the multi-type problem since one membrane protein may simultaneously belong to two or more different types? To address these problems, which are obviously very important to both basic research and drug development, a new multi-label classifier was developed based on pseudo amino acid composition with multi-label k-nearest neighbor algorithm. The success rate achieved by the new predictor on the benchmark dataset by jackknife test is 73.94 %, indicating that the method is promising and the predictor may become a very useful high-throughput tool, or at least play a complementary role to the existing predictors in identifying functional types of membrane proteins. PMID:25433431

Zou, Hong-Liang; Xiao, Xuan



Ontogeny of the barley plant as related to mutation expression and detection of pollen mutations  

SciTech Connect

Clustering of mutant pollen grains in a population of normal pollen due to premeiotic mutational events complicates translating mutation frequencies into rates. Embryo ontogeny in barley will be described and used to illustrate the formation of such mutant clusters. The nature of the statistics for mutation frequency will be described from a study of the reversion frequencies of various waxy mutants in barley. Computer analysis by a ''jackknife'' method of the reversion of a waxy mutant treated with the mutagen sodium azide showed a significantly higher reversion frequency than untreated material. Problems of the computer analysis suggest a better experimental design for pollen mutation experiments. Preliminary work on computer modeling for pollen development and mutation will be described.

Hodgdon, A.L.; Marcus, A.H.; Arenaz, P.; Rosichan, J.L.; Bogyo, T.P.; Nilan, R.A.



Ontogeny of the barley plant as related to mutation expression and detection of pollen mutations  

SciTech Connect

Clustering of mutant pollen grains in a population of normal pollen due to premeiotic mutational events complicates translating mutation frequencies into rates. Embryo ontogeny in barley will be described and used to illustrate the formation of such mutant clusters. The nature of the statistics for mutation frequency will be described from a study of the reversion frequencies of various waxy mutants in barley. Computer analysis by a jackknife method of the reversion frequencies of a waxy mutant treated with the mutagen sodium azide showed a significantly higher reversion frequency than untreated material. Problems of the computer analysis suggest a better experimental design for pollen mutation experiments. Preliminary work on computer modeling for pollen development and mutation will be described.

Hodgdon, A.L.; Marcus, A.H.; Arenaz, P.; Rosichan, J.L.; Bogyo, T.P.; Nilan, R.A.



Linear regression in astronomy. II  

NASA Astrophysics Data System (ADS)

A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.

Feigelson, Eric D.; Babu, Gutti J.



Design-based treatment of unit nonresponse in environmental surveys using calibration weighting.  


Unit nonresponse is often a problem in sample surveys. It arises when the values of the survey variable cannot be recorded for some sampled units. In this paper, the use of nonresponse calibration weighting to treat nonresponse is considered in a complete design-based framework. Nonresponse is viewed as a fixed characteristic of the units. The approach is suitable in environmental and forest surveys when sampled sites cannot be reached by field crews. Approximate expressions of design-based bias and variance of the calibration estimator are derived and design-based consistency is investigated. Choice of auxiliary variables to perform calibration is discussed. Sen-Yates-Grundy, Horvitz-Thompson, and jackknife estimators of the sampling variance are proposed. Analytical and Monte Carlo results demonstrate the validity of the procedure when the relationship between survey and auxiliary variables is similar in respondent and nonrespondent strata. An application to a forest survey performed in Northeastern Italy is considered. PMID:24022794

Fattorini, Lorenzo; Franceschi, Sara; Maffei, Daniela



A protein structural classes prediction method based on PSI-BLAST profile.  


Knowledge of protein structural classes plays an important role in understanding protein folding patterns. Prediction of protein structural class based solely on sequence data remains to be a challenging problem. In this study, we extract the long-range correlation information and linear correlation information from position-specific score matrix (PSSM). A total of 3600 features are extracted, then, 278 features are selected by a filter feature selection method based on 1189 dataset. To verify the performance of our method (named by LCC-PSSM), jackknife tests are performed on three widely used low similarity benchmark datasets. Comparison of our results with the existing methods shows that our method provides the favorable performance for protein structural class prediction. Stand-alone version of the proposed method (LCC-PSSM) is written in MATLAB language and it can be downloaded from PMID:24607742

Ding, Shuyan; Yan, Shoujiang; Qi, Shuhua; Li, Yan; Yao, Yuhua



A status report on free-response analysis.  


The purpose of this paper is to summarise recent progress in free-response receiver operating characteristic (FROC) methodology. These are: (1) jackknife alternative FROC analysis including recent extensions and alternative methods; (2) the search-model simulator that enables validation and objective comparison of different methods of analysing the data; (3) case-based analysis that has the potential of greater clinical relevance than conventional free-response analysis; (4) a method for collectively analysing the multiple lesion types in an image (e.g. microcalcifications, masses and architectural distortions); (5) a method for sample-size estimation for FROC studies; and (6) a method for determining an objective proximity criterion, namely how close must a mark be to a true lesion in order to credit the observer for a true localisation. FROC analysis is being increasingly used to evaluate the imaging systems and understanding of recent progress should help researchers conduct better FROC studies. PMID:20085898

Chakraborty, D P



Gulls identified as major source of fecal pollution in coastal waters: a microbial source tracking study.  


Gulls were reported as sources of fecal pollution in coastal environments and potential vectors of human infections. Microbial source tracking (MST) methods were rarely tested to identify this pollution origin. This study was conducted to ascertain the source of water fecal contamination in the Berlenga Island, Portugal. A total of 169 Escherichia coli isolates from human sewage, 423 isolates from gull feces and 334 water isolates were analyzed by BOX-PCR. An average correct classification of 79.3% was achieved. When an 85% similarity cutoff was applied 24% of water isolates were present in gull feces against 2.7% detected in sewage. Jackknifing resulted in 29.3% of water isolates classified as gull, and 10.8% classified as human. Results indicate that gulls constitute a major source of water contamination in the Berlenga Island. This study validated a methodology to differentiate human and gull fecal pollution sources in a real case of a contaminated beach. PMID:24140684

Araújo, Susana; Henriques, Isabel S; Leandro, Sérgio Miguel; Alves, Artur; Pereira, Anabela; Correia, António



PACo: A Novel Procrustes Application to Cophylogenetic Analysis  

PubMed Central

We present Procrustean Approach to Cophylogeny (PACo), a novel statistical tool to test for congruence between phylogenetic trees, or between phylogenetic distance matrices of associated taxa. Unlike previous tests, PACo evaluates the dependence of one phylogeny upon the other. This makes it especially appropriate to test the classical coevolutionary model that assumes that parasites that spend part of their life in or on their hosts track the phylogeny of their hosts. The new method does not require fully resolved phylogenies and allows for multiple host-parasite associations. PACo produces a Procrustes superimposition plot enabling a graphical assessment of the fit of the parasite phylogeny onto the host phylogeny and a goodness-of-fit statistic, whose significance is established by randomization of the host-parasite association data. The contribution of each individual host-parasite association to the global fit is measured by means of jackknife estimation of their respective squared residuals and confidence intervals associated to each host-parasite link. We carried out different simulations to evaluate the performance of PACo in terms of Type I and Type II errors with respect to two similar published tests. In most instances, PACo performed at least as well as the other tests and showed higher overall statistical power. In addition, the jackknife estimation of squared residuals enabled more elaborate validations about the nature of individual links than the ParaFitLink1 test of the program ParaFit. In order to demonstrate how it can be used in real biological situations, we applied PACo to two published studies using a script written in the public-domain statistical software R. PMID:23580325

Balbuena, Juan Antonio; Míguez-Lozano, Raúl; Blasco-Costa, Isabel



Pine Hollow Watershed Project : FY 2000 Projects.  

SciTech Connect

The Pine Hollow Project (1999-010-00) is an on-going watershed restoration effort administered by Sherman County Soil and Water Conservation District and spearheaded by Pine Hollow/Jackknife Watershed Council. The headwaters are located near Shaniko in Wasco County, and the mouth is in Sherman County on the John Day River. Pine Hollow provides more than 20 miles of potential summer steelhead spawning and rearing habitat. The watershed is 92,000 acres. Land use is mostly range, with some dryland grain. There are no water rights on Pine Hollow. Due to shallow soils, the watershed is prone to rapid runoff events which scour out the streambed and the riparian vegetation. This project seeks to improve the quality of upland, riparian and in-stream habitat by restoring the natural hydrologic function of the entire watershed. Project implementation to date has consisted of construction of water/sediment control basins, gradient terraces on croplands, pasture cross-fences, upland water sources, and grass seeding on degraded sites, many of which were crop fields in the early part of the century. The project is expected to continue through about 2007. From March 2000 to June 2001, the Pine Hollow Project built 6 sediment basins, 1 cross-fence, 2 spring developments, 1 well development, 1 solar pump, 50 acres of native range seeding and 1 livestock waterline. FY2000 projects were funded by BPA, Oregon Watershed Enhancement Board, US Fish and Wildlife Service and landowners. In-kind services were provided by Sherman County Soil and Water Conservation District, USDA Natural Resources Conservation Service, USDI Bureau of Land Management, Oregon Department of Fish and Wildlife, Pine Hollow/Jackknife Watershed Council, landowners and Wasco County Soil and Water Conservation District.

Sherman County Soil and Water Conservation District



Diagnostic Performance of Gadoxetic Acid-enhanced Liver MR Imaging in the Detection of HCCs and Allocation of Transplant Recipients on the Basis of the Milan Criteria and UNOS Guidelines: Correlation with Histopathologic Findings.  


Purpose To determine whether hepatobiliary phase ( HBP hepatobiliary phase ) imaging can improve the diagnostic performance of gadoxetic acid-enhanced liver magnetic resonance (MR) imaging in the detection of hepatocellular carcinomas ( HCC hepatocellular carcinoma s) and to investigate the accuracy of gadoxetic acid-enhanced MR imaging in the allocation of transplant recipients on the basis of the Milan criteria and United Network for Organ Sharing ( UNOS United Network for Organ Sharing ) guidelines. Materials and Methods This retrospective study had institutional review board approval; the requirement for informed consent was waived. Between June 2008 and June 2011, 63 patients who underwent liver transplantation (LT) were included. All patients underwent a gadoxetic acid-enhanced 3.0-T MR imaging examination of the liver that included HBP hepatobiliary phase images obtained 20 minutes after contrast material administration. Two abdominal radiologists independently assessed two MR imaging data sets to detect HCC hepatocellular carcinoma s: Set 1 included unenhanced and gadoxetic acid-enhanced dynamic images, and set 2 also included HBP hepatobiliary phase images. Patients were allocated into three groups: Those who did not meet the Milan criteria, those who did meet the Milan criteria with additional priority according to UNOS United Network for Organ Sharing guidelines, and those who did meet the Milan criteria without additional priority. Diagnostic performance of each data set in depicting HCC hepatocellular carcinoma s was compared by using jackknife alternative free-response receiver operating characteristics ( JAFROC jackknife alternative free-response receiver operating characteristic s). Sensitivity and accuracy of patient allocation were compared by using generalized estimating equations. Results Sixty-three HCC hepatocellular carcinoma s were found in 36 of 63 patients. Eight patients were classified as not meeting Milan criteria, 12 as meeting Milan criteria with additional priority, and 43 as meeting Milan criteria without additional priority. For the detection of HCC hepatocellular carcinoma s, reader-averaged figures of merit estimated with JAFROC jackknife alternative free-response receiver operating characteristic s were 0.761 for set 1 and 0.791 for set 2 (P < .001). Addition of HBP hepatobiliary phase images significantly improved sensitivity for the detection of HCC hepatocellular carcinoma s, particularly 1-2-cm HCC hepatocellular carcinoma s (six [20.7%] vs 13 [44.8%] of 29 [P = .008] for reader 1 and eight [27.6%] vs 12 [41.4%] of 29 [P = .041] for reader 2). Accuracy of patient allocation was 88.9% for set 1 and 92.1% for set 2 (P = .151). Conclusion Addition of HBP hepatobiliary phase images can significantly improve the diagnostic performance of gadoxetic acid-enhanced liver MR imaging in the detection of 1-2-cm HCC hepatocellular carcinoma s in liver transplantation candidates. In addition, gadoxetic acid-enhanced MR imaging showed 92.1% accuracy in patient allocation on the basis of the Milan criteria and UNOS United Network for Organ Sharing guidelines. © RSNA, 2014 Online supplemental material is available for this article. PMID:25203131

Lee, Dong Ho; Lee, Jeong Min; Baek, Jee Hyun; Shin, Cheong-Il; Han, Joon Koo; Choi, Byung Ihn



Hierarchical Bayes estimation of species richness and occupancy in spatially replicated surveys  

USGS Publications Warehouse

1. Species richness is the most widely used biodiversity metric, but cannot be observed directly as, typically, some species are overlooked. Imperfect detectability must therefore be accounted for to obtain unbiased species-richness estimates. When richness is assessed at multiple sites, two approaches can be used to estimate species richness: either estimating for each site separately, or pooling all samples. The first approach produces imprecise estimates, while the second loses site-specific information. 2. In contrast, a hierarchical Bayes (HB) multispecies site-occupancy model benefits from the combination of information across sites without losing site-specific information and also yields occupancy estimates for each species. The heart of the model is an estimate of the incompletely observed presence-absence matrix, a centrepiece of biogeography and monitoring studies. We illustrate the model using Swiss breeding bird survey data, and compare its estimates with the widely used jackknife species-richness estimator and raw species counts. 3. Two independent observers each conducted three surveys in 26 1-km(2) quadrats, and detected 27-56 (total 103) species. The average estimated proportion of species detected after three surveys was 0.87 under the HB model. Jackknife estimates were less precise (less repeatable between observers) than raw counts, but HB estimates were as repeatable as raw counts. The combination of information in the HB model thus resulted in species-richness estimates presumably at least as unbiased as previous approaches that correct for detectability, but without costs in precision relative to uncorrected, biased species counts. 4. Total species richness in the entire region sampled was estimated at 113.1 (CI 106-123); species detectability ranged from 0.08 to 0.99, illustrating very heterogeneous species detectability; and species occupancy was 0.06-0.96. Even after six surveys, absolute bias in observed occupancy was estimated at up to 0.40. 5. Synthesis and applications. The HB model for species-richness estimation combines information across sites and enjoys more precise, and presumably less biased, estimates than previous approaches. It also yields estimates of several measures of community size and composition. Covariates for occupancy and detectability can be included. We believe it has considerable potential for monitoring programmes as well as in biogeography and community ecology.

Kery, M.; Royle, J.A.



Phylogenetic analysis identifies the invertebrate pathogen Helicosporidium sp. as a green alga (Chlorophyta).  


Historically, the invertebrate pathogens of the genus Helicosporidium were considered to be either protozoa or fungi, but the taxonomic position of this group has not been considered since 1931. Recently, a Helicosporidium sp., isolated from the blackfly Simulium jonesi Stone & Snoddy (Diptera: Simuliidae), has been amplified in the heterologous host Helicoverpa zea. Genomic DNA has been extracted from gradient-purified cysts. The 185, 28S and 5.8S regions of the Helicosporidium rDNA, as well as partial sequences of the actin and beta-tubulin genes, were amplified by PCR and sequenced. Comparative analysis of these nucleotide sequences was performed using neighbour-joining and maximum-parsimony methods. All inferred phylogenetic trees placed Helicosporidium sp. among the green algae (Chlorophyta), and this association was supported by bootstrap and parsimony jackknife values. Phylogenetic analysis focused on the green algae depicted Helicosporidium sp. as a close relative of Prototheca wickerhamii and Prototheca zopfii (Chlorophyta, Trebouxiophyceae), two achlorophylous, pathogenic green algae. On the basis of this phylogenetic analysis, Helicosporidium sp. is clearly neither a protist nor a fungus, but appears to be the first described algal invertebrate pathogen. These conclusions lead us to propose the transfer of the genus Helicosporidium to Chlorophyta, Trebouxiophyceae. PMID:11837312

Tartar, Aurélien; Boucias, Drion G; Adams, Byron J; Becnel, James J



Predicting red wolf release success in the southeastern United States  

USGS Publications Warehouse

Although the red wolf (Canis rufus) was once found throughout the southeastern United States, indiscriminate killing and habitat destruction reduced its range to a small section of coastal Texas and Louisiana. Wolves trapped from 1973 to 1980 were taken to establish a captive breeding program that was used to repatriate 2 mainland and 3 island red wolf populations. We collected data from 320 red wolf releases in these areas and classified each as a success or failure based on survival and reproductive criteria, and whether recaptures were necessary to resolve conflicts with humans. We evaluated the relations between release success and conditions at the release sites, characteristics of released wolves, and release procedures. Although <44% of the variation in release success was explained, model performance based on jackknife tests indicated a 72-80% correct prediction rate for the 4 operational models we developed. The models indicated that success was associated with human influences on the landscape and the level of wolf habituation to humans prior to release. We applied the models to 31 prospective areas for wolf repatriation and calculated an index of release success for each area. Decision-makers can use these models to objectively rank prospective release areas and compare strengths and weaknesses of each.

Van Manen, F.T.; Crawford, B.A.; Clark, J.D.



Interpolation of Global Monthly Rain-Gauge Observations for Climate Change Analysis  

NASA Astrophysics Data System (ADS)

Monthly precipitation sums are observed at thousands of meteorological stations worldwide. Different institutes (e.g. the Global Precipitation Climatology Centre, GPCC, and the Climatic Research Unit, CRU, of the University of East Anglia) interpolate these observations to regular grids. These data are used widely in climate research, e.g. for the investigation of the hydrological cycle and climate change. Results of the interpolation depend on the station density, which varies considerably around the globe. It also depends on the interpolation method used (e.g. Ordinary Kriging and Shepard's Method). These methods are general interpolation methods that do not take into account the specifics of precipitation. The question discussed in this presentation is whether we can do better by using an interpolation strategy especially designed for monthly precipitation observations. Based on a dense local dataset (one station per 109 km2) and a less dense global dataset (one station per 27,000 km2) of 50 years of monthly precipitation observations, various interpolation strategies are compared. This includes the interpolation of transformed variables, the consideration of local spatial correlation of precipitation as well as data quality. The Jack-knife error is used to compare the different strategies. The major result is that some strategies used so far are far from optimal.

Grieser, Jürgen



Patterns of connectivity among populations of a coral reef fish  

NASA Astrophysics Data System (ADS)

Knowledge of the patterns and scale of connectivity among populations is essential for the effective management of species, but our understanding is still poor for marine species. We used otolith microchemistry of newly settled bicolor damselfish ( Stegastes partitus) in the Mesoamerican Reef System (MRS), Western Caribbean, to investigate patterns of connectivity among populations over 2 years. First, we assessed spatial and temporal variability in trace elemental concentrations from the otolith edge to make a `chemical map' of potential source reef(s) in the region. Significant otolith chemical differences were detected at three spatial scales (within-atoll, between-atolls, and region-wide), such that individuals were classified to locations with moderate (52 % jackknife classification) to high (99 %) accuracy. Most sites at Turneffe Atoll, Belize showed significant temporal variability in otolith concentrations on the scale of 1-2 months. Using a maximum likelihood approach, we estimated the natal source of larvae recruiting to reefs across the MRS by comparing `natal' chemical signatures from the otolith of recruits to the `chemical map' of potential source reef(s). Our results indicated that populations at both Turneffe Atoll and Banco Chinchorro supply a substantial amount of individuals to their own reefs (i.e., self-recruitment) and thus emphasize that marine conservation and management in the MRS region would benefit from localized management efforts as well as international cooperation.

Chittaro, P. M.; Hogan, J. D.



Predicting subcellular location of proteins using integrated-algorithm method.  


Protein's subcellular location, which indicates where a protein resides in a cell, is an important characteristic of protein. Correctly assigning proteins to their subcellular locations would be of great help to the prediction of proteins' function, genome annotation, and drug design. Yet, in spite of great technical advance in the past decades, it is still time-consuming and laborious to experimentally determine protein subcellular locations on a high throughput scale. Hence, four integrated-algorithm methods were developed to fulfill such high throughput prediction in this article. Two data sets taken from the literature (Chou and Elrod, Protein Eng 12:107-118, 1999) were used as training set and test set, which consisted of 2,391 and 2,598 proteins, respectively. Amino acid composition was applied to represent the protein sequences. The jackknife cross-validation was used to test the training set. The final best integrated-algorithm predictor was constructed by integrating 10 algorithms in Weka (a software tool for tackling data mining tasks, ) based on an mRMR (Minimum Redundancy Maximum Relevance, ) method. It can achieve correct rate of 77.83 and 80.56% for the training set and test set, respectively, which is better than all of the 60 algorithms collected in Weka. This predicting software is available upon request. PMID:19662505

Cai, Yu-Dong; Lu, Lin; Chen, Lei; He, Jian-Feng



Optimizing the feature set for a Bayesian network for breast cancer diagnosis using genetic algorithm techniques  

NASA Astrophysics Data System (ADS)

This study investigates the degree to which the performance of Bayesian belief networks (BBNs), for computer-assisted diagnosis of breast cancer, can be improved by optimizing their input feature sets using a genetic algorithm (GA). 421 cases (all women) were used in this study, of which 92 were positive for breast cancer. Each case contained both non-image information and image information derived from mammograms by radiologists. A GA was used to select an optimal subset of features, from a total of 21, to use as the basis for a BBN classifier. The figure-of-merit used in the GA's evaluation of feature subsets was Az, the area under the ROC curve produced by the corresponding BBN classifier. For each feature subset evaluated by the GA, a BBN was developed to classify positive and negative cases. Overall performance of the BBNs was evaluated using a jackknife testing method to calculate Az, for their respective ROC curves. The Az value of the BBN incorporating all 21 features was 0.851 plus or minus 0.012. After a 93 generation search, the GA found an optimal feature set with four non-image and four mammographic features, which achieved an Az value of 0.927 plus or minus 0.009. This study suggests that GAs are a viable means to optimize feature sets, and optimizing feature sets can result in significant performance improvements.

Wang, Xiao Hui; Zheng, Bin; Chang, Yuan-Hsiang; Good, Walter F.



iMethyl-PseAAC: Identification of Protein Methylation Sites via a Pseudo Amino Acid Composition Approach  

PubMed Central

Before becoming the native proteins during the biosynthesis, their polypeptide chains created by ribosome's translating mRNA will undergo a series of “product-forming” steps, such as cutting, folding, and posttranslational modification (PTM). Knowledge of PTMs in proteins is crucial for dynamic proteome analysis of various human diseases and epigenetic inheritance. One of the most important PTMs is the Arg- or Lys-methylation that occurs on arginine or lysine, respectively. Given a protein, which site of its Arg (or Lys) can be methylated, and which site cannot? This is the first important problem for understanding the methylation mechanism and drug development in depth. With the avalanche of protein sequences generated in the postgenomic age, its urgency has become self-evident. To address this problem, we proposed a new predictor, called iMethyl-PseAAC. In the prediction system, a peptide sample was formulated by a 346-dimensional vector, formed by incorporating its physicochemical, sequence evolution, biochemical, and structural disorder information into the general form of pseudo amino acid composition. It was observed by the rigorous jackknife test and independent dataset test that iMethyl-PseAAC was superior to any of the existing predictors in this area. PMID:24977164

Qiu, Wang-Ren; Lin, Wei-Zhong; Chou, Kuo-Chen



Can horizontally oriented breast tomosynthesis image volumes or the use of a systematic search strategy improve interpretation? An eye tracking and free response human observer study  

NASA Astrophysics Data System (ADS)

Our aim was to evaluate if there is a benefit in diagnostic accuracy and efficiency of viewing breast tomosynthesis (BT) image volumes presented horizontally oriented, but also to evaluate the use of a systematic search strategy where the breast is divided, and analyzed consecutively, into two sections. These image presentations were compared to regular vertical image presentation. All methods were investigated using viewing procedures consisting of free scroll volume browsing, and a combination of initial cine loops at three different frame rates (9, 14, 25 fps) terminated upon request followed by free scroll volume browsing if needed. Fifty-five normal BT image volumes in MLO view were collected. In these, simulated lesions (20 masses and 20 clusters of microcalcifications) were randomly inserted, creating four unique image sets for each procedure. Four readers interpreted the cases in a random order. Their task was to locate the lesions, mark and assign a five level confidence scale. The diagnostic accuracy was analyzed using Jackknife Free Receiver Operating Characteristics (JAFROC). Time efficiency and visual search behavior were also investigated using eye tracking. Results indicate there was no statistically significant difference in JAFROC FOM between the different image presentations, although visual search was more time efficient when viewing horizontally oriented image volumes in medium cine loops.

Lång, Kristina; Zackrisson, Sophia; Holmqvist, Kenneth; Nyström, Marcus; Andersson, Ingvar; Förnvik, Daniel; Tingberg, Anders; Timberg, Pontus



Bioequivalence evaluation of two formulations of pidotimod using a limited sampling strategy.  


The aim of this study was to develop a limited sampling strategy (LSS) to assess the bioequivalence of two formulations of pidotimod. A randomized, two-way, cross-over study was conducted in healthy Chinese volunteers to compare two formulations of pidotimod. A limited sampling model was established using regression models to estimate the pharmacokinetic parameters and assess the bioequivalence of pidotimod. The model was internally validated by the Jack-knife method and graphical methods. The traditional non-compartmental method was also used to analyze the data and compared with LSS method. The results indicate that following oral administration of a single 800 mg dose, the plasma AUC(0-12 h) and C(max) of pidotimod can be predicted accurately using only two to four plasma samples. The bioequivalence assessment based on the LSS models provided results very similar to that obtained using all the observed concentration-time data points and indicate that the two pidotimod formulations were bioequivalent. A LSS method for assessing the bioequivalence of pidotimod formulations was established and proved to be applicable and accurate. This LSS method could be considered appropriate for a pidotimod bioequivalence study, providing an inexpensive cost of sampling acquisition and analysis. And the methodology presented here may also be applicable to bioequivalence evaluation of other medications. PMID:23639228

Huang, Ji-Han; Huang, Xiao-Hui; Wang, Kun; Li, Jian-Chun; Xie, Xue-Feng; Shen, Chen-Lin; Li, Lu-Jin; Zheng, Qing-Shan



Analysis of secondary outcomes in nested case-control study designs.  


One of the main perceived advantages of using a case-cohort design compared with a nested case-control design in an epidemiologic study is the ability to evaluate with the same subcohort outcomes other than the primary outcome of interest. In this paper, we show that valid inferences about secondary outcomes can also be achieved in nested case-control studies by using the inclusion probability weighting method in combination with an approximate jackknife standard error that can be computed using existing software. Simulation studies demonstrate that when the sample size is sufficient, this approach yields valid type 1 error and coverage rates for the analysis of secondary outcomes in nested case-control designs. Interestingly, the statistical power of the nested case-control design was comparable with that of the case-cohort design when the primary and secondary outcomes were positively correlated. The proposed method is illustrated with the data from a cohort in Cardiovascular Health Study to study the association of C-reactive protein levels and the incidence of congestive heart failure. PMID:24919979

Kim, Ryung S; Kaplan, Robert C



Predicting protein subchloroplast locations with both single and multiple sites via three different modes of Chou's pseudo amino acid compositions.  


Owing to the fact that location information can indicate important functionalities of proteins, developing computational tools to predict protein subcellular localization is one of the most efficient and meaningful tasks with no doubt. The existence methods dealing with prediction of protein subchloroplast locations can only handle the case of single location site. Therefore, it is meaningful and challenging to make effort in how to deal with the proteins with multiple subchloroplast location sites instead of just excluding them. To solve this problem, new systems for predicting protein subchloroplast localization with single or multiple sites are developed and discussed in the paper. Three different editions of KNN algorithms and four different types of feature extraction were adopted to construct the prediction systems. This is the first effort to predict the proteins with multiple subchloroplast locations. The overall jackknife success rates achieved by the best combination (features+classifier) on three dataset with different levels of homology were 89.08%, 81.29% and 71.11%. The performance of the prediction models indicate that the proposed methods might be applied as a useful and efficient assistant tool for the prediction of sub-subcellular localizations. PMID:23850480

Huang, Chao; Yuan, Jing-Qi



BICEP2 I: Detection Of B-mode Polarization at Degree Angular Scales  

E-print Network

We report results from the BICEP2 experiment, a Cosmic Microwave Background (CMB) polarimeter specifically designed to search for the signal of inflationary gravitational waves in the B-mode power spectrum around l=80. The telescope comprised a 26 cm aperture all-cold refracting optical system equipped with a focal plane of 512 antenna coupled transition edge sensor (TES) 150 GHz bolometers each with temperature sensitivity of approx. 300 uk.sqrt(s). BICEP2 observed from the South Pole for three seasons from 2010 to 2012. A low-foreground region of sky with an effective area of 380 square degrees was observed to a depth of 87 nK-degrees in Stokes Q and U. In this paper we describe the observations, data reduction, maps, simulations and results. We find an excess of B-mode power over the base lensed-LCDM expectation in the range 305\\sigma$. Through jackknife tests and simulations based on detailed calibration measurements we show that systematic contamination is much smaller than the observed excess. We also e...

Ade, P A R; Barkats, D; Benton, S J; Bischoff, C A; Bock, J J; Brevik, J A; Buder, I; Bullock, E; Dowell, C D; Duband, L; Filippini, J P; Fliescher, S; Golwala, S R; Halpern, M; Hasselfield, M; Hildebrandt, S R; Hilton, G C; Hristov, V V; Irwin, K D; Karkare, K S; Kaufman, J P; Keating, B G; Kernasovskiy, S A; Kovac, J M; Kuo, C L; Leitch, E M; Lueker, M; Mason, P; Netterfield, C B; Nguyen, H T; O'Brient, R; Ogburn, R W; Orlando, A; Pryke, C; Reintsema, C D; Richter, S; Schwarz, R; Sheehy, C D; Staniszewski, Z K; Sudiwala, R V; Teply, G P; Tolan, J E; Turner, A D; Vieregg, A G; Wong, C L; Yoon, K W



Assessment of ultrasonic computed tomography in symptomatic breast patients by discriminant analysis.  


From 95 subjects imaged with both speed of sound and attenuation ultrasonic computed tomography (UCT), quantitative analyses are presented on 40 cases where unequivocal correlating clinical diagnoses are available. Using four attenuation and speed of sound parameters from different regions of interest in the breast, a linear discriminator detects cancer with approximately 90% sensitivity and specificity. Increased confidence in the predictive power of this small study is given by a modern test of predictive power (jackknifing) and by the fact that diagnostic discrimination remains as high as 85% when only two parameters are employed--attenuation and speed of sound in the lesion minus those values in the remaining central mammary tissues. Speed of sound images appear particularly useful in older, fatty breasts where pulse echo ultrasound is particularly lacking. While UCT in the form studied here is not likely to receive wide clinical acceptance in the near future, a combined UCT/pulse echo system might find wide clinical utility if it can be sufficiently convenient and inexpensive. PMID:2538018

Scherzinger, A L; Belgam, R A; Carson, P L; Meyer, C R; Sutherland, J V; Bookstein, F L; Silver, T M



[Limited sampling strategy to estimate pharmacokinetic parameters of orally administered metformin hydrochloride].  


The present study was to estimate pharmacokinetic parameters of metformin hydrochloride in 20 Chinese healthy volunteers with a limited sampling strategy (LSS), which will provide scientific data for bioequivalence and clinical application. A single dose of metformin was administrated to 20 healthy volunteers. The concentration of metformin in whole blood was determined by validated high performance liquid chromatography (HPLC) method. Multi-linear regression analysis was performed to establish a model to estimate AUC(0-24 h) and Cmax of metformin by LSS method. The LSS models were validated by the Jackknife method. The result indicated: the linearity relationship between AUC(0-24 h) or Cmax and single concentration point was poor. Several models for metformin AUC(0-24 h) or Cmax, estimation were better (r2 > 0.9, P < 0.05). Validation tests indicated that most informative sampling points (C2, C6 for AUC(0-24 h), C1.5, C2 for Cmax) provided accurate estimations of these parameters. So, a multi-linear regression model for estimation pharmacokinetic parameters of metformin by using LSS method is feasible. PMID:21351492

Chen, Li-fang; Jiao, Jian-jie; Zhang, Cai-li; Lou, Jian-shi; Liu, Chang-xiao



Parallel Worldline Numerics: Implementation and Error Analysis  

E-print Network

We give an overview of the worldline numerics technique, and discuss the parallel CUDA implementation of a worldline numerics algorithm. In the worldline numerics technique, we wish to generate an ensemble of representative closed-loop particle trajectories, and use these to compute an approximate average value for Wilson loops. We show how this can be done with a specific emphasis on cylindrically symmetric magnetic fields. The fine-grained, massive parallelism provided by the GPU architecture results in considerable speedup in computing Wilson loop averages. Furthermore, we give a brief overview of uncertainty analysis in the worldline numerics method. There are uncertainties from discretizing each loop, and from using a statistical ensemble of representative loops. The former can be minimized so that the latter dominates. However, determining the statistical uncertainties is complicated by two subtleties. Firstly, the distributions generated by the worldline ensembles are highly non-Gaussian, and so the standard error in the mean is not a good measure of the statistical uncertainty. Secondly, because the same ensemble of worldlines is used to compute the Wilson loops at different values of $T$ and $x_\\mathrm{ cm}$, the uncertainties associated with each computed value of the integrand are strongly correlated. We recommend a form of jackknife analysis which deals with both of these problems.

Dan Mazur; Jeremy S. Heyl



A two-stage SVM method to predict membrane protein types by incorporating amino acid classifications and physicochemical properties into a general form of Chou's PseAAC.  


Membrane proteins play important roles in many biochemical processes and are also attractive targets of drug discovery for various diseases. The elucidation of membrane protein types provides clues for understanding the structure and function of proteins. Recently we developed a novel system for predicting protein subnuclear localizations. In this paper, we propose a simplified version of our system for predicting membrane protein types directly from primary protein structures, which incorporates amino acid classifications and physicochemical properties into a general form of pseudo-amino acid composition. In this simplified system, we will design a two-stage multi-class support vector machine combined with a two-step optimal feature selection process, which proves very effective in our experiments. The performance of the present method is evaluated on two benchmark datasets consisting of five types of membrane proteins. The overall accuracies of prediction for five types are 93.25% and 96.61% via the jackknife test and independent dataset test, respectively. These results indicate that our method is effective and valuable for predicting membrane protein types. A web server for the proposed method is available at PMID:24316387

Han, Guo-Sheng; Yu, Zu-Guo; Anh, Vo



Prediction of bacterial protein subcellular localization by incorporating various features into Chou's PseAAC and a backward feature selection approach.  


Information on the subcellular localization of bacterial proteins is essential for protein function prediction, genome annotation and drug design. Here we proposed a novel approach to predict the subcellular localization of bacterial proteins by fusing features from position-specific score matrix (PSSM), Gene Ontology (GO) and PROFEAT. A backward feature selection approach by linear kennel of SVM was then used to rank the integrated feature vectors and extract optimal features. Finally, SVM was applied for predicting protein subcellular locations based on these optimal features. To validate the performance of our method, we employed jackknife cross-validation tests on three low similarity datasets, i.e., M638, Gneg1456 and Gpos523. The overall accuracies of 94.98%, 93.21%, and 94.57% were achieved for these three datasets, which are higher (from 1.8% to 10.9%) than those by state-of-the-art tools. Comparison results suggest that our method could serve as a very useful vehicle for expediting the prediction of bacterial protein subcellular localization. PMID:24929100

Li, Liqi; Yu, Sanjiu; Xiao, Weidong; Li, Yongsheng; Li, Maolin; Huang, Lan; Zheng, Xiaoqi; Zhou, Shiwen; Yang, Hua



An elusive search for regional flood frequency estimates in the River Nile basin  

NASA Astrophysics Data System (ADS)

Estimation of peak flow quantiles in ungauged catchments is a challenge often faced by water professionals in many parts of the world. Approaches to address such problem exist, but widely used techniques such as flood frequency regionalisation is often not subjected to performance evaluation. In this study, the jack-knifing principle is used to assess the performance of the flood frequency regionalisation in the complex and data-scarce River Nile basin by examining the error (regionalisation error) between locally and regionally estimated peak flow quantiles for different return periods (QT). Agglomerative hierarchical clustering based algorithms were used to search for regions with similar hydrological characteristics. Hydrological data employed were from 180 gauged catchments and several physical characteristics in order to regionalise 365 identified catchments. The Generalised Extreme Value (GEV) distribution, selected using L-moment based approach, was used to construct regional growth curves from which peak flow growth factors could be derived and mapped through interpolation. Inside each region, variations in at-site flood frequency distribution were modelled by regression of the mean annual maximum peak flow (MAF) versus catchment area. The results showed that the performance of the regionalisation is heavily dependent on the historical flow record length and the similarity of the hydrological characteristics inside the regions. The flood frequency regionalisation of the River Nile basin can be improved if sufficient flow data of longer record length of at least 40 yr become available.

Nyeko-Ogiramoi, P.; Willems, P.; Mutua, F. M.; Moges, S. A.



Bacterial community structure and soil properties of a subarctic tundra soil in Council, Alaska.  


The subarctic region is highly responsive and vulnerable to climate change. Understanding the structure of subarctic soil microbial communities is essential for predicting the response of the subarctic soil environment to climate change. To determine the composition of the bacterial community and its relationship with soil properties, we investigated the bacterial community structure and properties of surface soil from the moist acidic tussock tundra in Council, Alaska. We collected 70 soil samples with 25-m intervals between sampling points from 0-10 cm to 10-20 cm depths. The bacterial community was analyzed by pyrosequencing of 16S rRNA genes, and the following soil properties were analyzed: soil moisture content (MC), pH, total carbon (TC), total nitrogen (TN), and inorganic nitrogen (NH4+ and NO3-). The community compositions of the two different depths showed that Alphaproteobacteria decreased with soil depth. Among the soil properties measured, soil pH was the most significant factor correlating with bacterial community in both upper and lower-layer soils. Bacterial community similarity based on jackknifed unweighted unifrac distance showed greater similarity across horizontal layers than through the vertical depth. This study showed that soil depth and pH were the most important soil properties determining bacterial community structure of the subarctic tundra soil in Council, Alaska. PMID:24893754

Kim, Hye Min; Jung, Ji Young; Yergeau, Etienne; Hwang, Chung Yeon; Hinzman, Larry; Nam, Sungjin; Hong, Soon Gyu; Kim, Ok-Sun; Chun, Jongsik; Lee, Yoo Kyung



Predicting DNA binding proteins using support vector machine with hybrid fractal features.  


DNA-binding proteins play a vitally important role in many biological processes. Prediction of DNA-binding proteins from amino acid sequence is a significant but not fairly resolved scientific problem. Chaos game representation (CGR) investigates the patterns hidden in protein sequences, and visually reveals previously unknown structure. Fractal dimensions (FD) are good tools to measure sizes of complex, highly irregular geometric objects. In order to extract the intrinsic correlation with DNA-binding property from protein sequences, CGR algorithm, fractal dimension and amino acid composition are applied to formulate the numerical features of protein samples in this paper. Seven groups of features are extracted, which can be computed directly from the primary sequence, and each group is evaluated by the 10-fold cross-validation test and Jackknife test. Comparing the results of numerical experiments, the group of amino acid composition and fractal dimension (21-dimension vector) gets the best result, the average accuracy is 81.82% and average Matthew's correlation coefficient (MCC) is 0.6017. This resulting predictor is also compared with existing method DNA-Prot and shows better performances. PMID:24189096

Niu, Xiao-Hui; Hu, Xue-Hai; Shi, Feng; Xia, Jing-Bo



Probabilistic principal component analysis for metabolomic data  

PubMed Central

Background Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique for analyzing metabolomic data. However, PCA is limited by the fact that it is not based on a statistical model. Results Here, probabilistic principal component analysis (PPCA) which addresses some of the limitations of PCA, is reviewed and extended. A novel extension of PPCA, called probabilistic principal component and covariates analysis (PPCCA), is introduced which provides a flexible approach to jointly model metabolomic data and additional covariate information. The use of a mixture of PPCA models for discovering the number of inherent groups in metabolomic data is demonstrated. The jackknife technique is employed to construct confidence intervals for estimated model parameters throughout. The optimal number of principal components is determined through the use of the Bayesian Information Criterion model selection tool, which is modified to address the high dimensionality of the data. Conclusions The methods presented are illustrated through an application to metabolomic data sets. Jointly modeling metabolomic data and covariates was successfully achieved and has the potential to provide deeper insight to the underlying data structure. Examination of confidence intervals for the model parameters, such as loadings, allows for principled and clear interpretation of the underlying data structure. A software package called MetabolAnalyze, freely available through the R statistical software, has been developed to facilitate implementation of the presented methods in the metabolomics field. PMID:21092268



Auditory morphology and hearing sensitivity in fossil New World monkeys.  


In recent years it has become possible to investigate the hearing capabilities in fossils by analogy with studies in living taxa that correlate the bony morphology of the auditory system with hearing sensitivity. In this analysis, we used a jack-knife procedure to test the accuracy of one such study that examined the functional morphology of the primate auditory system and we found that low-frequency hearing (sound pressure level at 250 Hz) can be predicted with relatively high confidence (±3-8 dB depending on the structure). Based on these functional relationships, we then used high-resolution computed tomography to examine the auditory region of three fossil New World monkeys (Homunculus, Dolicocebus, and Tremacebus) and compared their morphology and predicted low-frequency sensitivity with a phylogenetically diverse sample of extant primates. These comparisons reveal that these extinct taxa shared many auditory characteristics with living platyrrhines. However, the fossil with the best preserved auditory region (Homunculus) also displayed a few unique features such as the relative size of the tympanic membrane and stapedial footplate and the degree of trabeculation of the anterior accessory cavity. Still, the majority of evidence suggests that these fossil species likely had similar low-frequency sensitivity to extant South American monkeys. This research adds to the small but growing body of evidence on the evolution of hearing abilities in extinct taxa and lays the groundwork for predicting hearing sensitivity in additional fossil primate specimens. PMID:20730868

Coleman, Mark N; Kay, Richard F; Colbert, Matthew W



A computational approach to identify genes for functional RNAs in genomic sequences  

PubMed Central

Currently there is no successful computational approach for identification of genes encoding novel functional RNAs (fRNAs) in genomic sequences. We have developed a machine learning approach using neural networks and support vector machines to extract common features among known RNAs for prediction of new RNA genes in the unannotated regions of prokaryotic and archaeal genomes. The Escherichia coli genome was used for development, but we have applied this method to several other bacterial and archaeal genomes. Networks based on nucleotide composition were 80–90% accurate in jackknife testing experiments for bacteria and 90–99% for hyperthermophilic archaea. We also achieved a significant improvement in accuracy by combining these predictions with those obtained using a second set of parameters consisting of known RNA sequence motifs and the calculated free energy of folding. Several known fRNAs not included in the training datasets were identified as well as several hundred predicted novel RNAs. These studies indicate that there are many unidentified RNAs in simple genomes that can be predicted computationally as a precursor to experimental study. Public access to our RNA gene predictions and an interface for user predictions is available via the web. PMID:11574674

Carter, Richard J.; Dubchak, Inna; Holbrook, Stephen R.



Assessing long-term pH change in an Australian river catchment using monitoring and palaeolimnological data.  


Reviews of stream monitoring data suggest that there has been significant acidification (>1.0 pH unit at some sites) of Victorian streamwaters over the past 3 decades. To assess whether these declines are within the range of natural variability, we developed a diatom model for inferring past pH and applied it to a ca. 3500-yr diatom record from a flood plain lake, Callemondah 1 Billabong, on the Goulburn River, which has among the most substantial observed pH declines. The model has a jackkniffed r2 between diatom inferred and measured pH of 0.77 and a root mean square error of prediction of 0.35 pH units. In the pre-European period, pH was stable (range 6.5-6.7) for approximately 3000 yr. Since European settlement around 160 yr ago, diatom-inferred billabong pH has increased significantly by >0.5 units. We hypothesize that this increase in pH is related to processes associated with land clearance (e.g., increased base cation load and decreased organic acid load). There is no evidence of the recent monitored declines in the Callemondah record, which may indicate that that flood plain lakes and the main stream are experiencing divergent pH trends or that the temporal resolution in the billabong sediment record is insufficient to register recent declines. PMID:12966966

Tibby, John; Reid, Michael A; Fluin, Jennie; Hart, Barry T; Kershaw, A Peter



Demography and randomized life table statistics for peach twig borer Anarsia lineatella (Lepidoptera: Gelechiidae).  


This work studies for first time the effect of constant temperatures (15, 20, 25, 30 and 3 degrees C) on the demography of Anarsia lineatella Zeller (Lepidoptera: Gelechiidae) based on jackknife and bootstrap randomization methods. Male and female longevity was substantially reduced at the higher temperatures in contrast to intermediate and lower temperatures. According to a second order polynomial regression function, high correlations were observed between temperatures and the age of first reproduction as well as temperature and oviposition times. Net reproductive rate was highest at 25 degrees C and 74.172, while the intrinsic rate of increase displayed its highest values at 30 degrees C and was estimated to be 0.238. Birth rate and finite capacity of increase were higher at 30 degrees C and estimated to be 0.235 and 1.268, respectively. Mean generation time and doubling time varied significantly with temperature and the shortest mean generation and doubling time was obtained at 30 degrees C (25.566 and 2.909 d respectively). Life expectancy had its lowest value 10.3 d at 25 degrees C, whereas cohorts that were maintained at 20 and 15 degrees C increased their life expectation approximately three to sixfold. PMID:23786054

Damos, Petros



Application of image analysis techniques to distinguish benign from malignant solitary pulmonary nodules imaged on CT  

NASA Astrophysics Data System (ADS)

The purpose of this research is to characterize solitary pulmonary nodules as benign or malignant based on quantitative measures extracted from high resolution CT images. High resolution CT images of 17 patients with solitary pulmonary nodules and definitive diagnoses were obtained. The diagnoses of these 17 cases (11 benign and 6 malignant) were determined from either radiologic follow-up or pathological specimens. On the HRCT images, solitary nodules were identified using semiautomated contouring techniques. From the resulting contours, several quantitative measures are extracted related to the nodule's size, shape, density and texture. A stepwise discriminant analysis was performed to determine which combination of measures are best able to discriminate between the benign and malignant nodules. Using several selected features, a linear discriminant analysis was performed on the 17 cases. The preliminary discriminant analysis identified two different texture measures as the top features in discriminating between benign and malignant nodules. The linear discriminant analysis using these features correctly classified 16/17 cases (94.1%) of the training set. A less biased estimate, using jackknifed training and testing yielded 15/17 cases (88.2%) correctly classified. The preliminary results of this approach are very promising in characterizing solitary nodules using quantitative measures extracted from HRCT images.

McNitt-Gray, Michael F.; Hart, Eric M.; Wyckoff, Nathaniel; Sayre, James W.; Goldin, Jonathan G.; Aberle, Denise R.



PredHydroxy: computational prediction of protein hydroxylation site locations based on the primary structure.  


Compared to well-known and extensively studied protein phosphorylation, protein hydroxylation attracts much less attention and the molecular mechanism of the hydroxylation is still incompletely understood. And yet annotation of hydroxylation in proteomes is a first-critical step toward decoding protein function and understanding their physiological roles that have been implicated in the pathological processes and providing useful information for the drug designs of various diseases related with hydroxylation. In this work, we present a novel method called PredHydroxy to automate the prediction of the proline and lysine hydroxylation sites based on position weight amino acids composition, 8 high-quality amino acid indices and support vector machines. The PredHydroxy achieved a promising performance with an area under the receiver operating characteristic curve (AUC) of 82.72% and a Matthew's correlation coefficient (MCC) of 69.03% for hydroxyproline as well as an AUC of 87.41% and a MCC of 66.68% for hydroxylysine in jackknife cross-validation. The results obtained from both the cross validation and independent tests suggest that the PredHydroxy might be a powerful and complementary tool for further experimental investigation of protein hydroxylation. Feature analyses demonstrate that hydroxylation and non-hydroxylation have distinct location-specific differences; alpha and turn propensity is of importance for the hydroxylation of proline and lysine residues. A user-friendly server is freely available on the web at: . PMID:25534958

Shi, Shao-Ping; Chen, Xiang; Xu, Hao-Dong; Qiu, Jian-Ding



Prediction of protein structural class using tri-gram probabilities of position-specific scoring matrix and recursive feature elimination.  


Knowledge of structural class plays an important role in understanding protein folding patterns. As a transitional stage in recognition of three-dimensional structure of a protein, protein structural class prediction is considered to be an important and challenging task. In this study, we firstly introduce a feature extraction technique which is based on tri-grams computed directly from position-specific scoring matrix (PSSM). A total of 8,000 features are extracted to represent a protein. Then, support vector machine-recursive feature elimination (SVM-RFE) is applied for feature selection and reduced features are input to a support vector machine (SVM) classifier to predict structural class of a given protein. To examine the effectiveness of our method, jackknife tests are performed on six widely used benchmark datasets, i.e., Z277, Z498, 1189, 25PDB, D640, and D1185. The overall accuracies of 97.1, 98.6, 92.5, 93.5, 94.2, and 95.9 % are achieved on these datasets, respectively. Comparison of the proposed method with other prediction methods shows that our method is very promising to perform the prediction of protein structural class. PMID:25583603

Tao, Peiying; Liu, Taigang; Li, Xiaowei; Chen, Lanming



Variables influencing the presence of subyearling fall Chinook salmon in shoreline habitats of the Hanford Reach, Columbia River  

USGS Publications Warehouse

Little information currently exists on habitat use by subyearling fall Chinook salmon Oncorhynchus tshawytscha rearing in large, main-stem habitats. We collected habitat use information on subyearlings in the Hanford Reach of the Columbia River during May 1994 and April-May 1995 using point abundance electrofishing. We analyzed measures of physical habitat using logistic regression to predict fish presence and absence in shoreline habitats. The difference between water temperature at the point of sampling and in the main river channel was the most important variable for predicting the presence and absence of subyearlings. Mean water velocities of 45 cm/s or less and habitats with low lateral bank slopes were also associated with a greater likelihood of subyearling presence. Intermediate-sized gravel and cobble substrates were significant predictors of fish presence, but small (256-mm) substrates were not. Our rearing model was accurate at predicting fish presence and absence using jackknifing (80% correct) and classification of observations from an independent data set (76% correct). The habitat requirements of fall Chinook salmon in the Hanford Reach are similar to those reported for juvenile Chinook salmon in smaller systems but are met in functionally different ways in a large river.

Tiffan, K.F.; Clark, L.O.; Garland, R.D.; Rondorf, D.W.



Human DNA Ligase III Recognizes DNA Ends by Dynamic Switching between Two DNA-Bound States  

SciTech Connect

Human DNA ligase III has essential functions in nuclear and mitochondrial DNA replication and repair and contains a PARP-like zinc finger (ZnF) that increases the extent of DNA nick joining and intermolecular DNA ligation, yet the bases for ligase III specificity and structural variation among human ligases are not understood. Here combined crystal structure and small-angle X-ray scattering results reveal dynamic switching between two nick-binding components of ligase III: the ZnF-DNA binding domain (DBD) forms a crescent-shaped surface used for DNA end recognition which switches to a ring formed by the nucleotidyl transferase (NTase) and OB-fold (OBD) domains for catalysis. Structural and mutational analyses indicate that high flexibility and distinct DNA binding domain features in ligase III assist both nick sensing and the transition from nick sensing by the ZnF to nick joining by the catalytic core. The collective results support a 'jackknife model' in which the ZnF loads ligase III onto nicked DNA and conformational changes deliver DNA into the active site. This work has implications for the biological specificity of DNA ligases and functions of PARP-like zinc fingers.

Cotner-Gohara, Elizabeth; Kim, In-Kwon; Hammel, Michal; Tainer, John A.; Tomkinson, Alan E.; Ellenberger, Tom (Scripps); (Maryland-MED); (WU-MED); (LBNL)



Evaluation of marked-recapture for estimating striped skunk abundance  

USGS Publications Warehouse

The mark-recapture method for estimating striped skunk (Mephitis mephitis) abundance was evaluated by systematically livetrapping a radio-equipped population on a 31.4-km2 study area in North Dakota during late April of 1977 and 1978. The study population was 10 females and 13 males in 1977 and 20 females and 8 males in 1978. Skunks were almost exclusively nocturnal. Males traveled greater nightly distances than females (3.3 vs. 2.6 km, P < 0.05) and had larger home ranges (308 vs. 242 ha) although not significantly so. Increased windchill reduced night-time activity. The population was demographically but not geographically closed. Frequency of capture was positively correlated with time skunks spent on the study area. Little variation in capture probabilities was found among trap-nights. Skunks exhibited neither trap-proneness nor shyness. Capture rates in 1977 were higher for males than for females; the reverse occurred in 1978. Variation in individual capture rates was indicated among males in 1977 and among females in 1978. Ten estimators produced generally similar results, but all underestimated true population size. Underestimation was a function of the number of untrapped skunks, primarily those that spent limited time on the study area. The jackknife method produced the best estimates of skunk abundance.

Greenwood, R.J.; Sargeant, A.B.; Johnson, D.H.



PSSP-RFE: Accurate Prediction of Protein Structural Class by Recursive Feature Extraction from PSI-BLAST Profile, Physical-Chemical Property and Functional Annotations  

PubMed Central

Protein structure prediction is critical to functional annotation of the massively accumulated biological sequences, which prompts an imperative need for the development of high-throughput technologies. As a first and key step in protein structure prediction, protein structural class prediction becomes an increasingly challenging task. Amongst most homological-based approaches, the accuracies of protein structural class prediction are sufficiently high for high similarity datasets, but still far from being satisfactory for low similarity datasets, i.e., below 40% in pairwise sequence similarity. Therefore, we present a novel method for accurate and reliable protein structural class prediction for both high and low similarity datasets. This method is based on Support Vector Machine (SVM) in conjunction with integrated features from position-specific score matrix (PSSM), PROFEAT and Gene Ontology (GO). A feature selection approach, SVM-RFE, is also used to rank the integrated feature vectors through recursively removing the feature with the lowest ranking score. The definitive top features selected by SVM-RFE are input into the SVM engines to predict the structural class of a query protein. To validate our method, jackknife tests were applied to seven widely used benchmark datasets, reaching overall accuracies between 84.61% and 99.79%, which are significantly higher than those achieved by state-of-the-art tools. These results suggest that our method could serve as an accurate and cost-effective alternative to existing methods in protein structural classification, especially for low similarity datasets. PMID:24675610

Yu, Sanjiu; Zhang, Yuan; Luo, Zhong; Yang, Hua; Zhou, Yue; Zheng, Xiaoqi



Transient neurologic syndrome after spinal anesthesia with epidural steroid treatment  

PubMed Central

Background: Transient neurologic syndrome (TNS) is a rare complication of spinal and epidural anesthesia. It is defined as paradoxic postoperative back pain radiating to the lower extremities with no neurologic deficits. Because it is a self-limited disease, the treatment is usually symptomatic and consists of NSAIDs and injections of a neuromuscular-blocking drug at the trigger points. The syndrome may be resistant to this treatment regimen and may last for several months, resulting in a long convalescence. Case summary: A 63-year-old Turkish woman (height, 165 cm; weight, 71 kg) underwent hemorrhoidectomy in the jackknife position using spinal anesthesia. No adverse events occurred during puncture or surgery or in the immediate postoperative recovery period. Recovery from the sensory and motor block was normal. Twenty-four hours after surgery, lower limb and plantar pain developed with no sensory or motor deficit. Neurologic examination revealed normal motor and sensory function. Electroneuromyography showed partial denervation potential of muscles innervated by the left sciatic nerve. The symptoms were suggestive of TNS. Combination oral NSAID treatment with amitriptyline (25 mg/d) and gabapentin (1200 mg/d) was initiated. Because the pain still persisted 6 weeks after surgery, epidural steroid injection with triamcinolone acetate (80 mg) with isotonic saline was administered, resulting in definite pain relief (visual analog scale score = 0). Conclusions: Epidural steroid treatment was effective in this patient with TNS resistant to treatment with NSAIDs, amitriptyline, and gabapentin. Future studies are needed to evaluate this treatment. PMID:24683240

Cöcelli, L. Pirbudak; Erkutlu, Ibrahim; Karakurum, Gunhan; Avci, Neslihan; Gül, Rauf; Öner, Ünsal



Limited sampling hampers “big data” estimation of species richness in a tropical biodiversity hotspot  

PubMed Central

Macro-scale species richness studies often use museum specimens as their main source of information. However, such datasets are often strongly biased due to variation in sampling effort in space and time. These biases may strongly affect diversity estimates and may, thereby, obstruct solid inference on the underlying diversity drivers, as well as mislead conservation prioritization. In recent years, this has resulted in an increased focus on developing methods to correct for sampling bias. In this study, we use sample-size-correcting methods to examine patterns of tropical plant diversity in Ecuador, one of the most species-rich and climatically heterogeneous biodiversity hotspots. Species richness estimates were calculated based on 205,735 georeferenced specimens of 15,788 species using the Margalef diversity index, the Chao estimator, the second-order Jackknife and Bootstrapping resampling methods, and Hill numbers and rarefaction. Species richness was heavily correlated with sampling effort, and only rarefaction was able to remove this effect, and we recommend this method for estimation of species richness with “big data” collections. PMID:25692000

Engemann, Kristine; Enquist, Brian J; Sandel, Brody; Boyle, Brad; Jørgensen, Peter M; Morueta-Holme, Naia; Peet, Robert K; Violle, Cyrille; Svenning, Jens-Christian



Predicting the subcellular localization of mycobacterial proteins by incorporating the optimal tripeptides into the general form of pseudo amino acid composition.  


Mycobacterium tuberculosis is a bacterium that causes tuberculosis, one of the most prevalent infectious diseases. Predicting the subcellular localization of mycobacterial proteins in this bacterium may provide vital clues for the prediction of protein function as well as for drug discovery and design. Therefore, a computational method that can predict the subcellular localization of mycobacterial proteins with high precision is highly desirable. We propose a computational method to predict the subcellular localization of mycobacterial proteins. An objective and strict benchmark dataset was constructed after collecting 272 non-redundant proteins from the universal protein resource (the UniProt database). Subsequently, a novel feature selection strategy based on binomial distribution was used to optimize the feature vector. Finally, a subset containing 219 chosen tripeptide features was imported into a support vector machine-based method to estimate the performance of the dataset in accurately and sensitively identifying these proteins. We found that the proposed method gave a maximum overall accuracy of 89.71% with an average accuracy of 81.12% in the jackknife cross-validation. The results indicate that our prediction method gave an efficient and powerful performance when compared with other published methods. We made the proposed method available on a purpose built Web server called MycoSub that is freely accessible at . We anticipate that MycoSub will become a useful tool for studying the functions of mycobacterial proteins and for designing and developing anti-mycobacterium drugs. PMID:25437899

Zhu, Pan-Pan; Li, Wen-Chao; Zhong, Zhe-Jin; Deng, En-Ze; Ding, Hui; Chen, Wei; Lin, Hao



Mem-PHybrid: hybrid features-based prediction system for classifying membrane protein types.  


Membrane proteins are a major class of proteins and encoded by approximately 20% to 30% of genes in most organisms. In this work, a two-layer novel membrane protein prediction system, called Mem-PHybrid, is proposed. It is able to first identify the protein query as a membrane or nonmembrane protein. In the second level, it further identifies the type of membrane protein. The proposed Mem-PHybrid prediction system is based on hybrid features, whereby a fusion of both the physicochemical and split amino acid composition-based features is performed. This enables the proposed Mem-PHybrid to exploit the discrimination capabilities of both types of feature extraction strategy. In addition, minimum redundancy and maximum relevance has also been applied to reduce the dimensionality of a feature vector. We employ random forest, evidence-theoretic K-nearest neighbor, and support vector machine (SVM) as classifiers and analyze their performance on two datasets. SVM using hybrid features yields the highest accuracy of 89.6% and 97.3% on dataset1 and 91.5% and 95.5% on dataset2 for jackknife and independent dataset tests, respectively. The enhanced prediction performance of Mem-PHybrid is largely attributed to the exploitation of the discrimination power of the hybrid features and of the learning capability of SVM. Mem-PHybrid is accessible at http://www. PMID:22342883

Hayat, Maqsood; Khan, Asifullah



Neural bases of atypical emotional face processing in autism: A meta-analysis of fMRI studies.  


Objectives. We aim to outline the neural correlates of atypical emotional face processing in individuals with ASD. Methods. A comprehensive literature search was conducted through electronic databases to identify functional magnetic resonance imaging (fMRI) studies of whole brain analysis with emotional-face processing tasks in individuals with ASD. The Signed Differential Mapping with random effects model was used to conduct meta-analyses. Identified fMRI studies were further divided into sub-groups based on contrast ("emotional-face vs. non-emotional-face" or "emotional-face vs. non-face") to confirm the results of a meta-analysis of the whole studies. Results. Thirteen studies with 226 individuals with ASD and 251 typically developing people were identified. We found ASD-related hyperactivation in subcortical structures, including bilateral thalamus, bilateral caudate, and right precuneus, and ASD-related hypoactivation in the hypothalamus during emotional-face processing. Sub-analyses with more homogeneous contrasts preserved the findings of the main analysis such as hyperactivation in sub-cortical structure. Jackknife analyses showed that hyperactivation of the left caudate was the most robust finding. Conclusions. Abnormalities in the subcortical structures, such as amygdala, hypothalamus and basal ganglia, are associated with atypical emotional-face processing in individuals with ASD. PMID:25264291

Aoki, Yuta; Cortese, Samuele; Tansella, Michele



Identifying the Subfamilies of Voltage-Gated Potassium Channels Using Feature Selection Technique  

PubMed Central

Voltage-gated K+ channel (VKC) plays important roles in biology procession, especially in nervous system. Different subfamilies of VKCs have different biological functions. Thus, knowing VKCs’ subfamilies has become a meaningful job because it can guide the direction for the disease diagnosis and drug design. However, the traditional wet-experimental methods were costly and time-consuming. It is highly desirable to develop an effective and powerful computational tool for identifying different subfamilies of VKCs. In this study, a predictor, called iVKC-OTC, has been developed by incorporating the optimized tripeptide composition (OTC) generated by feature selection technique into the general form of pseudo-amino acid composition to identify six subfamilies of VKCs. One of the remarkable advantages of introducing the optimized tripeptide composition is being able to avoid the notorious dimension disaster or over fitting problems in statistical predictions. It was observed on a benchmark dataset, by using a jackknife test, that the overall accuracy achieved by iVKC-OTC reaches to 96.77% in identifying the six subfamilies of VKCs, indicating that the new predictor is promising or at least may become a complementary tool to the existing methods in this area. It has not escaped our notice that the optimized tripeptide composition can also be used to investigate other protein classification problems. PMID:25054318

Liu, Wei-Xin; Deng, En-Ze; Chen, Wei; Lin, Hao



Driver assistance system for passive multi-trailer vehicles with haptic steering limitations on the leading unit.  


Driving vehicles with one or more passive trailers has difficulties in both forward and backward motion due to inter-unit collisions, jackknife, and lack of visibility. Consequently, advanced driver assistance systems (ADAS) for multi-trailer combinations can be beneficial to accident avoidance as well as to driver comfort. The ADAS proposed in this paper aims to prevent unsafe steering commands by means of a haptic handwheel. Furthermore, when driving in reverse, the steering-wheel and pedals can be used as if the vehicle was driven from the back of the last trailer with visual aid from a rear-view camera. This solution, which can be implemented in drive-by-wire vehicles with hitch angle sensors, profits from two methods previously developed by the authors: safe steering by applying a curvature limitation to the leading unit, and a virtual tractor concept for backward motion that includes the complex case of set-point propagation through on-axle hitches. The paper addresses system requirements and provides implementation details to tele-operate two different off- and on-axle combinations of a tracked mobile robot pulling and pushing two dissimilar trailers. PMID:23552102

Morales, Jesús; Mandow, Anthony; Martínez, Jorge L; Reina, Antonio J; García-Cerezo, Alfonso



Crash involvement of large trucks by configuration: a case-control study.  

PubMed Central

For a two-year period, large truck crashes on the interstate system in Washington State were investigated using a case-control method. For each large truck involved in a crash, three trucks were randomly selected for inspection from the traffic stream at the same time and place as the crash but one week later. The effects of truck and driver characteristics on crashes were assessed by comparing their relative frequency among the crash-involved and comparison sample trucks. Double trailer trucks were consistently overinvolved in crashes by a factor of two to three in both single and multiple vehicle crashes. Single unit trucks pulling trailers also were overinvolved. Doubles also had a higher frequency of jackknifing compared to tractor-trailers. The substantial overinvolvement of doubles in crashes was found regardless of driver age, hours of driving, cargo weight, or type of fleet. Younger drivers, long hours of driving, and operating empty trucks were also associated with higher crash involvement. PMID:3354729

Stein, H S; Jones, I S



Driver Assistance System for Passive Multi-Trailer Vehicles with Haptic Steering Limitations on the Leading Unit  

PubMed Central

Driving vehicles with one or more passive trailers has difficulties in both forward and backward motion due to inter-unit collisions, jackknife, and lack of visibility. Consequently, advanced driver assistance systems (ADAS) for multi-trailer combinations can be beneficial to accident avoidance as well as to driver comfort. The ADAS proposed in this paper aims to prevent unsafe steering commands by means of a haptic handwheel. Furthermore, when driving in reverse, the steering-wheel and pedals can be used as if the vehicle was driven from the back of the last trailer with visual aid from a rear-view camera. This solution, which can be implemented in drive-by-wire vehicles with hitch angle sensors, profits from two methods previously developed by the authors: safe steering by applying a curvature limitation to the leading unit, and a virtual tractor concept for backward motion that includes the complex case of set-point propagation through on-axle hitches. The paper addresses system requirements and provides implementation details to tele-operate two different off- and on-axle combinations of a tracked mobile robot pulling and pushing two dissimilar trailers. PMID:23552102

Morales, Jesús; Mandow, Anthony; Martínez, Jorge L.; Reina, Antonio J.; García-Cerezo, Alfonso



Analysis and identification of essential genes in humans using topological properties and biological information.  


Genes that are indispensable for survival are termed essential genes. The analysis and identification of essential genes are very important for understanding the minimal requirements of cellular survival and for practical purposes. Proteins do not exert their function in isolation of one another but rather interact together in PPI networks. A global analysis of protein interaction networks provides an effective way to elucidate the relationships between proteins. With the recent large-scale identifications of essential genes and the production of large amounts of PPIs in humans, we are able to investigate the topological properties and biological properties of essential genes. However, until recently, no one has ever investigated human essential genes using topological and biological properties. In this study, for the first time, 28 topological properties and 22 biological properties were used to investigate the characteristics of essential and non-essential genes in humans. Most of the properties were statistically discriminative between essential and non-essential genes. The F-score was used to estimate the essentiality of each property. The GO-enrichment analysis was performed to investigate the functions of the essential and non-essential genes. Finally, based on the topological features and the biological characteristics, a machine-learning classifier was constructed to predict the essential genes. The results of the jackknife test and 10-fold cross validation test are encouraging, indicating that our classifier is an effective human essential gene discovery method. PMID:25168893

Yang, Lei; Wang, Jizhe; Wang, Huiping; Lv, Yingli; Zuo, Yongchun; Li, Xiang; Jiang, Wei




SciTech Connect

We present new measurements of the redshift-space three-point correlation function (3PCF) of Luminous Red Galaxies (LRGs) from the Sloan Digital Sky Survey (SDSS). Using the largest data set to date, the Data Release 7 LRGs, and an improved binning scheme compared to previous measurements, we measure the LRG 3PCF on large scales up to {approx}90 h{sup -1} Mpc, from the mildly nonlinear to quasi-linear regimes. Comparing the LRG correlations to the dark matter two- and three-point correlation functions, obtained from N-body simulations we infer linear and nonlinear bias parameters. As expected, LRGs are highly biased tracers of large-scale structure, with a linear bias b{sub 1} {approx} 2; the LRGs also have a large positive nonlinear bias parameter, in agreement with predictions of galaxy population models. The use of the 3PCF to estimate biasing helps to also make estimates of the cosmological parameter {sigma}{sub 8}, as well as to infer best-fit parameters of the halo occupation distribution parameters for LRGs. We also use a large suite of public mock catalogs to characterize the error covariance matrix for the 3PCF and compare the variance among simulation results with jackknife error estimates.

Marin, Felipe, E-mail: [Department of Astronomy and Astrophysics and Kavli Institute for Cosmological Physics, University of Chicago, Chicago, IL 60637 (United States); Centre for Astrophysics and Supercomputing, Swinburne University of Technology, P.O. Box 218, Hawthorn, VIC 3122 (Australia)



iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition  

PubMed Central

The ?54 promoters are unique in prokaryotic genome and responsible for transcripting carbon and nitrogen-related genes. With the avalanche of genome sequences generated in the postgenomic age, it is highly desired to develop automated methods for rapidly and effectively identifying the ?54 promoters. Here, a predictor called ‘iPro54-PseKNC’ was developed. In the predictor, the samples of DNA sequences were formulated by a novel feature vector called ‘pseudo k-tuple nucleotide composition’, which was further optimized by the incremental feature selection procedure. The performance of iPro54-PseKNC was examined by the rigorous jackknife cross-validation tests on a stringent benchmark data set. As a user-friendly web-server, iPro54-PseKNC is freely accessible at For the convenience of the vast majority of experimental scientists, a step-by-step protocol guide was provided on how to use the web-server to get the desired results without the need to follow the complicated mathematics that were presented in this paper just for its integrity. Meanwhile, we also discovered through an in-depth statistical analysis that the distribution of distances between the transcription start sites and the translation initiation sites were governed by the gamma distribution, which may provide a fundamental physical principle for studying the ?54 promoters. PMID:25361964

Lin, Hao; Deng, En-Ze; Ding, Hui; Chen, Wei; Chou, Kuo-Chen



Estimating treatment effects in a two-arm parallel trial of a continuous?outcome.  


For a continuous outcome in a two-arm trial that satisfies normal distribution assumptions, we can transform the standardized mean difference with the use of the cumulative distribution function to be the effect size measure?P(X?jackknife methods to estimate confidence intervals against two further methods for estimating P(X?

Nunney, Ian; Clark, Allan; Shepstone, Lee



Calibration plots for risk prediction models in the presence of competing risks.  


A predicted risk of 17% can be called reliable if it can be expected that the event will occur to about 17 of 100 patients who all received a predicted risk of 17%. Statistical models can predict the absolute risk of an event such as cardiovascular death in the presence of competing risks such as death due to other causes. For personalized medicine and patient counseling, it is necessary to check that the model is calibrated in the sense that it provides reliable predictions for all subjects. There are three often encountered practical problems when the aim is to display or test if a risk prediction model is well calibrated. The first is lack of independent validation data, the second is right censoring, and the third is that when the risk scale is continuous, the estimation problem is as difficult as density estimation. To deal with these problems, we propose to estimate calibration curves for competing risks models based on jackknife pseudo-values that are combined with a nearest neighborhood smoother and a cross-validation approach to deal with all three problems. PMID:24668611

Gerds, Thomas A; Andersen, Per K; Kattan, Michael W



Phylogenetic relationships in the order Ericales s.l.: analyses of molecular data from five genes from the plastid and mitochondrial genomes.  


Phylogenetic interrelationships in the enlarged order Ericales were investigated by jackknife analysis of a combination of DNA sequences from the plastid genes rbcL, ndhF, atpB, and the mitochondrial genes atp1 and matR. Several well-supported groups were identified, but neither a combination of all gene sequences nor any one alone fully resolved the relationships between all major clades in Ericales. All investigated families except Theaceae were found to be monophyletic. Four families, Marcgraviaceae, Balsaminaceae, Pellicieraceae, and Tetrameristaceae form a monophyletic group that is the sister of the remaining families. On the next higher level, Fouquieriaceae and Polemoniaceae form a clade that is sister to the majority of families that form a group with eight supported clades between which the interrelationships are unresolved: Theaceae-Ternstroemioideae with Ficalhoa, Sladenia, and Pentaphylacaceae; Theaceae-Theoideae; Ebenaceae and Lissocarpaceae; Symplocaceae; Maesaceae, Theophrastaceae, Primulaceae, and Myrsinaceae; Styracaceae and Diapensiaceae; Lecythidaceae and Sapotaceae; Actinidiaceae, Roridulaceae, Sarraceniaceae, Clethraceae, Cyrillaceae, and Ericaceae. PMID:21665668

Anderberg, Arne A; Rydin, Catarina; Källersjö, Mari



iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition.  


The ?(54) promoters are unique in prokaryotic genome and responsible for transcripting carbon and nitrogen-related genes. With the avalanche of genome sequences generated in the postgenomic age, it is highly desired to develop automated methods for rapidly and effectively identifying the ?(54) promoters. Here, a predictor called 'iPro54-PseKNC' was developed. In the predictor, the samples of DNA sequences were formulated by a novel feature vector called 'pseudo k-tuple nucleotide composition', which was further optimized by the incremental feature selection procedure. The performance of iPro54-PseKNC was examined by the rigorous jackknife cross-validation tests on a stringent benchmark data set. As a user-friendly web-server, iPro54-PseKNC is freely accessible at For the convenience of the vast majority of experimental scientists, a step-by-step protocol guide was provided on how to use the web-server to get the desired results without the need to follow the complicated mathematics that were presented in this paper just for its integrity. Meanwhile, we also discovered through an in-depth statistical analysis that the distribution of distances between the transcription start sites and the translation initiation sites were governed by the gamma distribution, which may provide a fundamental physical principle for studying the ?(54) promoters. PMID:25361964

Lin, Hao; Deng, En-Ze; Ding, Hui; Chen, Wei; Chou, Kuo-Chen



Effect of temperature on the life-history traits of Neoseiulus californicus (Acari: Phytoseiidae) fed on Panonychus ulmi.  


The developmental rate and reproductive biology of Neoseiulus californicus, a generalist predator on spider mites and small insects, was investigated in the laboratory at five constant temperatures: 15, 20, 25, 30, and 34°C. The European red mite, Panonychus ulmi, an important pest in Korean apple orchards, was used as prey. Mean developmental time and adult longevity were inversely related to temperature from 15 to 30°C. Lifetime fecundity was greatest at 25°C, whereas daily fecundity was highest at 30°C. The sex ratio (female to male) was highest (0.77) at 25°C and lowest (0.67) at 34°C. Survivorship during immature development varied from 74.3 to 92.9%, with the lowest rate at 34°C. Life table parameters were analyzed and pseudo-replicates for the generation time (t ( G )), the intrinsic rate of natural increase (r (m)), finite rate of increase (?), net reproductive rate (R (0)), and doubling time (t ( D )) were generated using the Jackknife method. Generation time (t ( G )) was lowest (10.7 days) at 34°C, R (0) was highest (49.2) at 25°C, and both r (m) (0.29) and ? (1.34) were highest at 30°C. In conclusion, the development and adult life-history traits obtained for N. californicus fed on P. ulmi indicated significant potential for biological control. PMID:22270114

El Taj, H F; Jung, Chuleui



Prediction of subcellular location of apoptosis proteins combining tri-gram encoding based on PSSM and recursive feature elimination.  


Knowledge of apoptosis proteins plays an important role in understanding the mechanism of programmed cell death. Obtaining information on subcellular location of apoptosis proteins is very helpful to reveal the apoptosis mechanism and understand the function of apoptosis proteins. Because of the cost in time and labor associated with large-scale wet-bench experiments, computational prediction of apoptosis proteins subcellular location becomes very important and many computational tools have been developed in the recent decades. Existing methods differ in the protein sequence representation techniques and classification algorithms adopted. In this study, we firstly introduce a sequence encoding scheme based on tri-grams computed directly from position-specific score matrices, which incorporates evolution information represented in the PSI-BLAST profile and sequence-order information. Then SVM-RFE algorithm is applied for feature selection and reduced vectors are input to a support vector machine classifier to predict subcellular location of apoptosis proteins. Jackknife tests on three widely used datasets show that our method provides the state-of-the-art performance in comparison with other existing methods. PMID:25463695

Liu, Taigang; Tao, Peiying; Li, Xiaowei; Qin, Yufang; Wang, Chunhua



Predicting Protein Phenotypes Based on Protein-Protein Interaction Network  

PubMed Central

Background Identifying associated phenotypes of proteins is a challenge of the modern genetics since the multifactorial trait often results from contributions of many proteins. Besides the high-through phenotype assays, the computational methods are alternative ways to identify the phenotypes of proteins. Methodology/Principal Findings Here, we proposed a new method for predicting protein phenotypes in yeast based on protein-protein interaction network. Instead of only the most likely phenotype, a series of possible phenotypes for the query protein were generated and ranked acording to the tethering potential score. As a result, the first order prediction accuracy of our method achieved 65.4% evaluated by Jackknife test of 1,267 proteins in budding yeast, much higher than the success rate (15.4%) of a random guess. And the likelihood of the first 3 predicted phenotypes including all the real phenotypes of the proteins was 70.6%. Conclusions/Significance The candidate phenotypes predicted by our method provided useful clues for the further validation. In addition, the method can be easily applied to the prediction of protein associated phenotypes in other organisms. PMID:21423698

Liu, Xiao-Jun; Cai, Yu-Dong



PSSP-RFE: accurate prediction of protein structural class by recursive feature extraction from PSI-BLAST profile, physical-chemical property and functional annotations.  


Protein structure prediction is critical to functional annotation of the massively accumulated biological sequences, which prompts an imperative need for the development of high-throughput technologies. As a first and key step in protein structure prediction, protein structural class prediction becomes an increasingly challenging task. Amongst most homological-based approaches, the accuracies of protein structural class prediction are sufficiently high for high similarity datasets, but still far from being satisfactory for low similarity datasets, i.e., below 40% in pairwise sequence similarity. Therefore, we present a novel method for accurate and reliable protein structural class prediction for both high and low similarity datasets. This method is based on Support Vector Machine (SVM) in conjunction with integrated features from position-specific score matrix (PSSM), PROFEAT and Gene Ontology (GO). A feature selection approach, SVM-RFE, is also used to rank the integrated feature vectors through recursively removing the feature with the lowest ranking score. The definitive top features selected by SVM-RFE are input into the SVM engines to predict the structural class of a query protein. To validate our method, jackknife tests were applied to seven widely used benchmark datasets, reaching overall accuracies between 84.61% and 99.79%, which are significantly higher than those achieved by state-of-the-art tools. These results suggest that our method could serve as an accurate and cost-effective alternative to existing methods in protein structural classification, especially for low similarity datasets. PMID:24675610

Li, Liqi; Cui, Xiang; Yu, Sanjiu; Zhang, Yuan; Luo, Zhong; Yang, Hua; Zhou, Yue; Zheng, Xiaoqi



Evaluation of the potential of Raman microspectroscopy for prediction of chemotherapeutic response to cisplatin in lung adenocarcinoma.  


The study of the interaction of anticancer drugs with mammalian cells in vitro is important to elucidate the mechanisms of action of the drug on its biological targets. In this context, Raman spectroscopy is a potential candidate for high throughput, non-invasive analysis. To explore this potential, the interaction of cis-diamminedichloroplatinum(II) (cisplatin) with a human lung adenocarcinoma cell line (A549) was investigated using Raman microspectroscopy. The results were correlated with parallel measurements from the MTT cytotoxicity assay, which yielded an IC(50) value of 1.2 ± 0.2 µM. To further confirm the spectral results, Raman spectra were also acquired from DNA extracted from A549 cells exposed to cisplatin and from unexposed controls. Partial least squares (PLS) multivariate regression and PLS Jackknifing were employed to highlight spectral regions which varied in a statistically significant manner with exposure to cisplatin and with the resultant changes in cellular physiology measured by the MTT assay. The results demonstrate the potential of the cellular Raman spectrum to non-invasively elucidate spectral changes that have their origin either in the biochemical interaction of external agents with the cell or its physiological response, allowing the prediction of the cellular response and the identification of the origin of the chemotherapeutic response at a molecular level in the cell. PMID:20931112

Nawaz, Haq; Bonnier, Franck; Knief, Peter; Howe, Orla; Lyng, Fiona M; Meade, Aidan D; Byrne, Hugh J



The potential distribution of Phlebotomus papatasi (Diptera: Psychodidae) in Libya based on ecological niche model.  


The increased cases of cutaneous leishmaniasis vectored by Phlebotomus papatasi (Scopoli) in Libya have driven considerable effort to develop a predictive model for the potential geographical distribution of this disease. We collected adult P. papatasi from 17 sites in Musrata and Yefern regions of Libya using four different attraction traps. Our trap results and literature records describing the distribution of P. papatasi were incorporated into a MaxEnt algorithm prediction model that used 22 environmental variables. The model showed a high performance (AUC = 0.992 and 0.990 for training and test data, respectively). High suitability for P. papatasi was predicted to be largely confined to the coast at altitudes <600 m. Regions south of 300 degrees N latitude were calculated as unsuitable for this species. Jackknife analysis identified precipitation as having the most significant predictive power, while temperature and elevation variables were less influential. The National Leishmaniasis Control Program in Libya may find this information useful in their efforts to control zoonotic cutaneous leishmaniasis. Existing records are strongly biased toward a few geographical regions, and therefore, further sand fly collections are warranted that should include documentation of such factors as soil texture and humidity, land cover, and normalized difference vegetation index (NDVI) data to increase the model's predictive power. PMID:22679884

Abdel-Dayem, M S; Annajar, B B; Hanafi, H A; Obenauer, P J



Predicting deleterious non-synonymous single nucleotide polymorphisms in signal peptides based on hybrid sequence attributes.  


Signal peptides play a crucial role in various biological processes, such as localization of cell surface receptors, translocation of secreted proteins and cell-cell communication. However, the amino acid mutation in signal peptides, also called non-synonymous single nucleotide polymorphisms (nsSNPs or SAPs) may lead to the loss of their functions. In the present study, a computational method was proposed for predicting deleterious nsSNPs in signal peptides based on random forest (RF) by incorporating position specific scoring matrix (PSSM) profile, SignalP score and physicochemical properties. These features were optimized by the maximum relevance minimum redundancy (mRMR) method. Then, a cost matrix was used to minimize the effect of the imbalanced data classification problem that usually occurred in nsSNPs prediction. The method achieved an overall accuracy of 84.5% and the area under the ROC curve (AUC) of 0.822 by Jackknife test, when the optimal subset included 10 features. Furthermore, on the same dataset, we compared our predictor with other existing methods, including R-score-based method and D-score-based methods, and the result of our method was superior to those of the two methods. The satisfactory performance suggests that our method is effective in predicting the deleterious nsSNPs in signal peptides. PMID:22277674

Qin, Wenli; Li, Yizhou; Li, Juan; Yu, Lezheng; Wu, Di; Jing, Runyu; Pu, Xuemei; Guo, Yanzhi; Li, Menglong



North American Tropical Cyclone Landfall and SST: A Statistical Model Study  

NASA Technical Reports Server (NTRS)

A statistical-stochastic model of the complete life cycle of North Atlantic (NA) tropical cyclones (TCs) is used to examine the relationship between climate and landfall rates along the North American Atlantic and Gulf Coasts. The model draws on archived data of TCs throughout the North Atlantic to estimate landfall rates at high geographic resolution as a function of the ENSO state and one of two different measures of sea surface temperature (SST): 1) SST averaged over the NA subtropics and the hurricane season and 2) this SST relative to the seasonal global subtropical mean SST (termed relSST). Here, the authors focus on SST by holding ENSO to a neutral state. Jackknife uncertainty tests are employed to test the significance of SST and relSST landfall relationships. There are more TC and major hurricane landfalls overall in warm years than cold, using either SST or relSST, primarily due to a basinwide increase in the number of storms. The signal along the coast, however, is complex. Some regions have large and significant sensitivity (e.g., an approximate doubling of annual major hurricane landfall probability on Texas from -2 to +2 standard deviations in relSST), while other regions have no significant sensitivity (e.g., the U.S. mid-Atlantic and Northeast coasts). This geographic structure is due to both shifts in the regions of primary TC genesis and shifts in TC propagation.

Hall, Timothy; Yonekura, Emmi



Prediction of space sickness in astronauts from preflight fluid, electrolyte, and cardiovascular variables and Weightless Environmental Training Facility (WETF) training  

NASA Technical Reports Server (NTRS)

Nine preflight variables related to fluid, electrolyte, and cardiovascular status from 64 first-time Shuttle crewmembers were differentially weighted by discrimination analysis to predict the incidence and severity of each crewmember's space sickness as rated by NASA flight surgeons. The nine variables are serum uric acid, red cell count, environmental temperature at the launch site, serum phosphate, urine osmolality, serum thyroxine, sitting systolic blood pressure, calculated blood volume, and serum chloride. Using two methods of cross-validation on the original samples (jackknife and a stratefied random subsample), these variables enable the prediction of space sickness incidence (NONE or SICK) with 80 percent sickness and space severity (NONE, MILD, MODERATE, of SEVERE) with 59 percent success by one method of cross-validation and 67 percent by another method. Addition of a tenth variable, hours spent in the Weightlessness Environment Training Facility (WETF) did not improve the prediction of space sickness incidences but did improve the prediction of space sickness severity to 66 percent success by the first method of cross-validation of original samples and to 71 percent by the second method. Results to date suggest the presence of predisposing physiologic factors to space sickness that implicate fluid shift etiology. The data also suggest that prior exposure to fluid shift during WETF training may produce some circulatory pre-adaption to fluid shifts in weightlessness that results in a reduction of space sickness severity.

Simanonok, K.; Mosely, E.; Charles, J.



Orthology Inference in Nonmodel Organisms Using Transcriptomes and Low-Coverage Genomes: Improving Accuracy and Matrix Occupancy for Phylogenomics  

PubMed Central

Orthology inference is central to phylogenomic analyses. Phylogenomic data sets commonly include transcriptomes and low-coverage genomes that are incomplete and contain errors and isoforms. These properties can severely violate the underlying assumptions of orthology inference with existing heuristics. We present a procedure that uses phylogenies for both homology and orthology assignment. The procedure first uses similarity scores to infer putative homologs that are then aligned, constructed into phylogenies, and pruned of spurious branches caused by deep paralogs, misassembly, frameshifts, or recombination. These final homologs are then used to identify orthologs. We explore four alternative tree-based orthology inference approaches, of which two are new. These accommodate gene and genome duplications as well as gene tree discordance. We demonstrate these methods in three published data sets including the grape family, Hymenoptera, and millipedes with divergence times ranging from approximately 100 to over 400 Ma. The procedure significantly increased the completeness and accuracy of the inferred homologs and orthologs. We also found that data sets that are more recently diverged and/or include more high-coverage genomes had more complete sets of orthologs. To explicitly evaluate sources of conflicting phylogenetic signals, we applied serial jackknife analyses of gene regions keeping each locus intact. The methods described here can scale to over 100 taxa. They have been implemented in python with independent scripts for each step, making it easy to modify or incorporate them into existing pipelines. All scripts are available from PMID:25158799

Yang, Ya; Smith, Stephen A.



Prediction of Drugs Target Groups Based on ChEBI Ontology  

PubMed Central

Most drugs have beneficial as well as adverse effects and exert their biological functions by adjusting and altering the functions of their target proteins. Thus, knowledge of drugs target proteins is essential for the improvement of therapeutic effects and mitigation of undesirable side effects. In the study, we proposed a novel prediction method based on drug/compound ontology information extracted from ChEBI to identify drugs target groups from which the kind of functions of a drug may be deduced. By collecting data in KEGG, a benchmark dataset consisting of 876 drugs, categorized into four target groups, was constructed. To evaluate the method more thoroughly, the benchmark dataset was divided into a training dataset and an independent test dataset. It is observed by jackknife test that the overall prediction accuracy on the training dataset was 83.12%, while it was 87.50% on the test dataset—the predictor exhibited an excellent generalization. The good performance of the method indicates that the ontology information of the drugs contains rich information about their target groups, and the study may become an inspiration to solve the problems of this sort and bridge the gap between ChEBI ontology and drugs target groups. PMID:24350241

Gao, Yu-Fei; Chen, Lei; Huang, Guo-Hua; Zhang, Tao; Feng, Kai-Yan; Li, Hai-Peng; Jiang, Yang



[Composition of the Araneae (Arachnida) fauna of the provincial Iberá Reserve, Corrientes, Argentina].  


A survey of the spider community composition and diversity was carried out in grasslands and woods in three localities: Colonia Pellegrini, Paraje Galarza and Estancia Rinc6n (Iberá province Reserve). Pit fall traps, leaf litter sifting, foliage beating, hand collecting and sweep nets were used. Shannon's diversity index, evenness, Berger-Parker's dominance index, beta and gamma diversity were calculated, and a checklist of spider fauna was compiled. Species richness was estimated by Chao 1, Chao 2, first and second order Jack-knife. A total of 4,138 spiders grouped into 150 species from 33 families of Araneomorphae and two species from two families of Mygalomorphae were collected. Five species are new records for Argentina and eleven for Corrientes province. Araneidae was the most abundant family (39.8%), followed by Salticidae (10.9%), Anyphaenidae (7.9%), Tetragnathidae (7.4%), and Lycosidae (5.5%). The other families represented less than 5% of the total catch. The web-builder guild had the highest number of specimens and the highest richness index. The abundance, observed richness, Shannon diversity and evenness indexes were highest in Colonia Pellegrini woodland and Paraje Galarza grassland. Alpha diversity represented 89% of the gamma; the remaining 11% corresponded to beta diversity. According to the indexes, between 67% and 97% of the existing spider fauna was represented in the collected specimens from Iberá. PMID:19637711

Avalos, Gilberto; Damborsky, Miryam P; Bar, María E; Oscherov, Elena B; Porcel, E



Synergism between constituents of multicomponent catalysts designed for ethanol steam reforming using partial least squares regression and artificial neural networks.  


Effects of different catalyst components on the catalytic performance in steam reforming of ethanol have been investigated by means of Artificial Neural Networks (ANNs) and Partial Least Square regression (PLSR). The data base consisted of ca. 400 items (catalysts with varied composition), which were obtained from a former catalyst optimization procedure. Marten's uncertainty (jackknife) test showed that simultaneous addition of Ni and Co has crucial effect on the hydrogen production. The catalyst containing both Ni and Co provided remarkable hydrogen production at 450°C. The addition of Ceas modifier to the bimetallic NiCo catalyst has high importance at lower temperatures: the hydrogen concentration is doubled at 350°C. Addition of Pt had only little effect on the product distribution. The outliers in the data set have been investigated by means of Hotelling T2 control chart. Compositions containing high amount of Cu or Ce have been identified as outliers, which points to the nonlinear effect of Cu and Ce on the catalytic performance. ANNs were used for analysis of the non-linear effects: an optimum was found with increasing amount of Cu and Ce in the catalyst composition. Hydrogen production can be improved by Ce only in the absence of Zn. Additionally, negative cross-effect was evidenced between Ni and Cu. The above relationships have been visualized in Holographic Maps, too. Although predictive ability of PLSR is somewhat worse than that of ANN, PLSR provided indirect evidence that ANNs were trained adequately. PMID:21902647

Szijjárto, Gábor P; Tompos, András; Héberger, Károly; Margitfalvi, József L



Orthology inference in nonmodel organisms using transcriptomes and low-coverage genomes: improving accuracy and matrix occupancy for phylogenomics.  


Orthology inference is central to phylogenomic analyses. Phylogenomic data sets commonly include transcriptomes and low-coverage genomes that are incomplete and contain errors and isoforms. These properties can severely violate the underlying assumptions of orthology inference with existing heuristics. We present a procedure that uses phylogenies for both homology and orthology assignment. The procedure first uses similarity scores to infer putative homologs that are then aligned, constructed into phylogenies, and pruned of spurious branches caused by deep paralogs, misassembly, frameshifts, or recombination. These final homologs are then used to identify orthologs. We explore four alternative tree-based orthology inference approaches, of which two are new. These accommodate gene and genome duplications as well as gene tree discordance. We demonstrate these methods in three published data sets including the grape family, Hymenoptera, and millipedes with divergence times ranging from approximately 100 to over 400 Ma. The procedure significantly increased the completeness and accuracy of the inferred homologs and orthologs. We also found that data sets that are more recently diverged and/or include more high-coverage genomes had more complete sets of orthologs. To explicitly evaluate sources of conflicting phylogenetic signals, we applied serial jackknife analyses of gene regions keeping each locus intact. The methods described here can scale to over 100 taxa. They have been implemented in python with independent scripts for each step, making it easy to modify or incorporate them into existing pipelines. All scripts are available from PMID:25158799

Yang, Ya; Smith, Stephen A



Identification of core T cell network based on immunome interactome  

PubMed Central

Background Data-driven studies on the dynamics of reconstructed protein-protein interaction (PPI) networks facilitate investigation and identification of proteins important for particular processes or diseases and reduces time and costs of experimental verification. Modeling the dynamics of very large PPI networks is computationally costly. Results To circumvent this problem, we created a link-weighted human immunome interactome and performed filtering. We reconstructed the immunome interactome and weighed the links using jackknife gene expression correlation of integrated, time course gene expression data. Statistical significance of the links was computed using the Global Statistical Significance (GloSS) filtering algorithm. P-values from GloSS were computed for the integrated, time course gene expression data. We filtered the immunome interactome to identify core components of the T cell PPI network (TPPIN). The interconnectedness of the major pathways for T cell survival and response, including the T cell receptor, MAPK and JAK-STAT pathways, are maintained in the TPPIN network. The obtained TPPIN network is supported both by Gene Ontology term enrichment analysis along with study of essential genes enrichment. Conclusions By integrating gene expression data to the immunome interactome and using a weighted network filtering method, we identified the T cell PPI immune response network. This network reveals the most central and crucial network in T cells. The approach is general and applicable to any dataset that contains sufficient information. PMID:24528953



A Swiss Watch Running on Chilean Time: A Progress Report on Two New Automated CORALIE RV Pipelines  

NASA Astrophysics Data System (ADS)

We present the current status of two new fully automated reduction and analysis pipelines, built for the Euler telescope and the CORALIE spectrograph. Both pipelines have been designed and built independently at the Universidad de Chile and Universidad Catolica by the two authors. Each pipeline has also been written on two different platforms, IDL and Python, and both can run fully automatically through full reduction and analysis of CORALIE datasets. The reduction goes through all standard steps from bias subtraction, flat-fielding, scattered light removal, optimal extraction and full wavelength calibration of the data using well exposed ThAr arc lamps. The reduced data are then cross-correlated with a binary template matched to the spectral type of each star and the cross-correlation functions are fit with a Gaussian to extract precision radial-velocities. For error analysis we are currently testing bootstrap, jackknifing and cross validation methods to properly determine uncertainties directly from the data. Our pipelines currently show long term stability at the 12-15m/s level, measured by observations of two known radial-velocity standard stars. In the near future we plan to get the stability down to the 5-6m/s level and also transfer these pipelines to other instruments like HARPS.

Jenkins, J. S.; Jordán, A.



A meta-analysis of voxel-based morphometry studies on gray matter volume alteration in juvenile myoclonic epilepsy.  


The findings of structural neuroimaging studies on gray matter volume (GMV) of juvenile myoclonic epilepsy (JME) with voxel-based morphometry (VBM) were inconsistent. We aim to evaluate consistent gray matter changes in JME quantitatively. A systematic review of VBM studies on GMV of patients with JME and healthy control (HC) subjects indexed in PubMed and EMBASE from January 1990 to June 2012 was conducted. Coordinates were extracted from clusters of significant GMV difference between patients with JME and HC subjects. Meta-analysis was performed using Effect Size Signed Differential Mapping (ES-SDM). Seven studies with a total of 211 JME patients and 241 HC subjects were included in the meta-analysis. Increased GMV were observed in the bilateral medial frontal gyrus and anterior cingulate, whereas decreased GMV in the bilateral thalamus. The findings remain largely unchanged in the jackknife sensitivity analyses. The meta-analysis not only identified consistent changes in some regions of gray matter in patients with JME, but also supports the notion of thalamocortical circuitry involved in the pathogenesis of JME. PMID:23962795

Cao, Bei; Tang, Yingying; Li, Jianpeng; Zhang, Xiang; Shang, Hui-Fang; Zhou, Dong



Comparing two correlated C indices with right-censored survival outcome: a one-shot nonparametric approach.  


The area under the receiver operating characteristic curve is often used as a summary index of the diagnostic ability in evaluating biomarkers when the clinical outcome (truth) is binary. When the clinical outcome is right-censored survival time, the C index, motivated as an extension of area under the receiver operating characteristic curve, has been proposed by Harrell as a measure of concordance between a predictive biomarker and the right-censored survival outcome. In this work, we investigate methods for statistical comparison of two diagnostic or predictive systems, of which they could either be two biomarkers or two fixed algorithms, in terms of their C indices. We adopt a U-statistics-based C estimator that is asymptotically normal and develop a nonparametric analytical approach to estimate the variance of the C estimator and the covariance of two C estimators. A z-score test is then constructed to compare the two C indices. We validate our one-shot nonparametric method via simulation studies in terms of the type I error rate and power. We also compare our one-shot method with resampling methods including the jackknife and the bootstrap. Simulation results show that the proposed one-shot method provides almost unbiased variance estimations and has satisfactory type I error control and power. Finally, we illustrate the use of the proposed method with an example from the Framingham Heart Study. Copyright © 2014 John Wiley & Sons, Ltd. PMID:25399736

Kang, Le; Chen, Weijie; Petrick, Nicholas A; Gallas, Brandon D



COMDYN: Software to study the dynamics of animal communities using a capture-recapture approach  

USGS Publications Warehouse

COMDYN is a set of programs developed for estimation of parameters associated with community dynamics using count data from two locations or time periods. It is Internet-based, allowing remote users either to input their own data, or to use data from the North American Breeding Bird Survey for analysis. COMDYN allows probability of detection to vary among species and among locations and time periods. The basic estimator for species richness underlying all estimators is the jackknife estimator proposed by Burnham and Overton. Estimators are presented for quantities associated with temporal change in species richness, including rate of change in species richness over time, local extinction probability, local species turnover and number of local colonizing species. Estimators are also presented for quantities associated with spatial variation in species richness, including relative richness at two locations and proportion of species present in one location that are also present at a second location. Application of the estimators to species richness estimation has been previously described and justified. The potential applications of these programs are discussed.

Hines, J.E.; Boulinier, T.; Nichols, J.D.; Sauer, J.R.; Pollock, K.H.



Computer aided morphometry of the neonatal fetal alcohol syndrome face  

NASA Astrophysics Data System (ADS)

Facial dysmorphology related to Fetal Alcohol Syndrome (FAS) has been studied from neonatal snapshots with computer-aided imaging tools by looking at facial landmarks and silhouettes. Statistical methods were used to characterize FAS-related midfacial hypoplasia by using standardized landmark coordinates of frontal and profile snapshots. Additional analyses were performed by tracing a segment of the facial silhouettes from the profile snapshots. In spite of inherent distortions due to the coordinate standardization procedure, controlled for race, three significant facial landmark coordinates accounted for 30.6% of the explained variance of FAS. Residualized for race, eight points along the silhouettes were shown to be significant in explaining 45.8% of the outcome variance. Combining the landmark coordinates and silhouettes points, 57% of the outcome variance was explained. Finally, including birthweight with landmark coordinates and silhouettes, 63% of the outcome variance was explained, with a jackknifed sensitivity of 95% (19/20) and a specificity of 92.9% (52/56).

Chik, Lawrence; Sokol, Robert J.; Martier, Susan S.



Multivariate seismic calibration for the Novaya Zemlya test site. Report No. 2, 27 June 1991-22 June 1992  

SciTech Connect

Within the last year, Soviet yield data have been acquired by DARPA for over 40 underground nuclear explosions at the Novaya Zemlya Test Site between 1964 and 1990. These yields are compared to previous estimates by other authors, based on observed seismic magnitudes and magnitude-log yield relations transported from other test sites. Several discrepancies in the yield data are noted. Seismic magnitude data, based on NORSAR Lg and P coda, Grafenberg Lg, and a world-wide m sub b, have been published by Ringdal and Fyen (1991) for 18 of these events. A similar set of Soviet network magnitudes have been published by Israelsson (1992). Using these data, estimates of the multivariate calibration parameters of the magnitude-log yield relations are computed. An outlier test is applied to the residuals to the lines of best fit. One of the two smallest events is identified as an outlier for every multivariate magnitude combination. A classical confidence interval is presented to estimate future yields, based on estimates of the unknown multivariate calibration parameters. A test of TTBT compliance and a definition of the F-number, based on the confidence interval, are also provided. F-number estimates are obtained for various magnitude combinations by jackknifing. The reliability of the results is discussed, in light of the fact that the data are tightly clustered for 16 of the 18 events.

Fisk, M.D.; Gray, H.L.; Alewine, R.W.; McCartor, G.D.



The Transparency of Galaxy Clusters  

E-print Network

If galaxy clusters contain intracluster dust, the spectra of galaxies lying behind clusters should show attenuation by dust absorption. We compare the optical (3500 - 7200 \\AA) spectra of 60,267 luminous, early-type galaxies selected from the Sloan Digital Sky Survey to search for the signatures of intracluster dust in z ~ 0.05 clusters. We select massive, quiescent (i.e., non-star-forming) galaxies using an EW(Halpha) <= 2 \\AA cut and consider galaxies in three bins of velocity dispersion, ranging from 150 to 300 km s^{-1}. The uniformity of early-type galaxy spectra in the optical allows us to construct inverse-variance-weighted composite spectra with high signal-to-noise ratio (ranging from 10^2-10^3). We compare the composite spectra of galaxies that lie behind and adjacent to galaxy clusters and find no convincing evidence of dust attenuation on scales ~ 0.15-2 Mpc; we derive a generic limit of E(B-V) < 3 x 10^{-3} mag on scales ~ 1-2 Mpc at the 99% confidence level, using conservative jackknife error bars, corresponding to a dust mass <~ 10^8 $M_{\\odot}$. On scales smaller than 1 Mpc this limit is slightly weaker, E(B-V) < 8 x 10^{-3} mag.

Jo Bovy; David W. Hogg; John Moustakas



The Effects of Topography on Shortwave solar radiation modelling: The JGrass-NewAge System way  

NASA Astrophysics Data System (ADS)

The NewAGE-SwRB and NewAGE-DEC-MOD's are the two components of JGrass-NewAge hydrological modeling system to estimate the shortwave incident radiation. Shortwave solar radiation at the land surface is influenced by topographic parameters such as slope, aspect, altitude, and skyview factor, hence, detail analyses and discussions on their effect is the way to improve the modeling approach. The NewAGE-SwRB accounts for slope, aspect, shadow and the topographical information of the sites to estimate the cloudless irradiance. The first part of the paper is on the topographic parameter analysis using Udig GIS spatial toolbox, which is integrated in JGrass-NewAge system, and indicates the effect of each topographic parameters on the shortwave radiation. A statistical study on station topographic geometry (slope, aspect, altitude and Sky-view factor) and correlation of pairs of measurements of station analyzed to get closer look at the impact of rugged topography. The jackknife correlation coefficients has been used to analyze the estimate bias between shortwave radiations in different topographic geometric position, thereby helping to develop generalized linear models to explain the impacts of those topographic features. In addition to the NewAGE-SwRB accounts for the topographical parameters, there are three (an estimation of the visibility extent(V), the single-scattering albedo fraction of incident energy scattered to total attenuation by aerosols (Wo), and fraction of forward scattering to total scattering (Fs )) parameter needed to run the NewAGE-DEC-MOD's component. Sufficient knowledge regarding the magnitude and spatial distribution of the these parameters are very crucial. In this paper, the particle swarm NewAge component of the NewAge System used for automatic calibration of NewAGE-DEC-MOD's parameters for each stations based on different optimization and objective functions. Finally, the estimated parameters for all measurements station are interpolated in space, and, Kriging spatial interpolation techniques has applied to give their spatial structure. Different variogram models were determined to explain the spatial corrologram of parameters over space, and in return, used to estimate spatially distributed parameters using kriging. Jackknife kriging, which is a rekriging of each station by eliminating one sample from the original sample set and then taking the average of the rekriged estimates, has been used to test the practical validity of the model. The method gives better estimation and also resulting with standard deviation as useful indicator of uncertainty associated with station estimates. This analysis helps to understand spatial variability of radiative transmittance with position, height, aspect, slope and other topographic features. Two basin shortwave radiation data set (one in flat topography and the other in mountainous topography) are used to test statistical analysis of the modeling components of JGrass-NewAGE model systems.

Abera, Wuletawu; Formetta, Giuseppe; Rigon, Riccardo



The Internal Pudendal Artery Perforator Thigh Flap: A New Freestyle Pedicle Flap for the Ischial Region  

PubMed Central

Background: Recurrence and complication rates of pressure sores are highest in the ischial region, and other donor sites are needed for recurrent pressure sores. The potential of a new freestyle pedicle flap for ischial lesions, an internal pudendal artery perforator (iPap) thigh flap, was examined through anatomical and theoretical analyses and a case series using computed tomography angiography. Methods: The skin flap was designed in the thigh region based on an iPap. The skin perforators were marked with a Doppler probe. One patient underwent computed tomography angiography with fistulography to identify the damage to or effects on the pedicle vessels of the flap. Debridement of ischial lesions and flap elevation were performed in the jackknife position. Results: The iPap thigh flaps were performed in 5 patients, 4 with ischial pressure sores and 1 with calcinosis cutis of the ischial region. The width and length of the flaps ranged from 5 to 8?cm (mean, 6.6?cm) and 10 to 17?cm (mean, 12.6?cm), respectively. Three patients underwent partial osteotomy of the ischial bone. No complications, including flap necrosis or wound dehiscence of the donor and reconstructed sites, were observed. Conclusions: The perforator vessels of the internal pudendal artery are very close to the ischial tuberosity. Blood flow to the flap is reliable when careful debridement of the pressure sore is performed. The iPap thigh flap is a new option for soft-tissue defects in the ischial region, including ischial pressure sores. PMID:25289335

Goishi, Keiichi; Abe, Yoshiro; Takaku, Mitsuru; Seike, Takuya; Harada, Hiroshi; Nakanishi, Hideki



A comparison of ROC inferred from FROC and conventional ROC  

NASA Astrophysics Data System (ADS)

This study aims to determine whether receiver operating characteristic (ROC) scores inferred from free-response receiver operating characteristic (FROC) were equivalent to conventional ROC scores for the same readers and cases. Forty-five examining radiologists of the American Board of Radiology independently reviewed 47 PA chest radiographs under at least two conditions. Thirty-seven cases had abnormal findings and 10 cases had normal findings. Half the readers were asked to first locate any visualized lung nodules, mark them and assign a level of confidence [the FROC mark-rating pair] and second give an overall to the entire image on the same scale [the ROC score]. The second half of readers gave the ROC rating first followed by the FROC mark-rating pairs. A normal image was represented with number 1 and malignant lesions with numbers 2-5. A jackknife free-response receiver operating characteristic (JAFROC), and inferred ROC (infROC) was calculated from the mark-rating pairs using JAFROC V4.1 software. ROC based on the overall rating of the image calculated using DBM MRMC software, which was also used to compare infROC and ROC AUCs treating the methods as modalities. Pearson's correlations coefficient and linear regression were used to examine their relationship using SPSS, version 21.0; (SPSS, Chicago, IL). The results of this study showed no significant difference between the ROC and Inferred ROC AUCs (p?0.25). While Pearson's correlation coefficient was 0.7 (p?0.01). Inter-reader correlation calculated from Obuchowski- Rockette covariance's ranged from 0.43-0.86 while intra-reader agreement was greater than previously reported ranging from 0.68-0.82.

McEntee, Mark F.; Littlefair, Stephen; Pietrzyk, Mariusz W.



Efficacy of digital breast tomosynthesis for breast cancer diagnosis  

NASA Astrophysics Data System (ADS)

Purpose: To compare the diagnostic performance of digital breast tomosynthesis (DBT) in combination with digital mammography (DM) with that of digital mammography alone. Materials and Methods: Twenty six experienced radiologists who specialized in breast imaging read 50 cases (27 cancers and 23 non-cancer cases) of patients who underwent DM and DBT. Both exams included the craniocaudal (CC) and mediolateral oblique (MLO) views. Histopathologic examination established truth in all lesions. Each case was interpreted in two modes, once with DM alone followed by DM+DBT, and the observers were asked to mark the location of any lesions, if present, and give it a score based on a five-category assessment by the Royal Australian and New Zealand College of Radiologists (RANZCR). The diagnostic performance of DM compared with that of DM+DBT was evaluated in terms of the difference between areas under receiver-operating characteristic curves (AUCs), Jackknife free-response receiver operator characteristics (JAFROC) figure-of-merit, sensitivity, location sensitivity and specificity. Results: Average AUC and JAFROC for DM versus DM+DBT was significantly different (AUCs 0.690 vs 0.781, p=< 0.0001), (JAFROC 0.618 vs. 0.732, p=< 0.0001) respectively. In addition, the use of DM+DBT resulted in an improvement in sensitivity (0.629 vs. 0.701, p=0.0011), location sensitivity (0.548 vs. 0.690, p=< 0.0001) and specificity (0.656 vs. 0.758, p=0.0015) when compared to DM alone. Conclusion: Adding DBT to the standard DM significantly improved radiologists' performance in terms of AUCs, JAFROC figure of merit, sensitivity, location sensitivity and specificity values.

Alakhras, M.; Mello-Thoms, C.; Rickard, M.; Bourne, R.; Brennan, P. C.



H-ATLAS: estimating redshifts of Herschel sources from sub-mm fluxes  

NASA Astrophysics Data System (ADS)

Upon its completion, the Herschel Astrophysics Terahertz Large Area Survey (H-ATLAS) will be the largest sub-millimetre survey to date, detecting close to half-a-million sources. It will only be possible to measure spectroscopic redshifts for a small fraction of these sources. However, if the rest-frame spectral energy distribution (SED) of a typical H-ATLAS source is known, this SED and the observed Herschel fluxes can be used to estimate the redshifts of the H-ATLAS sources without spectroscopic redshifts. In this paper, we use a sub-set of 40 H-ATLAS sources with previously measured redshifts in the range 0.5 < z < 4.2 to derive a suitable average template for high-redshift H-ATLAS sources. We find that a template with two dust components (Tc = 23.9 K, Th = 46.9 K and ratio of mass of cold dust to mass of warm dust of 30.1) provides a good fit to the rest-frame fluxes of the sources in our calibration sample. We use a jackknife technique to estimate the accuracy of the redshifts estimated with this template, finding a root mean square of ?z/(1 + z) = 0.26. For sources for which there is prior information that they lie at z > 1, we estimate that the rms of ?z/(1 + z) = 0.12. We have used this template to estimate the redshift distribution for the sources detected in the H-ATLAS equatorial fields, finding a bimodal distribution with a mean redshift of 1.2, 1.9 and 2.5 for 250, 350 and 500 ?m selected sources, respectively.

Pearson, E. A.; Eales, S.; Dunne, L.; Gonzalez-Nuevo, J.; Maddox, S.; Aguirre, J. E.; Baes, M.; Baker, A. J.; Bourne, N.; Bradford, C. M.; Clark, C. J. R.; Cooray, A.; Dariush, A.; De Zotti, G.; Dye, S.; Frayer, D.; Gomez, H. L.; Harris, A. I.; Hopwood, R.; Ibar, E.; Ivison, R. J.; Jarvis, M.; Krips, M.; Lapi, A.; Lupu, R. E.; Micha?owski, M. J.; Rosenman, M.; Scott, D.; Valiante, E.; Valtchanov, I.; van der Werf, P.; Vieira, J. D.



A comparison of Australian and USA radiologists' performance in detection of breast cancer  

NASA Astrophysics Data System (ADS)

The aim of current work was to compare the performance of radiologists that read a higher number of cases to those that read a lower number, as well as examine the effect of number of years of experience on performance. This study compares Australian and USA radiologist with differing levels of experience when reading mammograms. Thirty mammographic cases were presented to 41 radiologists, 21 from Australia and 20 from the USA. Readers were asked to locate and visualize cancer and assign a mark-rating pair with confidence levels from 1 to 5. A jackknife free-response receiver operating characteristic (JAFROC), inferred receiver operating characteristic (ROC), sensitivity, specificity and location sensitivity were calculated. A Mann-Whitney test was used to compare the performance of Australian and USA radiologists using SPSS software. The results showed that the USA radiologists sampled had more years of experience (p?0.01) but read less mammograms per year (p?0.03). Significantly higher sensitivity and location sensitivity (p? 0.001) were found for the Australia radiologists when experience and the number of mammograms read per year were taken into account. There were no differences between the two countries in overall performance measured by JAFROC and inferred ROC. For the most experienced radiologists within the Australian sample experienced ROC and location sensitivity were higher when compared to the least experienced. The increased number of years experience of the USA radiologists did not result in an increase in any performance metrics. The number of cases per year is a better predictor of improved diagnostic performance.

Suleiman, Wasfi I.; Georgian-Smith, Dianne; Evanoff, Michael G.; Lewis, Sarah; McEntee, Mark F.



Comparison of soil bacterial communities of Pinus patula of Nilgiris, western ghats with other biogeographically distant pine forest clone libraries.  


The bacterial community structure of the rhizosphere and non-rhizosphere soil of Pinus patula, found in the Nilgiris region of Western Ghats, was studied by constructing 16S rRNA gene clone libraries. In the rhizosphere and non-rhizosphere soil clone libraries constructed, 13 and 15 bacterial phyla were identified, respectively. The clone libraries showed the predominance of members of culturally underrepresented phyla like Acidobacteria and Verrucomicrobia. The Alphaproteobacteria and Acidobacteria clones were predominant in rhizosphere and non-rhizosphere soil samples, respectively. In rhizosphere, amongst Alphaproteobacteria members, Bradyrhizobium formed the significant proportion, whereas in non-rhizosphere, members of subdivision-6 of phylum Acidobacteria were abundant. The diversity analysis of P. patula soil libraries showed that the phylotypes (16S rRNA gene similarity cutoff, ?97 %) of Acidobacteria and Bacteroidetes were relatively predominant and diverse followed by Alphaproteobacteria and Verrucomicrobia. The diversity indices estimated higher richness and abundance of bacteria in P. patula soil clone libraries than the pine forest clone libraries retrieved from previous studies. The tools like principal co-ordinate analysis and Jackknife cluster analysis, which were under UniFrac analysis indicated that variations in soil bacterial communities were attributed to their respective geographical locations due to the phylogenetic divergence amongst the clone libraries. Overall, the P. patula rhizosphere and non-rhizosphere clone libraries were found significantly unique in composition, evenly distributed and highly rich in phylotypes, amongst the biogeographically distant clone libraries. It was finally hypothesised that the phylogenetic divergence amongst the bacterial phylotypes and natural selection plays a pivotal role in the variations of bacterial communities across the geographical distance. PMID:23274880

Rohini-Kumar, M; Osborne, Jabez W; Saravanan, V S



Asymmetric constriction of dividing Escherichia coli cells induced by expression of a fusion between two min proteins.  


The Min system, consisting of MinC, MinD, and MinE, plays an important role in localizing the Escherichia coli cell division machinery to midcell by preventing FtsZ ring (Z ring) formation at cell poles. MinC has two domains, MinCn and MinCc, which both bind to FtsZ and act synergistically to inhibit FtsZ polymerization. Binary fission of E. coli usually proceeds symmetrically, with daughter cells at roughly 180° to each other. In contrast, we discovered that overproduction of an artificial MinCc-MinD fusion protein in the absence of other Min proteins induced frequent and dramatic jackknife-like bending of cells at division septa, with cell constriction predominantly on the outside of the bend. Mutations in the fusion known to disrupt MinCc-FtsZ, MinCc-MinD, or MinD-membrane interactions largely suppressed bending division. Imaging of FtsZ-green fluorescent protein (GFP) showed no obvious asymmetric localization of FtsZ during MinCc-MinD overproduction, suggesting that a downstream activity of the Z ring was inhibited asymmetrically. Consistent with this, MinCc-MinD fusions localized predominantly to segments of the Z ring at the inside of developing cell bends, while FtsA (but not ZipA) tended to localize to the outside. As FtsA is required for ring constriction, we propose that this asymmetric localization pattern blocks constriction of the inside of the septal ring while permitting continued constriction of the outside portion. PMID:24682325

Rowlett, Veronica Wells; Margolin, William



Reliability of Different Mark-Recapture Methods for Population Size Estimation Tested against Reference Population Sizes Constructed from Field Data  

PubMed Central

Reliable estimates of population size are fundamental in many ecological studies and biodiversity conservation. Selecting appropriate methods to estimate abundance is often very difficult, especially if data are scarce. Most studies concerning the reliability of different estimators used simulation data based on assumptions about capture variability that do not necessarily reflect conditions in natural populations. Here, we used data from an intensively studied closed population of the arboreal gecko Gehyra variegata to construct reference population sizes for assessing twelve different population size estimators in terms of bias, precision, accuracy, and their 95%-confidence intervals. Two of the reference populations reflect natural biological entities, whereas the other reference populations reflect artificial subsets of the population. Since individual heterogeneity was assumed, we tested modifications of the Lincoln-Petersen estimator, a set of models in programs MARK and CARE-2, and a truncated geometric distribution. Ranking of methods was similar across criteria. Models accounting for individual heterogeneity performed best in all assessment criteria. For populations from heterogeneous habitats without obvious covariates explaining individual heterogeneity, we recommend using the moment estimator or the interpolated jackknife estimator (both implemented in CAPTURE/MARK). If data for capture frequencies are substantial, we recommend the sample coverage or the estimating equation (both models implemented in CARE-2). Depending on the distribution of catchabilities, our proposed multiple Lincoln-Petersen and a truncated geometric distribution obtained comparably good results. The former usually resulted in a minimum population size and the latter can be recommended when there is a long tail of low capture probabilities. Models with covariates and mixture models performed poorly. Our approach identified suitable methods and extended options to evaluate the performance of mark-recapture population size estimators under field conditions, which is essential for selecting an appropriate method and obtaining reliable results in ecology and conservation biology, and thus for sound management. PMID:24896260

Grimm, Annegret; Gruber, Bernd; Henle, Klaus



BICEP2 I: Detection Of B-mode Polarization at Degree Angular Scales  

E-print Network

(abridged for arXiv) We report results from the BICEP2 experiment, a cosmic microwave background (CMB) polarimeter specifically designed to search for the signal of inflationary gravitational waves in the B-mode power spectrum around $\\ell\\sim80$. The telescope comprised a 26 cm aperture all-cold refracting optical system equipped with a focal plane of 512 antenna coupled transition edge sensor 150 GHz bolometers each with temperature sensitivity of $\\approx300\\mu\\mathrm{K}_\\mathrm{CMB}\\sqrt{s}$. BICEP2 observed from the South Pole for three seasons from 2010 to 2012. A low-foreground region of sky with an effective area of 380 square deg was observed to a depth of 87 nK deg in Stokes $Q$ and $U$. We find an excess of $B$-mode power over the base lensed-LCDM expectation in the range $30 5\\sigma$. Through jackknife tests and simulations we show that systematic contamination is much smaller than the observed excess. We also examine a number of available models of polarized dust emission and find that at their default parameter values they predict power $\\sim(5-10)\\times$ smaller than the observed excess signal. However, these models are not sufficiently constrained to exclude the possibility of dust emission bright enough to explain the entire excess signal. Cross correlating BICEP2 against 100 GHz maps from the BICEP1 experiment, the excess signal is confirmed and its spectral index is found to be consistent with that of the CMB, disfavoring dust at $1.7\\sigma$. The observed $B$-mode power spectrum is well fit by a lensed-LCDM + tensor theoretical model with tensor-to-scalar ratio $r=0.20^{+0.07}_{-0.05}$, with $r=0$ disfavored at $7.0\\sigma$. Accounting for the contribution of foreground dust will shift this value downward by an amount which will be better constrained with upcoming data sets.

P. A. R Ade; R. W. Aikin; D. Barkats; S. J. Benton; C. A. Bischoff; J. J. Bock; J. A. Brevik; I. Buder; E. Bullock; C. D. Dowell; L. Duband; J. P. Filippini; S. Fliescher; S. R. Golwala; M. Halpern; M. Hasselfield; S. R. Hildebrandt; G. C. Hilton; V. V. Hristov; K. D. Irwin; K. S. Karkare; J. P. Kaufman; B. G. Keating; S. A. Kernasovskiy; J. M. Kovac; C. L. Kuo; E. M. Leitch; M. Lueker; P. Mason; C. B. Netterfield; H. T. Nguyen; R. O'Brient; R. W. Ogburn IV; A. Orlando; C. Pryke; C. D. Reintsema; S. Richter; R. Schwarz; C. D. Sheehy; Z. K. Staniszewski; R. V. Sudiwala; G. P. Teply; J. E. Tolan; A. D. Turner; A. G. Vieregg; C. L. Wong; K. W. Yoon



Modelling temperature, photoperiod and vernalization responses of Brunonia australis (Goodeniaceae) and Calandrinia sp. (Portulacaceae) to predict flowering time  

PubMed Central

Background and Aims Crop models for herbaceous ornamental species typically include functions for temperature and photoperiod responses, but very few incorporate vernalization, which is a requirement of many traditional crops. This study investigated the development of floriculture crop models, which describe temperature responses, plus photoperiod or vernalization requirements, using Australian native ephemerals Brunonia australis and Calandrinia sp. Methods A novel approach involved the use of a field crop modelling tool, DEVEL2. This optimization program estimates the parameters of selected functions within the development rate models using an iterative process that minimizes sum of squares residual between estimated and observed days for the phenological event. Parameter profiling and jack-knifing are included in DEVEL2 to remove bias from parameter estimates and introduce rigour into the parameter selection process. Key Results Development rate of B. australis from planting to first visible floral bud (VFB) was predicted using a multiplicative approach with a curvilinear function to describe temperature responses and a broken linear function to explain photoperiod responses. A similar model was used to describe the development rate of Calandrinia sp., except the photoperiod function was replaced with an exponential vernalization function, which explained a facultative cold requirement and included a coefficient for determining the vernalization ceiling temperature. Temperature was the main environmental factor influencing development rate for VFB to anthesis of both species and was predicted using a linear model. Conclusions The phenology models for B. australis and Calandrinia sp. described development rate from planting to VFB and from VFB to anthesis in response to temperature and photoperiod or vernalization and may assist modelling efforts of other herbaceous ornamental plants. In addition to crop management, the vernalization function could be used to identify plant communities most at risk from predicted increases in temperature due to global warming. PMID:23404991

Cave, Robyn L.; Hammer, Graeme L.; McLean, Greg; Birch, Colin J.; Erwin, John E.; Johnston, Margaret E.



Test–Retest Intervisit Variability of Functional and Structural Parameters in X-Linked Retinoschisis  

PubMed Central

Purpose To examine the variability of four outcome measures that could be used to address safety and efficacy in therapeutic trials with X-linked juvenile retinoschisis. Methods Seven men with confirmed mutations in the RS1 gene were evaluated over four visits spanning 6 months. Assessments included visual acuity, full-field electroretinograms (ERG), microperimetric macular sensitivity, and retinal thickness measured by optical coherence tomography (OCT). Eyes were separated into Better or Worse Eye groups based on acuity at baseline. Repeatability coefficients were calculated for each parameter and jackknife resampling used to derive 95% confidence intervals (CIs). Results The threshold for statistically significant change in visual acuity ranged from three to eight letters. For ERG a-wave, an amplitude reduction greater than 56% would be considered significant. For other parameters, variabilities were lower in the Worse Eye group, likely a result of floor effects due to collapse of the schisis pockets and/or retinal atrophy. The criteria for significant change (Better/Worse Eye) for three important parameters were: ERG b/a-wave ratio (0.44/0.23), point wise sensitivity (10.4/7.0 dB), and central retinal thickness (31%/18%). Conclusions The 95% CI range for visual acuity, ERG, retinal sensitivity, and central retinal thickness relative to baseline are described for this cohort of participants with X-linked juvenile retinoschisis (XLRS). Translational Relevance A quantitative understanding of the variability of outcome measures is vital to establishing the safety and efficacy limits for therapeutic trials of XLRS patients. PMID:25346871

Jeffrey, Brett G.; Cukras, Catherine A.; Vitale, Susan; Turriff, Amy; Bowles, Kristin; Sieving, Paul A.



Predicting membrane protein types by fusing composite protein sequence features into pseudo amino acid composition.  


Membrane proteins are vital type of proteins that serve as channels, receptors, and energy transducers in a cell. Prediction of membrane protein types is an important research area in bioinformatics. Knowledge of membrane protein types provides some valuable information for predicting novel example of the membrane protein types. However, classification of membrane protein types can be both time consuming and susceptible to errors due to the inherent similarity of membrane protein types. In this paper, neural networks based membrane protein type prediction system is proposed. Composite protein sequence representation (CPSR) is used to extract the features of a protein sequence, which includes seven feature sets; amino acid composition, sequence length, 2 gram exchange group frequency, hydrophobic group, electronic group, sum of hydrophobicity, and R-group. Principal component analysis is then employed to reduce the dimensionality of the feature vector. The probabilistic neural network (PNN), generalized regression neural network, and support vector machine (SVM) are used as classifiers. A high success rate of 86.01% is obtained using SVM for the jackknife test. In case of independent dataset test, PNN yields the highest accuracy of 95.73%. These classifiers exhibit improved performance using other performance measures such as sensitivity, specificity, Mathew's correlation coefficient, and F-measure. The experimental results show that the prediction performance of the proposed scheme for classifying membrane protein types is the best reported, so far. This performance improvement may largely be credited to the learning capabilities of neural networks and the composite feature extraction strategy, which exploits seven different properties of protein sequences. The proposed Mem-Predictor can be accessed at PMID:21110985

Hayat, Maqsood; Khan, Asifullah



Grid search modeling of receiver functions: Implications for crustal structure in the Middle East and North Africa  

SciTech Connect

A grid search is used to estimate average crustal thickness and shear wave velocity structure beneath 12 three-component broadband seismic stations in the Middle East, North Africa, and nearby regions. The crustal thickness in these regions is found to vary from a minimum of 8.0{plus_minus}1.5&hthinsp;km in East Africa (Afar) region to possibly a maximum of 64{plus_minus}4.8&hthinsp;km in the lesser Caucasus. Stations located within the stable African platform indicate a crustal thickness of about 40 km. Teleseismic three-component waveform data produced by 165 earthquakes are used to create receiver function stacks for each station. Using a grid search, we have solved for the optimal and most simple shear velocity models beneath all 12 stations. Unlike other techniques (linearized least squares or forward modeling), the grid search methodology guarantees that we solve for the global minimum within our defined model parameter space. Using the grid search, we also qualitatively estimate the least number of layers required to model the observed receiver functions{close_quote} major seismic phases (e.g., PS{sub Moho}). A jackknife error estimation method is used to test the stability of our receiver function inversions for all 12 stations in the region that had recorded a sufficient number of high-quality broadband teleseismic waveforms. Five of the 12 estimates of crustal thicknesses are consistent with what is known of crustal structure from prior geophysical work. Furthermore, the remaining seven estimates of crustal structure are in regions for which previously there were few or no data about crustal thickness. {copyright} 1998 American Geophysical Union

Sandvol, E.; Seber, D.; Calvert, A.; Barazangi, M. [Institute for the Study of the Continents, Cornell University, Ithaca, New York (United States)] [Institute for the Study of the Continents, Cornell University, Ithaca, New York (United States)



Classification and Analysis of Regulatory Pathways Using Graph Property, Biochemical and Physicochemical Property, and Functional Property  

PubMed Central

Given a regulatory pathway system consisting of a set of proteins, can we predict which pathway class it belongs to? Such a problem is closely related to the biological function of the pathway in cells and hence is quite fundamental and essential in systems biology and proteomics. This is also an extremely difficult and challenging problem due to its complexity. To address this problem, a novel approach was developed that can be used to predict query pathways among the following six functional categories: (i) “Metabolism”, (ii) “Genetic Information Processing”, (iii) “Environmental Information Processing”, (iv) “Cellular Processes”, (v) “Organismal Systems”, and (vi) “Human Diseases”. The prediction method was established trough the following procedures: (i) according to the general form of pseudo amino acid composition (PseAAC), each of the pathways concerned is formulated as a 5570-D (dimensional) vector; (ii) each of components in the 5570-D vector was derived by a series of feature extractions from the pathway system according to its graphic property, biochemical and physicochemical property, as well as functional property; (iii) the minimum redundancy maximum relevance (mRMR) method was adopted to operate the prediction. A cross-validation by the jackknife test on a benchmark dataset consisting of 146 regulatory pathways indicated that an overall success rate of 78.8% was achieved by our method in identifying query pathways among the above six classes, indicating the outcome is quite promising and encouraging. To the best of our knowledge, the current study represents the first effort in attempting to identity the type of a pathway system or its biological function. It is anticipated that our report may stimulate a series of follow-up investigations in this new and challenging area. PMID:21980418

Cai, Yu-Dong; Chou, Kuo-Chen



PRIMUS: Galaxy Clustering as a Function of Luminosity and Color at 0.2 < z < 1  

NASA Astrophysics Data System (ADS)

We present measurements of the luminosity and color-dependence of galaxy clustering at 0.2 < z < 1.0 in the Prism Multi-object Survey. We quantify the clustering with the redshift-space and projected two-point correlation functions, ?(rp , ?) and wp (rp ), using volume-limited samples constructed from a parent sample of over ~130, 000 galaxies with robust redshifts in seven independent fields covering 9 deg2 of sky. We quantify how the scale-dependent clustering amplitude increases with increasing luminosity and redder color, with relatively small errors over large volumes. We find that red galaxies have stronger small-scale (0.1 Mpc h -1 < rp < 1 Mpc h -1) clustering and steeper correlation functions compared to blue galaxies, as well as a strong color dependent clustering within the red sequence alone. We interpret our measured clustering trends in terms of galaxy bias and obtain values of b gal ? 0.9-2.5, quantifying how galaxies are biased tracers of dark matter depending on their luminosity and color. We also interpret the color dependence with mock catalogs, and find that the clustering of blue galaxies is nearly constant with color, while redder galaxies have stronger clustering in the one-halo term due to a higher satellite galaxy fraction. In addition, we measure the evolution of the clustering strength and bias, and we do not detect statistically significant departures from passive evolution. We argue that the luminosity- and color-environment (or halo mass) relations of galaxies have not significantly evolved since z ~ 1. Finally, using jackknife subsampling methods, we find that sampling fluctuations are important and that the COSMOS field is generally an outlier, due to having more overdense structures than other fields; we find that "cosmic variance" can be a significant source of uncertainty for high-redshift clustering measurements.

Skibba, Ramin A.; Smith, M. Stephen M.; Coil, Alison L.; Moustakas, John; Aird, James; Blanton, Michael R.; Bray, Aaron D.; Cool, Richard J.; Eisenstein, Daniel J.; Mendez, Alexander J.; Wong, Kenneth C.; Zhu, Guangtun



Demographic history and rare allele sharing among human populations.  


High-throughput sequencing technology enables population-level surveys of human genomic variation. Here, we examine the joint allele frequency distributions across continental human populations and present an approach for combining complementary aspects of whole-genome, low-coverage data and targeted high-coverage data. We apply this approach to data generated by the pilot phase of the Thousand Genomes Project, including whole-genome 2-4× coverage data for 179 samples from HapMap European, Asian, and African panels as well as high-coverage target sequencing of the exons of 800 genes from 697 individuals in seven populations. We use the site frequency spectra obtained from these data to infer demographic parameters for an Out-of-Africa model for populations of African, European, and Asian descent and to predict, by a jackknife-based approach, the amount of genetic diversity that will be discovered as sample sizes are increased. We predict that the number of discovered nonsynonymous coding variants will reach 100,000 in each population after ?1,000 sequenced chromosomes per population, whereas ?2,500 chromosomes will be needed for the same number of synonymous variants. Beyond this point, the number of segregating sites in the European and Asian panel populations is expected to overcome that of the African panel because of faster recent population growth. Overall, we find that the majority of human genomic variable sites are rare and exhibit little sharing among diverged populations. Our results emphasize that replication of disease association for specific rare genetic variants across diverged populations must overcome both reduced statistical power because of rarity and higher population divergence. PMID:21730125

Gravel, Simon; Henn, Brenna M; Gutenkunst, Ryan N; Indap, Amit R; Marth, Gabor T; Clark, Andrew G; Yu, Fuli; Gibbs, Richard A; Bustamante, Carlos D



Predicting physical activity energy expenditure using accelerometry in adults from sub-Sahara Africa  

PubMed Central

Lack of physical activity may be an important etiological factor in the current epidemiological transition characterised by increasing prevalence of obesity and chronic diseases in sub-Sahara Africa. However, there is a dearth of data on objectively measured physical activity energy expenditure (PAEE) in this region. We sought to develop regression equations using body composition and accelerometer counts to predict PAEE. We conducted a cross-sectional study of 33 adult volunteers from an urban (n=16) and a rural (n=17) residential site in Cameroon. Energy expenditure was measured by doubly labelled water over a period of 7 consecutive days. Simultaneously, a hip-mounted Actigraph® accelerometer recorded body movement. PAEE prediction equations were derived using accelerometer counts, age, sex and body composition variables, and cross-validated by the jack-knife method. The Bland and Altman limits of agreement (LOA) approach was used to assess agreement. Our results show that PAEE (kJ·kg?1·day?1) was significantly and positively correlated with activity counts from the accelerometer (r=0.37, p=0.03). The derived equations explained 14 to 40% of the variance in PAEE. Age, sex and accelerometer counts together explained 34% of the variance in PAEE, with accelerometer counts alone explaining 14%. The LOA between DLW and the derived equations were wide, with predicted PAEE being up to 60 kJ·kg?1·day?1 below or above the measured value. In summary, the derived equations performed better than existing published equations in predicting PAEE from accelerometer counts in this population. Accelerometry could be used to predict PAEE in this population and therefore has important applications for monitoring population levels of total physical activity patterns. PMID:19247268

Assah, Felix K.; Ekelund, Ulf; Brage, Soren; Corder, Kirsten; Wright, Antony; Mbanya, Jean Claude; Wareham, Nicholas J.



Prediction of protein S-nitrosylation sites based on adapted normal distribution bi-profile Bayes and Chou's pseudo amino acid composition.  


Protein S-nitrosylation is a reversible post-translational modification by covalent modification on the thiol group of cysteine residues by nitric oxide. Growing evidence shows that protein S-nitrosylation plays an important role in normal cellular function as well as in various pathophysiologic conditions. Because of the inherent chemical instability of the S-NO bond and the low abundance of endogenous S-nitrosylated proteins, the unambiguous identification of S-nitrosylation sites by commonly used proteomic approaches remains challenging. Therefore, computational prediction of S-nitrosylation sites has been considered as a powerful auxiliary tool. In this work, we mainly adopted an adapted normal distribution bi-profile Bayes (ANBPB) feature extraction model to characterize the distinction of position-specific amino acids in 784 S-nitrosylated and 1568 non-S-nitrosylated peptide sequences. We developed a support vector machine prediction model, iSNO-ANBPB, by incorporating ANBPB with the Chou's pseudo amino acid composition. In jackknife cross-validation experiments, iSNO-ANBPB yielded an accuracy of 65.39% and a Matthew's correlation coefficient (MCC) of 0.3014. When tested on an independent dataset, iSNO-ANBPB achieved an accuracy of 63.41% and a MCC of 0.2984, which are much higher than the values achieved by the existing predictors SNOSite, iSNO-PseAAC, the Li et al. algorithm, and iSNO-AAPair. On another training dataset, iSNO-ANBPB also outperformed GPS-SNO and iSNO-PseAAC in the 10-fold crossvalidation test. PMID:24918295

Jia, Cangzhi; Lin, Xin; Wang, Zhiping



Historical extension of operational NDVI products for livestock insurance in Kenya  

NASA Astrophysics Data System (ADS)

Droughts induce livestock losses that severely affect Kenyan pastoralists. Recent index insurance schemes have the potential of being a viable tool for insuring pastoralists against drought-related risk. Such schemes require as input a forage scarcity (or drought) index that can be reliably updated in near real-time, and that strongly relates to livestock mortality. Generally, a long record (>25 years) of the index is needed to correctly estimate mortality risk and calculate the related insurance premium. Data from current operational satellites used for large-scale vegetation monitoring span over a maximum of 15 years, a time period that is considered insufficient for accurate premium computation. This study examines how operational NDVI datasets compare to, and could be combined with the non-operational recently constructed 30-year GIMMS AVHRR record (1981-2011) to provide a near-real time drought index with a long term archive for the arid lands of Kenya. We compared six freely available, near-real time NDVI products: five from MODIS and one from SPOT-VEGETATION. Prior to comparison, all datasets were averaged in time for the two vegetative seasons in Kenya, and aggregated spatially at the administrative division level at which the insurance is offered. The feasibility of extending the resulting aggregated drought indices back in time was assessed using jackknifed R2 statistics (leave-one-year-out) for the overlapping period 2002-2011. We found that division-specific models were more effective than a global model for linking the division-level temporal variability of the index between NDVI products. Based on our results, good scope exists for historically extending the aggregated drought index, thus providing a longer operational record for insurance purposes. We showed that this extension may have large effects on the calculated insurance premium. Finally, we discuss several possible improvements to the drought index.

Vrieling, Anton; Meroni, Michele; Shee, Apurba; Mude, Andrew G.; Woodard, Joshua; de Bie, C. A. J. M. (Kees); Rembold, Felix



[Forest lighting fire forecasting for Daxing'anling Mountains based on MAXENT model].  


Daxing'anling Mountains is one of the areas with the highest occurrence of forest lighting fire in Heilongjiang Province, and developing a lightning fire forecast model to accurately predict the forest fires in this area is of importance. Based on the data of forest lightning fires and environment variables, the MAXENT model was used to predict the lightning fire in Daxing' anling region. Firstly, we studied the collinear diagnostic of each environment variable, evaluated the importance of the environmental variables using training gain and the Jackknife method, and then evaluated the prediction accuracy of the MAXENT model using the max Kappa value and the AUC value. The results showed that the variance inflation factor (VIF) values of lightning energy and neutralized charge were 5.012 and 6.230, respectively. They were collinear with the other variables, so the model could not be used for training. Daily rainfall, the number of cloud-to-ground lightning, and current intensity of cloud-to-ground lightning were the three most important factors affecting the lightning fires in the forest, while the daily average wind speed and the slope was of less importance. With the increase of the proportion of test data, the max Kappa and AUC values were increased. The max Kappa values were above 0.75 and the average value was 0.772, while all of the AUC values were above 0.5 and the average value was 0. 859. With a moderate level of prediction accuracy being achieved, the MAXENT model could be used to predict forest lightning fire in Daxing'anling Mountains. PMID:25011305

Sun, Yu; Shi, Ming-Chang; Peng, Huan; Zhu, Pei-Lin; Liu, Si-Lin; Wu, Shi-Lei; He, Cheng; Chen, Feng



Remote Sensing of Miombo Woodland's Aboveground Biomass and LAI using RADARSAT and Landsat ETM+ Data  

NASA Astrophysics Data System (ADS)

Estimations of biomass are critical in Miombo Woodlands because they represent a primary source of food, fiber, and fuel for 340 million rural peoples and another 15 million urban dwellers in southern Africa. The purpose of this study is to estimate woody aboveground biomass and Leaf Area Index (LAI) in Niassa Reserve, northern Mozambique. The objective of this study is to use optical and microwave satellite data with contemporaneous field data to estimate biomass and LAI. Fifty field plots were surveyed across the Niassa Reserve for biomass and LAI in July and December 2004, respectively. Remote sensing data consisting of RADARSAT backscatter (C- band, ë=5.6 cm) and a June 2004 Landsat ETM+ were acquired. Normalized Difference Vegetation Index (NDVI), Simple Ratio (SR), and a land-cover map (72% total accuracy) were derived from the Landsat scene. Field measurements of biomass and LAI correlated with Radarsat backscatter (Rsqbiomass=0.45, RsqLAI = 0.35, P<0.0001 ), NDVI (Rsqbiomass =0.15, RsqLAI=0.14-, p <0.0001 ) and SR (Rsqbiomass=-0.14, RsqLAI= 0.17, p <0.0001). A jackknife stepwise regression technique was used to develop the best predictive models for biomass (biomass = -5.19 +0.074*radarsat+1.56*SR, Rsq=0.53) and LAI (LAI= -0.66+0.01*radarsat+0.22*SR, Rsq=0.45). The addition of NDVI did not improve the model. Forest biomass and LAI maps were then produced for Niassa Reserve with an estimated peak total biomass of 18 kg/hm2 and a mean LAI of 2.8 m2/m2. In the east both biomass and LAI are lower than the western Niassa Reserve.

Ribeiro, N. S.; Saatchi, S. S.; Shugart, H. H.; Wshington-Allen, R. A.



The effect of compression on confidence during the detection of skull fractures in CT  

NASA Astrophysics Data System (ADS)

As part of a study to establish whether detection of cranial vault fractures is affected by JPEG 2000 30:1 and 60:1 lossy compression when compared to JPEG 2000 lossless compression we looked at the effects on confidence ratings 55 CT images, with three levels of JPEG 2000 compression (lossless, 30:1 & 60:1) were presented to 14 senior radiologists, 12 from the American Board of Radiology and 2 form Australia, 7 of whom were MSK specialists and 7 were neuroradiologists. 32 Images contained a single skull fracture while 23 were normal. Images were displayed on one calibrated, secondary LCD, in an ambient lighting of 32.2 lux. Observers were asked to identify the presence or absence of a fracture and where a fracture was present to locate and rate their confidence in its presence. A jack-knifed alternate free-response receiver operating characteristic (JAFROC) and a ROC methodology was employed and the DBM MRMC and ANOVA were used to explore differences between the lossless and lossy compressed images. A significant trend of increased confidence in true and false positive scores was seen with JPEG2000 Lossy 60:1 compression. An ANOVA on the mean confidence rating obtained for correct (TP) and incorrect (FP) localization skull fractions demonstrated that this was a significant difference between lossless and 60:1 [FP, p<0.001 TP, p<0.014] and 30:1 and 60:1 [FP, p<0.014 TP, p<0.037].

Nikolovski, Ines; McEntee, Mark F.; Bourne, Roger; Pietrzyk, Mariusz W.; Evanoff, Michael G.; Brennan, Patrick C.; Tay, Kevin



Prediction of protein structure classes using hybrid space of multi-profile Bayes and bi-gram probability feature spaces.  


Proteins are the executants of biological functions in living organisms. Comprehension of protein structure is a challenging problem in the era of proteomics, computational biology, and bioinformatics because of its pivotal role in protein folding patterns. Owing to the large exploration of protein sequences in protein databanks and intricacy of protein structures, experimental and theoretical methods are insufficient for prediction of protein structure classes. Therefore, it is highly desirable to develop an accurate, reliable, and high throughput computational model to predict protein structure classes correctly from polygenetic sequences. In this regard, we propose a promising model employing hybrid descriptor space in conjunction with optimized evidence-theoretic K-nearest neighbor algorithm. Hybrid space is the composition of two descriptor spaces including Multi-profile Bayes and bi-gram probability. In order to enhance the generalization power of the classifier, we have selected high discriminative descriptors from the hybrid space using particle swarm optimization, a well-known evolutionary feature selection technique. Performance evaluation of the proposed model is performed using the jackknife test on three low similarity benchmark datasets including 25PDB, 1189, and 640. The success rates of the proposed model are 87.0%, 86.6%, and 88.4%, respectively on the three benchmark datasets. The comparative analysis exhibits that our proposed model has yielded promising results compared to the existing methods in the literature. In addition, our proposed prediction system might be helpful in future research particularly in cases where the major focus of research is on low similarity datasets. PMID:24384128

Hayat, Maqsood; Tahir, Muhammad; Khan, Sher Afzal



Breast tomosynthesis and digital mammography: a comparison of diagnostic accuracy  

PubMed Central

Objective Our aim was to compare the ability of radiologists to detect breast cancers using one-view breast tomosynthesis (BT) and two-view digital mammography (DM) in an enriched population of diseased patients and benign and/or healthy patients. Methods All participants gave informed consent. The BT and DM examinations were performed with about the same average glandular dose to the breast. The study population comprised patients with subtle signs of malignancy seen on DM and/or ultrasonography. Ground truth was established by pathology, needle biopsy and/or by 1-year follow-up by mammography, which retrospectively resulted in 89 diseased breasts (1 breast per patient) with 95 malignant lesions and 96 healthy or benign breasts. Two experienced radiologists, who were not participants in the study, determined the locations of the malignant lesions. Five radiologists, experienced in mammography, interpreted the cases independently in a free-response study. The data were analysed by the receiver operating characteristic (ROC) and jackknife alternative free-response ROC (JAFROC) methods, regarding both readers and cases as random effects. Results The diagnostic accuracy of BT was significantly better than that of DM (JAFROC: p=0.0031, ROC: p=0.0415). The average sensitivity of BT was higher than that of DM (?90% vs ?79%; 95% confidence interval of difference: 0.036, 0.108) while the average false-positive fraction was not significantly different (95% confidence interval of difference: ?0.117, 0.010). Conclusion The diagnostic accuracy of BT was superior to DM in an enriched population. PMID:22674710

Svahn, T M; Chakraborty, D P; Ikeda, D; Zackrisson, S; Do, Y; Mattsson, S; Andersson, I



Improved classification of lung cancer tumors based on structural and physicochemical properties of proteins using data mining models.  


Detecting divergence between oncogenic tumors plays a pivotal role in cancer diagnosis and therapy. This research work was focused on designing a computational strategy to predict the class of lung cancer tumors from the structural and physicochemical properties (1497 attributes) of protein sequences obtained from genes defined by microarray analysis. The proposed methodology involved the use of hybrid feature selection techniques (gain ratio and correlation based subset evaluators with Incremental Feature Selection) followed by Bayesian Network prediction to discriminate lung cancer tumors as Small Cell Lung Cancer (SCLC), Non-Small Cell Lung Cancer (NSCLC) and the COMMON classes. Moreover, this methodology eliminated the need for extensive data cleansing strategies on the protein properties and revealed the optimal and minimal set of features that contributed to lung cancer tumor classification with an improved accuracy compared to previous work. We also attempted to predict via supervised clustering the possible clusters in the lung tumor data. Our results revealed that supervised clustering algorithms exhibited poor performance in differentiating the lung tumor classes. Hybrid feature selection identified the distribution of solvent accessibility, polarizability and hydrophobicity as the highest ranked features with Incremental feature selection and Bayesian Network prediction generating the optimal Jack-knife cross validation accuracy of 87.6%. Precise categorization of oncogenic genes causing SCLC and NSCLC based on the structural and physicochemical properties of their protein sequences is expected to unravel the functionality of proteins that are essential in maintaining the genomic integrity of a cell and also act as an informative source for drug design, targeting essential protein properties and their composition that are found to exist in lung cancer tumors. PMID:23505559

Ramani, R Geetha; Jacob, Shomona Gracia



Discriminating between deleterious and neutral non-frameshifting indels based on protein interaction networks and hybrid properties.  


More than ten thousand coding variants are contained in each human genome; however, our knowledge of the way genetic variants underlie phenotypic differences is far from complete. Small insertions and deletions (indels) are one of the most common types of human genetic variants, and indels play a significant role in human inherited disease. To date, we still lack a comprehensive understanding of how indels cause diseases. Therefore, identification and analysis of such deleterious variants is a key challenge and has been of great interest in the current research in genome biology. Increasing numbers of computational methods have been developed for discriminating between deleterious indels and neutral indels. However, most of the existing methods are based on traditional sequential or structural features, which cannot completely explain the association between indels and the resulting induced inherited disease. In this study, we establish a novel method to predict deleterious non-frameshifting indels based on features extracted from both protein interaction networks and traditional hybrid properties. Each indel was coded by 1,246 features. Using the maximum relevance minimum redundancy method and the incremental feature selection method, we obtained an optimal feature set containing 42 features, of which 21 features were derived from protein interaction networks. Based on the optimal feature set, an 88 % accuracy and a 0.76 MCC value were achieved by a Random Forest as evaluated by the Jackknife cross-validation test. This method outperformed existing methods of predicting deleterious indels, and can be applied in practice for deleterious non-frameshifting indel predictions in genome research. The analysis of the optimal features selected in the model revealed that network interactions play more important roles and could be informative for better illustrating an indel's function and disease associations than traditional sequential or structural features. These results could shed some light on the genetic basis of human genetic variations and human inherited diseases. PMID:25248637

Zhang, Ning; Huang, Tao; Cai, Yu-Dong



iNitro-Tyr: Prediction of Nitrotyrosine Sites in Proteins with General Pseudo Amino Acid Composition  

PubMed Central

Nitrotyrosine is one of the post-translational modifications (PTMs) in proteins that occurs when their tyrosine residue is nitrated. Compared with healthy people, a remarkably increased level of nitrotyrosine is detected in those suffering from rheumatoid arthritis, septic shock, and coeliac disease. Given an uncharacterized protein sequence that contains many tyrosine residues, which one of them can be nitrated and which one cannot? This is a challenging problem, not only directly related to in-depth understanding the PTM’s mechanism but also to the nitrotyrosine-based drug development. Particularly, with the avalanche of protein sequences generated in the postgenomic age, it is highly desired to develop a high throughput tool in this regard. Here, a new predictor called “iNitro-Tyr” was developed by incorporating the position-specific dipeptide propensity into the general pseudo amino acid composition for discriminating the nitrotyrosine sites from non-nitrotyrosine sites in proteins. It was demonstrated via the rigorous jackknife tests that the new predictor not only can yield higher success rate but also is much more stable and less noisy. A web-server for iNitro-Tyr is accessible to the public at For the convenience of most experimental scientists, we have further provided a protocol of step-by-step guide, by which users can easily get their desired results without the need to follow the complicated mathematics that were presented in this paper just for the integrity of its development process. It has not escaped our notice that the approach presented here can be also used to deal with the other PTM sites in proteins. PMID:25121969

Xu, Yan; Wen, Xin; Wen, Li-Shu; Wu, Ling-Yun; Deng, Nai-Yang; Chou, Kuo-Chen



Does more sequence data improve estimates of galliform phylogeny? Analyses of a rapid radiation using a complete data matrix  

PubMed Central

The resolution of rapid evolutionary radiations or “bushes” in the tree of life has been one of the most difficult and interesting problems in phylogenetics. The avian order Galliformes appears to have undergone several rapid radiations that have limited the resolution of prior studies and obscured the position of taxa important both agriculturally and as model systems (chicken, turkey, Japanese quail). Here we present analyses of a multi-locus data matrix comprising over 15,000 sites, primarily from nuclear introns but also including three mitochondrial regions, from 46 galliform taxa with all gene regions sampled for all taxa. The increased sampling of unlinked nuclear genes provided strong bootstrap support for all but a small number of relationships. Coalescent-based methods to combine individual gene trees and analyses of datasets that are independent of published data indicated that this well-supported topology is likely to reflect the galliform species tree. The inclusion or exclusion of mitochondrial data had a limited impact upon analyses upon analyses using either concatenated data or multispecies coalescent methods. Some of the key phylogenetic findings include support for a second major clade within the core phasianids that includes the chicken and Japanese quail and clarification of the phylogenetic relationships of turkey. Jackknifed datasets suggested that there is an advantage to sampling many independent regions across the genome rather than obtaining long sequences for a small number of loci, possibly reflecting the differences among gene trees that differ due to incomplete lineage sorting. Despite the novel insights we obtained using this increased sampling of gene regions, some nodes remain unresolved, likely due to periods of rapid diversification. Resolving these remaining groups will likely require sequencing a very large number of gene regions, but our analyses now appear to support a robust backbone for this order. PMID:24795852

Braun, Edward L.



Clinical validation of a medical grade color monitor for chest radiology  

NASA Astrophysics Data System (ADS)

Until recently, the specifications of medical grade monochrome LCD monitors outperformed those of color LCD monitors. New generations of color LCD monitors, however, show specifications that are in many respects similar to those of monochrome monitors typically used in diagnostic workstations. The aim of present study was to evaluate the impact of different medical grade monitors in terms of detection of simulated lung nodules in chest x-ray images. Specifically, we wanted to compare a new medical grade color monitor (Barco Coronis 6MP color) to a medical grade grayscale monitor (Barco Coronis 3MP monochrome) and a consumer color monitor (Philips 200VW 1.7MP color) by means of an observer performance experiment. Using the free-response acquisition data paradigm, seven radiologists were asked to detect and locate lung nodules (170 in total), simulated in half of the 200 chest X-ray images used in the experiment. The jackknife free-response receiver operating characteristic (JAFROC) analysis of the data showed a statistically significant difference between at least two monitors, F-value=3.77 and p-value =0.0481. The different Figure of Merit values were 0.727, 0.723 and 0.697 for the new color LCD monitor, the medical grade monitor and the consumer color monitor respectively. There was no difference between the needed reading times but there was a difference between the mean calculated Euclidian distances between the position marked by the observers and the center of the simulated nodule, indicating a better accuracy with both medical grade monitors. Present data suggests that the new generation of medical grade color monitors could be used as diagnostic workstations.

Jacobs, J.; Zanca, F.; Verschakelen, J.; Marchal, G.; Bosmans, H.



Demographic history and rare allele sharing among human populations  

PubMed Central

High-throughput sequencing technology enables population-level surveys of human genomic variation. Here, we examine the joint allele frequency distributions across continental human populations and present an approach for combining complementary aspects of whole-genome, low-coverage data and targeted high-coverage data. We apply this approach to data generated by the pilot phase of the Thousand Genomes Project, including whole-genome 2–4× coverage data for 179 samples from HapMap European, Asian, and African panels as well as high-coverage target sequencing of the exons of 800 genes from 697 individuals in seven populations. We use the site frequency spectra obtained from these data to infer demographic parameters for an Out-of-Africa model for populations of African, European, and Asian descent and to predict, by a jackknife-based approach, the amount of genetic diversity that will be discovered as sample sizes are increased. We predict that the number of discovered nonsynonymous coding variants will reach 100,000 in each population after ?1,000 sequenced chromosomes per population, whereas ?2,500 chromosomes will be needed for the same number of synonymous variants. Beyond this point, the number of segregating sites in the European and Asian panel populations is expected to overcome that of the African panel because of faster recent population growth. Overall, we find that the majority of human genomic variable sites are rare and exhibit little sharing among diverged populations. Our results emphasize that replication of disease association for specific rare genetic variants across diverged populations must overcome both reduced statistical power because of rarity and higher population divergence. PMID:21730125

Gravel, Simon; Henn, Brenna M.; Gutenkunst, Ryan N.; Indap, Amit R.; Marth, Gabor T.; Clark, Andrew G.; Yu, Fuli; Gibbs, Richard A.; Bustamante, Carlos D.; Altshuler, David L.; Durbin, Richard M.; Abecasis, Gonçalo R.; Bentley, David R.; Chakravarti, Aravinda; Clark, Andrew G.; Collins, Francis S.; De La Vega, Francisco M.; Donnelly, Peter; Egholm, Michael; Flicek, Paul; Gabriel, Stacey B.; Gibbs, Richard A.; Knoppers, Bartha M.; Lander, Eric S.; Lehrach, Hans; Mardis, Elaine R.; McVean, Gil A.; Nickerson, Debbie A.; Peltonen, Leena; Schafer, Alan J.; Sherry, Stephen T.; Wang, Jun; Wilson, Richard K.; Gibbs, Richard A.; Deiros, David; Metzker, Mike; Muzny, Donna; Reid, Jeff; Wheeler, David; Wang, Jun; Li, Jingxiang; Jian, Min; Li, Guoqing; Li, Ruiqiang; Liang, Huiqing; Tian, Geng; Wang, Bo; Wang, Jian; Wang, Wei; Yang, Huanming; Zhang, Xiuqing; Zheng, Huisong; Lander, Eric S.; Altshuler, David L.; Ambrogio, Lauren; Bloom, Toby; Cibulskis, Kristian; Fennell, Tim J.; Gabriel, Stacey B.; Jaffe, David B.; Shefler, Erica; Sougnez, Carrie L.; Bentley, David R.; Gormley, Niall; Humphray, Sean; Kingsbury, Zoya; Koko-Gonzales, Paula; Stone, Jennifer; McKernan, Kevin J.; Costa, Gina L.; Ichikawa, Jeffry K.; Lee, Clarence C.; Sudbrak, Ralf; Lehrach, Hans; Borodina, Tatiana A.; Dahl, Andreas; Davydov, Alexey N.; Marquardt, Peter; Mertes, Florian; Nietfeld, Wilfiried; Rosenstiel, Philip; Schreiber, Stefan; Soldatov, Aleksey V.; Timmermann, Bernd; Tolzmann, Marius; Egholm, Michael; Affourtit, Jason; Ashworth, Dana; Attiya, Said; Bachorski, Melissa; Buglione, Eli; Burke, Adam; Caprio, Amanda; Celone, Christopher; Clark, Shauna; Conners, David; Desany, Brian; Gu, Lisa; Guccione, Lorri; Kao, Kalvin; Kebbel, Andrew; Knowlton, Jennifer; Labrecque, Matthew; McDade, Louise; Mealmaker, Craig; Minderman, Melissa; Nawrocki, Anne; Niazi, Faheem; Pareja, Kristen; Ramenani, Ravi; Riches, David; Song, Wanmin; Turcotte, Cynthia; Wang, Shally; Mardis, Elaine R.; Wilson, Richard K.; Dooling, David; Fulton, Lucinda; Fulton, Robert; Weinstock, George; Durbin, Richard M.; Burton, John; Carter, David M.; Churcher, Carol; Coffey, Alison; Cox, Anthony; Palotie, Aarno; Quail, Michael; Skelly, Tom; Stalker, James; Swerdlow, Harold P.; Turner, Daniel; De Witte, Anniek; Giles, Shane; Gibbs, Richard A.; Wheeler, David; Bainbridge, Matthew; Challis, Danny; Sabo, Aniko; Yu, Fuli; Yu, Jin; Wang, Jun; Fang, Xiaodong; Guo, Xiaosen; Li, Ruiqiang; Li, Yingrui; Luo, Ruibang; Tai, Shuaishuai; Wu, Honglong; Zheng, Hancheng; Zheng, Xiaole; Zhou, Yan; Li, Guoqing; Wang, Jian; Yang, Huanming; Marth, Gabor T.; Garrison, Erik P.; Huang, Weichun; Indap, Amit; Kural, Deniz; Lee, Wan-Ping; Leong, Wen Fung; Quinlan, Aaron R.; Stewart, Chip; Stromberg, Michael P.; Ward, Alistair N.; Wu, Jiantao; Lee, Charles; Mills, Ryan E.; Shi, Xinghua; Daly, Mark J.; DePristo, Mark A.; Altshuler, David L.; Ball, Aaron D.; Banks, Eric; Bloom, Toby; Browning, Brian L.; Cibulskis, Kristian; Fennell, Tim J.; Garimella, Kiran V.; Grossman, Sharon R.; Handsaker, Robert E.; Hanna, Matt; Hartl, Chris; Jaffe, David B.; Kernytsky, Andrew M.; Korn, Joshua M.; Li, Heng; Maguire, Jared R.; McCarroll, Steven A.; McKenna, Aaron; Nemesh, James C.; Philippakis, Anthony A.; Poplin, Ryan E.; Price, Alkes; Rivas, Manuel A.; Sabeti, Pardis C.; Schaffner, Stephen F.; Shefler, Erica; Shlyakhter, Ilya A.; Cooper, David N.; Ball, Edward V.; Mort, Matthew; Phillips, Andrew D.; Stenson, Peter D.; Sebat, Jonathan; Makarov, Vladimir; Ye, Kenny; Yoon, Seungtai C.; Bustamante, Carlos D.; Clark, Andrew G.; Boyko, Adam; Degenhardt, Jeremiah; Gravel, Simon; Gutenkunst, Ryan N.; Kaganovich, Mark; Keinan, Alon; Lacroute, Phil; Ma, Xin; Reynolds, Andy; Clarke, Laura; Flicek, Paul; Cunningham, Fiona; Herrero, Javier; Keenen, Stephen; Kulesha, Eugene; Leinonen, Rasko; McLaren, William M.; Radhakrishnan, Rajesh; Smith, Richard E.; Zalunin, Vadim; Zheng-Bradley, Xiangqun; Korbel, Jan O.; Stütz, Adrian M.; Humphray, Sean; Bauer, Markus; Cheetham, R. Keira; Cox, Tony; Eberle, Michael; James, Terena; Kahn, Scott; Murray, Lisa; Chakravarti, Aravinda; Ye, Kai; De La Vega, Francisco M.; Fu, Yutao; Hyland, Fiona C. L.; Manning, Jonathan M.; McLaughlin, Stephen F.; Peckham, Heather E.; Sakarya, Onur; Sun, Yongming A.; Tsung, Eric F.; Batzer, Mark A.; Konkel, Miriam K.; Walker, Jerilyn A.; Sudbrak, Ralf; Albrecht, Marcus W.; Amstislavskiy, Vyacheslav S.; Herwig, Ralf; Parkhomchuk, Dimitri V.; Sherry, Stephen T.; Agarwala, Richa; Khouri, Hoda M.; Morgulis, Aleksandr O.; Paschall, Justin E.; Phan, Lon D.; Rotmistrovsky, Kirill E.; Sanders, Robert D.



Microbial Diversity of Biofilms in Dental Unit Water Systems  

PubMed Central

We investigated the microbial diversity of biofilms found in dental unit water systems (DUWS) by three methods. The first was microscopic examination by scanning electron microscopy (SEM), acridine orange staining, and fluorescent in situ hybridization (FISH). Most bacteria present in the biofilm were viable. FISH detected the ? and ?, but not the ?, subclasses of Proteobacteria. In the second method, 55 cultivated biofilm isolates were identified with the Biolog system, fatty acid analysis, and 16S ribosomal DNA (rDNA) sequencing. Only 16S identified all 55 isolates, which represented 13 genera. The most common organisms, as shown by analyses of 16S rDNA, belonged to the genera Afipia (28%) and Sphingomonas (16%). The third method was a culture-independent direct amplification and sequencing of 165 subclones from community biofilm 16S rDNA. This method revealed 40 genera: the most common ones included Leptospira (20%), Sphingomonas (14%), Bacillus (7%), Escherichia (6%), Geobacter (5%), and Pseudomonas (5%). Some of these organisms may be opportunistic pathogens. Our results have demonstrated that a biofilm in a health care setting may harbor a vast diversity of organisms. The results also reflect the limitations of culture-based techniques to detect and identify bacteria. Although this is the greatest diversity reported in DUWS biofilms, other genera may have been missed. Using a technique based on jackknife subsampling, we projected that a 25-fold increase in the number of subclones sequenced would approximately double the number of genera observed, reflecting the richness and high diversity of microbial communities in these biofilms. PMID:12788744

Singh, Ruby; Stine, O. Colin; Smith, David L.; Spitznagel, John K.; Labib, Mohamed E.; Williams, Henry N.



Influence of poplar clones on fertility life-table parameters of Chaitophorus leucomelas (Hemiptera: Aphididae).  


The aphid Chaitophorus leucomelas Koch (Hemiptera: Aphididae) is one of the most important pests of poplar (Populus spp.) plantations in Iran. In this study, development, reproduction, and life history of the aphid were assessed on 11 poplar clones; belong to three species, Populus nigra L., Populus deltoides Bartram ex Marshall, and Populus. euramericana Guinier. The experiments were carried out under controlled conditions at 24 +/- 1 degrees C, 50-60% RH, and a photoperiod of 12:12 (L:D) h. The developmental time at immature stage ranged from 10 to 12 d. Nymphs reproduced per female were ranged from 49 to 98 nymphs on Populus deltoides var. missoriensis and P. deltoides 72/51, respectively. The intrinsic rate of natural increase (r(m)) varied from 0.176 to 0.264 d(-1) among poplar clones. The r(m) values of the aphids were adversely affected in P. euramericana 242 in comparison with P. nigra 56/72 and P. nigra 63/135. In addition, the jackknife estimates of net reproductive rate (R0) indicated the presence of resistance among poplar clones. R0 ranged from 16.48 on P. nigra var. betulifoli to 47.53 on P. nigra 63/135. Mean generation times (T) was last 17.56 d on P. euramericana 242 to 14.51 d on P. deltoides 69/55. However, doubling time (DT) was 3.87 d on P. euramericana var. grandis to 2.63 d on P. nigra 63/135. The finite rate of increase (lambda) was 1.192 on resistant clone (P. euramericana 242) and 1.302 on susceptible clone (P. nigra 63/135). These results indicate that variation in life-table parameters could be an important component of variation in resistance to C. leucomelas in poplar. PMID:21309247

Yali, M Pahlavan; Moharramipour, S; Sadeghi, S E; Razmjou, J



Aboveground biomass and leaf area index (LAI) mapping for Niassa Reserve, northern Mozambique  

NASA Astrophysics Data System (ADS)

Estimations of biomass are critical in miombo woodlands because they represent the primary source of goods and services for over 80% of the population in southern Africa. This study was carried out in Niassa Reserve, northern Mozambique. The main objectives were first to estimate woody biomass and Leaf Area Index (LAI) using remotely sensed data [RADARSAT (C-band, ? = 5.7-cm)] and Landsat ETM+ derived Normalized Difference Vegetation Index (NDVI) and Simple Ratio (SR) calibrated by field measurements and, second to determine, at both landscape and plot scales, the environmental controls (precipitation, woody cover density, fire and elephants) of biomass and LAI. A land-cover map (72% overall accuracy) was derived from the June 2004 ETM+ mosaic. Field biomass and LAI were correlated with RADARSAT backscatter (rbiomass = 0.65, rLAI = 0.57, p < 0.0001) from July 2004, NDVI (rbiomass = 0.30, rLAI = 0.35; p < 0.0001) and SR (rbiomass = 0.36, rLAI = 0.40, p < 0.0001). A jackknife stepwise regression technique was used to develop the best predictive models for biomass (biomass = -5.19 + 0.074 * radarsat + 1.56 * SR, r2 = 0.55) and LAI (LAI = -0.66 + 0.01 * radarsat + 0.22 * SR, r2 = 0.45). Biomass and LAI maps were produced with an estimated peak of 18 kg m-2 and 2.80 m2 m-2, respectively. On the landscape-scale, both biomass and LAI were strongly determined by mean annual precipitation (F = 13.91, p = 0.0002). On the plot spatial scale, woody biomass was significantly determined by fire frequency, and LAI by vegetation type.

Ribeiro, Natasha S.; Saatchi, Sassan S.; Shugart, Herman H.; Washington-Allen, Robert A.



Predicting protein subnuclear location with optimized evidence-theoretic K-nearest classifier and pseudo amino acid composition  

SciTech Connect

The nucleus is the brain of eukaryotic cells that guides the life processes of the cell by issuing key instructions. For in-depth understanding of the biochemical process of the nucleus, the knowledge of localization of nuclear proteins is very important. With the avalanche of protein sequences generated in the post-genomic era, it is highly desired to develop an automated method for fast annotating the subnuclear locations for numerous newly found nuclear protein sequences so as to be able to timely utilize them for basic research and drug discovery. In view of this, a novel approach is developed for predicting the protein subnuclear location. It is featured by introducing a powerful classifier, the optimized evidence-theoretic K-nearest classifier, and using the pseudo amino acid composition [K.C. Chou, PROTEINS: Structure, Function, and Genetics, 43 (2001) 246], which can incorporate a considerable amount of sequence-order effects, to represent protein samples. As a demonstration, identifications were performed for 370 nuclear proteins among the following 9 subnuclear locations: (1) Cajal body, (2) chromatin, (3) heterochromatin, (4) nuclear diffuse, (5) nuclear pore, (6) nuclear speckle, (7) nucleolus, (8) PcG body, and (9) PML body. The overall success rates thus obtained by both the re-substitution test and jackknife cross-validation test are significantly higher than those by existing classifiers on the same working dataset. It is anticipated that the powerful approach may also become a useful high throughput vehicle to bridge the huge gap occurring in the post-genomic era between the number of gene sequences in databases and the number of gene products that have been functionally characterized. The OET-KNN classifier will be available at

Shen Hongbin [Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai 200030 (China); Chou Kuochen [Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai 200030 (China) and Gordon Life Science Institute, San Diego, CA 92130 (United States)]. E-mail:



Development of Pneumatic Aerodynamic Devices to Improve the Performance, Economics, and Safety of Heavy Vehicles  

SciTech Connect

Under contract to the DOE Office of Heavy Vehicle Technologies, the Georgia Tech Research Institute (GTRI) is developing and evaluating pneumatic (blown) aerodynamic devices to improve the performance, economics, stability and safety of operation of Heavy Vehicles. The objective of this program is to apply the pneumatic aerodynamic aircraft technology previously developed and flight-tested by GTRI personnel to the design of an efficient blown tractor-trailer configuration. Recent experimental results obtained by GTRI using blowing have shown drag reductions of 35% on a streamlined automobile wind-tunnel model. Also measured were lift or down-load increases of 100-150% and the ability to control aerodynamic moments about all 3 axes without any moving control surfaces. Similar drag reductions yielded by blowing on bluff afterbody trailers in current US trucking fleet operations are anticipated to reduce yearly fuel consumption by more than 1.2 billion gallons, while even further reduction is possible using pneumatic lift to reduce tire rolling resistance. Conversely, increased drag and down force generated instantaneously by blowing can greatly increase braking characteristics and control in wet/icy weather due to effective ''weight'' increases on the tires. Safety is also enhanced by controlling side loads and moments caused on these Heavy Vehicles by winds, gusts and other vehicles passing. This may also help to eliminate the jack-knifing problem if caused by extreme wind side loads on the trailer. Lastly, reduction of the turbulent wake behind the trailer can reduce splash and spray patterns and rough air being experienced by following vehicles. To be presented by GTRI in this paper will be results developed during the early portion of this effort, including a preliminary systems study, CFD prediction of the blown flowfields, and design of the baseline conventional tractor-trailer model and the pneumatic wind-tunnel model.

Robert J. Englar



Effect of herbicide combinations on Bt-maize rhizobacterial diversity.  


Reports of herbicide resistance events are proliferating worldwide, leading to new cultivation strategies using combinations of pre-emergence and post-emergence herbicides. We analyzed the impact during a one-year cultivation cycle of several herbicide combinations on the rhizobacterial community of glyphosate-tolerant Bt-maize and compared them to those of the untreated or glyphosate-treated soils. Samples were analyzed using pyrosequencing of the V6 hypervariable region of the 16S rRNA gene. The sequences obtained were subjected to taxonomic, taxonomy-independent, and phylogeny-based diversity studies, followed by a statistical analysis using principal components analysis and hierarchical clustering with jackknife statistical validation. The resilience of the microbial communities was analyzed by comparing their relative composition at the end of the cultivation cycle. The bacterial communites from soil subjected to a combined treatment with mesotrione plus s-metolachlor followed by glyphosate were not statistically different from those treated with glyphosate or the untreated ones. The use of acetochlor plus terbuthylazine followed by glyphosate, and the use of aclonifen plus isoxaflutole followed by mesotrione clearly affected the resilience of their corresponding bacterial communities. The treatment with pethoxamid followed by glyphosate resulted in an intermediate effect. The use of glyphosate alone seems to be the less aggressive one for bacterial communities. Should a combined treatment be needed, the combination of mesotrione and s-metolachlor shows the next best final resilience. Our results show the relevance of comparative rhizobacterial community studies when novel combined herbicide treatments are deemed necessary to control weed growth.. PMID:25394507

Valverde, José R; Marín, Silvia; Mellado, Rafael P



[Seasonal evaluation of mammal species richness and abundance in the "Mário Viana" municipal reserve, Mato Grosso, Brasil].  


We evaluated seasonal species presence and richness, and abundance of medium and large sized mammalian terrestrial fauna in the "Mário Viana" Municipal Biological Reserve, Nova Xavantina, Mato Grosso, Brazil. During 2001, two monthly visits were made to an established transect, 2,820 m in length. Records of 22 mammal species were obtained and individual footprint sequences quantified for seasonal calculation of species richness and relative abundance index (x footprints/km traveled). All 22 species occurred during the rainy season, but only 18 during the dry season. Pseudalopex vetulus (Lund, 1842) (hoary fox), Eira barbara (Linnaeus, 1758) (tayra), Puma concolor (Linnaeus, 1771) (cougar) and Hydrochaeris hydrochaeris (Linnaeus, 1766) (capybara) were only registered during the rainy season. The species diversity estimated using the Jackknife procedure in the dry season (19.83, CI = 2.73) was smaller than in the rainy season (25.67, CI = 3.43). Among the 18 species common in the two seasons, only four presented significantly different abundance indexes: Dasypus novemcinctus Linnaeus, 1758 (nine-banded armadillo), Euphractus sexcinctus (Linnaeus, 1758) (six-banded armadillo), Dasyprocta azarae Lichtenstein, 1823 (Azara's Agouti) and Tapirus terrestris (Linnaeus, 1758) (tapir). On the other hand, Priodontes maximus (Kerr, 1792) (giant armadillo) and Leopardus pardalis (Linnaeus, 1758) (ocelot) had identical abundance index over the two seasons. Distribution of species abundance in the sampled area followed the expected pattern for communities in equilibrium, especially in the rainy season, suggesting that the environment still maintains good characteristics for mammal conservation. The present study shows that the reserve, although only 470 ha in size, plays an important role for conservation of mastofauna of the area as a refuge in an environment full of anthropic influence (mainly cattle breeding in exotic pasture). PMID:18491629

Rocha, Ednaldo Cândido; Silva, Elias; Martins, Sebastião Venâncio; Barreto, Francisco Cândido Cardoso



Fast empirical pKa prediction by Ewald summation.  


pK(a) calculations for macromolecules are normally performed by solving the Poisson-Boltzmann equation, accounting for the different dielectric constants of solvent and solute, as well as the ionic strength. Despite the large number of successful applications, there are some situations where the current algorithms are not suitable: (1) large scale, high-throughput analysis which requires calculations to be completed within a fraction of a second, e.g. when permanently monitoring pK(a) shifts during a molecular dynamics simulation; (2) prediction of pK(a)s in periodic boundaries, e.g. when reconstructing entire protein crystal unit cells from PDB files, including the correct protonation patterns at experimental pH. Such in silico crystals are needed by 'self-parameterizing' molecular dynamics force fields like YASARA YAMBER, that optimize their parameters while energy-minimizing high-resolution protein crystals. To address both problems, we define an empirical equation that expresses the pK(a) as a function of electrostatic potential, hydrogen bonds and accessible surface area. The electrostatic potential is evaluated by Ewald summation, which captures periodic crystal environments and the uncertainty in atom positions using Gaussian charge densities. The empirical proportionality constants are derived from 217 experimentally determined pK(a)s, and despite its simplicity, this pK(a) calculation method reaches a high overall jack-knifed accuracy, and is fast enough to be used during a molecular dynamics simulation. A reliable null-model to judge pK(a) prediction accuracies is also presented. PMID:16644253

Krieger, Elmar; Nielsen, Jens E; Spronk, Chris A E M; Vriend, Gert



Climate change in our backyards: the reshuffling of North America's winter bird communities.  


Much of the recent changes in North American climate have occurred during the winter months, and as result, overwintering birds represent important sentinels of anthropogenic climate change. While there is mounting evidence that bird populations are responding to a warming climate (e.g., poleward shifts) questions remain as to whether these species-specific responses are resulting in community-wide changes. Here, we test the hypothesis that a changing winter climate should favor the formation of winter bird communities dominated by warm-adapted species. To do this, we quantified changes in community composition using a functional index - the Community Temperature Index (CTI) - which measures the balance between low- and high-temperature dwelling species in a community. Using data from Project FeederWatch, an international citizen science program, we quantified spatiotemporal changes in winter bird communities (n = 38 bird species) across eastern North America and tested the influence of changes in winter minimum temperature over a 22-year period. We implemented a jackknife analysis to identify those species most influential in driving changes at the community level and the population dynamics (e.g., extinction or colonization) responsible for these community changes. Since 1990, we found that the winter bird community structure has changed with communities increasingly composed of warm-adapted species. This reshuffling of winter bird communities was strongest in southerly latitudes and driven primarily by local increases in abundance and regional patterns of colonization by southerly birds. CTI tracked patterns of changing winter temperature at different temporal scales ranging from 1 to 35 years. We conclude that a shifting winter climate has provided an opportunity for smaller, southerly distributed species to colonize new regions and promote the formation of unique winter bird assemblages throughout eastern North America. PMID:25322929

Princé, Karine; Zuckerberg, Benjamin



Influence of cell surface hydrophobicity on attachment of Campylobacter to abiotic surfaces.  


This work aimed to investigate the influence of physicochemical properties and prior mode of growth (planktonic or sessile culture) on attachment of 13 Campylobacter jejuni strains and 5 Campylobacter coli strains isolated from chicken samples to three abiotic surfaces: stainless steel, glass and polyurethane. Water contact angle and zeta potential measurements indicated that the strains varied with respect to surface hydrophobicity (17.6 ± 1.5 to 53.0 ± 2.3°) and surface charge (-3.3 ± 0.4 to -15.1 ± 0.5 mV). Individual strains had different attachment abilities to stainless steel and glass (3.79 ± 0.16 to 5.45 ± 0.08 log cell cm(-2)) but did not attach to polyurethane, with one exception. Attachment of Campylobacter to abiotic surfaces significantly correlated with cell surface hydrophobicity (P ? 0.007), but not with surface charge (P ? 0.507). Cells grown as planktonic and sessile culture generally differed significantly from each other with respect to hydrophobicity and attachment (P < 0.05), but not with respect to surface charge (P > 0.05). Principal component analysis (PCA) clustered strains into three groups (planktonic culture) and two groups (sessile culture) representing those with similar hydrophobicity and attachment. Of the four highly hydrophobic and adherent strains, three were C. coli suggesting that isolates with greater hydrophobicity and adherence may occur more frequently among C. coli than C. jejuni strains although this requires further investigation using a larger number of strains. Assignment of pulsed-field gel electrophoresis profiles to PCA groups using Jackknife analysis revealed no overall relationship between bacterial genotypes and bacterial attachment. No relationship between serotype distribution and bacterial attachment was apparent in this study. PMID:21569937

Nguyen, Vu Tuan; Turner, Mark S; Dykes, Gary A



Polynesian ant (Hymenoptera: Formicidae) species richness and distribution: a regional survey  

NASA Astrophysics Data System (ADS)

Thirteen Polynesian islands, including five true atolls, an uplifted atoll, and seven high volcanic islands of varying ages, were surveyed for ants by hand collecting techniques. Ten of the thirteen islands had been surveyed previously, and more and species were found in the present survey than were known from all earlier surveys combined, with two exception (Ducie Atoll and Easter Island). This represents the first report of the Argentine ant, Linepithema humile Mayr, from Easter Island. L. humile is a very successful pest species which has only recently invaded Easter Island, and is now very abundant and widespread, occurring at 16 of the 17 sample sites scattered across the island. The introduction of this species is almost certainly responsible for the apparent decline in species richness on Easter Island. In general, more species were present on high islands than atolls of a similar size, and elevation was significant while log (area) and latitude were not in a multiple linear regression with ant species number as the dependent variable. Not enough time was spent on the islands to survey their ant faunas completely, and extrapolations from species effort curves and jackknife estimators of earlier, thorough surverys for ants in the society Islands suggest that only about 50% of the total species were collected in the present survey, at least on the high islands. My collections were probably more complete on the atolls. The increase in species numbers from the present survey relative to known species richnesses (particularly when a large fraction of the species actually present were probably not included in the present survey) supports the hypothesis that remote Polynesian islands are not as depauperate in terms of ant species numbers as previously thought.

Morrison, Lloyd W.



High-resolution taxonomic profiling of the subgingival microbiome for biomarker discovery and periodontitis diagnosis.  


The oral microbiome plays a key role for caries, periodontitis, and systemic diseases. A method for rapid, high-resolution, robust taxonomic profiling of subgingival bacterial communities for early detection of periodontitis biomarkers would therefore be a useful tool for individualized medicine. Here, we used Illumina sequencing of the V1-V2 and V5-V6 hypervariable regions of the 16S rRNA gene. A sample stratification pipeline was developed in a pilot study of 19 individuals, 9 of whom had been diagnosed with chronic periodontitis. Five hundred twenty-three operational taxonomic units (OTUs) were obtained from the V1-V2 region and 432 from the V5-V6 region. Key periodontal pathogens like Porphyromonas gingivalis, Treponema denticola, and Tannerella forsythia could be identified at the species level with both primer sets. Principal coordinate analysis identified two outliers that were consistently independent of the hypervariable region and method of DNA extraction used. The linear discriminant analysis (LDA) effect size algorithm (LEfSe) identified 80 OTU-level biomarkers of periodontitis and 17 of health. Health- and periodontitis-related clusters of OTUs were identified using a connectivity analysis, and the results confirmed previous studies with several thousands of samples. A machine learning algorithm was developed which was trained on all but one sample and then predicted the diagnosis of the left-out sample (jackknife method). Using a combination of the 10 best biomarkers, 15 of 17 samples were correctly diagnosed. Training the algorithm on time-resolved community profiles might provide a highly sensitive tool to detect the onset of periodontitis. PMID:25452281

Szafranski, Szymon P; Wos-Oxley, Melissa L; Vilchez-Vargas, Ramiro; Jáuregui, Ruy; Plumeier, Iris; Klawonn, Frank; Tomasch, Jürgen; Meisinger, Christa; Kühnisch, Jan; Sztajer, Helena; Pieper, Dietmar H; Wagner-Döbler, Irene



DNA hybridization evidence for the principal lineages of hummingbirds (Aves:Trochilidae).  


The spectacular evolutionary radiation of hummingbirds (Trochilidae) has served as a model system for many biological studies. To begin to provide a historical context for these investigations, we generated a complete matrix of DNA hybridization distances among 26 hummingbirds and an outgroup swift (Chaetura pelagica) to determine the principal hummingbird lineages. FITCH topologies estimated from symmetrized delta TmH-C values and subjected to various validation methods (bootstrapping, weighted jackknifing, branch length significance) indicated a fundamental split between hermit (Eutoxeres aquila, Threnetes ruckeri; Phaethornithinae) and nonhermit (Trochilinae) hummingbirds, and provided strong support for six principal nonhermit clades with the following branching order: (1) a predominantly lowland group comprising caribs (Eulampis holosericeus) and relatives (Androdon aequatorialis and Heliothryx barroti) with violet-ears (Colibri coruscans) and relatives (Doryfera ludovicae); (2) an Andean-associated clade of highly polytypic taxa (Eriocnemis, Heliodoxa, and Coeligena); (3) a second endemic Andean clade (Oreotrochilus chimborazo, Aglaiocercus coelestis, and Lesbia victoriae) paired with thorntails (Popelairia conversii); (4) emeralds and relatives (Chlorostilbon mellisugus, Amazilia tzacatl, Thalurania colombica, Orthorhyncus cristatus and Campylopterus villaviscensio); (5) mountain-gems (Lampornis clemenciae and Eugenes fulgens); and (6) tiny bee-like forms (Archilochus colubris, Myrtis fanny, Acestrura mulsant, and Philodice mitchellii). Corresponding analyses on a matrix of unsymmetrized delta values gave similar support for these relationships except that the branching order of the two Andean clades (2, 3 above) was unresolved. In general, subsidiary relationships were consistent and well supported by both matrices, sometimes revealing surprising associations between forms that differ dramatically in plumage and bill morphology. Our results also reveal some basic aspects of hummingbird ecologic and morphologic evolution. For example, most of the diverse endemic Andean assemblage apparently comprises two genetically divergent clades, whereas the majority of North American hummingbirds belong a single third clade. Genetic distances separating some morphologically distinct genera (Oreotrochilus, Aglaiocercus, Lesbia; Myrtis, Acestrura, Philodice) were no greater than among congeneric (Coeligena) species, indicating that, in hummingbirds, morphological divergence does not necessarily reflect level of genetic divergence. PMID:9066799

Bleiweiss, R; Kirsch, J A; Matheus, J C



Phylogenetic studies favour the unification of Pennisetum, Cenchrus and Odontelytrum (Poaceae): a combined nuclear, plastid and morphological analysis, and nomenclatural combinations in Cenchrus  

PubMed Central

Backgrounds and Aims Twenty-five genera having sterile inflorescence branches were recognized as the bristle clade within the x = 9 Paniceae (Panicoideae). Within the bristle clade, taxonomic circumscription of Cenchrus (20–25 species), Pennisetum (80–140) and the monotypic Odontelytrum is still unclear. Several criteria have been applied to characterize Cenchrus and Pennisetum, but none of these has proved satisfactory as the diagnostic characters, such as fusion of bristles in the inflorescences, show continuous variation. Methods A phylogenetic analysis based on morphological, plastid (trnL-F, ndhF) and nuclear (knotted) data is presented for a representative species sampling of the genera. All analyses were conducted under parsimony, using heuristic searches with TBR branch swapping. Branch support was assessed with parsimony jackknifing. Key Results Based on plastid and morphological data, Pennisetum, Cenchrus and Odontelytrum were supported as a monophyletic group: the PCO clade. Only one section of Pennisetum (Brevivalvula) was supported as monophyletic. The position of P. lanatum differed among data partitions, although the combined plastid and morphology and nuclear analyses showed this species to be a member of the PCO clade. The basic chromosome number x = 9 was found to be plesiomorphic, and x = 5, 7, 8, 10 and 17 were derived states. The nuclear phylogenetic analysis revealed a reticulate pattern of relationships among Pennisetum and Cenchrus, suggesting that there are at least three different genomes. Because apomixis can be transferred among species through hybridization, its history most likely reflects crossing relationships, rather than multiple independent appearances. Conclusions Due to the consistency between the present results and different phylogenetic hypotheses (including morphological, developmental and multilocus approaches), and the high support found for the PCO clade, also including the type species of the three genera, we propose unification of Pennisetum, Cenchrus and Odontelytrum. Species of Pennisetum and Odontelytrum are here transferred into Cenchrus, which has priority. Sixty-six new combinations are made here. PMID:20570830

Chemisquy, M. Amelia; Giussani, Liliana M.; Scataglini, María A.; Kellogg, Elizabeth A.; Morrone, Osvaldo



Comparison of Regionalization Methods for Flow Regime Simulation at Ungauged Basins in Ontario.  

NASA Astrophysics Data System (ADS)

In this study, regionalization, a process of transferring hydrological information from gauged to ungauged basins, is used to simulate continuous flow regime in different watersheds across Ontario climatic regions. The entire study area covers approximately 1 million km2 and most of the basins have incomplete or short period of data records and most of them are located in the northern regions. Various regionalisation approaches have been proposed in the literature; however, it is unclear which methods could be the most appropriate for a given climatic and physical environment. The data collected for this study includes the catchment attributes (e.g. soil and geology types, landscape properties, shape characteristics of the catchments, etc) and computed model parameters of the integrated hydrologic modeling system (IHMS-HBV) for gauged basins. The regional model parameters used to simulate continuous flows in ungauged basins are obtained using a physical similarity approach through clustering technique, a non-physical similarity approach such as multiple regression, and methods which do not consider the role of catchment attributes such as kriging and weighting based on the inverse distance. Preliminary results based on jackknife cross correlation validation show that the weighting approach based on the inverse distance technique produces better results than kriging, multiple regression and clustering. Although kriging and multiple regression are the most largely used regionalization methods, they appear inappropriate in this region. This may be due to the large size of the catchments and/or the large number of selected attributes. Other emerging regionalization methods such as logistic regression implemented through neural network technique are under investigation. The best methods identified will be used to simulate flow regime at gauged and ungauged basins across Ontario. The flow regime information is essential to establishing environmental flow policy, regulations, and sustainable water management.

Samuel, J.; Coulibaly, P.; Metcalfe, R.



Comparison of subcellular responses for the evaluation and prediction of the chemotherapeutic response to cisplatin in lung adenocarcinoma using Raman spectroscopy.  


Confocal Raman Micro-spectroscopy (CRM) is employed to examine the chemical and physiological effects of anticancer agents, using cisplatin and A549 adenocarcinoma cells as a model compound and test system respectively. Spectral responses of the membrane and cytoplasm of the cell are analysed independently and the results are compared to previously reported spectroscopic studies of the nucleus. Moreover, Raman spectra from the proteins extracted from the control and exposed samples are acquired and analysed to confirm the origin of the molecular changes of the cell membrane and cytoplasm of the A549 cells. Multivariate data analysis techniques including Principal Component Analysis (PCA) and Partial Least Squares Regression (PLSR) along with PLS-Jackknifing are used to analyse the data measured from the cell membrane and cytoplasm of the A549 cells and results are correlated with parallel measurements from the cytotoxicity assay MTT. A PLSR model is used to differentiate between the chemical effect of the chemotherapeutic agent and the physiological response of the A549 cells and to identify regions of the spectrum that are associated with these processes respectively. The PLSR model is also employed to predict, on the basis of the Raman spectra, the effective dose as well as the level of physiological response, using spectra data from the cytoplasmic and cell membrane regions. The effectiveness of the models based on spectral datasets from the cell membrane and cytoplasm is compared to similar models constructed using spectral data from the nuclear region as well as one combining spectral data from all regions. In all cases, higher prediction accuracy is found for regression against the cisplatin dose, and for both regression against the dose and the physiological response, nuclear data yield higher precision. PMID:21519610

Nawaz, Haq; Bonnier, Franck; Meade, Aidan D; Lyng, Fiona M; Byrne, Hugh J



Dose reduction and its influence on diagnostic accuracy and radiation risk in digital mammography: an observer performance study using an anthropomorphic breast phantom  

PubMed Central

This study aimed to investigate the effect of dose reduction on diagnostic accuracy and radiation risk in digital mammography. Simulated masses and microcalcifications were positioned in an anthropomorphic breast phantom. Thirty digital images, 14 with lesions, 16 without, were acquired of the phantom using a Mammomat Novation (Siemens, Erlangen, Germany) at each of three dose levels. These corresponded to 100%, 50% and 30% of the normally used average glandular dose (AGD; 1.3 mGy for a standard breast). Eight observers interpreted the 90 unprocessed images in a free-response study and the data was analyzed with the jackknife free-response receiver operating characteristic (JAFROC) method. Observer performance was assessed using the JAFROC figure of merit (FOM). The benefit of radiation risk reduction was estimated based on several risk models. There was no statistically significant difference in performance, as described by the FOM, between the 100% and the 50% dose levels. However, the FOMs for both the 100% and the 50% dose were significantly different from the corresponding quantity for the 30% dose level (F-statistic = 4.95, p-value = 0.01). A dose reduction of 50% would result in 3-9 fewer breast cancer fatalities per 100,000 women undergoing annual screening from the age of 40 to 49 years. The results of the study indicate a possibility of reducing the dose to the breast to half of the dose level currently used. This has to be confirmed in clinical studies and possible differences depending on lesion type should be further examined. PMID:17704316

Svahn, Tony; Hemdal, Bengt; Ruschin, Mark; Chakraborty, Dev P; Andersson, Ingvar; Tingberg, Anders; Mattsson, Sören



Prediction of deleterious non-synonymous SNPs based on protein interaction network and hybrid properties.  


Non-synonymous SNPs (nsSNPs), also known as Single Amino acid Polymorphisms (SAPs) account for the majority of human inherited diseases. It is important to distinguish the deleterious SAPs from neutral ones. Most traditional computational methods to classify SAPs are based on sequential or structural features. However, these features cannot fully explain the association between a SAP and the observed pathophysiological phenotype. We believe the better rationale for deleterious SAP prediction should be: If a SAP lies in the protein with important functions and it can change the protein sequence and structure severely, it is more likely related to disease. So we established a method to predict deleterious SAPs based on both protein interaction network and traditional hybrid properties. Each SAP is represented by 472 features that include sequential features, structural features and network features. Maximum Relevance Minimum Redundancy (mRMR) method and Incremental Feature Selection (IFS) were applied to obtain the optimal feature set and the prediction model was Nearest Neighbor Algorithm (NNA). In jackknife cross-validation, 83.27% of SAPs were correctly predicted when the optimized 263 features were used. The optimized predictor with 263 features was also tested in an independent dataset and the accuracy was still 80.00%. In contrast, SIFT, a widely used predictor of deleterious SAPs based on sequential features, has a prediction accuracy of 71.05% on the same dataset. In our study, network features were found to be most important for accurate prediction and can significantly improve the prediction performance. Our results suggest that the protein interaction context could provide important clues to help better illustrate SAP's functional association. This research will facilitate the post genome-wide association studies. PMID:20689580

Huang, Tao; Wang, Ping; Ye, Zhi-Qiang; Xu, Heng; He, Zhisong; Feng, Kai-Yan; Hu, Lele; Cui, Weiren; Wang, Kai; Dong, Xiao; Xie, Lu; Kong, Xiangyin; Cai, Yu-Dong; Li, Yixue



Robust Estimation of Precipitation Extremes from Short-Period Regional Climate Downscales  

NASA Astrophysics Data System (ADS)

The US Southwest is likely to experience significant changes in precipitation patterns in coming decades as a result of regional climate change. One serious issue is to better understand extreme precipitation events, which affect infrastructure planning, and human life and safety management. Extreme precipitation events are characterized by the maximum expectation of accumulated precipitation over a short time period, which has a long-period return over some number of years; e.g., the 100-year return of daily precipitation. These measures are statistics drawn from Extreme Value Theory, and can be challenging to accurately and reliably estimate for short data sets. Regional Climate Models (RCM) are often run for shorter decadal periods, both to economize on computational expense, and to characterize specific decadal time bands. In each case, one needs robust statistical estimation algorithms to accurately and reliably retrieve the precipitation recurrence statistics. To produce these important decision-aiding products, we added several processes to an otherwise conventional Peaks Over Threshold technique operating on the combined grid-scale and cumuliform precipitation outputs from our 12 kilometer Weather Research and Forecasting (WRF) downscale of the National Centers for Environmental Prediction (NCEP) reanalysis fields for the ten year period of 2000-2009 over the Southwest US. These processes included interleaved sub-year intermediate aggregations, correlated sample corrections, distributional tail feature extraction, and trimmed set tail fitting with jackknife error estimation. The process resulted in estimated 100-year return 24-hour accumulated precipitation expectations with accompanying error bounds, which compare well to established historical precipitation statistics.

Apling, D.; Darmenova, K.; Higgins, G. J.



Simulating cosmic reionization: how large a volume is large enough?  

NASA Astrophysics Data System (ADS)

We present the largest-volume (425 Mpc h-1 = 607 Mpc on a side) full radiative transfer simulation of cosmic reionization to date. We show that there is significant additional power in density fluctuations at very large scales. We systematically investigate the effects this additional power has on the progress, duration and features of reionization and on selected reionization observables. We find that comoving volume of ˜100 Mpc h-1 per side is sufficient for deriving a convergent mean reionization history, but that the reionization patchiness is significantly underestimated. We use jackknife splitting to quantify the convergence of reionization properties with simulation volume. We find that sub-volumes of ˜100 Mpc h-1 per side or larger yield convergent reionization histories, except for the earliest times, but smaller volumes of ˜50 Mpc h-1 or less are not well converged at any redshift. Reionization history milestones show significant scatter between the sub-volumes, as high as ?z ˜ 1 for ˜50 Mpc h-1 volumes. If we only consider mean-density sub-regions the scatter decreases, but remains at ?z ˜ 0.1-0.2 for the different size sub-volumes. Consequently, many potential reionization observables like 21-cm rms, 21-cm PDF skewness and kurtosis all show good convergence for volumes of ˜200 Mpc h-1, but retain considerable scatter for smaller volumes. In contrast, the three-dimensional 21-cm power spectra at large scales (k < 0.25 h Mpc-1) do not fully converge for any sub-volume size. These additional large-scale fluctuations significantly enhance the 21-cm fluctuations, which should improve the prospects of detection considerably, given the lower foregrounds and greater interferometer sensitivity at higher frequencies.

Iliev, Ilian T.; Mellema, Garrelt; Ahn, Kyungjin; Shapiro, Paul R.; Mao, Yi; Pen, Ue-Li



An Ancient Origin for the Enigmatic Flat-Headed Frogs (Bombinatoridae: Barbourula) from the Islands of Southeast Asia  

PubMed Central

Background The complex history of Southeast Asian islands has long been of interest to biogeographers. Dispersal and vicariance events in the Pleistocene have received the most attention, though recent studies suggest a potentially more ancient history to components of the terrestrial fauna. Among this fauna is the enigmatic archaeobatrachian frog genus Barbourula, which only occurs on the islands of Borneo and Palawan. We utilize this lineage to gain unique insight into the temporal history of lineage diversification in Southeast Asian islands. Methodology/Principal Findings Using mitochondrial and nuclear genetic data, multiple fossil calibration points, and likelihood and Bayesian methods, we estimate phylogenetic relationships and divergence times for Barbourula. We determine the sensitivity of focal divergence times to specific calibration points by jackknife approach in which each calibration point is excluded from analysis. We find that relevant divergence time estimates are robust to the exclusion of specific calibration points. Barbourula is recovered as a monophyletic lineage nested within a monophyletic Costata. Barbourula diverged from its sister taxon Bombina in the Paleogene and the two species of Barbourula diverged in the Late Miocene. Conclusions/Significance The divergences within Barbourula and between it and Bombina are surprisingly old and represent the oldest estimates for a cladogenetic event resulting in living taxa endemic to Southeast Asian islands. Moreover, these divergence time estimates are consistent with a new biogeographic scenario: the Palawan Ark Hypothesis. We suggest that components of Palawan's terrestrial fauna might have “rafted” on emergent portions of the North Palawan Block during its migration from the Asian mainland to its present-day position near Borneo. Further, dispersal from Palawan to Borneo (rather than Borneo to Palawan) may explain the current day disjunct distribution of this ancient lineage. PMID:20711504

Blackburn, David C.; Bickford, David P.; Diesmos, Arvin C.; Iskandar, Djoko T.; Brown, Rafe M.



Effect of volatile compounds in grass silage on voluntary intake by growing cattle.  


Twenty-four low dry matter (DM) silages differing in fermentation quality were harvested at the same time from a crop that consisted mainly of timothy (Phleum pratense), and meadow fescue (Festuca pratensis). The silage samples were analysed by gas chromatography (GC) - mass spectrometry and gas chromatography - flame ionisation detection in order to determine and quantify volatiles present in silage. The voluntary intake of the 24 silages had been measured in a previous feeding trial with growing steers of Norwegian Red. Thirteen esters, five aldehydes, three alcohols, and one sulphide were identified and quantified. A total of 51 variables describing the chemical composition of the silages were included in a partial least-squares regression, and the relationship of silage fermentation quality to voluntary intake was elucidated. The importance of variables describing silage fermentation quality in relation to intake was judged from a best combination procedure, jack-knifing, and empirical correlations of the variables to intake. The GC-analysed compounds were mainly present in poorly fermented silages. However, compared with other explanatory chemical variables none of these compounds was of importance for the voluntary intake as evaluated by partial least-squares regression. A validated variance of 71% in silage DM intake was explained with the selected variables: total acids (TA), total volatile fatty acids (TVFA), lactic acid/total acid ratio and propionic acid. In this study extent (by the variable TA) and type of silage fermentation (by TVFA) influenced intake. Further, it is suggested that by restricting the fermentation in low DM grass silages the potential intake of silage DM is maximised. PMID:22444294

Krizsan, S J; Westad, F; Adnøy, T; Odden, E; Aakre, S E; Randby, A T



Prediction of Protein S-Nitrosylation Sites Based on Adapted Normal Distribution Bi-Profile Bayes and Chou’s Pseudo Amino Acid Composition  

PubMed Central

Protein S-nitrosylation is a reversible post-translational modification by covalent modification on the thiol group of cysteine residues by nitric oxide. Growing evidence shows that protein S-nitrosylation plays an important role in normal cellular function as well as in various pathophysiologic conditions. Because of the inherent chemical instability of the S-NO bond and the low abundance of endogenous S-nitrosylated proteins, the unambiguous identification of S-nitrosylation sites by commonly used proteomic approaches remains challenging. Therefore, computational prediction of S-nitrosylation sites has been considered as a powerful auxiliary tool. In this work, we mainly adopted an adapted normal distribution bi-profile Bayes (ANBPB) feature extraction model to characterize the distinction of position-specific amino acids in 784 S-nitrosylated and 1568 non-S-nitrosylated peptide sequences. We developed a support vector machine prediction model, iSNO-ANBPB, by incorporating ANBPB with the Chou’s pseudo amino acid composition. In jackknife cross-validation experiments, iSNO-ANBPB yielded an accuracy of 65.39% and a Matthew’s correlation coefficient (MCC) of 0.3014. When tested on an independent dataset, iSNO-ANBPB achieved an accuracy of 63.41% and a MCC of 0.2984, which are much higher than the values achieved by the existing predictors SNOSite, iSNO-PseAAC, the Li et al. algorithm, and iSNO-AAPair. On another training dataset, iSNO-ANBPB also outperformed GPS-SNO and iSNO-PseAAC in the 10-fold crossvalidation test. PMID:24918295

Jia, Cangzhi; Lin, Xin; Wang, Zhiping



Housefly Population Density Correlates with Shigellosis among Children in Mirzapur, Bangladesh: A Time Series Analysis  

PubMed Central

Background Shigella infections are a public health problem in developing and transitional countries because of high transmissibility, severity of clinical disease, widespread antibiotic resistance and lack of a licensed vaccine. Whereas Shigellae are known to be transmitted primarily by direct fecal-oral contact and less commonly by contaminated food and water, the role of the housefly Musca domestica as a mechanical vector of transmission is less appreciated. We sought to assess the contribution of houseflies to Shigella-associated moderate-to-severe diarrhea (MSD) among children less than five years old in Mirzapur, Bangladesh, a site where shigellosis is hyperendemic, and to model the potential impact of a housefly control intervention. Methods Stool samples from 843 children presenting to Kumudini Hospital during 2009–2010 with new episodes of MSD (diarrhea accompanied by dehydration, dysentery or hospitalization) were analyzed. Housefly density was measured twice weekly in six randomly selected sentinel households. Poisson time series regression was performed and autoregression-adjusted attributable fractions (AFs) were calculated using the Bruzzi method, with standard errors via jackknife procedure. Findings Dramatic springtime peaks in housefly density in 2009 and 2010 were followed one to two months later by peaks of Shigella-associated MSD among toddlers and pre-school children. Poisson time series regression showed that housefly density was associated with Shigella cases at three lags (six weeks) (Incidence Rate Ratio?=?1.39 [95% CI: 1.23 to 1.58] for each log increase in fly count), an association that was not confounded by ambient air temperature. Autocorrelation-adjusted AF calculations showed that a housefly control intervention could have prevented approximately 37% of the Shigella cases over the study period. Interpretation Houseflies may play an important role in the seasonal transmission of Shigella in some developing country ecologies. Interventions to control houseflies should be evaluated as possible additions to the public health arsenal to diminish Shigella (and perhaps other causes of) diarrheal infection. PMID:23818998

Farag, Tamer H.; Faruque, Abu S.; Wu, Yukun; Das, Sumon K.; Hossain, Anowar; Ahmed, Shahnawaz; Ahmed, Dilruba; Nasrin, Dilruba; Kotloff, Karen L.; Panchilangam, Sandra; Nataro, James P.; Cohen, Dani; Blackwelder, William C.; Levine, Myron M.



The effect of image processing on the detection of cancers in digital mammography.  


OBJECTIVE. The objective of our study was to investigate the effect of image processing on the detection of cancers in digital mammography images. MATERIALS AND METHODS. Two hundred seventy pairs of breast images (both breasts, one view) were collected from eight systems using Hologic amorphous selenium detectors: 80 image pairs showed breasts containing subtle malignant masses; 30 image pairs, biopsy-proven benign lesions; 80 image pairs, simulated calcification clusters; and 80 image pairs, no cancer (normal). The 270 image pairs were processed with three types of image processing: standard (full enhancement), low contrast (intermediate enhancement), and pseudo-film-screen (no enhancement). Seven experienced observers inspected the images, locating and rating regions they suspected to be cancer for likelihood of malignancy. The results were analyzed using a jackknife-alternative free-response receiver operating characteristic (JAFROC) analysis. RESULTS. The detection of calcification clusters was significantly affected by the type of image processing: The JAFROC figure of merit (FOM) decreased from 0.65 with standard image processing to 0.63 with low-contrast image processing (p = 0.04) and from 0.65 with standard image processing to 0.61 with film-screen image processing (p = 0.0005). The detection of noncalcification cancers was not significantly different among the image-processing types investigated (p > 0.40). CONCLUSION. These results suggest that image processing has a significant impact on the detection of calcification clusters in digital mammography. For the three image-processing versions and the system investigated, standard image processing was optimal for the detection of calcification clusters. The effect on cancer detection should be considered when selecting the type of image processing in the future. PMID:25055275

Warren, Lucy M; Given-Wilson, Rosalind M; Wallis, Matthew G; Cooke, Julie; Halling-Brown, Mark D; Mackenzie, Alistair; Chakraborty, Dev P; Bosmans, Hilde; Dance, David R; Young, Kenneth C



Early detection of production deficit hot spots in semi-arid environment using FAPAR time series and a probabilistic approach  

NASA Astrophysics Data System (ADS)

Timely information on vegetation development at regional scale is needed in arid and semiarid African regions where rainfall variability leads to high inter-annual fluctuations in crop and pasture productivity, as well as to high risk of food crisis in the presence of severe drought events. The present study aims at developing and testing an automatic procedure to estimate the probability of experiencing a seasonal biomass production deficit solely on the basis of historical and near real-time remote sensing observations. The method is based on the extraction of vegetation phenology from SPOT-VEGTATION time series of the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) and the subsequent computation of seasonally cumulated FAPAR as a proxy for vegetation gross primary production. Within season forecasts of the overall seasonal performance, expressed in terms of probability of experiencing a critical deficit, are based on a statistical approach taking into account two factors: i) the similarity between the current FAPAR profile and past profiles observable in the 15 years FAPAR time series; ii) the uncertainty of past predictions of season outcome as derived using jack-knifing technique. The method is applicable at the regional to continental scale and can be updated regularly during the season (whenever a new satellite observation is made available) to provide a synoptic view of the hot spots of likely production deficit. The specific objective of the procedure described here is to deliver to the food security analyst, as early as possible within the season, only the relevant information (e.g., masking out areas without active vegetation at the time of analysis), expressed through a reliable and easily interpretable measure of impending risk. Evaluation of method performance and examples of application in the Sahel region are discussed.

Meroni, M.; Fasbender, D.; Kayitakire, F.; Pini, G.; Rembold, F.; Urbano, F.; Verstraete, M. M.



Phylogenetic diversity and ecological pattern of ammonia-oxidizing archaea in the surface sediments of the western Pacific.  


The phylogenetic diversity of ammonia-oxidizing archaea (AOA) was surveyed in the surface sediments from the northern part of the South China Sea (SCS). The distribution pattern of AOA in the western Pacific was discussed through comparing the SCS with other areas in the western Pacific including Changjiang Estuary and the adjacent East China Sea where high input of anthropogenic nitrogen was evident, the tropical West Pacific Continental Margins close to the Philippines, the deep-sea methane seep sediments in the Okhotsk Sea, the cold deep sea of Northeastern Japan Sea, and the hydrothermal field in the Southern Okinawa Trough. These various environments provide a wide spectrum of physical and chemical conditions for a better understanding of the distribution pattern and diversities of AOA in the western Pacific. Under these different conditions, the distinct community composition between shallow and deep-sea sediments was clearly delineated based on the UniFrac PCoA and Jackknife Environmental Cluster analyses. Phylogenetic analyses showed that a few ammonia-oxidizing archaeal subclades in the marine water column/sediment clade and endemic lineages were indicative phylotypes for some environments. Higher phylogenetic diversity was observed in the Philippines while lower diversity in the hydrothermal vent habitat. Water depth and possibly with other environmental factors could be the main driving forces to shape the phylogenetic diversity of AOA observed, not only in the SCS but also in the whole western Pacific. The multivariate regression tree analysis also supported this observation consistently. Moreover, the functions of current and other climate factors were also discussed in comparison of phylogenetic diversity. The information collectively provides important insights into the ecophysiological requirements of uncultured ammonia-oxidizing archaeal lineages in the western Pacific Ocean. PMID:21748268

Cao, Huiluo; Hong, Yiguo; Li, Meng; Gu, Ji-Dong



A hybrid orographic plus statistical model for downscaling daily precipitation in Northern California  

USGS Publications Warehouse

A hybrid (physical-statistical) scheme is developed to resolve the finescale distribution of daily precipitation over complex terrain. The scheme generates precipitation by combining information from the upper-air conditions and from sparsely distributed station measurements; thus, it proceeds in two steps. First, an initial estimate of the precipitation is made using a simplified orographic precipitation model. It is a steady-state, multilayer, and two-dimensional model following the concepts of Rhea. The model is driven by the 2.5?? ?? 2.5?? gridded National Oceanic and Atmospheric Administration-National Centers for Environmental Prediction upper-air profiles, and its parameters are tuned using the observed precipitation structure of the region. Precipitation is generated assuming a forced lifting of the air parcels as they cross the mountain barrier following a straight trajectory. Second, the precipitation is adjusted using errors between derived precipitation and observations from nearby sites. The study area covers the northern half of California, including coastal mountains, central valley, and the Sierra Nevada. The model is run for a 5-km rendition of terrain for days of January-March over the period of 1988-95. A jackknife analysis demonstrates the validity of the approach. The spatial and temporal distributions of the simulated precipitation field agree well with the observed precipitation. Further, a mapping of model performance indices (correlation coefficients, model bias, root-mean-square error, and threat scores) from an array of stations from the region indicates that the model performs satisfactorily in resolving daily precipitation at 5-km resolution.

Pandey, G.R.; Cayan, D.R.; Dettinger, M.D.; Georgakakos, K.P.



A hybrid method for prediction and repositioning of drug Anatomical Therapeutic Chemical classes.  


In the Anatomical Therapeutic Chemical (ATC) classification system, therapeutic drugs are divided into 14 main classes according to the organ or system on which they act and their chemical, pharmacological and therapeutic properties. This system, recommended by the World Health Organization (WHO), provides a global standard for classifying medical substances and serves as a tool for international drug utilization research to improve quality of drug use. In view of this, it is necessary to develop effective computational prediction methods to identify the ATC-class of a given drug, which thereby could facilitate further analysis of this system. In this study, we initiated an attempt to develop a prediction method and to gain insights from it by utilizing ontology information of drug compounds. Since only about one-fourth of drugs in the ATC classification system have ontology information, a hybrid prediction method combining the ontology information, chemical interaction information and chemical structure information of drug compounds was proposed for the prediction of drug ATC-classes. As a result, by using the Jackknife test, the 1st prediction accuracies for identifying the 14 main ATC-classes in the training dataset, the internal validation dataset and the external validation dataset were 75.90%, 75.70% and 66.36%, respectively. Analysis of some samples with false-positive predictions in the internal and external validation datasets indicated that some of them may even have a relationship with the false-positive predicted ATC-class, suggesting novel uses of these drugs. It was conceivable that the proposed method could be used as an efficient tool to identify ATC-classes of novel drugs or to discover novel uses of known drugs. PMID:24492783

Chen, Lei; Lu, Jing; Zhang, Ning; Huang, Tao; Cai, Yu-Dong



EMPeror: a tool for visualizing high-throughput microbial community data  

PubMed Central

Background As microbial ecologists take advantage of high-throughput sequencing technologies to describe microbial communities across ever-increasing numbers of samples, new analysis tools are required to relate the distribution of microbes among larger numbers of communities, and to use increasingly rich and standards-compliant metadata to understand the biological factors driving these relationships. In particular, the Earth Microbiome Project drives these needs by profiling the genomic content of tens of thousands of samples across multiple environment types. Findings Features of EMPeror include: ability to visualize gradients and categorical data, visualize different principal coordinates axes, present the data in the form of parallel coordinates, show taxa as well as environmental samples, dynamically adjust the size and transparency of the spheres representing the communities on a per-category basis, dynamically scale the axes according to the fraction of variance each explains, show, hide or recolor points according to arbitrary metadata including that compliant with the MIxS family of standards developed by the Genomic Standards Consortium, display jackknifed-resampled data to assess statistical confidence in clustering, perform coordinate comparisons (useful for procrustes analysis plots), and greatly reduce loading times and overall memory footprint compared with existing approaches. Additionally, ease of sharing, given EMPeror’s small output file size, enables agile collaboration by allowing users to embed these visualizations via emails or web pages without the need for extra plugins. Conclusions Here we present EMPeror, an open source and web browser enabled tool with a versatile command line interface that allows researchers to perform rapid exploratory investigations of 3D visualizations of microbial community data, such as the widely used principal coordinates plots. EMPeror includes a rich set of controllers to modify features as a function of the metadata. By being specifically tailored to the requirements of microbial ecologists, EMPeror thus increases the speed with which insight can be gained from large microbiome datasets. PMID:24280061



Development of waveform inversion techniques for using body-wave waveforms to infer localized three-dimensional seismic structure and an application to D"  

NASA Astrophysics Data System (ADS)

In order to further extract information on localized three-dimensional seismic structure from observed seismic data, we have developed and applied methods for seismic waveform inversion. Deriving algorithms for the calculation of synthetic seismograms and their partial derivatives, development of efficient software for their computation and for data handling, correction for near-source and near-receiver structure, and choosing appropriate parameterization of the model space are the key steps in such an inversion. We formulate the inverse problem of waveform inversion for localized structure, computing partial derivatives of waveforms with respect to the 3-D elastic moduli at arbitrary points in space for anisotropic and anelastic media. Our method does not use any great circle approximations in computing the synthetics and their partial derivatives. In order to efficiently solve the inverse problem we use the conjugate gradient (CG) method. We apply our methods to inversion for the three-dimensional shear wave structure in the lowermost mantle beneath Central America and the Western Pacific using waveforms in the period band from 12.5 to 200~s. Checkerboard tests show that waveform inversion of S, ScS, and the other phases which arrive between them can resolve laterally heterogenous shear-wave structure in the lowermost mantle using waves propagating only in a relatively limited range of azimuths. Checkerboard tests show that white noise has little impact on the results of waveform inversion. Various tests such as a jackknife test show that our model is robust. We verify the near-orthogonality of partial derivatives with respect to structure inside and outside the target region; we find that although datasets with only a small number of waveforms (e.g., waveforms recorded by stations for only a single event) cannot resolve structure inside and outside the target region, a dataset with a large number of waveforms can almost completely remove the effects of near-source and near-receiver structure. Waveform inversion with a large dataset is thus confirmed to be a promising approach to infer 3-D seismic fine structure in the Earth's deep interior.

Kawai, K.; Konishi, K.; Geller, R. J.; Fuji, N.



Source mechanisms of the 2000 earthquake swarm in the West Bohemia/Vogtland region (Central Europe)  

NASA Astrophysics Data System (ADS)

An earthquake swarm of magnitudes up to ML = 3.2 occurred in the region of West Bohemia/Vogtland (border area between Czech Republic and Germany) in autumn 2000. This swarm consisted of nine episodic phases and lasted 4 months. We retrieved source mechanisms of 102 earthquakes with magnitudes between ML = 1.6 and 3.2 applying inversion of the peak amplitudes of direct P and SH waves, which were determined from ground motion seismograms. The investigated events cover the whole swarm activity in both time and space. We use data from permanent stations of seismic network WEBNET and from temporal stations, which were deployed in the epicentral area during the swarm; the number of stations varied from 7 to 18. The unconstrained moment tensor (MT) expression of the mechanism, which describes a general system of dipoles, that is both double-couple (DC) and non-DC sources, was applied. MTs of each earthquake were estimated by inversion of three different sets of data: P-wave amplitudes only, P- and SH-wave amplitudes and P-wave amplitudes along with the SH-wave amplitudes from a priori selected four `base' WEBNET stations, the respective MT solutions are nearly identical for each event investigated. The resultant mechanisms of all events are dominantly DCs with only insignificant non-DC components mostly not exceeding 10 per cent. We checked reliability of the MTs in jackknife trials eliminating some data; we simulated the mislocation of hypocentre or contaminated the P- and SH-wave amplitudes by accidental errors. These tests proved stable and well constrained MT solutions. The massive dominance of the DC in all investigated events implies that the 2000 swarm consisted of a large number of pure shears along a fault plane. The focal mechanisms indicate both oblique-normal and oblique-thrust faulting, however, the oblique-normal faulting prevails. The predominant strikes and dips of the oblique-normal events fit well the geometry of the main fault plane Nový Kostel (NK) and also match the strike, dip and rake of the largest ML = 4.6 earthquake of a strong swarm in 1985/86. On the contrary, the 2000 source mechanisms differ substantially from those of the 1997-swarm (which took place in two fault segments at the edge of the main NK fault plane) in both the faulting and the content of non-DC components. Further, we found that the scalar seismic moment M0 is related to the local magnitude ML used by WEBNET as M0 ? 101.12ML, which differs from the scaling law using moment magnitude Mw, that is M0 ? 101.5Mw.

Horálek, Josef; Šílený, Jan



Detection of B-Mode Polarization at Degree Angular Scales by BICEP2  

NASA Astrophysics Data System (ADS)

We report results from the BICEP2 experiment, a cosmic microwave background (CMB) polarimeter specifically designed to search for the signal of inflationary gravitational waves in the B-mode power spectrum around ?˜80. The telescope comprised a 26 cm aperture all-cold refracting optical system equipped with a focal plane of 512 antenna coupled transition edge sensor 150 GHz bolometers each with temperature sensitivity of ?300 ?KCMB?s . BICEP2 observed from the South Pole for three seasons from 2010 to 2012. A low-foreground region of sky with an effective area of 380 square deg was observed to a depth of 87 nK deg in Stokes Q and U. In this paper we describe the observations, data reduction, maps, simulations, and results. We find an excess of B-mode power over the base lensed-?CDM expectation in the range 305?. Through jackknife tests and simulations based on detailed calibration measurements we show that systematic contamination is much smaller than the observed excess. Cross correlating against WMAP 23 GHz maps we find that Galactic synchrotron makes a negligible contribution to the observed signal. We also examine a number of available models of polarized dust emission and find that at their default parameter values they predict power ˜(5-10)× smaller than the observed excess signal (with no significant cross-correlation with our maps). However, these models are not sufficiently constrained by external public data to exclude the possibility of dust emission bright enough to explain the entire excess signal. Cross correlating BICEP2 against 100 GHz maps from the BICEP1 experiment, the excess signal is confirmed with 3? significance and its spectral index is found to be consistent with that of the CMB, disfavoring dust at 1.7?. The observed B-mode power spectrum is well fit by a lensed-?CDM+tensor theoretical model with tensor-to-scalar ratio r =0.20-0.05+0.07, with r=0 disfavored at 7.0?. Accounting for the contribution of foreground, dust will shift this value downward by an amount which will be better constrained with upcoming data sets.

Ade, P. A. R.; Aikin, R. W.; Barkats, D.; Benton, S. J.; Bischoff, C. A.; Bock, J. J.; Brevik, J. A.; Buder, I.; Bullock, E.; Dowell, C. D.; Duband, L.; Filippini, J. P.; Fliescher, S.; Golwala, S. R.; Halpern, M.; Hasselfield, M.; Hildebrandt, S. R.; Hilton, G. C.; Hristov, V. V.; Irwin, K. D.; Karkare, K. S.; Kaufman, J. P.; Keating, B. G.; Kernasovskiy, S. A.; Kovac, J. M.; Kuo, C. L.; Leitch, E. M.; Lueker, M.; Mason, P.; Netterfield, C. B.; Nguyen, H. T.; O'Brient, R.; Ogburn, R. W.; Orlando, A.; Pryke, C.; Reintsema, C. D.; Richter, S.; Schwarz, R.; Sheehy, C. D.; Staniszewski, Z. K.; Sudiwala, R. V.; Teply, G. P.; Tolan, J. E.; Turner, A. D.; Vieregg, A. G.; Wong, C. L.; Yoon, K. W.; Bicep2 Collaboration



Are the orbital poles of binary stars in the solar neighbourhood anisotropically distributed?  

NASA Astrophysics Data System (ADS)

We test whether or not the orbital poles of the systems in the solar neighbourhood are isotropically distributed on the celestial sphere. The problem is plagued by the ambiguity on the position of the ascending node. Of the 95 systems closer than 18 pc from the Sun with an orbit in the 6th Catalogue of Orbits of Visual Binaries, the pole ambiguity could be resolved for 51 systems using radial velocity collected in the literature and CORAVEL database or acquired with the HERMES/Mercator spectrograph. For several systems, we can correct the erroneous nodes in the 6th Catalogue of Orbits and obtain new combined spectroscopic/astrometric orbits for seven systems [WDS 01083+5455Aa,Ab; 01418+4237AB; 02278+0426AB (SB2); 09006+4147AB (SB2); 16413+3136AB; 17121+4540AB; 18070+3034AB]. We used of spherical statistics to test for possible anisotropy. After ordering the binary systems by increasing distance from the Sun, we computed the false-alarm probability for subsamples of increasing sizes, from N = 1 up to the full sample of 51 systems. Rayleigh-Watson and Beran tests deliver a false-alarm probability of 0.5% for the 20 systems closer than 8.1 pc. To evaluate the robustness of this conclusion, we used a jackknife approach, for which we repeated this procedure after removing one system at a time from the full sample. The false-alarm probability was then found to vary between 1.5% and 0.1%, depending on which system is removed. The reality of the deviation from isotropy can thus not be assessed with certainty at this stage, because only so few systems are available, despite our efforts to increase the sample. However, when considering the full sample of 51 systems, the concentration of poles toward the Galactic position l = 46.0°, b = 37°, as observed in the 8.1 pc sphere, totally vanishes (the Rayleigh-Watson false-alarm probability then rises to 18%). Tables 1-3 and Appendices are available in electronic form at† Deceased October 1, 2014.

Agati, J.-L.; Bonneau, D.; Jorissen, A.; Soulié, E.; Udry, S.; Verhas, P.; Dommanget, J.



Subspace Dimensionality: A Tool for Automated QC in Seismic Array Processing  

NASA Astrophysics Data System (ADS)

Because of the great resolving power of seismic arrays, the application of automated processing to array data is critically important in treaty verification work. A significant problem in array analysis is the inclusion of bad sensor channels in the beamforming process. We are testing an approach to automated, on-the-fly quality control (QC) to aid in the identification of poorly performing sensor channels prior to beam-forming in routine event detection or location processing. The idea stems from methods used for large computer servers, when monitoring traffic at enormous numbers of nodes is impractical on a node-by node basis, so the dimensionality of the node traffic is instead monitoried for anomalies that could represent malware, cyber-attacks or other problems. The technique relies upon the use of subspace dimensionality or principal components of the overall system traffic. The subspace technique is not new to seismology, but its most common application has been limited to comparing waveforms to an a priori collection of templates for detecting highly similar events in a swarm or seismic cluster. In the established template application, a detector functions in a manner analogous to waveform cross-correlation, applying a statistical test to assess the similarity of the incoming data stream to known templates for events of interest. In our approach, we seek not to detect matching signals, but instead, we examine the signal subspace dimensionality in much the same way that the method addresses node traffic anomalies in large computer systems. Signal anomalies recorded on seismic arrays affect the dimensional structure of the array-wide time-series. We have shown previously that this observation is useful in identifying real seismic events, either by looking at the raw signal or derivatives thereof (entropy, kurtosis), but here we explore the effects of malfunctioning channels on the dimension of the data and its derivatives, and how to leverage this effect for identifying bad array elements through a jackknifing process to isolate the anomalous channels, so that an automated analysis system might discard them prior to FK analysis and beamforming on events of interest.

Rowe, C. A.; Stead, R. J.; Begnaud, M. L.




SciTech Connect

We present an improved analysis of the final data set from the QUaD experiment. Using an improved technique to remove ground contamination, we double the effective sky area and hence increase the precision of our cosmic microwave background (CMB) power spectrum measurements by approx30% versus that previously reported. In addition, we have improved our modeling of the instrument beams and have reduced our absolute calibration uncertainty from 5% to 3.5% in temperature. The robustness of our results is confirmed through extensive jackknife tests, and by way of the agreement that we find between our two fully independent analysis pipelines. For the standard six-parameter LAMBDACDM model, the addition of QUaD data marginally improves the constraints on a number of cosmological parameters over those obtained from the WMAP experiment alone. The impact of QUaD data is significantly greater for a model extended to include either a running in the scalar spectral index, or a possible tensor component, or both. Adding both the QUaD data and the results from the Arcminute Cosmology Bolometer Array Receiver experiment, the uncertainty in the spectral index running is reduced by approx25% compared to WMAP alone, while the upper limit on the tensor-to-scalar ratio is reduced from r < 0.48 to r < 0.33 (95% c.l.). This is the strongest limit on tensors to date from the CMB alone. We also use our polarization measurements to place constraints on parity-violating interactions to the surface of last scattering, constraining the energy scale of Lorentz violating interactions to <1.5 x 10{sup -43} GeV (68% c.l.). Finally, we place a robust upper limit on the strength of the lensing B-mode signal. Assuming a single flat band power between l = 200 and l = 2000, we constrain the amplitude of B-modes to be <0.57 muK{sup 2} (95% c.l.).

Brown, M. L. [Cavendish Astrophysics, University of Cambridge, J. J. Thomson Avenue, Cambridge CB3 OHE (United Kingdom); Ade, P.; Bowden, M.; Gear, W. K.; Gupta, S.; Orlando, A. [School of Physics and Astronomy, Cardiff University, Queen's Buildings, The Parade, Cardiff CF24 3AA (United Kingdom); Bock, J.; Leitch, E. [Jet Propulsion Laboratory, 4800 Oak Grove Dr., Pasadena, CA 91109 (United States); Cahill, G.; Murphy, J. A. [Department of Experimental Physics, National University of Ireland Maynooth, Maynooth, Co. Kildare, Republic of Ireland (Ireland); Castro, P. G.; Memari, Y. [Institute for Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh EH9 3HJ (United Kingdom); Church, S.; Hinderks, J. [Kavli Institute for Particle Astrophysics and Cosmology and Department of Physics, Stanford University, 382 Via Pueblo Mall, Stanford, CA 94305 (United States); Culverhouse, T.; Friedman, R. B. [Kavli Institute for Cosmological Physics, Department of Astronomy and Astrophysics, Enrico Fermi Institute, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637 (United States); Ganga, K. [APC/Universite Paris 7-Denis Diderot/CNRS, Batiment Condorcet, 10, rue Alice Domon et Leonie Duquet, 75205 Paris Cedex 13 (France); Kovac, J.; Lange, A. E. [California Institute of Technology, Pasadena, CA 91125 (United States); Melhuish, S. J. [School of Physics and Astronomy, University of Manchester, Manchester M13 9PL (United Kingdom)



Atlantic Tropical Cyclone Monitoring with AMSU-A: Estimation of Maximum Sustained Wind Speeds  

NASA Technical Reports Server (NTRS)

The first Advanced Microwave Sounding Unit temperature sounder (AMSU-A) was launched on the NOAA-15 satellite on 13 May 1998. The AMSU-A's higher spatial and radiometric resolutions provide more useful information on the strength of the middle- and upper-tropospheric warm cores associated with tropical cyclones than have previous microwave temperature sounders. The gradient wind relationship suggests that the temperature gradient near the core of tropical cyclones increases nonlinearly with wind speed. The gradient wind equation is recast to include AMSU-A-derived variables, Stepwise regression is used to determine which of these variables is most closely related to maximum sustained winds (V(sub max)). The satellite variables investigated include the radially averaged gradients at two spatial resolutions of AMSU-A channels 1-10 T(sub b) data (delta(sub r)T(sub B)), the squares of these gradients, a channel-15-based scattering index (SI(sub 89)), and area-averaged T(sub B). Calculations of T(sub B) and delta(sub r)T(sub B) from mesoscale model simulations of Andrew reveal the effects of the AMSU spatial sampling on the cyclone warm core presentation. Stepwise regression of 66 AMSU-A terms against National Hurricane Center V(sub max) estimates from the 1998 and 1999 Atlantic hurricane season confirms the existence of a nonlinear relationship between wind speed and radially averaged temperature gradients near the cyclone warm core. Of six regression terms, four are dominated by temperature information, and two are interpreted as correcting for hydrometeor contamination. Jackknifed regressions were performed to estimate the algorithm performance on independent data. For the 82 cases that had in situ measurements of V(sub max), the average error standard deviation was 4.7 m/s. For 108 cases without in situ wind data, the average error standard deviation was 7.5 m/s Operational considerations, including the detection of weak cyclones and false alarm reduction, are also discussed.

Spencer, Roy W.; Braswell, William D.



Atlantic Tropical Cyclone Monitoring with AMSU-A: Estimation of Maximum Sustained Wind Speeds  

NASA Technical Reports Server (NTRS)

The first Advanced Microwave Sounding Unit temperature sounder (AMSU-A) was launched on the NOAA-15 satellite on 13 May 1998. The AMSU-A's higher spatial and radiometric resolutions provide more useful information on the strength of the middle and upper tropospheric warm cores associated with tropical cyclones than have previous microwave temperature sounders. The gradient wind relationship suggests that the temperature gradient near the core of tropical cyclones increases nonlinearly with wind speed. We recast the gradient wind equation to include AMSU-A derived variables. Stepwise regression is used to determine which of these variables is most closely related to maximum sustained winds (V(sub max)). The satellite variables investigated include the radially averaged gradients at two spatial resolutions of AMSU-A channels 1 through 10 T(sub b) data (delta(sub r)T(sub b)), the squares of these gradients, a channel 15 based scattering index (SI-89), and area averaged T(sub b). Calculations of Tb and delta(sub r)T(sub b) from mesoscale model simulations of Andrew reveal the effects of the AMSU spatial sampling on the cyclone warm core presentation. Stepwise regression of 66 AMSU-A terms against National Hurricane Center (NHC) V(sub max) estimates from the 1998 and 1999 Atlantic hurricane season confirms the existence of a nonlinear relationship between wind speed and radially averaged temperature gradients near the cyclone warm core. Of six regression terms, four are dominated by temperature information, and two are interpreted as correcting for hydrometeor contamination. Jackknifed regressions were performed to estimate the algorithm performance on independent data. For the 82 cases that had in situ measurements of V(sub max), the average error standard deviation was 4.7 m/s. For 108 cases without in situ wind data, the average error standard deviation was 7.5 m/s. Operational considerations, including the detection of weak cyclones and false alarm reduction are also discussed.

Spencer, Roy; Braswell, William D.; Goodman, H. Michael (Technical Monitor)



Detection of breast abnormalities using a prototype resonance electrical impedance spectroscopy system: A preliminary study  

PubMed Central

Electrical impedance spectroscopy has been investigated with but limited success as an adjunct procedure to mammography and as a possible pre-screening tool to stratify risk for having or developing breast cancer in younger women. In this study, the authors explored a new resonance frequency based [resonance electrical impedance spectroscopy (REIS)] approach to identify breasts that may have highly suspicious abnormalities that had been recommended for biopsies. The authors assembled a prototype REIS system generating multifrequency electrical sweeps ranging from 100 to 4100 kHz every 12 s. Using only two probes, one in contact with the nipple and the other with the outer breast skin surface 60 mm away, a paired transmission signal detection system is generated. The authors recruited 150 women between 30 and 50 years old to participate in this study. REIS measurements were performed on both breasts. Of these women 58 had been scheduled for a breast biopsy and 13 had been recalled for additional imaging procedures due to suspicious findings. The remaining 79 women had negative screening examinations. Eight REIS output signals at and around the resonance frequency were computed for each breast and the subtracted signals between the left and right breasts were used in a simple jackknifing method to select an optimal feature set to be inputted into a multi-feature based artificial neural network (ANN) that aims to predict whether a woman’s breast had been determined as abnormal (warranting a biopsy) or not. The classification performance was evaluated using a leave-one-case-out method and receiver operating characteristics (ROC) analysis. The study shows that REIS examination is easy to perform, short in duration, and acceptable to all participants in terms of comfort level and there is no indication of sensation of an electrical current during the measurements. Six REIS difference features were selected as input signals to the ANN. The area under the ROC curve (Az) was 0.707±0.033 for classifying between biopsy cases and non-biopsy (including recalled and screening negative) and the performance (Az) increased to 0.746±0.033 after excluding recalled but negative cases. At 95% specificity, the sensitivity levels were approximately 20.5% and 30.4% in the two data sets tested. The results suggest that differences in REIS signals between two breasts measured in and around the tissue resonance frequency can be used to identify at least some of the women with suspicious abnormalities warranting biopsy with high specificity. PMID:18697526

Zheng, Bin; Zuley, Margarita L.; Sumkin, Jules H.; Catullo, Victor J.; Abrams, Gordon S.; Rathfon, Grace Y.; Chough, Denise M.; Gruss, Michelle Z.; Gur, David



Growing Season Temperatures in Europe and Climate Forcings Over the Past 1400 Years  

PubMed Central

Background The lack of instrumental data before the mid-19th-century limits our understanding of present warming trends. In the absence of direct measurements, we used proxies that are natural or historical archives recording past climatic changes. A gridded reconstruction of spring-summer temperature was produced for Europe based on tree-rings, documentaries, pollen assemblages and ice cores. The majority of proxy series have an annual resolution. For a better inference of long-term climate variation, they were completed by low-resolution data (decadal or more), mostly on pollen and ice-core data. Methodology/Principal Findings An original spectral analog method was devised to deal with this heterogeneous dataset, and to preserve long-term variations and the variability of temperature series. So we can replace the recent climate changes in a broader context of the past 1400 years. This preservation is possible because the method is not based on a calibration (regression) but on similarities between assemblages of proxies. The reconstruction of the April-September temperatures was validated with a Jack-knife technique. It was also compared to other spatially gridded temperature reconstructions, literature data, and glacier advance and retreat curves. We also attempted to relate the spatial distribution of European temperature anomalies to known solar and volcanic forcings. Conclusions We found that our results were accurate back to 750. Cold periods prior to the 20th century can be explained partly by low solar activity and/or high volcanic activity. The Medieval Warm Period (MWP) could be correlated to higher solar activity. During the 20th century, however only anthropogenic forcing can explain the exceptionally high temperature rise. Warm periods of the Middle Age were spatially more heterogeneous than last decades, and then locally it could have been warmer. However, at the continental scale, the last decades were clearly warmer than any period of the last 1400 years. The heterogeneity of MWP versus the homogeneity of the last decades is likely an argument that different forcings could have operated. These results support the fact that we are living a climate change in Europe never seen in the past 1400 years. PMID:20376366

Guiot, Joel; Corona, Christophe



Computer-aided detection of clustered microcalcifications in multiscale bilateral filtering regularized reconstructed digital breast tomosynthesis volume  

SciTech Connect

Purpose: Develop a computer-aided detection (CADe) system for clustered microcalcifications in digital breast tomosynthesis (DBT) volume enhanced with multiscale bilateral filtering (MSBF) regularization. Methods: With Institutional Review Board approval and written informed consent, two-view DBT of 154 breasts, of which 116 had biopsy-proven microcalcification (MC) clusters and 38 were free of MCs, was imaged with a General Electric GEN2 prototype DBT system. The DBT volumes were reconstructed with MSBF-regularized simultaneous algebraic reconstruction technique (SART) that was designed to enhance MCs and reduce background noise while preserving the quality of other tissue structures. The contrast-to-noise ratio (CNR) of MCs was further improved with enhancement-modulated calcification response (EMCR) preprocessing, which combined multiscale Hessian response to enhance MCs by shape and bandpass filtering to remove the low-frequency structured background. MC candidates were then located in the EMCR volume using iterative thresholding and segmented by adaptive region growing. Two sets of potential MC objects, cluster centroid objects and MC seed objects, were generated and the CNR of each object was calculated. The number of candidates in each set was controlled based on the breast volume. Dynamic clustering around the centroid objects grouped the MC candidates to form clusters. Adaptive criteria were designed to reduce false positive (FP) clusters based on the size, CNR values and the number of MCs in the cluster, cluster shape, and cluster based maximum intensity projection. Free-response receiver operating characteristic (FROC) and jackknife alternative FROC (JAFROC) analyses were used to assess the performance and compare with that of a previous study. Results: Unpaired two-tailedt-test showed a significant increase (p < 0.0001) in the ratio of CNRs for MCs with and without MSBF regularization compared to similar ratios for FPs. For view-based detection, a sensitivity of 85% was achieved at an FP rate of 2.16 per DBT volume. For case-based detection, a sensitivity of 85% was achieved at an FP rate of 0.85 per DBT volume. JAFROC analysis showed a significant improvement in the performance of the current CADe system compared to that of our previous system (p = 0.003). Conclusions: MBSF regularized SART reconstruction enhances MCs. The enhancement in the signals, in combination with properly designed adaptive threshold criteria, effective MC feature analysis, and false positive reduction techniques, leads to a significant improvement in the detection of clustered MCs in DBT.

Samala, Ravi K., E-mail:; Chan, Heang-Ping; Lu, Yao; Hadjiiski, Lubomir; Wei, Jun; Helvie, Mark A. [Department of Radiology, University of Michigan, Ann Arbor, Michigan 48109-5842 (United States)] [Department of Radiology, University of Michigan, Ann Arbor, Michigan 48109-5842 (United States); Sahiner, Berkman [Center for Devices and Radiological Health, U.S. Food and Drug Administration, Maryland 20993 (United States)] [Center for Devices and Radiological Health, U.S. Food and Drug Administration, Maryland 20993 (United States)



Spatial downscaling and mapping of daily precipitation and air temperature using daily station data and monthly mean maps  

NASA Astrophysics Data System (ADS)

Accurate maps of daily weather variables are an essential component of hydrologic and ecologic modeling. Here we present a four-step method that uses daily station data and transient monthly maps of precipitation and air temperature. This method uses the monthly maps to help interpolate between stations for more accurate production of daily maps at any spatial resolution. The first step analyzes the quality of the each station's data using a discrepancy analysis that compares statistics derived from a statistical jack-knifing approach with a time-series evaluation of discrepancies generated for each station. Although several methods could be used for the second step of producing initial maps, such as kriging, splines, etc., we used a gradient plus inverse distance squared method that was developed to produce accurate climate maps for sparse data regions with widely separated and few climate stations, far fewer than would be needed for techniques such as kriging. The gradient plus inverse distance squared method uses local gradients in the climate parameters, easting, northing, and elevation, to adjust the inverse distance squared estimates for local gradients such as lapse rates, inversions, or rain shadows at scales of 10's of meters to kilometers. The third step is to downscale World Wide Web (web) based transient monthly data, such as Precipitation-Elevation Regression on Independent Slope Method (PRISM) for the US (4 km or 800 m maps) or Climate Research Unit (CRU 3.1) data sets (40 km for global applications) to the scale of the daily data's digital elevation model. In the final step the downscaled transient monthly maps are used to adjust the daily time-series mapped data (~30 maps/month) for each month. These adjustments are used to scale daily maps so that summing them for precipitation or averaging them for temperature would more accurately reproduce the variability in selected monthly maps. This method allows for individual days to have maxima or minima values away from the station locations based on the underlying geographic structure of the monthly maps. We compare our results with the web based 12 km Variable Infiltration Capacity model (VIC) daily data and the 1 km DayMet daily data as well as make comparisons of the month summation or average of daily data sets with the PRISM and CRU data sets. There were mixed results in the comparisons with some good agreement and some bad agreement, even between VIC and DayMet. These daily maps are intended to be used as input to daily hydrological models. The results will provide more insight into the significance of the differences, at least from a hydrology perspective.

Flint, A. L.; Flint, L. E.; Stern, M. A.



Modelling and mapping the local distribution of representative species on the Le Danois Bank, El Cachucho Marine Protected Area (Cantabrian Sea)  

NASA Astrophysics Data System (ADS)

The management and protection of potentially vulnerable species and habitats require the availability of detailed spatial data. However, such data are often not readily available in particular areas that are challenging for sampling by traditional sampling techniques, for example seamounts. Within this study habitat modelling techniques were used to create predictive maps of six species of conservation concern for the Le Danois Bank (El Cachucho Marine Protected Area in the South of the Bay of Biscay). The study used data from ECOMARG multidisciplinary surveys that aimed to create a representative picture of the physical and biological composition of the area. Classical fishing gear (otter trawl and beam trawl) was used to sample benthic communities that inhabit sedimentary areas, and non-destructive visual sampling techniques (ROV and photogrammetric sled) were used to determine the presence of epibenthic macrofauna in complex and vulnerable habitats. Multibeam echosounder data, high-resolution seismic profiles (TOPAS system) and geological data from box-corer were used to characterize the benthic terrain. ArcGIS software was used to produce high-resolution maps (75×75 m2) of such variables in the entire area. The Maximum Entropy (MAXENT) technique was used to process these data and create Habitat Suitability maps for six species of special conservation interest. The model used seven environmental variables (depth, rugosity, aspect, slope, Bathymetric Position Index (BPI) in fine and broad scale and morphosedimentary characteristics) to identify the most suitable habitats for such species and indicates which environmental factors determine their distribution. The six species models performed highly significantly better than random (p<0.0001; Mann-Whitney test) when Area Under the Curve (AUC) values were tested. This indicates that the environmental variables chosen are relevant to distinguish the distribution of these species. The Jackknife test estimated depth to be the key factor structuring their distribution, followed by the seabed morpho-sedimentary characteristics and rugosity variables. Three of the species studied (Asconema setubalense, Callogorgia verticillata and Helicolenus dactylopterus) were found to have small suitable areas as a result of being restrictive species related to the environmental characteristics of the top of the bank. The other species (Pheronema carpenteri, Phycis blennoides and Trachyscorpia cristulata), which were species less restrictive to the environmental variables used, had highly suitable areas of distribution. The study provides high-resolution maps of species that characterize the habitat of two communities included in OSPAR and NATURA networks, whose distributions corroborate the adequate protection of this area by the management measures applied at present.

García-Alegre, Ana; Sánchez, Francisco; Gómez-Ballesteros, María; Hinz, Hilmar; Serrano, Alberto; Parra, Santiago




SciTech Connect

We present deep radio observations of four nearby dwarf spheroidal (dSph) galaxies, designed to detect extended synchrotron emission resulting from weakly interacting massive particle (WIMP) dark matter annihilations in their halos. Models by Colafrancesco et al. (CPU07) predict the existence of angularly large, smoothly distributed radio halos in such systems, which stem from electron and positron annihilation products spiraling in a turbulent magnetic field. We map a total of 40.5 deg{sup 2} around the Draco, Ursa Major II, Coma Berenices, and Willman 1 dSphs with the Green Bank Telescope (GBT) at 1.4 GHz to detect this annihilation signature, greatly reducing discrete-source confusion using the NVSS catalog. We achieve a sensitivity of {sigma}{sub sub} {approx}< 7 mJy beam{sup -1} in our discrete source-subtracted maps, implying that the NVSS is highly effective at removing background sources from GBT maps. For Draco we obtained approximately concurrent Very Large Array observations to quantify the variability of the discrete source background, and find it to have a negligible effect on our results. We construct radial surface brightness profiles from each of the subtracted maps, and jackknife the data to quantify the significance of the features therein. At the {approx}10' resolution of our observations, foregrounds contribute a standard deviation of 1.8 mJy beam{sup -1} {<=} {sigma}{sub ast} {<=} 5.7 mJy beam{sup -1} to our high-latitude maps, with the emission in Draco and Coma dominated by foregrounds. On the other hand, we find no significant emission in the Ursa Major II and Willman 1 fields, and explore the implications of non-detections in these fields for particle dark matter using the fiducial models of CPU07. For a WIMP mass M{sub {chi}} = 100 GeV annihilating into b b-bar final states and B = 1 {mu}G, upper limits on the annihilation cross-section for Ursa Major II and Willman I are log (({sigma}v){sub {chi}}, cm{sup 3} s{sup -1}) {approx}< -25 for the preferred set of charged particle propagation parameters adopted by CPU07; this is comparable to that inferred at {gamma}-ray energies from the two-year Fermi Large Area Telescope data. We discuss three avenues for improving the constraints on ({sigma}v){sub {chi}} presented here, and conclude that deep radio observations of dSphs are highly complementary to indirect WIMP searches at higher energies.

Spekkens, Kristine [Department of Physics, Royal Military College of Canada, P.O. Box 17000, Station Forces, Kingston, Ontario K7K 7B4 (Canada); Mason, Brian S. [National Radio Astronomy Observatory, 520 Edgemont Road, Charlottesville, VA 22903-2475 (United States); Aguirre, James E. [Department of Physics and Astronomy, University of Pennsylvania, 209 South 33rd Street, Philadelphia, PA 19104 (United States); Nhan, Bang, E-mail: [Department of Astrophysical and Planetary Sciences, University of Colorado, 391 UCB, Boulder, CO 80309 (United States)



Climatic Determinants and Statistical Prediction of Tropical Cyclone Days in the Southwest Indian Ocean.  

NASA Astrophysics Data System (ADS)

Climatic determinants of tropical cyclone (TC) days in the southwest Indian Ocean area (10°-25°S, 50°-70°E) are analyzed using statistical techniques. A TC days index is formulated from records of local meteorological services over the December-March season in the period 1961-91. The index is correlated with gridded fields of sea surface temperature (SST), outgoing longwave radiation (OLR), and tropospheric winds, using monthly standardized departures at various lags.SST relationships with TC days are positive over the entire southwest Indian Ocean from 4 to +2 months, as expected. Peak correlations of >+0.5 occur in the genesis region 0°-10°S, 50°-60°E to the northeast of Madagascar at lag 4 (September). The synoptic-scale response of monsoon convection is approximated by OLR correlations. Negative correlations (associated with increased convection) are found to the northeast of Madagascar at lag 4 and 0 months. At lags 4 and 2 (November) opposing positive OLR correlations are found over Africa, suggesting a convective sink region during the spring season transition.Wind correlation vectors at the 200-hPa level indicate the persistence of an anticyclonic gyre centered near 35°S, 70°E in the south Indian Ocean and upper easterly flow in the equatorial zone. Surface northwesterly flow is a prominent feature in the central Indian Ocean (Diego Garcia), while strengthened midlatitude westerlies are found at lag 4 (September). In November surface northwesterly flow anomalies dominate the entire tropical zone with respect to summers with increased TC days. At lag 0 and to a lesser extent +2 months, a distinct cyclonic anomaly is centered on 20°S, 55°E with enhanced monsoon westerlies to the north.The correlation patterns offer statistical guidance in long-range forecasts and insights to the climatic processes involved in the interannual variability of TC days in the southwest Indian Ocean. Using predictors selected from present analysis, a linear multivariate model is constructed. The model has three predictors from the preceding July to November period and accounts for 59% of the variance over the 1971-92 period. The model performs adequately, achieving a jackknife correlation of 70% and a Heidke tercile score of 52.5%. A conceptual framework is used to highlight relationships between the predictors, the Indian monsoon, and tropical cyclogenesis.

Jury, Mark R.; Pathack, Beenay; Parker, Bhawoodien



School-age effects of the newborn individualized developmental care and assessment program for preterm infants with intrauterine growth restriction: preliminary findings  

PubMed Central

Background The experience in the newborn intensive care nursery results in premature infants’ neurobehavioral and neurophysiological dysfunction and poorer brain structure. Preterms with severe intrauterine growth restriction are doubly jeopardized given their compromised brains. The Newborn Individualized Developmental Care and Assessment Program improved outcome at early school-age for preterms with appropriate intrauterine growth. It also showed effectiveness to nine months for preterms with intrauterine growth restriction. The current study tested effectiveness into school-age for preterms with intrauterine growth restriction regarding executive function (EF), electrophysiology (EEG) and neurostructure (MRI). Methods Twenty-three 9-year-old former growth-restricted preterms, randomized at birth to standard care (14 controls) or to the Newborn Individualized Developmental Care and Assessment Program (9 experimentals) were assessed with standardized measures of cognition, achievement, executive function, electroencephalography, and magnetic resonance imaging. The participating children were comparable to those lost to follow-up, and the controls to the experimentals, in terms of newborn background health and demographics. All outcome measures were corrected for mother’s intelligence. Analysis techniques included two-group analysis of variance and stepwise discriminate analysis for the outcome measures, Wilks’ lambda and jackknifed classification to ascertain two-group classification success per and across domains; canonical correlation analysis to explore relationships among neuropsychological, electrophysiological and neurostructural domains at school-age, and from the newborn period to school-age. Results Controls and experimentals were comparable in age at testing, anthropometric and health parameters, and in cognitive and achievement scores. Experimentals scored better in executive function, spectral coherence, and cerebellar volumes. Furthermore, executive function, spectral coherence and brain structural measures discriminated controls from experimentals. Executive function correlated with coherence and brain structure measures, and with newborn-period neurobehavioral assessment. Conclusion The intervention in the intensive care nursery improved executive function as well as spectral coherence between occipital and frontal as well as parietal regions. The experimentals’ cerebella were significantly larger than the controls’. These results, while preliminary, point to the possibility of long-term brain improvement even of intrauterine growth compromised preterms if individualized intervention begins with admission to the NICU and extends throughout transition home. Larger sample replications are required in order to confirm these results. Clinical trial registration The study is registered as a clinical trial. The trial registration number is NCT00914108. PMID:23421857



A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study  

PubMed Central

Background The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact. Methods Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls. Results Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences for the ASD-groups, when compared to the controls. Average spectral loading per factor was wide (10.1 Hz). Conclusions Classification success suggests a stable coherence loading pattern that differentiates ASD- from C-group subjects. This might constitute an EEG coherence-based phenotype of childhood autism. The predominantly reduced short-distance coherences may indicate poor local network function. The increased long-distance coherences may represent compensatory processes or reduced neural pruning. The wide average spectral range of factor loadings may suggest over-damped neural networks. PMID:22730909



One year survival of ART and conventional restorations in patients with disability  

PubMed Central

Background Providing restorative treatment for persons with disability may be challenging and has been related to the patient’s ability to cope with the anxiety engendered by treatment and to cooperate fully with the demands of the clinical situation. The aim of the present study was to assess the survival rate of ART restorations compared to conventional restorations in people with disability referred for special care dentistry. Methods Three treatment protocols were distinguished: ART (hand instruments/high-viscosity glass-ionomer); conventional restorative treatment (rotary instrumentation/resin composite) in the clinic (CRT/clinic) and under general anaesthesia (CRT/GA). Patients were referred for restorative care to a special care centre and treated by one of two specialists. Patients and/or their caregivers were provided with written and verbal information regarding the proposed techniques, and selected the type of treatment they were to receive. Treatment was provided as selected but if this option proved clinically unfeasible one of the alternative techniques was subsequently proposed. Evaluation of restoration survival was performed by two independent trained and calibrated examiners using established ART restoration assessment codes at 6 months and 12 months. The Proportional Hazard model with frailty corrections was applied to calculate survival estimates over a one year period. Results 66 patients (13.6?±?7.8 years) with 16 different medical disorders participated. CRT/clinic proved feasible for 5 patients (7.5%), the ART approach for 47 patients (71.2%), and 14 patients received CRT/GA (21.2%). In all, 298 dentine carious lesions were restored in primary and permanent teeth, 182 (ART), 21 (CRT/clinic) and 95 (CRT/GA). The 1-year survival rates and jackknife standard error of ART and CRT restorations were 97.8?±?1.0% and 90.5?±?3.2%, respectively (p?=?0.01). Conclusions These short-term results indicate that ART appears to be an effective treatment protocol for treating patients with disability restoratively, many of whom have difficulty coping with the conventional restorative treatment. Trial registration number Netherlands Trial Registration: NTR 4400 PMID:24885938



A Perspective on Simulations of Environmental Systems and Prediction Uncertainty  

NASA Astrophysics Data System (ADS)

Prediction uncertainty is the likely discrepancy between model predictions and the actual, unrealized system responses. Contributions to uncertainty include anything that causes inaccurate predictions. This can include numerical model solution error and capability limitation, data error and deficiency, and conceptual model error. For example, using conceptual models to build simulations forces ideas about system behavior that are often vague and(or) wrong to be tested against measurements. Closer correspondence between the simulation and measurements often indicates the model more accurately represents a system. However, when models are calibrated, predictive capability can be degraded by fitting measurements too closely. This can occur when the model is overparameterized and close model fit is achieved by fitting measurement and other errors. The connection between such errors and prediction accuracy is clear, and thorough evaluation of such errors and the possibility of overfitting are critical. This is especially true for stochastic and Bayesian methods applied to models with many parameters, for which overfitting is controlled using prior information and smoothness constraints that may not be well understood by the modeler. When a reasonably accurate simulation of a system has been achieved through careful model development, calibration, and error evaluation, the simulation itself becomes an invaluable tool for sensitivity analysis, data assessment, and uncertainty evaluation. Three categories of sensitivity and data assessment methods include techniques for identifying (1) the importance of observations important to parameter values (observations that dominate model calibration); (2) parameter values that dominate the predictions; and (3) observations that dominate the predictions. For instance, gradient-based methods such as composite scaled sensitivities, prediction scaled sensitivities and the value of improved information, and the observation-prediction statistic are used to address the three categories, respectively. These local-sensitivity methods assume model linearity, but have found to be useful for nonlinear ground-water models. More computationally intensive methods that do not assume model linearity include variance-based global sensitivity analysis methods for identifying parameters important to predictions, and jackknife and bootstrap methods for identifying observations that dominate predictions. Uncertainty evaluation methods can be categorized as gradient, selective sampling, and random sampling methods. Gradient methods include linear and nonlinear confidence intervals, and are limited to propagating uncertainties related to parameter values. Selective sampling often involves establishing a most probable and one or more worst-case scenarios. Random sampling includes Monte Carlo methods such as Latin-Hypercube sampling, and can produce results similar to nonlinear confidence intervals if only parameter values are sampled and if simulations with poor model fit are omitted. Model development and evaluation are obviously complex endeavors involving a number of steps. To make wise societal decisions based on environmental model predictions, it is important to establish solid methods for evaluating the importance of observations and parameters to predictions and for quantifying prediction uncertainty.

Hill, M. C.; Tiedeman, C. R.



Comparison of soft computing systems for the post-calibration of weather radar  

NASA Astrophysics Data System (ADS)

The most usual tools to monitor rainfall events are raingauges and weather radar. Networks of raingauges provide accurate point estimates of rainfall, when appropriately set, but their usual low density restricts considerably the spatial resolution of the gathered information. Such networks, with rain gauges at distinct points, do not reflect the spatial distribution of rainfall. The quality of raingauge observations is also susceptible to some error sources, for example wind effects around the raingauges and poor raingauge reports due to hardware problems. Radar systems offer high spatial and temporal resolution observation which is much more efficient at providing the space-time evolution of a rainfall event in comparison with raingauge networks. However the radar measurements are not free of errors due to a variety of factors including ground clutter, bright bands, anomalous propagation, beam blockages, and attenuation. The effectiveness of weather radar operation is strongly linked to rigorous calibration. Various methods have been proposed to calibrate radar data. They can be classified into two main categories: deterministic and statistical. The deterministic approach involves the calibration of radar rainfall estimations against raingauge observations. The statistical approach includes multivariate analysis and cokriging. Geostatistical approaches are known as the best methods for radar-raingauge data integration but they are usually inefficient in real time, especially when dealing with the sampling rates of one hour or less necessary for urban and small watershed applications. Such methods also rely on a strong human expertise which can lead to user-dependent results. The objectives of this research are to introduce and to investigate the feasibility of soft computing systems for the post-calibration of weather radar in comparison with the best existing method based on geostatistics. In this work, the soft computing systems include artificial neural networks and Adaptive Neuro-Fuzzy Inference System (ANFIS) and the geostatistical approach includes residual kriging. The residual kriging calibration results are satisfying however this method is based on stationary hypotheses and requires variogram modeling, making it difficult in an operational context. This method has the advantage of providing a mean squared errors map based on variogram modeling for the estimations. For the artificial neural network, thirteen variants of the multilayer feedforward networks and two variants of radial basis functions are tested in this work. The neural calibration results showed that the Levenberg-Marquardt algorithm using Bayesian regularization is robust and reliable for radar-raingauge data integration. The ANFIS offers the precision and learning capability of artificial neural networks combined with the advantages of fuzzy logic. This method based on the Jackknife approach allows the use of all the available data for training and checking the neuro-fuzzy inference system, and provides a degree of reliability of the post-calibration. The training and the interpolation results of proposed methods can be obtained within just a few seconds using an ordinary personal computer, which is incomparably faster than geostatistical approaches. The proposed algorithms would be very efficient for real time post-calibration.

Hessami Kermani, Masoud Reza


Azimuthal anisotropy beneath southern Africa from very broad-band surface-wave dispersion measurements  

NASA Astrophysics Data System (ADS)

Seismic anisotropy within the lithosphere of cratons preserves an important record of their ancient assembly. In southern Africa, anisotropy across the Archean Kaapvaal Craton and Limpopo Belt has been detected previously by observations of SKS-wave splitting. Because SKS-splitting measurements lack vertical resolution, however, the depth distribution of anisotropy has remained uncertain. End-member interpretations invoked the dominance of either anisotropy in the lithosphere (due to the fabric formed by deformation in Archean or Palaeoproterozoic orogenies) or that in the asthenosphere (due to the fabric formed by the recent plate motion), each with significant geodynamic implications. To determine the distribution of anisotropy with depth, we measured phase velocities of seismic surface waves between stations of the Southern African Seismic Experiment. We applied two complementary measurement approaches, very broad-band cross-correlation and multimode waveform inversion. Robust, Rayleigh- and Love-wave dispersion curves were derived for four different subregions of the Archean southern Africa in a period range from 5 s to 250-400 s (Rayleigh) and 5 s to 100-250 s (Love), depending on the region. Rayleigh-wave anisotropy was determined in each region at periods from 5 s to 150-200 s, sampling from the upper crust down to the asthenosphere. The jackknife method was used to estimate uncertainties, and the F-test to verify the statistical significance of anisotropy. We detected strong anisotropy with a N-S fast-propagation azimuth in the upper crust of the Limpopo Belt. We attribute it to aligned cracks, formed by the regional, E-W extensional stress associated with the southward propagation of the East African Rift. Our results show that it is possible to estimate regional stress from short-period, surface wave anisotropy, measured in this study using broad-band array recordings of teleseismic surface waves. Rayleigh-wave anisotropy at 70-120 s periods shows that the fabric within the deep mantle lithosphere of the Limpopo Belt and northern Kaapvaal Craton is aligned parallel to the Archean-Palaeoproterozoic sutures at block boundaries. This confirms that the fabric within the lithosphere created by pervasive ancient deformation is preserved to this day. Suture-parallel fabric is absent, however, in the deep lithosphere of the western Kaapvaal Craton, suggesting that it was not reworked in the collision with the craton's core, either due to its mechanical strength or because the deformation mechanism was different from those that operated in the north. Anisotropy at periods greater than 120-130 s shows fast directions parallel to the plate motion and indicates shear wave anisotropy in the asthenosphere. The depth distribution of anisotropy revealed by surface wave measurements comprises elements of both end-member models proposed previously: anisotropy in the asthenosphere shows fast-propagation directions parallel to the plate motion; anisotropy in the Limpopo and northern Kaapvaal lithosphere shows fast directions parallel to the Archean-Palaeoproterozoic sutures. The distribution of SKS-splitting orientations across southern Africa reflects anisotropic fabric both within the lithosphere (dominating the splitting beneath the Limpopo Belt and northern Kaapvaal Craton) and within the asthenosphere (dominating beneath the western Kaapvaal Craton).

Adam, Joanne M.-C.; Lebedev, Sergei