Two Paradoxes in Linear Regression Analysis.

PubMed

Feng, Ge; Peng, Jing; Tu, Dongke; Zheng, Julia Z; Feng, Changyong

2016-12-25

Regression is one of the favorite tools in applied statistics. However, misuse and misinterpretation of results from regression analysis are common in biomedical research. In this paper we use statistical theory and simulation studies to clarify some paradoxes around this popular statistical method. In particular, we show that a widely used model selection procedure employed in many publications in top medical journals is wrong. Formal procedures based on solid statistical theory should be used in model selection.

[Recent advances of anastomosis techniques of esophagojejunostomy after laparoscopic totally gastrectomy in gastric tumor].

PubMed

Li, Xi; Ke, Chongwei

2015-05-01

The esophageal jejunum anastomosis of the digestive tract reconstruction techniques in laparoscopic total gastrectomy includes two categories: circular stapler anastomosis techniques and linear stapler anastomosis techniques. Circular stapler anastomosis techniques include manual anastomosis method, purse string instrument method, Hiki improved special anvil anastomosis technique, the transorally inserted anvil(OrVil(TM)) and reverse puncture device technique. Linear stapler anastomosis techniques include side to side anastomosis technique and Overlap side to side anastomosis technique. Esophageal jejunum anastomosis technique has a wide selection of different technologies with different strengths and the corresponding limitations. This article will introduce research progress of laparoscopic total gastrectomy esophagus jejunum anastomosis from both sides of the development of anastomosis technology and the selection of anastomosis technology.

Two Paradoxes in Linear Regression Analysis

PubMed Central

FENG, Ge; PENG, Jing; TU, Dongke; ZHENG, Julia Z.; FENG, Changyong

2016-01-01

Summary Regression is one of the favorite tools in applied statistics. However, misuse and misinterpretation of results from regression analysis are common in biomedical research. In this paper we use statistical theory and simulation studies to clarify some paradoxes around this popular statistical method. In particular, we show that a widely used model selection procedure employed in many publications in top medical journals is wrong. Formal procedures based on solid statistical theory should be used in model selection. PMID:28638214

Sexual selection on cuticular hydrocarbons in the Australian field cricket, Teleogryllus oceanicus

PubMed Central

Thomas, Melissa L; Simmons, Leigh W

2009-01-01

Background Females in a wide range of taxa have been shown to base their choice of mates on pheromone signals. However, little research has focussed specifically on the form and intensity of selection that mate choice imposes on the pheromone signal. Using multivariate selection analysis, we characterise directly the form and intensity of sexual selection acting on cuticular hydrocarbons, chemical compounds widely used in the selection of mates in insects. Using the Australian field cricket Teleogryllus oceanicus as a model organism, we use three measures of male attractiveness to estimate fitness; mating success, the duration of courtship required to elicit copulation, and subsequent spermatophore attachment duration. Results We found that all three measures of male attractiveness generated sexual selection on male cuticular hydrocarbons, however there were differences in the form and intensity of selection among these three measures. Mating success was the only measure of attractiveness that imposed both univariate linear and quadratic selection on cuticular hydrocarbons. Although we found that all three attractiveness measures generated nonlinear selection, again only mating success was found to exert statistically significant stabilizing selection. Conclusion This study shows that sexual selection plays an important role in the evolution of male cuticular hydrocarbon signals. PMID:19594896

Bayesian whole-genome prediction and genome-wide association analysis with missing genotypes using variable selection

USDA-ARS?s Scientific Manuscript database

Single-step Genomic Best Linear Unbiased Predictor (ssGBLUP) has become increasingly popular for whole-genome prediction (WGP) modeling as it utilizes any available pedigree and phenotypes on both genotyped and non-genotyped individuals. The WGP accuracy of ssGBLUP has been demonstrated to be greate...

Perylene Diimide Based Fluorescent Dyes for Selective Sensing of Nitroaromatic Compounds: Selective Sensing in Aqueous Medium Across Wide pH Range.

PubMed

Hariharan, P S; Pitchaimani, J; Madhu, Vedichi; Anthony, Savarimuthu Philip

2016-03-01

Water soluble perylenediimide based fluorophore salt, N,N'-bis(ethelenetrimethyl ammoniumiodide)-perylene-3,4,9,10-tetracarboxylicbisimide (PDI-1), has been used for selective fluorescence sensing of picric acid (PA) and 4-nitroaniline (4-NA) in organic as well as aqueous medium across wide pH range (1.0 to 10.0). PDI-1 showed strong fluorescence in dimethylformamide (DMF) (Φf = 0.26 (DMF) and moderate fluorescence in water. Addition of picric acid (PA) and 4-nitroaniline (4-NA) into PDI-1 in DMF/aqueous solution selectively quenches the fluorescence. The concentration dependent studies showed decrease of fluorescence linearly with increase of PA and 4-NA concentration. The interference studies demonstrate high selectivity for PA and 4-NA. Interestingly, PDI-1 showed selective fluorescence sensing of PA and 4-NA across wide pH range (1.0 to 10.0). Selective fluorescence sensing of PA and 4-NA has also been observed with trifluoroacetate (PDI-2), sulfate (PDI-3) salt of PDI-1 as well as octyl chain substituted PDI (PDI-4) without amine functionality. These studies suggest that PA and 4-NA might be having preferential interaction with PDI aromatic core and quenches the fluorescence. Thus PDI based dyes have been used for selective fluorescent sensing of explosive NACs for the first time to the best our knowledge.

Development and Validation of High-performance Thin Layer Chromatographic Method for Ursolic Acid in Malus domestica Peel

PubMed Central

Nikam, P. H.; Kareparamban, J. A.; Jadhav, A. P.; Kadam, V. J.

2013-01-01

Ursolic acid, a pentacyclic triterpenoid possess a wide range of pharmacological activities. It shows hypoglycemic, antiandrogenic, antibacterial, antiinflammatory, antioxidant, diuretic and cynogenic activity. It is commonly present in plants especially coating of leaves and fruits, such as apple fruit, vinca leaves, rosemary leaves, and eucalyptus leaves. A simple high-performance thin layer chromatographic method has been developed for the quantification of ursolic acid from apple peel (Malus domestica). The samples dissolved in methanol and linear ascending development was carried out in twin trough glass chamber. The mobile phase was selected as toluene:ethyl acetate:glacial acetic acid (70:30:2). The linear regression analysis data for the calibration plots showed good linear relationship with r2=0.9982 in the concentration range 0.2-7 μg/spot with respect to peak area. According to the ICH guidelines the method was validated for linearity, accuracy, precision, and robustness. Statistical analysis of the data showed that the method is reproducible and selective for the estimation of ursolic acid. PMID:24302805

Comparison of linear and non-linear models for the adsorption of fluoride onto geo-material: limonite.

PubMed

Sahin, Rubina; Tapadia, Kavita

2015-01-01

The three widely used isotherms Langmuir, Freundlich and Temkin were examined in an experiment using fluoride (F⁻) ion adsorption on a geo-material (limonite) at four different temperatures by linear and non-linear models. Comparison of linear and non-linear regression models were given in selecting the optimum isotherm for the experimental results. The coefficient of determination, r², was used to select the best theoretical isotherm. The four Langmuir linear equations (1, 2, 3, and 4) are discussed. Langmuir isotherm parameters obtained from the four Langmuir linear equations using the linear model differed but they were the same when using the nonlinear model. Langmuir-2 isotherm is one of the linear forms, and it had the highest coefficient of determination (r² = 0.99) compared to the other Langmuir linear equations (1, 3 and 4) in linear form, whereas, for non-linear, Langmuir-4 fitted best among all the isotherms because it had the highest coefficient of determination (r² = 0.99). The results showed that the non-linear model may be a better way to obtain the parameters. In the present work, the thermodynamic parameters show that the absorption of fluoride onto limonite is both spontaneous (ΔG < 0) and endothermic (ΔH > 0). Scanning electron microscope and X-ray diffraction images also confirm the adsorption of F⁻ ion onto limonite. The isotherm and kinetic study reveals that limonite can be used as an adsorbent for fluoride removal. In future we can develop new technology for fluoride removal in large scale by using limonite which is cost-effective, eco-friendly and is easily available in the study area.

A linear-to-circular polarization converter based on a second-order band-pass frequency selective surface

NASA Astrophysics Data System (ADS)

Lin, Baoqin; Wu, Jia-liang; Da, Xin-yu; Li, Wei; Ma, Jia-jun

2017-01-01

In this work, we propose a linear-to-circular transmission polarization converter based on a second-order band-pass frequency selective surface (FSS). The FSS is composed of a three-layer aperture-coupled-patch structure, it can be interpreted as an array of antenna-filter-antenna modules, wherein the antenna is just a circularly polarized corner-truncated square microstrip antenna. A prototype of the proposed polarization converter is analyzed, fabricated and tested. Both simulation and experimental results show that the 3-dB axial ratio relative bandwidth of the polarization converter is over 30%, and the maximum insertion loss is only 1.87 dB; in addition, it can maintain good performance over a wide angular bandwidth at TE incidence.

GENERAL EARTHQUAKE-OBSERVATION SYSTEM (GEOS).

USGS Publications Warehouse

Borcherdt, R.D.; Fletcher, Joe B.; Jensen, E.G.; Maxwell, G.L.; VanSchaack, J.R.; Warrick, R.E.; Cranswick, E.; Johnston, M.J.S.; McClearn, R.

1985-01-01

Microprocessor technology has permitted the development of a General Earthquake-Observation System (GEOS) useful for most seismic applications. Central-processing-unit control via robust software of system functions that are isolated on hardware modules permits field adaptability of the system to a wide variety of active and passive seismic experiments and straightforward modification for incorporation of improvements in technology. Various laboratory tests and numerous deployments of a set of the systems in the field have confirmed design goals, including: wide linear dynamic range (16 bit/96 dB); broad bandwidth (36 hr to 600 Hz; greater than 36 hr available); selectable sensor-type (accelerometer, seismometer, dilatometer); selectable channels (1 to 6); selectable record mode (continuous, preset, trigger); large data capacity (1. 4 to 60 Mbytes); selectable time standard (WWVB, master, manual); automatic self-calibration; simple field operation; full capability to adapt system in the field to a wide variety of experiments; low power; portability; and modest costs. System design goals for a microcomputer-controlled system with modular software and hardware components as implemented on the GEOS are presented. The systems have been deployed for 15 experiments, including: studies of near-source strong motion; high-frequency microearthquakes; crustal structure; down-hole wave propagation; teleseismicity; and earth-tidal strains.

Use of Longitudinal Data in Genetic Studies in the Genome-wide Association Studies Era: Summary of Group 14

PubMed Central

Kerner, Berit; North, Kari E; Fallin, M Daniele

2010-01-01

Participants analyzed actual and simulated longitudinal data from the Framingham Heart Study for various metabolic and cardiovascular traits. The genetic information incorporated into these investigations ranged from selected single-nucleotide polymorphisms to genome-wide association arrays. Genotypes were incorporated using a broad range of methodological approaches including conditional logistic regression, linear mixed models, generalized estimating equations, linear growth curve estimation, growth modeling, growth mixture modeling, population attributable risk fraction based on survival functions under the proportional hazards models, and multivariate adaptive splines for the analysis of longitudinal data. The specific scientific questions addressed by these different approaches also varied, ranging from a more precise definition of the phenotype, bias reduction in control selection, estimation of effect sizes and genotype associated risk, to direct incorporation of genetic data into longitudinal modeling approaches and the exploration of population heterogeneity with regard to longitudinal trajectories. The group reached several overall conclusions: 1) The additional information provided by longitudinal data may be useful in genetic analyses. 2) The precision of the phenotype definition as well as control selection in nested designs may be improved, especially if traits demonstrate a trend over time or have strong age-of-onset effects. 3) Analyzing genetic data stratified for high-risk subgroups defined by a unique development over time could be useful for the detection of rare mutations in common multi-factorial diseases. 4) Estimation of the population impact of genomic risk variants could be more precise. The challenges and computational complexity demanded by genome-wide single-nucleotide polymorphism data were also discussed. PMID:19924713

An alternative to the breeder's and Lande's equations.

PubMed

Houchmandzadeh, Bahram

2014-01-10

The breeder's equation is a cornerstone of quantitative genetics, widely used in evolutionary modeling. Noting the mean phenotype in parental, selected parents, and the progeny by E(Z0), E(ZW), and E(Z1), this equation relates response to selection R = E(Z1) - E(Z0) to the selection differential S = E(ZW) - E(Z0) through a simple proportionality relation R = h(2)S, where the heritability coefficient h(2) is a simple function of genotype and environment factors variance. The validity of this relation relies strongly on the normal (Gaussian) distribution of the parent genotype, which is an unobservable quantity and cannot be ascertained. In contrast, we show here that if the fitness (or selection) function is Gaussian with mean μ, an alternative, exact linear equation of the form R' = j(2)S' can be derived, regardless of the parental genotype distribution. Here R' = E(Z1) - μ and S' = E(ZW) - μ stand for the mean phenotypic lag with respect to the mean of the fitness function in the offspring and selected populations. The proportionality coefficient j(2) is a simple function of selection function and environment factors variance, but does not contain the genotype variance. To demonstrate this, we derive the exact functional relation between the mean phenotype in the selected and the offspring population and deduce all cases that lead to a linear relation between them. These results generalize naturally to the concept of G matrix and the multivariate Lande's equation Δ(z) = GP(-1)S. The linearity coefficient of the alternative equation are not changed by Gaussian selection.

Incorporation of economic values into the component traits of a ratio: feed efficiency.

PubMed

Lin, C Y; Aggrey, S E

2013-04-01

Direct selection on a ratio (R) of 2 traits (x1/x2) does not have a mechanism to accommodate the relative economic values (a1 and a2) between x1 and x2 because selection criteria x1/x2 and a1x1/a2x2 rank animals in the same order. This study presented a procedure to incorporate the economic weights into ratio traits through linear transformation. The partial derivatives of a nonlinear profit function evaluated at the means were widely taken as economic weights in the literature. This study showed that the economic weights derived in this manner were erroneous because they actually contain a mixture of actual economic weights and transformation effects. The ratios 1/2 and 2/4 are considered equal by selection on R, but are treated differently by the linear index. In addition, this study presented a unified approach to compare 4 different selection strategies for genetic improvement of ratio traits: linear index (I), selection on the ratio (R), selection on difference between x1 and x2 (D), and selection on x1 alone. This study considered 3 levels of heritability each for variables x1 and x2 and 2 levels of genetic correlations (γG), 2 ratios of means (µ1/µ2), and 4 ratios of phenotypic variances giving a total of 96 scenarios. Linear index I was the most efficient of the 4 criteria compared in all 96 scenarios studied. The superiority of index I over R, D, and selection on x1 alone are particularly remarkable when x1 and x2 have a large difference in heritability and are highly correlated. Selection on x1 alone is an economically viable alternative to criterion I or R for the improvement of ratio traits particularly when x1 is more heritable than x2 and when x2 is costly to measure. Selection on D is more efficient than direct selection on R or selection on x1 alone when x1 is less heritable than x2 and the difference between µ1 and µ2 is small.

Schiff's Bases and Crown Ethers as Supramolecular Sensing Materials in the Construction of Potentiometric Membrane Sensors

PubMed Central

Faridbod, Farnoush; Ganjali, Mohammad Reza; Dinarvand, Rassoul; Norouzi, Parviz; Riahi, Siavash

2008-01-01

Ionophore incorporated PVC membrane sensors are well-established analytical tools routinely used for the selective and direct measurement of a wide variety of different ions in complex biological and environmental samples. Potentiometric sensors have some outstanding advantages including simple design and operation, wide linear dynamic range, relatively fast response and rational selectivity. The vital component of such plasticized PVC members is the ionophore involved, defining the selectivity of the electrodes' complex formation. Molecular recognition causes the formation of many different supramolecules. Different types of supramolecules, like calixarenes, cyclodextrins and podands, have been used as a sensing material in the construction of ion selective sensors. Schiff's bases and crown ethers, which feature prominently in supramolecular chemistry, can be used as sensing materials in the construction of potentiometric ion selective electrodes. Up to now, more than 200 potentiometric membrane sensors for cations and anions based on Schiff's bases and crown ethers have been reported. In this review cation binding and anion complexes will be described. Liquid membrane sensors based on Schiff's bases and crown ethers will then be discussed. PMID:27879786

Improving mass-univariate analysis of neuroimaging data by modelling important unknown covariates: Application to Epigenome-Wide Association Studies.

PubMed

Guillaume, Bryan; Wang, Changqing; Poh, Joann; Shen, Mo Jun; Ong, Mei Lyn; Tan, Pei Fang; Karnani, Neerja; Meaney, Michael; Qiu, Anqi

2018-06-01

Statistical inference on neuroimaging data is often conducted using a mass-univariate model, equivalent to fitting a linear model at every voxel with a known set of covariates. Due to the large number of linear models, it is challenging to check if the selection of covariates is appropriate and to modify this selection adequately. The use of standard diagnostics, such as residual plotting, is clearly not practical for neuroimaging data. However, the selection of covariates is crucial for linear regression to ensure valid statistical inference. In particular, the mean model of regression needs to be reasonably well specified. Unfortunately, this issue is often overlooked in the field of neuroimaging. This study aims to adopt the existing Confounder Adjusted Testing and Estimation (CATE) approach and to extend it for use with neuroimaging data. We propose a modification of CATE that can yield valid statistical inferences using Principal Component Analysis (PCA) estimators instead of Maximum Likelihood (ML) estimators. We then propose a non-parametric hypothesis testing procedure that can improve upon parametric testing. Monte Carlo simulations show that the modification of CATE allows for more accurate modelling of neuroimaging data and can in turn yield a better control of False Positive Rate (FPR) and Family-Wise Error Rate (FWER). We demonstrate its application to an Epigenome-Wide Association Study (EWAS) on neonatal brain imaging and umbilical cord DNA methylation data obtained as part of a longitudinal cohort study. Software for this CATE study is freely available at http://www.bioeng.nus.edu.sg/cfa/Imaging_Genetics2.html. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Efficiency of using first-generation information during second-generation selection: results of computer simulation.

Treesearch

T.Z. Ye; K.J.S. Jayawickrama; G.R. Johnson

2004-01-01

BLUP (Best linear unbiased prediction) method has been widely used in forest tree improvement programs. Since one of the properties of BLUP is that related individuals contribute to the predictions of each other, it seems logical that integrating data from all generations and from all populations would improve both the precision and accuracy in predicting genetic...

Voltammetric behavior of dopamine at a glassy carbon electrode modified with NiFe(2)O(4) magnetic nanoparticles decorated with multiwall carbon nanotubes.

PubMed

Ensafi, Ali A; Arashpour, B; Rezaei, B; Allafchian, Ali R

2014-06-01

Voltammetric behavior of dopamine was studied on a glassy carbon electrode (GCE) modified-NiFe(2)O(4) magnetic nanoparticles decorated with multiwall carbon nanotubes. Impedance spectroscopy and cyclic voltammetry were used to characterize the behavior of dopamine at the surface of modified-GCE. The modified electrode showed a synergic effect toward the oxidation of dopamine. The oxidation peak current is increased linearly with the dopamine concentration (at pH7.0) in wide dynamic ranges of 0.05-6.0 and 6.0-100μmolL(-1) with a detection limit of 0.02μmolL(-1), using differential pulse voltammetry. The selectivity of the method was studied and the results showed that the modified electrode is free from interference of organic compounds especially ascorbic acid, uric acid, cysteine and urea. Its applicability in the determination of dopamine in pharmaceutical, urine samples and human blood serum was also evaluated. The proposed electrochemical sensor has appropriate properties such as high selectivity, low detection limit and wide linear dynamic range when compared with that of the previous reported papers for dopamine detection. Copyright © 2014 Elsevier B.V. All rights reserved.

Consideration in selecting crops for the human-rated life support system: a Linear Programming model

NASA Technical Reports Server (NTRS)

Wheeler, E. F.; Kossowski, J.; Goto, E.; Langhans, R. W.; White, G.; Albright, L. D.; Wilcox, D.; Henninger, D. L. (Principal Investigator)

1996-01-01

A Linear Programming model has been constructed which aids in selecting appropriate crops for CELSS (Controlled Environment Life Support System) food production. A team of Controlled Environment Agriculture (CEA) faculty, staff, graduate students and invited experts representing more than a dozen disciplines, provided a wide range of expertise in developing the model and the crop production program. The model incorporates nutritional content and controlled-environment based production yields of carefully chosen crops into a framework where a crop mix can be constructed to suit the astronauts' needs. The crew's nutritional requirements can be adequately satisfied with only a few crops (assuming vitamin mineral supplements are provided) but this will not be satisfactory from a culinary standpoint. This model is flexible enough that taste and variety driven food choices can be built into the model.

Consideration in selecting crops for the human-rated life support system: a linear programming model

NASA Astrophysics Data System (ADS)

Wheeler, E. F.; Kossowski, J.; Goto, E.; Langhans, R. W.; White, G.; Albright, L. D.; Wilcox, D.

A Linear Programming model has been constructed which aids in selecting appropriate crops for CELSS (Controlled Environment Life Support System) food production. A team of Controlled Environment Agriculture (CEA) faculty, staff, graduate students and invited experts representing more than a dozen disciplines, provided a wide range of expertise in developing the model and the crop production program. The model incorporates nutritional content and controlled-environment based production yields of carefully chosen crops into a framework where a crop mix can be constructed to suit the astronauts' needs. The crew's nutritional requirements can be adequately satisfied with only a few crops (assuming vitamin mineral supplements are provided) but this will not be satisfactory from a culinary standpoint. This model is flexible enough that taste and variety driven food choices can be built into the model.

Applicability of hybrid linear ion trap-high resolution mass spectrometry and quadrupole-linear ion trap-mass spectrometry for mycotoxin analysis in baby food.

PubMed

Rubert, Josep; James, Kevin J; Mañes, Jordi; Soler, Carla

2012-02-03

Recent developments in mass spectrometers have created a paradoxical situation; different mass spectrometers are available, each of them with their specific strengths and drawbacks. Hybrid instruments try to unify several advantages in one instrument. In this study two of wide-used hybrid instruments were compared: hybrid quadrupole-linear ion trap-mass spectrometry (QTRAP®) and the hybrid linear ion trap-high resolution mass spectrometry (LTQ-Orbitrap®). Both instruments were applied to detect the presence of 18 selected mycotoxins in baby food. Analytical parameters were validated according to 2002/657/CE. Limits of quantification (LOQs) obtained by QTRAP® instrument ranged from 0.45 to 45 μg kg⁻¹ while lower limits of quantification (LLOQs) values were obtained by LTQ-Orbitrap®: 7-70 μg kg⁻¹. The correlation coefficients (r) in both cases were upper than 0.989. These values highlighted that both instruments were complementary for the analysis of mycotoxin in baby food; while QTRAP® reached best sensitivity and selectivity, LTQ-Orbitrap® allowed the identification of non-target and unknowns compounds. Copyright © 2011 Elsevier B.V. All rights reserved.

Variable Selection with Prior Information for Generalized Linear Models via the Prior LASSO Method.

PubMed

Jiang, Yuan; He, Yunxiao; Zhang, Heping

LASSO is a popular statistical tool often used in conjunction with generalized linear models that can simultaneously select variables and estimate parameters. When there are many variables of interest, as in current biological and biomedical studies, the power of LASSO can be limited. Fortunately, so much biological and biomedical data have been collected and they may contain useful information about the importance of certain variables. This paper proposes an extension of LASSO, namely, prior LASSO (pLASSO), to incorporate that prior information into penalized generalized linear models. The goal is achieved by adding in the LASSO criterion function an additional measure of the discrepancy between the prior information and the model. For linear regression, the whole solution path of the pLASSO estimator can be found with a procedure similar to the Least Angle Regression (LARS). Asymptotic theories and simulation results show that pLASSO provides significant improvement over LASSO when the prior information is relatively accurate. When the prior information is less reliable, pLASSO shows great robustness to the misspecification. We illustrate the application of pLASSO using a real data set from a genome-wide association study.

Estimated breeding values for canine hip dysplasia radiographic traits in a cohort of Australian German Shepherd dogs.

PubMed

Wilson, Bethany J; Nicholas, Frank W; James, John W; Wade, Claire M; Thomson, Peter C

2013-01-01

Canine hip dysplasia (CHD) is a serious and common musculoskeletal disease of pedigree dogs and therefore represents both an important welfare concern and an imperative breeding priority. The typical heritability estimates for radiographic CHD traits suggest that the accuracy of breeding dog selection could be substantially improved by the use of estimated breeding values (EBVs) in place of selection based on phenotypes of individuals. The British Veterinary Association/Kennel Club scoring method is a complex measure composed of nine bilateral ordinal traits, intended to evaluate both early and late dysplastic changes. However, the ordinal nature of the traits may represent a technical challenge for calculation of EBVs using linear methods. The purpose of the current study was to calculate EBVs of British Veterinary Association/Kennel Club traits in the Australian population of German Shepherd Dogs, using linear (both as individual traits and a summed phenotype), binary and ordinal methods to determine the optimal method for EBV calculation. Ordinal EBVs correlated well with linear EBVs (r = 0.90-0.99) and somewhat well with EBVs for the sum of the individual traits (r = 0.58-0.92). Correlation of ordinal and binary EBVs varied widely (r = 0.24-0.99) depending on the trait and cut-point considered. The ordinal EBVs have increased accuracy (0.48-0.69) of selection compared with accuracies from individual phenotype-based selection (0.40-0.52). Despite the high correlations between linear and ordinal EBVs, the underlying relationship between EBVs calculated by the two methods was not always linear, leading us to suggest that ordinal models should be used wherever possible. As the population of German Shepherd Dogs which was studied was purportedly under selection for the traits studied, we examined the EBVs for evidence of a genetic trend in these traits and found substantial genetic improvement over time. This study suggests the use of ordinal EBVs could increase the rate of genetic improvement in this population.

An Alternative to the Breeder’s and Lande’s Equations

PubMed Central

Houchmandzadeh, Bahram

2013-01-01

The breeder’s equation is a cornerstone of quantitative genetics, widely used in evolutionary modeling. Noting the mean phenotype in parental, selected parents, and the progeny by E(Z0), E(ZW), and E(Z1), this equation relates response to selection R = E(Z1) − E(Z0) to the selection differential S = E(ZW) − E(Z0) through a simple proportionality relation R = h2S, where the heritability coefficient h2 is a simple function of genotype and environment factors variance. The validity of this relation relies strongly on the normal (Gaussian) distribution of the parent genotype, which is an unobservable quantity and cannot be ascertained. In contrast, we show here that if the fitness (or selection) function is Gaussian with mean μ, an alternative, exact linear equation of the form R′ = j2S′ can be derived, regardless of the parental genotype distribution. Here R′ = E(Z1) − μ and S′ = E(ZW) − μ stand for the mean phenotypic lag with respect to the mean of the fitness function in the offspring and selected populations. The proportionality coefficient j2 is a simple function of selection function and environment factors variance, but does not contain the genotype variance. To demonstrate this, we derive the exact functional relation between the mean phenotype in the selected and the offspring population and deduce all cases that lead to a linear relation between them. These results generalize naturally to the concept of G matrix and the multivariate Lande’s equation Δz¯=GP−1S. The linearity coefficient of the alternative equation are not changed by Gaussian selection. PMID:24212080

Linear test bed. Volume 1: Test bed no. 1. [aerospike test bed with segmented combustor

NASA Technical Reports Server (NTRS)

1972-01-01

The Linear Test Bed program was to design, fabricate, and evaluation test an advanced aerospike test bed which employed the segmented combustor concept. The system is designated as a linear aerospike system and consists of a thrust chamber assembly, a power package, and a thrust frame. It was designed as an experimental system to demonstrate the feasibility of the linear aerospike-segmented combustor concept. The overall dimensions are 120 inches long by 120 inches wide by 96 inches in height. The propellants are liquid oxygen/liquid hydrogen. The system was designed to operate at 1200-psia chamber pressure, at a mixture ratio of 5.5. At the design conditions, the sea level thrust is 200,000 pounds. The complete program including concept selection, design, fabrication, component test, system test, supporting analysis and posttest hardware inspection is described.

Conversion of alkanes to linear alkylsilanes using an iridium-iron-catalysed tandem dehydrogenation-isomerization-hydrosilylation

NASA Astrophysics Data System (ADS)

Jia, Xiangqing; Huang, Zheng

2016-02-01

The conversion of inexpensive, saturated hydrocarbon feedstocks into value-added speciality chemicals using regiospecific, catalytic functionalization of alkanes is a major goal of organometallic chemistry. Linear alkylsilanes represent one such speciality chemical—they have a wide range of applications, including release coatings, silicone rubbers and moulding products. Direct, selective, functionalization of alkanes at primary C-H bonds is difficult and, to date, methods for catalytically converting alkanes into linear alkylsilanes are unknown. Here, we report a well-defined, dual-catalyst system for one-pot, two-step alkane silylations. The system comprises a pincer-ligated Ir catalyst for alkane dehydrogenation and an Fe catalyst that effects a subsequent tandem olefin isomerization-hydrosilylation. This method exhibits exclusive regioselectivity for the production of terminally functionalized alkylsilanes. This dual-catalyst strategy has also been applied to regioselective alkane borylations to form linear alkylboronate esters.

Testing, Selection, and Implementation of Random Number Generators

DTIC Science & Technology

2008-07-01

Complexity and Lempel - Ziv Compression tests. This causes concern for cryptographic use but is not relevant for our applications. In fact, the features of...Linear Complexity, Lempel - Ziv Compression , and Matrix Rank test failures excluded. The Mersenne Twister is widely accepted by the community; in fact...searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection information. Send comments

Widely Tunable On-Chip Microwave Circulator for Superconducting Quantum Circuits

NASA Astrophysics Data System (ADS)

Chapman, Benjamin J.; Rosenthal, Eric I.; Kerckhoff, Joseph; Moores, Bradley A.; Vale, Leila R.; Mates, J. A. B.; Hilton, Gene C.; Lalumière, Kevin; Blais, Alexandre; Lehnert, K. W.

2017-10-01

We report on the design and performance of an on-chip microwave circulator with a widely (GHz) tunable operation frequency. Nonreciprocity is created with a combination of frequency conversion and delay, and requires neither permanent magnets nor microwave bias tones, allowing on-chip integration with other superconducting circuits without the need for high-bandwidth control lines. Isolation in the device exceeds 20 dB over a bandwidth of tens of MHz, and its insertion loss is small, reaching as low as 0.9 dB at select operation frequencies. Furthermore, the device is linear with respect to input power for signal powers up to hundreds of fW (≈103 circulating photons), and the direction of circulation can be dynamically reconfigured. We demonstrate its operation at a selection of frequencies between 4 and 6 GHz.

Enhanced selectivity for the hydrolysis of block copoly(2-oxazoline)s in ethanol-water resulting in linear poly(ethylene imine) copolymers.

PubMed

van Kuringen, Huub P C; de la Rosa, Victor R; Fijten, Martin W M; Heuts, Johan P A; Hoogenboom, Richard

2012-05-14

The ability of merging the properties of poly(2-oxazoline)s and poly(ethylene imine) is of high interest for various biomedical applications, including gene delivery, biosensors, and switchable surfaces and nanoparticles. In the present research, a methodology for the controlled and selective hydrolysis of (co)poly(2-oxazoline)s is developed in an ethanol-water solvent mixture, opening the path toward a wide range of block poly(2-oxazoline-co-ethylene imine) (POx-PEI) copolymers with tunable properties. The unexpected influence of the selected ethanol-water binary solvent mixture on the hydrolysis kinetics and selectivity is highlighted in the pursue of well-defined POx-PEI block copolymers. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

On estimation of linear transformation models with nested case–control sampling

PubMed Central

Liu, Mengling

2011-01-01

Nested case–control (NCC) sampling is widely used in large epidemiological cohort studies for its cost effectiveness, but its data analysis primarily relies on the Cox proportional hazards model. In this paper, we consider a family of linear transformation models for analyzing NCC data and propose an inverse selection probability weighted estimating equation method for inference. Consistency and asymptotic normality of our estimators for regression coefficients are established. We show that the asymptotic variance has a closed analytic form and can be easily estimated. Numerical studies are conducted to support the theory and an application to the Wilms’ Tumor Study is also given to illustrate the methodology. PMID:21912975

DMD-based programmable wide field spectrograph for Earth observation

NASA Astrophysics Data System (ADS)

Zamkotsian, Frédéric; Lanzoni, Patrick; Liotard, Arnaud; Viard, Thierry; Costes, Vincent; Hébert, Philippe-Jean

2015-03-01

In Earth Observation, Universe Observation and Planet Exploration, scientific return could be optimized in future missions using MOEMS devices. In Earth Observation, we propose an innovative reconfigurable instrument, a programmable wide-field spectrograph where both the FOV and the spectrum could be tailored thanks to a 2D micromirror array (MMA). For a linear 1D field of view (FOV), the principle is to use a MMA to select the wavelengths by acting on intensity. This component is placed in the focal plane of a first grating. On the MMA surface, the spatial dimension is along one side of the device and for each spatial point, its spectrum is displayed along the perpendicular direction: each spatial and spectral feature of the 1D FOV is then fully adjustable dynamically and/or programmable. A second stage with an identical grating recomposes the beam after wavelengths selection, leading to an output tailored 1D image. A mock-up has been designed, fabricated and tested. The micromirror array is the largest DMD in 2048 x 1080 mirrors format, with a pitch of 13.68μm. A synthetic linear FOV is generated and typical images have been recorded o at the output focal plane of the instrument. By tailoring the DMD, we could modify successfully each pixel of the input image: for example, it is possible to remove bright objects or, for each spatial pixel, modify the spectral signature. The very promising results obtained on the mock-up of the programmable wide-field spectrograph reveal the efficiency of this new instrument concept for Earth Observation.

Single Nanochannel-Aptamer-Based Biosensor for Ultrasensitive and Selective Cocaine Detection.

PubMed

Wang, Jian; Hou, Jue; Zhang, Huacheng; Tian, Ye; Jiang, Lei

2018-01-17

Ultrasensitive and selective detection of molecules at nano or sub-nanomolar level is very important for many areas such as early diagnosis and drug testing. Herein, we report a high-sensitive cocaine sensor based on a single nanochannel coupled with DNA aptamers. The single nanochannel-aptamer-based biosensor can recognize cocaine molecules with an excellent sensitivity and good selectivity. A linear relationship between target cocaine concentration and output ionic current is obtained in a wide concentration range of cocaine from 1 nM to 10 μM. The cocaine sensor also shows a detection limit down to 1 nM. This study provides a new avenue to develop new nanochannel-aptamer-based biosensors for rapid and ultratrace detection of a variety of illicit drugs.

An SVM-based solution for fault detection in wind turbines.

PubMed

Santos, Pedro; Villa, Luisa F; Reñones, Aníbal; Bustillo, Andres; Maudes, Jesús

2015-03-09

Research into fault diagnosis in machines with a wide range of variable loads and speeds, such as wind turbines, is of great industrial interest. Analysis of the power signals emitted by wind turbines for the diagnosis of mechanical faults in their mechanical transmission chain is insufficient. A successful diagnosis requires the inclusion of accelerometers to evaluate vibrations. This work presents a multi-sensory system for fault diagnosis in wind turbines, combined with a data-mining solution for the classification of the operational state of the turbine. The selected sensors are accelerometers, in which vibration signals are processed using angular resampling techniques and electrical, torque and speed measurements. Support vector machines (SVMs) are selected for the classification task, including two traditional and two promising new kernels. This multi-sensory system has been validated on a test-bed that simulates the real conditions of wind turbines with two fault typologies: misalignment and imbalance. Comparison of SVM performance with the results of artificial neural networks (ANNs) shows that linear kernel SVM outperforms other kernels and ANNs in terms of accuracy, training and tuning times. The suitability and superior performance of linear SVM is also experimentally analyzed, to conclude that this data acquisition technique generates linearly separable datasets.

Development of a ceramic membrane from a lithian spinel, Li1+xMyMn2-yO4 (M=trivalent or tetravalent cations) for a Li ion-selective electrode

NASA Astrophysics Data System (ADS)

Yoon, H.; Venugopal, N.; Rim, T.; Yang, B.; Chung, K.; Ko, T.

2010-12-01

Recently a few lithium containing ceramics are reported as promising cathodes for application in lithium batteries. Among them, a spinel-type lithium manganate (LM) exhibits an exceptionally high ion selectivity at room temperature. Thus, LM could have a great potential as an ion selective membrane material for screening interfering ions from lithium ion for the determination of lithium ion in salt solution. In this study, we developed an ion-selective electrode based on LM as a membrane material and investigated its lithium ion selectivity by varying the content of M in composition. A sol-gel process was successfully applied for preparing LM films without resorting to calcination at a high temperature. The LM thin film-type membranes exhibit a high selectivity for Li ion over other cations, a wide operation detection range of 10-5 ~ 10-2 M, and a fast response time less than 60 s. Furthermore, our result demonstrates a linear potentiometric response over a wide range of lithium concentration, which is compared to that of a lithium ion-selective electrode based on an ionophore. Acknowledgements: This research was supported by a grant from the Development of Technology for Extraction of Resources Dissolved in Sea Water Program funded by Ministry of Land Transport and Maritime Affairs in Korean Government (2010).

Advances in diagnostic ultrasonography.

PubMed

Reef, V B

1991-08-01

A wide variety of ultrasonographic equipment currently is available for use in equine practice, but no one machine is optimal for every type of imaging. Image quality is the most important factor in equipment selection once the needs of the practitioner are ascertained. The transducer frequencies available, transducer footprints, depth of field displayed, frame rate, gray scale, simultaneous electrocardiography, Doppler, and functions to modify the image are all important considerations. The ability to make measurements off of videocassette recorder playback and future upgradability should be evaluated. Linear array and sector technology are the backbone of equine ultrasonography today. Linear array technology is most useful for a high-volume broodmare practice, whereas sector technology is ideal for a more general equine practice. The curved or convex linear scanner has more applications than the standard linear array and is equipped with the linear array rectal probe, which provides the equine practitioner with a more versatile unit for equine ultrasonographic evaluations. The annular array and phased array systems have improved image quality, but each has its own limitations. The new sector scanners still provide the most versatile affordable equipment for equine general practice.

Turn-On Fluorescent Chemosensor for Hg2+ Based on Multivalent Rhodamine Ligands

PubMed Central

Wang, Xuemei; Iqbal, Mudassir; Huskens, Jurriaan; Verboom, Willem

2012-01-01

Rhodamine-based fluorescent chemosensors 1 and 2 exhibit selective fluorescence enhancement to Fe3+ and Hg2+ over other metal ions at 580 nm in CH3CN/H2O (3/1, v/v) solution. Bis(rhodamine) chemosensor 1, under optimized conditions (CH3CN/HEPES buffer (0.02 M, pH = 7.0) (95/5, v/v)), shows a high selectivity and sensitivity to Hg2+, with a linear working range of 0–50 μM, a wide pH span of 4–10, and a detection limit of 0.4 μM Hg2+. PMID:23222686

Multiple long-term trends and trend reversals dominate environmental conditions in a man-made freshwater reservoir.

PubMed

Znachor, Petr; Nedoma, Jiří; Hejzlar, Josef; Seďa, Jaromír; Kopáček, Jiří; Boukal, David; Mrkvička, Tomáš

2018-05-15

Man-made reservoirs are common across the world and provide a wide range of ecological services. Environmental conditions in riverine reservoirs are affected by the changing climate, catchment-wide processes and manipulations with the water level, and water abstraction from the reservoir. Long-term trends of environmental conditions in reservoirs thus reflect a wider range of drivers in comparison to lakes, which makes the understanding of reservoir dynamics more challenging. We analysed a 32-year time series of 36 environmental variables characterising weather, land use in the catchment, reservoir hydrochemistry, hydrology and light availability in the small, canyon-shaped Římov Reservoir in the Czech Republic to detect underlying trends, trend reversals and regime shifts. To do so, we fitted linear and piecewise linear regression and a regime shift model to the time series of mean annual values of each variable and to principal components produced by Principal Component Analysis. Models were weighted and ranked using Akaike information criterion and the model selection approach. Most environmental variables exhibited temporal changes that included time-varying trends and trend reversals. For instance, dissolved organic carbon showed a linear increasing trend while nitrate concentration or conductivity exemplified trend reversal. All trend reversals and cessations of temporal trends in reservoir hydrochemistry (except total phosphorus concentrations) occurred in the late 1980s and during 1990s as a consequence of dramatic socioeconomic changes. After a series of heavy rains in the late 1990s, an administrative decision to increase the flood-retention volume of the reservoir resulted in a significant regime shift in reservoir hydraulic conditions in 1999. Our analyses also highlight the utility of the model selection framework, based on relatively simple extensions of linear regression, to describe temporal trends in reservoir characteristics. This approach can provide a solid basis for a better understanding of processes in freshwater reservoirs. Copyright © 2017 Elsevier B.V. All rights reserved.

Construction of a new selective coated disk electrode for Ag (I) based on modified polypyrrole-carbon nanotubes composite with new lariat ether.

PubMed

Abbaspour, A; Tashkhourian, J; Ahmadpour, S; Mirahmadi, E; Sharghi, H; Khalifeh, R; Shahriyari, M R

2014-01-01

A poly (vinyl chloride) (PVC) matrix membrane ion-selective electrode for silver (I) ion is fabricated based on modified polypyrrole - multiwalled carbon nanotubes composite with new lariat ether. This sensor has a Nernstian slope of 59.4±0.5mV/decade over a wide linear concentration range of 1.0×10(-7) to 1.0×10(-1)molL(-1) for silver (I) ion. It has a short response time of about 8.0s and can be used for at least 50days. The detection limit is 9.3×10(-8)molL(-1) for silver (I) ion, and the electrode was applicable in the wide pH range of 1.6 -7.7. The electrode shows good selectivity for silver ion against many cations such as Hg (II), which usually imposes serious interference in the determination of silver ion concentration. The use of multiwalled carbon nanotubes (MWCNTs) in a polymer matrix improves the linear range and sensitivity of the electrode. In addition by coating the solid contact with a layer of the polypyrrole (Ppy) before coating the membrane on it, not only did it reduce the drift in potential, but a shorter response time was also resulted. The proposed electrode was used as an indicator electrode for potentiometric titration of silver ions with chloride anions and in the titration of mixed halides. This electrode was successfully applied for the determination of silver ions in silver sulphadiazine as a burning cream. © 2013.

Development of a method of clozapine dosage by selective electrode to the iodides.

PubMed

Teyeb, Hassen; Douki, Wahiba; Najjar, Mohamed Fadhel

2012-07-01

Clozapine (Leponex(®)), the main neuroleptic indicated in the treatment of resistant schizophrenia, requires therapeutic monitoring because of its side effects and the individual variability in metabolism. In addition, several cases of intoxication by this drug were described in the literature. In this work, we studied the indirect dosage of clozapine by selective electrode to the iodides for the optimization of an analytical protocol allowing therapeutic monitoring and the diagnosis of intoxication and/or overdose. Our results showed that the developed method is linear between 0.05 and 12.5 µg/mL (r = 0.980), with a limit of detection of 0.645.10(-3) µg/mL. It presents good precision (coefficient of variation less than 4%) and accuracy (coefficient less than 10%) for all the studied concentrations. With a domain of linearity covering a wide margin of concentrations, this method can be applicable to the dosage of clozapine in tablets and in different biological matrices, such as plasma, urines, and postmortem samples.

Evaluation of a transfinite element numerical solution method for nonlinear heat transfer problems

NASA Technical Reports Server (NTRS)

Cerro, J. A.; Scotti, S. J.

1991-01-01

Laplace transform techniques have been widely used to solve linear, transient field problems. A transform-based algorithm enables calculation of the response at selected times of interest without the need for stepping in time as required by conventional time integration schemes. The elimination of time stepping can substantially reduce computer time when transform techniques are implemented in a numerical finite element program. The coupling of transform techniques with spatial discretization techniques such as the finite element method has resulted in what are known as transfinite element methods. Recently attempts have been made to extend the transfinite element method to solve nonlinear, transient field problems. This paper examines the theoretical basis and numerical implementation of one such algorithm, applied to nonlinear heat transfer problems. The problem is linearized and solved by requiring a numerical iteration at selected times of interest. While shown to be acceptable for weakly nonlinear problems, this algorithm is ineffective as a general nonlinear solution method.

An Ultrastable Europium(III)-Organic Framework with the Capacity of Discriminating Fe2+/Fe3+ Ions in Various Solutions.

PubMed

Wen, Guo-Xuan; Wu, Ya-Pan; Dong, Wen-Wen; Zhao, Jun; Li, Dong-Sheng; Zhang, Jian

2016-10-05

An ultrastable luminescent europium-organic framework, {[Eu(L)(H 2 O) 2 ]·NMP·H 2 O} n (CTGU-2; NMP = N-methyl-2-pyrrolidone), can first detect Fe 2+ /Fe 3+ cations in different medium systems with high selectivity and sensitivity, and it also exhibits high sensitivity for Cr 2 O 7 2- anion and acetone with a wide linear range and a low detection limit.

Three Dimensional Integration and On-Wafer Packaging for Heterogeneous Wafer-Scale Circuit Architectures

DTIC Science & Technology

2006-11-01

Chip Level CMOS Chip High resistivity Si Metal Interconnect 25μm 24GHz fully integrated receiver CMOS transimpedance Amplifier (13GHz BW, 52dBΩ...power of a high-resistivity SiGe power amplifier chip with the wide operating frequency range and compactness of a CMOS mixed signal chip operating...With good RF channel selectivity, system specifications such as the linearity of the low noise amplifier (LNA), the phase noise of the voltage

Nano-biosensor for highly sensitive detection of HER2 positive breast cancer.

PubMed

Salahandish, Razieh; Ghaffarinejad, Ali; Naghib, Seyed Morteza; Majidzadeh-A, Keivan; Zargartalebi, Hossein; Sanati-Nezhad, Amir

2018-05-25

Nanocomposite materials have provided a wide range of conductivity, sensitivity, selectivity and linear response for electrochemical biosensors. However, the detection of rare cells at single cell level requires a new class of nanocomposite-coated electrodes with exceptional sensitivity and specificity. We recently developed a construct of gold nanoparticle-grafted functionalized graphene and nanostructured polyaniline (PANI) for high-performance biosensing within a very wide linear response and selective performance. Further, replacing the expensive gold nanoparticles with low-cost silver nanoparticles as well as optimizing the nanocomposite synthesis and functionalization protocols on the electrode surface in this work enabled us to develop ultrasensitive nanocomposites for label-free detection of breast cancer cells. The sensor presented a fast response time of 30 min within a dynamic range of 10 - 5 × 10 6 cells mL -1 and with a detection limit of 2 cells mL -1 for the detection of SK-BR3 breast cancer cell. The nano-biosensor, for the first time, demonstrated a high efficiency of > 90% for the label-free detection of cancer cells in whole blood sample without any need for sample preparation and cell staining. The results demonstrated that the optimized nanocomposite developed in this work is a promising nanomaterial for electrochemical biosensing and with the potential applications in electro-catalysis and super-capacitances. Copyright © 2018 Elsevier B.V. All rights reserved.

Compensatory selection for roads over natural linear features by wolves in northern Ontario: Implications for caribou conservation

PubMed Central

Patterson, Brent R.; Anderson, Morgan L.; Rodgers, Arthur R.; Vander Vennen, Lucas M.; Fryxell, John M.

2017-01-01

Woodland caribou (Rangifer tarandus caribou) in Ontario are a threatened species that have experienced a substantial retraction of their historic range. Part of their decline has been attributed to increasing densities of anthropogenic linear features such as trails, roads, railways, and hydro lines. These features have been shown to increase the search efficiency and kill rate of wolves. However, it is unclear whether selection for anthropogenic linear features is additive or compensatory to selection for natural (water) linear features which may also be used for travel. We studied the selection of water and anthropogenic linear features by 52 resident wolves (Canis lupus x lycaon) over four years across three study areas in northern Ontario that varied in degrees of forestry activity and human disturbance. We used Euclidean distance-based resource selection functions (mixed-effects logistic regression) at the seasonal range scale with random coefficients for distance to water linear features, primary/secondary roads/railways, and hydro lines, and tertiary roads to estimate the strength of selection for each linear feature and for several habitat types, while accounting for availability of each feature. Next, we investigated the trade-off between selection for anthropogenic and water linear features. Wolves selected both anthropogenic and water linear features; selection for anthropogenic features was stronger than for water during the rendezvous season. Selection for anthropogenic linear features increased with increasing density of these features on the landscape, while selection for natural linear features declined, indicating compensatory selection of anthropogenic linear features. These results have implications for woodland caribou conservation. Prey encounter rates between wolves and caribou seem to be strongly influenced by increasing linear feature densities. This behavioral mechanism–a compensatory functional response to anthropogenic linear feature density resulting in decreased use of natural travel corridors–has negative consequences for the viability of woodland caribou. PMID:29117234

Compensatory selection for roads over natural linear features by wolves in northern Ontario: Implications for caribou conservation.

PubMed

Newton, Erica J; Patterson, Brent R; Anderson, Morgan L; Rodgers, Arthur R; Vander Vennen, Lucas M; Fryxell, John M

2017-01-01

Woodland caribou (Rangifer tarandus caribou) in Ontario are a threatened species that have experienced a substantial retraction of their historic range. Part of their decline has been attributed to increasing densities of anthropogenic linear features such as trails, roads, railways, and hydro lines. These features have been shown to increase the search efficiency and kill rate of wolves. However, it is unclear whether selection for anthropogenic linear features is additive or compensatory to selection for natural (water) linear features which may also be used for travel. We studied the selection of water and anthropogenic linear features by 52 resident wolves (Canis lupus x lycaon) over four years across three study areas in northern Ontario that varied in degrees of forestry activity and human disturbance. We used Euclidean distance-based resource selection functions (mixed-effects logistic regression) at the seasonal range scale with random coefficients for distance to water linear features, primary/secondary roads/railways, and hydro lines, and tertiary roads to estimate the strength of selection for each linear feature and for several habitat types, while accounting for availability of each feature. Next, we investigated the trade-off between selection for anthropogenic and water linear features. Wolves selected both anthropogenic and water linear features; selection for anthropogenic features was stronger than for water during the rendezvous season. Selection for anthropogenic linear features increased with increasing density of these features on the landscape, while selection for natural linear features declined, indicating compensatory selection of anthropogenic linear features. These results have implications for woodland caribou conservation. Prey encounter rates between wolves and caribou seem to be strongly influenced by increasing linear feature densities. This behavioral mechanism-a compensatory functional response to anthropogenic linear feature density resulting in decreased use of natural travel corridors-has negative consequences for the viability of woodland caribou.

Non-LTE line-blanketed model atmospheres of hot stars. 1: Hybrid complete linearization/accelerated lambda iteration method

NASA Technical Reports Server (NTRS)

Hubeny, I.; Lanz, T.

1995-01-01

A new munerical method for computing non-Local Thermodynamic Equilibrium (non-LTE) model stellar atmospheres is presented. The method, called the hybird complete linearization/accelerated lambda iretation (CL/ALI) method, combines advantages of both its constituents. Its rate of convergence is virtually as high as for the standard CL method, while the computer time per iteration is almost as low as for the standard ALI method. The method is formulated as the standard complete lineariation, the only difference being that the radiation intensity at selected frequency points is not explicity linearized; instead, it is treated by means of the ALI approach. The scheme offers a wide spectrum of options, ranging from the full CL to the full ALI method. We deonstrate that the method works optimally if the majority of frequency points are treated in the ALI mode, while the radiation intensity at a few (typically two to 30) frequency points is explicity linearized. We show how this method can be applied to calculate metal line-blanketed non-LTE model atmospheres, by using the idea of 'superlevels' and 'superlines' introduced originally by Anderson (1989). We calculate several illustrative models taking into accont several tens of thosands of lines of Fe III to Fe IV and show that the hybrid CL/ALI method provides a robust method for calculating non-LTE line-blanketed model atmospheres for a wide range of stellar parameters. The results for individual stellar types will be presented in subsequent papers in this series.

Advancing Forward-Looking Metrics: A Linear Program Optimization and Robust Variable Selection for Change in Stock Levels as a Result of Recurring MICAP Parts

DTIC Science & Technology

2013-06-01

Kobu, 2007) Gunasekaran and Kobu also presented six observations as they relate to these key performance indicators ( KPI ), as follows: 1...Internal business process (50% of the KPI ) and customers (50% of the KPI ) play a significant role in SC environments. This implies that internal business...process PMs have significant impact on the operational performance. 2. The most widely used PM is financial performance (38% of the KPI ). This

Molecularly imprinted covalent organic polymers for the selective extraction of benzoxazole fluorescent whitening agents from food samples.

PubMed

Ding, Hui; Wang, Rongyu; Wang, Xiao; Ji, Wenhua

2018-06-21

Molecularly imprinted covalent organic polymers were constructed by an imine-linking reaction between 1,3,5-triformylphloroglucinol and 2,6-diaminopyridine and used for the selective solid-phase extraction of benzoxazole fluorescent whitening agents from food samples. Binding experiments showed that imprinting sites on molecularly imprinted polymers had higher selectivity for targets compared with those of the corresponding non-imprinted polymers. Parameters affecting the solid-phase extraction procedure were examined. Under optimal conditions, actual samples were treated and the eluent was analyzed with high-performance liquid chromatography with diode-array detection. The results showed that the established method owned the wide linearity, satisfactory detection limits and quantification limits, and acceptable recoveries. Thus, this developed method possesses the practical potential to the selectively determine benzoxazole fluorescent whitening agents in complex food samples. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

GAPIT: genome association and prediction integrated tool.

PubMed

Lipka, Alexander E; Tian, Feng; Wang, Qishan; Peiffer, Jason; Li, Meng; Bradbury, Peter J; Gore, Michael A; Buckler, Edward S; Zhang, Zhiwu

2012-09-15

Software programs that conduct genome-wide association studies and genomic prediction and selection need to use methodologies that maximize statistical power, provide high prediction accuracy and run in a computationally efficient manner. We developed an R package called Genome Association and Prediction Integrated Tool (GAPIT) that implements advanced statistical methods including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large datasets in excess of 10 000 individuals and 1 million single-nucleotide polymorphisms with minimal computational time, while providing user-friendly access and concise tables and graphs to interpret results. http://www.maizegenetics.net/GAPIT. zhiwu.zhang@cornell.edu Supplementary data are available at Bioinformatics online.

An SVM-Based Solution for Fault Detection in Wind Turbines

PubMed Central

Santos, Pedro; Villa, Luisa F.; Reñones, Aníbal; Bustillo, Andres; Maudes, Jesús

2015-01-01

Research into fault diagnosis in machines with a wide range of variable loads and speeds, such as wind turbines, is of great industrial interest. Analysis of the power signals emitted by wind turbines for the diagnosis of mechanical faults in their mechanical transmission chain is insufficient. A successful diagnosis requires the inclusion of accelerometers to evaluate vibrations. This work presents a multi-sensory system for fault diagnosis in wind turbines, combined with a data-mining solution for the classification of the operational state of the turbine. The selected sensors are accelerometers, in which vibration signals are processed using angular resampling techniques and electrical, torque and speed measurements. Support vector machines (SVMs) are selected for the classification task, including two traditional and two promising new kernels. This multi-sensory system has been validated on a test-bed that simulates the real conditions of wind turbines with two fault typologies: misalignment and imbalance. Comparison of SVM performance with the results of artificial neural networks (ANNs) shows that linear kernel SVM outperforms other kernels and ANNs in terms of accuracy, training and tuning times. The suitability and superior performance of linear SVM is also experimentally analyzed, to conclude that this data acquisition technique generates linearly separable datasets. PMID:25760051

Switchable electrochemiluminescence aptasensor coupled with resonance energy transfer for selective attomolar detection of Hg2+ via CdTe@CdS/dendrimer probe and Au nanoparticle quencher.

PubMed

Babamiri, Bahareh; Salimi, Abdollah; Hallaj, Rahman

2018-04-15

In the present study, an ultrasensitive electrochemiluminescence (ECL) aptasensing assay for selective detection of Hg 2+ was designed. In this electrochemiluminescence resonance energy transfer (ECL-RET) approach, Fe 3 O 4 @SiO 2 /dendrimers/QDs exhibited amplified ECL emissions (switch "on" state) and with the hybridization between T-rich ssDNA(S 1 ) immobilized on the Fe 3 O 4 @SiO 2 /dendrimers/QDs and AuNPs modified with complementary aptamer (AuNPs-S 2 ), the ECL of QDs nanocomposites was efficiently quenched (switch "off" state). In the presence of Hg 2+ ions, formation of strong and stable T-Hg 2+ -T complex led to the release of the AuNPs-S 2 from double-stranded DNA(dsDNA) and the recovery of the ECL signal of QDs (second signal switch "on" state). Under optimal conditions, Hg 2+ can be detected in a wide linear range from 20aM to 2µM with a very low detection limit of 2aM. The proposed ECL aptasensor showed high selectivity for Hg 2+ determination compared to other environmentally relevant metal ions at concentration ratio more than 1000 times. The aptasensor was used for detection Hg 2+ ions from samples of tap waters, carp and saltwater fishes with satisfactory results. The aptasensor exhibited high sensitivity, wide linear response (11 orders of magnitude), excellent reproducibility and stability. The proposed aptasensor will be a promising candidate for facile and rapid determination of Hg 2＋ in environmental and fishery samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparison of l₁-Norm SVR and Sparse Coding Algorithms for Linear Regression.

PubMed

Zhang, Qingtian; Hu, Xiaolin; Zhang, Bo

2015-08-01

Support vector regression (SVR) is a popular function estimation technique based on Vapnik's concept of support vector machine. Among many variants, the l1-norm SVR is known to be good at selecting useful features when the features are redundant. Sparse coding (SC) is a technique widely used in many areas and a number of efficient algorithms are available. Both l1-norm SVR and SC can be used for linear regression. In this brief, the close connection between the l1-norm SVR and SC is revealed and some typical algorithms are compared for linear regression. The results show that the SC algorithms outperform the Newton linear programming algorithm, an efficient l1-norm SVR algorithm, in efficiency. The algorithms are then used to design the radial basis function (RBF) neural networks. Experiments on some benchmark data sets demonstrate the high efficiency of the SC algorithms. In particular, one of the SC algorithms, the orthogonal matching pursuit is two orders of magnitude faster than a well-known RBF network designing algorithm, the orthogonal least squares algorithm.

Linear and nonlinear analysis of fluid slosh dampers

NASA Astrophysics Data System (ADS)

Sayar, B. A.; Baumgarten, J. R.

1982-11-01

A vibrating structure and a container partially filled with fluid are considered coupled in a free vibration mode. To simplify the mathematical analysis, a pendulum model to duplicate the fluid motion and a mass-spring dashpot representing the vibrating structure are used. The equations of motion are derived by Lagrange's energy approach and expressed in parametric form. For a wide range of parametric values the logarithmic decrements of the main system are calculated from theoretical and experimental response curves in the linear analysis. However, for the nonlinear analysis the theoretical and experimental response curves of the main system are compared. Theoretical predictions are justified by experimental observations with excellent agreement. It is concluded finally that for a proper selection of design parameters, containers partially filled with viscous fluids serve as good vibration dampers.

Statistical quality assessment criteria for a linear mixing model with elliptical t-distribution errors

NASA Astrophysics Data System (ADS)

Manolakis, Dimitris G.

2004-10-01

The linear mixing model is widely used in hyperspectral imaging applications to model the reflectance spectra of mixed pixels in the SWIR atmospheric window or the radiance spectra of plume gases in the LWIR atmospheric window. In both cases it is important to detect the presence of materials or gases and then estimate their amount, if they are present. The detection and estimation algorithms available for these tasks are related but they are not identical. The objective of this paper is to theoretically investigate how the heavy tails observed in hyperspectral background data affect the quality of abundance estimates and how the F-test, used for endmember selection, is robust to the presence of heavy tails when the model fits the data.

An improved discriminative filter bank selection approach for motor imagery EEG signal classification using mutual information.

PubMed

Kumar, Shiu; Sharma, Alok; Tsunoda, Tatsuhiko

2017-12-28

Common spatial pattern (CSP) has been an effective technique for feature extraction in electroencephalography (EEG) based brain computer interfaces (BCIs). However, motor imagery EEG signal feature extraction using CSP generally depends on the selection of the frequency bands to a great extent. In this study, we propose a mutual information based frequency band selection approach. The idea of the proposed method is to utilize the information from all the available channels for effectively selecting the most discriminative filter banks. CSP features are extracted from multiple overlapping sub-bands. An additional sub-band has been introduced that cover the wide frequency band (7-30 Hz) and two different types of features are extracted using CSP and common spatio-spectral pattern techniques, respectively. Mutual information is then computed from the extracted features of each of these bands and the top filter banks are selected for further processing. Linear discriminant analysis is applied to the features extracted from each of the filter banks. The scores are fused together, and classification is done using support vector machine. The proposed method is evaluated using BCI Competition III dataset IVa, BCI Competition IV dataset I and BCI Competition IV dataset IIb, and it outperformed all other competing methods achieving the lowest misclassification rate and the highest kappa coefficient on all three datasets. Introducing a wide sub-band and using mutual information for selecting the most discriminative sub-bands, the proposed method shows improvement in motor imagery EEG signal classification.

Constructing Compact Takagi-Sugeno Rule Systems: Identification of Complex Interactions in Epidemiological Data

PubMed Central

Zhou, Shang-Ming; Lyons, Ronan A.; Brophy, Sinead; Gravenor, Mike B.

2012-01-01

The Takagi-Sugeno (TS) fuzzy rule system is a widely used data mining technique, and is of particular use in the identification of non-linear interactions between variables. However the number of rules increases dramatically when applied to high dimensional data sets (the curse of dimensionality). Few robust methods are available to identify important rules while removing redundant ones, and this results in limited applicability in fields such as epidemiology or bioinformatics where the interaction of many variables must be considered. Here, we develop a new parsimonious TS rule system. We propose three statistics: R, L, and ω-values, to rank the importance of each TS rule, and a forward selection procedure to construct a final model. We use our method to predict how key components of childhood deprivation combine to influence educational achievement outcome. We show that a parsimonious TS model can be constructed, based on a small subset of rules, that provides an accurate description of the relationship between deprivation indices and educational outcomes. The selected rules shed light on the synergistic relationships between the variables, and reveal that the effect of targeting specific domains of deprivation is crucially dependent on the state of the other domains. Policy decisions need to incorporate these interactions, and deprivation indices should not be considered in isolation. The TS rule system provides a basis for such decision making, and has wide applicability for the identification of non-linear interactions in complex biomedical data. PMID:23272108

Constructing compact Takagi-Sugeno rule systems: identification of complex interactions in epidemiological data.

PubMed

Zhou, Shang-Ming; Lyons, Ronan A; Brophy, Sinead; Gravenor, Mike B

2012-01-01

The Takagi-Sugeno (TS) fuzzy rule system is a widely used data mining technique, and is of particular use in the identification of non-linear interactions between variables. However the number of rules increases dramatically when applied to high dimensional data sets (the curse of dimensionality). Few robust methods are available to identify important rules while removing redundant ones, and this results in limited applicability in fields such as epidemiology or bioinformatics where the interaction of many variables must be considered. Here, we develop a new parsimonious TS rule system. We propose three statistics: R, L, and ω-values, to rank the importance of each TS rule, and a forward selection procedure to construct a final model. We use our method to predict how key components of childhood deprivation combine to influence educational achievement outcome. We show that a parsimonious TS model can be constructed, based on a small subset of rules, that provides an accurate description of the relationship between deprivation indices and educational outcomes. The selected rules shed light on the synergistic relationships between the variables, and reveal that the effect of targeting specific domains of deprivation is crucially dependent on the state of the other domains. Policy decisions need to incorporate these interactions, and deprivation indices should not be considered in isolation. The TS rule system provides a basis for such decision making, and has wide applicability for the identification of non-linear interactions in complex biomedical data.

Association between surgeon volume and hospitalisation costs for patients with oral cancer: a nationwide population base study in Taiwan.

PubMed

Lee, C-C; Ho, H-C; Jack, Lee C-C; Su, Y-C; Lee, M-S; Hung, S-K; Chou, Pesus

2010-02-01

Oral cancer leads to a considerable use of and expenditure on health care. Wide resection of the tumour and reconstruction with a pedicle flap/free flap is widely used. This study was conducted to explore the relationship between hospitalisation costs and surgeon case volume when this operation was performed. A population-based study. This study uses data for the years 2005-2006 obtained from the National Health Insurance Research Database published in the Taiwanese National Health Research Institute. From this population-based data, the authors selected a total of 2663 oral cancer patients who underwent tumour resection and reconstruction. Case volume relationships were based on the following criteria; low-, medium-, high-, very high-volume surgeons were defined by or= 56 resections with reconstruction, respectively. Hierarchical linear regression analysis was subsequently performed to explore the relationship between surgeon case volume and the cost and length of hospitalisation. The mean hospitalisation cost among the 2663 patients was US$ 9528 (all costs are given in US dollars). After adjusting for physician, hospital, and patient characteristics in a hierarchical linear regression model, the cost per patient for low-volume surgeons was found to be US$ 741 (P = 0.012) higher than that for medium-volume surgeons, US$ 1546 (P < 0.001) higher than that for high-volume surgeons, and US$ 1820 (P < 0.001) higher than that for very-high-volume surgeons. After adjustment for physician, hospital, and patient characteristics, the hierarchical linear regression model revealed that the mean length of stay per patient for low-volume surgeons was the highest (P < 0.001). After adjustment for physician, hospital, and patient characteristics, low-volume surgeons performing wide excision with reconstructive surgery in oral cancer patients incurred significantly higher costs and longer hospital stays per patient than did other surgeons. Treatment strategies adopted by high- and very-high-volume surgeons should be analysed further and utilised more widely.

Evolution of conditional cooperation under multilevel selection.

PubMed

Zhang, Huanren; Perc, Matjaž

2016-03-11

We study the emergence of conditional cooperation in the presence of both intra-group and inter-group selection. Individuals play public goods games within their groups using conditional strategies, which are represented as piecewise linear response functions. Accordingly, groups engage in conflicts with a certain probability. In contrast to previous studies, we consider continuous contribution levels and a rich set of conditional strategies, allowing for a wide range of possible interactions between strategies. We find that the existence of conditional strategies enables the stabilization of cooperation even under strong intra-group selection. The strategy that eventually dominates in the population has two key properties: (i) It is unexploitable with strong intra-group selection; (ii) It can achieve full contribution to outperform other strategies in the inter-group selection. The success of this strategy is robust to initial conditions as well as changes to important parameters. We also investigate the influence of different factors on cooperation levels, including group conflicts, group size, and migration rate. Their effect on cooperation can be attributed to and explained by their influence on the relative strength of intra-group and inter-group selection.

Genomic Predictions and Genome-Wide Association Study of Resistance Against Piscirickettsia salmonis in Coho Salmon (Oncorhynchus kisutch) Using ddRAD Sequencing

PubMed Central

Barría, Agustín; Christensen, Kris A.; Yoshida, Grazyella M.; Correa, Katharina; Jedlicki, Ana; Lhorente, Jean P.; Davidson, William S.; Yáñez, José M.

2018-01-01

Piscirickettsia salmonis is one of the main infectious diseases affecting coho salmon (Oncorhynchus kisutch) farming, and current treatments have been ineffective for the control of this disease. Genetic improvement for P. salmonis resistance has been proposed as a feasible alternative for the control of this infectious disease in farmed fish. Genotyping by sequencing (GBS) strategies allow genotyping of hundreds of individuals with thousands of single nucleotide polymorphisms (SNPs), which can be used to perform genome wide association studies (GWAS) and predict genetic values using genome-wide information. We used double-digest restriction-site associated DNA (ddRAD) sequencing to dissect the genetic architecture of resistance against P. salmonis in a farmed coho salmon population and to identify molecular markers associated with the trait. We also evaluated genomic selection (GS) models in order to determine the potential to accelerate the genetic improvement of this trait by means of using genome-wide molecular information. A total of 764 individuals from 33 full-sib families (17 highly resistant and 16 highly susceptible) were experimentally challenged against P. salmonis and their genotypes were assayed using ddRAD sequencing. A total of 9,389 SNPs markers were identified in the population. These markers were used to test genomic selection models and compare different GWAS methodologies for resistance measured as day of death (DD) and binary survival (BIN). Genomic selection models showed higher accuracies than the traditional pedigree-based best linear unbiased prediction (PBLUP) method, for both DD and BIN. The models showed an improvement of up to 95% and 155% respectively over PBLUP. One SNP related with B-cell development was identified as a potential functional candidate associated with resistance to P. salmonis defined as DD. PMID:29440129

An analysis of hypercritical states in elastic and inelastic systems

NASA Astrophysics Data System (ADS)

Kowalczk, Maciej

The author raises a wide range of problems whose common characteristic is an analysis of hypercritical states in elastic and inelastic systems. the article consists of two basic parts. The first part primarily discusses problems of modelling hypercritical states, while the second analyzes numerical methods (so-called continuation methods) used to solve non-linear problems. The original approaches for modelling hypercritical states found in this article include the combination of plasticity theory and an energy condition for cracking, accounting for the variability and cyclical nature of the forms of fracture of a brittle material under a die, and the combination of plasticity theory and a simplified description of the phenomenon of localization along a discontinuity line. The author presents analytical solutions of three non-linear problems for systems made of elastic/brittle/plastic and elastic/ideally plastic materials. The author proceeds to discuss the analytical basics of continuation methods and analyzes the significance of the parameterization of non-linear problems, provides a method for selecting control parameters based on an analysis of the rank of a rectangular matrix of a uniform system of increment equations, and also provides a new method for selecting an equilibrium path originating from a bifurcation point. The author provides a general outline of continuation methods based on an analysis of the rank of a matrix of a corrective system of equations. The author supplements his theoretical solutions with numerical solutions of non-linear problems for rod systems and problems of the plastic disintegration of a notched rectangular plastic plate.

Graphene quantum dot as a green and facile sensor for free chlorine in drinking water.

PubMed

Dong, Yongqiang; Li, Geli; Zhou, Nana; Wang, Ruixue; Chi, Yuwu; Chen, Guonan

2012-10-02

Free chlorine was found to be able to destroy the passivated surface of the graphene quantum dots (GQDs) obtained by pyrolyzing citric acid, resulting in significant quenching of their fluorescence (FL) signal. After optimizing some experimental conditions (including response time, concentration of GQDs, and pH value of solution), a green and facile sensing system has been developed for the detection of free residual chlorine in water based on FL quenching of GQDs. The sensing system exhibits many advantages, such as short response time, excellent selectivity, wide linear response range, and high sensitivity. The linear response range of free chlorine (R(2) = 0.992) was from 0.05 to 10 μM. The detection limit (S/N = 3) was as low as 0.05 μM, which is much lower than that of the most widely used N-N-diethyl-p-phenylenediamine (DPD) colorimetric method. This sensing system was finally used to detect free residual chlorine in local tap water samples. The result agreed well with that by the DPD colorimetric method, suggesting the potential application of this new, green, sensitive, and facile sensing system in drinking water quality monitoring.

LOSITAN: a workbench to detect molecular adaptation based on a Fst-outlier method.

PubMed

Antao, Tiago; Lopes, Ana; Lopes, Ricardo J; Beja-Pereira, Albano; Luikart, Gordon

2008-07-28

Testing for selection is becoming one of the most important steps in the analysis of multilocus population genetics data sets. Existing applications are difficult to use, leaving many non-trivial, error-prone tasks to the user. Here we present LOSITAN, a selection detection workbench based on a well evaluated Fst-outlier detection method. LOSITAN greatly facilitates correct approximation of model parameters (e.g., genome-wide average, neutral Fst), provides data import and export functions, iterative contour smoothing and generation of graphics in a easy to use graphical user interface. LOSITAN is able to use modern multi-core processor architectures by locally parallelizing fdist, reducing computation time by half in current dual core machines and with almost linear performance gains in machines with more cores. LOSITAN makes selection detection feasible to a much wider range of users, even for large population genomic datasets, by both providing an easy to use interface and essential functionality to complete the whole selection detection process.

Discrimination of serum Raman spectroscopy between normal and colorectal cancer

NASA Astrophysics Data System (ADS)

Li, Xiaozhou; Yang, Tianyue; Yu, Ting; Li, Siqi

2011-07-01

Raman spectroscopy of tissues has been widely studied for the diagnosis of various cancers, but biofluids were seldom used as the analyte because of the low concentration. Herein, serum of 30 normal people, 46 colon cancer, and 44 rectum cancer patients were measured Raman spectra and analyzed. The information of Raman peaks (intensity and width) and that of the fluorescence background (baseline function coefficients) were selected as parameters for statistical analysis. Principal component regression (PCR) and partial least square regression (PLSR) were used on the selected parameters separately to see the performance of the parameters. PCR performed better than PLSR in our spectral data. Then linear discriminant analysis (LDA) was used on the principal components (PCs) of the two regression method on the selected parameters, and a diagnostic accuracy of 88% and 83% were obtained. The conclusion is that the selected features can maintain the information of original spectra well and Raman spectroscopy of serum has the potential for the diagnosis of colorectal cancer.

Signatures of negative selection in the genetic architecture of human complex traits.

PubMed

Zeng, Jian; de Vlaming, Ronald; Wu, Yang; Robinson, Matthew R; Lloyd-Jones, Luke R; Yengo, Loic; Yap, Chloe X; Xue, Angli; Sidorenko, Julia; McRae, Allan F; Powell, Joseph E; Montgomery, Grant W; Metspalu, Andres; Esko, Tonu; Gibson, Greg; Wray, Naomi R; Visscher, Peter M; Yang, Jian

2018-05-01

We develop a Bayesian mixed linear model that simultaneously estimates single-nucleotide polymorphism (SNP)-based heritability, polygenicity (proportion of SNPs with nonzero effects), and the relationship between SNP effect size and minor allele frequency for complex traits in conventionally unrelated individuals using genome-wide SNP data. We apply the method to 28 complex traits in the UK Biobank data (N = 126,752) and show that on average, 6% of SNPs have nonzero effects, which in total explain 22% of phenotypic variance. We detect significant (P < 0.05/28) signatures of natural selection in the genetic architecture of 23 traits, including reproductive, cardiovascular, and anthropometric traits, as well as educational attainment. The significant estimates of the relationship between effect size and minor allele frequency in complex traits are consistent with a model of negative (or purifying) selection, as confirmed by forward simulation. We conclude that negative selection acts pervasively on the genetic variants associated with human complex traits.

Wide Linear Corticotomy and Anterior Segmental Osteotomy Under Local Anesthesia Combined Corticision for Correcting Severe Anterior Protrusion With Insufficient Alveolar Housing.

PubMed

Noh, Min-Ki; Lee, Baek-Soo; Kim, Shin-Yeop; Jeon, Hyeran Helen; Kim, Seong-Hun; Nelson, Gerald

2017-11-01

This article presents an alternate surgical treatment method to correct a severe anterior protrusion in an adult patient with an extremely thin alveolus. To accomplish an effective and efficient anterior segmental retraction without periodontal complications, the authors performed, under local anesthesia, a wide linear corticotomy and corticision in the maxilla and an anterior segmental osteotomy in mandible. In the maxilla, a wide linear corticotomy was performed under local anesthesia. In the maxillary first premolar area, a wide section of cortical bone was removed. Retraction forces were applied buccolingually with the aid of temporary skeletal anchorage devices. Corticision was later performed to close residual extraction space. In the mandible, an anterior segmental osteotomy was performed and the first premolars were extracted under local anesthesia. In the maxilla, a wide linear corticotomy facilitated a bony block movement with temporary skeletal anchorage devices, without complications. The remaining extraction space after the bony block movement was closed effectively, accelerated by corticision. In the mandible, anterior segmental retraction was facilitated by an anterior segmental osteotomy performed under local anesthesia. Corticision was later employed to accelerate individual tooth movements. A wide linear corticotomy and an anterior segmental osteotomy combined with corticision can be an effective and efficient alternative to conventional orthodontic treatment in the bialveolar protrusion patient with an extremely thin alveolar housing.

Genome wide selection in Citrus breeding.

PubMed

Gois, I B; Borém, A; Cristofani-Yaly, M; de Resende, M D V; Azevedo, C F; Bastianel, M; Novelli, V M; Machado, M A

2016-10-17

Genome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seq TM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus.

Citalopram and escitalopram plasma drug and metabolite concentrations: genome-wide associations

PubMed Central

Ji, Yuan; Schaid, Daniel J; Desta, Zeruesenay; Kubo, Michiaki; Batzler, Anthony J; Snyder, Karen; Mushiroda, Taisei; Kamatani, Naoyuki; Ogburn, Evan; Hall-Flavin, Daniel; Flockhart, David; Nakamura, Yusuke; Mrazek, David A; Weinshilboum, Richard M

2014-01-01

Aims Citalopram (CT) and escitalopram (S-CT) are among the most widely prescribed selective serotonin reuptake inhibitors used to treat major depressive disorder (MDD). We applied a genome-wide association study to identify genetic factors that contribute to variation in plasma concentrations of CT or S-CT and their metabolites in MDD patients treated with CT or S-CT. Methods Our genome-wide association study was performed using samples from 435 MDD patients. Linear mixed models were used to account for within-subject correlations of longitudinal measures of plasma drug/metabolite concentrations (4 and 8 weeks after the initiation of drug therapy), and single-nucleotide polymorphisms (SNPs) were modelled as additive allelic effects. Results Genome-wide significant associations were observed for S-CT concentration with SNPs in or near the CYP2C19 gene on chromosome 10 (rs1074145, P = 4.1 × 10−9) and with S-didesmethylcitalopram concentration for SNPs near the CYP2D6 locus on chromosome 22 (rs1065852, P = 2.0 × 10−16), supporting the important role of these cytochrome P450 (CYP) enzymes in biotransformation of citalopram. After adjustment for the effect of CYP2C19 functional alleles, the analyses also identified novel loci that will require future replication and functional validation. Conclusions In vitro and in vivo studies have suggested that the biotransformation of CT to monodesmethylcitalopram and didesmethylcitalopram is mediated by CYP isozymes. The results of our genome-wide association study performed in MDD patients treated with CT or S-CT have confirmed those observations but also identified novel genomic loci that might play a role in variation in plasma levels of CT or its metabolites during the treatment of MDD patients with these selective serotonin reuptake inhibitors. PMID:24528284

Citalopram and escitalopram plasma drug and metabolite concentrations: genome-wide associations.

PubMed

Ji, Yuan; Schaid, Daniel J; Desta, Zeruesenay; Kubo, Michiaki; Batzler, Anthony J; Snyder, Karen; Mushiroda, Taisei; Kamatani, Naoyuki; Ogburn, Evan; Hall-Flavin, Daniel; Flockhart, David; Nakamura, Yusuke; Mrazek, David A; Weinshilboum, Richard M

2014-08-01

Citalopram (CT) and escitalopram (S-CT) are among the most widely prescribed selective serotonin reuptake inhibitors used to treat major depressive disorder (MDD). We applied a genome-wide association study to identify genetic factors that contribute to variation in plasma concentrations of CT or S-CT and their metabolites in MDD patients treated with CT or S-CT. Our genome-wide association study was performed using samples from 435 MDD patients. Linear mixed models were used to account for within-subject correlations of longitudinal measures of plasma drug/metabolite concentrations (4 and 8 weeks after the initiation of drug therapy), and single-nucleotide polymorphisms (SNPs) were modelled as additive allelic effects. Genome-wide significant associations were observed for S-CT concentration with SNPs in or near the CYP2C19 gene on chromosome 10 (rs1074145, P = 4.1 × 10(-9) ) and with S-didesmethylcitalopram concentration for SNPs near the CYP2D6 locus on chromosome 22 (rs1065852, P = 2.0 × 10(-16) ), supporting the important role of these cytochrome P450 (CYP) enzymes in biotransformation of citalopram. After adjustment for the effect of CYP2C19 functional alleles, the analyses also identified novel loci that will require future replication and functional validation. In vitro and in vivo studies have suggested that the biotransformation of CT to monodesmethylcitalopram and didesmethylcitalopram is mediated by CYP isozymes. The results of our genome-wide association study performed in MDD patients treated with CT or S-CT have confirmed those observations but also identified novel genomic loci that might play a role in variation in plasma levels of CT or its metabolites during the treatment of MDD patients with these selective serotonin reuptake inhibitors. © 2014 The British Pharmacological Society.

Selective optical sensing of biothiols with Ellman's reagent: 5,5'-Dithio-bis(2-nitrobenzoic acid)-modified gold nanoparticles.

PubMed

Güçlü, Kubilay; Ozyürek, Mustafa; Güngör, Nilay; Baki, Sefa; Apak, Reşat

2013-09-10

Development of sensitive and selective methods of determination for biothiols is important because of their significant roles in biological systems. We present a new optical sensor using Ellman's reagent (DTNB)-adsorbed gold nanoparticles (Au-NPs) (DTNB-Au-NP) in a colloidal solution devised to selectively determine biologically important thiols (biothiols) from biological samples and pharmaceuticals. 5,5'-Dithio-bis(2-nitrobenzoic acid) (DTNB), a versatile water-soluble compound for quantitating free sulfhydryl groups in solution, was adsorbed through non-covalent interaction onto Au-NPs, and the absorbance changes associated with the formation of the yellow-colored 5-thio-2-nitrobenzoate (TNB(2-)) anion as a result of reaction with biothiols was measured at 410nm. The sensor gave a linear response over a wide concentration range of standard biothiols comprising cysteine, glutathione, homocysteine, cysteamine, dihydrolipoic acid and 1,4-dithioerythritol. The calibration curves of individual biothiols were constructed, and their molar absorptivities and linear concentration ranges determined. The cysteine equivalent thiol content (CETC) values of various biothiols using the DTNB-Au-NP assay were comparable to those of the conventional DTNB assay, showing that the immobilized DTNB reagent retained its reactivity toward thiols. Common biological sample ingredients like amino acids, flavonoids, vitamins, and plasma antioxidants did not interfere with the proposed sensing method. This assay was validated through linearity, additivity, precision and recovery, demonstrating that the assay is reliable and robust. DTNB-adsorbed Au-NPs probes provided higher sensitivity (i.e., lower detection limits) in biothiol determination than conventional DTNB reagent. Under optimized conditions, cysteine (Cys) was quantified by the proposed assay, with a detection limit (LOD) of 0.57μM and acceptable linearity ranging from 0.4 to 29.0μM (r=0.998). Copyright © 2013 Elsevier B.V. All rights reserved.

The Synaptic and Morphological Basis of Orientation Selectivity in a Polyaxonal Amacrine Cell of the Rabbit Retina.

PubMed

Murphy-Baum, Benjamin L; Taylor, W Rowland

2015-09-30

Much of the computational power of the retina derives from the activity of amacrine cells, a large and diverse group of GABAergic and glycinergic inhibitory interneurons. Here, we identify an ON-type orientation-selective, wide-field, polyaxonal amacrine cell (PAC) in the rabbit retina and demonstrate how its orientation selectivity arises from the structure of the dendritic arbor and the pattern of excitatory and inhibitory inputs. Excitation from ON bipolar cells and inhibition arising from the OFF pathway converge to generate a quasi-linear integration of visual signals in the receptive field center. This serves to suppress responses to high spatial frequencies, thereby improving sensitivity to larger objects and enhancing orientation selectivity. Inhibition also regulates the magnitude and time course of excitatory inputs to this PAC through serial inhibitory connections onto the presynaptic terminals of ON bipolar cells. This presynaptic inhibition is driven by graded potentials within local microcircuits, similar in extent to the size of single bipolar cell receptive fields. Additional presynaptic inhibition is generated by spiking amacrine cells on a larger spatial scale covering several hundred microns. The orientation selectivity of this PAC may be a substrate for the inhibition that mediates orientation selectivity in some types of ganglion cells. Significance statement: The retina comprises numerous excitatory and inhibitory circuits that encode specific features in the visual scene, such as orientation, contrast, or motion. Here, we identify a wide-field inhibitory neuron that responds to visual stimuli of a particular orientation, a feature selectivity that is primarily due to the elongated shape of the dendritic arbor. Integration of convergent excitatory and inhibitory inputs from the ON and OFF visual pathways suppress responses to small objects and fine textures, thus enhancing selectivity for larger objects. Feedback inhibition regulates the strength and speed of excitation on both local and wide-field spatial scales. This study demonstrates how different synaptic inputs are regulated to tune a neuron to respond to specific features in the visual scene. Copyright © 2015 the authors 0270-6474/15/3513336-15$15.00/0.

Analysis of the load selection on the error of source characteristics identification for an engine exhaust system

NASA Astrophysics Data System (ADS)

Zheng, Sifa; Liu, Haitao; Dan, Jiabi; Lian, Xiaomin

2015-05-01

Linear time-invariant assumption for the determination of acoustic source characteristics, the source strength and the source impedance in the frequency domain has been proved reasonable in the design of an exhaust system. Different methods have been proposed to its identification and the multi-load method is widely used for its convenience by varying the load number and impedance. Theoretical error analysis has rarely been referred to and previous results have shown an overdetermined set of open pipes can reduce the identification error. This paper contributes a theoretical error analysis for the load selection. The relationships between the error in the identification of source characteristics and the load selection were analysed. A general linear time-invariant model was built based on the four-load method. To analyse the error of the source impedance, an error estimation function was proposed. The dispersion of the source pressure was obtained by an inverse calculation as an indicator to detect the accuracy of the results. It was found that for a certain load length, the load resistance at the frequency points of one-quarter wavelength of odd multiples results in peaks and in the maximum error for source impedance identification. Therefore, the load impedance of frequency range within the one-quarter wavelength of odd multiples should not be used for source impedance identification. If the selected loads have more similar resistance values (i.e., the same order of magnitude), the identification error of the source impedance could be effectively reduced.

pLARmEB: integration of least angle regression with empirical Bayes for multilocus genome-wide association studies.

PubMed

Zhang, J; Feng, J-Y; Ni, Y-L; Wen, Y-J; Niu, Y; Tamba, C L; Yue, C; Song, Q; Zhang, Y-M

2017-06-01

Multilocus genome-wide association studies (GWAS) have become the state-of-the-art procedure to identify quantitative trait nucleotides (QTNs) associated with complex traits. However, implementation of multilocus model in GWAS is still difficult. In this study, we integrated least angle regression with empirical Bayes to perform multilocus GWAS under polygenic background control. We used an algorithm of model transformation that whitened the covariance matrix of the polygenic matrix K and environmental noise. Markers on one chromosome were included simultaneously in a multilocus model and least angle regression was used to select the most potentially associated single-nucleotide polymorphisms (SNPs), whereas the markers on the other chromosomes were used to calculate kinship matrix as polygenic background control. The selected SNPs in multilocus model were further detected for their association with the trait by empirical Bayes and likelihood ratio test. We herein refer to this method as the pLARmEB (polygenic-background-control-based least angle regression plus empirical Bayes). Results from simulation studies showed that pLARmEB was more powerful in QTN detection and more accurate in QTN effect estimation, had less false positive rate and required less computing time than Bayesian hierarchical generalized linear model, efficient mixed model association (EMMA) and least angle regression plus empirical Bayes. pLARmEB, multilocus random-SNP-effect mixed linear model and fast multilocus random-SNP-effect EMMA methods had almost equal power of QTN detection in simulation experiments. However, only pLARmEB identified 48 previously reported genes for 7 flowering time-related traits in Arabidopsis thaliana.

Construction of a new Cu2+ coated wire ion selective electrode based on 2-((2-(2-(2-(2-hydroxy-5-methoxybenzylidene amino)phenyl)disufanyl)phenylimino)methyl)-4-methoxyphenol Schiff base.

PubMed

Shokrollahi, A; Abbaspour, A; Ghaedi, M; Haghighi, A Naghashian; Kianfar, A H; Ranjbar, M

2011-03-15

In this article a new coated platinum Cu(2+) ion selective electrode based on 2-((2-(2-(2-(2-hydroxy-5-methoxybenzylideneamino)phenyl)disufanyl)phenylimino) methyl)-4-methoxyphenol Schiff base (L(1)) as a new ionophore is described. This sensor has a wide linear range of concentration (1.2 × 10(-7)-1.0 × 10(-1) mol L(-1)) and a low detection limit of 9.8 × 10(-8) mol L(-1)of Cu(NO(3))(2). It has a Nernstian response with slope of 29.54 ± 1.62 mV decade(-1) and it is applicable in the pH range of 4.0-6.0 without any divergence in potential. The coated electrode has a short response time of approximately 9s and is stable at least for 3.5 months. The electrode shows a good selectivity for Cu(2+) ion toward a wide variety of metal ions. The proposed sensor was successfully applied for the determination of Cu(2+) ion in different real and environmental samples and as indicator electrode for potentiometric titration of Cu(2+) ion with EDTA. Copyright © 2010 Elsevier B.V. All rights reserved.

Decision-Related Activity in Macaque V2 for Fine Disparity Discrimination Is Not Compatible with Optimal Linear Readout

PubMed Central

Clery, Stephane; Cumming, Bruce G.

2017-01-01

Fine judgments of stereoscopic depth rely mainly on relative judgments of depth (relative binocular disparity) between objects, rather than judgments of the distance to where the eyes are fixating (absolute disparity). In macaques, visual area V2 is the earliest site in the visual processing hierarchy for which neurons selective for relative disparity have been observed (Thomas et al., 2002). Here, we found that, in macaques trained to perform a fine disparity discrimination task, disparity-selective neurons in V2 were highly selective for the task, and their activity correlated with the animals' perceptual decisions (unexplained by the stimulus). This may partially explain similar correlations reported in downstream areas. Although compatible with a perceptual role of these neurons for the task, the interpretation of such decision-related activity is complicated by the effects of interneuronal “noise” correlations between sensory neurons. Recent work has developed simple predictions to differentiate decoding schemes (Pitkow et al., 2015) without needing measures of noise correlations, and found that data from early sensory areas were compatible with optimal linear readout of populations with information-limiting correlations. In contrast, our data here deviated significantly from these predictions. We additionally tested this prediction for previously reported results of decision-related activity in V2 for a related task, coarse disparity discrimination (Nienborg and Cumming, 2006), thought to rely on absolute disparity. Although these data followed the predicted pattern, they violated the prediction quantitatively. This suggests that optimal linear decoding of sensory signals is not generally a good predictor of behavior in simple perceptual tasks. SIGNIFICANCE STATEMENT Activity in sensory neurons that correlates with an animal's decision is widely believed to provide insights into how the brain uses information from sensory neurons. Recent theoretical work developed simple predictions to differentiate decoding schemes, and found support for optimal linear readout of early sensory populations with information-limiting correlations. Here, we observed decision-related activity for neurons in visual area V2 of macaques performing fine disparity discrimination, as yet the earliest site for this task. These findings, and previously reported results from V2 in a different task, deviated from the predictions for optimal linear readout of a population with information-limiting correlations. Our results suggest that optimal linear decoding of early sensory information is not a general decoding strategy used by the brain. PMID:28100751

Diverse alternative back-splicing and alternative splicing landscape of circular RNAs

PubMed Central

Zhang, Xiao-Ou; Dong, Rui; Zhang, Yang; Zhang, Jia-Lin; Luo, Zheng; Zhang, Jun; Chen, Ling-Ling; Yang, Li

2016-01-01

Circular RNAs (circRNAs) derived from back-spliced exons have been widely identified as being co-expressed with their linear counterparts. A single gene locus can produce multiple circRNAs through alternative back-splice site selection and/or alternative splice site selection; however, a detailed map of alternative back-splicing/splicing in circRNAs is lacking. Here, with the upgraded CIRCexplorer2 pipeline, we systematically annotated different types of alternative back-splicing and alternative splicing events in circRNAs from various cell lines. Compared with their linear cognate RNAs, circRNAs exhibited distinct patterns of alternative back-splicing and alternative splicing. Alternative back-splice site selection was correlated with the competition of putative RNA pairs across introns that bracket alternative back-splice sites. In addition, all four basic types of alternative splicing that have been identified in the (linear) mRNA process were found within circRNAs, and many exons were predominantly spliced in circRNAs. Unexpectedly, thousands of previously unannotated exons were detected in circRNAs from the examined cell lines. Although these novel exons had similar splice site strength, they were much less conserved than known exons in sequences. Finally, both alternative back-splicing and circRNA-predominant alternative splicing were highly diverse among the examined cell lines. All of the identified alternative back-splicing and alternative splicing in circRNAs are available in the CIRCpedia database (http://www.picb.ac.cn/rnomics/circpedia). Collectively, the annotation of alternative back-splicing and alternative splicing in circRNAs provides a valuable resource for depicting the complexity of circRNA biogenesis and for studying the potential functions of circRNAs in different cells. PMID:27365365

A simple and selective method for the measurement of azadirachtin and related azadirachtoid levels in fruits and vegetables using liquid chromatography electrospray ionization tandem mass spectrometry.

PubMed

Sarais, Giorgia; Caboni, Pierluigi; Sarritzu, Erika; Russo, Mariateresa; Cabras, Paolo

2008-05-14

Neem-based insecticides containing azadirachtin and related azadirachtoids are widely used in agriculture. Here, we report an analytical method for the rapid and accurate quantification of the insecticide azadirachtin A and B and other azadirachtoids such as salannin, nimbin, and their deacetylated analogues on tomatoes and peaches. Azadirachtoids were extracted from fruits and vegetables with acetonitrile. Using high-performance liquid chromatography/electrospray ionization tandem mass spectrometer, azadirachtoids were selectively detected monitoring the multiple reaction transitions of sodium adduct precursor ions. For azadirachtin A, calibration was linear over a working range of 1-1000 microg/L with r > 0.996. The limit of detection and limit of quantification for azadirachtin A were 0.4 and 0.8 microg/kg, respectively. The presence of interfering compounds in the peach and tomato extracts was evaluated and found to be minimal. Because of the linear behavior, it was concluded that the multiple reaction transitions of sodium adduct ions can be used for analytical purposes, that is, for the identification and quantification of azadirachtin A and B and related azadirachtoids in fruit and vegetable extracts at trace levels.

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3

NASA Technical Reports Server (NTRS)

Lin, Shu

1998-01-01

Decoding algorithms based on the trellis representation of a code (block or convolutional) drastically reduce decoding complexity. The best known and most commonly used trellis-based decoding algorithm is the Viterbi algorithm. It is a maximum likelihood decoding algorithm. Convolutional codes with the Viterbi decoding have been widely used for error control in digital communications over the last two decades. This chapter is concerned with the application of the Viterbi decoding algorithm to linear block codes. First, the Viterbi algorithm is presented. Then, optimum sectionalization of a trellis to minimize the computational complexity of a Viterbi decoder is discussed and an algorithm is presented. Some design issues for IC (integrated circuit) implementation of a Viterbi decoder are considered and discussed. Finally, a new decoding algorithm based on the principle of compare-select-add is presented. This new algorithm can be applied to both block and convolutional codes and is more efficient than the conventional Viterbi algorithm based on the add-compare-select principle. This algorithm is particularly efficient for rate 1/n antipodal convolutional codes and their high-rate punctured codes. It reduces computational complexity by one-third compared with the Viterbi algorithm.

A highly sensitive and selective detection of Cr(VI) and ascorbic acid based on nitrogen-doped carbon dots.

PubMed

Zhang, Yuhua; Fang, Xian; Zhao, Hong; Li, Zengxi

2018-05-01

A highly sensitive and selective detection of hexavalent chromium (Cr(VI)) and ascorbic acid (AA) was proposed using nitrogen-doped carbon dots (N-CDs). In the absence of AA, the quantitative detection of Cr(VI) was realized through Cr(VI) acting as a quencher to quench the fluorescence of N-CDs by inner filter effect (IFE) and static quenching effect. Under the optimal conditions, the linear range for Cr(VI) detection was from 0.01 to 250μM with a detection limit of 5nM (S/N = 3). In the presence of AA, the fluorescence intensity could be rapidly enhanced compared with the fluorescence of N-CDs/Cr(VI) system since Cr(VI) can be reduced into trivalent chromium (Cr(III)) by AA. And a wide linear range for AA detection was obtained from 1 to 750μM. The detection limit was 0.3μM (S/N = 3). More importantly, this method can be successfully applied to the detection of Cr(VI) in real water samples, and AA in vitamins C tablets and human serum sample. Copyright © 2018 Elsevier B.V. All rights reserved.

Development of Monoclonal Antibodies Recognizing Linear Epitope: Illustration by Three Bacillus thuringiensis Crystal Proteins of Genetically Modified Cotton, Maize, and Tobacco.

PubMed

Cao, Zhen; Zhang, Wei; Ning, Xiangxue; Wang, Baomin; Liu, Yunjun; Li, Qing X

2017-11-22

Bacillus thuringiensis Cry1Ac, Cry1Ia1, and Cry1Ie are δ-endotoxin insecticidal proteins widely implemented in genetically modified organisms (GMO), such as cotton, maize, and potato. Western blot assay integrates electrophoresis separation power and antibody high specificity for monitoring specific exogenous proteins expressed in GMO. Procedures for evoking monoclonal antibody (mAb) for Western blot were poorly documented. In the present study, Cry1Ac partially denatured at 100 °C for 5 min was used as an immunogen to develop mAbs selectively recognizing a linear epitope of Cry1Ac for Western blot. mAb 5E9C6 and 3E6E2 selected with sandwich ELISA strongly recognized the heat semidenatured Cry1Ac. Particularly, 3E6E2 recognized both E. coli and cotton seed expressed Cry1Ac in Western blot. Such strategy of using partially denatured proteins as immunogens and using sandwich ELISA for mAb screening was also successfully demonstrated with production of mAbs against Cry1Ie for Western blot assay in maize.

Designing of fluorescent and magnetic imprinted polymer for rapid, selective and sensitive detection of imidacloprid via activators regenerated by the electron transfer-atom transfer radical polymerization (ARGET-ATRP) technique

NASA Astrophysics Data System (ADS)

Kumar, Sunil; Karfa, Paramita; Madhuri, Rashmi; Sharma, Prashant K.

2018-05-01

In this work, we report on a dual-behavior electrochemical/optical sensor for sensitive determination of Imidacloprid by fluorescent dye (fluorescein, FL) and imprinted polymer modified europium doped superparamagnetic iron oxide nanoparticles (FL@SPIONs@MIP). The imidacloprid (IMD)-imprinted polymer was directly synthesized on the Eu-SPIONs surface via Activators regenerated by the electron transfer-atom transfer radical polymerization (ARGET-ATRP) technique. Preparation, characterization and application of the prepared FL@SPIONs@MIP were systematically investigated using scanning electron microscopy (SEM), X-ray diffraction (XRD), vibrating sample magnetometer (VSM), fluorescence spectroscopy and electrochemical techniques. The electrochemical experiments exhibited a remarkable selectivity of the prepared sensor towards IMD. Determination of IMD by the square wave stripping voltammetry method represented a wide linear range of 0.059-0.791 μg L-1 with a detection limit of 0.0125 μg L-1. In addition, the fluorescence method shows a linear range of 0.039-0.942 μg L-1 and LOD of 0.0108 μg L-1. The fluorescence property of prepared FL@SPIONs@MIP was used for rapid, on-spot but selective detection of IMD in real samples. The proposed electrode displayed excellent repeatability and long-term stability and was successfully applied for quantitative and trace level determination of IMD in several real samples.

Copula Entropy coupled with Wavelet Neural Network Model for Hydrological Prediction

NASA Astrophysics Data System (ADS)

Wang, Yin; Yue, JiGuang; Liu, ShuGuang; Wang, Li

2018-02-01

Artificial Neural network(ANN) has been widely used in hydrological forecasting. in this paper an attempt has been made to find an alternative method for hydrological prediction by combining Copula Entropy(CE) with Wavelet Neural Network(WNN), CE theory permits to calculate mutual information(MI) to select Input variables which avoids the limitations of the traditional linear correlation(LCC) analysis. Wavelet analysis can provide the exact locality of any changes in the dynamical patterns of the sequence Coupled with ANN Strong non-linear fitting ability. WNN model was able to provide a good fit with the hydrological data. finally, the hybrid model(CE+WNN) have been applied to daily water level of Taihu Lake Basin, and compared with CE ANN, LCC WNN and LCC ANN. Results showed that the hybrid model produced better results in estimating the hydrograph properties than the latter models.

Novel polymeric monolith materials with a β-cyclodextrin-graphene composite for the highly selective extraction of methyl jasmonate.

PubMed

Yu, Xinhong; Ling, Xu; Zou, Li; Chen, Zilin

2017-04-01

A novel polymeric monolith column with a  β-cyclodextrin-graphene composite was prepared for extraction of methyl jasmonate. A simple, sensitive, and effective polymeric monolith microextraction with high-performance liquid chromatography method has been presented for the determination. To carry out the best microextraction efficiency, several parameters such as sample flow rate, sample volume, and sample pH value were systematically optimized. In addition, the method validation showed a wide linear range of 5-2000 ng/mL, with a good linearity and low limits of detection for methyl jasmonate. The proposed method was successfully applied for the determination of methyl jasmonate in wintersweet flowers with recoveries of 90.67%. The result was confirmed by high-performance liquid chromatography with mass spectrometry. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Global quasi-linearization (GQL) versus QSSA for a hydrogen-air auto-ignition problem.

PubMed

Yu, Chunkan; Bykov, Viatcheslav; Maas, Ulrich

2018-04-25

A recently developed automatic reduction method for systems of chemical kinetics, the so-called Global Quasi-Linearization (GQL) method, has been implemented to study and reduce the dimensions of a homogeneous combustion system. The results of application of the GQL and the Quasi-Steady State Assumption (QSSA) are compared. A number of drawbacks of the QSSA are discussed, i.e. the selection criteria of QSS-species and its sensitivity to system parameters, initial conditions, etc. To overcome these drawbacks, the GQL approach has been developed as a robust, automatic and scaling invariant method for a global analysis of the system timescale hierarchy and subsequent model reduction. In this work the auto-ignition problem of the hydrogen-air system is considered in a wide range of system parameters and initial conditions. The potential of the suggested approach to overcome most of the drawbacks of the standard approaches is illustrated.

Genome-wide association and genomic prediction of resistance to viral nervous necrosis in European sea bass (Dicentrarchus labrax) using RAD sequencing.

PubMed

Palaiokostas, Christos; Cariou, Sophie; Bestin, Anastasia; Bruant, Jean-Sebastien; Haffray, Pierrick; Morin, Thierry; Cabon, Joëlle; Allal, François; Vandeputte, Marc; Houston, Ross D

2018-06-08

European sea bass (Dicentrarchus labrax) is one of the most important species for European aquaculture. Viral nervous necrosis (VNN), commonly caused by the redspotted grouper nervous necrosis virus (RGNNV), can result in high levels of morbidity and mortality, mainly during the larval and juvenile stages of cultured sea bass. In the absence of efficient therapeutic treatments, selective breeding for host resistance offers a promising strategy to control this disease. Our study aimed at investigating genetic resistance to VNN and genomic-based approaches to improve disease resistance by selective breeding. A population of 1538 sea bass juveniles from a factorial cross between 48 sires and 17 dams was challenged with RGNNV with mortalities and survivors being recorded and sampled for genotyping by the RAD sequencing approach. We used genome-wide genotype data from 9195 single nucleotide polymorphisms (SNPs) for downstream analysis. Estimates of heritability of survival on the underlying scale for the pedigree and genomic relationship matrices were 0.27 (HPD interval 95%: 0.14-0.40) and 0.43 (0.29-0.57), respectively. Classical genome-wide association analysis detected genome-wide significant quantitative trait loci (QTL) for resistance to VNN on chromosomes (unassigned scaffolds in the case of 'chromosome' 25) 3, 20 and 25 (P < 1e06). Weighted genomic best linear unbiased predictor provided additional support for the QTL on chromosome 3 and suggested that it explained 4% of the additive genetic variation. Genomic prediction approaches were tested to investigate the potential of using genome-wide SNP data to estimate breeding values for resistance to VNN and showed that genomic prediction resulted in a 13% increase in successful classification of resistant and susceptible animals compared to pedigree-based methods, with Bayes A and Bayes B giving the highest predictive ability. Genome-wide significant QTL were identified but each with relatively small effects on the trait. Tests of genomic prediction suggested that incorporating genome-wide SNP data is likely to result in higher accuracy of estimated breeding values for resistance to VNN. RAD sequencing is an effective method for generating such genome-wide SNPs, and our findings highlight the potential of genomic selection to breed farmed European sea bass with improved resistance to VNN.

A Highly Linear and Wide Input Range Four-Quadrant CMOS Analog Multiplier Using Active Feedback

NASA Astrophysics Data System (ADS)

Huang, Zhangcai; Jiang, Minglu; Inoue, Yasuaki

Analog multipliers are one of the most important building blocks in analog signal processing circuits. The performance with high linearity and wide input range is usually required for analog four-quadrant multipliers in most applications. Therefore, a highly linear and wide input range four-quadrant CMOS analog multiplier using active feedback is proposed in this paper. Firstly, a novel configuration of four-quadrant multiplier cell is presented. Its input dynamic range and linearity are improved significantly by adding two resistors compared with the conventional structure. Then based on the proposed multiplier cell configuration, a four-quadrant CMOS analog multiplier with active feedback technique is implemented by two operational amplifiers. Because of both the proposed multiplier cell and active feedback technique, the proposed multiplier achieves a much wider input range with higher linearity than conventional structures. The proposed multiplier was fabricated by a 0.6µm CMOS process. Experimental results show that the input range of the proposed multiplier can be up to 5.6Vpp with 0.159% linearity error on VX and 4.8Vpp with 0.51% linearity error on VY for ±2.5V power supply voltages, respectively.

In situ electrochemical synthesis of highly loaded zirconium nanoparticles decorated reduced graphene oxide for the selective determination of dopamine and paracetamol in presence of ascorbic acid.

PubMed

Ezhil Vilian, A T; Rajkumar, Muniyandi; Chen, Shen-Ming

2014-03-01

Highly loaded zirconium oxide (ZrO2) nanoparticles were supported on graphene oxide (ERGO/ZrO2) via an in situ, simple and clean strategy on the basis of the electrochemical redox reaction between zirconyl chloride and graphene oxide (ZrOCl2 and GO). The electrochemical measurements and surface morphology of the as prepared nanocomposite were studied using cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and field emission scanning electron microscopy (FESEM). This ZrO2 decorated reduced graphene oxide nanocomposite modified GCE (ERGO/ZrO2) exhibits a prominent electrocatalytic activity toward the selective detection and determination of dopamine (DA) and paracetamol (PA) in presence of ascorbic acid (AA). The peaks of linear sweep voltammetry (LSV) for DA and PA oxidation at ERGO/ZrO2 modified electrode surface were clearly separated from each other when they co-existed in the physiological pH (pH 7.0) with a potential value of 140 mV (between AA and DA) and 330 mV (between AA and PA). It was, therefore, possible to simultaneously determine DA and PA in the samples at ERGO/ZrO2 nanocomposite modified GCE. Linear calibration curves were obtained for 9-237 μM of PA and DA. The ERGO/ZrO2 nanocomposite electrode has been satisfactorily used for the determination of DA and PA in the presence of AA at pharmaceutical formulations in human urine samples with a linear range of 3-174 μM. The proposed biosensor shows a wide linear range, low detection limit, good reproducibility and acceptable stability, providing a biocompatible platform for bio sensing and bio catalysis. Copyright © 2013 Elsevier B.V. All rights reserved.

A systems wide mass spectrometric based linear motif screen to identify dominant in-vivo interacting proteins for the ubiquitin ligase MDM2.

PubMed

Nicholson, Judith; Scherl, Alex; Way, Luke; Blackburn, Elizabeth A; Walkinshaw, Malcolm D; Ball, Kathryn L; Hupp, Ted R

2014-06-01

Linear motifs mediate protein-protein interactions (PPI) that allow expansion of a target protein interactome at a systems level. This study uses a proteomics approach and linear motif sub-stratifications to expand on PPIs of MDM2. MDM2 is a multi-functional protein with over one hundred known binding partners not stratified by hierarchy or function. A new linear motif based on a MDM2 interaction consensus is used to select novel MDM2 interactors based on Nutlin-3 responsiveness in a cell-based proteomics screen. MDM2 binds a subset of peptide motifs corresponding to real proteins with a range of allosteric responses to MDM2 ligands. We validate cyclophilin B as a novel protein with a consensus MDM2 binding motif that is stabilised by Nutlin-3 in vivo, thus identifying one of the few known interactors of MDM2 that is stabilised by Nutlin-3. These data invoke two modes of peptide binding at the MDM2 N-terminus that rely on a consensus core motif to control the equilibrium between MDM2 binding proteins. This approach stratifies MDM2 interacting proteins based on the linear motif feature and provides a new biomarker assay to define clinically relevant Nutlin-3 responsive MDM2 interactors. Copyright © 2014 Elsevier Inc. All rights reserved.

Genome-wide association analysis for feed efficiency in Angus cattle.

PubMed

Rolf, M M; Taylor, J F; Schnabel, R D; McKay, S D; McClure, M C; Northcutt, S L; Kerley, M S; Weaber, R L

2012-08-01

Estimated breeding values for average daily feed intake (AFI; kg/day), residual feed intake (RFI; kg/day) and average daily gain (ADG; kg/day) were generated using a mixed linear model incorporating genomic relationships for 698 Angus steers genotyped with the Illumina BovineSNP50 assay. Association analyses of estimated breeding values (EBVs) were performed for 41,028 single nucleotide polymorphisms (SNPs), and permutation analysis was used to empirically establish the genome-wide significance threshold (P < 0.05) for each trait. SNPs significantly associated with each trait were used in a forward selection algorithm to identify genomic regions putatively harbouring genes with effects on each trait. A total of 53, 66 and 68 SNPs explained 54.12% (24.10%), 62.69% (29.85%) and 55.13% (26.54%) of the additive genetic variation (when accounting for the genomic relationships) in steer breeding values for AFI, RFI and ADG, respectively, within this population. Evaluation by pathway analysis revealed that many of these SNPs are in genomic regions that harbour genes with metabolic functions. The presence of genetic correlations between traits resulted in 13.2% of SNPs selected for AFI and 4.5% of SNPs selected for RFI also being selected for ADG in the analysis of breeding values. While our study identifies panels of SNPs significant for efficiency traits in our population, validation of all SNPs in independent populations will be necessary before commercialization. © 2011 The Authors, Animal Genetics © 2011 Stichting International Foundation for Animal Genetics.

Linear and nonlinear variable selection in competing risks data.

PubMed

Ren, Xiaowei; Li, Shanshan; Shen, Changyu; Yu, Zhangsheng

2018-06-15

Subdistribution hazard model for competing risks data has been applied extensively in clinical researches. Variable selection methods of linear effects for competing risks data have been studied in the past decade. There is no existing work on selection of potential nonlinear effects for subdistribution hazard model. We propose a two-stage procedure to select the linear and nonlinear covariate(s) simultaneously and estimate the selected covariate effect(s). We use spectral decomposition approach to distinguish the linear and nonlinear parts of each covariate and adaptive LASSO to select each of the 2 components. Extensive numerical studies are conducted to demonstrate that the proposed procedure can achieve good selection accuracy in the first stage and small estimation biases in the second stage. The proposed method is applied to analyze a cardiovascular disease data set with competing death causes. Copyright © 2018 John Wiley & Sons, Ltd.

Accommodation of practical constraints by a linear programming jet select. [for Space Shuttle

NASA Technical Reports Server (NTRS)

Bergmann, E.; Weiler, P.

1983-01-01

An experimental spacecraft control system will be incorporated into the Space Shuttle flight software and exercised during a forthcoming mission to evaluate its performance and handling qualities. The control system incorporates a 'phase space' control law to generate rate change requests and a linear programming jet select to compute jet firings. Posed as a linear programming problem, jet selection must represent the rate change request as a linear combination of jet acceleration vectors where the coefficients are the jet firing times, while minimizing the fuel expended in satisfying that request. This problem is solved in real time using a revised Simplex algorithm. In order to implement the jet selection algorithm in the Shuttle flight control computer, it was modified to accommodate certain practical features of the Shuttle such as limited computer throughput, lengthy firing times, and a large number of control jets. To the authors' knowledge, this is the first such application of linear programming. It was made possible by careful consideration of the jet selection problem in terms of the properties of linear programming and the Simplex algorithm. These modifications to the jet select algorithm may by useful for the design of reaction controlled spacecraft.

Genome-wide association analysis of seedling root development in maize (Zea mays L.).

PubMed

Pace, Jordon; Gardner, Candice; Romay, Cinta; Ganapathysubramanian, Baskar; Lübberstedt, Thomas

2015-02-05

Plants rely on the root system for anchorage to the ground and the acquisition and absorption of nutrients critical to sustaining productivity. A genome wide association analysis enables one to analyze allelic diversity of complex traits and identify superior alleles. 384 inbred lines from the Ames panel were genotyped with 681,257 single nucleotide polymorphism markers using Genotyping-by-Sequencing technology and 22 seedling root architecture traits were phenotyped. Utilizing both a general linear model and mixed linear model, a GWAS study was conducted identifying 268 marker trait associations (p ≤ 5.3×10(-7)). Analysis of significant SNP markers for multiple traits showed that several were located within gene models with some SNP markers localized within regions of previously identified root quantitative trait loci. Gene model GRMZM2G153722 located on chromosome 4 contained nine significant markers. This predicted gene is expressed in roots and shoots. This study identifies putatively associated SNP markers associated with root traits at the seedling stage. Some SNPs were located within or near (<1 kb) gene models. These gene models identify possible candidate genes involved in root development at the seedling stage. These and respective linked or functional markers could be targets for breeders for marker assisted selection of seedling root traits.

Efficient and selective degradation of polyethylenes into liquid fuels and waxes under mild conditions.

PubMed

Jia, Xiangqing; Qin, Chuan; Friedberger, Tobias; Guan, Zhibin; Huang, Zheng

2016-06-01

Polyethylene (PE) is the largest-volume synthetic polymer, and its chemical inertness makes its degradation by low-energy processes a challenging problem. We report a tandem catalytic cross alkane metathesis method for highly efficient degradation of polyethylenes under mild conditions. With the use of widely available, low-value, short alkanes (for example, petroleum ethers) as cross metathesis partners, different types of polyethylenes with various molecular weights undergo complete conversion into useful liquid fuels and waxes. This method shows excellent selectivity for linear alkane formation, and the degradation product distribution (liquid fuels versus waxes) can be controlled by the catalyst structure and reaction time. In addition, the catalysts are compatible with various polyolefin additives; therefore, common plastic wastes, such as postconsumer polyethylene bottles, bags, and films could be converted into valuable chemical feedstocks without any pretreatment.

Efficient and selective degradation of polyethylenes into liquid fuels and waxes under mild conditions

PubMed Central

Jia, Xiangqing; Qin, Chuan; Friedberger, Tobias; Guan, Zhibin; Huang, Zheng

2016-01-01

Polyethylene (PE) is the largest-volume synthetic polymer, and its chemical inertness makes its degradation by low-energy processes a challenging problem. We report a tandem catalytic cross alkane metathesis method for highly efficient degradation of polyethylenes under mild conditions. With the use of widely available, low-value, short alkanes (for example, petroleum ethers) as cross metathesis partners, different types of polyethylenes with various molecular weights undergo complete conversion into useful liquid fuels and waxes. This method shows excellent selectivity for linear alkane formation, and the degradation product distribution (liquid fuels versus waxes) can be controlled by the catalyst structure and reaction time. In addition, the catalysts are compatible with various polyolefin additives; therefore, common plastic wastes, such as postconsumer polyethylene bottles, bags, and films could be converted into valuable chemical feedstocks without any pretreatment. PMID:27386559

Pd nanoparticle-modified electrodes for nonenzymatic hydrogen peroxide detection

NASA Astrophysics Data System (ADS)

Wang, Jue; Chen, Xue-jiao; Liao, Kai-ming; Wang, Guang-hou; Han, Min

2015-08-01

A hydrogen peroxide (H2O2) sensor based on Pd nanoparticles (NPs) and glassy carbon electrodes (GCEs) is fabricated. Pd NPs are deposited on GCEs by using a gas phase cluster beam deposition technique. The NP-deposited electrodes show enhanced electrocatalytic activity in reduction of H2O2. The electrode with an optimized NP coverage of 85 % has a high selective and stable nonenzymatic sensing ability of H2O2 with a low detection limit (3.4 × 10-7 M), high sensitivity (50.9 μA mM-1), and a wide linear range (from 1.0 × 10-6 to 6.0 × 10-3 M). The reduction peak potential of the electrode is close to -0.12 V, which enables high selective amperometric detection of H2O2 at a low applied potential.

Holographic elements and curved slit used to enlarge field of view in rocket detection system

NASA Astrophysics Data System (ADS)

Breton, Mélanie; Fortin, Jean; Lessard, Roger A.; Châteauneuf, Marc

2006-09-01

Rocket detection over a wide field of view is an important issue in the protection of light armored vehicle. Traditionally, the detection occurs in UV band, but recent studies have shown the existence of significant emission peaks in the visible and near infrared at rocket launch time. The use of the visible region is interesting in order to reduce the weight and cost of systems. Current methods to detect those specific peaks involve use of interferometric filters. However, they fail to combine wide angle with wavelength selectivity. A linear array of volume holographic elements combined with a curved exit slit is proposed for the development of a wide field of view sensor for the detection of solid propellant motor launch flash. The sensor is envisaged to trigger an active protection system. On the basis of geometric theory, a system has been designed. It consists of a collector, a linear array of holographic elements, a curved slit and a detector. The collector is an off-axis parabolic mirror. Holographic elements are recorded subdividing a hologram film in regions, each individually exposed with a different incidence angle. All regions have a common diffraction angle. The incident angle determines the instantaneous field of view of the elements. The volume hologram performs the function of separating and focusing the diffracted beam on an image plane to achieve wavelength filtering. Conical diffraction property is used to enlarge the field of view in elevation. A curved slit was designed to correspond to oblique incidence of the holographic linear array. It is situated at the image plane and filters the diffracted spectrum toward the sensor. The field of view of the design was calculated to be 34 degrees. This was validated by a prototype tested during a field trial. Results are presented and analyzed. The system succeeded in detecting the rocket launch flash at desired fields of view.

Olefinic Thermoplastic Elastomer Gels: Combining Polymer Crystallization and Microphase Separation in a Selective Solvent

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

Armstrong, Daniel P.; Mineart, Kenneth P.; Lee, Byeongdu

Since selectively swollen thermoplastic elastomer gels (TPEGs) afford a wide range of beneficial properties that open new doors to developing elastomer-based technologies, in this study we examine the unique structure-property behavior of TPEGs composed of olefinic block copolymers (OBCs). Unlike their styrenic counterparts typically possessing two chemically different blocks, this class of multiblock copolymers consists of linear polyethylene hard blocks and poly(ethylene-co-α-octene) soft blocks, in which case, microphase separation between the hard and the soft blocks is accompanied by crystallization of the hard blocks. We prepare olefinic TPEGs (OTPEGs) through the incorporation of a primarily aliphatic oil that selectively swellsmore » the soft block and investigate the resultant morphological features through the use of polarized light microscopy and small-/wideangle X-ray scattering. These features are correlated with thermal and mechanical property measurements from calorimetry, rheology, and extensiometry to elucidate the roles of crystallization and self-assembly on gel characteristics and establish useful structure-property relationships.« less

Olefinic Thermoplastic Elastomer Gels: Combining Polymer Crystallization and Microphase Separation in a Selective Solvent

DOE PAGES

Armstrong, Daniel P.; Mineart, Kenneth P.; Lee, Byeongdu; ...

2016-11-01

Since selectively swollen thermoplastic elastomer gels (TPEGs) afford a wide range of beneficial properties that open new doors to developing elastomer-based technologies, in this study we examine the unique structure-property behavior of TPEGs composed of olefinic block copolymers (OBCs). Unlike their styrenic counterparts typically possessing two chemically different blocks, this class of multiblock copolymers consists of linear polyethylene hard blocks and poly(ethylene-co-α-octene) soft blocks, in which case, microphase separation between the hard and the soft blocks is accompanied by crystallization of the hard blocks. We prepare olefinic TPEGs (OTPEGs) through the incorporation of a primarily aliphatic oil that selectively swellsmore » the soft block and investigate the resultant morphological features through the use of polarized light microscopy and small-/wideangle X-ray scattering. These features are correlated with thermal and mechanical property measurements from calorimetry, rheology, and extensiometry to elucidate the roles of crystallization and self-assembly on gel characteristics and establish useful structure-property relationships.« less

Efficient and Highly Selective Solvent-Free Oxidation of Primary Alcohols to Aldehydes Using Bucky Nanodiamond.

PubMed

Lin, Yangming; Wu, Kuang-Hsu Tim; Yu, Linhui; Heumann, Saskia; Su, Dang Sheng

2017-09-11

Selective oxidation of alcohols to aldehydes is widely applicable to the synthesis of various green chemicals. The poor chemoselectivity for complicated primary aldehydes over state-of-the-art metal-free or metal-based catalysts represents a major obstacle for industrial application. Bucky nanodiamond is a potential green catalyst that exhibits excellent chemoselectivity and cycling stability for the selective oxidation of primary alcohols in diverse structures (22 examples, including aromatic, substituted aromatic, unsaturated, heterocyclic, and linear chain alcohols) to their corresponding aldehydes. The results are comparable to reported transition-metal catalysts including conventional Pt/C and Ru/C catalysts for certain substrates under solvent-free conditions. The possible activation process of the oxidant and substrates by the surface oxygen groups and defect species are revealed with model catalysts, ex situ electrochemical measurements, and ex situ attenuated total reflectance. The zigzag edges of sp 2 carbon planes are shown to play a key role in these reactions. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Comparative Investigation of the Combined Effects of Pre-Processing, Wavelength Selection, and Regression Methods on Near-Infrared Calibration Model Performance.

PubMed

Wan, Jian; Chen, Yi-Chieh; Morris, A Julian; Thennadil, Suresh N

2017-07-01

Near-infrared (NIR) spectroscopy is being widely used in various fields ranging from pharmaceutics to the food industry for analyzing chemical and physical properties of the substances concerned. Its advantages over other analytical techniques include available physical interpretation of spectral data, nondestructive nature and high speed of measurements, and little or no need for sample preparation. The successful application of NIR spectroscopy relies on three main aspects: pre-processing of spectral data to eliminate nonlinear variations due to temperature, light scattering effects and many others, selection of those wavelengths that contribute useful information, and identification of suitable calibration models using linear/nonlinear regression . Several methods have been developed for each of these three aspects and many comparative studies of different methods exist for an individual aspect or some combinations. However, there is still a lack of comparative studies for the interactions among these three aspects, which can shed light on what role each aspect plays in the calibration and how to combine various methods of each aspect together to obtain the best calibration model. This paper aims to provide such a comparative study based on four benchmark data sets using three typical pre-processing methods, namely, orthogonal signal correction (OSC), extended multiplicative signal correction (EMSC) and optical path-length estimation and correction (OPLEC); two existing wavelength selection methods, namely, stepwise forward selection (SFS) and genetic algorithm optimization combined with partial least squares regression for spectral data (GAPLSSP); four popular regression methods, namely, partial least squares (PLS), least absolute shrinkage and selection operator (LASSO), least squares support vector machine (LS-SVM), and Gaussian process regression (GPR). The comparative study indicates that, in general, pre-processing of spectral data can play a significant role in the calibration while wavelength selection plays a marginal role and the combination of certain pre-processing, wavelength selection, and nonlinear regression methods can achieve superior performance over traditional linear regression-based calibration.

Effective synthesis of magnetic porous molecularly imprinted polymers for efficient and selective extraction of cinnamic acid from apple juices.

PubMed

Shi, Shuyun; Fan, Dengxin; Xiang, Haiyan; Li, Huan

2017-12-15

An effective strategy was proposed to prepare novel magnetic porous molecularly imprinted polymers (MPMIPs) for highly selective extraction of cinnamic acid (CMA) from complex matrices. Characterization and various parameters affecting adsorption and desorption behaviors were investigated. Results revealed adsorption behavior between CMA and MPMIPs followed Freundlich equation adsorption isotherm with a maximum adsorption capacity at 4.35mg/g and pseudo-second-order reaction kinetics with equilibrium time at 60min. Subsequently, MPMIPs were successfully used to selectively extract CMA from apple juice with a relatively satisfactory recovery (92.7-101.4%). Coupling with high-performance liquid chromatography and ultraviolet detection (HPLC-UV), the limit of detection (LOD) for CMA was 0.006µg/mL, and the linear range (0.02-10μg/mL) was wide with correlation coefficient at 0.9995. Finally, the contents of CMA in two kinds of apple juices were determined as 0.132 and 0.120μg/mL. Results indicated the superiority of MPMIPs in the selective extraction field. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ni-Co bimetal nanowires filled multiwalled carbon nanotubes for the highly sensitive and selective non-enzymatic glucose sensor applications

PubMed Central

Ramachandran, K.; Raj kumar, T.; Babu, K. Justice; Gnana kumar, G.

2016-01-01

The facile, time and cost efficient and environmental benign approach has been developed for the preparation of Nickel (Ni)-Cobalt (Co) alloy nanowires filled multiwalled carbon nanotubes (MWCNTs) with the aid of mesoporous silica nanoparticles (MSN)/Ni-Co catalyst. The controlled incorporation of Ni-Co nanostructures in the three dimensional (3D) pore structures of MSN yielded the catalytically active system for the MWCNT growth. The inner surface of MWCNTs was quasi-continuously filled with face-centered cubic (fcc) structured Ni-Co nanowires. The as-prepared nanostructures were exploited as non-enzymatic electrochemical sensor probes for the reliable detection of glucose. The electrochemical measurements illustrated that the fabricated sensor exhibited an excellent electrochemical performance toward glucose oxidation with a high sensitivity of 0.695 mA mM−1 cm−2, low detection limit of 1.2 μM, a wide linear range from 5 μM–10 mM and good selectivity. The unprecedented electrochemical performances obtained for the prepared nanocomposite are purely attributed to the synergistic effects of Ni-Co nanowires and MWCNTs. The constructed facile, selective and sensitive glucose sensor has also endowed its reliability in analyzing the human serum samples, which wide opened the new findings for exploring the novel nanostructures based glucose sensor devices with affordable cost and good stability. PMID:27833123

SVM Based Descriptor Selection and Classification of Neurodegenerative Disease Drugs for Pharmacological Modeling.

PubMed

Shahid, Mohammad; Shahzad Cheema, Muhammad; Klenner, Alexander; Younesi, Erfan; Hofmann-Apitius, Martin

2013-03-01

Systems pharmacological modeling of drug mode of action for the next generation of multitarget drugs may open new routes for drug design and discovery. Computational methods are widely used in this context amongst which support vector machines (SVM) have proven successful in addressing the challenge of classifying drugs with similar features. We have applied a variety of such SVM-based approaches, namely SVM-based recursive feature elimination (SVM-RFE). We use the approach to predict the pharmacological properties of drugs widely used against complex neurodegenerative disorders (NDD) and to build an in-silico computational model for the binary classification of NDD drugs from other drugs. Application of an SVM-RFE model to a set of drugs successfully classified NDD drugs from non-NDD drugs and resulted in overall accuracy of ∼80 % with 10 fold cross validation using 40 top ranked molecular descriptors selected out of total 314 descriptors. Moreover, SVM-RFE method outperformed linear discriminant analysis (LDA) based feature selection and classification. The model reduced the multidimensional descriptors space of drugs dramatically and predicted NDD drugs with high accuracy, while avoiding over fitting. Based on these results, NDD-specific focused libraries of drug-like compounds can be designed and existing NDD-specific drugs can be characterized by a well-characterized set of molecular descriptors. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Finite Adaptation and Multistep Moves in the Metropolis-Hastings Algorithm for Variable Selection in Genome-Wide Association Analysis

PubMed Central

Peltola, Tomi; Marttinen, Pekka; Vehtari, Aki

2012-01-01

High-dimensional datasets with large amounts of redundant information are nowadays available for hypothesis-free exploration of scientific questions. A particular case is genome-wide association analysis, where variations in the genome are searched for effects on disease or other traits. Bayesian variable selection has been demonstrated as a possible analysis approach, which can account for the multifactorial nature of the genetic effects in a linear regression model. Yet, the computation presents a challenge and application to large-scale data is not routine. Here, we study aspects of the computation using the Metropolis-Hastings algorithm for the variable selection: finite adaptation of the proposal distributions, multistep moves for changing the inclusion state of multiple variables in a single proposal and multistep move size adaptation. We also experiment with a delayed rejection step for the multistep moves. Results on simulated and real data show increase in the sampling efficiency. We also demonstrate that with application specific proposals, the approach can overcome a specific mixing problem in real data with 3822 individuals and 1,051,811 single nucleotide polymorphisms and uncover a variant pair with synergistic effect on the studied trait. Moreover, we illustrate multimodality in the real dataset related to a restrictive prior distribution on the genetic effect sizes and advocate a more flexible alternative. PMID:23166669

Ni-Co bimetal nanowires filled multiwalled carbon nanotubes for the highly sensitive and selective non-enzymatic glucose sensor applications

NASA Astrophysics Data System (ADS)

Ramachandran, K.; Raj Kumar, T.; Babu, K. Justice; Gnana Kumar, G.

2016-11-01

The facile, time and cost efficient and environmental benign approach has been developed for the preparation of Nickel (Ni)-Cobalt (Co) alloy nanowires filled multiwalled carbon nanotubes (MWCNTs) with the aid of mesoporous silica nanoparticles (MSN)/Ni-Co catalyst. The controlled incorporation of Ni-Co nanostructures in the three dimensional (3D) pore structures of MSN yielded the catalytically active system for the MWCNT growth. The inner surface of MWCNTs was quasi-continuously filled with face-centered cubic (fcc) structured Ni-Co nanowires. The as-prepared nanostructures were exploited as non-enzymatic electrochemical sensor probes for the reliable detection of glucose. The electrochemical measurements illustrated that the fabricated sensor exhibited an excellent electrochemical performance toward glucose oxidation with a high sensitivity of 0.695 mA mM-1 cm-2, low detection limit of 1.2 μM, a wide linear range from 5 μM-10 mM and good selectivity. The unprecedented electrochemical performances obtained for the prepared nanocomposite are purely attributed to the synergistic effects of Ni-Co nanowires and MWCNTs. The constructed facile, selective and sensitive glucose sensor has also endowed its reliability in analyzing the human serum samples, which wide opened the new findings for exploring the novel nanostructures based glucose sensor devices with affordable cost and good stability.

A simple bias correction in linear regression for quantitative trait association under two-tail extreme selection.

PubMed

Kwan, Johnny S H; Kung, Annie W C; Sham, Pak C

2011-09-01

Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias.

Multilocus approaches for the measurement of selection on correlated genetic loci.

PubMed

Gompert, Zachariah; Egan, Scott P; Barrett, Rowan D H; Feder, Jeffrey L; Nosil, Patrik

2017-01-01

The study of ecological speciation is inherently linked to the study of selection. Methods for estimating phenotypic selection within a generation based on associations between trait values and fitness (e.g. survival) of individuals are established. These methods attempt to disentangle selection acting directly on a trait from indirect selection caused by correlations with other traits via multivariate statistical approaches (i.e. inference of selection gradients). The estimation of selection on genotypic or genomic variation could also benefit from disentangling direct and indirect selection on genetic loci. However, achieving this goal is difficult with genomic data because the number of potentially correlated genetic loci (p) is very large relative to the number of individuals sampled (n). In other words, the number of model parameters exceeds the number of observations (p ≫ n). We present simulations examining the utility of whole-genome regression approaches (i.e. Bayesian sparse linear mixed models) for quantifying direct selection in cases where p ≫ n. Such models have been used for genome-wide association mapping and are common in artificial breeding. Our results show they hold promise for studies of natural selection in the wild and thus of ecological speciation. But we also demonstrate important limitations to the approach and discuss study designs required for more robust inferences. © 2016 John Wiley & Sons Ltd.

Wrapper-based selection of genetic features in genome-wide association studies through fast matrix operations

PubMed Central

2012-01-01

Background Through the wealth of information contained within them, genome-wide association studies (GWAS) have the potential to provide researchers with a systematic means of associating genetic variants with a wide variety of disease phenotypes. Due to the limitations of approaches that have analyzed single variants one at a time, it has been proposed that the genetic basis of these disorders could be determined through detailed analysis of the genetic variants themselves and in conjunction with one another. The construction of models that account for these subsets of variants requires methodologies that generate predictions based on the total risk of a particular group of polymorphisms. However, due to the excessive number of variants, constructing these types of models has so far been computationally infeasible. Results We have implemented an algorithm, known as greedy RLS, that we use to perform the first known wrapper-based feature selection on the genome-wide level. The running time of greedy RLS grows linearly in the number of training examples, the number of features in the original data set, and the number of selected features. This speed is achieved through computational short-cuts based on matrix calculus. Since the memory consumption in present-day computers can form an even tighter bottleneck than running time, we also developed a space efficient variation of greedy RLS which trades running time for memory. These approaches are then compared to traditional wrapper-based feature selection implementations based on support vector machines (SVM) to reveal the relative speed-up and to assess the feasibility of the new algorithm. As a proof of concept, we apply greedy RLS to the Hypertension – UK National Blood Service WTCCC dataset and select the most predictive variants using 3-fold external cross-validation in less than 26 minutes on a high-end desktop. On this dataset, we also show that greedy RLS has a better classification performance on independent test data than a classifier trained using features selected by a statistical p-value-based filter, which is currently the most popular approach for constructing predictive models in GWAS. Conclusions Greedy RLS is the first known implementation of a machine learning based method with the capability to conduct a wrapper-based feature selection on an entire GWAS containing several thousand examples and over 400,000 variants. In our experiments, greedy RLS selected a highly predictive subset of genetic variants in a fraction of the time spent by wrapper-based selection methods used together with SVM classifiers. The proposed algorithms are freely available as part of the RLScore software library at http://users.utu.fi/aatapa/RLScore/. PMID:22551170

A simple method for finding explicit analytic transition densities of diffusion processes with general diploid selection.

PubMed

Song, Yun S; Steinrücken, Matthias

2012-03-01

The transition density function of the Wright-Fisher diffusion describes the evolution of population-wide allele frequencies over time. This function has important practical applications in population genetics, but finding an explicit formula under a general diploid selection model has remained a difficult open problem. In this article, we develop a new computational method to tackle this classic problem. Specifically, our method explicitly finds the eigenvalues and eigenfunctions of the diffusion generator associated with the Wright-Fisher diffusion with recurrent mutation and arbitrary diploid selection, thus allowing one to obtain an accurate spectral representation of the transition density function. Simplicity is one of the appealing features of our approach. Although our derivation involves somewhat advanced mathematical concepts, the resulting algorithm is quite simple and efficient, only involving standard linear algebra. Furthermore, unlike previous approaches based on perturbation, which is applicable only when the population-scaled selection coefficient is small, our method is nonperturbative and is valid for a broad range of parameter values. As a by-product of our work, we obtain the rate of convergence to the stationary distribution under mutation-selection balance.

Genomic selection in sugar beet breeding populations.

PubMed

Würschum, Tobias; Reif, Jochen C; Kraft, Thomas; Janssen, Geert; Zhao, Yusheng

2013-09-18

Genomic selection exploits dense genome-wide marker data to predict breeding values. In this study we used a large sugar beet population of 924 lines representing different germplasm types present in breeding populations: unselected segregating families and diverse lines from more advanced stages of selection. All lines have been intensively phenotyped in multi-location field trials for six agronomically important traits and genotyped with 677 SNP markers. We used ridge regression best linear unbiased prediction in combination with fivefold cross-validation and obtained high prediction accuracies for all except one trait. In addition, we investigated whether a calibration developed based on a training population composed of diverse lines is suited to predict the phenotypic performance within families. Our results show that the prediction accuracy is lower than that obtained within the diverse set of lines, but comparable to that obtained by cross-validation within the respective families. The results presented in this study suggest that a training population derived from intensively phenotyped and genotyped diverse lines from a breeding program does hold potential to build up robust calibration models for genomic selection. Taken together, our results indicate that genomic selection is a valuable tool and can thus complement the genomics toolbox in sugar beet breeding.

A Simple Method for Finding Explicit Analytic Transition Densities of Diffusion Processes with General Diploid Selection

PubMed Central

Song, Yun S.; Steinrücken, Matthias

2012-01-01

The transition density function of the Wright–Fisher diffusion describes the evolution of population-wide allele frequencies over time. This function has important practical applications in population genetics, but finding an explicit formula under a general diploid selection model has remained a difficult open problem. In this article, we develop a new computational method to tackle this classic problem. Specifically, our method explicitly finds the eigenvalues and eigenfunctions of the diffusion generator associated with the Wright–Fisher diffusion with recurrent mutation and arbitrary diploid selection, thus allowing one to obtain an accurate spectral representation of the transition density function. Simplicity is one of the appealing features of our approach. Although our derivation involves somewhat advanced mathematical concepts, the resulting algorithm is quite simple and efficient, only involving standard linear algebra. Furthermore, unlike previous approaches based on perturbation, which is applicable only when the population-scaled selection coefficient is small, our method is nonperturbative and is valid for a broad range of parameter values. As a by-product of our work, we obtain the rate of convergence to the stationary distribution under mutation–selection balance. PMID:22209899

Genomic Prediction of Testcross Performance in Canola (Brassica napus)

PubMed Central

Jan, Habib U.; Abbadi, Amine; Lücke, Sophie; Nichols, Richard A.; Snowdon, Rod J.

2016-01-01

Genomic selection (GS) is a modern breeding approach where genome-wide single-nucleotide polymorphism (SNP) marker profiles are simultaneously used to estimate performance of untested genotypes. In this study, the potential of genomic selection methods to predict testcross performance for hybrid canola breeding was applied for various agronomic traits based on genome-wide marker profiles. A total of 475 genetically diverse spring-type canola pollinator lines were genotyped at 24,403 single-copy, genome-wide SNP loci. In parallel, the 950 F1 testcross combinations between the pollinators and two representative testers were evaluated for a number of important agronomic traits including seedling emergence, days to flowering, lodging, oil yield and seed yield along with essential seed quality characters including seed oil content and seed glucosinolate content. A ridge-regression best linear unbiased prediction (RR-BLUP) model was applied in combination with 500 cross-validations for each trait to predict testcross performance, both across the whole population as well as within individual subpopulations or clusters, based solely on SNP profiles. Subpopulations were determined using multidimensional scaling and K-means clustering. Genomic prediction accuracy across the whole population was highest for seed oil content (0.81) followed by oil yield (0.75) and lowest for seedling emergence (0.29). For seed yieId, seed glucosinolate, lodging resistance and days to onset of flowering (DTF), prediction accuracies were 0.45, 0.61, 0.39 and 0.56, respectively. Prediction accuracies could be increased for some traits by treating subpopulations separately; a strategy which only led to moderate improvements for some traits with low heritability, like seedling emergence. No useful or consistent increase in accuracy was obtained by inclusion of a population substructure covariate in the model. Testcross performance prediction using genome-wide SNP markers shows considerable potential for pre-selection of promising hybrid combinations prior to resource-intensive field testing over multiple locations and years. PMID:26824924

Decision-Related Activity in Macaque V2 for Fine Disparity Discrimination Is Not Compatible with Optimal Linear Readout.

PubMed

Clery, Stephane; Cumming, Bruce G; Nienborg, Hendrikje

2017-01-18

Fine judgments of stereoscopic depth rely mainly on relative judgments of depth (relative binocular disparity) between objects, rather than judgments of the distance to where the eyes are fixating (absolute disparity). In macaques, visual area V2 is the earliest site in the visual processing hierarchy for which neurons selective for relative disparity have been observed (Thomas et al., 2002). Here, we found that, in macaques trained to perform a fine disparity discrimination task, disparity-selective neurons in V2 were highly selective for the task, and their activity correlated with the animals' perceptual decisions (unexplained by the stimulus). This may partially explain similar correlations reported in downstream areas. Although compatible with a perceptual role of these neurons for the task, the interpretation of such decision-related activity is complicated by the effects of interneuronal "noise" correlations between sensory neurons. Recent work has developed simple predictions to differentiate decoding schemes (Pitkow et al., 2015) without needing measures of noise correlations, and found that data from early sensory areas were compatible with optimal linear readout of populations with information-limiting correlations. In contrast, our data here deviated significantly from these predictions. We additionally tested this prediction for previously reported results of decision-related activity in V2 for a related task, coarse disparity discrimination (Nienborg and Cumming, 2006), thought to rely on absolute disparity. Although these data followed the predicted pattern, they violated the prediction quantitatively. This suggests that optimal linear decoding of sensory signals is not generally a good predictor of behavior in simple perceptual tasks. Activity in sensory neurons that correlates with an animal's decision is widely believed to provide insights into how the brain uses information from sensory neurons. Recent theoretical work developed simple predictions to differentiate decoding schemes, and found support for optimal linear readout of early sensory populations with information-limiting correlations. Here, we observed decision-related activity for neurons in visual area V2 of macaques performing fine disparity discrimination, as yet the earliest site for this task. These findings, and previously reported results from V2 in a different task, deviated from the predictions for optimal linear readout of a population with information-limiting correlations. Our results suggest that optimal linear decoding of early sensory information is not a general decoding strategy used by the brain. Copyright © 2017 the authors 0270-6474/17/370715-11$15.00/0.

Margin-maximizing feature elimination methods for linear and nonlinear kernel-based discriminant functions.

PubMed

Aksu, Yaman; Miller, David J; Kesidis, George; Yang, Qing X

2010-05-01

Feature selection for classification in high-dimensional spaces can improve generalization, reduce classifier complexity, and identify important, discriminating feature "markers." For support vector machine (SVM) classification, a widely used technique is recursive feature elimination (RFE). We demonstrate that RFE is not consistent with margin maximization, central to the SVM learning approach. We thus propose explicit margin-based feature elimination (MFE) for SVMs and demonstrate both improved margin and improved generalization, compared with RFE. Moreover, for the case of a nonlinear kernel, we show that RFE assumes that the squared weight vector 2-norm is strictly decreasing as features are eliminated. We demonstrate this is not true for the Gaussian kernel and, consequently, RFE may give poor results in this case. MFE for nonlinear kernels gives better margin and generalization. We also present an extension which achieves further margin gains, by optimizing only two degrees of freedom--the hyperplane's intercept and its squared 2-norm--with the weight vector orientation fixed. We finally introduce an extension that allows margin slackness. We compare against several alternatives, including RFE and a linear programming method that embeds feature selection within the classifier design. On high-dimensional gene microarray data sets, University of California at Irvine (UCI) repository data sets, and Alzheimer's disease brain image data, MFE methods give promising results.

A Secondary Antibody-Detecting Molecular Weight Marker with Mouse and Rabbit IgG Fc Linear Epitopes for Western Blot Analysis

PubMed Central

Cheng, Ta-Chun; Tung, Yi-Ching; Chu, Pei-Yu; Chuang, Chih-Hung; Hsieh, Yuan-Chin; Huang, Chien-Chiao; Wang, Yeng-Tseng; Kao, Chien-Han; Roffler, Steve R.; Cheng, Tian-Lu

2016-01-01

Molecular weight markers that can tolerate denaturing conditions and be auto-detected by secondary antibodies offer great efficacy and convenience for Western Blotting. Here, we describe M&R LE protein markers which contain linear epitopes derived from the heavy chain constant regions of mouse and rabbit immunoglobulin G (IgG Fc LE). These markers can be directly recognized and stained by a wide range of anti-mouse and anti-rabbit secondary antibodies. We selected three mouse (M1, M2 and M3) linear IgG1 and three rabbit (R1, R2 and R3) linear IgG heavy chain epitope candidates based on their respective crystal structures. Western blot analysis indicated that M2 and R2 linear epitopes are effectively recognized by anti-mouse and anti-rabbit secondary antibodies, respectively. We fused the M2 and R2 epitopes (M&R LE) and incorporated the polypeptide in a range of 15–120 kDa auto-detecting markers (M&R LE protein marker). The M&R LE protein marker can be auto-detected by anti-mouse and anti-rabbit IgG secondary antibodies in standard immunoblots. Linear regression analysis of the M&R LE protein marker plotted as gel mobility versus the log of the marker molecular weights revealed good linearity with a correlation coefficient R2 value of 0.9965, indicating that the M&R LE protein marker displays high accuracy for determining protein molecular weights. This accurate, regular and auto-detected M&R LE protein marker may provide a simple, efficient and economical tool for protein analysis. PMID:27494183

A Secondary Antibody-Detecting Molecular Weight Marker with Mouse and Rabbit IgG Fc Linear Epitopes for Western Blot Analysis.

PubMed

Lin, Wen-Wei; Chen, I-Ju; Cheng, Ta-Chun; Tung, Yi-Ching; Chu, Pei-Yu; Chuang, Chih-Hung; Hsieh, Yuan-Chin; Huang, Chien-Chiao; Wang, Yeng-Tseng; Kao, Chien-Han; Roffler, Steve R; Cheng, Tian-Lu

2016-01-01

Molecular weight markers that can tolerate denaturing conditions and be auto-detected by secondary antibodies offer great efficacy and convenience for Western Blotting. Here, we describe M&R LE protein markers which contain linear epitopes derived from the heavy chain constant regions of mouse and rabbit immunoglobulin G (IgG Fc LE). These markers can be directly recognized and stained by a wide range of anti-mouse and anti-rabbit secondary antibodies. We selected three mouse (M1, M2 and M3) linear IgG1 and three rabbit (R1, R2 and R3) linear IgG heavy chain epitope candidates based on their respective crystal structures. Western blot analysis indicated that M2 and R2 linear epitopes are effectively recognized by anti-mouse and anti-rabbit secondary antibodies, respectively. We fused the M2 and R2 epitopes (M&R LE) and incorporated the polypeptide in a range of 15-120 kDa auto-detecting markers (M&R LE protein marker). The M&R LE protein marker can be auto-detected by anti-mouse and anti-rabbit IgG secondary antibodies in standard immunoblots. Linear regression analysis of the M&R LE protein marker plotted as gel mobility versus the log of the marker molecular weights revealed good linearity with a correlation coefficient R2 value of 0.9965, indicating that the M&R LE protein marker displays high accuracy for determining protein molecular weights. This accurate, regular and auto-detected M&R LE protein marker may provide a simple, efficient and economical tool for protein analysis.

Quantum description of light propagation in generalized media

NASA Astrophysics Data System (ADS)

Häyrynen, Teppo; Oksanen, Jani

2016-02-01

Linear quantum input-output relation based models are widely applied to describe the light propagation in a lossy medium. The details of the interaction and the associated added noise depend on whether the device is configured to operate as an amplifier or an attenuator. Using the traveling wave (TW) approach, we generalize the linear material model to simultaneously account for both the emission and absorption processes and to have point-wise defined noise field statistics and intensity dependent interaction strengths. Thus, our approach describes the quantum input-output relations of linear media with net attenuation, amplification or transparency without pre-selection of the operation point. The TW approach is then applied to investigate materials at thermal equilibrium, inverted materials, the transparency limit where losses are compensated, and the saturating amplifiers. We also apply the approach to investigate media in nonuniform states which can be e.g. consequences of a temperature gradient over the medium or a position dependent inversion of the amplifier. Furthermore, by using the generalized model we investigate devices with intensity dependent interactions and show how an initial thermal field transforms to a field having coherent statistics due to gain saturation.

Sixth SIAM conference on applied linear algebra: Final program and abstracts. Final technical report

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

NONE

1997-12-31

Linear algebra plays a central role in mathematics and applications. The analysis and solution of problems from an amazingly wide variety of disciplines depend on the theory and computational techniques of linear algebra. In turn, the diversity of disciplines depending on linear algebra also serves to focus and shape its development. Some problems have special properties (numerical, structural) that can be exploited. Some are simply so large that conventional approaches are impractical. New computer architectures motivate new algorithms, and fresh ways to look at old ones. The pervasive nature of linear algebra in analyzing and solving problems means that peoplemore » from a wide spectrum--universities, industrial and government laboratories, financial institutions, and many others--share an interest in current developments in linear algebra. This conference aims to bring them together for their mutual benefit. Abstracts of papers presented are included.« less

Highly Sensitive and Selective Sensing of Free Bilirubin Using Metal-Organic Frameworks-Based Energy Transfer Process.

PubMed

Du, Yaran; Li, Xiqian; Lv, Xueju; Jia, Qiong

2017-09-13

Free bilirubin, a key biomarker for jaundice, was detected with a newly designed fluorescent postsynthetically modified metal organic framework (MOF) (UIO-66-PSM) sensor. UiO-66-PSM was prepared based on the aldimine condensation reaction of UiO-66-NH 2 with 2,3,4-trihydroxybenzaldehyde. The fluorescence of UIO-66-PSM could be effectively quenched by free bilirubin via a fluorescent resonant energy transfer process, thus achieving its recognition of free bilirubin. It was the first attempt to design a MOF-based fluorescent probe for sensing free bilirubin. The probe exhibited fast response time, low detection limit, wide linear range, and high selectivity toward free bilirubin. The sensing system enabled the monitor of free bilirubin in real human serum. Hence, the reported free bilirubin sensing platform has potential applications for clinical diagnosis of jaundice.

Design of a Selective and Sensitive PVC-Membrane Potentiometric Sensor for Strontium Ion Based on 1,10-Diaza-5,6-benzo-4,7-dioxacyclohexadecane-2,9-dione as a Neutral Ionophore

PubMed Central

Shamsipur, Mojtaba; Kazemi, Sayed Yahya; Sharghi, Hashem

2007-01-01

A novel PVC membrane sensor for the Sr2+ ion based on 1,10-diaza-5,6-benzo-4,7-dioxacyclohexadecane-2,9-dione has been prepared. The sensor possesses a Nernstian slope of 30.0 ± 0.6 mV decade-1 over a wide linear concentration range of 1.6 × 10-6-3.0 ×10-3 M with a detection limit of 6.3 ×10-7 M. It has a fast response time of <15 s and can be used for at least two months without any considerable divergence in potential. The potentiometric response is independent of the pH of test solution in the pH range 4.3-9.4. The proposed electrode shows good selectivities over a variety of alkali, alkaline earth, and transition metal ions.

Projection of distributed-collector solar-thermal electric power plant economics to years 1990-2000

NASA Technical Reports Server (NTRS)

Fujita, T.; Elgabalawi, N.; Herrera, G.; Turner, R. H.

1977-01-01

A preliminary comparative evaluation of distributed-collector solar thermal power plants was undertaken by projecting power plant economics of selected systems to the 1990 to 2000 time frame. The selected systems include: (1) fixed orientation collectors with concentrating reflectors and vacuum tube absorbers, (2) one axis tracking linear concentrator including parabolic trough and variable slat designs, and (3) two axis tracking parabolic dish systems including concepts with small heat engine-electric generator assemblies at each focal point as well as approaches having steam generators at the focal point with pipeline collection to a central power conversion unit. Comparisons are presented primarily in terms of energy cost and capital cost over a wide range of operating load factors. Sensitvity of energy costs for a range of efficiency and cost of major subsystems/components is presented to delineate critical technological development needs.

Fast Principal-Component Analysis Reveals Convergent Evolution of ADH1B in Europe and East Asia

PubMed Central

Galinsky, Kevin J.; Bhatia, Gaurav; Loh, Po-Ru; Georgiev, Stoyan; Mukherjee, Sayan; Patterson, Nick J.; Price, Alkes L.

2016-01-01

Searching for genetic variants with unusual differentiation between subpopulations is an established approach for identifying signals of natural selection. However, existing methods generally require discrete subpopulations. We introduce a method that infers selection using principal components (PCs) by identifying variants whose differentiation along top PCs is significantly greater than the null distribution of genetic drift. To enable the application of this method to large datasets, we developed the FastPCA software, which employs recent advances in random matrix theory to accurately approximate top PCs while reducing time and memory cost from quadratic to linear in the number of individuals, a computational improvement of many orders of magnitude. We apply FastPCA to a cohort of 54,734 European Americans, identifying 5 distinct subpopulations spanning the top 4 PCs. Using the PC-based test for natural selection, we replicate previously known selected loci and identify three new genome-wide significant signals of selection, including selection in Europeans at ADH1B. The coding variant rs1229984∗T has previously been associated to a decreased risk of alcoholism and shown to be under selection in East Asians; we show that it is a rare example of independent evolution on two continents. We also detect selection signals at IGFBP3 and IGH, which have also previously been associated to human disease. PMID:26924531

Toward optimal feature and time segment selection by divergence method for EEG signals classification.

PubMed

Wang, Jie; Feng, Zuren; Lu, Na; Luo, Jing

2018-06-01

Feature selection plays an important role in the field of EEG signals based motor imagery pattern classification. It is a process that aims to select an optimal feature subset from the original set. Two significant advantages involved are: lowering the computational burden so as to speed up the learning procedure and removing redundant and irrelevant features so as to improve the classification performance. Therefore, feature selection is widely employed in the classification of EEG signals in practical brain-computer interface systems. In this paper, we present a novel statistical model to select the optimal feature subset based on the Kullback-Leibler divergence measure, and automatically select the optimal subject-specific time segment. The proposed method comprises four successive stages: a broad frequency band filtering and common spatial pattern enhancement as preprocessing, features extraction by autoregressive model and log-variance, the Kullback-Leibler divergence based optimal feature and time segment selection and linear discriminate analysis classification. More importantly, this paper provides a potential framework for combining other feature extraction models and classification algorithms with the proposed method for EEG signals classification. Experiments on single-trial EEG signals from two public competition datasets not only demonstrate that the proposed method is effective in selecting discriminative features and time segment, but also show that the proposed method yields relatively better classification results in comparison with other competitive methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

Wide Temperature Characteristics of Transverse Magnetically Annealed Amorphous Tapes for High Frequency Aerospace Magnetics

NASA Technical Reports Server (NTRS)

Niedra, Janis M.

1999-01-01

100 kHz core loss and magnetization properties of sample transverse magnetically annealed, cobalt-based amorphous and iron-based nanocrystalline tape wound magnetic cores are presented over the temperature range of -150 to 150 C, at selected values of B(sub peak). For B-fields not close to saturation, the core loss is not sensitive to temperature in this range and is as low as seen in the best MnZn power ferrites at their optimum temperatures. Frequency resolved characteristics are given over the range of 50 kHz to 1 MHz, at B(sub peak) = 0.1 T and 50 C only. A linear permeability model is used to interpret and present the magnetization characteristics and several figures of merit applicable to inductor materials arc reviewed. This linear modeling shows that, due to their high permeabilities, these cores must he gapped in order to make up high Q or high current inductors. However, they should serve well, as is, for high frequency, anti ratcheting transformer applications.

Evaluation of Piecewise Polynomial Equations for Two Types of Thermocouples

PubMed Central

Chen, Andrew; Chen, Chiachung

2013-01-01

Thermocouples are the most frequently used sensors for temperature measurement because of their wide applicability, long-term stability and high reliability. However, one of the major utilization problems is the linearization of the transfer relation between temperature and output voltage of thermocouples. The linear calibration equation and its modules could be improved by using regression analysis to help solve this problem. In this study, two types of thermocouple and five temperature ranges were selected to evaluate the fitting agreement of different-order polynomial equations. Two quantitative criteria, the average of the absolute error values |e|ave and the standard deviation of calibration equation estd, were used to evaluate the accuracy and precision of these calibrations equations. The optimal order of polynomial equations differed with the temperature range. The accuracy and precision of the calibration equation could be improved significantly with an adequate higher degree polynomial equation. The technique could be applied with hardware modules to serve as an intelligent sensor for temperature measurement. PMID:24351627

Tumor evolution: Linear, branching, neutral or punctuated?☆

PubMed Central

Davis, Alexander; Gao, Ruli; Navin, Nicholas

2017-01-01

Intratumor heterogeneity has been widely reported in human cancers, but our knowledge of how this genetic diversity emerges over time remains limited. A central challenge in studying tumor evolution is the difficulty in collecting longitudinal samples from cancer patients. Consequently, most studies have inferred tumor evolution from single time-point samples, providing very indirect information. These data have led to several competing models of tumor evolution: linear, branching, neutral and punctuated. Each model makes different assumptions regarding the timing of mutations and selection of clones, and therefore has different implications for the diagnosis and therapeutic treatment of cancer patients. Furthermore, emerging evidence suggests that models may change during tumor progression or operate concurrently for different classes of mutations. Finally, we discuss data that supports the theory that most human tumors evolve from a single cell in the normal tissue. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby. PMID:28110020

Recent advances in integrated photonic sensors.

PubMed

Passaro, Vittorio M N; de Tullio, Corrado; Troia, Benedetto; La Notte, Mario; Giannoccaro, Giovanni; De Leonardis, Francesco

2012-11-09

Nowadays, optical devices and circuits are becoming fundamental components in several application fields such as medicine, biotechnology, automotive, aerospace, food quality control, chemistry, to name a few. In this context, we propose a complete review on integrated photonic sensors, with specific attention to materials, technologies, architectures and optical sensing principles. To this aim, sensing principles commonly used in optical detection are presented, focusing on sensor performance features such as sensitivity, selectivity and rangeability. Since photonic sensors provide substantial benefits regarding compatibility with CMOS technology and integration on chips characterized by micrometric footprints, design and optimization strategies of photonic devices are widely discussed for sensing applications. In addition, several numerical methods employed in photonic circuits and devices, simulations and design are presented, focusing on their advantages and drawbacks. Finally, recent developments in the field of photonic sensing are reviewed, considering advanced photonic sensor architectures based on linear and non-linear optical effects and to be employed in chemical/biochemical sensing, angular velocity and electric field detection.

Recent Advances in Integrated Photonic Sensors

PubMed Central

Passaro, Vittorio M. N.; de Tullio, Corrado; Troia, Benedetto; La Notte, Mario; Giannoccaro, Giovanni; De Leonardis, Francesco

2012-01-01

Nowadays, optical devices and circuits are becoming fundamental components in several application fields such as medicine, biotechnology, automotive, aerospace, food quality control, chemistry, to name a few. In this context, we propose a complete review on integrated photonic sensors, with specific attention to materials, technologies, architectures and optical sensing principles. To this aim, sensing principles commonly used in optical detection are presented, focusing on sensor performance features such as sensitivity, selectivity and rangeability. Since photonic sensors provide substantial benefits regarding compatibility with CMOS technology and integration on chips characterized by micrometric footprints, design and optimization strategies of photonic devices are widely discussed for sensing applications. In addition, several numerical methods employed in photonic circuits and devices, simulations and design are presented, focusing on their advantages and drawbacks. Finally, recent developments in the field of photonic sensing are reviewed, considering advanced photonic sensor architectures based on linear and non-linear optical effects and to be employed in chemical/biochemical sensing, angular velocity and electric field detection. PMID:23202223

Adaptive fusion of infrared and visible images in dynamic scene

NASA Astrophysics Data System (ADS)

Yang, Guang; Yin, Yafeng; Man, Hong; Desai, Sachi

2011-11-01

Multiple modalities sensor fusion has been widely employed in various surveillance and military applications. A variety of image fusion techniques including PCA, wavelet, curvelet and HSV has been proposed in recent years to improve human visual perception for object detection. One of the main challenges for visible and infrared image fusion is to automatically determine an optimal fusion strategy for different input scenes along with an acceptable computational cost. This paper, we propose a fast and adaptive feature selection based image fusion method to obtain high a contrast image from visible and infrared sensors for targets detection. At first, fuzzy c-means clustering is applied on the infrared image to highlight possible hotspot regions, which will be considered as potential targets' locations. After that, the region surrounding the target area is segmented as the background regions. Then image fusion is locally applied on the selected target and background regions by computing different linear combination of color components from registered visible and infrared images. After obtaining different fused images, histogram distributions are computed on these local fusion images as the fusion feature set. The variance ratio which is based on Linear Discriminative Analysis (LDA) measure is employed to sort the feature set and the most discriminative one is selected for the whole image fusion. As the feature selection is performed over time, the process will dynamically determine the most suitable feature for the image fusion in different scenes. Experiment is conducted on the OSU Color-Thermal database, and TNO Human Factor dataset. The fusion results indicate that our proposed method achieved a competitive performance compared with other fusion algorithms at a relatively low computational cost.

An Interactive Tool For Semi-automated Statistical Prediction Using Earth Observations and Models

NASA Astrophysics Data System (ADS)

Zaitchik, B. F.; Berhane, F.; Tadesse, T.

2015-12-01

We developed a semi-automated statistical prediction tool applicable to concurrent analysis or seasonal prediction of any time series variable in any geographic location. The tool was developed using Shiny, JavaScript, HTML and CSS. A user can extract a predictand by drawing a polygon over a region of interest on the provided user interface (global map). The user can select the Climatic Research Unit (CRU) precipitation or Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) as predictand. They can also upload their own predictand time series. Predictors can be extracted from sea surface temperature, sea level pressure, winds at different pressure levels, air temperature at various pressure levels, and geopotential height at different pressure levels. By default, reanalysis fields are applied as predictors, but the user can also upload their own predictors, including a wide range of compatible satellite-derived datasets. The package generates correlations of the variables selected with the predictand. The user also has the option to generate composites of the variables based on the predictand. Next, the user can extract predictors by drawing polygons over the regions that show strong correlations (composites). Then, the user can select some or all of the statistical prediction models provided. Provided models include Linear Regression models (GLM, SGLM), Tree-based models (bagging, random forest, boosting), Artificial Neural Network, and other non-linear models such as Generalized Additive Model (GAM) and Multivariate Adaptive Regression Splines (MARS). Finally, the user can download the analysis steps they used, such as the region they selected, the time period they specified, the predictand and predictors they chose and preprocessing options they used, and the model results in PDF or HTML format. Key words: Semi-automated prediction, Shiny, R, GLM, ANN, RF, GAM, MARS

Integrating environmental covariates and crop modeling into the genomic selection framework to predict genotype by environment interactions.

PubMed

Heslot, Nicolas; Akdemir, Deniz; Sorrells, Mark E; Jannink, Jean-Luc

2014-02-01

Development of models to predict genotype by environment interactions, in unobserved environments, using environmental covariates, a crop model and genomic selection. Application to a large winter wheat dataset. Genotype by environment interaction (G*E) is one of the key issues when analyzing phenotypes. The use of environment data to model G*E has long been a subject of interest but is limited by the same problems as those addressed by genomic selection methods: a large number of correlated predictors each explaining a small amount of the total variance. In addition, non-linear responses of genotypes to stresses are expected to further complicate the analysis. Using a crop model to derive stress covariates from daily weather data for predicted crop development stages, we propose an extension of the factorial regression model to genomic selection. This model is further extended to the marker level, enabling the modeling of quantitative trait loci (QTL) by environment interaction (Q*E), on a genome-wide scale. A newly developed ensemble method, soft rule fit, was used to improve this model and capture non-linear responses of QTL to stresses. The method is tested using a large winter wheat dataset, representative of the type of data available in a large-scale commercial breeding program. Accuracy in predicting genotype performance in unobserved environments for which weather data were available increased by 11.1% on average and the variability in prediction accuracy decreased by 10.8%. By leveraging agronomic knowledge and the large historical datasets generated by breeding programs, this new model provides insight into the genetic architecture of genotype by environment interactions and could predict genotype performance based on past and future weather scenarios.

Linear reduction method for predictive and informative tag SNP selection.

PubMed

He, Jingwu; Westbrooks, Kelly; Zelikovsky, Alexander

2005-01-01

Constructing a complete human haplotype map is helpful when associating complex diseases with their related SNPs. Unfortunately, the number of SNPs is very large and it is costly to sequence many individuals. Therefore, it is desirable to reduce the number of SNPs that should be sequenced to a small number of informative representatives called tag SNPs. In this paper, we propose a new linear algebra-based method for selecting and using tag SNPs. We measure the quality of our tag SNP selection algorithm by comparing actual SNPs with SNPs predicted from selected linearly independent tag SNPs. Our experiments show that for sufficiently long haplotypes, knowing only 0.4% of all SNPs the proposed linear reduction method predicts an unknown haplotype with the error rate below 2% based on 10% of the population.

Passive wide spectrum harmonic filter for adjustable speed drives in oil and gas industry

NASA Astrophysics Data System (ADS)

Al Jaafari, Khaled Ali

Non-linear loads such as variable speed drives constitute the bulky load of oil and gas industry power systems. They are widely used in driving induction and permanent magnet motors for variable speed applications. That is because variable speed drives provide high static and dynamic performance. Moreover, they are known of their high energy efficiency and high motion quality, and high starting torque. However, these non-linear loads are main sources of current and voltage harmonics and lower the quality of electric power system. In fact, it is the six-pulse and twelve-pulse diode and thyristor rectifiers that spoil the AC power line with the dominant harmonics (5th, 7th, 11th). They provide DC voltage to the inverter of the variable speed drives. Typical problems that arise from these harmonics are Harmonic resonances', harmonic losses, interference with electronic equipment, and line voltage distortion at the Point of Common Coupling (PCC). Thus, it is necessary to find efficient, reliable, and economical harmonic filters. The passive filters have definite advantage over active filters in terms of components count, cost and reliability. Reliability and maintenance is a serious issue in drilling rigs which are located in offshore and onshore with extreme operating conditions. Passive filters are tuned to eliminate a certain frequency and therefore there is a need to equip the system with more than one passive filter to eliminate all unwanted frequencies. An alternative solution is Wide Spectrum Harmonic passive filter. The wide spectrum harmonic filters are becoming increasingly popular in these applications and found to overcome some of the limitations of conventional tuned passive filter. The most important feature of wide spectrum harmonic passive filters is that only one capacitor is required to filter a wide range of harmonics. Wide spectrum filter is essentially a low-pass filter for the harmonic at fundamental frequency. It can also be considered as a single-stage passive filter plus input and output inductors. The work proposed gives a complete analysis of wide spectrum harmonic passive filters, the methodology to choose its parameters according to the operational condition, effect of load and source inductance on its characteristics. Also, comparison of the performance of the wide band passive filter with tuned filter is given. The analyses are supported with the simulation results and were verified experimentally. The analysis given in this thesis will be useful for the selection of proper wide spectrum harmonic filters for harmonic mitigation applications in oil and gas industry.

Genome wide association analysis of cold tolerance at germination in temperate japonica rice (Oryza sativa L.) varieties.

PubMed

Sales, Ester; Viruel, Juan; Domingo, Concha; Marqués, Luis

2017-01-01

A pool of 200 traditional, landraces and modern elite and old cultivars of rice, mainly japonica varieties adapted to temperate regions, have been used to perform a genome wide association study to detect chromosome regions associated to low temperature germination (LTG) regulation using a panel of 1672 SNP markers. Phenotyping was performed by determining growth rates when seeds were germinated at 25° and 15°C in order to separate the germination vigorousness from cold tolerance effects. As expected, the ability to produce viable seedlings varied widely among rice cultivars and also depended greatly on temperature. Furthermore, we observed a differential response during seed germination and in coleoptile elongation. Faster development at 15°C was observed in seeds from varieties traditionally used as cold tolerant parents by breeders, along with other potentially useful cultivars, mainly of Italian origin. When phenotypic data were combined with the panel of SNPs for japonica rice cultivars, significant associations were detected for 31 markers: 7 were related to growth rate at 25°C and 24 to growth rates at 15°. Among the latter, some chromosome regions were associated to LTG while others were related to coleoptile elongation. Individual effects of the associated markers were low, but by combining favourable alleles in a linear regression model we estimated that 27 loci significantly explained the observed phenotypic variation. From these, a core panel of 13 markers was selected and, furthermore, two wide regions of chromosomes 3 and 6 were consistently associated to rice LTG. Varieties with higher numbers of favourable alleles for the panels of associated markers significantly correlated with increased phenotypic values at both temperatures, thus corroborating the utility of the tagged markers for marker assisted selection (MAS) when breeding japonica rice for LTG.

Genome wide association analysis of cold tolerance at germination in temperate japonica rice (Oryza sativa L.) varieties

PubMed Central

Viruel, Juan; Domingo, Concha; Marqués, Luis

2017-01-01

A pool of 200 traditional, landraces and modern elite and old cultivars of rice, mainly japonica varieties adapted to temperate regions, have been used to perform a genome wide association study to detect chromosome regions associated to low temperature germination (LTG) regulation using a panel of 1672 SNP markers. Phenotyping was performed by determining growth rates when seeds were germinated at 25° and 15°C in order to separate the germination vigorousness from cold tolerance effects. As expected, the ability to produce viable seedlings varied widely among rice cultivars and also depended greatly on temperature. Furthermore, we observed a differential response during seed germination and in coleoptile elongation. Faster development at 15°C was observed in seeds from varieties traditionally used as cold tolerant parents by breeders, along with other potentially useful cultivars, mainly of Italian origin. When phenotypic data were combined with the panel of SNPs for japonica rice cultivars, significant associations were detected for 31 markers: 7 were related to growth rate at 25°C and 24 to growth rates at 15°. Among the latter, some chromosome regions were associated to LTG while others were related to coleoptile elongation. Individual effects of the associated markers were low, but by combining favourable alleles in a linear regression model we estimated that 27 loci significantly explained the observed phenotypic variation. From these, a core panel of 13 markers was selected and, furthermore, two wide regions of chromosomes 3 and 6 were consistently associated to rice LTG. Varieties with higher numbers of favourable alleles for the panels of associated markers significantly correlated with increased phenotypic values at both temperatures, thus corroborating the utility of the tagged markers for marker assisted selection (MAS) when breeding japonica rice for LTG. PMID:28817683

Optimal design of stimulus experiments for robust discrimination of biochemical reaction networks.

PubMed

Flassig, R J; Sundmacher, K

2012-12-01

Biochemical reaction networks in the form of coupled ordinary differential equations (ODEs) provide a powerful modeling tool for understanding the dynamics of biochemical processes. During the early phase of modeling, scientists have to deal with a large pool of competing nonlinear models. At this point, discrimination experiments can be designed and conducted to obtain optimal data for selecting the most plausible model. Since biological ODE models have widely distributed parameters due to, e.g. biologic variability or experimental variations, model responses become distributed. Therefore, a robust optimal experimental design (OED) for model discrimination can be used to discriminate models based on their response probability distribution functions (PDFs). In this work, we present an optimal control-based methodology for designing optimal stimulus experiments aimed at robust model discrimination. For estimating the time-varying model response PDF, which results from the nonlinear propagation of the parameter PDF under the ODE dynamics, we suggest using the sigma-point approach. Using the model overlap (expected likelihood) as a robust discrimination criterion to measure dissimilarities between expected model response PDFs, we benchmark the proposed nonlinear design approach against linearization with respect to prediction accuracy and design quality for two nonlinear biological reaction networks. As shown, the sigma-point outperforms the linearization approach in the case of widely distributed parameter sets and/or existing multiple steady states. Since the sigma-point approach scales linearly with the number of model parameter, it can be applied to large systems for robust experimental planning. An implementation of the method in MATLAB/AMPL is available at http://www.uni-magdeburg.de/ivt/svt/person/rf/roed.html. flassig@mpi-magdeburg.mpg.de Supplementary data are are available at Bioinformatics online.

Wide-range and accurate modeling of linear alkylbenzene sulfonate (LAS) adsorption/desorption on agricultural soil.

PubMed

Oliver-Rodríguez, B; Zafra-Gómez, A; Reis, M S; Duarte, B P M; Verge, C; de Ferrer, J A; Pérez-Pascual, M; Vílchez, J L

2015-11-01

In this paper, rigorous data and adequate models about linear alkylbenzene sulfonate (LAS) adsorption/desorption on agricultural soil are presented, contributing with a substantial improvement over available adsorption works. The kinetics of the adsorption/desorption phenomenon and the adsorption/desorption equilibrium isotherms were determined through batch studies for total LAS amount and also for each homologue series: C10, C11, C12 and C13. The proposed multiple pseudo-first order kinetic model provides the best fit to the kinetic data, indicating the presence of two adsorption/desorption processes in the general phenomenon. Equilibrium adsorption and desorption data have been properly fitted by a model consisting of a Langmuir plus quadratic term, which provides a good integrated description of the experimental data over a wide range of concentrations. At low concentrations, the Langmuir term explains the adsorption of LAS on soil sites which are highly selective of the n-alkyl groups and cover a very small fraction of the soil surface area, whereas the quadratic term describes adsorption on the much larger part of the soil surface and on LAS retained at moderate to high concentrations. Since adsorption/desorption phenomenon plays a major role in the LAS behavior in soils, relevant conclusions can be drawn from the obtained results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Understanding Linear Function: A Comparison of Selected Textbooks from England and Shanghai

ERIC Educational Resources Information Center

Wang, Yuqian; Barmby, Patrick; Bolden, David

2017-01-01

This study describes a comparison of how worked examples in selected textbooks from England and Shanghai presented possible learning trajectories towards understanding linear function. Six selected English textbooks and one Shanghai compulsory textbook were analysed with regards to the understanding required for pure mathematics knowledge in…

A linear model fails to predict orientation selectivity of cells in the cat visual cortex.

PubMed Central

Volgushev, M; Vidyasagar, T R; Pei, X

1996-01-01

1. Postsynaptic potentials (PSPs) evoked by visual stimulation in simple cells in the cat visual cortex were recorded using in vivo whole-cell technique. Responses to small spots of light presented at different positions over the receptive field and responses to elongated bars of different orientations centred on the receptive field were recorded. 2. To test whether a linear model can account for orientation selectivity of cortical neurones, responses to elongated bars were compared with responses predicted by a linear model from the receptive field map obtained from flashing spots. 3. The linear model faithfully predicted the preferred orientation, but not the degree of orientation selectivity or the sharpness of orientation tuning. The ratio of optimal to non-optimal responses was always underestimated by the model. 4. Thus non-linear mechanisms, which can include suppression of non-optimal responses and/or amplification of optimal responses, are involved in the generation of orientation selectivity in the primary visual cortex. PMID:8930828

A Comparative Analysis for Selection of Appropriate Mother Wavelet for Detection of Stationary Disturbances

NASA Astrophysics Data System (ADS)

Kamble, Saurabh Prakash; Thawkar, Shashank; Gaikwad, Vinayak G.; Kothari, D. P.

2017-12-01

Detection of disturbances is the first step of mitigation. Power electronics plays a crucial role in modern power system which makes system operation efficient but it also bring stationary disturbances in the power system and added impurities to the supply. It happens because of the non-linear loads used in modern day power system which inject disturbances like harmonic disturbances, flickers, sag etc. in power grid. These impurities can damage equipments so it is necessary to mitigate these impurities present in the supply very quickly. So, digital signal processing techniques are incorporated for detection purpose. Signal processing techniques like fast Fourier transform, short-time Fourier transform, Wavelet transform etc. are widely used for the detection of disturbances. Among all, wavelet transform is widely used because of its better detection capabilities. But, which mother wavelet has to use for detection is still a mystery. Depending upon the periodicity, the disturbances are classified as stationary and non-stationary disturbances. This paper presents the importance of selection of mother wavelet for analyzing stationary disturbances using discrete wavelet transform. Signals with stationary disturbances of various frequencies are generated using MATLAB. The analysis of these signals is done using various mother wavelets like Daubechies and bi-orthogonal wavelets and the measured root mean square value of stationary disturbance is obtained. The measured value obtained by discrete wavelet transform is compared with the exact RMS value of the frequency component and the percentage differences are presented which helps to select optimum mother wavelet.

Fuzzy bi-objective linear programming for portfolio selection problem with magnitude ranking function

NASA Astrophysics Data System (ADS)

Kusumawati, Rosita; Subekti, Retno

2017-04-01

Fuzzy bi-objective linear programming (FBOLP) model is bi-objective linear programming model in fuzzy number set where the coefficients of the equations are fuzzy number. This model is proposed to solve portfolio selection problem which generate an asset portfolio with the lowest risk and the highest expected return. FBOLP model with normal fuzzy numbers for risk and expected return of stocks is transformed into linear programming (LP) model using magnitude ranking function.

Lipidomics by ultrahigh performance liquid chromatography-high resolution mass spectrometry and its application to complex biological samples

PubMed Central

Triebl, Alexander; Trötzmüller, Martin; Hartler, Jürgen; Stojakovic, Tatjana; Köfeler, Harald C

2018-01-01

An improved approach for selective and sensitive identification and quantitation of lipid molecular species using reversed phase chromatography coupled to high resolution mass spectrometry was developed. The method is applicable to a wide variety of biological matrices using a simple liquid-liquid extraction procedure. Together, this approach combines three selectivity criteria: Reversed phase chromatography separates lipids according to their acyl chain length and degree of unsaturation and is capable of resolving positional isomers of lysophospholipids, as well as structural isomers of diacyl phospholipids and glycerolipids. Orbitrap mass spectrometry delivers the elemental composition of both positive and negative ions with high mass accuracy. Finally, automatically generated tandem mass spectra provide structural insight into numerous glycerolipids, phospholipids, and sphingolipids within a single run. Method validation resulted in a linearity range of more than four orders of magnitude, good values for accuracy and precision at biologically relevant concentration levels, and limits of quantitation of a few femtomoles on column. Hundreds of lipid molecular species were detected and quantified in three different biological matrices, which cover well the wide variety and complexity of various model organisms in lipidomic research. Together with a reliable software package, this method is a prime choice for global lipidomic analysis of even the most complex biological samples. PMID:28415015

Lipidomics by ultrahigh performance liquid chromatography-high resolution mass spectrometry and its application to complex biological samples.

PubMed

Triebl, Alexander; Trötzmüller, Martin; Hartler, Jürgen; Stojakovic, Tatjana; Köfeler, Harald C

2017-05-15

An improved approach for selective and sensitive identification and quantitation of lipid molecular species using reversed phase chromatography coupled to high resolution mass spectrometry was developed. The method is applicable to a wide variety of biological matrices using a simple liquid-liquid extraction procedure. Together, this approach combines multiple selectivity criteria: Reversed phase chromatography separates lipids according to their acyl chain length and degree of unsaturation and is capable of resolving positional isomers of lysophospholipids, as well as structural isomers of diacyl phospholipids and glycerolipids. Orbitrap mass spectrometry delivers the elemental composition of both positive and negative ions with high mass accuracy. Finally, automatically generated tandem mass spectra provide structural insight into numerous glycerolipids, phospholipids, and sphingolipids within a single run. Calibration showed linearity ranges of more than four orders of magnitude, good values for accuracy and precision at biologically relevant concentration levels, and limits of quantitation of a few femtomoles on column. Hundreds of lipid molecular species were detected and quantified in three different biological matrices, which cover well the wide variety and complexity of various model organisms in lipidomic research. Together with a software package, this method is a prime choice for global lipidomic analysis of even the most complex biological samples. Copyright © 2017 Elsevier B.V. All rights reserved.

A selective iodide ion sensor electrode based on functionalized ZnO nanotubes.

PubMed

Ibupoto, Zafar Hussain; Khun, Kimleang; Willander, Magnus

2013-02-04

In this research work, ZnO nanotubes were fabricated on a gold coated glass substrate through chemical etching by the aqueous chemical growth method. For the first time a nanostructure-based iodide ion selective electrode was developed. The ZnO nanotubes were functionalized with miconazole ion exchanger and the electromotive force (EMF) was measured by the potentiometric method. The iodide ion sensor exhibited a linear response over a wide range of concentrations (1 × 10-6 to 1 × 10-1 M) and excellent sensitivity of -62 ± 1 mV/decade. The detection limit of the proposed sensor was found to be 5 × 10-7 M. The effects of pH, temperature, additive, plasticizer and stabilizer on the potential response of iodide ion selective electrode were also studied. The proposed iodide ion sensor demonstrated a fast response time of less than 5 s and high selectivity against common organic and the inorganic anions. All the obtained results revealed that the iodide ion sensor based on functionalized ZnO nanotubes may be used for the detection of iodide ion in environmental water samples, pharmaceutical products and other real samples.

A Selective Iodide Ion Sensor Electrode Based on Functionalized ZnO Nanotubes

PubMed Central

Ibupoto, Zafar Hussain; Khun, Kimleang; Willander, Magnus

2013-01-01

In this research work, ZnO nanotubes were fabricated on a gold coated glass substrate through chemical etching by the aqueous chemical growth method. For the first time a nanostructure-based iodide ion selective electrode was developed. The ZnO nanotubes were functionalized with miconazole ion exchanger and the electromotive force (EMF) was measured by the potentiometric method. The iodide ion sensor exhibited a linear response over a wide range of concentrations (1 × 10−6 to 1 × 10−1 M) and excellent sensitivity of −62 ± 1 mV/decade. The detection limit of the proposed sensor was found to be 5 × 10−7 M. The effects of pH, temperature, additive, plasticizer and stabilizer on the potential response of iodide ion selective electrode were also studied. The proposed iodide ion sensor demonstrated a fast response time of less than 5 s and high selectivity against common organic and the inorganic anions. All the obtained results revealed that the iodide ion sensor based on functionalized ZnO nanotubes may be used for the detection of iodide ion in environmental water samples, pharmaceutical products and other real samples. PMID:23385412

Efficient robust doubly adaptive regularized regression with applications.

PubMed

Karunamuni, Rohana J; Kong, Linglong; Tu, Wei

2018-01-01

We consider the problem of estimation and variable selection for general linear regression models. Regularized regression procedures have been widely used for variable selection, but most existing methods perform poorly in the presence of outliers. We construct a new penalized procedure that simultaneously attains full efficiency and maximum robustness. Furthermore, the proposed procedure satisfies the oracle properties. The new procedure is designed to achieve sparse and robust solutions by imposing adaptive weights on both the decision loss and the penalty function. The proposed method of estimation and variable selection attains full efficiency when the model is correct and, at the same time, achieves maximum robustness when outliers are present. We examine the robustness properties using the finite-sample breakdown point and an influence function. We show that the proposed estimator attains the maximum breakdown point. Furthermore, there is no loss in efficiency when there are no outliers or the error distribution is normal. For practical implementation of the proposed method, we present a computational algorithm. We examine the finite-sample and robustness properties using Monte Carlo studies. Two datasets are also analyzed.

One-step Synthesis of Highly Luminescent Nitrogen-doped Carbon Dots for Selective and Sensitive Detection of Mercury(II) Ions and Cellular Imaging.

PubMed

Liu, Ying; Liao, Mei; He, Xueling; Liu, Xia; Kou, Xingming; Xiao, Dan

2015-01-01

In this paper, nitrogen-doped carbon dots (N-CDs) with high quantum yield (QY) of 40.5% were prepared through a facile and straightforward hydrothermal route. The as-prepared N-CDs exhibited excellent photoluminescence properties, good water-solublity and photostability, negligible cytotoxicity and favourable biocompatibility. Such N-CDs were found to serve as an effective fluorescent sensor for selective and sensitive detection of Hg(2+) in a wide linear response concentration range of 0 - 8 μM with a limit of detection (LOD) of 0.087 μM and could be applied to the determination of Hg(2+) in environmental water samples. The corresponding mechanisms were discussed in detail. Moreover, another attractive finding was that the N-CDs showed satisfactory performance in bioimaging before and after the addition of Hg(2+) in human lung cancer PC14 cells. With excellent sensitivity, selectivity and biocompatibility, such cheap carbonmaterials are potentially suitable for monitoring of Hg(2+) in environmental applications and promising for biological applications.

Quantitation of cocaine and cocaethylene in small volumes of rat whole blood using gas chromatography-mass spectrometry.

PubMed

Burdick, J D; Boni, R L; Fochtman, F W

1997-05-01

A simple solid phase extraction (SPE) technique combined with gas chromatography-mass spectrometry (GC/MS) operated in selected ion monitoring (SIM) mode is described for quantitation of cocaine and cocaethylene in small samples (250 microliters) of rat whole blood. Use of (N-[2H3C])-cocaine and (N-[2H3C])-cocaethylene internal standards resulted in high sensitivity and selectivity for this analytical method. Analysis was performed using a Hewlett-Packard 5890 GC equipped with a 7673A Automatic Liquid Sampler linked to a Hewlett-Packard 5972 Mass Selective Detector. Separation of analytes was accomplished on a cross-linked methyl silicone gum capillary column (Ultra 1: 12m x 0.2mm (i.d.) x 0.33 microns). Linearity was established over a wide range of concentrations (5.0-2000.0 ng ml-1) with good precision. Limits of detection (LOD) were 1.0 and 2.0 ng ml-1 for cocaine and cocaethylene, respectively. This analytical method was designed for use in pharmacokinetic experiments studying the formation of cocaethylene following ethanol pretreatment in rats administered cocaine.

An empirical analysis of thermal protective performance of fabrics used in protective clothing.

PubMed

Mandal, Sumit; Song, Guowen

2014-10-01

Fabric-based protective clothing is widely used for occupational safety of firefighters/industrial workers. The aim of this paper is to study thermal protective performance provided by fabric systems and to propose an effective model for predicting the thermal protective performance under various thermal exposures. Different fabric systems that are commonly used to manufacture thermal protective clothing were selected. Laboratory simulations of the various thermal exposures were created to evaluate the protective performance of the selected fabric systems in terms of time required to generate second-degree burns. Through the characterization of selected fabric systems in a particular thermal exposure, various factors affecting the performances were statistically analyzed. The key factors for a particular thermal exposure were recognized based on the t-test analysis. Using these key factors, the performance predictive multiple linear regression and artificial neural network (ANN) models were developed and compared. The identified best-fit ANN models provide a basic tool to study thermal protective performance of a fabric. © The Author 2014. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Utilization of Meteorological Satellite Imagery for World-Wide Environmental Monitoring the Lower Mississippi River Flood of 1979 - Case 1. [St. Louis, Missouri

NASA Technical Reports Server (NTRS)

Helfert, M. R.; Mccrary, D. G.; Gray, T. I. (Principal Investigator)

1981-01-01

The 1979 Lower Mississippi River flood was selected as a test case of environmental disaster monitoring utilizing NOAA-n imagery. A small scale study of the St. Louis Missouri area comparing ERTS-1 (LANDSAT) and NOAA-2 imagery and flood studies using only LANDSAT imagery for mapping the Rad River of the North, and Nimbus-5 imagery for East Australia show the nonmeteorological applications of NOAA satellites. While the level of NOAA-n imagery detail is not that of a LANDSAT image, for operational environmental monitoring users the NOAA-n imagery may provide acceptable linear resolution and spectral isolation.

Spectrofluorometric determination of DNA and RNA with berberine

NASA Astrophysics Data System (ADS)

Gong, Guo-Quan; Zong, Zhi-Xin; Song, Yu-Min

1999-08-01

On binding to nucleic acids, the dye berberine increases its fluorescence quantum efficiency by a factor of 25-30. Based on this, an easy, rapid and accurate method for the determination of nucleic acids was developed. Berberine is very like ethidium bromide (EB), but it is non-poisonous. Determination can be made at any pH between 4 and 10, where the native structure of DNA and RNA is not disrupted. The maximum emission is near 520 nm for excitation at 355 or 450 nm. This method has good sensitivity (0.01 μg ml -1 of ctDNA), high selectivity and a wide linear range (0.05-14.0 μg ml -1 of ctDNA).

Fast and wide tuning wavelength-swept source based on dispersion-tuned fiber optical parametric oscillator.

PubMed

Zhou, Yue; Cheung, Kim K Y; Li, Qin; Yang, Sigang; Chui, P C; Wong, Kenneth K Y

2010-07-15

We demonstrate a dispersion-tuned fiber optical parametric oscillator (FOPO)-based swept source with a sweep rate of 40 kHz and a wavelength tuning range of 109 nm around 1550 nm. The cumulative speed exceeds 4,000,000 nm/s. The FOPO is pumped by a sinusoidally modulated pump, which is driven by a clock sweeping linearly from 1 to 1.0006 GHz. A spool of dispersion-compensating fiber is added inside the cavity to perform dispersion tuning. The instantaneous linewidth is 0.8 nm without the use of any wavelength selective element inside the cavity. 1 GHz pulses with pulse width of 150 ps are generated.

Model Selection with the Linear Mixed Model for Longitudinal Data

ERIC Educational Resources Information Center

Ryoo, Ji Hoon

2011-01-01

Model building or model selection with linear mixed models (LMMs) is complicated by the presence of both fixed effects and random effects. The fixed effects structure and random effects structure are codependent, so selection of one influences the other. Most presentations of LMM in psychology and education are based on a multilevel or…

Sensing small neurotransmitter-enzyme interaction with nanoporous gated ion-sensitive field effect transistors.

PubMed

Kisner, Alexandre; Stockmann, Regina; Jansen, Michael; Yegin, Ugur; Offenhäusser, Andreas; Kubota, Lauro Tatsuo; Mourzina, Yulia

2012-01-15

Ion-sensitive field effect transistors with gates having a high density of nanopores were fabricated and employed to sense the neurotransmitter dopamine with high selectivity and detectability at micromolar range. The nanoporous structure of the gates was produced by applying a relatively simple anodizing process, which yielded a porous alumina layer with pores exhibiting a mean diameter ranging from 20 to 35 nm. Gate-source voltages of the transistors demonstrated a pH-dependence that was linear over a wide range and could be understood as changes in surface charges during protonation and deprotonation. The large surface area provided by the pores allowed the physical immobilization of tyrosinase, which is an enzyme that oxidizes dopamine, on the gates of the transistors, and thus, changes the acid-base behavior on their surfaces. Concentration-dependent dopamine interacting with immobilized tyrosinase showed a linear dependence into a physiological range of interest for dopamine concentration in the changes of gate-source voltages. In comparison with previous approaches, a response time relatively fast for detecting dopamine was obtained. Additionally, selectivity assays for other neurotransmitters that are abundantly found in the brain were examined. These results demonstrate that the nanoporous structure of ion-sensitive field effect transistors can easily be used to immobilize specific enzyme that can readily and selectively detect small neurotransmitter molecule based on its acid-base interaction with the receptor. Therefore, it could serve as a technology platform for molecular studies of neurotransmitter-enzyme binding and drugs screening. Copyright © 2011 Elsevier B.V. All rights reserved.

Tachydysrhythmia treatment and adverse events in patients with wolff-Parkinson-white syndrome.

PubMed

Siegelman, Jeffrey N; Marill, Keith A; Adler, Jonathan N

2014-09-01

Current guidelines recommend avoiding atrioventricular-nodal blocking agents (AVNB) when treating tachydysrhythmias in Wolff-Parkinson-White syndrome (WPW) patients. We investigated medications selected and resulting outcomes for patients with tachydysrhythmias and WPW. In this single-center retrospective cohort study, we searched a hospital-wide database for the following inclusion criteria: WPW, tachycardia, and intravenous antidysrhythmics. The composite outcome of adverse events was acceleration of tachycardia, new hypotension, new malignant dysrhythmia, and cardioversion. The difference in binomial proportions of patients meeting the composite outcome after AVNB or non-AVNB (NAVNB) treatment was calculated after dividing the groups by QRS duration. A random-effects mixed linear analysis was performed to analyze the vital sign response. The initial database search yielded 1158 patient visits, with 60 meeting inclusion criteria. Patients' median age was 52.5 years; 53% were male, 43% presented in wide complex tachycardia (WCT), with 75% in atrial fibrillation (AF) or flutter. AVNBs were administered in 42 (70%) patient visits. For those patients with WCT in AF, the difference in proportions of patients meeting the composite outcome after AVNBs vs. NAVNBs treatment was an increase of 3% (95% confidence interval [CI] -39%-49%), and for those with narrow complex AF it was a decrease of 13% (95% CI -37%-81%). No instances of malignant dysrhythmia occurred. Mixed linear analysis showed no statistically significant effects on heart rate, though suggested a trend toward increasing heart rate after AVNB in wide complex AF. In this sample of WPW-associated tachydysrhythmia patients, many were treated with AVNBs. The composite outcome was similarly met after use of either AVNB or NAVNB, and no malignant dysrhythmias were observed. Copyright © 2014 Elsevier Inc. All rights reserved.

Will genomic selection be a practical method for plant breeding?

PubMed

Nakaya, Akihiro; Isobe, Sachiko N

2012-11-01

Genomic selection or genome-wide selection (GS) has been highlighted as a new approach for marker-assisted selection (MAS) in recent years. GS is a form of MAS that selects favourable individuals based on genomic estimated breeding values. Previous studies have suggested the utility of GS, especially for capturing small-effect quantitative trait loci, but GS has not become a popular methodology in the field of plant breeding, possibly because there is insufficient information available on GS for practical use. In this review, GS is discussed from a practical breeding viewpoint. Statistical approaches employed in GS are briefly described, before the recent progress in GS studies is surveyed. GS practices in plant breeding are then reviewed before future prospects are discussed. Statistical concepts used in GS are discussed with genetic models and variance decomposition, heritability, breeding value and linear model. Recent progress in GS studies is reviewed with a focus on empirical studies. For the practice of GS in plant breeding, several specific points are discussed including linkage disequilibrium, feature of populations and genotyped markers and breeding scheme. Currently, GS is not perfect, but it is a potent, attractive and valuable approach for plant breeding. This method will be integrated into many practical breeding programmes in the near future with further advances and the maturing of its theory.

Genomic selection in sugar beet breeding populations

PubMed Central

2013-01-01

Background Genomic selection exploits dense genome-wide marker data to predict breeding values. In this study we used a large sugar beet population of 924 lines representing different germplasm types present in breeding populations: unselected segregating families and diverse lines from more advanced stages of selection. All lines have been intensively phenotyped in multi-location field trials for six agronomically important traits and genotyped with 677 SNP markers. Results We used ridge regression best linear unbiased prediction in combination with fivefold cross-validation and obtained high prediction accuracies for all except one trait. In addition, we investigated whether a calibration developed based on a training population composed of diverse lines is suited to predict the phenotypic performance within families. Our results show that the prediction accuracy is lower than that obtained within the diverse set of lines, but comparable to that obtained by cross-validation within the respective families. Conclusions The results presented in this study suggest that a training population derived from intensively phenotyped and genotyped diverse lines from a breeding program does hold potential to build up robust calibration models for genomic selection. Taken together, our results indicate that genomic selection is a valuable tool and can thus complement the genomics toolbox in sugar beet breeding. PMID:24047500

Phylogeny of the beaked whale genus Mesoplodon (Ziphiidae: Cetacea) revealed by nuclear introns: implications for the evolution of male tusks.

PubMed

Dalebout, Merel L; Steel, Debbie; Baker, C Scott

2008-12-01

With 14 species currently recognized, the beaked whale genus Mesoplodon (family Ziphiidae) is the most speciose in the order Cetacea. Beaked whales are widely distributed but are rarely seen at sea due to their oceanic distribution, deep-diving capacity, and apparent low abundance. Morphological differentiation among Mesoplodon species is relatively limited, with the exception of tooth form in adult males. Based on scarring patterns, males appear to use their tusk-like teeth as weapons in aggressive encounters with other males. Females are effectively toothless. We used sequences from seven nuclear introns (3348 base pairs) to construct a robust and highly resolved phylogeny, which was then used as a framework to test predictions from four hypotheses seeking to explain patterns of Mesoplodon tusk morphology and/or the processes that have driven the diversification of this genus: (1) linear progression of tusk form; (2) allopatric speciation through isolation in adjacent deep-sea canyons; (3) sympatric speciation through sexual selection on tusks; and (4) selection for species-recognition cues. Maximum-likelihood and Bayesian reconstructions confirmed the monophyly of the genus and revealed that what were considered ancestral and derived tusk forms have in fact arisen independently on several occasions, contrary to predictions from the linear-progression hypothesis. Further, none of the three well-supported species clades was confined to a single ocean basin, as might have been expected from the deep-sea canyon-isolation or sexual-selection hypotheses, and some species with similar tusks have overlapping distributions, contrary to predictions from the species-recognition hypothesis. However, the divergent tusk forms and sympatric distributions of three of the four sister-species pairs identified suggest that sexual selection on male tusks has likely played an important role in this unique radiation, although other forces are clearly also involved. To our knowledge, this is the first time that sexual selection has been explicitly implicated in the radiation of a mammalian group outside terrestrial ungulates.

Evolution stings: the origin and diversification of scorpion toxin peptide scaffolds.

PubMed

Sunagar, Kartik; Undheim, Eivind A B; Chan, Angelo H C; Koludarov, Ivan; Muñoz-Gómez, Sergio A; Antunes, Agostinho; Fry, Bryan G

2013-12-13

The episodic nature of natural selection and the accumulation of extreme sequence divergence in venom-encoding genes over long periods of evolutionary time can obscure the signature of positive Darwinian selection. Recognition of the true biocomplexity is further hampered by the limited taxon selection, with easy to obtain or medically important species typically being the subject of intense venom research, relative to the actual taxonomical diversity in nature. This holds true for scorpions, which are one of the most ancient terrestrial venomous animal lineages. The family Buthidae that includes all the medically significant species has been intensely investigated around the globe, while almost completely ignoring the remaining non-buthid families. Australian scorpion lineages, for instance, have been completely neglected, with only a single scorpion species (Urodacus yaschenkoi) having its venom transcriptome sequenced. Hence, the lack of venom composition and toxin sequence information from an entire continent's worth of scorpions has impeded our understanding of the molecular evolution of scorpion venom. The molecular origin, phylogenetic relationships and evolutionary histories of most scorpion toxin scaffolds remain enigmatic. In this study, we have sequenced venom gland transcriptomes of a wide taxonomical diversity of scorpions from Australia, including buthid and non-buthid representatives. Using state-of-art molecular evolutionary analyses, we show that a majority of CSα/β toxin scaffolds have experienced episodic influence of positive selection, while most non-CSα/β linear toxins evolve under the extreme influence of negative selection. For the first time, we have unraveled the molecular origin of the major scorpion toxin scaffolds, such as scorpion venom single von Willebrand factor C-domain peptides (SV-SVC), inhibitor cystine knot (ICK), disulphide-directed beta-hairpin (DDH), bradykinin potentiating peptides (BPP), linear non-disulphide bridged peptides and antimicrobial peptides (AMP). We have thus demonstrated that even neglected lineages of scorpions are a rich pool of novel biochemical components, which have evolved over millions of years to target specific ion channels in prey animals, and as a result, possess tremendous implications in therapeutics.

Prediction of the sorption capacities and affinities of organic chemicals by XAD-7.

PubMed

Yang, Kun; Qi, Long; Wei, Wei; Wu, Wenhao; Lin, Daohui

2016-01-01

Macro-porous resins are widely used as adsorbents for the treatment of organic contaminants in wastewater and for the pre-concentration of organic solutes from water. However, the sorption mechanisms for organic contaminants on such adsorbents have not been systematically investigated so far. Therefore, in this study, the sorption capacities and affinities of 24 organic chemicals by XAD-7 were investigated and the experimentally obtained sorption isotherms were fitted to the Dubinin-Ashtakhov model. Linear positive correlations were observed between the sorption capacities and the solubilities (SW) of the chemicals in water or octanol and between the sorption affinities and the solvatochromic parameters of the chemicals, indicating that the sorption of various organic compounds by XAD-7 occurred by non-linear partitioning into XAD-7, rather than by adsorption on XAD-7 surfaces. Both specific interactions (i.e., hydrogen-bonding interactions) as well as nonspecific interactions were considered to be responsible for the non-linear partitioning. The correlation equations obtained in this study allow the prediction of non-linear partitioning using well-known chemical parameters, namely SW, octanol-water partition coefficients (KOW), and the hydrogen-bonding donor parameter (αm). The effect of pH on the sorption of ionizable organic compounds (IOCs) could also be predicted by combining the correlation equations with additional equations developed from the estimation of IOC dissociation rates. The prediction equations developed in this study and the proposed non-linear partition mechanism shed new light on the selective removal and pre-concentration of organic solutes from water and on the regeneration of exhausted XAD-7 using solvent extraction.

Near-Infrared Fluorescent Turn-on Probe with a Remarkable Large Stokes Shift for Imaging Selenocysteine in Living Cells and Animals.

PubMed

Feng, Weiyong; Li, Meixing; Sun, Yao; Feng, Guoqiang

2017-06-06

Selenocysteine (Sec) is the 21st naturally occurring amino acid and has emerged as an important sensing target in recent years. However, fluorescent detection of Sec in living systems is challenging. To date, very few fluorescent Sec probes have been reported and most of them respond fluorescence to Sec in the visible region. In this paper, a very promising near-infrared fluorescent probe for Sec was developed. This probe works in aqueous solution over a wide pH range under mild conditions and can be used for rapid, highly selective and sensitive detection of Sec with significant near-infrared fluorescent turn-on signal changes. In addition, it features a remarkable large Stokes shift (192 nm) and a low detection limit (60 nM) for Sec with a wide linear range (0-70 μM). Moreover, this probe can be conveniently used to detect Sec in serum samples, living cells, and animals, indicating it holds great promise for biological applications.

Wide variation of prostate-specific antigen doubling time of untreated, clinically localized, low-to-intermediate grade, prostate carcinoma.

PubMed

Choo, Richard; Klotz, Laurence; Deboer, Gerrit; Danjoux, Cyril; Morton, Gerard C

2004-08-01

To assess the prostate specific antigen (PSA) doubling time of untreated, clinically localized, low-to-intermediate grade prostate carcinoma. A prospective single-arm cohort study has been in progress since November 1995 to assess the feasibility of a watchful-observation protocol with selective delayed intervention for clinically localized, low-to-intermediate grade prostate adenocarcinoma. The PSA doubling time was estimated from a linear regression of ln(PSA) against time, assuming a simple exponential growth model. As of March 2003, 231 patients had at least 6 months of follow-up (median 45) and at least three PSA measurements (median 8, range 3-21). The distribution of the doubling time was: < 2 years, 26 patients; 2-5 years, 65; 5-10 years, 42; 10-20 years, 26; 20-50 years, 16; >50 years, 56. The median doubling time was 7.0 years; 42% of men had a doubling time of >10 years. The doubling time of untreated clinically localized, low-to-intermediate grade prostate cancer varies widely.

A new skin friction balance and selected measurements

NASA Technical Reports Server (NTRS)

Vakili, A. D.

1992-01-01

A new skin friction balance with moving belt has been developed for measurement of the surface shear stress component in the direction of belt motion. The device is described in this paper with typical measurement results. This instrument is symmetric in design with small moving mass negligible internal friction. It is 3.8 cm high, 3.8 cm long and 2.1 cm wide, with the sensing surface 0.7 cm wide and 1.5 cm long, and it can be made in various sizes. The unique design of this instrument has reduced some of the errors associated with conventional floating-element balances. The instrument can use various sensing systems and the output signal is a linear function of the wall shear stress. Measurements show good agreement with data obtained by the floating element balances and flat plate prediction techniques. Dynamic measurements have been made in a limited range. The overall uncertainty of measurement is estimated to be +/- 2 percent.

Minimizing energy dissipation of matrix multiplication kernel on Virtex-II

NASA Astrophysics Data System (ADS)

Choi, Seonil; Prasanna, Viktor K.; Jang, Ju-wook

2002-07-01

In this paper, we develop energy-efficient designs for matrix multiplication on FPGAs. To analyze the energy dissipation, we develop a high-level model using domain-specific modeling techniques. In this model, we identify architecture parameters that significantly affect the total energy (system-wide energy) dissipation. Then, we explore design trade-offs by varying these parameters to minimize the system-wide energy. For matrix multiplication, we consider a uniprocessor architecture and a linear array architecture to develop energy-efficient designs. For the uniprocessor architecture, the cache size is a parameter that affects the I/O complexity and the system-wide energy. For the linear array architecture, the amount of storage per processing element is a parameter affecting the system-wide energy. By using maximum amount of storage per processing element and minimum number of multipliers, we obtain a design that minimizes the system-wide energy. We develop several energy-efficient designs for matrix multiplication. For example, for 6×6 matrix multiplication, energy savings of upto 52% for the uniprocessor architecture and 36% for the linear arrary architecture is achieved over an optimized library for Virtex-II FPGA from Xilinx.

CORRELATION PURSUIT: FORWARD STEPWISE VARIABLE SELECTION FOR INDEX MODELS

PubMed Central

Zhong, Wenxuan; Zhang, Tingting; Zhu, Yu; Liu, Jun S.

2012-01-01

In this article, a stepwise procedure, correlation pursuit (COP), is developed for variable selection under the sufficient dimension reduction framework, in which the response variable Y is influenced by the predictors X1, X2, …, Xp through an unknown function of a few linear combinations of them. Unlike linear stepwise regression, COP does not impose a special form of relationship (such as linear) between the response variable and the predictor variables. The COP procedure selects variables that attain the maximum correlation between the transformed response and the linear combination of the variables. Various asymptotic properties of the COP procedure are established, and in particular, its variable selection performance under diverging number of predictors and sample size has been investigated. The excellent empirical performance of the COP procedure in comparison with existing methods are demonstrated by both extensive simulation studies and a real example in functional genomics. PMID:23243388

Fluorescent probes for "off-on" highly sensitive detection of Hg²⁺ and L-cysteine based on nitrogen-doped carbon dots.

PubMed

Zhang, Yi; Cui, Peipei; Zhang, Feng; Feng, Xiaoting; Wang, Yaling; Yang, Yongzhen; Liu, Xuguang

2016-05-15

Fluorescent nitrogen-doped carbon dots (NCDs) were synthesized by a facile, and low-cost one-step hydrothermal strategy using citric acid as carbon source and ammonia solution as nitrogen source for the first time. The obtained NCDs show stable blue fluorescence with a high quantum yield of 35.4%, along with the fluorescence lifetime of ca. 6.75 ns. Most importantly, Hg(2+) can completely quench the fluorescence of NCDs as a result of the formation of a non-fluorescent stable NCDs-Hg(2+) complex. Static fluorescence quenching towards Hg(2+) is proved by the Stern-Volmer equation, ultraviolet-visible absorption spectra, temperature dependent quenching and fluorescence lifetime measurements. Subsequently, the fluorescence of the NCDs-Hg(2+) system is completely recovered with the addition L-cysteine (L-Cys) owing to the dissociation of NCDs-Hg(2+) complex to form a more stable Hg(2+)-L-Cys complex by Hg(2+)-S bonding. Therefore, such NCDs can be used as an effective fluorescent "turn-off" probe for rapid, rather highly selective and sensitive detection of Hg(2+), with a limit of detection (LOD) as low as 1.48 nM and a linear detection range of 0-10 μM. Interestingly, NCDs-Hg(2+) system can be conveniently employed as a fluorescent "turn-on" sensor for highly selective and sensitive detection of L-Cys with a low LOD of 0.79 nM and a wide linear detection range of 0-50 μM. Further, the sensitivity of NCDs to Hg(2+) is preserved in tap water with a LOD of 1.65 nM and a linear detection range of 0-10 μM. Copyright © 2016 Elsevier B.V. All rights reserved.

Thin layer chromatography-densitometric determination of some non-sedating antihistamines in combination with pseudoephedrine or acetaminophen in synthetic mixtures and in pharmaceutical formulations.

PubMed

El-Kommos, Michael E; El-Gizawy, Samia M; Atia, Noha N; Hosny, Noha M

2014-03-01

The combination of certain non-sedating antihistamines (NSA) such as fexofenadine (FXD), ketotifen (KET) and loratadine (LOR) with pseudoephedrine (PSE) or acetaminophen (ACE) is widely used in the treatment of allergic rhinitis, conjunctivitis and chronic urticaria. A rapid, simple, selective and precise densitometric method was developed and validated for simultaneous estimation of six synthetic binary mixtures and their pharmaceutical dosage forms. The method employed thin layer chromatography aluminum plates precoated with silica gel G 60 F254 as the stationary phase. The mobile phases chosen for development gave compact bands for the mixtures FXD-PSE (I), KET-PSE (II), LOR-PSE (III), FXD-ACE (IV), KET-ACE (V) and LOR-ACE (VI) [Retardation factor (Rf ) values were (0.20, 0.32), (0.69, 0.34), (0.79, 0.13), (0.36, 0.70), (0.51, 0.30) and (0.76, 0.26), respectively]. Spectrodensitometric scanning integration was performed at 217, 218, 218, 233, 272 and 251 nm for the mixtures I-VI, respectively. The linear regression data for the calibration plots showed an excellent linear relationship. The method was validated for precision, accuracy, robustness and recovery. Limits of detection and quantitation were calculated. Statistical analysis proved that the method is reproducible and selective for the simultaneous estimation of these binary mixtures. Copyright © 2013 John Wiley & Sons, Ltd.

Base-Controlled Completely Selective Linear or Branched Rhodium(I)-Catalyzed C-H ortho-Alkylation of Azines without Preactivation.

PubMed

Tran, Gaël; Hesp, Kevin D; Mascitti, Vincent; Ellman, Jonathan A

2017-05-15

A [Rh I ]/bisphosphine/base catalytic system for the ortho-selective C-H alkylation of azines by acrylates and acrylamides is reported. This catalytic system features an unprecedented complete linear or branched selectivity that is solely dependent on the catalytic base that is used. Complete branched selectivity is even achieved for ethyl methacrylate, which enables the introduction of a quaternary carbon center. Excellent functional group compatibility is demonstrated for both linear and branched alkylations. The operational simplicity and broad scope of this transformation allow for rapid access to functionalized azines of direct pharmaceutical and agrochemical relevance. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Linearity versus Nonlinearity of Offspring-Parent Regression: An Experimental Study of Drosophila Melanogaster

PubMed Central

Gimelfarb, A.; Willis, J. H.

1994-01-01

An experiment was conducted to investigate the offspring-parent regression for three quantitative traits (weight, abdominal bristles and wing length) in Drosophila melanogaster. Linear and polynomial models were fitted for the regressions of a character in offspring on both parents. It is demonstrated that responses by the characters to selection predicted by the nonlinear regressions may differ substantially from those predicted by the linear regressions. This is true even, and especially, if selection is weak. The realized heritability for a character under selection is shown to be determined not only by the offspring-parent regression but also by the distribution of the character and by the form and strength of selection. PMID:7828818

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification

PubMed Central

Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC2), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible. PMID:29666661

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

PubMed

Xu, Jiucheng; Mu, Huiyu; Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC 2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.

Wide-angle full-vector beam propagation method based on an alternating direction implicit preconditioner

NASA Astrophysics Data System (ADS)

Chui, Siu Lit; Lu, Ya Yan

2004-03-01

Wide-angle full-vector beam propagation methods (BPMs) for three-dimensional wave-guiding structures can be derived on the basis of rational approximants of a square root operator or its exponential (i.e., the one-way propagator). While the less accurate BPM based on the slowly varying envelope approximation can be efficiently solved by the alternating direction implicit (ADI) method, the wide-angle variants involve linear systems that are more difficult to handle. We present an efficient solver for these linear systems that is based on a Krylov subspace method with an ADI preconditioner. The resulting wide-angle full-vector BPM is used to simulate the propagation of wave fields in a Y branch and a taper.

Wide-angle full-vector beam propagation method based on an alternating direction implicit preconditioner.

PubMed

Chui, Siu Lit; Lu, Ya Yan

2004-03-01

Wide-angle full-vector beam propagation methods (BPMs) for three-dimensional wave-guiding structures can be derived on the basis of rational approximants of a square root operator or its exponential (i.e., the one-way propagator). While the less accurate BPM based on the slowly varying envelope approximation can be efficiently solved by the alternating direction implicit (ADI) method, the wide-angle variants involve linear systems that are more difficult to handle. We present an efficient solver for these linear systems that is based on a Krylov subspace method with an ADI preconditioner. The resulting wide-angle full-vector BPM is used to simulate the propagation of wave fields in a Y branch and a taper.

An Evidence-Based Systematic Review of Amplitude Compression in Hearing Aids for School-Age Children With Hearing Loss

PubMed Central

McCreery, Ryan W.; Venediktov, Rebecca A.; Coleman, Jaumeiko J.; Leech, Hillary M.

2013-01-01

Purpose Two clinical questions were developed: one addressing the comparison of linear amplification with compression limiting to linear amplification with peak clipping, and the second comparing wide dynamic range compression with linear amplification for outcomes of audibility, speech recognition, speech and language, and self- or parent report in children with hearing loss. Method Twenty-six databases were systematically searched for studies addressing a clinical question and meeting all inclusion criteria. Studies were evaluated for methodological quality, and effect sizes were reported or calculated when possible. Results The literature search resulted in the inclusion of 8 studies. All 8 studies included comparisons of wide dynamic range compression to linear amplification, and 2 of the 8 studies provided comparisons of compression limiting versus peak clipping. Conclusions Moderate evidence from the included studies demonstrated that audibility was improved and speech recognition was either maintained or improved with wide dynamic range compression as compared with linear amplification. No significant differences were observed between compression limiting and peak clipping on outcomes (i.e., speech recognition and self-/parent report) reported across the 2 studies. Preference ratings appear to be influenced by participant characteristics and environmental factors. Further research is needed before conclusions can confidently be drawn. PMID:22858616

Combining linear polarization spectroscopy and the Representative Layer Theory to measure the Beer-Lambert law absorbance of highly scattering materials.

PubMed

Gobrecht, Alexia; Bendoula, Ryad; Roger, Jean-Michel; Bellon-Maurel, Véronique

2015-01-01

Visible and Near Infrared (Vis-NIR) Spectroscopy is a powerful non destructive analytical method used to analyze major compounds in bulk materials and products and requiring no sample preparation. It is widely used in routine analysis and also in-line in industries, in-vivo with biomedical applications or in-field for agricultural and environmental applications. However, highly scattering samples subvert Beer-Lambert law's linear relationship between spectral absorbance and the concentrations. Instead of spectral pre-processing, which is commonly used by Vis-NIR spectroscopists to mitigate the scattering effect, we put forward an optical method, based on Polarized Light Spectroscopy to improve the absorbance signal measurement on highly scattering samples. This method selects part of the signal which is less impacted by scattering. The resulted signal is combined in the Absorption/Remission function defined in Dahm's Representative Layer Theory to compute an absorbance signal fulfilling Beer-Lambert's law, i.e. being linearly related to concentration of the chemicals composing the sample. The underpinning theories have been experimentally evaluated on scattering samples in liquid form and in powdered form. The method produced more accurate spectra and the Pearson's coefficient assessing the linearity between the absorbance spectra and the concentration of the added dye improved from 0.94 to 0.99 for liquid samples and 0.84-0.97 for powdered samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Changes in the selection differential exerted on a marine snail during the ontogeny of a predatory shore crab.

PubMed

Pakes, D; Boulding, E G

2010-08-01

Empirical estimates of selection gradients caused by predators are common, yet no one has quantified how these estimates vary with predator ontogeny. We used logistic regression to investigate how selection on gastropod shell thickness changed with predator size. Only small and medium purple shore crabs (Hemigrapsus nudus) exerted a linear selection gradient for increased shell-thickness within a single population of the intertidal snail (Littorina subrotundata). The shape of the fitness function for shell thickness was confirmed to be linear for small and medium crabs but was humped for large male crabs, suggesting no directional selection. A second experiment using two prey species to amplify shell thickness differences established that the selection differential on adult snails decreased linearly as crab size increased. We observed differences in size distribution and sex ratios among three natural shore crab populations that may cause spatial and temporal variation in predator-mediated selection on local snail populations.

Blind I/Q imbalance and nonlinear ISI mitigation in Nyquist-SCM direct detection system with cascaded widely linear and Volterra equalizer

NASA Astrophysics Data System (ADS)

Liu, Na; Ju, Cheng

2018-02-01

Nyquist-SCM signal after fiber transmission, direct detection (DD), and analog down-conversion suffers from linear ISI, nonlinear ISI, and I/Q imbalance, simultaneously. Theoretical analysis based on widely linear (WL) and Volterra series is given to explain the relationship and interaction of these three interferences. A blind equalization algorithm, cascaded WL and Volterra equalizer, is designed to mitigate these three interferences. Furthermore, the feasibility of the proposed cascaded algorithm is experimentally demonstrated based on a 40-Gbps data rate 16-quadrature amplitude modulation (QAM) virtual single sideband (VSSB) Nyquist-SCM DD system over 100-km standard single mode fiber (SSMF) transmission. In addition, the performances of conventional strictly linear equalizer, WL equalizer, Volterra equalizer, and cascaded WL and Volterra equalizer are experimentally evaluated, respectively.

Second-order kinetic model for the sorption of cadmium onto tree fern: a comparison of linear and non-linear methods.

PubMed

Ho, Yuh-Shan

2006-01-01

A comparison was made of the linear least-squares method and a trial-and-error non-linear method of the widely used pseudo-second-order kinetic model for the sorption of cadmium onto ground-up tree fern. Four pseudo-second-order kinetic linear equations are discussed. Kinetic parameters obtained from the four kinetic linear equations using the linear method differed but they were the same when using the non-linear method. A type 1 pseudo-second-order linear kinetic model has the highest coefficient of determination. Results show that the non-linear method may be a better way to obtain the desired parameters.

Nonlinear aeroacoustic characterization of Helmholtz resonators with a local-linear neuro-fuzzy network model

NASA Astrophysics Data System (ADS)

Förner, K.; Polifke, W.

2017-10-01

The nonlinear acoustic behavior of Helmholtz resonators is characterized by a data-based reduced-order model, which is obtained by a combination of high-resolution CFD simulation and system identification. It is shown that even in the nonlinear regime, a linear model is capable of describing the reflection behavior at a particular amplitude with quantitative accuracy. This observation motivates to choose a local-linear model structure for this study, which consists of a network of parallel linear submodels. A so-called fuzzy-neuron layer distributes the input signal over the linear submodels, depending on the root mean square of the particle velocity at the resonator surface. The resulting model structure is referred to as an local-linear neuro-fuzzy network. System identification techniques are used to estimate the free parameters of this model from training data. The training data are generated by CFD simulations of the resonator, with persistent acoustic excitation over a wide range of frequencies and sound pressure levels. The estimated nonlinear, reduced-order models show good agreement with CFD and experimental data over a wide range of amplitudes for several test cases.

Effective seed-assisted synthesis of gold nanoparticles anchored nitrogen-doped graphene for electrochemical detection of glucose and dopamine.

PubMed

Thanh, Tran Duy; Balamurugan, Jayaraman; Lee, Seung Hee; Kim, Nam Hoon; Lee, Joong Hee

2016-07-15

A novel gold nanoparticle-anchored nitrogen-doped graphene (AuNP/NG) nanohybrid was synthesized through a seed-assisted growth method, as an effective electrocatalyst for glucose and dopamine detection. The AuNP/NG nanohybrids exhibited high sensitivity and selectivity toward glucose and dopamine sensing applications. The as-synthesized nanohybrids exhibited excellent catalytic activity toward glucose, with a linear response throughout the concentration range from 40μM to 16.1mM, a detection limit of 12μM, and a short response time (∼ 10s). It also exhibited an excellent response toward DA, with a wide detection range from 30nM to 48μM, a low detection limit of 10nM, and a short response time (∼ 8s). Furthermore, it also showed long-term stability and high selectivity for the target analytes. These results imply that such nanohybrids show a great potential for electrochemical biosensing application. Copyright © 2016 Elsevier B.V. All rights reserved.

Selective wave-transmitting electromagnetic absorber through composite metasurface

NASA Astrophysics Data System (ADS)

Sun, Zhiwei; Zhao, Junming; Zhu, Bo; Jiang, Tian; Feng, Yijun

2017-11-01

Selective wave-transmitting absorbers which have one or more narrow transmission bands inside a wide absorption band are often demanded in wireless communication and radome applications for reducing the coupling between different systems, improving anti-jamming capability, and reducing antennas' radar cross section. Here we propose a feasible method that utilizing composite of two metasurfaces with different polarization dependent characteristics, one works as electromagnetic polarization rotator and the other as a wideband polarization dependent electromagnetic wave absorber. The polarization rotator produces a cross polarization output in the wave-transmitting band, while preserves the polarization of the incidence outside the band. The metasurface absorber works for certain linear polarization with a much wider absorption band covering the wave-transmitting frequency. When combining these two metasurfaces properly, the whole structure behaves as a wideband absorber with a certain frequency transmission window. The proposal may be applied in radome designs to reduce the radar cross section of antenna or improving the electromagnetic compatibility in communication devices.

On equivalent parameter learning in simplified feature space based on Bayesian asymptotic analysis.

PubMed

Yamazaki, Keisuke

2012-07-01

Parametric models for sequential data, such as hidden Markov models, stochastic context-free grammars, and linear dynamical systems, are widely used in time-series analysis and structural data analysis. Computation of the likelihood function is one of primary considerations in many learning methods. Iterative calculation of the likelihood such as the model selection is still time-consuming though there are effective algorithms based on dynamic programming. The present paper studies parameter learning in a simplified feature space to reduce the computational cost. Simplifying data is a common technique seen in feature selection and dimension reduction though an oversimplified space causes adverse learning results. Therefore, we mathematically investigate a condition of the feature map to have an asymptotically equivalent convergence point of estimated parameters, referred to as the vicarious map. As a demonstration to find vicarious maps, we consider the feature space, which limits the length of data, and derive a necessary length for parameter learning in hidden Markov models. Copyright © 2012 Elsevier Ltd. All rights reserved.

Limitations of inclusive fitness.

PubMed

Allen, Benjamin; Nowak, Martin A; Wilson, Edward O

2013-12-10

Until recently, inclusive fitness has been widely accepted as a general method to explain the evolution of social behavior. Affirming and expanding earlier criticism, we demonstrate that inclusive fitness is instead a limited concept, which exists only for a small subset of evolutionary processes. Inclusive fitness assumes that personal fitness is the sum of additive components caused by individual actions. This assumption does not hold for the majority of evolutionary processes or scenarios. To sidestep this limitation, inclusive fitness theorists have proposed a method using linear regression. On the basis of this method, it is claimed that inclusive fitness theory (i) predicts the direction of allele frequency changes, (ii) reveals the reasons for these changes, (iii) is as general as natural selection, and (iv) provides a universal design principle for evolution. In this paper we evaluate these claims, and show that all of them are unfounded. If the objective is to analyze whether mutations that modify social behavior are favored or opposed by natural selection, then no aspect of inclusive fitness theory is needed.

Divergent Hd1, Ghd7, and DTH7 Alleles Control Heading Date and Yield Potential of Japonica Rice in Northeast China.

PubMed

Ye, Jing; Niu, Xiaojun; Yang, Yaolong; Wang, Shan; Xu, Qun; Yuan, Xiaoping; Yu, Hanyong; Wang, Yiping; Wang, Shu; Feng, Yue; Wei, Xinghua

2018-01-01

The heading date is a vital factor in achieving a full rice yield. Cultivars with particular flowering behaviors have been artificially selected to survive in the long-day and low-temperature conditions of Northeast China. To dissect the genetic mechanism responsible for heading date in rice populations from Northeast China, association mapping was performed to identify major controlling loci. A genome-wide association study (GWAS) identified three genetic loci, Hd1 , Ghd7 , and DTH7 , using general and mixed linear models. The three genes were sequenced to analyze natural variations and identify their functions. Loss-of-function alleles of these genes contributed to early rice heading dates in the northern regions of Northeast China, while functional alleles promoted late rice heading dates in the southern regions of Northeast China. Selecting environmentally appropriate allele combinations in new varieties is recommended during breeding. Introducing the early indica rice's genetic background into Northeast japonica rice is a reasonable strategy for improving genetic diversity.

An evaluation of alternative selection indexes for a non-linear profit trait approaching its economic optimum.

PubMed

Martin-Collado, D; Byrne, T J; Visser, B; Amer, P R

2016-12-01

This study used simulation to evaluate the performance of alternative selection index configurations in the context of a breeding programme where a trait with a non-linear economic value is approaching an economic optimum. The simulation used a simple population structure that approximately mimics selection in dual purpose sheep flocks in New Zealand (NZ). In the NZ dual purpose sheep population, number of lambs born is a genetic trait that is approaching an economic optimum, while genetically correlated growth traits have linear economic values and are not approaching any optimum. The predominant view among theoretical livestock geneticists is that the optimal approach to select for nonlinear profit traits is to use a linear selection index and to update it regularly. However, there are some nonlinear index approaches that have not been evaluated. This study assessed the efficiency of the following four alternative selection index approaches in terms of genetic progress relative to each other: (i) a linear index, (ii) a linear index updated regularly, (iii) a nonlinear (quadratic) index, and (iv) a NLF index (nonlinear index below the optimum and then flat). The NLF approach does not reward or penalize animals for additional genetic merit beyond the trait optimum. It was found to be at least comparable in efficiency to the approach of regularly updating the linear index with short (15 year) and long (30 year) time frames. The relative efficiency of this approach was slightly reduced when the current average value of the nonlinear trait was close to the optimum. Finally, practical issues of industry application of indexes are considered and some potential practical benefits of efficient deployment of a NLF index in highly heterogeneous industries (breeds, flocks and production environments) such as in the NZ dual purpose sheep population are discussed. © 2016 Blackwell Verlag GmbH.

SIMD Optimization of Linear Expressions for Programmable Graphics Hardware

PubMed Central

Bajaj, Chandrajit; Ihm, Insung; Min, Jungki; Oh, Jinsang

2009-01-01

The increased programmability of graphics hardware allows efficient graphical processing unit (GPU) implementations of a wide range of general computations on commodity PCs. An important factor in such implementations is how to fully exploit the SIMD computing capacities offered by modern graphics processors. Linear expressions in the form of ȳ = Ax̄ + b̄, where A is a matrix, and x̄, ȳ and b̄ are vectors, constitute one of the most basic operations in many scientific computations. In this paper, we propose a SIMD code optimization technique that enables efficient shader codes to be generated for evaluating linear expressions. It is shown that performance can be improved considerably by efficiently packing arithmetic operations into four-wide SIMD instructions through reordering of the operations in linear expressions. We demonstrate that the presented technique can be used effectively for programming both vertex and pixel shaders for a variety of mathematical applications, including integrating differential equations and solving a sparse linear system of equations using iterative methods. PMID:19946569

Avoidance, biomass and survival response of soil dwelling (endogeic) earthworms to OECD artificial soil: potential implications for earthworm ecotoxicology.

PubMed

Brami, C; Glover, A R; Butt, K R; Lowe, C N

2017-05-01

Soil dwelling earthworms are now adopted more widely in ecotoxicology, so it is vital to establish if standardised test parameters remain applicable. The main aim of this study was to determine the influence of OECD artificial soil on selected soil-dwelling, endogeic earthworm species. In an initial experiment, biomass change in mature Allolobophora chlorotica was recorded in Standard OECD Artificial Soil (AS) and also in Kettering Loam (KL). In a second experiment, avoidance behaviour was recorded in a linear gradient with varying proportions of AS and KL (100% AS, 75% AS + 25% KL, 50% KS + 50% KL, 25% AS + 75% KL, 100% KL) with either A. chlorotica or Octolasion cyaneum. Results showed a significant decrease in A. chlorotica biomass in AS relative to KL, and in the linear gradient, both earthworm species preferentially occupied sections containing higher proportions of KL over AS. Soil texture and specifically % composition and particle size of sand are proposed as key factors that influenced observed results. This research suggests that more suitable substrates are required for ecotoxicology tests with soil dwelling earthworms.

Simple diagnosis of HbA1c using the dual-plasmonic platform integrated with LSPR and SERS

NASA Astrophysics Data System (ADS)

Heo, Nam Su; Kwak, Cheol Hwan; Lee, Hoomin; Kim, Dongjoo; Lee, Sunmook; Kim, Gi-bum; Kwon, Soonjo; Kim, Woo Sik; Huh, Yun Suk

2017-07-01

A plasmonic active chip was designed with a transparent polymer film self-assembled with gold nanoparticles (AuNPs). In this study, we demonstrated the feasibility and sensitivity of biosensors by employing a plasmonic resonance technique. AuNPs are widely used as biosensing probes because they facilitate stable immobilization of biomolecules. Transparent polymer film facilitated measurement of changes in absorbance via transmitted light and analysis of Raman scattering via scattered light. The cysteine rich protein G and anti-HbA1c were sequentially conjugated to self-assembled AuNPs on the transparent polymer film to detect a target protein. HbA1c, which is used as an indicator for diabetes diagnosis, was selected for target protein detection. We confirmed the linearly increased absorbance values with increasing HbA1c level (3.19-14.0%) by LSPR detection. We also verified the linear increase in SERS intensity as the concentration of anti-Hb increased from 10 ng mL-1 to 1 μg mL-1 by analyzing the SERS spectra of Cy3 labeled anti-Hb added substrates.

Regression analysis using dependent Polya trees.

PubMed

Schörgendorfer, Angela; Branscum, Adam J

2013-11-30

Many commonly used models for linear regression analysis force overly simplistic shape and scale constraints on the residual structure of data. We propose a semiparametric Bayesian model for regression analysis that produces data-driven inference by using a new type of dependent Polya tree prior to model arbitrary residual distributions that are allowed to evolve across increasing levels of an ordinal covariate (e.g., time, in repeated measurement studies). By modeling residual distributions at consecutive covariate levels or time points using separate, but dependent Polya tree priors, distributional information is pooled while allowing for broad pliability to accommodate many types of changing residual distributions. We can use the proposed dependent residual structure in a wide range of regression settings, including fixed-effects and mixed-effects linear and nonlinear models for cross-sectional, prospective, and repeated measurement data. A simulation study illustrates the flexibility of our novel semiparametric regression model to accurately capture evolving residual distributions. In an application to immune development data on immunoglobulin G antibodies in children, our new model outperforms several contemporary semiparametric regression models based on a predictive model selection criterion. Copyright © 2013 John Wiley & Sons, Ltd.

A study of different modeling choices for simulating platelets within the immersed boundary method

PubMed Central

Shankar, Varun; Wright, Grady B.; Fogelson, Aaron L.; Kirby, Robert M.

2012-01-01

The Immersed Boundary (IB) method is a widely-used numerical methodology for the simulation of fluid–structure interaction problems. The IB method utilizes an Eulerian discretization for the fluid equations of motion while maintaining a Lagrangian representation of structural objects. Operators are defined for transmitting information (forces and velocities) between these two representations. Most IB simulations represent their structures with piecewise linear approximations and utilize Hookean spring models to approximate structural forces. Our specific motivation is the modeling of platelets in hemodynamic flows. In this paper, we study two alternative representations – radial basis functions (RBFs) and Fourier-based (trigonometric polynomials and spherical harmonics) representations – for the modeling of platelets in two and three dimensions within the IB framework, and compare our results with the traditional piecewise linear approximation methodology. For different representative shapes, we examine the geometric modeling errors (position and normal vectors), force computation errors, and computational cost and provide an engineering trade-off strategy for when and why one might select to employ these different representations. PMID:23585704

Can we predict uranium bioavailability based on soil parameters? Part 1: effect of soil parameters on soil solution uranium concentration.

PubMed

Vandenhove, H; Van Hees, M; Wouters, K; Wannijn, J

2007-01-01

Present study aims to quantify the influence of soil parameters on soil solution uranium concentration for (238)U spiked soils. Eighteen soils collected under pasture were selected such that they covered a wide range for those parameters hypothesised as being potentially important in determining U sorption. Maximum soil solution uranium concentrations were observed at alkaline pH, high inorganic carbon content and low cation exchange capacity, organic matter content, clay content, amorphous Fe and phosphate levels. Except for the significant correlation between the solid-liquid distribution coefficients (K(d), L kg(-1)) and the organic matter content (R(2)=0.70) and amorphous Fe content (R(2)=0.63), there was no single soil parameter significantly explaining the soil solution uranium concentration (which varied 100-fold). Above pH=6, log(K(d)) was linearly related with pH [log(K(d))=-1.18 pH+10.8, R(2)=0.65]. Multiple linear regression analysis did result in improved predictions of the soil solution uranium concentration but the model was complex.

40 CFR 1065.307 - Linearity verification.

Code of Federal Regulations, 2012 CFR

2012-07-01

... meter at different flow rates. Use a gravimetric reference measurement (such as a scale, balance, or... nitrogen. Select gas divisions that you typically use. Use a selected gas division as the measured value.... For linearity verification for gravimetric PM balances, use external calibration weights that that...

40 CFR 1065.307 - Linearity verification.

Code of Federal Regulations, 2013 CFR

2013-07-01

... meter at different flow rates. Use a gravimetric reference measurement (such as a scale, balance, or... nitrogen. Select gas divisions that you typically use. Use a selected gas division as the measured value.... For linearity verification for gravimetric PM balances, use external calibration weights that that...

Are highly morphed peptide frameworks lurking silently in microbial genomes valuable as next generation antibiotic scaffolds?

PubMed

Walsh, Christopher T

2017-07-01

Antibiotics are a therapeutic class that, once deployed, select for resistant bacterial pathogens and so shorten their useful life cycles. As a consequence new versions of antibiotics are constantly needed. Among the antibiotic natural products, morphed peptide scaffolds, converting conformationally mobile, short-lived linear peptides into compact, rigidified small molecule frameworks, act on a wide range of bacterial targets. Advances in bacterial genome mining, biosynthetic gene cluster prediction and expression, and mass spectroscopic structure analysis suggests many more peptides, modified both in side chains and peptide backbones, await discovery. Such molecules may turn up new bacterial targets and be starting points for combinatorial or semisynthetic manipulations to optimize activity and pharmacology parameters.

Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information.

PubMed

Hieke, Stefanie; Benner, Axel; Schlenl, Richard F; Schumacher, Martin; Bullinger, Lars; Binder, Harald

2016-08-30

High-throughput technology allows for genome-wide measurements at different molecular levels for the same patient, e.g. single nucleotide polymorphisms (SNPs) and gene expression. Correspondingly, it might be beneficial to also integrate complementary information from different molecular levels when building multivariable risk prediction models for a clinical endpoint, such as treatment response or survival. Unfortunately, such a high-dimensional modeling task will often be complicated by a limited overlap of molecular measurements at different levels between patients, i.e. measurements from all molecular levels are available only for a smaller proportion of patients. We propose a sequential strategy for building clinical risk prediction models that integrate genome-wide measurements from two molecular levels in a complementary way. To deal with partial overlap, we develop an imputation approach that allows us to use all available data. This approach is investigated in two acute myeloid leukemia applications combining gene expression with either SNP or DNA methylation data. After obtaining a sparse risk prediction signature e.g. from SNP data, an automatically selected set of prognostic SNPs, by componentwise likelihood-based boosting, imputation is performed for the corresponding linear predictor by a linking model that incorporates e.g. gene expression measurements. The imputed linear predictor is then used for adjustment when building a prognostic signature from the gene expression data. For evaluation, we consider stability, as quantified by inclusion frequencies across resampling data sets. Despite an extremely small overlap in the application example with gene expression and SNPs, several genes are seen to be more stably identified when taking the (imputed) linear predictor from the SNP data into account. In the application with gene expression and DNA methylation, prediction performance with respect to survival also indicates that the proposed approach might work well. We consider imputation of linear predictor values to be a feasible and sensible approach for dealing with partial overlap in complementary integrative analysis of molecular measurements at different levels. More generally, these results indicate that a complementary strategy for integrating different molecular levels can result in more stable risk prediction signatures, potentially providing a more reliable insight into the underlying biology.

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

PubMed Central

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

2015-01-01

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

Controlling retention, selectivity and magnitude of EOF by segmented monolithic columns consisting of octadecyl and naphthyl monolithic segments--applications to RP-CEC of both neutral and charged solutes.

PubMed

Karenga, Samuel; El Rassi, Ziad

2011-04-01

Monolithic capillaries made of two adjoining segments each filled with a different monolith were introduced for the control and manipulation of the electroosmotic flow (EOF), retention and selectivity in reversed phase-capillary electrochromatography (RP-CEC). These columns were called segmented monolithic columns (SMCs) where one segment was filled with a naphthyl methacrylate monolith (NMM) to provide hydrophobic and π-interactions, while the other segment was filled with an octadecyl acrylate monolith (ODM) to provide solely hydrophobic interaction. The ODM segment not only provided hydrophobic interactions but also functioned as the EOF accelerator segment. The average EOF of the SMC increased linearly with increasing the fractional length of the ODM segment. The neutral SMC provided a convenient way for tuning EOF, selectivity and retention in the absence of annoying electrostatic interactions and irreversible solute adsorption. The SMCs allowed the separation of a wide range of neutral solutes including polycyclic aromatic hydrocarbons (PAHs) that are difficult to separate using conventional alkyl-bonded stationary phases. In all cases, the k' of a given solute was a linear function of the fractional length of the ODM or NMM segment in the SMCs, thus facilitating the tailoring of a given SMC to solve a given separation problem. At some ODM fractional length, the fabricated SMC allowed the separation of charged solutes such as peptides and proteins that could not otherwise be achieved on a monolithic column made from NMM as an isotropic stationary phase due to the lower EOF exhibited by this monolith. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Interpretability of Multivariate Brain Maps in Linear Brain Decoding: Definition, and Heuristic Quantification in Multivariate Analysis of MEG Time-Locked Effects.

PubMed

Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea

2016-01-01

Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms in the future.

Interpretability of Multivariate Brain Maps in Linear Brain Decoding: Definition, and Heuristic Quantification in Multivariate Analysis of MEG Time-Locked Effects

PubMed Central

Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea

2017-01-01

Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms in the future. PMID:28167896

Supersensitive and selective detection of picric acid explosive by fluorescent Ag nanoclusters.

PubMed

Zhang, Jian Rong; Yue, Yuan Yuan; Luo, Hong Qun; Li, Nian Bing

2016-02-07

Picric acid (PA) explosive is a hazard to public safety and health, so the sensitive and selective detection of PA is very important. In the present work, polyethyleneimine stabilized Ag nanoclusters were successfully used for the sensitive and selective quantification of PA on the basis of fluorescence quenching. The quenching efficiency of Ag nanoclusters is proportional to the concentration of PA and the logarithm of PA concentration over two different concentration ranges (1.0 nM-1 μM for the former and 0.25-20 μM for the latter), thus the proposed quantitative strategy for PA provides a wide linear range of 1.0 nM-20 μM. The detection limit based on 3σ/K is 0.1 nM. The quenching mechanism of Ag nanoclusters by PA is discussed in detail. The results indicate that the selective detection of PA over other nitroaromatics including 2,4,6-trinitrotoluene (TNT), 2,4-dinitrotoluene (2,4-DNT), p-nitrotoluene (p-NT), m-dinitrobenzene (m-DNB), and nitrobenzene (NB), is due to the electron transfer and energy transfer between PA and polyethyleneimine-capped Ag nanoclusters. In addition, the experimental data obtained for the analysis of artificial samples show that the proposed PA sensor is potentially applicable in the determination of trace PA explosive in real samples.

40 CFR 1065.307 - Linearity verification.

Code of Federal Regulations, 2014 CFR

2014-07-01

... measurement (such as a scale, balance, or mass comparator) at the inlet to the fuel-measurement system. Use a... nitrogen. Select gas divisions that you typically use. Use a selected gas division as the measured value.... (9) Mass. For linearity verification for gravimetric PM balances, use external calibration weights...

Achieving a Linear Dose Rate Response in Pulse-Mode Silicon Photodiode Scintillation Detectors Over a Wide Range of Excitations

NASA Astrophysics Data System (ADS)

Carroll, Lewis

2014-02-01

We are developing a new dose calibrator for nuclear pharmacies that can measure radioactivity in a vial or syringe without handling it directly or removing it from its transport shield “pig”. The calibrator's detector comprises twin opposing scintillating crystals coupled to Si photodiodes and current-amplifying trans-resistance amplifiers. Such a scheme is inherently linear with respect to dose rate over a wide range of radiation intensities, but accuracy at low activity levels may be impaired, beyond the effects of meager photon statistics, by baseline fluctuation and drift inevitably present in high-gain, current-mode photodiode amplifiers. The work described here is motivated by our desire to enhance accuracy at low excitations while maintaining linearity at high excitations. Thus, we are also evaluating a novel “pulse-mode” analog signal processing scheme that employs a linear threshold discriminator to virtually eliminate baseline fluctuation and drift. We will show the results of a side-by-side comparison of current-mode versus pulse-mode signal processing schemes, including perturbing factors affecting linearity and accuracy at very low and very high excitations. Bench testing over a wide range of excitations is done using a Poisson random pulse generator plus an LED light source to simulate excitations up to ˜106 detected counts per second without the need to handle and store large amounts of radioactive material.

A Comparison of Linear and Systems Thinking Approaches for Program Evaluation Illustrated Using the Indiana Interdisciplinary GK-12

ERIC Educational Resources Information Center

Dyehouse, Melissa; Bennett, Deborah; Harbor, Jon; Childress, Amy; Dark, Melissa

2009-01-01

Logic models are based on linear relationships between program resources, activities, and outcomes, and have been used widely to support both program development and evaluation. While useful in describing some programs, the linear nature of the logic model makes it difficult to capture the complex relationships within larger, multifaceted…

Stationary-phase optimized selectivity liquid chromatography: development of a linear gradient prediction algorithm.

PubMed

De Beer, Maarten; Lynen, Fréderic; Chen, Kai; Ferguson, Paul; Hanna-Brown, Melissa; Sandra, Pat

2010-03-01

Stationary-phase optimized selectivity liquid chromatography (SOS-LC) is a tool in reversed-phase LC (RP-LC) to optimize the selectivity for a given separation by combining stationary phases in a multisegment column. The presently (commercially) available SOS-LC optimization procedure and algorithm are only applicable to isocratic analyses. Step gradient SOS-LC has been developed, but this is still not very elegant for the analysis of complex mixtures composed of components covering a broad hydrophobicity range. A linear gradient prediction algorithm has been developed allowing one to apply SOS-LC as a generic RP-LC optimization method. The algorithm allows operation in isocratic, stepwise, and linear gradient run modes. The features of SOS-LC in the linear gradient mode are demonstrated by means of a mixture of 13 steroids, whereby baseline separation is predicted and experimentally demonstrated.

Compressed storage of arterial pressure waveforms by selection of significant points.

PubMed

de Graaf, P M; van Goudoever, J; Wesseling, K H

1997-09-01

Continuous records of arterial blood pressure can be obtained non-invasively with Finapres, even for periods of 24 hours. Increasingly, storage of such records is done digitally, requiring large disc capacities. It is therefore necessary to find methods to store blood pressure waveforms in compressed form. The method of selection of significant points known from ECG data compression is adapted. Points are selected as significant wherever the first derivative of the pressure wave changes sign. As a second stage recursive partitioning is used to select additional points such that the difference between the selected points, linearly interpolated, and the original curve remains below a maximum. This method is tested on finger arterial pressure waveform epochs of 60 s duration taken from 32 patients with a wide range of blood pressures and heart rates. An average compression factor of 4.6 (SD 1.0) is obtained when accepting a maximum difference of 3 mmHg. The root mean squared error is 1 mmHg averaged over the group of patient waveforms. Clinically relevant parameters such as systolic, diastolic and mean pressure are reproduced with an offset error of less than 0.5 (0.3) mmHg and scatter less than 0.6 (0.1) mmHg. It is concluded that a substantial compression factor can be achieved with a simple and computationally fast algorithm and little deterioration in waveform quality and pressure level accuracy.

Will genomic selection be a practical method for plant breeding?

PubMed Central

Nakaya, Akihiro; Isobe, Sachiko N.

2012-01-01

Background Genomic selection or genome-wide selection (GS) has been highlighted as a new approach for marker-assisted selection (MAS) in recent years. GS is a form of MAS that selects favourable individuals based on genomic estimated breeding values. Previous studies have suggested the utility of GS, especially for capturing small-effect quantitative trait loci, but GS has not become a popular methodology in the field of plant breeding, possibly because there is insufficient information available on GS for practical use. Scope In this review, GS is discussed from a practical breeding viewpoint. Statistical approaches employed in GS are briefly described, before the recent progress in GS studies is surveyed. GS practices in plant breeding are then reviewed before future prospects are discussed. Conclusions Statistical concepts used in GS are discussed with genetic models and variance decomposition, heritability, breeding value and linear model. Recent progress in GS studies is reviewed with a focus on empirical studies. For the practice of GS in plant breeding, several specific points are discussed including linkage disequilibrium, feature of populations and genotyped markers and breeding scheme. Currently, GS is not perfect, but it is a potent, attractive and valuable approach for plant breeding. This method will be integrated into many practical breeding programmes in the near future with further advances and the maturing of its theory. PMID:22645117

Cannabis with high δ9-THC contents affects perception and visual selective attention acutely: an event-related potential study.

PubMed

Böcker, K B E; Gerritsen, J; Hunault, C C; Kruidenier, M; Mensinga, Tj T; Kenemans, J L

2010-07-01

Cannabis intake has been reported to affect cognitive functions such as selective attention. This study addressed the effects of exposure to cannabis with up to 69.4mg Delta(9)-tetrahydrocannabinol (THC) on Event-Related Potentials (ERPs) recorded during a visual selective attention task. Twenty-four participants smoked cannabis cigarettes with four doses of THC on four test days in a randomized, double blind, placebo-controlled, crossover study. Two hours after THC exposure the participants performed a visual selective attention task and concomitant ERPs were recorded. Accuracy decreased linearly and reaction times increased linearly with THC dose. However, performance measures and most of the ERP components related specifically to selective attention did not show significant dose effects. Only in relatively light cannabis users the Occipital Selection Negativity decreased linearly with dose. Furthermore, ERP components reflecting perceptual processing, as well as the P300 component, decreased in amplitude after THC exposure. Only the former effect showed a linear dose-response relation. The decrements in performance and ERP amplitudes induced by exposure to cannabis with high THC content resulted from a non-selective decrease in attentional or processing resources. Performance requiring attentional resources, such as vehicle control, may be compromised several hours after smoking cannabis cigarettes containing high doses of THC, as presently available in Europe and Northern America. Copyright 2010 Elsevier Inc. All rights reserved.

Sensitive electrochemical sensors for simultaneous determination of ascorbic acid, dopamine, and uric acid based on Au@Pd-reduced graphene oxide nanocomposites

NASA Astrophysics Data System (ADS)

Jiang, Jingjing; Du, Xuezhong

2014-09-01

Sensitive electrochemical sensors were fabricated with reduced graphene oxide-supported Au@Pd (Au@Pd-RGO) nanocomposites by one-step synthesis for individual and simultaneous determination of ascorbic acid (AA), dopamine (DA), and uric acid (UA) with low detection limits and wide concentration ranges. From the Au@Pd-RGO-modified electrodes, well-separated oxidation peaks and enhanced peak currents of AA, DA, and UA were observed owing to the superior conductivity of RGO and the excellent catalytic activity of Au@Pd nanoparticles. For individual detection, the linear responses of AA, DA, and UA were in the concentration ranges of 0.1-1000, 0.01-100, and 0.02-500 μM with detection limits of 0.02, 0.002, and 0.005 μM (S/N = 3), respectively. For simultaneous detection by synchronous change of the concentrations of AA, DA, and UA, the linear response ranges were 1-800, 0.1-100, and 0.1-350 μM with detection limits of 0.28, 0.024, and 0.02 μM (S/N = 3), respectively. The fabricated sensors were further applied to the detection of AA, DA, and UA in urine samples. The Au@Pd-RGO nanocomposites have promising applications in highly sensitive and selective electrochemical sensing.Sensitive electrochemical sensors were fabricated with reduced graphene oxide-supported Au@Pd (Au@Pd-RGO) nanocomposites by one-step synthesis for individual and simultaneous determination of ascorbic acid (AA), dopamine (DA), and uric acid (UA) with low detection limits and wide concentration ranges. From the Au@Pd-RGO-modified electrodes, well-separated oxidation peaks and enhanced peak currents of AA, DA, and UA were observed owing to the superior conductivity of RGO and the excellent catalytic activity of Au@Pd nanoparticles. For individual detection, the linear responses of AA, DA, and UA were in the concentration ranges of 0.1-1000, 0.01-100, and 0.02-500 μM with detection limits of 0.02, 0.002, and 0.005 μM (S/N = 3), respectively. For simultaneous detection by synchronous change of the concentrations of AA, DA, and UA, the linear response ranges were 1-800, 0.1-100, and 0.1-350 μM with detection limits of 0.28, 0.024, and 0.02 μM (S/N = 3), respectively. The fabricated sensors were further applied to the detection of AA, DA, and UA in urine samples. The Au@Pd-RGO nanocomposites have promising applications in highly sensitive and selective electrochemical sensing. Electronic supplementary information (ESI) available: pH optimization, comparison of sensor performances, interference experiments, and detection in urine samples. See DOI: 10.1039/c4nr01774a

In vitro selection of resistance in Escherichia coli and Klebsiella spp. at in vivo fluoroquinolone concentrations

PubMed Central

2010-01-01

Background Fluoroquinolones are potent antimicrobial agents used for the treatment of a wide variety of community- and nosocomial- infections. However, resistance to fluoroquinolones in Enterobacteriaceae is increasingly reported. Studies assessing the ability of fluoroquinolones to select for resistance have often used antimicrobial concentrations quite different from those actually acquired at the site of infection. The present study compared the ability to select for resistance of levofloxacin, ciprofloxacin and prulifloxacin at concentrations observed in vivo in twenty strains of Escherichia coli and Klebsiella spp. isolated from patients with respiratory and urinary infections. The frequencies of spontaneous single-step mutations at plasma peak and trough antibiotic concentrations were calculated. Multi-step selection of resistance was evaluated by performing 10 serial cultures on agar plates containing a linear gradient from trough to peak antimicrobial concentrations, followed by 10 subcultures on antibiotic-free agar. E. coli resistant strains selected after multi-step selection were characterized for DNA mutations by sequencing gyrA, gyrB, parC and parE genes. Results Frequencies of mutations for levofloxacin and ciprofloxacin were less than 10-11 at peak concentration, while for prulifloxacin they ranged from <10-11 to 10-5. The lowest number of resistant mutants after multistep selection was selected by levofloxacin followed by ciprofloxacin and prulifloxacin. Both ciprofloxacin- and prulifloxacin-resistant mutants presented mutations in gyrA and parC, while levofloxacin resistance was found associated only to mutations in gyrA. Conclusions Among the tested fluoroquinolones, levofloxacin was the most capable of limiting the occurrence of resistance. PMID:20409341

Stabilometric parameters are affected by anthropometry and foot placement.

PubMed

Chiari, Lorenzo; Rocchi, Laura; Cappello, Angelo

2002-01-01

To recognize and quantify the influence of biomechanical factors, namely anthropometry and foot placement, on the more common measures of stabilometric performance, including new-generation stochastic parameters. Fifty normal-bodied young adults were selected in order to cover a sufficiently wide range of anthropometric properties. They were allowed to choose their preferred side-by-side foot position and their quiet stance was recorded with eyes open and closed by a force platform. biomechanical factors are known to influence postural stability but their impact on stabilometric parameters has not been extensively explored yet. Principal component analysis was used for feature selection among several biomechanical factors. A collection of 55 stabilometric parameters from the literature was estimated from the center-of-pressure time series. Linear relations between stabilometric parameters and selected biomechanical factors were investigated by robust regression techniques. The feature selection process returned height, weight, maximum foot width, base-of-support area, and foot opening angle as the relevant biomechanical variables. Only eleven out of the 55 stabilometric parameters were completely immune from a linear dependence on these variables. The remaining parameters showed a moderate to high dependence that was strengthened upon eye closure. For these parameters, a normalization procedure was proposed, to remove what can well be considered, in clinical investigations, a spurious source of between-subject variability. Care should be taken when quantifying postural sway through stabilometric parameters. It is suggested as a good practice to include some anthropometric measurements in the experimental protocol, and to standardize or trace foot position. Although the role of anthropometry and foot placement has been investigated in specific studies, there are no studies in the literature that systematically explore the relationship between such BF and stabilometric parameters. This knowledge may contribute to better defining the experimental protocol and improving the functional evaluation of postural sway for clinical purposes, e.g. by removing through normalization the spurious effects of body properties and foot position on postural performance.

Sulfur and nitrogen binary doped carbon dots derived from ammonium thiocyanate for selective probing doxycycline in living cells and multicolor cell imaging.

PubMed

Xue, Mingyue; Zhang, Liangliang; Zhan, Zhihua; Zou, Mengbing; Huang, Yong; Zhao, Shulin

2016-04-01

A novel sulfur and nitrogen binary doped carbon dots (S,N-CDs) was synthesized by one-step manner through the hydrothermal treatment of citric acid (CA) and ammonium thiocyanate, and the procedures for biomedical applications, including probing doxycycline in living cells and multicolor cell imaging were developed. The obtained S,N-CDs are stable in aqueous solution, possess a very high quantum yield (QY, 74.15%) and good photostability. The fluorescence of S,N-CDs can be specifically quenched by doxycycline, providing a convenient turn-off assay of doxycycline. This assay shows a wide linear detection range from 0.08 to 60 μM with a low detection limit of 20 nM. The present method also displays a good selectivity. More importantly, the S,N-CDs have an excellent biocompatibility and low cytotoxicity, allowing the multicolor cell imaging and doxycycline detection in living cells. Consequently, the developed doxycycline methods is facile, low-cost, biocompatible, sensitive and selective, which may hold the potential applications in the fields of food safety and environmental monitoring, as well as cancer therapy and related mechanism research. Copyright © 2015 Elsevier B.V. All rights reserved.

An electrochemical dopamine sensor based on the ZnO/CuO nanohybrid structures.

PubMed

Khun, K; Ibupoto, Z H; Liu, X; Mansor, N A; Turner, A P F; Beni, V; Willander, M

2014-09-01

The selective detection of dopamine (DA) is of great importance in the modern medicine because dopamine is one of the main regulators in human behaviour. In this study, ZnO/CuO nanohybrid structures, grown on the gold coated glass substrate, have been investigated as a novel electrode material for the electrochemical detection of dopamine. Scanning electron microscopy (SEM), X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) techniques were used for the material characterization and the obtained results are in good agreement. The selective determination of dopamine was demonstrated by cyclic voltammetry (CV) and amperometric experiments. The amperometric response was linear for dopamine concentrations between 1.0 x 10(-3) and 8.0 mM with a sensitivity of 90.9 μA mM(-1) cm(-2). The proposed dopamine biosensor is very stable, selective over common interferents as glucose, uric acid and ascorbic acid, and also good reproducibility was observed for seven electrodes. Moreover, the dopamine sensor exhibited a fast response time of less than 10 s. The wide range and acceptable sensitivity of the presented dopamine sensor provide the possible application in analysing the dopamine from the real samples.

Highly selective determination of amitriptyline using Nafion-AuNPs@branched polyethyleneimine-derived carbon hollow spheres in pharmaceutical drugs and biological fluids.

PubMed

Zad, Zeinab Rezayati; Davarani, Saied Saeed Hosseiny; Taheri, Ali Reza; Bide, Yasamin

2016-12-15

In this paper, AuNPs@Polyethyleneimine-derived carbon hollow spheres were synthesized by a versatile and facile method in three steps and successfully developed and validated as Amitriptyline sensor using cyclic voltammetry (CV), chronoamperometry (CA) and differential pulse voltammetry (DPV) methods. The characterization of the electrode surface has been carried out by means of scanning electron microscopy (SEM), transmission electron microscopy (TEM), x-ray diffraction (XRD), x-ray photo-electron spectrum (XPS), electrochemical impedance spectroscopy (EIS) and chronocoulometry (CC). The obtained negatively charged modified electrode was highly selective to Amitriptyline and it was shown a wide linear range from 0.1 to 700μmolL(-1), with a lower detection limit of 0.034μmolL(-1) (n=5, S/N=3), revealing the high-sensitivity properties. The modified electrode is used to achieve the real-time quantitative detection of AMT for biological applications, and satisfactory results are obtained. Due to the advantages of the sensor, its selectivity, sensitivity and stability, it will have a bright future in the field of medical diagnosis. Copyright © 2016 Elsevier B.V. All rights reserved.

A mechatronics platform to study prosthetic hand control using EMG signals.

PubMed

Geethanjali, P

2016-09-01

In this paper, a low-cost mechatronics platform for the design and development of robotic hands as well as a surface electromyogram (EMG) pattern recognition system is proposed. This paper also explores various EMG classification techniques using a low-cost electronics system in prosthetic hand applications. The proposed platform involves the development of a four channel EMG signal acquisition system; pattern recognition of acquired EMG signals; and development of a digital controller for a robotic hand. Four-channel surface EMG signals, acquired from ten healthy subjects for six different movements of the hand, were used to analyse pattern recognition in prosthetic hand control. Various time domain features were extracted and grouped into five ensembles to compare the influence of features in feature-selective classifiers (SLR) with widely considered non-feature-selective classifiers, such as neural networks (NN), linear discriminant analysis (LDA) and support vector machines (SVM) applied with different kernels. The results divulged that the average classification accuracy of the SVM, with a linear kernel function, outperforms other classifiers with feature ensembles, Hudgin's feature set and auto regression (AR) coefficients. However, the slight improvement in classification accuracy of SVM incurs more processing time and memory space in the low-level controller. The Kruskal-Wallis (KW) test also shows that there is no significant difference in the classification performance of SLR with Hudgin's feature set to that of SVM with Hudgin's features along with AR coefficients. In addition, the KW test shows that SLR was found to be better in respect to computation time and memory space, which is vital in a low-level controller. Similar to SVM, with a linear kernel function, other non-feature selective LDA and NN classifiers also show a slight improvement in performance using twice the features but with the drawback of increased memory space requirement and time. This prototype facilitated the study of various issues of pattern recognition and identified an efficient classifier, along with a feature ensemble, in the implementation of EMG controlled prosthetic hands in a laboratory setting at low-cost. This platform may help to motivate and facilitate prosthetic hand research in developing countries.

Nonlinear Pattern Selection in Bi-Modal Interfacial Instabilities

NASA Astrophysics Data System (ADS)

Picardo, Jason; Narayanan, Ranga

2016-11-01

We study the evolution of two interacting unstable interfaces, with the aim of understanding the role of non-linearity in pattern selection. Specifically, we consider two superposed thin films on a heated surface, that are susceptible to thermocapillary and Rayleigh-Taylor instabilities. Due to the presence of two unstable interfaces, the dispersion curve (linear growth rate plotted as a function of the perturbation wavelength) exhibits two peaks. If these peaks have equal heights, then the two corresponding disturbance patterns will grow with the same linear growth rate. Therefore, any selection between the two must occur via nonlinear effects. The two-interface problem under consideration provides a variety of such bi-modal situations, in which the role of nonlinearity in pattern selection is unveiled. We use a combination of long wave asymptotics, numerical simulations and amplitude expansions to understand the subtle nonlinear interactions between the two peak modes. Our results offer a counter-example to Rayleigh's principle of pattern formation, that the fastest growing linear mode will dominate the final pattern. Far from being governed by any such general dogma, the final selected pattern varies considerably from case to case. The authors acknowledge funding from NSF (0968313) and the Fulbright-Nehru fellowship.

Differential wide temperature range CMOS interface circuit for capacitive MEMS pressure sensors.

PubMed

Wang, Yucai; Chodavarapu, Vamsy P

2015-02-12

We describe a Complementary Metal-Oxide Semiconductor (CMOS) differential interface circuit for capacitive Micro-Electro-Mechanical Systems (MEMS) pressure sensors that is functional over a wide temperature range between -55 °C and 225 °C. The circuit is implemented using IBM 0.13 μm CMOS technology with 2.5 V power supply. A constant-gm biasing technique is used to mitigate performance degradation at high temperatures. The circuit offers the flexibility to interface with MEMS sensors with a wide range of the steady-state capacitance values from 0.5 pF to 10 pF. Simulation results show that the circuitry has excellent linearity and stability over the wide temperature range. Experimental results confirm that the temperature effects on the circuitry are small, with an overall linearity error around 2%.

Differential Wide Temperature Range CMOS Interface Circuit for Capacitive MEMS Pressure Sensors

PubMed Central

Wang, Yucai; Chodavarapu, Vamsy P.

2015-01-01

We describe a Complementary Metal-Oxide Semiconductor (CMOS) differential interface circuit for capacitive Micro-Electro-Mechanical Systems (MEMS) pressure sensors that is functional over a wide temperature range between −55 °C and 225 °C. The circuit is implemented using IBM 0.13 μm CMOS technology with 2.5 V power supply. A constant-gm biasing technique is used to mitigate performance degradation at high temperatures. The circuit offers the flexibility to interface with MEMS sensors with a wide range of the steady-state capacitance values from 0.5 pF to 10 pF. Simulation results show that the circuitry has excellent linearity and stability over the wide temperature range. Experimental results confirm that the temperature effects on the circuitry are small, with an overall linearity error around 2%. PMID:25686312

Face-selective regions show invariance to linear, but not to non-linear, changes in facial images.

PubMed

Baseler, Heidi A; Young, Andrew W; Jenkins, Rob; Mike Burton, A; Andrews, Timothy J

2016-12-01

Familiar face recognition is remarkably invariant across huge image differences, yet little is understood concerning how image-invariant recognition is achieved. To investigate the neural correlates of invariance, we localized the core face-responsive regions and then compared the pattern of fMR-adaptation to different stimulus transformations in each region to behavioural data demonstrating the impact of the same transformations on familiar face recognition. In Experiment 1, we compared linear transformations of size and aspect ratio to a non-linear transformation affecting only part of the face. We found that adaptation to facial identity in face-selective regions showed invariance to linear changes, but there was no invariance to non-linear changes. In Experiment 2, we measured the sensitivity to non-linear changes that fell within the normal range of variation across face images. We found no adaptation to facial identity for any of the non-linear changes in the image, including to faces that varied in different levels of caricature. These results show a compelling difference in the sensitivity to linear compared to non-linear image changes in face-selective regions of the human brain that is only partially consistent with their effect on behavioural judgements of identity. We conclude that while regions such as the FFA may well be involved in the recognition of face identity, they are more likely to contribute to some form of normalisation that underpins subsequent recognition than to form the neural substrate of recognition per se. Copyright © 2016 Elsevier Ltd. All rights reserved.

Performance comparison of two efficient genomic selection methods (gsbay & MixP) applied in aquacultural organisms

NASA Astrophysics Data System (ADS)

Su, Hailin; Li, Hengde; Wang, Shi; Wang, Yangfan; Bao, Zhenmin

2017-02-01

Genomic selection is more and more popular in animal and plant breeding industries all around the world, as it can be applied early in life without impacting selection candidates. The objective of this study was to bring the advantages of genomic selection to scallop breeding. Two different genomic selection tools MixP and gsbay were applied on genomic evaluation of simulated data and Zhikong scallop ( Chlamys farreri) field data. The data were compared with genomic best linear unbiased prediction (GBLUP) method which has been applied widely. Our results showed that both MixP and gsbay could accurately estimate single-nucleotide polymorphism (SNP) marker effects, and thereby could be applied for the analysis of genomic estimated breeding values (GEBV). In simulated data from different scenarios, the accuracy of GEBV acquired was ranged from 0.20 to 0.78 by MixP; it was ranged from 0.21 to 0.67 by gsbay; and it was ranged from 0.21 to 0.61 by GBLUP. Estimations made by MixP and gsbay were expected to be more reliable than those estimated by GBLUP. Predictions made by gsbay were more robust, while with MixP the computation is much faster, especially in dealing with large-scale data. These results suggested that both algorithms implemented by MixP and gsbay are feasible to carry out genomic selection in scallop breeding, and more genotype data will be necessary to produce genomic estimated breeding values with a higher accuracy for the industry.

Linear genetic programming application for successive-station monthly streamflow prediction

NASA Astrophysics Data System (ADS)

Danandeh Mehr, Ali; Kahya, Ercan; Yerdelen, Cahit

2014-09-01

In recent decades, artificial intelligence (AI) techniques have been pronounced as a branch of computer science to model wide range of hydrological phenomena. A number of researches have been still comparing these techniques in order to find more effective approaches in terms of accuracy and applicability. In this study, we examined the ability of linear genetic programming (LGP) technique to model successive-station monthly streamflow process, as an applied alternative for streamflow prediction. A comparative efficiency study between LGP and three different artificial neural network algorithms, namely feed forward back propagation (FFBP), generalized regression neural networks (GRNN), and radial basis function (RBF), has also been presented in this study. For this aim, firstly, we put forward six different successive-station monthly streamflow prediction scenarios subjected to training by LGP and FFBP using the field data recorded at two gauging stations on Çoruh River, Turkey. Based on Nash-Sutcliffe and root mean squared error measures, we then compared the efficiency of these techniques and selected the best prediction scenario. Eventually, GRNN and RBF algorithms were utilized to restructure the selected scenario and to compare with corresponding FFBP and LGP. Our results indicated the promising role of LGP for successive-station monthly streamflow prediction providing more accurate results than those of all the ANN algorithms. We found an explicit LGP-based expression evolved by only the basic arithmetic functions as the best prediction model for the river, which uses the records of the both target and upstream stations.

Pd nanoparticle assemblies--as the substitute of HRP, in their biosensing applications for H2O2 and glucose.

PubMed

Han, Min; Liu, Suli; Bao, Jianchun; Dai, Zhihui

2012-01-15

The spherical porous Pd nanoparticle assemblies (NPAs) have been successfully synthesized by starch-assisted chemical reduction of Pd(II) species at room temperature. Such Pd NPAs are not simply used to enlarge the surface area and to promote the electron transfer. They also catalyze the reduction of H(2)O(2) which are regarded as horseradish peroxidase (HRP) substitutes in electron transfer process. By using them as electrocatalysts, as low as 6.8×10(-7) M H(2)O(2) can be detected with a linear range from 1.0×10(-6) to 8.2×10(-4) M. Moreover, through co-immobilization of such Pd NPAs and glucose oxidase (GOx), a sensitive and selective glucose biosensor is developed. The detection principle lies on measuring the increase of cathodic current by co-reduction of dissolved oxygen and the in situ generated H(2)O(2) during the enzymatic reaction. Under optimal conditions, the detection limit is down to 6.1×10(-6) M with a very wide linear range from 4.0×10(-5) to 2.2×10(-2) M. The proposed biosensor shows a fast response, good stability, high selectivity and reproducibility of serum glucose level. It provides a promising strategy to construct fast, sensitive, stable and anti-interferential amperometric biosensors for early diagnosis and prevention of diabetes. Copyright © 2011 Elsevier B.V. All rights reserved.

An ultrasensitive electrochemiluminescence sensor based on reduced graphene oxide-copper sulfide composite coupled with capillary electrophoresis for determination of amlodipine besylate in mice plasma.

PubMed

Wei, Yanfen; Wang, Hao; Sun, Shuangjiao; Tang, Lifu; Cao, Yupin; Deng, Biyang

2016-12-15

A new electrochemiluminescence (ECL) sensor based on reduced graphene oxide-copper sulfide (rGO-CuS) composite coupled with capillary electrophoresis (CE) was constructed for the ultrasensitive detection of amlodipine besylate (AML) for the first time. In this work, rGO-CuS composite was synthesized by one-pot hydrothermal method and used for electrode modification. The electrochemical and ECL behaviors of the sensor were investigated. More than 5-fold enhance in ECL intensity was observed after modified with rGO-CuS composite. The results can be ascribed to the presence of rGO-CuS composite on the electrode surface that facilitates the electron transfer rate between the electroactive center of Ru(bpy)3(2+) and the electrode. The ECL sensor was coupled with CE to improve the selectivity and the CE-ECL parameters that affect separation and detection were optimized. Under the optimum conditions, the linear ranges for AML was 0.008-5.0μg/mL with a detection limit of 2.8ng/mL (S/N=3). The method displayed the advantages of high sensitivity, good selectivity, wide linear range, low detection limit and fine reproducibility, and was used to analyze AML in mice plasma with a satisfactory result, which holds a great potential in the field of pharmaceutical analysis. Copyright © 2016 Elsevier B.V. All rights reserved.

Low acclimation capacity of narrow-ranging thermal specialists exposes susceptibility to global climate change.

PubMed

Markle, Tricia M; Kozak, Kenneth H

2018-05-01

Thermal acclimation is hypothesized to offer a selective advantage in seasonal habitats and may underlie disparities in geographic range size among closely-related species with similar ecologies. Understanding this relationship is also critical for identifying species that are more sensitive to warming climates. Here, we study North American plethodontid salamanders to investigate whether acclimation ability is associated with species' latitudinal extents and the thermal range of the environments they inhabit. We quantified variation in thermal physiology by measuring standard metabolic rate (SMR) at different test and acclimation temperatures for 16 species of salamanders with varying latitudinal extents. A phylogenetically-controlled Markov chain Monte Carlo generalized linear mixed model (MCMCglmm) was then employed to determine whether there are differences in SMR between wide- and narrow-ranging species at different acclimation temperatures. In addition, we tested for a relationship between the acclimation ability of species and the environmental temperature ranges they inhabit. Further, we investigated if there is a trade-off between critical thermal maximum (CTMax) and thermal acclimation ability. MCMCglmm results show a significant difference in acclimation ability between wide and narrow-ranging temperate salamanders. Salamanders with wide latitudinal distributions maintain or slightly increase SMR when subjected to higher test and acclimation temperatures, whereas several narrow-ranging species show significant metabolic depression. We also found significant, positive relationships between acclimation ability and environmental thermal range, and between acclimation ability and CTMax. Wide-ranging salamander species exhibit a greater capacity for thermal acclimation than narrow-ranging species, suggesting that selection for acclimation ability may have been a key factor enabling geographic expansion into areas with greater thermal variability. Further, given that narrow-ranging salamanders are found to have both poor acclimation ability and lower tolerance to warm temperatures, they are likely to be more susceptible to environmental warming associated with anthropogenic climate change.

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

Jing, Yaqi; Meng, Qinghao, E-mail: qh-meng@tju.edu.cn; Qi, Peifeng

An electronic nose (e-nose) was designed to classify Chinese liquors of the same aroma style. A new method of feature reduction which combined feature selection with feature extraction was proposed. Feature selection method used 8 feature-selection algorithms based on information theory and reduced the dimension of the feature space to 41. Kernel entropy component analysis was introduced into the e-nose system as a feature extraction method and the dimension of feature space was reduced to 12. Classification of Chinese liquors was performed by using back propagation artificial neural network (BP-ANN), linear discrimination analysis (LDA), and a multi-linear classifier. The classificationmore » rate of the multi-linear classifier was 97.22%, which was higher than LDA and BP-ANN. Finally the classification of Chinese liquors according to their raw materials and geographical origins was performed using the proposed multi-linear classifier and classification rate was 98.75% and 100%, respectively.« less

Fluorescence Imaging of Two-Photon Linear Dichroism: Cholesterol Depletion Disrupts Molecular Orientation in Cell Membranes

PubMed Central

Benninger, Richard K. P.; Önfelt, Björn; Neil, Mark A. A.; Davis, Daniel M.; French, Paul M. W.

2005-01-01

The plasma membrane of cells is an ordered environment, giving rise to anisotropic orientation and restricted motion of molecules and proteins residing in the membrane. At the same time as being an organized matrix of defined structure, the cell membrane is heterogeneous and dynamic. Here we present a method where we use fluorescence imaging of linear dichroism to measure the orientation of molecules relative to the cell membrane. By detecting linear dichroism as well as fluorescence anisotropy, the orientation parameters are separated from dynamic properties such as rotational diffusion and homo energy transfer (energy migration). The sensitivity of the technique is enhanced by using two-photon excitation for higher photo-selection compared to single photon excitation. We show here that we can accurately image lipid organization in whole cell membranes and in delicate structures such as membrane nanotubes connecting two cells. The speed of our wide-field imaging system makes it possible to image changes in orientation and anisotropy occurring on a subsecond timescale. This is demonstrated by time-lapse studies showing that cholesterol depletion rapidly disrupts the orientation of a fluorophore located within the hydrophobic region of the cell membrane but not of a surface bound probe. This is consistent with cholesterol having an important role in stabilizing and ordering the lipid tails within the plasma membrane. PMID:15520272

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

Oliva, R.; Ibanez, J.; Cusco, R.

We use Raman scattering to investigate the composition behavior of the E{sub 2h} and A{sub 1}(LO) phonons of In{sub x}Ga{sub 1-x}N and to evaluate the role of lateral compositional fluctuations and in-depth strain/composition gradients on the frequency of the A{sub 1}(LO) bands. For this purpose, we have performed visible and ultraviolet Raman measurements on a set of high-quality epilayers grown by molecular beam epitaxy with In contents over a wide composition range (0.25 < x < 0.75). While the as-measured A{sub 1}(LO) frequency values strongly deviate from the linear dispersion predicted by the modified random-element isodisplacement (MREI) model, we showmore » that the strain-corrected A{sub 1}(LO) frequencies are qualitatively in good agreement with the expected linear dependence. In contrast, we find that the strain-corrected E{sub 2h} frequencies exhibit a bowing in relation to the linear behavior predicted by the MREI model. Such bowing should be taken into account to evaluate the composition or the strain state of InGaN material from the E{sub 2h} peak frequencies. We show that in-depth strain/composition gradients and selective resonance excitation effects have a strong impact on the frequency of the A{sub 1}(LO) mode, making very difficult the use of this mode to evaluate the strain state or the composition of InGaN material.« less

RESONANT AMPLIFICATION OF TURBULENCE BY THE BLAST WAVES

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

Zankovich, A. M.; Kovalenko, I. G., E-mail: ilya.g.kovalenko@gmail.com

2015-02-10

We discuss the idea of whether spherical blast waves can amplify by a nonlocal resonant hydrodynamic mechanism inhomogeneities formed by turbulence or phase segregation in the interstellar medium. We consider the problem of a blast-wave-turbulence interaction in the Linear Interaction Approximation. Mathematically, this is an eigenvalue problem for finding the structure and amplitude of eigenfunctions describing the response of the shock-wave flow to forced oscillations by external perturbations in the ambient interstellar medium. Linear analysis shows that the blast wave can amplify density and vorticity perturbations for a wide range of length scales with amplification coefficients of up to 20,more » with increasing amplification the larger the length. There also exist resonant harmonics for which the gain becomes formally infinite in the linear approximation. Their orbital wavenumbers are within the range of macro- (l ∼ 1), meso- (l ∼ 20), and microscopic (l > 200) scales. Since the resonance width is narrow (typically, Δl < 1), resonance should select and amplify discrete isolated harmonics. We speculate on a possible explanation of an observed regular filamentary structure of regularly shaped round supernova remnants such as SNR 1572, 1006, or 0509-67.5. Resonant mesoscales found (l ≈ 18) are surprisingly close to the observed scales (l ≈ 15) of ripples in the shell's surface of SNR 0509-67.5.« less

Calibration test of the temperature and strain sensitivity coefficient in regional reference grating method

NASA Astrophysics Data System (ADS)

Wu, Jing; Huang, Junbing; Wu, Hanping; Gu, Hongcan; Tang, Bo

2014-12-01

In order to verify the validity of the regional reference grating method in solve the strain/temperature cross sensitive problem in the actual ship structural health monitoring system, and to meet the requirements of engineering, for the sensitivity coefficients of regional reference grating method, national standard measurement equipment is used to calibrate the temperature sensitivity coefficient of selected FBG temperature sensor and strain sensitivity coefficient of FBG strain sensor in this modal. And the thermal expansion sensitivity coefficient of the steel for ships is calibrated with water bath method. The calibration results show that the temperature sensitivity coefficient of FBG temperature sensor is 28.16pm/°C within -10~30°C, and its linearity is greater than 0.999, the strain sensitivity coefficient of FBG strain sensor is 1.32pm/μɛ within -2900~2900μɛ whose linearity is almost to 1, the thermal expansion sensitivity coefficient of the steel for ships is 23.438pm/°C within 30~90°C, and its linearity is greater than 0.998. Finally, the calibration parameters are used in the actual ship structure health monitoring system for temperature compensation. The results show that the effect of temperature compensation is good, and the calibration parameters meet the engineering requirements, which provide an important reference for fiber Bragg grating sensor is widely used in engineering.

Automated mapping of impervious surfaces in urban and suburban areas: Linear spectral unmixing of high spatial resolution imagery

NASA Astrophysics Data System (ADS)

Yang, Jian; He, Yuhong

2017-02-01

Quantifying impervious surfaces in urban and suburban areas is a key step toward a sustainable urban planning and management strategy. With the availability of fine-scale remote sensing imagery, automated mapping of impervious surfaces has attracted growing attention. However, the vast majority of existing studies have selected pixel-based and object-based methods for impervious surface mapping, with few adopting sub-pixel analysis of high spatial resolution imagery. This research makes use of a vegetation-bright impervious-dark impervious linear spectral mixture model to characterize urban and suburban surface components. A WorldView-3 image acquired on May 9th, 2015 is analyzed for its potential in automated unmixing of meaningful surface materials for two urban subsets and one suburban subset in Toronto, ON, Canada. Given the wide distribution of shadows in urban areas, the linear spectral unmixing is implemented in non-shadowed and shadowed areas separately for the two urban subsets. The results indicate that the accuracy of impervious surface mapping in suburban areas reaches up to 86.99%, much higher than the accuracies in urban areas (80.03% and 79.67%). Despite its merits in mapping accuracy and automation, the application of our proposed vegetation-bright impervious-dark impervious model to map impervious surfaces is limited due to the absence of soil component. To further extend the operational transferability of our proposed method, especially for the areas where plenty of bare soils exist during urbanization or reclamation, it is still of great necessity to mask out bare soils by automated classification prior to the implementation of linear spectral unmixing.

Follow the line: Mysterious bright streaks on Dione and Rhea

NASA Astrophysics Data System (ADS)

Martin, E. S.; Patthoff, D. A.

2017-12-01

Our recent mapping of the wispy terrains of Saturn's moons Dione and Rhea has revealed unique linear features that are generally long (10s-100s km), narrow (1-10 km), brighter than the surrounding terrains, and their detection may be sensitive to lighting geometries. We refer to these features as `linear virgae.' Wherever linear virgae are observed, they appear to crosscut all other structures, suggesting that they are the youngest features on these satellites. Despite their young age and wide distribution, linear virgae on Rhea and Dione have largely been overlooked in the literature. Linear virgae on Dione have previously been identified in Voyager and Cassini Data, but their formation remains an open question. If linear virgae are found to be endogenic, it would suggest that the surfaces of Dione and Rhea have been active recently. Alternatively, if linear virgae are exogenic it would suggest that the surfaces have been modified by a possibly common mechanism. Further work would be necessary to determine both a source of material and the dynamical environment that could produce these features. Here we present detailed morphometric measurements to further constrain whether linear virgae on Rhea and Dione share common origins. We complete an in-depth assessment of the lighting geometries where these features are visible. If linear virgae in the Saturnian system show common morphologies and distributions, a new, recently active, possibly system-wide mechanism may be revealed, thereby improving our understanding of the recent dynamical environment around Saturn.

Selective removal of polyethylene or polypropylene from their blends based on difference in their adsorption behaviour.

PubMed

Macko, Tibor; Pasch, Harald; Brüll, Robert

2006-05-19

The adsorption of polyethylene and polypropylene on zeolites depends on the nature of zeolite, the solvent as well as the molar mass of the polymer sample. For example, linear polyethylene is strongly retained on zeolite SH-300 from decalin, while isotactic, syndiotactic or atactic polypropylene is fully eluted in this system. On the other hand, polypropylene is retained on zeolite CBV-780 from diphenylether, while linear polyethylene is eluted. These differences in the elution behaviour have been utilised for selective removal of either linear polyethylene or polypropylene from blends of both polymers. The desorption of the retained polymer is difficult, or at times impossible. However, the selected adsorption systems have complimentary character, i.e. either one or second component is eluted or fully retained. Thus these sorbent/solvent systems, identified herein, are the first isocratic chromatographic systems, which enable selectively to remove polyethylene or polypropylene from their mixture. Moreover, decalin/SH-300 enables the removal of both linear and branched polyethylene from mixtures with random ethylene/propylene copolymers (polyethylene fully retained, ethylene/propylene copolymers eluted).

Genome-Wide Association Mapping for Resistance to Leaf and Stripe Rust in Winter-Habit Hexaploid Wheat Landraces

PubMed Central

Kertho, Albert; Mamidi, Sujan; Bonman, J. Michael; McClean, Phillip E.; Acevedo, Maricelis

2015-01-01

Leaf rust, caused by Puccinia triticina (Pt), and stripe rust, caused by P. striiformis f. sp. tritici (Pst), are destructive foliar diseases of wheat worldwide. Breeding for disease resistance is the preferred strategy of managing both diseases. The continued emergence of new races of Pt and Pst requires a constant search for new sources of resistance. Here we report a genome-wide association analysis of 567 winter wheat (Triticum aestivum) landrace accessions using the Infinium iSelect 9K wheat SNP array to identify loci associated with seedling resistance to five races of Pt (MDCL, MFPS, THBL, TDBG, and TBDJ) and one race of Pst (PSTv-37) frequently found in the Northern Great Plains of the United States. Mixed linear models identified 65 and eight significant markers associated with leaf rust and stripe rust, respectively. Further, we identified 31 and three QTL associated with resistance to Pt and Pst, respectively. Eleven QTL, identified on chromosomes 3A, 4A, 5A, and 6D, are previously unknown for leaf rust resistance in T. aestivum. PMID:26076040

Experimental and statistical study on fracture boundary of non-irradiated Zircaloy-4 cladding tube under LOCA conditions

NASA Astrophysics Data System (ADS)

Narukawa, Takafumi; Yamaguchi, Akira; Jang, Sunghyon; Amaya, Masaki

2018-02-01

For estimating fracture probability of fuel cladding tube under loss-of-coolant accident conditions of light-water-reactors, laboratory-scale integral thermal shock tests were conducted on non-irradiated Zircaloy-4 cladding tube specimens. Then, the obtained binary data with respect to fracture or non-fracture of the cladding tube specimen were analyzed statistically. A method to obtain the fracture probability curve as a function of equivalent cladding reacted (ECR) was proposed using Bayesian inference for generalized linear models: probit, logit, and log-probit models. Then, model selection was performed in terms of physical characteristics and information criteria, a widely applicable information criterion and a widely applicable Bayesian information criterion. As a result, it was clarified that the log-probit model was the best among the three models to estimate the fracture probability in terms of the degree of prediction accuracy for both next data to be obtained and the true model. Using the log-probit model, it was shown that 20% ECR corresponded to a 5% probability level with a 95% confidence of fracture of the cladding tube specimens.

The influence of Reynolds numbers on resistance properties of jet pumps

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

Geng, Q.; Graduate University of Chinese Academy of Sciences, Beijing 100049; Zhou, G.

2014-01-29

Jet pumps are widely used in thermoacoustic Stirling heat engines and pulse tube cryocoolers to eliminate the effect of Gedeon streaming. The resistance properties of jet pumps are principally influenced by their structures and flow regimes which are always characterized by Reynolds numbers. In this paper, the jet pump of which cross section contracts abruptly is selected as our research subject. Based on linear thermoacoustic theory, a CFD model is built and the oscillating flow of the working gas is simulated and analyzed with different Reynolds numbers in the jet pump. According to the calculations, the influence of different structuresmore » and Reynolds numbers on the resistance properties of the jet pump are analyzed and presented. The results show that Reynolds numbers have a great influence on the resistance properties of jet pumps and some empirical formulas which are widely used are unsuitable for oscillating flow with small Reynolds numbers. This paper provides a more comprehensive understanding on resistance properties of jet pumps with oscillating flow and is significant for the design of jet pumps in practical thermoacoustic engines and refrigerators.« less

Multi-Objective Online Initialization of Spacecraft Formations

NASA Technical Reports Server (NTRS)

Jeffrey, Matthew; Breger, Louis; How, Jonathan P.

2007-01-01

This paper extends a previously developed method for finding spacecraft initial conditions (ICs) that minimize the drift resulting from J2 disturbances while also minimizing the fuel required to attain those ICs. It generalizes the single spacecraft optimization to a formation-wide optimization valid for an arbitrary number of vehicles. Additionally, the desired locations of the spacecraft, separate from the starting location, can be specified, either with respect to a reference orbit, or relative to the other spacecraft in the formation. The three objectives (minimize drift, minimize fuel, and maintain a geometric template) are expressed as competing costs in a linear optimization, and are traded against one another through the use of scalar weights. By carefully selecting these weights and re-initializing the formation at regular intervals, a closed-loop, formation-wide control system is created. This control system can be used to reconfigure the formations on the fly, and creates fuel-efficient plans by placing the spacecraft in semi-invariant orbits. The overall approach is demonstrated through nonlinear simulations for two formations a GEO orbit, and an elliptical orbit.

The influence of Reynolds numbers on resistance properties of jet pumps

NASA Astrophysics Data System (ADS)

Geng, Q.; Zhou, G.; Li, Q.

2014-01-01

Jet pumps are widely used in thermoacoustic Stirling heat engines and pulse tube cryocoolers to eliminate the effect of Gedeon streaming. The resistance properties of jet pumps are principally influenced by their structures and flow regimes which are always characterized by Reynolds numbers. In this paper, the jet pump of which cross section contracts abruptly is selected as our research subject. Based on linear thermoacoustic theory, a CFD model is built and the oscillating flow of the working gas is simulated and analyzed with different Reynolds numbers in the jet pump. According to the calculations, the influence of different structures and Reynolds numbers on the resistance properties of the jet pump are analyzed and presented. The results show that Reynolds numbers have a great influence on the resistance properties of jet pumps and some empirical formulas which are widely used are unsuitable for oscillating flow with small Reynolds numbers. This paper provides a more comprehensive understanding on resistance properties of jet pumps with oscillating flow and is significant for the design of jet pumps in practical thermoacoustic engines and refrigerators.

EEG feature selection method based on decision tree.

PubMed

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

Genetic parameters for linear type traits and milk, fat, and protein production in holstein cows in Brazil.

PubMed

Campos, Rafael Viegas; Cobuci, Jaime Araujo; Kern, Elisandra Lurdes; Costa, Cláudio Napolis; McManus, Concepta Margaret

2015-04-01

The objective of this study was to estimate genetic and phenotypic parameters for linear type traits, as well as milk yield (MY), fat yield (FY) and protein yield (PY) in 18,831 Holstein cows reared in 495 herds in Brazil. Restricted maximum likelihood with a bivariate model was used for estimation genetic parameters, including fixed effects of herd-year of classification, period of classification, classifier and stage of lactation for linear type traits and herd-year of calving, season of calving and lactation order effects for production traits. The age of cow at calving was fitted as a covariate (with linear and quadratic terms), common to both models. Heritability estimates varied from 0.09 to 0.38 for linear type traits and from 0.17 to 0.24 for production traits, indicating sufficient genetic variability to achieve genetic gain through selection. In general, estimates of genetic correlations between type and production traits were low, except for udder texture and angularity that showed positive genetic correlations (>0.29) with MY, FY, and PY. Udder depth had the highest negative genetic correlation (-0.30) with production traits. Selection for final score, commonly used by farmers as a practical selection tool to improve type traits, does not lead to significant improvements in production traits, thus the use of selection indices that consider both sets of traits (production and type) seems to be the most adequate to carry out genetic selection of animals in the Brazilian herd.

Genetic Parameters for Linear Type Traits and Milk, Fat, and Protein Production in Holstein Cows in Brazil

PubMed Central

Campos, Rafael Viegas; Cobuci, Jaime Araujo; Kern, Elisandra Lurdes; Costa, Cláudio Napolis; McManus, Concepta Margaret

2015-01-01

The objective of this study was to estimate genetic and phenotypic parameters for linear type traits, as well as milk yield (MY), fat yield (FY) and protein yield (PY) in 18,831 Holstein cows reared in 495 herds in Brazil. Restricted maximum likelihood with a bivariate model was used for estimation genetic parameters, including fixed effects of herd-year of classification, period of classification, classifier and stage of lactation for linear type traits and herd-year of calving, season of calving and lactation order effects for production traits. The age of cow at calving was fitted as a covariate (with linear and quadratic terms), common to both models. Heritability estimates varied from 0.09 to 0.38 for linear type traits and from 0.17 to 0.24 for production traits, indicating sufficient genetic variability to achieve genetic gain through selection. In general, estimates of genetic correlations between type and production traits were low, except for udder texture and angularity that showed positive genetic correlations (>0.29) with MY, FY, and PY. Udder depth had the highest negative genetic correlation (−0.30) with production traits. Selection for final score, commonly used by farmers as a practical selection tool to improve type traits, does not lead to significant improvements in production traits, thus the use of selection indices that consider both sets of traits (production and type) seems to be the most adequate to carry out genetic selection of animals in the Brazilian herd. PMID:25656190

Evidence of directional and stabilizing selection in contemporary humans.

PubMed

Sanjak, Jaleal S; Sidorenko, Julia; Robinson, Matthew R; Thornton, Kevin R; Visscher, Peter M

2018-01-02

Modern molecular genetic datasets, primarily collected to study the biology of human health and disease, can be used to directly measure the action of natural selection and reveal important features of contemporary human evolution. Here we leverage the UK Biobank data to test for the presence of linear and nonlinear natural selection in a contemporary population of the United Kingdom. We obtain phenotypic and genetic evidence consistent with the action of linear/directional selection. Phenotypic evidence suggests that stabilizing selection, which acts to reduce variance in the population without necessarily modifying the population mean, is widespread and relatively weak in comparison with estimates from other species.

Rank-based estimation in the {ell}1-regularized partly linear model for censored outcomes with application to integrated analyses of clinical predictors and gene expression data.

PubMed

Johnson, Brent A

2009-10-01

We consider estimation and variable selection in the partial linear model for censored data. The partial linear model for censored data is a direct extension of the accelerated failure time model, the latter of which is a very important alternative model to the proportional hazards model. We extend rank-based lasso-type estimators to a model that may contain nonlinear effects. Variable selection in such partial linear model has direct application to high-dimensional survival analyses that attempt to adjust for clinical predictors. In the microarray setting, previous methods can adjust for other clinical predictors by assuming that clinical and gene expression data enter the model linearly in the same fashion. Here, we select important variables after adjusting for prognostic clinical variables but the clinical effects are assumed nonlinear. Our estimator is based on stratification and can be extended naturally to account for multiple nonlinear effects. We illustrate the utility of our method through simulation studies and application to the Wisconsin prognostic breast cancer data set.

Evolution Stings: The Origin and Diversification of Scorpion Toxin Peptide Scaffolds

PubMed Central

Sunagar, Kartik; Undheim, Eivind A. B.; Chan, Angelo H. C.; Koludarov, Ivan; Muñoz-Gómez, Sergio A.; Antunes, Agostinho; Fry, Bryan G.

2013-01-01

The episodic nature of natural selection and the accumulation of extreme sequence divergence in venom-encoding genes over long periods of evolutionary time can obscure the signature of positive Darwinian selection. Recognition of the true biocomplexity is further hampered by the limited taxon selection, with easy to obtain or medically important species typically being the subject of intense venom research, relative to the actual taxonomical diversity in nature. This holds true for scorpions, which are one of the most ancient terrestrial venomous animal lineages. The family Buthidae that includes all the medically significant species has been intensely investigated around the globe, while almost completely ignoring the remaining non-buthid families. Australian scorpion lineages, for instance, have been completely neglected, with only a single scorpion species (Urodacus yaschenkoi) having its venom transcriptome sequenced. Hence, the lack of venom composition and toxin sequence information from an entire continent’s worth of scorpions has impeded our understanding of the molecular evolution of scorpion venom. The molecular origin, phylogenetic relationships and evolutionary histories of most scorpion toxin scaffolds remain enigmatic. In this study, we have sequenced venom gland transcriptomes of a wide taxonomical diversity of scorpions from Australia, including buthid and non-buthid representatives. Using state-of-art molecular evolutionary analyses, we show that a majority of CSα/β toxin scaffolds have experienced episodic influence of positive selection, while most non-CSα/β linear toxins evolve under the extreme influence of negative selection. For the first time, we have unraveled the molecular origin of the major scorpion toxin scaffolds, such as scorpion venom single von Willebrand factor C-domain peptides (SV-SVC), inhibitor cystine knot (ICK), disulphide-directed beta-hairpin (DDH), bradykinin potentiating peptides (BPP), linear non-disulphide bridged peptides and antimicrobial peptides (AMP). We have thus demonstrated that even neglected lineages of scorpions are a rich pool of novel biochemical components, which have evolved over millions of years to target specific ion channels in prey animals, and as a result, possess tremendous implications in therapeutics. PMID:24351712

Fiber-Optic Strain Sensors With Linear Characteristics

NASA Technical Reports Server (NTRS)

Egalon, Claudio O.; Rogowski, Robert S.

1993-01-01

Fiber-optic modal domain strain sensors having linear characteristics over wide range of strains proposed. Conceived in effort to improve older fiber-optic strain sensors. Linearity obtained by appropriate choice of design parameters. Pattern of light and dark areas at output end of optical fiber produced by interference between electromagnetic modes in which laser beam propagates in fiber. Photodetector monitors intensity at one point in pattern.

Functionalized linear and cyclic polyolefins

DOEpatents

Tuba, Robert; Grubbs, Robert H.

2018-02-13

This invention relates to methods and compositions for preparing linear and cyclic polyolefins. More particularly, the invention relates to methods and compositions for preparing functionalized linear and cyclic polyolefins via olefin metathesis reactions. Polymer products produced via the olefin metathesis reactions of the invention may be utilized for a wide range of materials applications. The invention has utility in the fields of polymer and materials chemistry and manufacture.

Linearization methods for optimizing the low thrust spacecraft trajectory: Theoretical aspects

NASA Astrophysics Data System (ADS)

Kazmerchuk, P. V.

2016-12-01

The theoretical aspects of the modified linearization method, which makes it possible to solve a wide class of nonlinear problems on optimizing low-thrust spacecraft trajectories (V. V. Efanov et al., 2009; V. V. Khartov et al., 2010) are examined. The main modifications of the linearization method are connected with its refinement for optimizing the main dynamic systems and design parameters of the spacecraft.

Glutathione-Capped Gold Nanoparticles-Based Photoacoustic Sensor for Label-Free Detection of Lead Ions

NASA Astrophysics Data System (ADS)

Shi, R.; Liu, X.-J.; Ying, Y.

2017-07-01

The photoacoustic signal generated by laser-induced nanobubbles (PA-LINB) proved to be a sensitive tool to monitor the aggregation of gold nanoparticles. Here, a simple and label-free photoacoustic method for the rapid detection of Pb2+ in the aqueous phase was developed. Due to the high affinity of Pb2+ ions to glutathione, the presence of Pb2+ led to the aggregation of glutathione-conjugated gold nanoparticles (GSH-GNPs). Hence, by measuring the variation of the PA-LINB signal after the aggregation of GSH-GNPs, Pb2+ can be quantified. A low detection limit for Pb2+ (42 nM) and a wide linear working range ( 42-1000 nM) were achieved. Furthermore, the proposed method showed good selectivity against other metal ions.

Possibilities of rock constitutive modelling and simulations

NASA Astrophysics Data System (ADS)

Baranowski, Paweł; Małachowski, Jerzy

2018-01-01

The paper deals with a problem of rock finite element modelling and simulation. The main intention of authors was to present possibilities of different approaches in case of rock constitutive modelling. For this purpose granite rock was selected, due to its wide mechanical properties recognition and prevalence in literature. Two significantly different constitutive material models were implemented to simulate the granite fracture in various configurations: Johnson - Holmquist ceramic model which is very often used for predicting rock and other brittle materials behavior, and a simple linear elastic model with a brittle failure which can be used for simulating glass fracturing. Four cases with different loading conditions were chosen to compare the aforementioned constitutive models: uniaxial compression test, notched three-point-bending test, copper ball impacting a block test and small scale blasting test.

A High-Linearity Low-Noise Amplifier with Variable Bandwidth for Neural Recoding Systems

NASA Astrophysics Data System (ADS)

Yoshida, Takeshi; Sueishi, Katsuya; Iwata, Atsushi; Matsushita, Kojiro; Hirata, Masayuki; Suzuki, Takafumi

2011-04-01

This paper describes a low-noise amplifier with multiple adjustable parameters for neural recording applications. An adjustable pseudo-resistor implemented by cascade metal-oxide-silicon field-effect transistors (MOSFETs) is proposed to achieve low-signal distortion and wide variable bandwidth range. The amplifier has been implemented in 0.18 µm standard complementary metal-oxide-semiconductor (CMOS) process and occupies 0.09 mm2 on chip. The amplifier achieved a selectable voltage gain of 28 and 40 dB, variable bandwidth from 0.04 to 2.6 Hz, total harmonic distortion (THD) of 0.2% with 200 mV output swing, input referred noise of 2.5 µVrms over 0.1-100 Hz and 18.7 µW power consumption at a supply voltage of 1.8 V.

Selection occurs within linear fruit and during the early stages of reproduction in Robinia pseudoacacia

PubMed Central

2014-01-01

Background Pollen donor compositions differ during the early stages of reproduction due to various selection mechanisms. In addition, ovules linearly ordered within a fruit have different probabilities of reaching maturity. Few attempts, however, have been made to directly examine the magnitude and timing of selection, as well as the mechanisms during early life stages and within fruit. Robinia pseudoacacia, which contains linear fruit and non-random ovule maturation and abortion patterns, has been used to study the viability of selection within fruit and during the early stages of reproduction. To examine changes in the pollen donor composition during the early stages of reproduction and of progeny originating from different positions within fruit, paternity analyses were performed for three early life stages (aborted seeds, mature seeds and seedlings) in the insect-pollinated tree R. pseudoacacia. Results Selection resulted in an overall decrease in the level of surviving selfed progeny at each life stage. The greatest change was observed between the aborted seed stage and mature seed stage, indicative of inbreeding depression (the reduced fitness of a given population that occurs when related individual breeding was responsible for early selection). A selective advantage was detected among paternal trees. Within fruits, the distal ends showed higher outcrossing rates than the basal ends, indicative of selection based on the order of seeds within the fruit. Conclusions Our results suggest that selection exists both within linear fruit and during the early stages of reproduction, and that this selection can affect male reproductive success during the early life stages. This indicates that tree species with mixed-mating systems may have evolved pollen selection mechanisms to increase the fitness of progeny and adjust the population genetic composition. The early selection that we detected suggests that inbreeding depression caused the high abortion rate and low seed set in R. pseudoacacia. PMID:24655746

Selection occurs within linear fruit and during the early stages of reproduction in Robinia pseudoacacia.

PubMed

Yuan, Cun-Quan; Sun, Yu-Han; Li, Yun-Fei; Zhao, Ke-Qi; Hu, Rui-Yang; Li, Yun

2014-03-21

Pollen donor compositions differ during the early stages of reproduction due to various selection mechanisms. In addition, ovules linearly ordered within a fruit have different probabilities of reaching maturity. Few attempts, however, have been made to directly examine the magnitude and timing of selection, as well as the mechanisms during early life stages and within fruit. Robinia pseudoacacia, which contains linear fruit and non-random ovule maturation and abortion patterns, has been used to study the viability of selection within fruit and during the early stages of reproduction. To examine changes in the pollen donor composition during the early stages of reproduction and of progeny originating from different positions within fruit, paternity analyses were performed for three early life stages (aborted seeds, mature seeds and seedlings) in the insect-pollinated tree R. pseudoacacia. Selection resulted in an overall decrease in the level of surviving selfed progeny at each life stage. The greatest change was observed between the aborted seed stage and mature seed stage, indicative of inbreeding depression (the reduced fitness of a given population that occurs when related individual breeding was responsible for early selection). A selective advantage was detected among paternal trees. Within fruits, the distal ends showed higher outcrossing rates than the basal ends, indicative of selection based on the order of seeds within the fruit. Our results suggest that selection exists both within linear fruit and during the early stages of reproduction, and that this selection can affect male reproductive success during the early life stages. This indicates that tree species with mixed-mating systems may have evolved pollen selection mechanisms to increase the fitness of progeny and adjust the population genetic composition. The early selection that we detected suggests that inbreeding depression caused the high abortion rate and low seed set in R. pseudoacacia.

Graphite paper-based bipolar electrode electrochemiluminescence sensing platform.

PubMed

Zhang, Xin; Ding, Shou-Nian

2017-08-15

In this work, aiming at the construction of a disposable, wireless, low-cost and sensitive system for bioassay, we report a closed bipolar electrode electrochemiluminescence (BPE-ECL) sensing platform based on graphite paper as BPE for the first time. Graphite paper is qualified as BPE due to its unique properties such as excellent electrical conductivity, uniform composition and ease of use. This simple BPE-ECL device was applied to the quantitative analysis of oxidant (H 2 O 2 ) and biomarker (CEA) respectively, according to the principle of BPE sensing-charge balance. For the H 2 O 2 analysis, Pt NPs were electrodeposited onto the cathode through a bipolar electrodeposition approach to promote the sensing performance. As a result, this BPE-ECL device exhibited a wide linear range of 0.001-15mM with a low detection limit of 0.5µM (S/N=3) for H 2 O 2 determination. For the determination of CEA, chitosan-multi-walled carbon nanotubes (CS-MWCNTs) were employed to supply a hydrophilic interface for immobilizing primary antibody (Ab 1 ); and Au@Pt nanostructures were conjugated with secondary antibody (Ab 2 ) as catalysts for H 2 O 2 reduction. Under the optimal conditions, the BPE-ECL immunodevice showed a wide linear range of 0.01-60ngmL -1 with a detection limit of 5.0pgmL -1 for CEA. Furthermore, it also displayed satisfactory selectivity, excellent stability and good reproducibility. The developed method opened a new avenue to clinical bioassay. Copyright © 2017 Elsevier B.V. All rights reserved.

Development of orientation tuning in simple cells of primary visual cortex

PubMed Central

Moore, Bartlett D.

2012-01-01

Orientation selectivity and its development are basic features of visual cortex. The original model of orientation selectivity proposes that elongated simple cell receptive fields are constructed from convergent input of an array of lateral geniculate nucleus neurons. However, orientation selectivity of simple cells in the visual cortex is generally greater than the linear contributions based on projections from spatial receptive field profiles. This implies that additional selectivity may arise from intracortical mechanisms. The hierarchical processing idea implies mainly linear connections, whereas cortical contributions are generally considered to be nonlinear. We have explored development of orientation selectivity in visual cortex with a focus on linear and nonlinear factors in a population of anesthetized 4-wk postnatal kittens and adult cats. Linear contributions are estimated from receptive field maps by which orientation tuning curves are generated and bandwidth is quantified. Nonlinear components are estimated as the magnitude of the power function relationship between responses measured from drifting sinusoidal gratings and those predicted from the spatial receptive field. Measured bandwidths for kittens are slightly larger than those in adults, whereas predicted bandwidths are substantially broader. These results suggest that relatively strong nonlinearities in early postnatal stages are substantially involved in the development of orientation tuning in visual cortex. PMID:22323631

Comparison of various error functions in predicting the optimum isotherm by linear and non-linear regression analysis for the sorption of basic red 9 by activated carbon.

PubMed

Kumar, K Vasanth; Porkodi, K; Rocha, F

2008-01-15

A comparison of linear and non-linear regression method in selecting the optimum isotherm was made to the experimental equilibrium data of basic red 9 sorption by activated carbon. The r(2) was used to select the best fit linear theoretical isotherm. In the case of non-linear regression method, six error functions namely coefficient of determination (r(2)), hybrid fractional error function (HYBRID), Marquardt's percent standard deviation (MPSD), the average relative error (ARE), sum of the errors squared (ERRSQ) and sum of the absolute errors (EABS) were used to predict the parameters involved in the two and three parameter isotherms and also to predict the optimum isotherm. Non-linear regression was found to be a better way to obtain the parameters involved in the isotherms and also the optimum isotherm. For two parameter isotherm, MPSD was found to be the best error function in minimizing the error distribution between the experimental equilibrium data and predicted isotherms. In the case of three parameter isotherm, r(2) was found to be the best error function to minimize the error distribution structure between experimental equilibrium data and theoretical isotherms. The present study showed that the size of the error function alone is not a deciding factor to choose the optimum isotherm. In addition to the size of error function, the theory behind the predicted isotherm should be verified with the help of experimental data while selecting the optimum isotherm. A coefficient of non-determination, K(2) was explained and was found to be very useful in identifying the best error function while selecting the optimum isotherm.

Comparison of Selection Procedures and Validation of Criterion Used in Selection of Significant Control Variates of a Simulation Model

DTIC Science & Technology

1990-03-01

and M.H. Knuter. Applied Linear Regression Models. Homewood IL: Richard D. Erwin Inc., 1983. Pritsker, A. Alan B. Introduction to Simulation and SLAM...Control Variates in Simulation," European Journal of Operational Research, 42: (1989). Neter, J., W. Wasserman, and M.H. Xnuter. Applied Linear Regression Models

LFSPMC: Linear feature selection program using the probability of misclassification

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.; Marion, B. P.

1975-01-01

The computational procedure and associated computer program for a linear feature selection technique are presented. The technique assumes that: a finite number, m, of classes exists; each class is described by an n-dimensional multivariate normal density function of its measurement vectors; the mean vector and covariance matrix for each density function are known (or can be estimated); and the a priori probability for each class is known. The technique produces a single linear combination of the original measurements which minimizes the one-dimensional probability of misclassification defined by the transformed densities.

Graph-based Data Modeling and Analysis for Data Fusion in Remote Sensing

NASA Astrophysics Data System (ADS)

Fan, Lei

Hyperspectral imaging provides the capability of increased sensitivity and discrimination over traditional imaging methods by combining standard digital imaging with spectroscopic methods. For each individual pixel in a hyperspectral image (HSI), a continuous spectrum is sampled as the spectral reflectance/radiance signature to facilitate identification of ground cover and surface material. The abundant spectrum knowledge allows all available information from the data to be mined. The superior qualities within hyperspectral imaging allow wide applications such as mineral exploration, agriculture monitoring, and ecological surveillance, etc. The processing of massive high-dimensional HSI datasets is a challenge since many data processing techniques have a computational complexity that grows exponentially with the dimension. Besides, a HSI dataset may contain a limited number of degrees of freedom due to the high correlations between data points and among the spectra. On the other hand, merely taking advantage of the sampled spectrum of individual HSI data point may produce inaccurate results due to the mixed nature of raw HSI data, such as mixed pixels, optical interferences and etc. Fusion strategies are widely adopted in data processing to achieve better performance, especially in the field of classification and clustering. There are mainly three types of fusion strategies, namely low-level data fusion, intermediate-level feature fusion, and high-level decision fusion. Low-level data fusion combines multi-source data that is expected to be complementary or cooperative. Intermediate-level feature fusion aims at selection and combination of features to remove redundant information. Decision level fusion exploits a set of classifiers to provide more accurate results. The fusion strategies have wide applications including HSI data processing. With the fast development of multiple remote sensing modalities, e.g. Very High Resolution (VHR) optical sensors, LiDAR, etc., fusion of multi-source data can in principal produce more detailed information than each single source. On the other hand, besides the abundant spectral information contained in HSI data, features such as texture and shape may be employed to represent data points from a spatial perspective. Furthermore, feature fusion also includes the strategy of removing redundant and noisy features in the dataset. One of the major problems in machine learning and pattern recognition is to develop appropriate representations for complex nonlinear data. In HSI processing, a particular data point is usually described as a vector with coordinates corresponding to the intensities measured in the spectral bands. This vector representation permits the application of linear and nonlinear transformations with linear algebra to find an alternative representation of the data. More generally, HSI is multi-dimensional in nature and the vector representation may lose the contextual correlations. Tensor representation provides a more sophisticated modeling technique and a higher-order generalization to linear subspace analysis. In graph theory, data points can be generalized as nodes with connectivities measured from the proximity of a local neighborhood. The graph-based framework efficiently characterizes the relationships among the data and allows for convenient mathematical manipulation in many applications, such as data clustering, feature extraction, feature selection and data alignment. In this thesis, graph-based approaches applied in the field of multi-source feature and data fusion in remote sensing area are explored. We will mainly investigate the fusion of spatial, spectral and LiDAR information with linear and multilinear algebra under graph-based framework for data clustering and classification problems.

Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines.

PubMed

Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R

2015-02-01

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.

Genomic Selection and Association Mapping in Rice (Oryza sativa): Effect of Trait Genetic Architecture, Training Population Composition, Marker Number and Statistical Model on Accuracy of Rice Genomic Selection in Elite, Tropical Rice Breeding Lines

PubMed Central

Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R.

2015-01-01

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline. PMID:25689273

SOME STATISTICAL ISSUES RELATED TO MULTIPLE LINEAR REGRESSION MODELING OF BEACH BACTERIA CONCENTRATIONS

EPA Science Inventory

As a fast and effective technique, the multiple linear regression (MLR) method has been widely used in modeling and prediction of beach bacteria concentrations. Among previous works on this subject, however, several issues were insufficiently or inconsistently addressed. Those is...

A copper ion-selective electrode with high selectivity prepared by sol-gel and coated wire techniques.

PubMed

Mazloum Ardakani, M; Salavati-Niasari, M; Khayat Kashani, M; Ghoreishi, S M

2004-03-01

A sol-gel electrode and a coated wire ion-selective poly(vinyl chloride) membrane, based on thiosemicarbazone as a neutral carrier, were successfully developed for the detection of Cu (II) in aqueous solutions. The sol-gel electrode and coated electrode exhibited linear response with Nernstian slopes of 29.2 and 28.1 mV per decade respectively, within the copper ion concentration ranges 1.0 x 10(-5) - 1.0 x 10(-1) M and 6.0 x 10(-6) - 1.0 x 10(-1) M for coated and sol-gel sensors. The coated and sol-gel electrodes show detection limits of 3.0 x 10(-6) and 6.0 x 10(-6) M respectively. The electrodes exhibited good selectivities for a number of alkali, alkaline earth, transition and heavy metal ions. The proposed electrodes have response times ranging from 10-50 s to achieve a 95% steady potential for Cu2+ concentration. The electrodes are suitable for use in aqueous solutions over a wide pH range (4-7.5). Applications of these electrodes for the determination of copper in real samples, and as an indicator electrode for potentiometric titration of Cu2+ ion using EDTA, are reported. The lifetimes of the electrodes were tested over a period of six months to investigate their stability. No significant change in the performance of the sol-gel electrode was observed over this period, but after two months the coated wire copper-selective electrode exhibited a gradual decrease in the slope. The selectivity of the sol-gel electrode was found to be better than that of the coated wire copper-selective electrode. Based on these results, a novel sol-gel copper-selective electrode is proposed for the determination of copper, and applied to real sample assays.

Elucidating spatially explicit behavioral landscapes in the Willow Flycatcher

USGS Publications Warehouse

Bakian, Amanda V.; Sullivan, Kimberly A.; Paxton, Eben H.

2012-01-01

Animal resource selection is a complex, hierarchical decision-making process, yet resource selection studies often focus on the presence and absence of an animal rather than the animal's behavior at resource use locations. In this study, we investigate foraging and vocalization resource selection in a population of Willow Flycatchers, Empidonax traillii adastus, using Bayesian spatial generalized linear models. These models produce “behavioral landscapes” in which space use and resource selection is linked through behavior. Radio telemetry locations were collected from 35 adult Willow Flycatchers (n = 14 males, n = 13 females, and n = 8 unknown sex) over the 2003 and 2004 breeding seasons at Fish Creek, Utah. Results from the 2-stage modeling approach showed that habitat type, perch position, and distance from the arithmetic mean of the home range (in males) or nest site (in females) were important factors influencing foraging and vocalization resource selection. Parameter estimates from the individual-level models indicated high intraspecific variation in the use of the various habitat types and perch heights for foraging and vocalization. On the population level, Willow Flycatchers selected riparian habitat over other habitat types for vocalizing but used multiple habitat types for foraging including mountain shrub, young riparian, and upland forest. Mapping of observed and predicted foraging and vocalization resource selection indicated that the behavior often occurred in disparate areas of the home range. This suggests that multiple core areas may exist in the home ranges of individual flycatchers, and demonstrates that the behavioral landscape modeling approach can be applied to identify spatially and behaviorally distinct core areas. The behavioral landscape approach is applicable to a wide range of animal taxa and can be used to improve our understanding of the spatial context of behavior and resource selection.

Geometric mean for subspace selection.

PubMed

Tao, Dacheng; Li, Xuelong; Wu, Xindong; Maybank, Stephen J

2009-02-01

Subspace selection approaches are powerful tools in pattern classification and data visualization. One of the most important subspace approaches is the linear dimensionality reduction step in the Fisher's linear discriminant analysis (FLDA), which has been successfully employed in many fields such as biometrics, bioinformatics, and multimedia information management. However, the linear dimensionality reduction step in FLDA has a critical drawback: for a classification task with c classes, if the dimension of the projected subspace is strictly lower than c - 1, the projection to a subspace tends to merge those classes, which are close together in the original feature space. If separate classes are sampled from Gaussian distributions, all with identical covariance matrices, then the linear dimensionality reduction step in FLDA maximizes the mean value of the Kullback-Leibler (KL) divergences between different classes. Based on this viewpoint, the geometric mean for subspace selection is studied in this paper. Three criteria are analyzed: 1) maximization of the geometric mean of the KL divergences, 2) maximization of the geometric mean of the normalized KL divergences, and 3) the combination of 1 and 2. Preliminary experimental results based on synthetic data, UCI Machine Learning Repository, and handwriting digits show that the third criterion is a potential discriminative subspace selection method, which significantly reduces the class separation problem in comparing with the linear dimensionality reduction step in FLDA and its several representative extensions.

Creating a non-linear total sediment load formula using polynomial best subset regression model

NASA Astrophysics Data System (ADS)

Okcu, Davut; Pektas, Ali Osman; Uyumaz, Ali

2016-08-01

The aim of this study is to derive a new total sediment load formula which is more accurate and which has less application constraints than the well-known formulae of the literature. 5 most known stream power concept sediment formulae which are approved by ASCE are used for benchmarking on a wide range of datasets that includes both field and flume (lab) observations. The dimensionless parameters of these widely used formulae are used as inputs in a new regression approach. The new approach is called Polynomial Best subset regression (PBSR) analysis. The aim of the PBRS analysis is fitting and testing all possible combinations of the input variables and selecting the best subset. Whole the input variables with their second and third powers are included in the regression to test the possible relation between the explanatory variables and the dependent variable. While selecting the best subset a multistep approach is used that depends on significance values and also the multicollinearity degrees of inputs. The new formula is compared to others in a holdout dataset and detailed performance investigations are conducted for field and lab datasets within this holdout data. Different goodness of fit statistics are used as they represent different perspectives of the model accuracy. After the detailed comparisons are carried out we figured out the most accurate equation that is also applicable on both flume and river data. Especially, on field dataset the prediction performance of the proposed formula outperformed the benchmark formulations.

Activation of Remote meta-C–H Bonds Assisted by an “End-on” Template

PubMed Central

Leow, Dasheng; Li, Gang; Mei, Tiansheng; Yu, Jin-Quan

2012-01-01

Controlling positional selectivity of C–H activation in molecules possessing multiple inequivalent C–H bonds is one of the most important challenges in developing synthetically useful C–H activation reactions. One widely used approach utilizes σ-chelating directing groups to achieve ortho-selectivity through conformational rigid five- or six-membered cyclic pre-transition states (TS).1–14 We envisioned that an “end-on” chelating template capable of delivering catalysts to previously inaccessible remote meta-C–H bonds via a macrocyclic cyclophane-like pre-TS could overcome the limitations imposed by traditional ortho-directing groups. Herein, we report a class of readily removable nitrile-containing templates that direct the activation of distal meta-C–H bonds (≥ 10 bonds away) of a tethered arene. We attribute this new mode of C–H activation to the weak “end-on” coordination of the linear nitrile group to metal center, as previously observed by Schwarz in the study of remote C–H activation of alkyl nitriles in gas phase.15, 16 The coordination geometry relieves the strain of the cyclophane-like pre-transition state of the meta-C–H activation event. Remarkably, this template overrides electronic and steric biases and ortho-directing effects with two broadly useful classes of arene substrates (toluene derivatives and hydrocinnamic acids), thus constituting a fundamentally new mode of directed C–H activation that is anticipated to be widely adopted. PMID:22739317

Prioritizing individual genetic variants after kernel machine testing using variable selection.

PubMed

He, Qianchuan; Cai, Tianxi; Liu, Yang; Zhao, Ni; Harmon, Quaker E; Almli, Lynn M; Binder, Elisabeth B; Engel, Stephanie M; Ressler, Kerry J; Conneely, Karen N; Lin, Xihong; Wu, Michael C

2016-12-01

Kernel machine learning methods, such as the SNP-set kernel association test (SKAT), have been widely used to test associations between traits and genetic polymorphisms. In contrast to traditional single-SNP analysis methods, these methods are designed to examine the joint effect of a set of related SNPs (such as a group of SNPs within a gene or a pathway) and are able to identify sets of SNPs that are associated with the trait of interest. However, as with many multi-SNP testing approaches, kernel machine testing can draw conclusion only at the SNP-set level, and does not directly inform on which one(s) of the identified SNP set is actually driving the associations. A recently proposed procedure, KerNel Iterative Feature Extraction (KNIFE), provides a general framework for incorporating variable selection into kernel machine methods. In this article, we focus on quantitative traits and relatively common SNPs, and adapt the KNIFE procedure to genetic association studies and propose an approach to identify driver SNPs after the application of SKAT to gene set analysis. Our approach accommodates several kernels that are widely used in SNP analysis, such as the linear kernel and the Identity by State (IBS) kernel. The proposed approach provides practically useful utilities to prioritize SNPs, and fills the gap between SNP set analysis and biological functional studies. Both simulation studies and real data application are used to demonstrate the proposed approach. © 2016 WILEY PERIODICALS, INC.

Secular instabilities of Keplerian stellar discs

NASA Astrophysics Data System (ADS)

Kaur, Karamveer; Kazandjian, Mher V.; Sridhar, S.; Touma, Jihad R.

2018-05-01

We present idealized models of a razor-thin, axisymmetric, Keplerian stellar disc around a massive black hole, and study non-axisymmetric secular instabilities in the absence of either counter-rotation or loss cones. These discs are prograde mono-energetic waterbags, whose phase-space distribution functions are constant for orbits within a range of eccentricities (e) and zero outside this range. The linear normal modes of waterbags are composed of sinusoidal disturbances of the edges of distribution function in phase space. Waterbags that include circular orbits (polarcaps) have one stable linear normal mode for each azimuthal wavenumber m. The m = 1 mode always has positive pattern speed and, for polarcaps consisting of orbits with e < 0.9428, only the m = 1 mode has positive pattern speed. Waterbags excluding circular orbits (bands) have two linear normal modes for each m, which can be stable or unstable. We derive analytical expressions for the instability condition, pattern speeds, growth rates, and normal mode structure. Narrow bands are unstable to modes with a wide range in m. Numerical simulations confirm linear theory and follow the non-linear evolution of instabilities. Long-time integration suggests that instabilities of different m grow, interact non-linearly, and relax collisionlessly to a coarse-grained equilibrium with a wide range of eccentricities.

Objective Model Selection for Identifying the Human Feedforward Response in Manual Control.

PubMed

Drop, Frank M; Pool, Daan M; van Paassen, Marinus Rene M; Mulder, Max; Bulthoff, Heinrich H

2018-01-01

Realistic manual control tasks typically involve predictable target signals and random disturbances. The human controller (HC) is hypothesized to use a feedforward control strategy for target-following, in addition to feedback control for disturbance-rejection. Little is known about human feedforward control, partly because common system identification methods have difficulty in identifying whether, and (if so) how, the HC applies a feedforward strategy. In this paper, an identification procedure is presented that aims at an objective model selection for identifying the human feedforward response, using linear time-invariant autoregressive with exogenous input models. A new model selection criterion is proposed to decide on the model order (number of parameters) and the presence of feedforward in addition to feedback. For a range of typical control tasks, it is shown by means of Monte Carlo computer simulations that the classical Bayesian information criterion (BIC) leads to selecting models that contain a feedforward path from data generated by a pure feedback model: "false-positive" feedforward detection. To eliminate these false-positives, the modified BIC includes an additional penalty on model complexity. The appropriate weighting is found through computer simulations with a hypothesized HC model prior to performing a tracking experiment. Experimental human-in-the-loop data will be considered in future work. With appropriate weighting, the method correctly identifies the HC dynamics in a wide range of control tasks, without false-positive results.

A geometric nonlinear degenerated shell element using a mixed formulation with independently assumed strain fields. Final Report; Ph.D. Thesis, 1989

NASA Technical Reports Server (NTRS)

Graf, Wiley E.

1991-01-01

A mixed formulation is chosen to overcome deficiencies of the standard displacement-based shell model. Element development is traced from the incremental variational principle on through to the final set of equilibrium equations. Particular attention is paid to developing specific guidelines for selecting the optimal set of strain parameters. A discussion of constraint index concepts and their predictive capability related to locking is included. Performance characteristics of the elements are assessed in a wide variety of linear and nonlinear plate/shell problems. Despite limiting the study to geometric nonlinear analysis, a substantial amount of additional insight concerning the finite element modeling of thin plate/shell structures is provided. For example, in nonlinear analysis, given the same mesh and load step size, mixed elements converge in fewer iterations than equivalent displacement-based models. It is also demonstrated that, in mixed formulations, lower order elements are preferred. Additionally, meshes used to obtain accurate linear solutions do not necessarily converge to the correct nonlinear solution. Finally, a new form of locking was identified associated with employing elements designed for biaxial bending in uniaxial bending applications.

Quantitative nanoimmunosensor based on dark-field illumination with enhanced sensitivity and on-off switching using scattering signals.

PubMed

Lee, Seungah; Nan, He; Yu, Hyunung; Kang, Seong Ho

2016-05-15

A nanoimmunosensor based on wavelength-dependent dark-field illumination with enhanced sensitivity was used to detect a disease-related protein molecule at zeptomolar (zM) concentrations. The assay platform of 100-nm gold nanospots could be selectively acquired using the wavelength-dependence of enhanced scattering signals from antibody-conjugated plasmonic silver nanoparticles (NPs) with on-off switching using optical filters. Detection of human thyroid-stimulating hormone (hTSH) at a sensitivity of 100 zM, which corresponds to 1-2 molecules per gold spot, was possible within a linear range of 100 zM-100 fM (R=0.9968). A significantly enhanced sensitivity (~4-fold) was achieved with enhanced dark-field illumination compared to using a total internal reflection fluorescence immunosensor. Immunoreactions were confirmed via optical axial-slicing based on the spectral characteristics of two plasmonic NPs. This method of using wavelength-dependent dark-field illumination had an enhanced sensitivity and a wide, linear dynamic range of 100 zM-100 fM, and was an effective tool for quantitatively detecting a single molecule on a nanobiochip for molecular diagnostics. Copyright © 2016 Elsevier B.V. All rights reserved.

Adaptive linear rank tests for eQTL studies

PubMed Central

Szymczak, Silke; Scheinhardt, Markus O.; Zeller, Tanja; Wild, Philipp S.; Blankenberg, Stefan; Ziegler, Andreas

2013-01-01

Expression quantitative trait loci (eQTL) studies are performed to identify single-nucleotide polymorphisms that modify average expression values of genes, proteins, or metabolites, depending on the genotype. As expression values are often not normally distributed, statistical methods for eQTL studies should be valid and powerful in these situations. Adaptive tests are promising alternatives to standard approaches, such as the analysis of variance or the Kruskal–Wallis test. In a two-stage procedure, skewness and tail length of the distributions are estimated and used to select one of several linear rank tests. In this study, we compare two adaptive tests that were proposed in the literature using extensive Monte Carlo simulations of a wide range of different symmetric and skewed distributions. We derive a new adaptive test that combines the advantages of both literature-based approaches. The new test does not require the user to specify a distribution. It is slightly less powerful than the locally most powerful rank test for the correct distribution and at least as powerful as the maximin efficiency robust rank test. We illustrate the application of all tests using two examples from different eQTL studies. PMID:22933317

Adaptive linear rank tests for eQTL studies.

PubMed

Szymczak, Silke; Scheinhardt, Markus O; Zeller, Tanja; Wild, Philipp S; Blankenberg, Stefan; Ziegler, Andreas

2013-02-10

Expression quantitative trait loci (eQTL) studies are performed to identify single-nucleotide polymorphisms that modify average expression values of genes, proteins, or metabolites, depending on the genotype. As expression values are often not normally distributed, statistical methods for eQTL studies should be valid and powerful in these situations. Adaptive tests are promising alternatives to standard approaches, such as the analysis of variance or the Kruskal-Wallis test. In a two-stage procedure, skewness and tail length of the distributions are estimated and used to select one of several linear rank tests. In this study, we compare two adaptive tests that were proposed in the literature using extensive Monte Carlo simulations of a wide range of different symmetric and skewed distributions. We derive a new adaptive test that combines the advantages of both literature-based approaches. The new test does not require the user to specify a distribution. It is slightly less powerful than the locally most powerful rank test for the correct distribution and at least as powerful as the maximin efficiency robust rank test. We illustrate the application of all tests using two examples from different eQTL studies. Copyright © 2012 John Wiley & Sons, Ltd.

Synthesis of gold-cellobiose nanocomposites for colorimetric measurement of cellobiase activity.

PubMed

Lai, Cui; Zeng, Guang-Ming; Huang, Dan-Lian; Zhao, Mei-Hua; Wei, Zhen; Huang, Chao; Xu, Piao; Li, Ning-Jie; Zhang, Chen; Chen, Ming; Li, Xue; Lai, Mingyong; He, Yibin

2014-11-11

Gold-cellobiose nanocomposites (GCNCs) were synthesized by reducing gold salt with a polysaccharide, cellobiose. Here, cellobiose acted as a controller of nucleation or stabilizer in the formation of gold nanoparticles. The obtained GCNCs were characterized with UV-visible spectroscopy; Zetasizer and Fourier transform infrared (FT-IR) spectrophotometer. Moreover, 6-Mercapto-1-hexanol (MCH) was modified on GCNCs, and the MCH-GCNCs were used to determine the cellobiase activity in compost extracts based on the surface plasmon resonance (SPR) property of MCH-GCNCs. The degradation of cellobiose on MCH-GCNCs by cellobiase could induce the aggregation, and the SPR absorption wavelength of MCH-GCNCs correspondingly red shifted. Thus, the absorbance ratio of treated MCH-GCNCs (A650/A520) could be used to estimate the cellobiase activity, and the probe exhibited highly sensitive and selective detection of the cellobiase activity with a wide linear from 3.0 to 100.0U L(-1) within 20 min. Meanwhile, a good linear relationship with correlation coefficient of R2=0.9976 was obtained. This approach successfully showed the suitability of gold nanocomposites as a colorimetric sensor for the sensitive and specific enzyme activity detection. Copyright © 2014 Elsevier B.V. All rights reserved.

Development of electrochemical folic acid sensor based on hydroxyapatite nanoparticles

NASA Astrophysics Data System (ADS)

Kanchana, P.; Sekar, C.

2015-02-01

We report the synthesis of hydroxyapatite (HA) nanoparticles (NPs) by a simple microwave irradiation method and its application as sensing element for the precise determination of folic acid (FA) by electrochemical method. The structure and composition of the HA NPs characterized using XRD, FTIR, Raman and XPS. SEM and EDX studies confirmed the formation of elongated spherical shaped HA NPs with an average particle size of about 34 nm. The HA NPs thin film on glassy carbon electrode (GCE) were deposited by drop casting method. Electrocatalytic behavior of FA in the physiological pH 7.0 was investigated by cyclic voltammetry (CV), linear sweep voltammetry (LSV) and chronoamperometry. The fabricated HA/GCE exhibited a linear calibration plot over a wide FA concentration ranging from 1.0 × 10-7 to 3.5 × 10-4 M with the detection limit of 75 nM. In addition, the HA NPs modified GCE showed good selectivity toward the determination of FA even in the presence of a 100-fold excess of ascorbic acid (AA) and 1000-fold excess of other common interferents. The fabricated biosensor exhibits good sensitivity and stability, and was successfully applied for the determination of FA in pharmaceutical samples.

Proof of the quantitative potential of immunofluorescence by mass spectrometry.

PubMed

Toki, Maria I; Cecchi, Fabiola; Hembrough, Todd; Syrigos, Konstantinos N; Rimm, David L

2017-03-01

Protein expression in formalin-fixed, paraffin-embedded patient tissue is routinely measured by Immunohistochemistry (IHC). However, IHC has been shown to be subject to variability in sensitivity, specificity and reproducibility, and is generally, at best, considered semi-quantitative. Mass spectrometry (MS) is considered by many to be the criterion standard for protein measurement, offering high sensitivity, specificity, and objective molecular quantification. Here, we seek to show that quantitative immunofluorescence (QIF) with standardization can achieve quantitative results comparable to MS. Epidermal growth factor receptor (EGFR) was measured by quantitative immunofluorescence in 15 cell lines with a wide range of EGFR expression, using different primary antibody concentrations, including the optimal signal-to-noise concentration after quantitative titration. QIF target measurement was then compared to the absolute EGFR concentration measured by Liquid Tissue-selected reaction monitoring mass spectrometry. The best agreement between the two assays was found when the EGFR primary antibody was used at the optimal signal-to-noise concentration, revealing a strong linear regression (R 2 =0.88). This demonstrates that quantitative optimization of titration by calculation of signal-to-noise ratio allows QIF to be standardized to MS and can therefore be used to assess absolute protein concentration in a linear and reproducible manner.

A novel approach for prediction of tacrolimus blood concentration in liver transplantation patients in the intensive care unit through support vector regression.

PubMed

Van Looy, Stijn; Verplancke, Thierry; Benoit, Dominique; Hoste, Eric; Van Maele, Georges; De Turck, Filip; Decruyenaere, Johan

2007-01-01

Tacrolimus is an important immunosuppressive drug for organ transplantation patients. It has a narrow therapeutic range, toxic side effects, and a blood concentration with wide intra- and interindividual variability. Hence, it is of the utmost importance to monitor tacrolimus blood concentration, thereby ensuring clinical effect and avoiding toxic side effects. Prediction models for tacrolimus blood concentration can improve clinical care by optimizing monitoring of these concentrations, especially in the initial phase after transplantation during intensive care unit (ICU) stay. This is the first study in the ICU in which support vector machines, as a new data modeling technique, are investigated and tested in their prediction capabilities of tacrolimus blood concentration. Linear support vector regression (SVR) and nonlinear radial basis function (RBF) SVR are compared with multiple linear regression (MLR). Tacrolimus blood concentrations, together with 35 other relevant variables from 50 liver transplantation patients, were extracted from our ICU database. This resulted in a dataset of 457 blood samples, on average between 9 and 10 samples per patient, finally resulting in a database of more than 16,000 data values. Nonlinear RBF SVR, linear SVR, and MLR were performed after selection of clinically relevant input variables and model parameters. Differences between observed and predicted tacrolimus blood concentrations were calculated. Prediction accuracy of the three methods was compared after fivefold cross-validation (Friedman test and Wilcoxon signed rank analysis). Linear SVR and nonlinear RBF SVR had mean absolute differences between observed and predicted tacrolimus blood concentrations of 2.31 ng/ml (standard deviation [SD] 2.47) and 2.38 ng/ml (SD 2.49), respectively. MLR had a mean absolute difference of 2.73 ng/ml (SD 3.79). The difference between linear SVR and MLR was statistically significant (p < 0.001). RBF SVR had the advantage of requiring only 2 input variables to perform this prediction in comparison to 15 and 16 variables needed by linear SVR and MLR, respectively. This is an indication of the superior prediction capability of nonlinear SVR. Prediction of tacrolimus blood concentration with linear and nonlinear SVR was excellent, and accuracy was superior in comparison with an MLR model.

One-Pot Green Synthesis of Graphene Nanosheets Encapsulated Gold Nanoparticles for Sensitive and Selective Detection of Dopamine

PubMed Central

Thirumalraj, Balamurugan; Rajkumar, Chellakannu; Chen, Shen-Ming; Palanisamy, Selvakumar

2017-01-01

We report a simple new approach for green preparation of gallic acid supported reduced graphene oxide encapsulated gold nanoparticles (GA-RGO/AuNPs) via one-pot hydrothermal method. The as-prepared composites were successfully characterized by using Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, X-ray powder diffraction techniques (XRD), scanning electron microscope (SEM), high resolution transmission electron microscopy (HRTEM) and elemental analysis. The GA-RGO/AuNPs modified electrode behaves as a hybrid electrode material for sensitive and selective detection of dopamine (DA) in presence of ascorbic acid (AA) and uric acid (UA). The GA-RGO/AuNPs modified electrode displays an excellent electrocatalytic activity towards the oxidation of DA and exhibits a wide linear response range over the DA concentrations from 0.01–100.3 μM with a detection limit (LOD) of 2.6 nM based on S/N = 3. In addition, the proposed sensor could be applied for the determination of DA in human serum and urine samples for practical analysis. PMID:28128225

Voltammetric determination of homocysteine using multiwall carbon nanotube paste electrode in the presence of chlorpromazine as a mediator.

PubMed

Gholami-Orimi, Fathali; Taleshi, Farshad; Biparva, Pourya; Karimi-Maleh, Hassan; Beitollahi, Hadi; Ebrahimi, Hamid R; Shamshiri, Mohamad; Bagheri, Hasan; Fouladgar, Masoud; Taherkhani, Ali

2012-01-01

We propose chlorpromazine (CHP) as a new mediator for the rapid, sensitive, and highly selective voltammetric determination of homocysteine (Hcy) using multiwall carbon nanotube paste electrode (MWCNTPE). The experimental results showed that the carbon nanotube paste electrode has a highly electrocatalytic activity for the oxidation of Hcy in the presence of CHP as a mediator. Cyclic voltammetry, double potential step chronoamperometry, and square wave voltammetry (SWV) are used to investigate the suitability of CHP at the surface of MWCNTPE as a mediator for the electrocatalytic oxidation of Hcy in aqueous solutions. The kinetic parameters of the system, including electron transfer coefficient, and catalytic rate constant were also determined using the electrochemical approaches. In addition, SWV was used for quantitative analysis. SWV showed wide linear dynamic range (0.1-210.0 μM Hcy) with a detection limit of 0.08 μM Hcy. Finally, this method was also examined as a selective, simple, and precise electrochemical sensor for the determination of Hcy in real samples.

Voltammetric Determination of Homocysteine Using Multiwall Carbon Nanotube Paste Electrode in the Presence of Chlorpromazine as a Mediator

PubMed Central

Gholami-Orimi, Fathali; Taleshi, Farshad; Biparva, Pourya; Karimi-Maleh, Hassan; Beitollahi, Hadi; Ebrahimi, Hamid R.; Shamshiri, Mohamad; Bagheri, Hasan; Fouladgar, Masoud; Taherkhani, Ali

2012-01-01

We propose chlorpromazine (CHP) as a new mediator for the rapid, sensitive, and highly selective voltammetric determination of homocysteine (Hcy) using multiwall carbon nanotube paste electrode (MWCNTPE). The experimental results showed that the carbon nanotube paste electrode has a highly electrocatalytic activity for the oxidation of Hcy in the presence of CHP as a mediator. Cyclic voltammetry, double potential step chronoamperometry, and square wave voltammetry (SWV) are used to investigate the suitability of CHP at the surface of MWCNTPE as a mediator for the electrocatalytic oxidation of Hcy in aqueous solutions. The kinetic parameters of the system, including electron transfer coefficient, and catalytic rate constant were also determined using the electrochemical approaches. In addition, SWV was used for quantitative analysis. SWV showed wide linear dynamic range (0.1–210.0 μM Hcy) with a detection limit of 0.08 μM Hcy. Finally, this method was also examined as a selective, simple, and precise electrochemical sensor for the determination of Hcy in real samples. PMID:22675657

Dual nickel and Lewis acid catalysis for cross-electrophile coupling: the allylation of aryl halides with allylic alcohols† †Electronic supplementary information (ESI) available. CCDC 1515176. For ESI and crystallographic data in CIF or other electronic format see DOI: 10.1039/c7sc03140h

PubMed Central

Jia, Xue-Gong; Guo, Peng; Duan, Jicheng

2017-01-01

Controlling the selectivity in cross-electrophile coupling reactions is a significant challenge, particularly when one electrophile is much more reactive. We report a general and practical strategy to address this problem in the reaction between reactive and unreactive electrophiles by a combination of nickel and Lewis acid catalysis. This strategy is used for the coupling of aryl halides with allylic alcohols to form linear allylarenes selectively. The reaction tolerates a wide range of functional groups (e.g. silanes, boronates, anilines, esters, alcohols, and various heterocycles) and works with various allylic alcohols. Complementary to most current routes for the C3 allylation of an unprotected indole, this method provides access to C2 and C4–C7 allylated indoles. Preliminary mechanistic experiments reveal that the reaction might start with an aryl nickel intermediate, which then reacts with Lewis acid activated allylic alcohols in the presence of Mn. PMID:29629130

One-Pot Green Synthesis of Graphene Nanosheets Encapsulated Gold Nanoparticles for Sensitive and Selective Detection of Dopamine

NASA Astrophysics Data System (ADS)

Thirumalraj, Balamurugan; Rajkumar, Chellakannu; Chen, Shen-Ming; Palanisamy, Selvakumar

2017-01-01

We report a simple new approach for green preparation of gallic acid supported reduced graphene oxide encapsulated gold nanoparticles (GA-RGO/AuNPs) via one-pot hydrothermal method. The as-prepared composites were successfully characterized by using Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, X-ray powder diffraction techniques (XRD), scanning electron microscope (SEM), high resolution transmission electron microscopy (HRTEM) and elemental analysis. The GA-RGO/AuNPs modified electrode behaves as a hybrid electrode material for sensitive and selective detection of dopamine (DA) in presence of ascorbic acid (AA) and uric acid (UA). The GA-RGO/AuNPs modified electrode displays an excellent electrocatalytic activity towards the oxidation of DA and exhibits a wide linear response range over the DA concentrations from 0.01-100.3 μM with a detection limit (LOD) of 2.6 nM based on S/N = 3. In addition, the proposed sensor could be applied for the determination of DA in human serum and urine samples for practical analysis.

A Label-Free Electrochemical Impedance Cytosensor Based on Specific Peptide-Fused Phage Selected from Landscape Phage Library

NASA Astrophysics Data System (ADS)

Han, Lei; Liu, Pei; Petrenko, Valery A.; Liu, Aihua

2016-02-01

One of the major challenges in the design of biosensors for cancer diagnosis is to introduce a low-cost and selective probe that can recognize cancer cells. In this paper, we combined the phage display technology and electrochemical impedance spectroscopy (EIS) to develop a label-free cytosensor for the detection of cancer cells, without complicated purification of recognition elements. Fabrication steps of the cytosensing interface were monitored by EIS. Due to the high specificity of the displayed octapeptides and avidity effect of their multicopy display on the phage scaffold, good biocompatibility of recombinant phage, the fibrous nanostructure of phage, and the inherent merits of EIS technology, the proposed cytosensor demonstrated a wide linear range (2.0 × 102 - 2.0 × 108 cells mL-1), a low limit of detection (79 cells mL-1, S/N = 3), high specificity, good inter-and intra-assay reproducibility and satisfactory storage stability. This novel cytosensor designing strategy will open a new prospect for rapid and label-free electrochemical platform for tumor diagnosis.

Speed selection for traveling-wave solutions to the diffusion-reaction equation with cubic reaction term and Burgers nonlinear convection.

PubMed

Sabelnikov, V A; Lipatnikov, A N

2014-09-01

The problem of traveling wave (TW) speed selection for solutions to a generalized Murray-Burgers-KPP-Fisher parabolic equation with a strictly positive cubic reaction term is considered theoretically and the initial boundary value problem is numerically solved in order to support obtained analytical results. Depending on the magnitude of a parameter inherent in the reaction term (i) the term is either a concave function or a function with the inflection point and (ii) transition from pulled to pushed TW solution occurs due to interplay of two nonlinear terms; the reaction term and the Burgers convection term. Explicit pushed TW solutions are derived. It is shown that physically observable TW solutions, i.e., solutions obtained by solving the initial boundary value problem with a sufficiently steep initial condition, can be determined by seeking the TW solution characterized by the maximum decay rate at its leading edge. In the Appendix, the developed approach is applied to a non-linear diffusion-reaction equation that is widely used to model premixed turbulent combustion.

Nonnegative constraint analysis of key fluorophores within human breast cancer using native fluorescence spectroscopy excited by selective wavelength of 300 nm

NASA Astrophysics Data System (ADS)

Pu, Yang; Sordillo, Laura A.; Alfano, Robert R.

2015-03-01

Native fluorescence spectroscopy offers an important role in cancer discrimination. It is widely acknowledged that the emission spectrum of tissue is a superposition of spectra of various salient fluorophores. In this study, the native fluorescence spectra of human cancerous and normal breast tissues excited by selected wavelength of 300 nm are used to investigate the key building block fluorophores: tryptophan and reduced nicotinamide adenine dinucleotide (NADH). The basis spectra of these key fluorophores' contribution to the tissue emission spectra are obtained by nonnegative constraint analysis. The emission spectra of human cancerous and normal tissue samples are projected onto the fluorophore spectral subspace. Since previous studies indicate that tryptophan and NADH are key fluorophores related with tumor evolution, it is essential to obtain their information from tissue fluorescence but discard the redundancy. To evaluate the efficacy of for cancer detection, linear discriminant analysis (LDA) classifier is used to evaluate the sensitivity, and specificity. This research demonstrates that the native fluorescence spectroscopy measurements are effective to detect changes of fluorophores' compositions in tissues due to the development of cancer.

Tree structure and cavity microclimate: implications for bats and birds.

PubMed

Clement, Matthew J; Castleberry, Steven B

2013-05-01

It is widely assumed that tree cavity structure and microclimate affect cavity selection and use in cavity-dwelling bats and birds. Despite the interest in tree structure and microclimate, the relationship between the two has rarely been quantified. Currently available data often comes from artificial structures that may not accurately represent conditions in natural cavities. We collected data on tree cavity structure and microclimate from 45 trees in five cypress-gum swamps in the Coastal Plain of Georgia in the United States in 2008. We used hierarchical linear models to predict cavity microclimate from tree structure and ambient temperature and humidity, and used Aikaike's information criterion to select the most parsimonious models. We found large differences in microclimate among trees, but tree structure variables explained <28% of the variation, while ambient conditions explained >80% of variation common to all trees. We argue that the determinants of microclimate are complex and multidimensional, and therefore cavity microclimate cannot be deduced easily from simple tree structures. Furthermore, we found that daily fluctuations in ambient conditions strongly affect microclimate, indicating that greater weather fluctuations will cause greater differences among tree cavities.

EDTA assisted synthesis of hydroxyapatite nanoparticles for electrochemical sensing of uric acid.

PubMed

Kanchana, P; Sekar, C

2014-09-01

Hydroxyapatite nanoparticles have been synthesized using EDTA as organic modifier by a simple microwave irradiation method and its application for the selective determination of uric acid (UA) has been demonstrated. Electrochemical behavior of uric acid at HA nanoparticle modified glassy carbon electrode (E-HA/GCE) has been investigated by electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), linear sweep voltammetry (LSV) and amperometry. The E-HA modified electrode exhibits efficient electrochemical activity towards uric acid sensing without requiring enzyme or electron mediator. Amperometry studies revealed that the fabricated electrode has excellent sensitivity for uric acid with the lowest detection limit of 142 nM over a wide concentration range from 1 × 10(-7) to 3 × 10(-5)M. Moreover, the studied E-HA modified GC electrode exhibits a good reproducibility and long-term stability and an admirable selectivity towards the determination of UA even in the presence of potential interferents. The analytical performance of this sensor was evaluated for the detection of uric acid in human urine and blood serum samples. Copyright © 2014. Published by Elsevier B.V.

Upconversion particles coated with molecularly imprinted polymers as fluorescence probe for detection of clenbuterol.

PubMed

Tang, Yiwei; Gao, Ziyuan; Wang, Shuo; Gao, Xue; Gao, Jingwen; Ma, Yong; Liu, Xiuying; Li, Jianrong

2015-09-15

A novel fluorescence probe based on upconversion particles, YF3:Yb(3+), Er(3+), coating with molecularly imprinted polymers (MIPs@UCPs) has been synthesized for selective recognition of the analyte clenbuterol (CLB), which was characterized by scan electron microscope and X-ray powder diffraction. The fluorescence of the MIPs@UCPs probe is quenched specifically by CLB, and the effect is much stronger than the NIPs@UCPs (non-imprinting polymers, NIPs). Good linear correlation was obtained for CLB over the concentration range of 5.0-100.0 μg L(-1) with a detection limit of 0.12 μg L(-1) (S/N=3). The developed method was also used in the determination of CLB in water and pork samples, and the recoveries ranged from 81.66% to 102.46% were obtained with relative standard deviation of 2.96-4.98% (n=3). The present study provides a new and general tactics to synthesize MIPs@UCPs fluorescence probe with highly selective recognition ability to the CLB and is desirable for application widely in the near future. Copyright © 2015 Elsevier B.V. All rights reserved.

Generalised Assignment Matrix Methodology in Linear Programming

ERIC Educational Resources Information Center

Jerome, Lawrence

2012-01-01

Discrete Mathematics instructors and students have long been struggling with various labelling and scanning algorithms for solving many important problems. This paper shows how to solve a wide variety of Discrete Mathematics and OR problems using assignment matrices and linear programming, specifically using Excel Solvers although the same…

The Elementary Operations of Human Vision Are Not Reducible to Template-Matching

PubMed Central

Neri, Peter

2015-01-01

It is generally acknowledged that biological vision presents nonlinear characteristics, yet linear filtering accounts of visual processing are ubiquitous. The template-matching operation implemented by the linear-nonlinear cascade (linear filter followed by static nonlinearity) is the most widely adopted computational tool in systems neuroscience. This simple model achieves remarkable explanatory power while retaining analytical tractability, potentially extending its reach to a wide range of systems and levels in sensory processing. The extent of its applicability to human behaviour, however, remains unclear. Because sensory stimuli possess multiple attributes (e.g. position, orientation, size), the issue of applicability may be asked by considering each attribute one at a time in relation to a family of linear-nonlinear models, or by considering all attributes collectively in relation to a specified implementation of the linear-nonlinear cascade. We demonstrate that human visual processing can operate under conditions that are indistinguishable from linear-nonlinear transduction with respect to substantially different stimulus attributes of a uniquely specified target signal with associated behavioural task. However, no specific implementation of a linear-nonlinear cascade is able to account for the entire collection of results across attributes; a satisfactory account at this level requires the introduction of a small gain-control circuit, resulting in a model that no longer belongs to the linear-nonlinear family. Our results inform and constrain efforts at obtaining and interpreting comprehensive characterizations of the human sensory process by demonstrating its inescapably nonlinear nature, even under conditions that have been painstakingly fine-tuned to facilitate template-matching behaviour and to produce results that, at some level of inspection, do conform to linear filtering predictions. They also suggest that compliance with linear transduction may be the targeted outcome of carefully crafted nonlinear circuits, rather than default behaviour exhibited by basic components. PMID:26556758

A Comparison of Classical Force-Fields for Molecular Dynamics Simulations of Lubricants

PubMed Central

Ewen, James P.; Gattinoni, Chiara; Thakkar, Foram M.; Morgan, Neal; Spikes, Hugh A.; Dini, Daniele

2016-01-01

For the successful development and application of lubricants, a full understanding of their complex nanoscale behavior under a wide range of external conditions is required, but this is difficult to obtain experimentally. Nonequilibrium molecular dynamics (NEMD) simulations can be used to yield unique insights into the atomic-scale structure and friction of lubricants and additives; however, the accuracy of the results depend on the chosen force-field. In this study, we demonstrate that the use of an accurate, all-atom force-field is critical in order to; (i) accurately predict important properties of long-chain, linear molecules; and (ii) reproduce experimental friction behavior of multi-component tribological systems. In particular, we focus on n-hexadecane, an important model lubricant with a wide range of industrial applications. Moreover, simulating conditions common in tribological systems, i.e., high temperatures and pressures (HTHP), allows the limits of the selected force-fields to be tested. In the first section, a large number of united-atom and all-atom force-fields are benchmarked in terms of their density and viscosity prediction accuracy of n-hexadecane using equilibrium molecular dynamics (EMD) simulations at ambient and HTHP conditions. Whilst united-atom force-fields accurately reproduce experimental density, the viscosity is significantly under-predicted compared to all-atom force-fields and experiments. Moreover, some all-atom force-fields yield elevated melting points, leading to significant overestimation of both the density and viscosity. In the second section, the most accurate united-atom and all-atom force-field are compared in confined NEMD simulations which probe the structure and friction of stearic acid adsorbed on iron oxide and separated by a thin layer of n-hexadecane. The united-atom force-field provides an accurate representation of the structure of the confined stearic acid film; however, friction coefficients are consistently under-predicted and the friction-coverage and friction-velocity behavior deviates from that observed using all-atom force-fields and experimentally. This has important implications regarding force-field selection for NEMD simulations of systems containing long-chain, linear molecules; specifically, it is recommended that accurate all-atom potentials, such as L-OPLS-AA, are employed. PMID:28773773

A Comparison of Classical Force-Fields for Molecular Dynamics Simulations of Lubricants.

PubMed

Ewen, James P; Gattinoni, Chiara; Thakkar, Foram M; Morgan, Neal; Spikes, Hugh A; Dini, Daniele

2016-08-02

For the successful development and application of lubricants, a full understanding of their complex nanoscale behavior under a wide range of external conditions is required, but this is difficult to obtain experimentally. Nonequilibrium molecular dynamics (NEMD) simulations can be used to yield unique insights into the atomic-scale structure and friction of lubricants and additives; however, the accuracy of the results depend on the chosen force-field. In this study, we demonstrate that the use of an accurate, all-atom force-field is critical in order to; (i) accurately predict important properties of long-chain, linear molecules; and (ii) reproduce experimental friction behavior of multi-component tribological systems. In particular, we focus on n -hexadecane, an important model lubricant with a wide range of industrial applications. Moreover, simulating conditions common in tribological systems, i.e., high temperatures and pressures (HTHP), allows the limits of the selected force-fields to be tested. In the first section, a large number of united-atom and all-atom force-fields are benchmarked in terms of their density and viscosity prediction accuracy of n -hexadecane using equilibrium molecular dynamics (EMD) simulations at ambient and HTHP conditions. Whilst united-atom force-fields accurately reproduce experimental density, the viscosity is significantly under-predicted compared to all-atom force-fields and experiments. Moreover, some all-atom force-fields yield elevated melting points, leading to significant overestimation of both the density and viscosity. In the second section, the most accurate united-atom and all-atom force-field are compared in confined NEMD simulations which probe the structure and friction of stearic acid adsorbed on iron oxide and separated by a thin layer of n -hexadecane. The united-atom force-field provides an accurate representation of the structure of the confined stearic acid film; however, friction coefficients are consistently under-predicted and the friction-coverage and friction-velocity behavior deviates from that observed using all-atom force-fields and experimentally. This has important implications regarding force-field selection for NEMD simulations of systems containing long-chain, linear molecules; specifically, it is recommended that accurate all-atom potentials, such as L-OPLS-AA, are employed.

Learning epistatic interactions from sequence-activity data to predict enantioselectivity

NASA Astrophysics Data System (ADS)

Zaugg, Julian; Gumulya, Yosephine; Malde, Alpeshkumar K.; Bodén, Mikael

2017-12-01

Enzymes with a high selectivity are desirable for improving economics of chemical synthesis of enantiopure compounds. To improve enzyme selectivity mutations are often introduced near the catalytic active site. In this compact environment epistatic interactions between residues, where contributions to selectivity are non-additive, play a significant role in determining the degree of selectivity. Using support vector machine regression models we map mutations to the experimentally characterised enantioselectivities for a set of 136 variants of the epoxide hydrolase from the fungus Aspergillus niger (AnEH). We investigate whether the influence a mutation has on enzyme selectivity can be accurately predicted through linear models, and whether prediction accuracy can be improved using higher-order counterparts. Comparing linear and polynomial degree = 2 models, mean Pearson coefficients (r) from 50 {× } 5 -fold cross-validation increase from 0.84 to 0.91 respectively. Equivalent models tested on interaction-minimised sequences achieve values of r=0.90 and r=0.93 . As expected, testing on a simulated control data set with no interactions results in no significant improvements from higher-order models. Additional experimentally derived AnEH mutants are tested with linear and polynomial degree = 2 models, with values increasing from r=0.51 to r=0.87 respectively. The study demonstrates that linear models perform well, however the representation of epistatic interactions in predictive models improves identification of selectivity-enhancing mutations. The improvement is attributed to higher-order kernel functions that represent epistatic interactions between residues.

Learning epistatic interactions from sequence-activity data to predict enantioselectivity

NASA Astrophysics Data System (ADS)

Zaugg, Julian; Gumulya, Yosephine; Malde, Alpeshkumar K.; Bodén, Mikael

2017-12-01

Enzymes with a high selectivity are desirable for improving economics of chemical synthesis of enantiopure compounds. To improve enzyme selectivity mutations are often introduced near the catalytic active site. In this compact environment epistatic interactions between residues, where contributions to selectivity are non-additive, play a significant role in determining the degree of selectivity. Using support vector machine regression models we map mutations to the experimentally characterised enantioselectivities for a set of 136 variants of the epoxide hydrolase from the fungus Aspergillus niger ( AnEH). We investigate whether the influence a mutation has on enzyme selectivity can be accurately predicted through linear models, and whether prediction accuracy can be improved using higher-order counterparts. Comparing linear and polynomial degree = 2 models, mean Pearson coefficients ( r) from 50 {× } 5-fold cross-validation increase from 0.84 to 0.91 respectively. Equivalent models tested on interaction-minimised sequences achieve values of r=0.90 and r=0.93. As expected, testing on a simulated control data set with no interactions results in no significant improvements from higher-order models. Additional experimentally derived AnEH mutants are tested with linear and polynomial degree = 2 models, with values increasing from r=0.51 to r=0.87 respectively. The study demonstrates that linear models perform well, however the representation of epistatic interactions in predictive models improves identification of selectivity-enhancing mutations. The improvement is attributed to higher-order kernel functions that represent epistatic interactions between residues.

Learning epistatic interactions from sequence-activity data to predict enantioselectivity.

PubMed

Zaugg, Julian; Gumulya, Yosephine; Malde, Alpeshkumar K; Bodén, Mikael

2017-12-01

Enzymes with a high selectivity are desirable for improving economics of chemical synthesis of enantiopure compounds. To improve enzyme selectivity mutations are often introduced near the catalytic active site. In this compact environment epistatic interactions between residues, where contributions to selectivity are non-additive, play a significant role in determining the degree of selectivity. Using support vector machine regression models we map mutations to the experimentally characterised enantioselectivities for a set of 136 variants of the epoxide hydrolase from the fungus Aspergillus niger (AnEH). We investigate whether the influence a mutation has on enzyme selectivity can be accurately predicted through linear models, and whether prediction accuracy can be improved using higher-order counterparts. Comparing linear and polynomial degree = 2 models, mean Pearson coefficients (r) from [Formula: see text]-fold cross-validation increase from 0.84 to 0.91 respectively. Equivalent models tested on interaction-minimised sequences achieve values of [Formula: see text] and [Formula: see text]. As expected, testing on a simulated control data set with no interactions results in no significant improvements from higher-order models. Additional experimentally derived AnEH mutants are tested with linear and polynomial degree = 2 models, with values increasing from [Formula: see text] to [Formula: see text] respectively. The study demonstrates that linear models perform well, however the representation of epistatic interactions in predictive models improves identification of selectivity-enhancing mutations. The improvement is attributed to higher-order kernel functions that represent epistatic interactions between residues.

Vive la résistance: genome-wide selection against introduced alleles in invasive hybrid zones

USGS Publications Warehouse

Kovach, Ryan P.; Hand, Brian K.; Hohenlohe, Paul A.; Cosart, Ted F.; Boyer, Matthew C.; Neville, Helen H.; Muhlfeld, Clint C.; Amish, Stephen J.; Carim, Kellie; Narum, Shawn R.; Lowe, Winsor H.; Allendorf, Fred W.; Luikart, Gordon

2016-01-01

Evolutionary and ecological consequences of hybridization between native and invasive species are notoriously complicated because patterns of selection acting on non-native alleles can vary throughout the genome and across environments. Rapid advances in genomics now make it feasible to assess locus-specific and genome-wide patterns of natural selection acting on invasive introgression within and among natural populations occupying diverse environments. We quantified genome-wide patterns of admixture across multiple independent hybrid zones of native westslope cutthroat trout and invasive rainbow trout, the world's most widely introduced fish, by genotyping 339 individuals from 21 populations using 9380 species-diagnostic loci. A significantly greater proportion of the genome appeared to be under selection favouring native cutthroat trout (rather than rainbow trout), and this pattern was pervasive across the genome (detected on most chromosomes). Furthermore, selection against invasive alleles was consistent across populations and environments, even in those where rainbow trout were predicted to have a selective advantage (warm environments). These data corroborate field studies showing that hybrids between these species have lower fitness than the native taxa, and show that these fitness differences are due to selection favouring many native genes distributed widely throughout the genome.

EPA Brownfields Area-Wide Planning Recipients Selected for FY13 Grant Funding

EPA Pesticide Factsheets

EPA has selected the following entities as Brownfields Area-Wide Planning grant recipients. These recipients will work with their local community members, other stakeholders and project partners to develop an area-wide plan and implementation strategy for

Maximizing the reliability of genomic selection by optimizing the calibration set of reference individuals: comparison of methods in two diverse groups of maize inbreds (Zea mays L.).

PubMed

Rincent, R; Laloë, D; Nicolas, S; Altmann, T; Brunel, D; Revilla, P; Rodríguez, V M; Moreno-Gonzalez, J; Melchinger, A; Bauer, E; Schoen, C-C; Meyer, N; Giauffret, C; Bauland, C; Jamin, P; Laborde, J; Monod, H; Flament, P; Charcosset, A; Moreau, L

2012-10-01

Genomic selection refers to the use of genotypic information for predicting breeding values of selection candidates. A prediction formula is calibrated with the genotypes and phenotypes of reference individuals constituting the calibration set. The size and the composition of this set are essential parameters affecting the prediction reliabilities. The objective of this study was to maximize reliabilities by optimizing the calibration set. Different criteria based on the diversity or on the prediction error variance (PEV) derived from the realized additive relationship matrix-best linear unbiased predictions model (RA-BLUP) were used to select the reference individuals. For the latter, we considered the mean of the PEV of the contrasts between each selection candidate and the mean of the population (PEVmean) and the mean of the expected reliabilities of the same contrasts (CDmean). These criteria were tested with phenotypic data collected on two diversity panels of maize (Zea mays L.) genotyped with a 50k SNPs array. In the two panels, samples chosen based on CDmean gave higher reliabilities than random samples for various calibration set sizes. CDmean also appeared superior to PEVmean, which can be explained by the fact that it takes into account the reduction of variance due to the relatedness between individuals. Selected samples were close to optimality for a wide range of trait heritabilities, which suggests that the strategy presented here can efficiently sample subsets in panels of inbred lines. A script to optimize reference samples based on CDmean is available on request.

Adaptive learning in complex reproducing kernel Hilbert spaces employing Wirtinger's subgradients.

PubMed

Bouboulis, Pantelis; Slavakis, Konstantinos; Theodoridis, Sergios

2012-03-01

This paper presents a wide framework for non-linear online supervised learning tasks in the context of complex valued signal processing. The (complex) input data are mapped into a complex reproducing kernel Hilbert space (RKHS), where the learning phase is taking place. Both pure complex kernels and real kernels (via the complexification trick) can be employed. Moreover, any convex, continuous and not necessarily differentiable function can be used to measure the loss between the output of the specific system and the desired response. The only requirement is the subgradient of the adopted loss function to be available in an analytic form. In order to derive analytically the subgradients, the principles of the (recently developed) Wirtinger's calculus in complex RKHS are exploited. Furthermore, both linear and widely linear (in RKHS) estimation filters are considered. To cope with the problem of increasing memory requirements, which is present in almost all online schemes in RKHS, the sparsification scheme, based on projection onto closed balls, has been adopted. We demonstrate the effectiveness of the proposed framework in a non-linear channel identification task, a non-linear channel equalization problem and a quadrature phase shift keying equalization scheme, using both circular and non circular synthetic signal sources.

Plasmonic micropolarizers for full Stokes vector imaging

NASA Astrophysics Data System (ADS)

Peltzer, J. J.; Bachman, K. A.; Rose, J. W.; Flammer, P. D.; Furtak, T. E.; Collins, R. T.; Hollingsworth, R. E.

2012-06-01

Polarimetric imaging using micropolarizers integrated on focal plane arrays has previously been limited to the linear components of the Stokes vector because of the lack of an effective structure with selectivity to circular polarization. We discuss a plasmonic micropolarizing filter that can be tuned for linear or circular polarization as well as wavelength selectivity from blue to infrared (IR) through simple changes in its horizontal geometry. The filter consists of a patterned metal film with an aperture in a central cavity that is surrounded by gratings that couple to incoming light. The aperture and gratings are covered with a transparent dielectric layer to form a surface plasmon slab waveguide. A metal cap covers the aperture and forms a metal-insulator-metal (MIM) waveguide. Structures with linear apertures and gratings provide sensitivity to linear polarization, while structures with circular apertures and spiral gratings give circular polarization selectivity. Plasmonic TM modes are transmitted down the MIM waveguide while the TE modes are cut off due to the sub-wavelength dielectric thickness, providing the potential for extremely high extinction ratios. Experimental results are presented for micropolarizers fabricated on glass or directly into the Ohmic contact metallization of silicon photodiodes. Extinction ratios for linear polarization larger than 3000 have been measured.

Localization of Non-Linearly Modeled Autonomous Mobile Robots Using Out-of-Sequence Measurements

PubMed Central

Besada-Portas, Eva; Lopez-Orozco, Jose A.; Lanillos, Pablo; de la Cruz, Jesus M.

2012-01-01

This paper presents a state of the art of the estimation algorithms dealing with Out-of-Sequence (OOS) measurements for non-linearly modeled systems. The state of the art includes a critical analysis of the algorithm properties that takes into account the applicability of these techniques to autonomous mobile robot navigation based on the fusion of the measurements provided, delayed and OOS, by multiple sensors. Besides, it shows a representative example of the use of one of the most computationally efficient approaches in the localization module of the control software of a real robot (which has non-linear dynamics, and linear and non-linear sensors) and compares its performance against other approaches. The simulated results obtained with the selected OOS algorithm shows the computational requirements that each sensor of the robot imposes to it. The real experiments show how the inclusion of the selected OOS algorithm in the control software lets the robot successfully navigate in spite of receiving many OOS measurements. Finally, the comparison highlights that not only is the selected OOS algorithm among the best performing ones of the comparison, but it also has the lowest computational and memory cost. PMID:22736962

Localization of non-linearly modeled autonomous mobile robots using out-of-sequence measurements.

PubMed

Besada-Portas, Eva; Lopez-Orozco, Jose A; Lanillos, Pablo; de la Cruz, Jesus M

2012-01-01

This paper presents a state of the art of the estimation algorithms dealing with Out-of-Sequence (OOS) measurements for non-linearly modeled systems. The state of the art includes a critical analysis of the algorithm properties that takes into account the applicability of these techniques to autonomous mobile robot navigation based on the fusion of the measurements provided, delayed and OOS, by multiple sensors. Besides, it shows a representative example of the use of one of the most computationally efficient approaches in the localization module of the control software of a real robot (which has non-linear dynamics, and linear and non-linear sensors) and compares its performance against other approaches. The simulated results obtained with the selected OOS algorithm shows the computational requirements that each sensor of the robot imposes to it. The real experiments show how the inclusion of the selected OOS algorithm in the control software lets the robot successfully navigate in spite of receiving many OOS measurements. Finally, the comparison highlights that not only is the selected OOS algorithm among the best performing ones of the comparison, but it also has the lowest computational and memory cost.

Optimal Linear Responses for Markov Chains and Stochastically Perturbed Dynamical Systems

NASA Astrophysics Data System (ADS)

Antown, Fadi; Dragičević, Davor; Froyland, Gary

2018-03-01

The linear response of a dynamical system refers to changes to properties of the system when small external perturbations are applied. We consider the little-studied question of selecting an optimal perturbation so as to (i) maximise the linear response of the equilibrium distribution of the system, (ii) maximise the linear response of the expectation of a specified observable, and (iii) maximise the linear response of the rate of convergence of the system to the equilibrium distribution. We also consider the inhomogeneous, sequential, or time-dependent situation where the governing dynamics is not stationary and one wishes to select a sequence of small perturbations so as to maximise the overall linear response at some terminal time. We develop the theory for finite-state Markov chains, provide explicit solutions for some illustrative examples, and numerically apply our theory to stochastically perturbed dynamical systems, where the Markov chain is replaced by a matrix representation of an approximate annealed transfer operator for the random dynamical system.

The Zeldovich approximation and wide-angle redshift-space distortions

NASA Astrophysics Data System (ADS)

Castorina, Emanuele; White, Martin

2018-06-01

The contribution of line-of-sight peculiar velocities to the observed redshift of objects breaks the translational symmetry of the underlying theory, modifying the predicted 2-point functions. These `wide angle effects' have mostly been studied using linear perturbation theory in the context of the multipoles of the correlation function and power spectrum . In this work we present the first calculation of wide angle terms in the Zeldovich approximation, which is known to be more accurate than linear theory on scales probed by the next generation of galaxy surveys. We present the exact result for dark matter and perturbatively biased tracers as well as the small angle expansion of the configuration- and Fourier-space two-point functions and the connection to the multi-frequency angular power spectrum. We compare different definitions of the line-of-sight direction and discuss how to translate between them. We show that wide angle terms can reach tens of percent of the total signal in a measurement at low redshift in some approximations, and that a generic feature of wide angle effects is to slightly shift the Baryon Acoustic Oscillation scale.

Parabolic variation in sexual selection intensity across the range of a cold-water pipefish: implications for susceptibility to climate change.

PubMed

Monteiro, Nuno; Cunha, Mário; Ferreira, Lídia; Vieira, Natividade; Antunes, Agostinho; Lyons, David; Jones, Adam G

2017-09-01

While an understanding of evolutionary processes in shifting environments is vital in the context of rapid ecological change, one of the most potent selective forces, sexual selection, remains curiously unexplored. Variation in sexual selection across a species range, especially across a gradient of temperature regimes, has the potential to provide a window into the possible impacts of climate change on the evolution of mating patterns. Here, we investigated some of the links between temperature and indicators of sexual selection, using a cold-water pipefish as model. We found that populations differed with respect to body size, length of the breeding season, fecundity, and sexual dimorphism across a wide latitudinal gradient. We encountered two types of latitudinal patterns, either linear, when related to body size, or parabolic in shape when considering variables related to sexual selection intensity, such as sexual dimorphism and reproductive investment. Our results suggest that sexual selection intensity increases toward both edges of the distribution and that the large differences in temperature likely play a significant role. Shorter breeding seasons in the north and reduced periods for gamete production in the south certainly have the potential to alter mating systems, breeding synchrony, and mate monopolization rates. As latitude and water temperature are tightly coupled across the European coasts, the observed patterns in traits related to sexual selection can lead to predictions regarding how sexual selection should change in response to climate change. Based on data from extant populations, we can predict that as the worm pipefish moves northward, a wave of decreasing selection intensity will likely replace the strong sexual selection at the northern range margin. In contrast, the southern populations will be followed by heightened sexual selection, which may exacerbate the problem of local extinction at this retreating boundary. © 2017 John Wiley & Sons Ltd.

INTRODUCTION TO A COMBINED MULTIPLE LINEAR REGRESSION AND ARMA MODELING APPROACH FOR BEACH BACTERIA PREDICTION

EPA Science Inventory

Due to the complexity of the processes contributing to beach bacteria concentrations, many researchers rely on statistical modeling, among which multiple linear regression (MLR) modeling is most widely used. Despite its ease of use and interpretation, there may be time dependence...

Identifying the Factors That Influence Change in SEBD Using Logistic Regression Analysis

ERIC Educational Resources Information Center

Camilleri, Liberato; Cefai, Carmel

2013-01-01

Multiple linear regression and ANOVA models are widely used in applications since they provide effective statistical tools for assessing the relationship between a continuous dependent variable and several predictors. However these models rely heavily on linearity and normality assumptions and they do not accommodate categorical dependent…

User's manual for LINEAR, a FORTRAN program to derive linear aircraft models

NASA Technical Reports Server (NTRS)

Duke, Eugene L.; Patterson, Brian P.; Antoniewicz, Robert F.

1987-01-01

This report documents a FORTRAN program that provides a powerful and flexible tool for the linearization of aircraft models. The program LINEAR numerically determines a linear system model using nonlinear equations of motion and a user-supplied nonlinear aerodynamic model. The system model determined by LINEAR consists of matrices for both state and observation equations. The program has been designed to allow easy selection and definition of the state, control, and observation variables to be used in a particular model.

Predictive models reduce talent development costs in female gymnastics.

PubMed

Pion, Johan; Hohmann, Andreas; Liu, Tianbiao; Lenoir, Matthieu; Segers, Veerle

2017-04-01

This retrospective study focuses on the comparison of different predictive models based on the results of a talent identification test battery for female gymnasts. We studied to what extent these models have the potential to optimise selection procedures, and at the same time reduce talent development costs in female artistic gymnastics. The dropout rate of 243 female elite gymnasts was investigated, 5 years past talent selection, using linear (discriminant analysis) and non-linear predictive models (Kohonen feature maps and multilayer perceptron). The coaches classified 51.9% of the participants correct. Discriminant analysis improved the correct classification to 71.6% while the non-linear technique of Kohonen feature maps reached 73.7% correctness. Application of the multilayer perceptron even classified 79.8% of the gymnasts correctly. The combination of different predictive models for talent selection can avoid deselection of high-potential female gymnasts. The selection procedure based upon the different statistical analyses results in decrease of 33.3% of cost because the pool of selected athletes can be reduced to 92 instead of 138 gymnasts (as selected by the coaches). Reduction of the costs allows the limited resources to be fully invested in the high-potential athletes.

Extraction optimization and UHPLC method development for determination of the 20-hydroxyecdysone in Sida tuberculata leaves.

PubMed

da Rosa, Hemerson S; Koetz, Mariana; Santos, Marí Castro; Jandrey, Elisa Helena Farias; Folmer, Vanderlei; Henriques, Amélia Teresinha; Mendez, Andreas Sebastian Loureiro

2018-04-01

Sida tuberculata (ST) is a Malvaceae species widely distributed in Southern Brazil. In traditional medicine, ST has been employed as hypoglycemic, hypocholesterolemic, anti-inflammatory and antimicrobial. Additionally, this species is chemically characterized by flavonoids, alkaloids and phytoecdysteroids mainly. The present work aimed to optimize the extractive technique and to validate an UHPLC method for the determination of 20-hydroxyecdsone (20HE) in the ST leaves. Box-Behnken Design (BBD) was used in method optimization. The extractive methods tested were: static and dynamic maceration, ultrasound, ultra-turrax and reflux. In the Box-Behnken three parameters were evaluated in three levels (-1, 0, +1), particle size, time and plant:solvent ratio. In validation method, the parameters of selectivity, specificity, linearity, limits of detection and quantification (LOD, LOQ), precision, accuracy and robustness were evaluated. The results indicate static maceration as better technique to obtain 20HE peak area in ST extract. The optimal extraction from surface response methodology was achieved with the parameters granulometry of 710 nm, 9 days of maceration and plant:solvent ratio 1:54 (w/v). The UHPLC-PDA analytical developed method showed full viability of performance, proving to be selective, linear, precise, accurate and robust for 20HE detection in ST leaves. The average content of 20HE was 0.56% per dry extract. Thus, the optimization of extractive method in ST leaves increased the concentration of 20HE in crude extract, and a reliable method was successfully developed according to validation requirements and in agreement with current legislation. Copyright © 2018 Elsevier Inc. All rights reserved.

Statistical sex determination from craniometrics: Comparison of linear discriminant analysis, logistic regression, and support vector machines.

PubMed

Santos, Frédéric; Guyomarc'h, Pierre; Bruzek, Jaroslav

2014-12-01

Accuracy of identification tools in forensic anthropology primarily rely upon the variations inherent in the data upon which they are built. Sex determination methods based on craniometrics are widely used and known to be specific to several factors (e.g. sample distribution, population, age, secular trends, measurement technique, etc.). The goal of this study is to discuss the potential variations linked to the statistical treatment of the data. Traditional craniometrics of four samples extracted from documented osteological collections (from Portugal, France, the U.S.A., and Thailand) were used to test three different classification methods: linear discriminant analysis (LDA), logistic regression (LR), and support vector machines (SVM). The Portuguese sample was set as a training model on which the other samples were applied in order to assess the validity and reliability of the different models. The tests were performed using different parameters: some included the selection of the best predictors; some included a strict decision threshold (sex assessed only if the related posterior probability was high, including the notion of indeterminate result); and some used an unbalanced sex-ratio. Results indicated that LR tends to perform slightly better than the other techniques and offers a better selection of predictors. Also, the use of a decision threshold (i.e. p>0.95) is essential to ensure an acceptable reliability of sex determination methods based on craniometrics. Although the Portuguese, French, and American samples share a similar sexual dimorphism, application of Western models on the Thai sample (that displayed a lower degree of dimorphism) was unsuccessful. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Efficient 2-Nitrophenol Chemical Sensor Development Based on Ce2O3 Nanoparticles Decorated CNT Nanocomposites for Environmental Safety

PubMed Central

Hussain, Mohammad M.; Rahman, Mohammed M.; Asiri, Abdullah M.

2016-01-01

Ce2O3 nanoparticle decorated CNT nanocomposites (Ce2O3.CNT NCs) were prepared by a wet-chemical method in basic medium. The Ce2O3.CNT NCs were examined using FTIR, UV/Vis, Field-Emission Scanning Electron Microscopy (FESEM), X-ray electron dispersive spectroscopy (XEDS), X-ray photoelectron spectroscopy (XPS), and powder X-ray diffraction (XRD). A selective 2-nitrophenol (2-NP) sensor was developed by fabricating a thin-layer of NCs onto a flat glassy carbon electrode (GCE, surface area = 0.0316 cm2). Higher sensitivity including linear dynamic range (LDR), long-term stability, and enhanced electrochemical performances towards 2-NP were achieved by a reliable current-voltage (I-V) method. The calibration curve was found linear (R2 = 0.9030) over a wide range of 2-NP concentration (100 pM ~ 100.0 mM). Limit of detection (LOD) and sensor sensitivity were calculated based on noise to signal ratio (~3N/S) as 60 ± 0.02 pM and 1.6×10−3 μAμM-1cm-2 respectively. The Ce2O3.CNT NCs synthesized by a wet-chemical process is an excellent way of establishing nanomaterial decorated carbon materials for chemical sensor development in favor of detecting hazardous compounds in health-care and environmental fields at broad-scales. Finally, the efficiency of the proposed chemical sensors can be applied and utilized in effectively for the selective detection of toxic 2-NP component in environmental real samples with acceptable and reasonable results. PMID:27973600

Efficient 2-Nitrophenol Chemical Sensor Development Based on Ce2O3 Nanoparticles Decorated CNT Nanocomposites for Environmental Safety.

PubMed

Hussain, Mohammad M; Rahman, Mohammed M; Asiri, Abdullah M

2016-01-01

Ce2O3 nanoparticle decorated CNT nanocomposites (Ce2O3.CNT NCs) were prepared by a wet-chemical method in basic medium. The Ce2O3.CNT NCs were examined using FTIR, UV/Vis, Field-Emission Scanning Electron Microscopy (FESEM), X-ray electron dispersive spectroscopy (XEDS), X-ray photoelectron spectroscopy (XPS), and powder X-ray diffraction (XRD). A selective 2-nitrophenol (2-NP) sensor was developed by fabricating a thin-layer of NCs onto a flat glassy carbon electrode (GCE, surface area = 0.0316 cm2). Higher sensitivity including linear dynamic range (LDR), long-term stability, and enhanced electrochemical performances towards 2-NP were achieved by a reliable current-voltage (I-V) method. The calibration curve was found linear (R2 = 0.9030) over a wide range of 2-NP concentration (100 pM ~ 100.0 mM). Limit of detection (LOD) and sensor sensitivity were calculated based on noise to signal ratio (~3N/S) as 60 ± 0.02 pM and 1.6×10-3 μAμM-1cm-2 respectively. The Ce2O3.CNT NCs synthesized by a wet-chemical process is an excellent way of establishing nanomaterial decorated carbon materials for chemical sensor development in favor of detecting hazardous compounds in health-care and environmental fields at broad-scales. Finally, the efficiency of the proposed chemical sensors can be applied and utilized in effectively for the selective detection of toxic 2-NP component in environmental real samples with acceptable and reasonable results.

Size-selective QD@MOF core-shell nanocomposites for the highly sensitive monitoring of oxidase activities.

PubMed

Wang, Ke; Li, Nan; Zhang, Jing; Zhang, Zhiqi; Dang, Fuquan

2017-01-15

In this work, we proposed a novel and facile method to monitor oxidase activities based on size-selective fluorescent quantum dot (QD)@metal-organic framework (MOF) core-shell nanocomposites (CSNCPs). The CSNCPs were synthesized from ZIF-8 and CdTe QDs in aqueous solution in 40min at room temperature with stirring. The prepared CdTe@ZIF-8 CSNCPs , which have excellent water dispersibility and stability, displays distinct fluorescence responses to hole scavengers of different molecular sizes (e.g., H 2 O 2 , substrate, and oxidase) due to the aperture limitation of the ZIF-8 shell. H 2 O 2 can efficiently quench the fluorescence of CdTe@ZIF-8 CSNCPs over a linearity range of 1-100nM with a detection limit of 0.29nM, whereas large molecules such as substrate and oxidase have very little effect on its fluorescence. Therefore, the highly sensitive detection of oxidase activities was achieved by monitoring the fluorescence quenching of CdTe@ZIF-8 CSNCPs by H 2 O 2 produced in the presence of substrate and oxidase, which is proportional to the oxidase activities. The linearity ranges of the uricase and glucose oxidase activity are 0.1-50U/L and 1-100U/L, respectively, and their detection limits are 0.024U/L and 0.26U/L, respectively. Therefore, the current QD@MOF CSNCPs based sensing system is a promising, widely applicable means of monitoring oxidase activities in biochemical research. Copyright © 2016 Elsevier B.V. All rights reserved.

QSRR modeling for diverse drugs using different feature selection methods coupled with linear and nonlinear regressions.

PubMed

Goodarzi, Mohammad; Jensen, Richard; Vander Heyden, Yvan

2012-12-01

A Quantitative Structure-Retention Relationship (QSRR) is proposed to estimate the chromatographic retention of 83 diverse drugs on a Unisphere poly butadiene (PBD) column, using isocratic elutions at pH 11.7. Previous work has generated QSRR models for them using Classification And Regression Trees (CART). In this work, Ant Colony Optimization is used as a feature selection method to find the best molecular descriptors from a large pool. In addition, several other selection methods have been applied, such as Genetic Algorithms, Stepwise Regression and the Relief method, not only to evaluate Ant Colony Optimization as a feature selection method but also to investigate its ability to find the important descriptors in QSRR. Multiple Linear Regression (MLR) and Support Vector Machines (SVMs) were applied as linear and nonlinear regression methods, respectively, giving excellent correlation between the experimental, i.e. extrapolated to a mobile phase consisting of pure water, and predicted logarithms of the retention factors of the drugs (logk(w)). The overall best model was the SVM one built using descriptors selected by ACO. Copyright © 2012 Elsevier B.V. All rights reserved.

A next-generation marker genotyping platform (AmpSeq) in heterozygous crops: A case study for marker assisted selection in grapevine

USDA-ARS?s Scientific Manuscript database

Marker assisted selection (MAS) has become widely used in perennial crop breeding programs to accelerate and enhance cultivar development via selection during the juvenile phase and parental selection prior to crossing. Next generation sequencing (NGS) has been widely used for whole genome molecular...

Improving the CD linearity and proximity performance of photomasks written on the Sigma7500-II DUV laser writer through embedded OPC

NASA Astrophysics Data System (ADS)

Österberg, Anders; Ivansen, Lars; Beyerl, Angela; Newman, Tom; Bowhill, Amanda; Sahouria, Emile; Schulze, Steffen

2007-10-01

Optical proximity correction (OPC) is widely used in wafer lithography to produce a printed image that best matches the design intent while optimizing CD control. OPC software applies corrections to the mask pattern data, but in general it does not compensate for the mask writer and mask process characteristics. The Sigma7500-II deep-UV laser mask writer projects the image of a programmable spatial light modulator (SLM) using partially coherent optics similar to wafer steppers, and the optical proximity effects of the mask writer are in principle correctable with established OPC methods. To enhance mask patterning, an embedded OPC function, LinearityEqualize TM, has been developed for the Sigma7500- II that is transparent to the user and which does not degrade mask throughput. It employs a Calibre TM rule-based OPC engine from Mentor Graphics, selected for the computational speed necessary for mask run-time execution. A multinode cluster computer applies optimized table-based CD corrections to polygonized pattern data that is then fractured into an internal writer format for subsequent data processing. This embedded proximity correction flattens the linearity behavior for all linewidths and pitches, which targets to improve the CD uniformity on production photomasks. Printing results show that the CD linearity is reduced to below 5 nm for linewidths down to 200 nm, both for clear and dark and for isolated and dense features, and that sub-resolution assist features (SRAF) are reliably printed down to 120 nm. This reduction of proximity effects for main mask features and the extension of the practical resolution for SRAFs expands the application space of DUV laser mask writing.

A widefield fluorescence microscope with a linear image sensor for image cytometry of biospecimens: Considerations for image quality optimization

NASA Astrophysics Data System (ADS)

Hutcheson, Joshua A.; Majid, Aneeka A.; Powless, Amy J.; Muldoon, Timothy J.

2015-09-01

Linear image sensors have been widely used in numerous research and industry applications to provide continuous imaging of moving objects. Here, we present a widefield fluorescence microscope with a linear image sensor used to image translating objects for image cytometry. First, a calibration curve was characterized for a custom microfluidic chamber over a span of volumetric pump rates. Image data were also acquired using 15 μm fluorescent polystyrene spheres on a slide with a motorized translation stage in order to match linear translation speed with line exposure periods to preserve the image aspect ratio. Aspect ratios were then calculated after imaging to ensure quality control of image data. Fluorescent beads were imaged in suspension flowing through the microfluidics chamber being pumped by a mechanical syringe pump at 16 μl min-1 with a line exposure period of 150 μs. The line period was selected to acquire images of fluorescent beads with a 40 dB signal-to-background ratio. A motorized translation stage was then used to transport conventional glass slides of stained cellular biospecimens. Whole blood collected from healthy volunteers was stained with 0.02% (w/v) proflavine hemisulfate was imaged to highlight leukocyte morphology with a 1.56 mm × 1.28 mm field of view (1540 ms total acquisition time). Oral squamous cells were also collected from healthy volunteers and stained with 0.01% (w/v) proflavine hemisulfate to demonstrate quantifiable subcellular features and an average nuclear to cytoplasmic ratio of 0.03 (n = 75), with a resolution of 0.31 μm pixels-1.

Effect of Logarithmic and Linear Frequency Scales on Parametric Modelling of Tissue Dielectric Data.

PubMed

Salahuddin, Saqib; Porter, Emily; Meaney, Paul M; O'Halloran, Martin

2017-02-01

The dielectric properties of biological tissues have been studied widely over the past half-century. These properties are used in a vast array of applications, from determining the safety of wireless telecommunication devices to the design and optimisation of medical devices. The frequency-dependent dielectric properties are represented in closed-form parametric models, such as the Cole-Cole model, for use in numerical simulations which examine the interaction of electromagnetic (EM) fields with the human body. In general, the accuracy of EM simulations depends upon the accuracy of the tissue dielectric models. Typically, dielectric properties are measured using a linear frequency scale; however, use of the logarithmic scale has been suggested historically to be more biologically descriptive. Thus, the aim of this paper is to quantitatively compare the Cole-Cole fitting of broadband tissue dielectric measurements collected with both linear and logarithmic frequency scales. In this way, we can determine if appropriate choice of scale can minimise the fit error and thus reduce the overall error in simulations. Using a well-established fundamental statistical framework, the results of the fitting for both scales are quantified. It is found that commonly used performance metrics, such as the average fractional error, are unable to examine the effect of frequency scale on the fitting results due to the averaging effect that obscures large localised errors. This work demonstrates that the broadband fit for these tissues is quantitatively improved when the given data is measured with a logarithmic frequency scale rather than a linear scale, underscoring the importance of frequency scale selection in accurate wideband dielectric modelling of human tissues.

Effect of Logarithmic and Linear Frequency Scales on Parametric Modelling of Tissue Dielectric Data

PubMed Central

Salahuddin, Saqib; Porter, Emily; Meaney, Paul M.; O’Halloran, Martin

2016-01-01

The dielectric properties of biological tissues have been studied widely over the past half-century. These properties are used in a vast array of applications, from determining the safety of wireless telecommunication devices to the design and optimisation of medical devices. The frequency-dependent dielectric properties are represented in closed-form parametric models, such as the Cole-Cole model, for use in numerical simulations which examine the interaction of electromagnetic (EM) fields with the human body. In general, the accuracy of EM simulations depends upon the accuracy of the tissue dielectric models. Typically, dielectric properties are measured using a linear frequency scale; however, use of the logarithmic scale has been suggested historically to be more biologically descriptive. Thus, the aim of this paper is to quantitatively compare the Cole-Cole fitting of broadband tissue dielectric measurements collected with both linear and logarithmic frequency scales. In this way, we can determine if appropriate choice of scale can minimise the fit error and thus reduce the overall error in simulations. Using a well-established fundamental statistical framework, the results of the fitting for both scales are quantified. It is found that commonly used performance metrics, such as the average fractional error, are unable to examine the effect of frequency scale on the fitting results due to the averaging effect that obscures large localised errors. This work demonstrates that the broadband fit for these tissues is quantitatively improved when the given data is measured with a logarithmic frequency scale rather than a linear scale, underscoring the importance of frequency scale selection in accurate wideband dielectric modelling of human tissues. PMID:28191324

Developmental models for estimating ecological responses to environmental variability: structural, parametric, and experimental issues.

PubMed

Moore, Julia L; Remais, Justin V

2014-03-01

Developmental models that account for the metabolic effect of temperature variability on poikilotherms, such as degree-day models, have been widely used to study organism emergence, range and development, particularly in agricultural and vector-borne disease contexts. Though simple and easy to use, structural and parametric issues can influence the outputs of such models, often substantially. Because the underlying assumptions and limitations of these models have rarely been considered, this paper reviews the structural, parametric, and experimental issues that arise when using degree-day models, including the implications of particular structural or parametric choices, as well as assumptions that underlie commonly used models. Linear and non-linear developmental functions are compared, as are common methods used to incorporate temperature thresholds and calculate daily degree-days. Substantial differences in predicted emergence time arose when using linear versus non-linear developmental functions to model the emergence time in a model organism. The optimal method for calculating degree-days depends upon where key temperature threshold parameters fall relative to the daily minimum and maximum temperatures, as well as the shape of the daily temperature curve. No method is shown to be universally superior, though one commonly used method, the daily average method, consistently provides accurate results. The sensitivity of model projections to these methodological issues highlights the need to make structural and parametric selections based on a careful consideration of the specific biological response of the organism under study, and the specific temperature conditions of the geographic regions of interest. When degree-day model limitations are considered and model assumptions met, the models can be a powerful tool for studying temperature-dependent development.

A widefield fluorescence microscope with a linear image sensor for image cytometry of biospecimens: Considerations for image quality optimization

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

Hutcheson, Joshua A.; Majid, Aneeka A.; Powless, Amy J.

Linear image sensors have been widely used in numerous research and industry applications to provide continuous imaging of moving objects. Here, we present a widefield fluorescence microscope with a linear image sensor used to image translating objects for image cytometry. First, a calibration curve was characterized for a custom microfluidic chamber over a span of volumetric pump rates. Image data were also acquired using 15 μm fluorescent polystyrene spheres on a slide with a motorized translation stage in order to match linear translation speed with line exposure periods to preserve the image aspect ratio. Aspect ratios were then calculated aftermore » imaging to ensure quality control of image data. Fluorescent beads were imaged in suspension flowing through the microfluidics chamber being pumped by a mechanical syringe pump at 16 μl min{sup −1} with a line exposure period of 150 μs. The line period was selected to acquire images of fluorescent beads with a 40 dB signal-to-background ratio. A motorized translation stage was then used to transport conventional glass slides of stained cellular biospecimens. Whole blood collected from healthy volunteers was stained with 0.02% (w/v) proflavine hemisulfate was imaged to highlight leukocyte morphology with a 1.56 mm × 1.28 mm field of view (1540 ms total acquisition time). Oral squamous cells were also collected from healthy volunteers and stained with 0.01% (w/v) proflavine hemisulfate to demonstrate quantifiable subcellular features and an average nuclear to cytoplasmic ratio of 0.03 (n = 75), with a resolution of 0.31 μm pixels{sup −1}.« less

Direct and Absolute Quantification of over 1800 Yeast Proteins via Selected Reaction Monitoring*

PubMed Central

Lawless, Craig; Holman, Stephen W.; Brownridge, Philip; Lanthaler, Karin; Harman, Victoria M.; Watkins, Rachel; Hammond, Dean E.; Miller, Rebecca L.; Sims, Paul F. G.; Grant, Christopher M.; Eyers, Claire E.; Beynon, Robert J.

2016-01-01

Defining intracellular protein concentration is critical in molecular systems biology. Although strategies for determining relative protein changes are available, defining robust absolute values in copies per cell has proven significantly more challenging. Here we present a reference data set quantifying over 1800 Saccharomyces cerevisiae proteins by direct means using protein-specific stable-isotope labeled internal standards and selected reaction monitoring (SRM) mass spectrometry, far exceeding any previous study. This was achieved by careful design of over 100 QconCAT recombinant proteins as standards, defining 1167 proteins in terms of copies per cell and upper limits on a further 668, with robust CVs routinely less than 20%. The selected reaction monitoring-derived proteome is compared with existing quantitative data sets, highlighting the disparities between methodologies. Coupled with a quantification of the transcriptome by RNA-seq taken from the same cells, these data support revised estimates of several fundamental molecular parameters: a total protein count of ∼100 million molecules-per-cell, a median of ∼1000 proteins-per-transcript, and a linear model of protein translation explaining 70% of the variance in translation rate. This work contributes a “gold-standard” reference yeast proteome (including 532 values based on high quality, dual peptide quantification) that can be widely used in systems models and for other comparative studies. PMID:26750110

Simultaneous determination of eight major steroids from Polyporus umbellatus by high-performance liquid chromatography coupled with mass spectrometry detections.

PubMed

Zhao, Ying-yong; Cheng, Xian-long; Zhang, Yongmin; Zhao, Ye; Lin, Rui-chao; Sun, Wen-ji

2010-02-01

Polyporus umbellatus is a widely used diuretic herbal medicine. In this study, a high-performance liquid chromatography coupled with atmospheric pressure chemical ionization-mass spectrometric detection (HPLC-APCI-MS) method was developed for qualitative and quantitative analysis of steroids, as well as for the quality control of Polyporus umbellatus. The selectivity, reproducibility and sensitivity were compared with HPLC with photodiode array detection and evaporative light scattering detection (ELSD). Selective ion monitoring in positive mode was used for qualitative and quantitative analysis of eight major components and beta-ecdysterone was used as the internal standard. Limits of detection and quantification fell in the ranges 7-21 and 18-63 ng/mL for the eight analytes with an injection of 10 microL samples, and all calibration curves showed good linear regression (r(2) > 0.9919) within the test range. The quantitative results demonstrated that samples from different localities showed different qualities. Advantages, in comparison with conventional HPLC-diode array detection and HPLC-ELSD, are that reliable identification of target compounds could be achieved by accurate mass measurements along with characteristic retention time, and the great enhancement in selectivity and sensitivity allows identification and quantification of low levels of constituents in complex Polyporus umbellatus matrixes. (c) 2009 John Wiley & Sons, Ltd.

Improved selection criteria for H II regions, based on IRAS sources

NASA Astrophysics Data System (ADS)

Yan, Qing-Zeng; Xu, Ye; Walsh, A. J.; Macquart, J. P.; MacLeod, G. C.; Zhang, Bo; Hancock, P. J.; Chen, Xi; Tang, Zheng-Hong

2018-05-01

We present new criteria for selecting H II regions from the Infrared Astronomical Satellite (IRAS) Point Source Catalogue (PSC), based on an H II region catalogue derived manually from the all-sky Wide-field Infrared Survey Explorer (WISE). The criteria are used to augment the number of H II region candidates in the Milky Way. The criteria are defined by the linear decision boundary of two samples: IRAS point sources associated with known H II regions, which serve as the H II region sample, and IRAS point sources at high Galactic latitudes, which serve as the non-H II region sample. A machine learning classifier, specifically a support vector machine, is used to determine the decision boundary. We investigate all combinations of four IRAS bands and suggest that the optimal criterion is log(F_{60}/F_{12})≥ ( -0.19 × log(F_{100}/F_{25})+ 1.52), with detections at 60 and 100 {μ}m. This selects 3041 H II region candidates from the IRAS PSC. We find that IRAS H II region candidates show evidence of evolution on the two-colour diagram. Merging the WISE H II catalogue with IRAS H II region candidates, we estimate a lower limit of approximately 10 200 for the number of H II regions in the Milky Way.

Water-Soluble Nonconjugated Polymer Nanoparticles with Strong Fluorescence Emission for Selective and Sensitive Detection of Nitro-Explosive Picric Acid in Aqueous Medium.

PubMed

Liu, Shi Gang; Luo, Dan; Li, Na; Zhang, Wei; Lei, Jing Lei; Li, Nian Bing; Luo, Hong Qun

2016-08-24

Water-soluble nonconjugated polymer nanoparticles (PNPs) with strong fluorescence emission were prepared from hyperbranched poly(ethylenimine) (PEI) and d-glucose via Schiff base reaction and self-assembly in aqueous phase. Preparation of the PEI-d-glucose (PEI-G) PNPs was facile (one-pot reaction) and environmentally friendly under mild conditions. Also, PEI-G PNPs showed a high fluorescence quantum yield in aqueous solution, and the fluorescence properties (such as concentration- and solvent-dependent fluorescence) and origin of intrinsic fluorescence were investigated and discussed. PEI-G PNPs were then used to develop a fluorescent probe for fast, selective, and sensitive detection of nitro-explosive picric acid (PA) in aqueous medium, because the fluorescence can be easily quenched by PA whereas other nitro-explosives and structurally similar compounds only caused negligible quenching. A wide linear range (0.05-70 μM) and a low detection limit (26 nM) were obtained. The fluorescence quenching mechanism was carefully explored, and it was due to a combined effect of electron transfer, resonance energy transfer, and inner filter effect between PA and PEI-G PNPs, which resulted in good selectivity and sensitivity for PA. Finally, the developed sensor was successfully applied to detection of PA in environmental water samples.

Genetic Dissection of End-Use Quality Traits in Adapted Soft White Winter Wheat

PubMed Central

Jernigan, Kendra L.; Godoy, Jayfred V.; Huang, Meng; Zhou, Yao; Morris, Craig F.; Garland-Campbell, Kimberly A.; Zhang, Zhiwu; Carter, Arron H.

2018-01-01

Soft white wheat is used in domestic and foreign markets for various end products requiring specific quality profiles. Phenotyping for end-use quality traits can be costly, time-consuming and destructive in nature, so it is advantageous to use molecular markers to select experimental lines with superior traits. An association mapping panel of 469 soft white winter wheat cultivars and advanced generation breeding lines was developed from regional breeding programs in the U.S. Pacific Northwest. This panel was genotyped on a wheat-specific 90 K iSelect single nucleotide polymorphism (SNP) chip. A total of 15,229 high quality SNPs were selected and combined with best linear unbiased predictions (BLUPs) from historical phenotypic data of the genotypes in the panel. Genome-wide association mapping was conducted using the Fixed and random model Circulating Probability Unification (FarmCPU). A total of 105 significant marker-trait associations were detected across 19 chromosomes. Potentially new loci for total flour yield, lactic acid solvent retention capacity, flour sodium dodecyl sulfate sedimentation and flour swelling volume were also detected. Better understanding of the genetic factors impacting end-use quality enable breeders to more effectively discard poor quality germplasm and increase frequencies of favorable end-use quality alleles in their breeding populations. PMID:29593752

Engineering multiphoton states for linear optics computation

NASA Astrophysics Data System (ADS)

Aniello, P.; Lupo, C.; Napolitano, M.; Paris, M. G. A.

2007-03-01

Transformations achievable by linear optical components allow to generate the whole unitary group only when restricted to the one-photon subspace of a multimode Fock space. In this paper, we address the more general problem of encoding quantum information by multiphoton states, and elaborating it via ancillary extensions, linear optical passive devices and photodetection. Our scheme stems in a natural way from the mathematical structures underlying the physics of linear optical passive devices. In particular, we analyze an economical procedure for mapping a fiducial 2-photon 2-mode state into an arbitrary 2-photon 2-mode state using ancillary resources and linear optical passive N-ports assisted by post-selection. We found that adding a single ancilla mode is enough to generate any desired target state. The effect of imperfect photodetection in post-selection is considered and a simple trade-off between success probability and fidelity is derived.

New exact solutions of the Tzitzéica-type equations in non-linear optics using the expa function method

NASA Astrophysics Data System (ADS)

Hosseini, K.; Ayati, Z.; Ansari, R.

2018-04-01

One specific class of non-linear evolution equations, known as the Tzitzéica-type equations, has received great attention from a group of researchers involved in non-linear science. In this article, new exact solutions of the Tzitzéica-type equations arising in non-linear optics, including the Tzitzéica, Dodd-Bullough-Mikhailov and Tzitzéica-Dodd-Bullough equations, are obtained using the expa function method. The integration technique actually suggests a useful and reliable method to extract new exact solutions of a wide range of non-linear evolution equations.

Progress Report on the Improved Linear Ion Trap Physics Package

NASA Technical Reports Server (NTRS)

Prestage, John D.

1995-01-01

This article describes the first operational results from the extended linear ion trap frequency standard now being developed at JPL. This new design separates the state selection/interrogation region from the more critical microwave resonance region where the multiplied local oscillator (LO) signal is compared to the stable atomic transition. Hg+ ions have been trapped, shuttled back and forth between the resonance and state selection traps. In addition, microwave transitions between the Hg+ clock levels have been driven in the resonance trap and detected in the state selection trap.

A methodology for evaluation of parent-mutant competition using a generalized non-linear ecosystem model

Treesearch

Raymond L. Czaplewski

1973-01-01

A generalized, non-linear population dynamics model of an ecosystem is used to investigate the direction of selective pressures upon a mutant by studying the competition between parent and mutant populations. The model has the advantages of considering selection as operating on the phenotype, of retaining the interaction of the mutant population with the ecosystem as a...

Property-process relations in simulated clinical abrasive adjusting of dental ceramics.

PubMed

Yin, Ling

2012-12-01

This paper reports on property-process correlations in simulated clinical abrasive adjusting of a wide range of dental restorative ceramics using a dental handpiece and diamond burs. The seven materials studied included four mica-containing glass ceramics, a feldspathic porcelain, a glass-infiltrated alumina, and a yttria-stabilized tetragonal zirconia. The abrasive adjusting process was conducted under simulated clinical conditions using diamond burs and a clinical dental handpiece. An attempt was made to establish correlations between process characteristics in terms of removal rate, chipping damage, and surface finish and material mechanical properties of hardness, fracture toughness and Young's modulus. The results show that the removal rate is mainly a function of hardness, which decreases nonlinearly with hardness. No correlations were noted between the removal rates and the complex relations of hardness, Young's modulus and fracture toughness. Surface roughness was primarily a linear function of diamond grit size and was relatively independent of materials. Chipping damage in terms of the average chipping width decreased with fracture toughness except for glass-infiltrated alumina. It also had higher linear correlations with critical strain energy release rates (R²=0.66) and brittleness (R²=0.62) and a lower linear correlation with indices of brittleness (R²=0.32). Implications of these results can provide guidance for the microstructural design of dental ceramics, optimize performance, and guide the proper selection of technical parameters in clinical abrasive adjusting conducted by dental practitioners. Copyright © 2012 Elsevier Ltd. All rights reserved.

Observation of a system of linear loops formed by re-growing hairs on rat skin.

PubMed

Liu, Li-Yuan; Guo, Dong-Sheng; Xin, Xiu-Yu; Fang, Jin

2008-07-01

This paper details linear hair re-growth patterns observed in rats. Adult rats were shaved and observed. The first wave of hair re-growth did not distribute everywhere, but along specific craniocaudally-oriented lines. The hair-lines were 2-15 mm wide and ran from the head, through the torso to the limbs, and were symmetrical along the left and right sides of the body. The symmetric hair-lines from both sides of the body converged around the mouth, nose, and at the pubic region or ventral midline to form a system of hair-loop-lines (HLLs). The loops can be differentiated into four main patterns. The Dorsal Loop and the Lateral Dorsal Loop run along the dorsum and hindlimb. The Ventral Loop and Lateral Ventral Loop travel along the thorax, abdomen, and forelimb. These hair-lines coincide with our previously observed sympathetic-substance lines (SSLs) in the rat's skin. Histological observation indicates that rat hair follicles along the hair-lines were at anagen phase. The catecholamine histofluorescent check showed abundant sympathetic nerve fibers beneath the hair-lines. After the rats' hairs were dyed, and selected portions shaved, re-growth was only observed on the shaved portions, indicating that the linear hair growth closely correlated with the shaving. Lastly we examine the cause of the preferential re-growth and briefly discuss the purpose and physiological role of the HLL. (c) 2008 Wiley-Liss, Inc.

Design studies of the Ku-band, wide-band Gyro-TWT amplifier

NASA Astrophysics Data System (ADS)

Jung, Sang Wook; Lee, Han Seul; Jang, Kwong Ho; Choi, Jin Joo; Hong, Yong Jun; Shin, Jin Woo; So, Jun Ho; Won, Jong Hyo

2014-02-01

This paper reports a Ku-band, wide band Gyrotron-Traveling-wave-tube(Gyro-TWT) that is currently being developed at Kwangwoon University. The Gyro-TWT has a two stage linear tapered interaction circuit to obtain a wide operating bandwidth. The linearly-tapered interaction circuit and nonlinearly-tapered magnetic field gives the Gyro-TWT a wide operating bandwidth. The Gyro-TWT bandwidth is 23%. The 2d-Particle-in-cell(PIC) and MAGIC2d code simulation results are 17.3 dB and 24.34 kW, respectively for the maximum saturated output power. A double anode MIG was simulated with E-Gun code. The results were 0.7 for the transvers to the axial beam velocity ratio (=alpha) and a 2.3% axial velocity spread at 50 kV and 4 A. A magnetic field profile simulation was performed by using the Poisson code to obtain the grazing magnetic field of the entire interaction circuit with Poisson code.

Control for Population Structure and Relatedness for Binary Traits in Genetic Association Studies via Logistic Mixed Models

PubMed Central

Chen, Han; Wang, Chaolong; Conomos, Matthew P.; Stilp, Adrienne M.; Li, Zilin; Sofer, Tamar; Szpiro, Adam A.; Chen, Wei; Brehm, John M.; Celedón, Juan C.; Redline, Susan; Papanicolaou, George J.; Thornton, Timothy A.; Laurie, Cathy C.; Rice, Kenneth; Lin, Xihong

2016-01-01

Linear mixed models (LMMs) are widely used in genome-wide association studies (GWASs) to account for population structure and relatedness, for both continuous and binary traits. Motivated by the failure of LMMs to control type I errors in a GWAS of asthma, a binary trait, we show that LMMs are generally inappropriate for analyzing binary traits when population stratification leads to violation of the LMM’s constant-residual variance assumption. To overcome this problem, we develop a computationally efficient logistic mixed model approach for genome-wide analysis of binary traits, the generalized linear mixed model association test (GMMAT). This approach fits a logistic mixed model once per GWAS and performs score tests under the null hypothesis of no association between a binary trait and individual genetic variants. We show in simulation studies and real data analysis that GMMAT effectively controls for population structure and relatedness when analyzing binary traits in a wide variety of study designs. PMID:27018471

The design of delay-dependent wide-area DOFC with prescribed degree of stability α for damping inter-area low-frequency oscillations in power system.

PubMed

Sun, Miaoping; Nian, Xiaohong; Dai, Liqiong; Guo, Hua

2017-05-01

In this paper, the delay-dependent wide-area dynamic output feedback controller (DOFC) with prescribed degree of stability is proposed for interconnected power system to damp inter-area low-frequency oscillations. Here, the prescribed degree of stability α is used to maintain all the poles on the left of s=-α in the s-plane. Firstly, residue approach is adopted to select input-output control signals and the schur balanced truncation model reduction method is utilized to obtain the reduced power system model. Secondly, based on Lyapunov stability theory and transformation operation in complex plane, the sufficient condition of asymptotic stability for closed-loop power system with prescribed degree of stability α is derived. Then, a novel method based on linear matrix inequalities (LMIs) is presented to obtain the parameters of DOFC and calculate delay margin of the closed-loop system considering the prescribed degree of stability α. Finally, case studies are carried out on the two-area four-machine system, which is controlled by classical wide-area power system stabilizer (WAPSS) in reported reference and our proposed DOFC respectively. The effectiveness and advantages of the proposed method are verified by the simulation results under different operating conditions. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Genome-Wide Prediction of the Performance of Three-Way Hybrids in Barley.

PubMed

Li, Zuo; Philipp, Norman; Spiller, Monika; Stiewe, Gunther; Reif, Jochen C; Zhao, Yusheng

2017-03-01

Predicting the grain yield performance of three-way hybrids is challenging. Three-way crosses are relevant for hybrid breeding in barley ( L.) and maize ( L.) adapted to East Africa. The main goal of our study was to implement and evaluate genome-wide prediction approaches of the performance of three-way hybrids using data of single-cross hybrids for a scenario in which parental lines of the three-way hybrids originate from three genetically distinct subpopulations. We extended the ridge regression best linear unbiased prediction (RRBLUP) and devised a genomic selection model allowing for subpopulation-specific marker effects (GSA-RRBLUP: general and subpopulation-specific additive RRBLUP). Using an empirical barley data set, we showed that applying GSA-RRBLUP tripled the prediction ability of three-way hybrids from 0.095 to 0.308 compared with RRBLUP, modeling one additive effect for all three subpopulations. The experimental findings were further substantiated with computer simulations. Our results emphasize the potential of GSA-RRBLUP to improve genome-wide hybrid prediction of three-way hybrids for scenarios of genetically diverse parental populations. Because of the advantages of the GSA-RRBLUP model in dealing with hybrids from different parental populations, it may also be a promising approach to boost the prediction ability for hybrid breeding programs based on genetically diverse heterotic groups. Copyright © 2017 Crop Science Society of America.

Simultaneous determination of centchroman and tamoxifen along with their metabolites in rat plasma using LC-MS/MS.

PubMed

Rama Raju, Kanumuri Siva; Taneja, Isha; Singh, Sheelendra Pratap; Tripathi, Amit; Mishra, Durga Prasad; Hussain, K Mahaboob; Gayen, Jiaur Rahman; Singh, Shio Kumar; Wahajuddin, Muhammad

2015-01-01

Tamoxifen and centchroman are two non-steroidal, selective estrogen receptors modulators, intended for long term therapy in the woman. Because of their wide spread use, there is a possibility of co-prescription of these agents. We studied the probable pharmacokinetic interaction between these agents in breast cancer model rats. A simple, sensitive and rapid LC-ESI-MS/MS method was developed and validated for the simultaneous determination of tamoxifen, centchroman and their active metabolites. The method was linear over a range of 0.2-200 ng/ml. All validation parameters met the acceptance criteria according to regulatory guidelines. LC-MS/MS method for determination of tamoxifen, centchroman and their metabolites was developed and validated. Results show the potential of drug-drug interaction upon co-administration these two marketed drugs.

Multi-linear model set design based on the nonlinearity measure and H-gap metric.

PubMed

Shaghaghi, Davood; Fatehi, Alireza; Khaki-Sedigh, Ali

2017-05-01

This paper proposes a model bank selection method for a large class of nonlinear systems with wide operating ranges. In particular, nonlinearity measure and H-gap metric are used to provide an effective algorithm to design a model bank for the system. Then, the proposed model bank is accompanied with model predictive controllers to design a high performance advanced process controller. The advantage of this method is the reduction of excessive switch between models and also decrement of the computational complexity in the controller bank that can lead to performance improvement of the control system. The effectiveness of the method is verified by simulations as well as experimental studies on a pH neutralization laboratory apparatus which confirms the efficiency of the proposed algorithm. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

All-Fiber Configuration Laser Self-Mixing Doppler Velocimeter Based on Distributed Feedback Fiber Laser.

PubMed

Wu, Shuang; Wang, Dehui; Xiang, Rong; Zhou, Junfeng; Ma, Yangcheng; Gui, Huaqiao; Liu, Jianguo; Wang, Huanqin; Lu, Liang; Yu, Benli

2016-07-27

In this paper, a novel velocimeter based on laser self-mixing Doppler technology has been developed for speed measurement. The laser employed in our experiment is a distributed feedback (DFB) fiber laser, which is an all-fiber structure using only one Fiber Bragg Grating to realize optical feedback and wavelength selection. Self-mixing interference for optical velocity sensing is experimentally investigated in this novel system, and the experimental results show that the Doppler frequency is linearly proportional to the velocity of a moving target, which agrees with the theoretical analysis commendably. In our experimental system, the velocity measurement can be achieved in the range of 3.58 mm/s-2216 mm/s with a relative error under one percent, demonstrating that our novel all-fiber configuration velocimeter can implement wide-range velocity measurements with high accuracy.

Marker optimization for facial motion acquisition and deformation.

PubMed

Le, Binh H; Zhu, Mingyang; Deng, Zhigang

2013-11-01

A long-standing problem in marker-based facial motion capture is what are the optimal facial mocap marker layouts. Despite its wide range of potential applications, this problem has not yet been systematically explored to date. This paper describes an approach to compute optimized marker layouts for facial motion acquisition as optimization of characteristic control points from a set of high-resolution, ground-truth facial mesh sequences. Specifically, the thin-shell linear deformation model is imposed onto the example pose reconstruction process via optional hard constraints such as symmetry and multiresolution constraints. Through our experiments and comparisons, we validate the effectiveness, robustness, and accuracy of our approach. Besides guiding minimal yet effective placement of facial mocap markers, we also describe and demonstrate its two selected applications: marker-based facial mesh skinning and multiresolution facial performance capture.

Nondestructive hydrogen analysis of steam-oxidized Zircaloy-4 by wide-angle neutron scattering

NASA Astrophysics Data System (ADS)

Yan, Yong; Qian, Shuo; Garrison, Ben; Smith, Tyler; Kim, Peter

2018-04-01

A nondestructive neutron scattering method to precisely measure the hydrogen content in high-temperature steam-oxidized Zircaloy-4 cladding was developed. Zircaloy-4 cladding was used to produce hydrided specimens with hydrogen content up to ≈500 wppm. Following hydrogen charging, the hydrogen content of the hydrided specimens was measured using the vacuum hot extraction method, by which the samples with desired hydrogen concentrations were selected for the neutron study. The hydrided samples were then oxidized in steam up to ≈6.0 wt. % at 1100 °C. Optical microscopy shows that our hydriding procedure results in uniform distribution of circumferential hydrides across the wall thickness, and uniform oxide layers were formed on the sample surfaces by the steam oxidation. Small- and wide-angle neutron scattering were simultaneously performed to provide a quick (less than an hour per sample) measurement of the hydrogen content in various types of hydrided and oxidized Zircaloy-4. Our study demonstrates that the hydrogen in pre-oxidized Zircaloy-4 cladding can be measured very accurately by both small- and wide-angle neutron scattering. For steam-oxidized samples, the small-angle neutron scattering is contaminated with coherent scattering from additional structural features induced by the steam oxidation. However, the scattering intensity of the wide-angle neutron scattering increases proportionally with the hydrogen charged in the samples. The hydrogen content and wide-angle neutron scattering intensity are highly linearly correlated for the oxidized cladding samples examined in this work, and can be used to precisely determine the hydrogen content in steam-oxidized Zircaloy-4 samples. Hydrogen contents determined by neutron scattering of oxidation samples were also found to be consistent with the results of chemical analysis within acceptable margins for error.

Nondestructive hydrogen analysis of steam-oxidized Zircaloy-4 by wide-angle neutron scattering

DOE PAGES

Yan, Yong; Qian, Shuo; Garrison, Ben; ...

2018-04-15

In this study, a nondestructive neutron scattering method to precisely measure the hydrogen content in high-temperature steam-oxidized Zircaloy-4 cladding was developed. Zircaloy-4 cladding was used to produce hydrided specimens with hydrogen content up to ≈500 wppm. Following hydrogen charging, the hydrogen content of the hydrided specimens was measured using the vacuum hot extraction method, by which the samples with desired hydrogen concentrations were selected for the neutron study. The hydrided samples were then oxidized in steam up to ≈6.0wt. % at 1100°C. Optical microscopy shows that our hydriding procedure results in uniform distribution of circumferential hydrides across the wall thickness,more » and uniform oxide layers were formed on the sample surfaces by the steam oxidation. Small- and wide-angle neutron scattering were simultaneously performed to provide a quick (less than an hour per sample) measurement of the hydrogen content in various types of hydrided and oxidized Zircaloy-4. Our study demonstrates that the hydrogen in pre-oxidized Zircaloy-4 cladding can be measured very accurately by both small- and wide-angle neutron scattering. For steam-oxidized samples, the small-angle neutron scattering is contaminated with coherent scattering from additional structural features induced by the steam oxidation. However, the scattering intensity of the wide-angle neutron scattering increases proportionally with the hydrogen charged in the samples. The hydrogen content and wide-angle neutron scattering intensity are highly linearly correlated for the oxidized cladding samples examined in this work, and can be used to precisely determine the hydrogen content in steam-oxidized Zircaloy-4 samples. Hydrogen contents determined by neutron scattering of oxidation samples were also found to be consistent with the results of chemical analysis within acceptable margins for error.« less

Nondestructive hydrogen analysis of steam-oxidized Zircaloy-4 by wide-angle neutron scattering

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

Yan, Yong; Qian, Shuo; Garrison, Ben

In this study, a nondestructive neutron scattering method to precisely measure the hydrogen content in high-temperature steam-oxidized Zircaloy-4 cladding was developed. Zircaloy-4 cladding was used to produce hydrided specimens with hydrogen content up to ≈500 wppm. Following hydrogen charging, the hydrogen content of the hydrided specimens was measured using the vacuum hot extraction method, by which the samples with desired hydrogen concentrations were selected for the neutron study. The hydrided samples were then oxidized in steam up to ≈6.0wt. % at 1100°C. Optical microscopy shows that our hydriding procedure results in uniform distribution of circumferential hydrides across the wall thickness,more » and uniform oxide layers were formed on the sample surfaces by the steam oxidation. Small- and wide-angle neutron scattering were simultaneously performed to provide a quick (less than an hour per sample) measurement of the hydrogen content in various types of hydrided and oxidized Zircaloy-4. Our study demonstrates that the hydrogen in pre-oxidized Zircaloy-4 cladding can be measured very accurately by both small- and wide-angle neutron scattering. For steam-oxidized samples, the small-angle neutron scattering is contaminated with coherent scattering from additional structural features induced by the steam oxidation. However, the scattering intensity of the wide-angle neutron scattering increases proportionally with the hydrogen charged in the samples. The hydrogen content and wide-angle neutron scattering intensity are highly linearly correlated for the oxidized cladding samples examined in this work, and can be used to precisely determine the hydrogen content in steam-oxidized Zircaloy-4 samples. Hydrogen contents determined by neutron scattering of oxidation samples were also found to be consistent with the results of chemical analysis within acceptable margins for error.« less

Multiscale Hierarchical Design of a Flexible Piezoresistive Pressure Sensor with High Sensitivity and Wide Linearity Range.

PubMed

Shi, Jidong; Wang, Liu; Dai, Zhaohe; Zhao, Lingyu; Du, Mingde; Li, Hongbian; Fang, Ying

2018-05-30

Flexible piezoresistive pressure sensors have been attracting wide attention for applications in health monitoring and human-machine interfaces because of their simple device structure and easy-readout signals. For practical applications, flexible pressure sensors with both high sensitivity and wide linearity range are highly desirable. Herein, a simple and low-cost method for the fabrication of a flexible piezoresistive pressure sensor with a hierarchical structure over large areas is presented. The piezoresistive pressure sensor consists of arrays of microscale papillae with nanoscale roughness produced by replicating the lotus leaf's surface and spray-coating of graphene ink. Finite element analysis (FEA) shows that the hierarchical structure governs the deformation behavior and pressure distribution at the contact interface, leading to a quick and steady increase in contact area with loads. As a result, the piezoresistive pressure sensor demonstrates a high sensitivity of 1.2 kPa -1 and a wide linearity range from 0 to 25 kPa. The flexible pressure sensor is applied for sensitive monitoring of small vibrations, including wrist pulse and acoustic waves. Moreover, a piezoresistive pressure sensor array is fabricated for mapping the spatial distribution of pressure. These results highlight the potential applications of the flexible piezoresistive pressure sensor for health monitoring and electronic skin. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Construction of multiple linear regression models using blood biomarkers for selecting against abdominal fat traits in broilers.

PubMed

Dong, J Q; Zhang, X Y; Wang, S Z; Jiang, X F; Zhang, K; Ma, G W; Wu, M Q; Li, H; Zhang, H

2018-01-01

Plasma very low-density lipoprotein (VLDL) can be used to select for low body fat or abdominal fat (AF) in broilers, but its correlation with AF is limited. We investigated whether any other biochemical indicator can be used in combination with VLDL for a better selective effect. Nineteen plasma biochemical indicators were measured in male chickens from the Northeast Agricultural University broiler lines divergently selected for AF content (NEAUHLF) in the fed state at 46 and 48 d of age. The average concentration of every parameter for the 2 d was used for statistical analysis. Levels of these 19 plasma biochemical parameters were compared between the lean and fat lines. The phenotypic correlations between these plasma biochemical indicators and AF traits were analyzed. Then, multiple linear regression models were constructed to select the best model used for selecting against AF content. and the heritabilities of plasma indicators contained in the best models were estimated. The results showed that 11 plasma biochemical indicators (triglycerides, total bile acid, total protein, globulin, albumin/globulin, aspartate transaminase, alanine transaminase, gamma-glutamyl transpeptidase, uric acid, creatinine, and VLDL) differed significantly between the lean and fat lines (P < 0.01), and correlated significantly with AF traits (P < 0.05). The best multiple linear regression models based on albumin/globulin, VLDL, triglycerides, globulin, total bile acid, and uric acid, had higher R2 (0.73) than the model based only on VLDL (0.21). The plasma parameters included in the best models had moderate heritability estimates (0.21 ≤ h2 ≤ 0.43). These results indicate that these multiple linear regression models can be used to select for lean broiler chickens. © 2017 Poultry Science Association Inc.

Variable selection in near-infrared spectroscopy: benchmarking of feature selection methods on biodiesel data.

PubMed

Balabin, Roman M; Smirnov, Sergey V

2011-04-29

During the past several years, near-infrared (near-IR/NIR) spectroscopy has increasingly been adopted as an analytical tool in various fields from petroleum to biomedical sectors. The NIR spectrum (above 4000 cm(-1)) of a sample is typically measured by modern instruments at a few hundred of wavelengths. Recently, considerable effort has been directed towards developing procedures to identify variables (wavelengths) that contribute useful information. Variable selection (VS) or feature selection, also called frequency selection or wavelength selection, is a critical step in data analysis for vibrational spectroscopy (infrared, Raman, or NIRS). In this paper, we compare the performance of 16 different feature selection methods for the prediction of properties of biodiesel fuel, including density, viscosity, methanol content, and water concentration. The feature selection algorithms tested include stepwise multiple linear regression (MLR-step), interval partial least squares regression (iPLS), backward iPLS (BiPLS), forward iPLS (FiPLS), moving window partial least squares regression (MWPLS), (modified) changeable size moving window partial least squares (CSMWPLS/MCSMWPLSR), searching combination moving window partial least squares (SCMWPLS), successive projections algorithm (SPA), uninformative variable elimination (UVE, including UVE-SPA), simulated annealing (SA), back-propagation artificial neural networks (BP-ANN), Kohonen artificial neural network (K-ANN), and genetic algorithms (GAs, including GA-iPLS). Two linear techniques for calibration model building, namely multiple linear regression (MLR) and partial least squares regression/projection to latent structures (PLS/PLSR), are used for the evaluation of biofuel properties. A comparison with a non-linear calibration model, artificial neural networks (ANN-MLP), is also provided. Discussion of gasoline, ethanol-gasoline (bioethanol), and diesel fuel data is presented. The results of other spectroscopic techniques application, such as Raman, ultraviolet-visible (UV-vis), or nuclear magnetic resonance (NMR) spectroscopies, can be greatly improved by an appropriate feature selection choice. Copyright © 2011 Elsevier B.V. All rights reserved.

A 400 KHz line rate 2048 pixel modular SWIR linear array for earth observation applications

NASA Astrophysics Data System (ADS)

Anchlia, Ankur; Vinella, Rosa M.; Wouters, Kristof; Gielen, Daphne; Hooylaerts, Peter; Deroo, Pieter; Ruythooren, Wouter; van der Zanden, Koen; Vermeiren, Jan; Merken, Patrick

2015-10-01

In this paper, we report about a family of linear imaging FPAs sensitive in the [0.9 - 1.7um] band, developed for high speed applications such as LIDAR, wavelength references and OCT analyzers and also for earth observation applications. Fast linear FPAs can also be used in a wide variety of terrestrial applications, including high speed sorting, electro- and photo-luminesce and medical applications. The arrays are based on a modular ROIC design concept: modules of 512 pixels are stitched during fabrication to achieve 512, 1024 and 2048 pixel arrays. In principle, this concept can be extended to any multiple of 512 pixels, the limiting factor being the pixel yield of long InGaAs arrays and the CTE differences in the hybrid setup. Each 512-pixel module has its own on-chip digital sequencer, analog readout chain and 4 output buffers. This modular concept enables a long-linear array to run at a high line rate of 400 KHz irrespective of the array length, which limits the line rate in a traditional linear array. The pixel has a pitch of 12.5um. The detector frontend is based on CTIA (Capacitor Trans-impedance Amplifier), having 5 selectable integration capacitors giving full well from 62x103e- (gain0) to 40x106e- (gain4). An auto-zero circuit limits the detector bias non-uniformity to 5-10mV across broad intensity levels, limiting the input referred dark signal noise to 20e-rms for Tint=3ms at room temperature. An on-chip CDS that follows the CTIA facilitates removal of Reset/KTC noise, CTIA offsets and most of the 1/f noise. The measured noise of the ROIC is 35e-rms in gain0. At a master clock rate of 60MHz and a minimum integration time of 1.4us, the FPAs reach the highest line rate of 400 KHz.

Large-scale linear rankSVM.

PubMed

Lee, Ching-Pei; Lin, Chih-Jen

2014-04-01

Linear rankSVM is one of the widely used methods for learning to rank. Although its performance may be inferior to nonlinear methods such as kernel rankSVM and gradient boosting decision trees, linear rankSVM is useful to quickly produce a baseline model. Furthermore, following its recent development for classification, linear rankSVM may give competitive performance for large and sparse data. A great deal of works have studied linear rankSVM. The focus is on the computational efficiency when the number of preference pairs is large. In this letter, we systematically study existing works, discuss their advantages and disadvantages, and propose an efficient algorithm. We discuss different implementation issues and extensions with detailed experiments. Finally, we develop a robust linear rankSVM tool for public use.

Isotherm investigation for the sorption of fluoride onto Bio-F: comparison of linear and non-linear regression method

NASA Astrophysics Data System (ADS)

Yadav, Manish; Singh, Nitin Kumar

2017-12-01

A comparison of the linear and non-linear regression method in selecting the optimum isotherm among three most commonly used adsorption isotherms (Langmuir, Freundlich, and Redlich-Peterson) was made to the experimental data of fluoride (F) sorption onto Bio-F at a solution temperature of 30 ± 1 °C. The coefficient of correlation (r2) was used to select the best theoretical isotherm among the investigated ones. A total of four Langmuir linear equations were discussed and out of which linear form of most popular Langmuir-1 and Langmuir-2 showed the higher coefficient of determination (0.976 and 0.989) as compared to other Langmuir linear equations. Freundlich and Redlich-Peterson isotherms showed a better fit to the experimental data in linear least-square method, while in non-linear method Redlich-Peterson isotherm equations showed the best fit to the tested data set. The present study showed that the non-linear method could be a better way to obtain the isotherm parameters and represent the most suitable isotherm. Redlich-Peterson isotherm was found to be the best representative (r2 = 0.999) for this sorption system. It is also observed that the values of β are not close to unity, which means the isotherms are approaching the Freundlich but not the Langmuir isotherm.

Galerkin finite difference Laplacian operators on isolated unstructured triangular meshes by linear combinations

NASA Technical Reports Server (NTRS)

Baumeister, Kenneth J.

1990-01-01

The Galerkin weighted residual technique using linear triangular weight functions is employed to develop finite difference formulae in Cartesian coordinates for the Laplacian operator on isolated unstructured triangular grids. The weighted residual coefficients associated with the weak formulation of the Laplacian operator along with linear combinations of the residual equations are used to develop the algorithm. The algorithm was tested for a wide variety of unstructured meshes and found to give satisfactory results.

Modelling and Inverse-Modelling: Experiences with O.D.E. Linear Systems in Engineering Courses

ERIC Educational Resources Information Center

Martinez-Luaces, Victor

2009-01-01

In engineering careers courses, differential equations are widely used to solve problems concerned with modelling. In particular, ordinary differential equations (O.D.E.) linear systems appear regularly in Chemical Engineering, Food Technology Engineering and Environmental Engineering courses, due to the usefulness in modelling chemical kinetics,…

Avoiding Boundary Estimates in Hierarchical Linear Models through Weakly Informative Priors

ERIC Educational Resources Information Center

Chung, Yeojin; Rabe-Hesketh, Sophia; Gelman, Andrew; Dorie, Vincent; Liu, Jinchen

2012-01-01

Hierarchical or multilevel linear models are widely used for longitudinal or cross-sectional data on students nested in classes and schools, and are particularly important for estimating treatment effects in cluster-randomized trials, multi-site trials, and meta-analyses. The models can allow for variation in treatment effects, as well as…

On decentralized estimation. [for large linear systems

NASA Technical Reports Server (NTRS)

Siljak, D. D.; Vukcevic, M. B.

1978-01-01

A multilevel scheme is proposed to construct decentralized estimators for large linear systems. The scheme is numerically attractive since only observability tests of low-order subsystems are required. Equally important is the fact that the constructed estimators are reliable under structural perturbations and can tolerate a wide range of nonlinearities in coupling among the subsystems.

The Influence of Playing Experience and Position on Injury Risk in NCAA Division I College Football Players.

PubMed

McCunn, Robert; Fullagar, Hugh H K; Williams, Sean; Halseth, Travis J; Sampson, John A; Murray, Andrew

2017-11-01

American football is widely played by college student-athletes throughout the United States; however, the associated injury risk is greater than in other team sports. Numerous factors likely contribute to this risk, yet research identifying these risk factors is limited. The present study sought to explore the relationship between playing experience and position on injury risk in NCAA Division I college football players. Seventy-six male college student-athletes in the football program of an American NCAA Division I university participated. Injuries were recorded over 2 consecutive seasons. Players were characterized based on college year (freshman, sophomore, junior, or senior) and playing position. The effect of playing experience and position on injury incidence rates was analyzed using a generalized linear mixed-effects model, with a Poisson distribution, log-linear link function, and offset for hours of training exposure or number of in-game plays (for training and game injuries, respectively). The overall rates of non-time-loss and time-loss game-related injuries were 2.1 (90% CI: 1.8-2.5) and 0.6 (90% CI: 0.4-0.8) per 1000 plays, respectively. The overall rates of non-time-loss and time-loss training-related injuries were 26.0 (90% CI: 22.6-29.9) and 7.1 (90% CI: 5.9-8.5) per 1000 h, respectively. During training, seniors and running backs displayed the greatest risk. During games, sophomores, juniors, and wide receivers were at greatest risk. Being aware of the elevated injury risk experienced by certain player groups may help coaches make considered decisions related to training design and player selection.

Linear Ion Trap for the Mars Organic Molecule Analyzer

NASA Astrophysics Data System (ADS)

Brinckerhoff, William; Arevalo, Ricardo; Danell, Ryan; van Amerom, Friso; Pinnick, Veronica; Li, Xiang; Hovmand, Lars; Getty, Stephanie; Mahaffy, Paul; Goesmann, Fred; Steininger, Harald

2014-05-01

The 2018 ExoMars rover mission includes the Mars Organic Molecule Analyzer (MOMA) investigation. MOMA will examine the chemical composition of samples acquired from depths of up to two meters below the martian surface, where organics may be protected from radiative and oxidative degradation. When combined with the complement of instruments in the rover's Pasteur Payload, MOMA has the potential to reveal the presence of a wide range of organics preserved in a variety of mineralogical environments, and to begin to understand the structural character and potential origin of those compounds. MOMA includes a linear, or 2D, ion trap mass spectrometer (ITMS) that is designed to analyze molecular composition of (i) gas evolved from pyrolyzed powder samples and separated on a gas chromatograph and (ii) ions directly desorbed from solid samples at Mars ambient pressure using a pulsed laser and a fast-valve capillary ion inlet system. This "dual source" approach gives MOMA unprecedented breadth of detection over a wide range of molecular weights and volatilities. Analysis of nonvolatile, higher-molecular weight organics such as carboxylic acids and peptides even in the presence of significant perchlorate concentrations is enabled by the extremely short (~1 ns) pulses of the desorption laser. Use of the ion trap's tandem mass spectrometry mode permits selective focus on key species for isolation and controlled fragmentation, providing structural analysis capabilities. The flight-like engineering test unit (ETU) of the ITMS, now under construction, will be used to verify breadboard performance with high fidelity, while simultaneously supporting the development of analytical scripts and spectral libraries using synthetic and natural Mars analog samples guided by current results from MSL. ETU campaign data will strongly advise the specifics of the calibration applied to the MOMA flight model as well as the science operational procedures during the mission.

Precision linear ramp function generator

DOEpatents

Jatko, W.B.; McNeilly, D.R.; Thacker, L.H.

1984-08-01

A ramp function generator is provided which produces a precise linear ramp function which is repeatable and highly stable. A derivative feedback loop is used to stabilize the output of an integrator in the forward loop and control the ramp rate. The ramp may be started from a selected baseline voltage level and the desired ramp rate is selected by applying an appropriate constant voltage to the input of the integrator.

Precision linear ramp function generator

DOEpatents

Jatko, W. Bruce; McNeilly, David R.; Thacker, Louis H.

1986-01-01

A ramp function generator is provided which produces a precise linear ramp unction which is repeatable and highly stable. A derivative feedback loop is used to stabilize the output of an integrator in the forward loop and control the ramp rate. The ramp may be started from a selected baseline voltage level and the desired ramp rate is selected by applying an appropriate constant voltage to the input of the integrator.

The feasibility of using methylene blue sensitized polyvinylalcohol film as a linear polarizer

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

Jyothilakshmi, K.; Anju, K. S.; Arathy, K.

2014-01-28

Linear light polarizing films selectively transmit radiations vibrating along an electromagnetic radiation vector and selectively absorb radiations vibrating along a second electromagnetic radiation vector. It happens according to the anisotropy of the film . In the present study the polarization effects of methylene blue sensitized polyvinyl alcohol is investigated. The polarization effects on the dye concentration, heating and stretching of film also are evaluated.

Novel Catalyst for the Chirality Selective Synthesis of Single Walled Carbon Nanotubes

DTIC Science & Technology

2015-05-12

hierarchical structures comprising nitrogen- doped reduced GO (rGO) and acid- oxidized SWCNTs was produced using a linear hydrothermal microreactor. Fiber...structures comprising nitrogen- doped reduced GO (rGO) and acidoxidized SWCNTs was produced using a linear hydrothermal microreactor. Fiber micro... doped into Co/SiO2 catalysts to change their chirality selectivity. Further, enrichment of (9,8) nanotubes was carried out by extraction using fluorene

Computing Linear Mathematical Models Of Aircraft

NASA Technical Reports Server (NTRS)

Duke, Eugene L.; Antoniewicz, Robert F.; Krambeer, Keith D.

1991-01-01

Derivation and Definition of Linear Aircraft Model (LINEAR) computer program provides user with powerful, and flexible, standard, documented, and verified software tool for linearization of mathematical models of aerodynamics of aircraft. Intended for use in software tool to drive linear analysis of stability and design of control laws for aircraft. Capable of both extracting such linearized engine effects as net thrust, torque, and gyroscopic effects, and including these effects in linear model of system. Designed to provide easy selection of state, control, and observation variables used in particular model. Also provides flexibility of allowing alternate formulations of both state and observation equations. Written in FORTRAN.

Highly linear dual ring resonator modulator for wide bandwidth microwave photonic links.

PubMed

Hosseinzadeh, Arash; Middlebrook, Christopher T

2016-11-28

A highly linear dual ring resonator modulator (DRRM) design is demonstrated to provide high spur-free dynamic range (SFDR) in a wide operational bandwidth. Harmonic and intermodulation distortions are theoretically analyzed in a single ring resonator modulator (RRM) with Lorentzian-shape transfer function and a strategy is proposed to enhance modulator linearity for wide bandwidth applications by utilizing DRRM. Third order intermodulation distortion is suppressed in a frequency independent process with proper splitting ratio of optical and RF power and proper dc biasing of the ring resonators. Operational bandwidth limits of the DRRM are compared to the RRM showing the capability of the DRRM in providing higher SFDR in an unlimited operational bandwidth. DRRM bandwidth limitations are a result of the modulation index from each RRM and their resonance characteristics that limit the gain and noise figure of the microwave photonic link. The impact of the modulator on microwave photonic link figure of merits is analyzed and compared to RRM and Mach-Zehnder Interference (MZI) modulators. Considering ± 5 GHz operational bandwidth around the resonance frequency imposed by the modulation index requirement the DRRM is capable of a ~15 dB SFDR improvement (1 Hz instantaneous bandwidth) versus RRM and MZI.

Generalized structural equations improve sexual-selection analyses

PubMed Central

Santini, Giacomo; Marchetti, Giovanni Maria; Focardi, Stefano

2017-01-01

Sexual selection is an intense evolutionary force, which operates through competition for the access to breeding resources. There are many cases where male copulatory success is highly asymmetric, and few males are able to sire most females. Two main hypotheses were proposed to explain this asymmetry: “female choice” and “male dominance”. The literature reports contrasting results. This variability may reflect actual differences among studied populations, but it may also be generated by methodological differences and statistical shortcomings in data analysis. A review of the statistical methods used so far in lek studies, shows a prevalence of Linear Models (LM) and Generalized Linear Models (GLM) which may be affected by problems in inferring cause-effect relationships; multi-collinearity among explanatory variables and erroneous handling of non-normal and non-continuous distributions of the response variable. In lek breeding, selective pressure is maximal, because large numbers of males and females congregate in small arenas. We used a dataset on lekking fallow deer (Dama dama), to contrast the methods and procedures employed so far, and we propose a novel approach based on Generalized Structural Equations Models (GSEMs). GSEMs combine the power and flexibility of both SEM and GLM in a unified modeling framework. We showed that LMs fail to identify several important predictors of male copulatory success and yields very imprecise parameter estimates. Minor variations in data transformation yield wide changes in results and the method appears unreliable. GLMs improved the analysis, but GSEMs provided better results, because the use of latent variables decreases the impact of measurement errors. Using GSEMs, we were able to test contrasting hypotheses and calculate both direct and indirect effects, and we reached a high precision of the estimates, which implies a high predictive ability. In synthesis, we recommend the use of GSEMs in studies on lekking behaviour, and we provide guidelines to implement these models. PMID:28809923

Isolation and characterization of novel chitinolytic bacteria

NASA Astrophysics Data System (ADS)

Gürkök, Sümeyra; Görmez, Arzu

2016-04-01

Chitin, a linear polymer of β-1,4-N-acetylglucosamine units, is one of the most abundant biopolymers widely distributed in the marine and terrestrial environments. It is found as a structural component of insects, crustaceans and the cell walls of fungi. Chitinases, the enzymes degrading chitin by cleaving the β-(1-4) bond, have gained increased attention due to their wide range of biotechnological applications, especially for biocontrol of harmful insects and phytopathogenic fungi in agriculture. In the present study, 200 bacterial isolates from Western Anatolia Region of Turkey were screened for chitinolytic activity on agar media amended with colloidal chitin. Based on the chitin hydrolysis zone, 13 isolates were selected for further study. Bacterial isolates with the highest chitinase activity were identified as Acinetobacter calcoaceticus, Arthrobacter oxydans, Bacillus cereus, Bacillus megaterium, Brevibacillus reuszeri, Kocuria erythromyxa, Kocuria rosea, Novosphingobium capsulatum, Rhodococcus bratislaviensis, Rhodococcus fascians and Staphylococcus cohnii by MIS and BIOLOG systems. The next aims of the study are to compare the productivity of these bacteria quantitatively, to purify the enzyme from the most potent producer and to apply the pure enzyme for the fight against the phytopathogenic fungi and harmful insects.

Wide range optofluidically tunable multimode interference fiber laser

NASA Astrophysics Data System (ADS)

Antonio-Lopez, J. E.; Sanchez-Mondragon, J. J.; LiKamWa, P.; May-Arrioja, D. A.

2014-08-01

An optofluidically tunable fiber laser based on multimode interference (MMI) effects with a wide tuning range is proposed and demonstrated. The tunable mechanism is based on an MMI fiber filter fabricated using a special fiber known as no-core fiber, which is a multimode fiber (MMF) without cladding. Therefore, when the MMI filter is covered by liquid the optical properties of the no-core fiber are modified, which allow us to tune the peak wavelength response of the MMI filter. Rather than applying the liquid on the entire no-core fiber, we change the liquid level along the no-core fiber, which provides a highly linear tuning response. In addition, by selecting the adequate refractive index of the liquid we can also choose the tuning range. We demonstrate the versatility of the optofluidically tunable MMI filter by wavelength tuning two different gain media, erbium doped fiber and a semiconductor optical amplifier, achieving tuning ranges of 55 and 90 nm respectively. In both cases, we achieve side-mode suppression ratios (SMSR) better than 50 dBm with output power variations of less than 0.76 dBm over the whole tuning range.

The Power Prior: Theory and Applications

PubMed Central

Ibrahim, Joseph G.; Chen, Ming-Hui; Gwon, Yeongjin; Chen, Fang

2015-01-01

The power prior has been widely used in many applications covering a large number of disciplines. The power prior is intended to be an informative prior constructed from historical data. It has been used in clinical trials, genetics, health care, psychology, environmental health, engineering, economics, and business. It has also been applied for a wide variety of models and settings, both in the experimental design and analysis contexts. In this review article, we give an A to Z exposition of the power prior and its applications to date. We review its theoretical properties, variations in its formulation, statistical contexts for which it has been used, applications, and its advantages over other informative priors. We review models for which it has been used, including generalized linear models, survival models, and random effects models. Statistical areas where the power prior has been used include model selection, experimental design, hierarchical modeling, and conjugate priors. Prequentist properties of power priors in posterior inference are established and a simulation study is conducted to further examine the empirical performance of the posterior estimates with power priors. Real data analyses are given illustrating the power prior as well as the use of the power prior in the Bayesian design of clinical trials. PMID:26346180

RRI-GBT MULTI-BAND RECEIVER: MOTIVATION, DESIGN, AND DEVELOPMENT

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

Maan, Yogesh; Deshpande, Avinash A.; Chandrashekar, Vinutha

2013-01-15

We report the design and development of a self-contained multi-band receiver (MBR) system, intended for use with a single large aperture to facilitate sensitive and high time-resolution observations simultaneously in 10 discrete frequency bands sampling a wide spectral span (100-1500 MHz) in a nearly log-periodic fashion. The development of this system was primarily motivated by need for tomographic studies of pulsar polar emission regions. Although the system design is optimized for the primary goal, it is also suited for several other interesting astronomical investigations. The system consists of a dual-polarization multi-band feed (with discrete responses corresponding to the 10 bandsmore » pre-selected as relatively radio frequency interference free), a common wide-band radio frequency front-end, and independent back-end receiver chains for the 10 individual sub-bands. The raw voltage time sequences corresponding to 16 MHz bandwidth each for the two linear polarization channels and the 10 bands are recorded at the Nyquist rate simultaneously. We present the preliminary results from the tests and pulsar observations carried out with the Robert C. Byrd Green Bank Telescope using this receiver. The system performance implied by these results and possible improvements are also briefly discussed.« less

One-way quasiplanar terahertz absorbers using nonstructured polar dielectric layers

NASA Astrophysics Data System (ADS)

Rodríguez-Ulibarri, P.; Beruete, M.; Serebryannikov, A. E.

2017-10-01

A concept of quasiplanar one-way transparent terahertz absorbers made of linear isotropic materials is presented. The resulting structure consists of a homogeneous absorbing layer of polar dielectric, GaAs, a dispersion-free substrate, and an ultrathin frequency-selective reflector. It is demonstrated that perfect absorption can be obtained for forward illumination, along with total reflection at backward illumination and transparency windows in the adjacent bands. The design is particularized for the polaritonic gap range where permittivity of GaAs varies in a wide range and includes epsilon-near-zero and transparency regimes. The underlying physics can be explained with the aid of a unified equivalent-circuit (EC) analytical model. Perfect matching of input impedance in forward operation and, simultaneously, strong mismatch in the backward case are the universal criteria of one-way absorption. It is shown that perfect one-way absorption can be achieved at rather arbitrary permittivity values, provided these criteria are fulfilled. The EC results are in good agreement with full-wave simulations in a wide range of material and geometrical parameters. The resulting one-way absorbers are very compact and geometrically simple, and enable transparency in the neighboring frequency ranges and, hence, multifunctionality that utilizes both absorption- and transmission-related regimes.

Linear systems on balancing chemical reaction problem

NASA Astrophysics Data System (ADS)

Kafi, R. A.; Abdillah, B.

2018-01-01

The concept of linear systems appears in a variety of applications. This paper presents a small sample of the wide variety of real-world problems regarding our study of linear systems. We show that the problem in balancing chemical reaction can be described by homogeneous linear systems. The solution of the systems is obtained by performing elementary row operations. The obtained solution represents the finding coefficients of chemical reaction. In addition, we present a computational calculation to show that mathematical software such as Matlab can be used to simplify completion of the systems, instead of manually using row operations.

GWAS with longitudinal phenotypes: performance of approximate procedures

PubMed Central

Sikorska, Karolina; Montazeri, Nahid Mostafavi; Uitterlinden, André; Rivadeneira, Fernando; Eilers, Paul HC; Lesaffre, Emmanuel

2015-01-01

Analysis of genome-wide association studies with longitudinal data using standard procedures, such as linear mixed model (LMM) fitting, leads to discouragingly long computation times. There is a need to speed up the computations significantly. In our previous work (Sikorska et al: Fast linear mixed model computations for genome-wide association studies with longitudinal data. Stat Med 2012; 32.1: 165–180), we proposed the conditional two-step (CTS) approach as a fast method providing an approximation to the P-value for the longitudinal single-nucleotide polymorphism (SNP) effect. In the first step a reduced conditional LMM is fit, omitting all the SNP terms. In the second step, the estimated random slopes are regressed on SNPs. The CTS has been applied to the bone mineral density data from the Rotterdam Study and proved to work very well even in unbalanced situations. In another article (Sikorska et al: GWAS on your notebook: fast semi-parallel linear and logistic regression for genome-wide association studies. BMC Bioinformatics 2013; 14: 166), we suggested semi-parallel computations, greatly speeding up fitting many linear regressions. Combining CTS with fast linear regression reduces the computation time from several weeks to a few minutes on a single computer. Here, we explore further the properties of the CTS both analytically and by simulations. We investigate the performance of our proposal in comparison with a related but different approach, the two-step procedure. It is analytically shown that for the balanced case, under mild assumptions, the P-value provided by the CTS is the same as from the LMM. For unbalanced data and in realistic situations, simulations show that the CTS method does not inflate the type I error rate and implies only a minimal loss of power. PMID:25712081

Estimation and Selection via Absolute Penalized Convex Minimization And Its Multistage Adaptive Applications

PubMed Central

Huang, Jian; Zhang, Cun-Hui

2013-01-01

The ℓ1-penalized method, or the Lasso, has emerged as an important tool for the analysis of large data sets. Many important results have been obtained for the Lasso in linear regression which have led to a deeper understanding of high-dimensional statistical problems. In this article, we consider a class of weighted ℓ1-penalized estimators for convex loss functions of a general form, including the generalized linear models. We study the estimation, prediction, selection and sparsity properties of the weighted ℓ1-penalized estimator in sparse, high-dimensional settings where the number of predictors p can be much larger than the sample size n. Adaptive Lasso is considered as a special case. A multistage method is developed to approximate concave regularized estimation by applying an adaptive Lasso recursively. We provide prediction and estimation oracle inequalities for single- and multi-stage estimators, a general selection consistency theorem, and an upper bound for the dimension of the Lasso estimator. Important models including the linear regression, logistic regression and log-linear models are used throughout to illustrate the applications of the general results. PMID:24348100

Controlling modal interactions in lasers for frequency selection and power enhancement

NASA Astrophysics Data System (ADS)

Ge, Li

2015-03-01

The laser is an out-of-equilibrium non-linear wave system where the interplay of the cavity geometry and non-linear wave interactions determines the self-organized oscillation frequencies and the associated spatial field patterns. Using the correspondence between nonlinear and linear systems, we propose a simple and systematic method to achieve selective excitation of lasing modes that would have been dwarfed by more dominant ones. The key idea is incorporating the control of modal interaction into the spatial pump profile. Our proposal is most valuable in the regime of spatially and spectrally overlapping modes, which can lead to a significant enhancement of laser power as well.

Chiral-selective nonlinear optical generation and emission control with plasmonic metamaterials (Conference Presentation)

NASA Astrophysics Data System (ADS)

Cai, Wenshan

2016-09-01

Metamaterials can be designed to exhibit extraordinarily strong chiral responses. Here we present a chiral metamaterial that produces both distinguishable linear and nonlinear features in the visible to near-infrared range. In additional to the gigantic chiral effects in the linear regime, the metamaterial demonstrates a pronounced contrast between second harmonic responses from the two circular polarizations. Linear and nonlinear images probed with circularly polarized lights show strongly defined contrast. Moreover, the chiral centers of the nanometallic structures with enhanced hotspots can be purposely opened for direct access, where emitters occupying the light-confining regions produce chiral-selective enhancement of two-photon luminescence.

A class of stochastic optimization problems with one quadratic & several linear objective functions and extended portfolio selection model

NASA Astrophysics Data System (ADS)

Xu, Jiuping; Li, Jun

2002-09-01

In this paper a class of stochastic multiple-objective programming problems with one quadratic, several linear objective functions and linear constraints has been introduced. The former model is transformed into a deterministic multiple-objective nonlinear programming model by means of the introduction of random variables' expectation. The reference direction approach is used to deal with linear objectives and results in a linear parametric optimization formula with a single linear objective function. This objective function is combined with the quadratic function using the weighted sums. The quadratic problem is transformed into a linear (parametric) complementary problem, the basic formula for the proposed approach. The sufficient and necessary conditions for (properly, weakly) efficient solutions and some construction characteristics of (weakly) efficient solution sets are obtained. An interactive algorithm is proposed based on reference direction and weighted sums. Varying the parameter vector on the right-hand side of the model, the DM can freely search the efficient frontier with the model. An extended portfolio selection model is formed when liquidity is considered as another objective to be optimized besides expectation and risk. The interactive approach is illustrated with a practical example.

FIRE: an SPSS program for variable selection in multiple linear regression analysis via the relative importance of predictors.

PubMed

Lorenzo-Seva, Urbano; Ferrando, Pere J

2011-03-01

We provide an SPSS program that implements currently recommended techniques and recent developments for selecting variables in multiple linear regression analysis via the relative importance of predictors. The approach consists of: (1) optimally splitting the data for cross-validation, (2) selecting the final set of predictors to be retained in the equation regression, and (3) assessing the behavior of the chosen model using standard indices and procedures. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.

On Large Time Behavior and Selection Principle for a Diffusive Carr-Penrose Model

NASA Astrophysics Data System (ADS)

Conlon, Joseph G.; Dabkowski, Michael; Wu, Jingchen

2016-04-01

This paper is concerned with the study of a diffusive perturbation of the linear LSW model introduced by Carr and Penrose. A main subject of interest is to understand how the presence of diffusion acts as a selection principle, which singles out a particular self-similar solution of the linear LSW model as determining the large time behavior of the diffusive model. A selection principle is rigorously proven for a model which is a semiclassical approximation to the diffusive model. Upper bounds on the rate of coarsening are also obtained for the full diffusive model.

A displacement-based approach for determining non-linear effects on pre-tensioned-cable cross-braced structures

NASA Astrophysics Data System (ADS)

Giaccu, Gian Felice; Caracoglia, Luca

2017-04-01

Pre-tensioned-cable bracing systems are widely employed in structural engineering to limit lateral deflections and stabilize structures. A suitable configuration of the pre-tensioned-cable bracing systems in a structure is an important issue since the internal force distribution, emerging from the interaction with the existing structure, significantly affects the structural dynamic behavior. The design, however, is often based on the intuition and the previous experience of the engineer. In recent years, the authors have been investigating the non-linear dynamic response of cable systems, installed on cable-stayed bridges, and in particular the so-called "cable-cross-tie systems" forming a cable network. The bracing cables (cross-ties) can exhibit slackening or snapping. Therefore, a non-linear unilateral model, combined with the taut-cable theory, is required to simulate the incipient slackening conditions in the stays. Capitalizing from this work on non-linear cable dynamics, this paper proposes a new approach to analyze, in laterally- braced truss structures, the unilateral effects and dynamic response accounting for the loss in the pre-tensioning force imparted to the bracing cables. This effect leads to non-linear vibration of the structure. In this preliminary study, the free vibrations of the structure are investigated by using the "Equivalent Linearization Method". A performance coefficient, a real positive number between 0.5 and 1.0, is defined and employed to monitor the relative reduction in the apparent stiffness of the braces during structural vibration, "mode by mode". It is shown that the system can exhibit alternate unilateral behavior of the cross-braces. A reduction of the performance coefficient close to fifty percent is observed in the braces when the initial pre-tensioning force is small. On the other hand the performance coefficient tends to one in the case of a high level of pre-stress. It is concluded that the performance coefficient may possibly be used as an indicator for the design of the braces since a suitable selection of the initial pre-tensioning force can avoid slackening in the braces.

A Wide Linearity Range Method for the Determination of Lenalidomide in Plasma by High-Performance Liquid Chromatography: Application to Pharmacokinetic Studies.

PubMed

Guglieri-López, Beatriz; Pérez-Pitarch, Alejandro; Martinez-Gómez, Maria Amparo; Porta-Oltra, Begoña; Climente-Martí, Mónica; Merino-Sanjuán, Matilde

2016-12-01

A wide linearity range analytical method for the determination of lenalidomide in patients with multiple myeloma for pharmacokinetic studies is required. Plasma samples were ultrasonicated for protein precipitation. A solid-phase extraction was performed. The eluted samples were evaporated to dryness under vacuum, and the solid obtained was diluted and injected into the high-performance liquid chromatography (HPLC) system. Separation of lenalidomide was performed on an Xterra RP C18 (250 mm length × 4.6 mm i.d., 5 µm) using a mobile phase consisting of phosphate buffer/acetonitrile (85:15, v/v, pH 3.2) at a flow rate of 0.5 mL · min -1 The samples were monitored at a wavelength of 311 nm. A linear relationship with good correlation coefficient (r = 0.997, n = 9) was found between the peak area and lenalidomide concentrations in the range of 100 to 950 ng · mL -1 The limits of detection and quantitation were 28 and 100 ng · mL -1 , respectively. The intra- and interassay precisions were satisfactory, and the accuracy of the method was proved. In conclusion, the proposed method is suitable for the accurate quantification of lenalidomide in human plasma with a wide linear range, from 100 to 950 ng · mL -1 This is a valuable method for pharmacokinetic studies of lenalidomide in human subjects. © 2016 Society for Laboratory Automation and Screening.

Developmental memory capacity resources of typical children retrieving picture communication symbols using direct selection and visual linear scanning with fixed communication displays.

PubMed

Wagner, Barry T; Jackson, Heather M

2006-02-01

This study examined the cognitive demands of 2 selection techniques in augmentative and alternative communication (AAC), direct selection, and visual linear scanning, by determining the memory retrieval abilities of typically developing children when presented with fixed communication displays. One hundred twenty typical children from kindergarten, 1st, and 3rd grades were randomly assigned to either a direct selection or visual linear scanning group. Memory retrieval was assessed through word span using Picture Communication Symbols (PCSs). Participants were presented various numbers and arrays of PCSs and asked to retrieve them by placing identical graphic symbols on fixed communication displays with grid layouts. The results revealed that participants were able to retrieve more PCSs during direct selection than scanning. Additionally, 3rd-grade children retrieved more PCSs than kindergarten and 1st-grade children. An analysis on the type of errors during retrieval indicated that children were more successful at retrieving the correct PCSs than the designated location of those symbols on fixed communication displays. AAC practitioners should consider using direct selection over scanning whenever possible and account for anticipatory monitoring and pulses when scanning is used in the service delivery of children with little or no functional speech. Also, researchers should continue to investigate AAC selection techniques in relationship to working memory resources.

Feature weight estimation for gene selection: a local hyperlinear learning approach

PubMed Central

2014-01-01

Background Modeling high-dimensional data involving thousands of variables is particularly important for gene expression profiling experiments, nevertheless,it remains a challenging task. One of the challenges is to implement an effective method for selecting a small set of relevant genes, buried in high-dimensional irrelevant noises. RELIEF is a popular and widely used approach for feature selection owing to its low computational cost and high accuracy. However, RELIEF based methods suffer from instability, especially in the presence of noisy and/or high-dimensional outliers. Results We propose an innovative feature weighting algorithm, called LHR, to select informative genes from highly noisy data. LHR is based on RELIEF for feature weighting using classical margin maximization. The key idea of LHR is to estimate the feature weights through local approximation rather than global measurement, which is typically used in existing methods. The weights obtained by our method are very robust in terms of degradation of noisy features, even those with vast dimensions. To demonstrate the performance of our method, extensive experiments involving classification tests have been carried out on both synthetic and real microarray benchmark datasets by combining the proposed technique with standard classifiers, including the support vector machine (SVM), k-nearest neighbor (KNN), hyperplane k-nearest neighbor (HKNN), linear discriminant analysis (LDA) and naive Bayes (NB). Conclusion Experiments on both synthetic and real-world datasets demonstrate the superior performance of the proposed feature selection method combined with supervised learning in three aspects: 1) high classification accuracy, 2) excellent robustness to noise and 3) good stability using to various classification algorithms. PMID:24625071

Note: Wide-operating-range control for thermoelectric coolers.

PubMed

Peronio, P; Labanca, I; Ghioni, M; Rech, I

2017-11-01

A new algorithm for controlling the temperature of a thermoelectric cooler is proposed. Unlike a classic proportional-integral-derivative (PID) control, which computes the bias voltage from the temperature error, the proposed algorithm exploits the linear relation that exists between the cold side's temperature and the amount of heat that is removed per unit time. Since this control is based on an existing linear relation, it is insensitive to changes in the operating point that are instead crucial in classic PID control of a non-linear system.

Note: Wide-operating-range control for thermoelectric coolers

NASA Astrophysics Data System (ADS)

Peronio, P.; Labanca, I.; Ghioni, M.; Rech, I.

2017-11-01

A new algorithm for controlling the temperature of a thermoelectric cooler is proposed. Unlike a classic proportional-integral-derivative (PID) control, which computes the bias voltage from the temperature error, the proposed algorithm exploits the linear relation that exists between the cold side's temperature and the amount of heat that is removed per unit time. Since this control is based on an existing linear relation, it is insensitive to changes in the operating point that are instead crucial in classic PID control of a non-linear system.

Forcing Regression through a Given Point Using Any Familiar Computational Routine.

DTIC Science & Technology

1983-03-01

a linear model , Y =a + OX + e ( Model I) then adopt the principle of least squares; and use sample data to estimate the unknown parameters, a and 8...has an expected value of zero indicates that the "average" response is considered linear . If c varies widely, Model I, though conceptually correct, may...relationship is linear from the maximum observed x to x - a, then Model II should be used. To pro- ceed with the customary evaluation of Model I would be

Video Image Tracking Engine

NASA Technical Reports Server (NTRS)

Howard, Richard T. (Inventor); Bryan, ThomasC. (Inventor); Book, Michael L. (Inventor)

2004-01-01

A method and system for processing an image including capturing an image and storing the image as image pixel data. Each image pixel datum is stored in a respective memory location having a corresponding address. Threshold pixel data is selected from the image pixel data and linear spot segments are identified from the threshold pixel data selected.. Ihe positions of only a first pixel and a last pixel for each linear segment are saved. Movement of one or more objects are tracked by comparing the positions of fust and last pixels of a linear segment present in the captured image with respective first and last pixel positions in subsequent captured images. Alternatively, additional data for each linear data segment is saved such as sum of pixels and the weighted sum of pixels i.e., each threshold pixel value is multiplied by that pixel's x-location).

Effect of village-wide use of long-lasting insecticidal nets on visceral Leishmaniasis vectors in India and Nepal: a cluster randomized trial.

PubMed

Picado, Albert; Das, Murari L; Kumar, Vijay; Kesari, Shreekant; Dinesh, Diwakar S; Roy, Lalita; Rijal, Suman; Das, Pradeep; Rowland, Mark; Sundar, Shyam; Coosemans, Marc; Boelaert, Marleen; Davies, Clive R

2010-01-26

Visceral leishmaniasis (VL) control in the Indian subcontinent is currently based on case detection and treatment, and on vector control using indoor residual spraying (IRS). The use of long-lasting insecticidal nets (LN) has been postulated as an alternative or complement to IRS. Here we tested the impact of comprehensive distribution of LN on the density of Phlebotomus argentipes in VL-endemic villages. A cluster-randomized controlled trial with household P. argentipes density as outcome was designed. Twelve clusters from an ongoing LN clinical trial--three intervention and three control clusters in both India and Nepal--were selected on the basis of accessibility and VL incidence. Ten houses per cluster selected on the basis of high pre-intervention P. argentipes density were monitored monthly for 12 months after distribution of LN using CDC light traps (LT) and mouth aspiration methods. Ten cattle sheds per cluster were also monitored by aspiration. A random effect linear regression model showed that the cluster-wide distribution of LNs significantly reduced the P. argentipes density/house by 24.9% (95% CI 1.80%-42.5%) as measured by means of LTs. The ongoing clinical trial, designed to measure the impact of LNs on VL incidence, will confirm whether LNs should be adopted as a control strategy in the regional VL elimination programs. The entomological evidence described here provides some evidence that LNs could be usefully deployed as part of the VL control program. ClinicalTrials.gov CT-2005-015374.

Ballistic impact resistance of selected organic ophthalmic lenses.

PubMed

Chou, B Ralph; Yuen, Gloria S-C; Dain, Stephen J

2011-11-01

The aim was to assess the impact resistance of coated and uncoated mid-index spectacle lens materials using the ballistic impact test. Nominally plano lenses of each material in three thicknesses were obtained. The lenses were flat edged to a 50 mm diameter. Each lens was impacted by a 6.35 mm steel ball. Impact velocities were selected using the Zippy Estimation by Sequential Testing protocol to determine the threshold fracture impact velocity. Threshold fracture impact velocity generally increased with thickness; however, there was a wide variation in performance among the various lens materials at each thickness. In all but two instances, the differences in impact velocity at each thickness of lens material were significant. Comparison of the data for CR39 and Hoya Phoenix with the results of earlier studies showed that the lens mounting is a significant factor. The fracture velocities found in the present study were significantly lower than the fracture velocities found when the lens edge is restrained in the mounting. A scratch resistant coating reduced the impact resistance of CR39. The effect of the antireflection coating on the fracture velocity depended on the nature of the base scratch-resistant coating. Mid-index lens materials of the same thickness show widely varying levels of impact resistance under the ballistic test. Impact resistance increases non-linearly with centre thickness. The lens mounting might affect the results of the ballistic impact test. The presence of 'cushion coatings' might enhance impact resistance. © 2011 The Authors. Clinical and Experimental Optometry © 2011 Optometrists Association Australia.

Social Impact of Participatory Health Research: Collaborative Non-Linear Processes of Knowledge Mobilization

ERIC Educational Resources Information Center

Abma, Tineke A.; Cook, Tina; Rämgård, Margaretha; Kleba, Elisabeth; Harris, Janet; Wallerstein, Nina

2017-01-01

Social impact, defined as an effect on society, culture, quality of life, community services, or public policy beyond academia, is widely considered as a relevant requirement for scientific research, especially in the field of health care. Traditionally, in health research, the process of knowledge transfer is rather linear and one-sided and has…

The Development of a High Speed Exponential Function Generator for Linearization of Microwave Voltage Controlled Oscillators.

DTIC Science & Technology

1985-10-01

characteristic of a p-n junction to provide exponential linearization in a simple, thermally-stable, wide band circuit. RESME Les oscillateurs A...exponentielle (fr6quence/tension) que V’on 1 retrouve chez plusieurs oscillateurs . Ce circuit, d’une grande largeur de bande, utilise la caractfiristique

A novel aptamer-based online magnetic solid phase extraction method for the selective determination of 8-hydroxy-2'-deoxyguanosine in human urine.

PubMed

Gan, Haijiao; Xu, Hui

2018-05-30

In this work, an innovative magnetic aptamer adsorbent (Fe 3 O 4 -aptamer MNPs) was synthesized for the selective extraction of 8-hydroxy-2'-deoxyguanosine (8-OHdG). Amino-functionalized-Fe 3 O 4 was crosslinked with 8-OHdG aptamer by glutaraldehyde and fixed into a steel stainless tube as the sorbent of magnetic solid phase extraction (MSPE). After selective extraction by the aptamer adsorbent, the adsorbed 8-OHdG was desorbed dynamically and online analyzed by high performance liquid chromatography-mass spectrometry (HPLC-MS). The synthesized sorbent presented outstanding features, including specific selectivity, high enrichment capacity, stability and biocompatibility. Moreover, this proposed MSPE-HPLC-MS can achieve adsorption and desorption operation integration, greatly simplify the analysis process and reduce human errors. When compared with offline MSPE, a sensitivity enhancement of 800 times was obtained for the online method. Some experimental parameters such as the amount of the sorbent, sample flow rate and sample volume, were optimized systematically. Under the optimal conditions, low limit of detection (0.01 ng mL -1 , S/N = 3), limit of quantity (0.03 ng mL -1 , S/N = 10) and wide linear range with a satisfactory correlation coefficient (R 2  ≥ 0.9992) were obtained. And the recoveries of 8-OHdG in the urine samples varied from 82% to 116%. All these results revealed that the method is simple, rapid, selective, sensitive and automated, and it could be expected to become a potential approach for the selective determination of trace 8-OHdG in complex urinary samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Beneficial laggards: multilevel selection, cooperative polymorphism and division of labour in threshold public good games

PubMed Central

2010-01-01

Background The origin and stability of cooperation is a hot topic in social and behavioural sciences. A complicated conundrum exists as defectors have an advantage over cooperators, whenever cooperation is costly so consequently, not cooperating pays off. In addition, the discovery that humans and some animal populations, such as lions, are polymorphic, where cooperators and defectors stably live together -- while defectors are not being punished--, is even more puzzling. Here we offer a novel explanation based on a Threshold Public Good Game (PGG) that includes the interaction of individual and group level selection, where individuals can contribute to multiple collective actions, in our model group hunting and group defense. Results Our results show that there are polymorphic equilibria in Threshold PGGs; that multi-level selection does not select for the most cooperators per group but selects those close to the optimum number of cooperators (in terms of the Threshold PGG). In particular for medium cost values division of labour evolves within the group with regard to the two types of cooperative actions (hunting vs. defense). Moreover we show evidence that spatial population structure promotes cooperation in multiple PGGs. We also demonstrate that these results apply for a wide range of non-linear benefit function types. Conclusions We demonstrate that cooperation can be stable in Threshold PGG, even when the proportion of so called free riders is high in the population. A fundamentally new mechanism is proposed how laggards, individuals that have a high tendency to defect during one specific group action can actually contribute to the fitness of the group, by playing part in an optimal resource allocation in Threshold Public Good Games. In general, our results show that acknowledging a multilevel selection process will open up novel explanations for collective actions. PMID:21044340

Genome-wide scans for loci under selection in humans

PubMed Central

2005-01-01

Natural selection, which can be defined as the differential contribution of genetic variants to future generations, is the driving force of Darwinian evolution. Identifying regions of the human genome that have been targets of natural selection is an important step in clarifying human evolutionary history and understanding how genetic variation results in phenotypic diversity, it may also facilitate the search for complex disease genes. Technological advances in high-throughput DNA sequencing and single nucleotide polymorphism genotyping have enabled several genome-wide scans of natural selection to be undertaken. Here, some of the observations that are beginning to emerge from these studies will be reviewed, including evidence for geographically restricted selective pressures (ie local adaptation) and a relationship between genes subject to natural selection and human disease. In addition, the paper will highlight several important problems that need to be addressed in future genome-wide studies of natural selection. PMID:16004726

Genome-wide association analysis reveals loci associated with resistance against Piscirickettsia salmonis in two Atlantic salmon (Salmo salar L.) chromosomes.

PubMed

Correa, Katharina; Lhorente, Jean P; López, María E; Bassini, Liane; Naswa, Sudhir; Deeb, Nader; Di Genova, Alex; Maass, Alejandro; Davidson, William S; Yáñez, José M

2015-10-24

Pisciricketssia salmonis is the causal agent of Salmon Rickettsial Syndrome (SRS), which affects salmon species and causes severe economic losses. Selective breeding for disease resistance represents one approach for controlling SRS in farmed Atlantic salmon. Knowledge concerning the architecture of the resistance trait is needed before deciding on the most appropriate approach to enhance artificial selection for P. salmonis resistance in Atlantic salmon. The purpose of the study was to dissect the genetic variation in the resistance to this pathogen in Atlantic salmon. 2,601 Atlantic salmon smolts were experimentally challenged against P. salmonis by means of intra-peritoneal injection. These smolts were the progeny of 40 sires and 118 dams from a Chilean breeding population. Mortalities were recorded daily and the experiment ended at day 40 post-inoculation. Fish were genotyped using a 50K Affymetrix® Axiom® myDesignTM Single Nucleotide Polymorphism (SNP) Genotyping Array. A Genome Wide Association Analysis was performed on data from the challenged fish. Linear regression and logistic regression models were tested. Genome Wide Association Analysis indicated that resistance to P. salmonis is a moderately polygenic trait. There were five SNPs in chromosomes Ssa01 and Ssa17 significantly associated with the traits analysed. The proportion of the phenotypic variance explained by each marker is small, ranging from 0.007 to 0.045. Candidate genes including interleukin receptors and fucosyltransferase have been found to be physically linked with these genetic markers and may play an important role in the differential immune response against this pathogen. Due to the small amount of variance explained by each significant marker we conclude that genetic resistance to this pathogen can be more efficiently improved with the implementation of genetic evaluations incorporating genotype information from a dense SNP array.

Non-Condon equilibrium Fermi’s golden rule electronic transition rate constants via the linearized semiclassical method

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

Sun, Xiang; Geva, Eitan

2016-06-28

In this paper, we test the accuracy of the linearized semiclassical (LSC) expression for the equilibrium Fermi’s golden rule rate constant for electronic transitions in the presence of non-Condon effects. We do so by performing a comparison with the exact quantum-mechanical result for a model where the donor and acceptor potential energy surfaces are parabolic and identical except for shifts in the equilibrium energy and geometry, and the coupling between them is linear in the nuclear coordinates. Since non-Condon effects may or may not give rise to conical intersections, both possibilities are examined by considering: (1) A modified Garg-Onuchic-Ambegaokar modelmore » for charge transfer in the condensed phase, where the donor-acceptor coupling is linear in the primary mode coordinate, and for which non-Condon effects do not give rise to a conical intersection; (2) the linear vibronic coupling model for electronic transitions in gas phase molecules, where non-Condon effects give rise to conical intersections. We also present a comprehensive comparison between the linearized semiclassical expression and a progression of more approximate expressions. The comparison is performed over a wide range of frictions and temperatures for model (1) and over a wide range of temperatures for model (2). The linearized semiclassical method is found to reproduce the exact quantum-mechanical result remarkably well for both models over the entire range of parameters under consideration. In contrast, more approximate expressions are observed to deviate considerably from the exact result in some regions of parameter space.« less

Wavelength selection in injection-driven Hele-Shaw flows: A maximum amplitude criterion

NASA Astrophysics Data System (ADS)

Dias, Eduardo; Miranda, Jose

2013-11-01

As in most interfacial flow problems, the standard theoretical procedure to establish wavelength selection in the viscous fingering instability is to maximize the linear growth rate. However, there are important discrepancies between previous theoretical predictions and existing experimental data. In this work we perform a linear stability analysis of the radial Hele-Shaw flow system that takes into account the combined action of viscous normal stresses and wetting effects. Most importantly, we introduce an alternative selection criterion for which the selected wavelength is determined by the maximum of the interfacial perturbation amplitude. The effectiveness of such a criterion is substantiated by the significantly improved agreement between theory and experiments. We thank CNPq (Brazilian Sponsor) for financial support.

Log-linear model based behavior selection method for artificial fish swarm algorithm.

PubMed

Huang, Zhehuang; Chen, Yidong

2015-01-01

Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm.

A normative study of the Italian printed word version of the free and cued selective reminding test.

PubMed

Girtler, N; De Carli, F; Amore, M; Arnaldi, D; Bosia, L E; Bruzzaniti, C; Cappa, S F; Cocito, L; Colazzo, G; Ghio, L; Magi, E; Mancardi, G L; Nobili, F; Pardini, M; Picco, A; Rissotto, R; Serrati, C; Brugnolo, A

2015-07-01

According to the new research criteria for the diagnosis of Alzheimer's disease, episodic memory impairment, not significantly improved by cueing, is the core neuropsychological marker, even at a pre-dementia stage. The FCSRT assesses verbal learning and memory using semantic cues and is widely used in Europe. Standardization values for the Italian population are available for the colored picture version, but not for the 16-item printed word version. In this study, we present age- and education-adjusted normative data for FCSRT-16 obtained using linear regression techniques and generalized linear model, and critical values for classifying sub-test performance into equivalent scores. Six scores were derived from the performance of 194 normal subjects (MMSE score, range 27-30, mean 29.5 ± 0.5) divided per decade (from 20 to 90), per gender and per level of education (4 levels: 3-5, 6-8, 9-13, >13 years): immediate free recall (IFR), immediate total recall (ITR), recognition phase (RP), delayed free recall (DFR), delayed total recall (DTR), Index of Sensitivity of Cueing (ISC), number of intrusions. This study confirms the effect of age and education, but not of gender on immediate and delayed free and cued recall. The Italian version of the FCSRT-16 can be useful for both clinical and research purposes.

Determination of sulfonamide antibiotics and metabolites in liver, muscle and kidney samples by pressurized liquid extraction or ultrasound-assisted extraction followed by liquid chromatography-quadrupole linear ion trap-tandem mass spectrometry (HPLC-QqLIT-MS/MS).

PubMed

Hoff, Rodrigo Barcellos; Pizzolato, Tânia Mara; Peralba, Maria do Carmo Ruaro; Díaz-Cruz, M Silvia; Barceló, Damià

2015-03-01

Sulfonamides are widely used in human and veterinary medicine. The presence of sulfonamides residues in food is an issue of great concern. Throughout the present work, a method for the targeted analysis of 16 sulfonamides and metabolites residue in liver of several species has been developed and validated. Extraction and clean-up has been statistically optimized using central composite design experiments. Two extraction methods have been developed, validated and compared: i) pressurized liquid extraction, in which samples were defatted with hexane and subsequently extracted with acetonitrile and ii) ultrasound-assisted extraction with acetonitrile and further liquid-liquid extraction with hexane. Extracts have been analyzed by liquid chromatography-quadrupole linear ion trap-tandem mass spectrometry. Validation procedure has been based on the Commission Decision 2002/657/EC and included the assessment of parameters such as decision limit (CCα), detection capability (CCβ), sensitivity, selectivity, accuracy and precision. Method׳s performance has been satisfactory, with CCα values within the range of 111.2-161.4 µg kg(-1), limits of detection of 10 µg kg(-1) and accuracy values around 100% for all compounds. Copyright © 2014 Elsevier B.V. All rights reserved.

Relationship between tendon stiffness and failure: a metaanalysis

PubMed Central

LaCroix, Andrew S.; Duenwald-Kuehl, Sarah E.; Lakes, Roderic S.

2013-01-01

Tendon is a highly specialized, hierarchical tissue designed to transfer forces from muscle to bone; complex viscoelastic and anisotropic behaviors have been extensively characterized for specific subsets of tendons. Reported mechanical data consistently show a pseudoelastic, stress-vs.-strain behavior with a linear slope after an initial toe region. Many studies report a linear, elastic modulus, or Young's modulus (hereafter called elastic modulus) and ultimate stress for their tendon specimens. Individually, these studies are unable to provide a broader, interstudy understanding of tendon mechanical behavior. Herein we present a metaanalysis of pooled mechanical data from a representative sample of tendons from different species. These data include healthy tendons and those altered by injury and healing, genetic modification, allograft preparation, mechanical environment, and age. Fifty studies were selected and analyzed. Despite a wide range of mechanical properties between and within species, elastic modulus and ultimate stress are highly correlated (R2 = 0.785), suggesting that tendon failure is highly strain-dependent. Furthermore, this relationship was observed to be predictable over controlled ranges of elastic moduli, as would be typical of any individual species. With the knowledge gained through this metaanalysis, noninvasive tools could measure elastic modulus in vivo and reasonably predict ultimate stress (or structural compromise) for diseased or injured tendon. PMID:23599401

Hierarchical NiCo2O4 Hollow Sphere as a Peroxidase Mimetic for Colorimetric Detection of H2O2 and Glucose

PubMed Central

Huang, Wei; Lin, Tianye; Cao, Yang; Lai, Xiaoyong; Peng, Juan; Tu, Jinchun

2017-01-01

In this work, the hierarchical NiCo2O4 hollow sphere synthesized via a “coordinating etching and precipitating” process was demonstrated to exhibit intrinsic peroxidase-like activity. The peroxidase-like activity of NiCo2O4, NiO, and Co3O4 hollow spheres were comparatively studied by the catalytic oxidation reaction of 3,3,5,5-tetramethylbenzidine (TMB) in presence of H2O2, and a superior peroxidase-like activity of NiCo2O4 was confirmed by stronger absorbance at 652 nm. Furthermore, the proposed sensing platform showed commendable response to H2O2 with a linear range from 10 μM to 400 μM, and a detection limit of 0.21 μM. Cooperated with GOx, the developed novel colorimetric and visual glucose-sensing platform exhibited high selectivity, favorable reproducibility, satisfactory applicability, wide linear range (from 0.1 mM to 4.5 mM), and a low detection limit of 5.31 μM. In addition, the concentration-dependent color change would offer a better and handier way for detection of H2O2 and glucose by naked eye. PMID:28124997

Sensitive electrochemical sensors for simultaneous determination of ascorbic acid, dopamine, and uric acid based on Au@Pd-reduced graphene oxide nanocomposites.

PubMed

Jiang, Jingjing; Du, Xuezhong

2014-10-07

Sensitive electrochemical sensors were fabricated with reduced graphene oxide-supported Au@Pd (Au@Pd-RGO) nanocomposites by one-step synthesis for individual and simultaneous determination of ascorbic acid (AA), dopamine (DA), and uric acid (UA) with low detection limits and wide concentration ranges. From the Au@Pd-RGO-modified electrodes, well-separated oxidation peaks and enhanced peak currents of AA, DA, and UA were observed owing to the superior conductivity of RGO and the excellent catalytic activity of Au@Pd nanoparticles. For individual detection, the linear responses of AA, DA, and UA were in the concentration ranges of 0.1-1000, 0.01-100, and 0.02-500 μM with detection limits of 0.02, 0.002, and 0.005 μM (S/N = 3), respectively. For simultaneous detection by synchronous change of the concentrations of AA, DA, and UA, the linear response ranges were 1-800, 0.1-100, and 0.1-350 μM with detection limits of 0.28, 0.024, and 0.02 μM (S/N = 3), respectively. The fabricated sensors were further applied to the detection of AA, DA, and UA in urine samples. The Au@Pd-RGO nanocomposites have promising applications in highly sensitive and selective electrochemical sensing.

Thermoluminescence characteristics of flat optical fiber in radiation dosimetry under different electron irradiation conditions

NASA Astrophysics Data System (ADS)

Alawiah, A.; Intan, A. M.; Bauk, S.; Abdul-Rashid, H. A.; Yusoff, Z.; Mokhtar, M. R.; Wan Abdullah, W. S.; Mat Sharif, K. A.; Mahdiraji, G. A.; Mahamd Adikan, F. R.; Tamchek, N.; Noor, N. M.; Bradley, D. A.

2013-05-01

Thermoluminescence (TL) flat optical fibers (FF) have been proposed as radiation sensor in medical dosimetry for both diagnostic and radiotherapy applications. A flat optical fiber with nominal dimensions of (3.226 × 3.417 × 0.980) mm3 contains pure silica SiO2 was selected for this research. The FF was annealed at 400°C for 1 h before irradiated. Kinetic parameters and dosimetric glow curve of TL response were studied in FF with respect to electron irradiation of 6 MeV, 15 MeV and 21 MeV using linear accelerator (LINAC) in the dose range of 2.0-10.0 Gy. The TL response was read using a TLD reader Harshaw Model 3500. The Time-Temperature-Profile (TTP) of the reader used includes; initial preheat temperature of 80°C, maximum readout temperature is 400°C and the heating rate of 30°Cs-1. The proposed FF shows excellent linear radiation response behavior within the clinical relevant dose range for all of these energies, good reproducibility, independence of radiation energy, independence of dose rate and exhibits a very low thermal fading. From these results, the proposed FF can be used as radiation dosimeter and favorably compares with the widely used of LiF:MgTi dosimeter in medical radiotherapy application.

High Aspect Ratio Perforated Co₃O₄ Nanowires Derived from Cobalt-Carbonate-Hydroxide Nanowires with Enhanced Sensing Performance.

PubMed

Zhou, Tuantuan; Gao, Wanlin; Wang, Qiang; Umar, Ahmad

2018-05-01

Herein, we report the facile synthesis of high-aspect ratio perforated Co3O4 nanowires derived from cobalt-carbonate-hydroxide (Co(CO3)0.5(OH) 0.11H2O) nanowires. The Co(CO3)0.5(OH) 0.11H2O nanowires were synthesized by simple hydrothermal process at 120 °C while annealing of such nanowires at 400 °C leads the formation of perforated Co3O4 nanowires. The prepared nanowires were characterized by several techniques which confirmed the high aspect ratio and well-crystallinity for the synthesized nanowires. For application point of view, the prepared perforated Co3O4 nanowires were used as efficient electrode material to fabricate highly sensitive and selective hydrazine chemical sensor. The electrochemical impedance spectroscopy (EIS) technique was employed to confirm the successful modification of the electrode. The key parameters of chemical sensor, such as detection limit, sensitivity, and linear range, have been systematically explored. The fabricated hydrazine sensor displayed a rather low detection limit of 4.52 μM (S/N = 3), a good sensitivity of 25.70 μA · mM-1, and a wide linear range of 16.97-358.34 μM.

AuNPs/CNOs/SWCNTs/chitosan-nanocomposite modified electrochemical sensor for the label-free detection of carcinoembryonic antigen.

PubMed

Rizwan, Mohammad; Elma, Syazwani; Lim, Syazana Abdullah; Ahmed, Minhaz Uddin

2018-06-01

In this work, a nanocomposite of gold nanoparticles (AuNPs), carbon nano-onions (CNOs), single-walled carbon nanotubes (SWCNTs) and chitosan (CS) (AuNPs/CNOs/SWCNTs/CS) was prepared for the development of highly sensitive electrochemical immunosensor for the detection of carcinoembryonic antigen (CEA), clinical tumor marker. Firstly, layer-by-layer fabrication of the CEA-immunosensors was studied using cyclic voltammetry (CV) and square wave voltammetry (SWV). By combining the advantages of large surface area and electronic properties of AuNPs, CNOs, SWCNTs, and film forming properties of CS, AuNPs/CNOs/SWCNTs/CS-nanocomposite-modified glassy carbon electrode showed a 200% increase in effective surface area and electronic conductivity. The calibration plot gave a negative linear relationship between log[concentration] of CEA and electrical current with a correlation coefficient of 0.9875. The CEA-immunosensor demonstrated a wide linear detection range of 100 fg mL -1 to 400 ng mL -1 with a low detection limit of 100 fg mL -1 . In addition to high sensitivity, reproducibility and large stability, CEA-immunosensor provided an excellent selectivity and resistant-to-interference in the presence of other antigens in serum and hence a potential to be used with real samples. Copyright © 2018 Elsevier B.V. All rights reserved.

Development of electrochemical folic acid sensor based on hydroxyapatite nanoparticles.

PubMed

Kanchana, P; Sekar, C

2015-02-25

We report the synthesis of hydroxyapatite (HA) nanoparticles (NPs) by a simple microwave irradiation method and its application as sensing element for the precise determination of folic acid (FA) by electrochemical method. The structure and composition of the HA NPs characterized using XRD, FTIR, Raman and XPS. SEM and EDX studies confirmed the formation of elongated spherical shaped HA NPs with an average particle size of about 34 nm. The HA NPs thin film on glassy carbon electrode (GCE) were deposited by drop casting method. Electrocatalytic behavior of FA in the physiological pH 7.0 was investigated by cyclic voltammetry (CV), linear sweep voltammetry (LSV) and chronoamperometry. The fabricated HA/GCE exhibited a linear calibration plot over a wide FA concentration ranging from 1.0×10(-7) to 3.5×10(-4) M with the detection limit of 75 nM. In addition, the HA NPs modified GCE showed good selectivity toward the determination of FA even in the presence of a 100-fold excess of ascorbic acid (AA) and 1000-fold excess of other common interferents. The fabricated biosensor exhibits good sensitivity and stability, and was successfully applied for the determination of FA in pharmaceutical samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Large decline in injecting drug use in Amsterdam, 1986-1998: explanatory mechanisms and determinants of injecting transitions.

PubMed

van Ameijden, E J; Coutinho, R A

2001-05-01

To study community wide trends in injecting prevalence and trends in injecting transitions, and determinants. Open cohort study with follow up every four months (Amsterdam Cohort Study). Generalised estimating equations were used for statistical analysis. Amsterdam has adopted a harm reduction approach as drug policy. 996 drug users who were recruited from 1986 to 1998, mainly at methadone programmes, who paid 13620 cohort visits. The prevalence of injecting decreased exponentially (66% to 36% in four to six monthly periods). Selective mortality and migration could maximally explain 33% of this decline. Instead, injecting initiation linearly decreased (4.1% to 0.7% per visit), cessation exponentially increased (10.0% to 17.1%), and relapse linearly decreased (21.3% to 11.8%). Non-injecting cocaine use (mainly pre-cooked, comparable to crack) and heroin use strongly increased. Trends were not attributable to changes in the study sample. Harm reduction, including large scale needle exchange programmes, does not lead to an increase in injecting drug use. The injecting decline seems mainly attributable to ecological factors (for example, drug culture and market). Prevention of injecting is possible and peer-based interventions may be effective. The consequences of the recent upsurge in crack use requires further study.

Evaluation of an LED Retrofit Project at Princeton University’s Carl Icahn Laboratory

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

Davis, Robert G.; Murphy, Arthur L.; Perrin, Tess E.

The LED lighting retrofit at the Carl Icahn Laboratory of the Lewis-Sigler Institute for Integrative Genomics was the first building-wide interior LED project at Princeton University, following the University’s experiences from several years of exterior and small-scale interior LED implementation projects. The project addressed three luminaire types – recessed 2x2 troffers, cove and other luminaires using linear T8 fluorescent lamps, and CFL downlights - which combined accounted for over 564,000 kWh of annual energy, over 90% of the lighting energy used in the facility. The Princeton Facilities Engineering staff used a thorough process of evaluating product alternatives before selecting anmore » acceptable LED retrofit solution for each luminaire type. Overall, 815 2x2 luminaires, 550 linear fluorescent luminaires, and 240 downlights were converted to LED as part of this project. Based solely on the reductions in wattage in converting from the incumbent fluorescent lamps to LED retrofit kits, the annual energy savings from the project was over 190,000 kWh, a savings of 37%. An additional 125,000 kWh of energy savings is expected from the implementation of occupancy and task-tuning control solutions, which will bring the total savings for the project to 62%.« less

Non-linear auto-regressive models for cross-frequency coupling in neural time series

PubMed Central

Tallot, Lucille; Grabot, Laetitia; Doyère, Valérie; Grenier, Yves; Gramfort, Alexandre

2017-01-01

We address the issue of reliably detecting and quantifying cross-frequency coupling (CFC) in neural time series. Based on non-linear auto-regressive models, the proposed method provides a generative and parametric model of the time-varying spectral content of the signals. As this method models the entire spectrum simultaneously, it avoids the pitfalls related to incorrect filtering or the use of the Hilbert transform on wide-band signals. As the model is probabilistic, it also provides a score of the model “goodness of fit” via the likelihood, enabling easy and legitimate model selection and parameter comparison; this data-driven feature is unique to our model-based approach. Using three datasets obtained with invasive neurophysiological recordings in humans and rodents, we demonstrate that these models are able to replicate previous results obtained with other metrics, but also reveal new insights such as the influence of the amplitude of the slow oscillation. Using simulations, we demonstrate that our parametric method can reveal neural couplings with shorter signals than non-parametric methods. We also show how the likelihood can be used to find optimal filtering parameters, suggesting new properties on the spectrum of the driving signal, but also to estimate the optimal delay between the coupled signals, enabling a directionality estimation in the coupling. PMID:29227989

Bayes factors for the linear ballistic accumulator model of decision-making.

PubMed

Evans, Nathan J; Brown, Scott D

2018-04-01

Evidence accumulation models of decision-making have led to advances in several different areas of psychology. These models provide a way to integrate response time and accuracy data, and to describe performance in terms of latent cognitive processes. Testing important psychological hypotheses using cognitive models requires a method to make inferences about different versions of the models which assume different parameters to cause observed effects. The task of model-based inference using noisy data is difficult, and has proven especially problematic with current model selection methods based on parameter estimation. We provide a method for computing Bayes factors through Monte-Carlo integration for the linear ballistic accumulator (LBA; Brown and Heathcote, 2008), a widely used evidence accumulation model. Bayes factors are used frequently for inference with simpler statistical models, and they do not require parameter estimation. In order to overcome the computational burden of estimating Bayes factors via brute force integration, we exploit general purpose graphical processing units; we provide free code for this. This approach allows estimation of Bayes factors via Monte-Carlo integration within a practical time frame. We demonstrate the method using both simulated and real data. We investigate the stability of the Monte-Carlo approximation, and the LBA's inferential properties, in simulation studies.

Supramolecular Recognition Allows Remote, Site-Selective C-H Oxidation of Methylenic Sites in Linear Amines.

PubMed

Olivo, Giorgio; Farinelli, Giulio; Barbieri, Alessia; Lanzalunga, Osvaldo; Di Stefano, Stefano; Costas, Miquel

2017-12-18

Site-selective C-H functionalization of aliphatic alkyl chains is a longstanding challenge in oxidation catalysis, given the comparable relative reactivity of the different methylenes. A supramolecular, bioinspired approach is described to address this challenge. A Mn complex able to catalyze C(sp 3 )-H hydroxylation with H 2 O 2 is equipped with 18-benzocrown-6 ether receptors that bind ammonium substrates via hydrogen bonding. Reversible pre-association of protonated primary aliphatic amines with the crown ether selectively exposes remote positions (C8 and C9) to the oxidizing unit, resulting in a site-selective oxidation. Remarkably, such control of selectivity retains its efficiency for a whole series of linear amines, overriding the intrinsic reactivity of C-H bonds, no matter the chain length. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

The use of ERTS/LANDSAT imagery in relation to airborne remote sensing for terrain analysis in western Queensland, Australia

NASA Technical Reports Server (NTRS)

Cole, M. M.; Wen-Jones, S. (Principal Investigator)

1976-01-01

The author has identified the following significant results. Series of linears were identified on the March imagery of Lady Annie-Mt. Gordon fault zone area. The series with a WSW-ENE orientation which is normal to the major structural units and also several linears with NNW-SSE orientation appears to be particularly important. Copper mineralization is known at several localities where these linears are intersected by faults. Automated outputs using supervised methods involving the selection of training sets selected by visual recognition of spectral signatures on the color composites obtained from combinations of MSS bands 4, 5 and 7 projected through appropriate filters, were generated.

Iterative usage of fixed and random effect models for powerful and efficient genome-wide association studies

USDA-ARS?s Scientific Manuscript database

False positives in a Genome-Wide Association Study (GWAS) can be effectively controlled by a fixed effect and random effect Mixed Linear Model (MLM) that incorporates population structure and kinship among individuals to adjust association tests on markers; however, the adjustment also compromises t...

A genome-wide survey reveals a deletion polymorphism associated with resistance to gastrointestinal nematodes in Angus cattle

USDA-ARS?s Scientific Manuscript database

Gastrointestinal (GI) nematode infections are a worldwide threat to animal health and production. In this study, we performed a genome-wide association study between copy number variations (CNV) and resistance to GI nematodes in an Angus cattle population. Using a linear regression analysis, we iden...

Control for Population Structure and Relatedness for Binary Traits in Genetic Association Studies via Logistic Mixed Models.

PubMed

Chen, Han; Wang, Chaolong; Conomos, Matthew P; Stilp, Adrienne M; Li, Zilin; Sofer, Tamar; Szpiro, Adam A; Chen, Wei; Brehm, John M; Celedón, Juan C; Redline, Susan; Papanicolaou, George J; Thornton, Timothy A; Laurie, Cathy C; Rice, Kenneth; Lin, Xihong

2016-04-07

Linear mixed models (LMMs) are widely used in genome-wide association studies (GWASs) to account for population structure and relatedness, for both continuous and binary traits. Motivated by the failure of LMMs to control type I errors in a GWAS of asthma, a binary trait, we show that LMMs are generally inappropriate for analyzing binary traits when population stratification leads to violation of the LMM's constant-residual variance assumption. To overcome this problem, we develop a computationally efficient logistic mixed model approach for genome-wide analysis of binary traits, the generalized linear mixed model association test (GMMAT). This approach fits a logistic mixed model once per GWAS and performs score tests under the null hypothesis of no association between a binary trait and individual genetic variants. We show in simulation studies and real data analysis that GMMAT effectively controls for population structure and relatedness when analyzing binary traits in a wide variety of study designs. Copyright © 2016 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Linear Covariance Analysis for a Lunar Lander

NASA Technical Reports Server (NTRS)

Jang, Jiann-Woei; Bhatt, Sagar; Fritz, Matthew; Woffinden, David; May, Darryl; Braden, Ellen; Hannan, Michael

2017-01-01

A next-generation lunar lander Guidance, Navigation, and Control (GNC) system, which includes a state-of-the-art optical sensor suite, is proposed in a concept design cycle. The design goal is to allow the lander to softly land within the prescribed landing precision. The achievement of this precision landing requirement depends on proper selection of the sensor suite. In this paper, a robust sensor selection procedure is demonstrated using a Linear Covariance (LinCov) analysis tool developed by Draper.

Inactivation, reactivation and regrowth of indigenous bacteria in reclaimed water after chlorine disinfection of a municipal wastewater treatment plant.

PubMed

Li, Dan; Zeng, Siyu; Gu, April Z; He, Miao; Shi, Hanchang

2013-07-01

Disinfection of reclaimed water prior to reuse is important to prevent the transmission of pathogens. Chlorine is a widely utilized disinfectant and as such is a leading contender for disinfection of reclaimed water. To understand the risks of chlorination resulting from the potential selection of pathogenic bacteria, the inactivation, reactivation and regrowth rates of indigenous bacteria were investigated in reclaimed water after chlorine disinfection. Inactivation of total coliforms, Enterococcus and Salmonella showed linear correlations, with constants of 0.1384, 0.1624 and 0.057 L/(mg.min) and R2 of 0.7617, 0.8316 and 0.845, respectively. However, inactivation of total viable cells by measurement of metabolic activity typically showed a linear correlation at lower chlorine dose (0-22 (mg-min)/L), and a trailing region with chlorine dose increasing from 22 to 69 (mg.min)/L. Reactivation and regrowth of bacteria were most likely to occur after exposure to lower chlorine doses, and extents of reactivation decreased gradually with increasing chlorine dose. In contrast to total coliforms and Enterococcus, Salmonella had a high level of regrowth and reactivation, and still had 2% regrowth even after chlorination of 69 (mg.min)/L and 24 hr storage. The bacterial compositions were also significantly altered by chlorination and storage of reclaimed water, and the ratio of Salmonella was significantly increased from 0.001% to 0.045% after chlorination of 69 (mg.min)/L and 24 hr storage. These trends indicated that chlorination contributes to the selection of chlorine-resistant pathogenic bacteria, and regrowth of pathogenic bacteria after chlorination in reclaimed water with a long retention time could threaten public health security during wastewater reuse.

Optical soliton solutions of the cubic-quintic non-linear Schrödinger's equation including an anti-cubic term

NASA Astrophysics Data System (ADS)

Kaplan, Melike; Hosseini, Kamyar; Samadani, Farzan; Raza, Nauman

2018-07-01

A wide range of problems in different fields of the applied sciences especially non-linear optics is described by non-linear Schrödinger's equations (NLSEs). In the present paper, a specific type of NLSEs known as the cubic-quintic non-linear Schrödinger's equation including an anti-cubic term has been studied. The generalized Kudryashov method along with symbolic computation package has been exerted to carry out this objective. As a consequence, a series of optical soliton solutions have formally been retrieved. It is corroborated that the generalized form of Kudryashov method is a direct, effectual, and reliable technique to deal with various types of non-linear Schrödinger's equations.

Accuracy enhancement of point triangulation probes for linear displacement measurement

NASA Astrophysics Data System (ADS)

Kim, Kyung-Chan; Kim, Jong-Ahn; Oh, SeBaek; Kim, Soo Hyun; Kwak, Yoon Keun

2000-03-01

Point triangulation probes (PTBs) fall into a general category of noncontact height or displacement measurement devices. PTBs are widely used for their simple structure, high resolution, and long operating range. However, there are several factors that must be taken into account in order to obtain high accuracy and reliability; measurement errors from inclinations of an object surface, probe signal fluctuations generated by speckle effects, power variation of a light source, electronic noises, and so on. In this paper, we propose a novel signal processing algorithm, named as EASDF (expanded average square difference function), for a newly designed PTB which is composed of an incoherent source (LED), a line scan array detector, a specially selected diffuse reflecting surface, and several optical components. The EASDF, which is a modified correlation function, is able to calculate displacement between the probe and the object surface effectively even if there are inclinations, power fluctuations, and noises.

Cosmic Dawn Intensity Mapper (CDIM): Instrument and Mission Design

NASA Astrophysics Data System (ADS)

Unwin, Stephen C.; CDIM Team

2018-01-01

CDIM is the Cosmic Dawn Intensity Mapper, one of the probe-class missions currently under study for NASA. A detailed Report from the study will be submitted to NASA and for consideration by the Decadal Survey. The flight system will comprise a wide-field cryogenic telescope with a large focal plane array providing complete coverage from optical through mid-IR. The system will be deployed to L2 or Earth-trailing orbit, to provide a stable thermal environment and allow extended observations of fields selected to be cross-correlated with deep surveys in other wavebands. Spectra with will be measured for every point in each target field, using linear variable filters (LVFs). These filters eliminate the need for a spectrometer in the focal plane. Spectra are built up through simple imaging of a series of telescope pointings separated by small angular offsets. This poster presents the initial concept for the instrument and mission design.

A Novel "Off-On" Fluorescent Probe Based on Carbon Nitride Nanoribbons for the Detection of Citrate Anion and Live Cell Imaging.

PubMed

Hu, Yanling; Yang, Donlgliang; Yang, Chen; Feng, Ning; Shao, Zhouwei; Zhang, Lei; Wang, Xiaodong; Weng, Lixing; Luo, Zhimin; Wang, Lianhui

2018-04-11

A novel fluorescent "off-on" probe based on carbon nitride (C₃N₄) nanoribbons was developed for citrate anion (C₆H₅O₇ 3- ) detection. The fluorescence of C₃N₄ nanoribbons can be quenched by Cu 2+ and then recovered by the addition of C₆H₅O₇ 3- , because the chelation between C₆H₅O₇ 3- and Cu 2+ blocks the electron transfer between Cu 2+ and C₃N₄ nanoribbons. The turn-on fluorescent sensor using this fluorescent "off-on" probe can detect C₆H₅O₇ 3- rapidly and selectively, showing a wide detection linear range (1~400 μM) and a low detection limit (0.78 μM) in aqueous solutions. Importantly, this C₃N₄ nanoribbon-based "off-on" probe exhibits good biocompatibility and can be used as fluorescent visualizer for exogenous C₆H₅O₇ 3- in HeLa cells.

High-performance electrochemical glucose sensing enabled by Cu(TCNQ) nanorod array

NASA Astrophysics Data System (ADS)

Wu, Xiufeng; Lu, Wenbo

2018-04-01

It is highly attractive to construct stable enzyme-free glucose sensors based on three-dimensional direct electrochemical detection of glucose. In this paper, a copper 7,7,8,8-tetracyanoquinodimethane (Cu(TCNQ)) nanorod array on Cu foam (Cu(TCNQ) NA/CF) is proposed as an efficient catalyst for electrochemical glucose oxidation in alkaline conditions. When Cu(TCNQ) NA/CF was used as the enzyme-free sensory of glucose, the sensor showed a response time within 3 s, a wide linear detection in the range 0.001-10.0 mM, the minimum limit of detection was as low as 10 nM (S/N = 3), and it had a high sensitivity of 26 987 μA mM-1 cm-2. Moreover, this sensor also possesses long-term stability, high selectivity, reproducibility, and actual applications for fresh human serum sample analysis is also successfully accepted.

Enhanced catalytic and dopamine sensing properties of electrochemically reduced conducting polymer nanocomposite doped with pure graphene oxide.

PubMed

Wang, Wenting; Xu, Guiyun; Cui, Xinyan Tracy; Sheng, Ge; Luo, Xiliang

2014-08-15

Significantly enhanced catalytic activity of a nanocomposite composed of conducting polymer poly (3,4-ethylenedioxythiophene) (PEDOT) doped with graphene oxide (GO) was achieved through a simple electrochemical reduction process. The nanocomposite (PEDOT/GO) was electrodeposited on an electrode and followed by electrochemical reduction, and the obtained reduced nanocomposite (PEDOT/RGO) modified electrode exhibited lowered electrochemical impedance and excellent electrocatalytic activity towards the oxidation of dopamine. Based on the excellent catalytic property of PEDOT/RGO, an electrochemical sensor capable of sensitive and selective detection of DA was developed. The fabricated sensor can detect DA in a wide linear range from 0.1 to 175μM, with a detection limit of 39nM, and it is free from common interferences such as uric acid and ascorbic acid. Copyright © 2014 Elsevier B.V. All rights reserved.

Tremella-like graphene-Au composites used for amperometric determination of dopamine.

PubMed

Li, Cong; Zhao, Jingyu; Yan, Xiaoyi; Gu, Yue; Liu, Weilu; Tang, Liu; Zheng, Bo; Li, Yaru; Chen, Ruixue; Zhang, Zhiquan

2015-03-21

Electrochemical detection of dopamine (DA) plays an important role in medical diagnosis. In this paper, tremella-like graphene-Au (t-GN-Au) composites were synthesized by a one-step hydrothermal method for selective detection of DA. Scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), Raman spectroscopy, and Fourier transform infrared (FTIR) spectroscopy were used to characterize as-prepared t-GN-Au composites. The t-GN-Au composites were directly used for the determination of DA via cyclic voltammetry (CV) and the chronoamperometry (CA) technique. CA measurement gave a wide linear range from 0.8 to 2000 μM, and the detection limit of 57 nM (S/N = 3) for DA. The mechanism and the heterogeneous electron transfer kinetics of the DA oxidation were discussed in the light of rotating disk electrode (RDE) experiments. Moreover, the modified electrode was applied to the determination of DA in human urine and serum samples.

Enantioselective construction of quaternary stereogenic carbon atoms by the Lewis base catalyzed additions of silyl ketene imines to aldehydes.

PubMed

Denmark, Scott E; Wilson, Tyler W; Burk, Matthew T

2014-07-21

Silyl ketene imines derived from a variety of α-branched nitriles have been developed as highly useful reagents for the construction of quaternary stereogenic centers via the aldol addition reaction. In the presence of SiCl4 and the catalytic action of a chiral phosphoramide, silyl ketene imines undergo extremely rapid and high yielding addition to a wide variety of aromatic aldehydes with excellent diastereo- and enantioselectivity. Of particular note are the high yields and selectivities obtained from electron-rich, electron-poor, and hindered aldehydes. Linear aliphatic aldehydes did react with good diastereo- and enantioselectivity in the presence of nBu4N(+)I(-), but branched aldehydes were much less reactive. Semiempirical calculations provided a rationalization of the observed diastereo- and enantioselectivity via open transitions states. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

All-Fiber Configuration Laser Self-Mixing Doppler Velocimeter Based on Distributed Feedback Fiber Laser

PubMed Central

Wu, Shuang; Wang, Dehui; Xiang, Rong; Zhou, Junfeng; Ma, Yangcheng; Gui, Huaqiao; Liu, Jianguo; Wang, Huanqin; Lu, Liang; Yu, Benli

2016-01-01

In this paper, a novel velocimeter based on laser self-mixing Doppler technology has been developed for speed measurement. The laser employed in our experiment is a distributed feedback (DFB) fiber laser, which is an all-fiber structure using only one Fiber Bragg Grating to realize optical feedback and wavelength selection. Self-mixing interference for optical velocity sensing is experimentally investigated in this novel system, and the experimental results show that the Doppler frequency is linearly proportional to the velocity of a moving target, which agrees with the theoretical analysis commendably. In our experimental system, the velocity measurement can be achieved in the range of 3.58 mm/s–2216 mm/s with a relative error under one percent, demonstrating that our novel all-fiber configuration velocimeter can implement wide-range velocity measurements with high accuracy. PMID:27472342

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

Ma, Xiang; Zhang, Shuai; Jiao, Fang

Two-step nucleation pathways in which disordered, amorphous, or dense liquid states precede appearance of crystalline phases have been reported for a wide range of materials, but the dynamics of such pathways are poorly understood. Moreover, whether these pathways are general features of crystallizing systems or a consequence of system-specific structural details that select for direct vs two-step processes is unknown. Using atomic force microscopy to directly observe crystallization of sequence-defined polymers, we show that crystallization pathways are indeed sequence dependent. When a short hydrophobic region is added to a sequence that directly forms crystalline particles, crystallization instead follows a two-stepmore » pathway that begins with creation of disordered clusters of 10-20 molecules and is characterized by highly non-linear crystallization kinetics in which clusters transform into ordered structures that then enter the growth phase. The results shed new light on non-classical crystallization mechanisms and have implications for design of self-assembling polymer systems.« less

Efficient Enzyme-Free Biomimetic Sensors for Natural Phenol Detection.

PubMed

Ferreira Garcia, Luane; Ribeiro Souza, Aparecido; Sanz Lobón, Germán; Dos Santos, Wallans Torres Pio; Alecrim, Morgana Fernandes; Fontes Santiago, Mariângela; de Sotomayor, Rafael Luque Álvarez; de Souza Gil, Eric

2016-08-13

The development of sensors and biosensors based on copper enzymes and/or copper oxides for phenol sensing is disclosed in this work. The electrochemical properties were studied by cyclic and differential pulse voltammetry using standard solutions of potassium ferrocyanide, phosphate/acetate buffers and representative natural phenols in a wide pH range (3.0 to 9.0). Among the natural phenols herein investigated, the highest sensitivity was observed for rutin, a powerful antioxidant widespread in functional foods and ubiquitous in the plant kingdom. The calibration curve for rutin performed at optimum pH (7.0) was linear in a broad concentration range, 1 to 120 µM (r = 0.99), showing detection limits of 0.4 µM. The optimized biomimetic sensor was also applied in total phenol determination in natural samples, exhibiting higher stability and sensitivity as well as distinct selectivity for antioxidant compounds.

Metallic layer-by-layer photonic crystals for linearly-polarized thermal emission and thermophotovoltaic device including same

DOEpatents

Lee, Jae-Hwang; Ho, Kai-Ming; Constant, Kristen P.

2016-07-26

Metallic thermal emitters consisting of two layers of differently structured nickel gratings on a homogeneous nickel layer are fabricated by soft lithography and studied for polarized thermal radiation. A thermal emitter in combination with a sub-wavelength grating shows a high extinction ratio, with a maximum value close to 5, in a wide mid-infrared range from 3.2 to 7.8 .mu.m, as well as high emissivity up to 0.65 at a wavelength of 3.7 .mu.m. All measurements show good agreement with theoretical predictions. Numerical simulations reveal that a high electric field exists within the localized air space surrounded by the gratings and the intensified electric-field is only observed for the polarizations perpendicular to the top sub-wavelength grating. This result suggests how the emissivity of a metal can be selectively enhanced at a certain range of wavelengths for a given polarization.

Colorimetric detection of trace copper ions based on catalytic leaching of silver-coated gold nanoparticles.

PubMed

Lou, Tingting; Chen, Lingxin; Chen, Zhaopeng; Wang, Yunqing; Chen, Ling; Li, Jinhua

2011-11-01

A colorimetric, label-free, and nonaggregation-based silver coated gold nanoparticles (Ag/Au NPs) probe has been developed for detection of trace Cu(2+) in aqueous solution, based on the fact that Cu(2+) can accelerate the leaching rate of Ag/Au NPs by thiosulfate (S(2)O(3)(2-)). The leaching of Ag/Au NPs would lead to dramatic decrease in the surface plasmon resonance (SPR) absorption as the size of Ag/Au NPs decreased. This colorimetric strategy based on size-dependence of nanoparticles during their leaching process provided a highly sensitive (1.0 nM) and selective detection toward Cu(2+), with a wide linear detection range (5-800 nM) over nearly 3 orders of magnitude. The cost-effective probe allows rapid and sensitive detection of trace Cu(2+) ions in water samples, indicating its potential applicability for the determination of copper in real samples.

Mango core inner shell membrane template-directed synthesis of porous ZnO films and their application for enzymatic glucose biosensor

NASA Astrophysics Data System (ADS)

Zhou, Yu; Wang, Lei; Ye, Zhizhen; Zhao, Minggang; Cai, Hui; Huang, Jingyun

2013-11-01

Micro/nano-porous ZnO films were synthesized through a simple biotemplate-directed method using mango core inner shell membranes as templates. The achieved ZnO films with wrinkles on the surface are combined of large holes and small pores in the bulk. High specific surface area, numerous microspaces, and small channels for fluid circulation provided by this unique structure along with the good biocompatibility and electron communication features of ZnO material make the product an ideal platform for the immobilization of enzymes The fabricated glucose biosensor based on the porous ZnO films exhibits good selective detection ability of analyte with good stability, high sensitivity of 50.58 μA cm-2 mM-1 and a wide linear range of 0.2-5.6 mM along with a low detection limit of 10 μM.

Kinetic modelling for zinc (II) ions biosorption onto Luffa cylindrica

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

Oboh, I., E-mail: innocentoboh@uniuyo.edu.ng; Aluyor, E.; Audu, T.

The biosorption of Zinc (II) ions onto a biomaterial - Luffa cylindrica has been studied. This biomaterial was characterized by elemental analysis, surface area, pore size distribution, scanning electron microscopy, and the biomaterial before and after sorption, was characterized by Fourier Transform Infra Red (FTIR) spectrometer. The kinetic nonlinear models fitted were Pseudo-first order, Pseudo-second order and Intra-particle diffusion. A comparison of non-linear regression method in selecting the kinetic model was made. Four error functions, namely coefficient of determination (R{sup 2}), hybrid fractional error function (HYBRID), average relative error (ARE), and sum of the errors squared (ERRSQ), were used tomore » predict the parameters of the kinetic models. The strength of this study is that a biomaterial with wide distribution particularly in the tropical world and which occurs as waste material could be put into effective utilization as a biosorbent to address a crucial environmental problem.« less

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

NASA Technical Reports Server (NTRS)

Huntsberger, Terry

2011-01-01

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

An electrochemical immunosensor for quantitative detection of ficolin-3

NASA Astrophysics Data System (ADS)

San, Lili; Zeng, Dongdong; Song, Shiping; Zuo, Xiaolei; Zhang, Huan; Wang, Chenguang; Wu, Jiarui; Mi, Xianqiang

2016-06-01

Diabetes mellitus (DM) is one of the most common metabolic disorders in the world, of which more than 90% is type-2 diabetes mellitus (T2DM). There is a rather urgent need for reliable, sensitive and quick detection techniques in clinical application of T2DM. Ficolin-3 is a potential biomarker of T2DM, because serum ficolin-3 levels are associated with insulin resistance and predict the incidence of T2DM. Herein, a sandwich-type electrochemical immunosensor was developed for the detection of ficolin-3 in human serum. Cyclic voltammetry and the amperometric current versus time were used to characterize the performance of the immunosensor. Under optimal conditions, the detection limitation of ficolin-3 was 100 ng ml-1 and the linear dynamic range was between 2 and 50 μg ml-1. The method has ideal accuracy, excellent stability and selectivity and has wide application prospects in clinical research.

A novel alcohol dehydrogenase biosensor based on solid-state electrogenerated chemiluminescence by assembling dehydrogenase to Ru(bpy)(3)2+-Au nanoparticles aggregates.

PubMed

Zhang, Lihua; Xu, Zhiai; Sun, Xuping; Dong, Shaojun

2007-01-15

Based on electrogenerated chemiluminescence (ECL), a novel method for fabrication of alcohol dehydrogenase (ADH) biosensor by self-assembling ADH to Ru(bpy)(3)(2+)-AuNPs aggregates (Ru-AuNPs) on indium tin oxide (ITO) electrode surface has been developed. Positively charged Ru(bpy)(3)(2+) could be immobilized stably on the electrode surface with negatively charged AuNPs in the form of aggregate via electrostatic interaction. On the other hand, AuNPs are favourable candidates for the immobilization of enzymes because amine groups and cysteine residues in the enzymes are known to bind strongly with AuNPs. Moreover, AuNPs can act as tiny conduction centers to facilitate the transfer of electrons. Such biosensor combined enzymatic selectivity with the sensitivity of ECL detection for quantification of enzyme substrate, and it displayed wide linear range, high sensitivity and good stability.

Kinetic modelling for zinc (II) ions biosorption onto Luffa cylindrica

NASA Astrophysics Data System (ADS)

Oboh, I.; Aluyor, E.; Audu, T.

2015-03-01

The biosorption of Zinc (II) ions onto a biomaterial - Luffa cylindrica has been studied. This biomaterial was characterized by elemental analysis, surface area, pore size distribution, scanning electron microscopy, and the biomaterial before and after sorption, was characterized by Fourier Transform Infra Red (FTIR) spectrometer. The kinetic nonlinear models fitted were Pseudo-first order, Pseudo-second order and Intra-particle diffusion. A comparison of non-linear regression method in selecting the kinetic model was made. Four error functions, namely coefficient of determination (R2), hybrid fractional error function (HYBRID), average relative error (ARE), and sum of the errors squared (ERRSQ), were used to predict the parameters of the kinetic models. The strength of this study is that a biomaterial with wide distribution particularly in the tropical world and which occurs as waste material could be put into effective utilization as a biosorbent to address a crucial environmental problem.

Eco-friendly surface modification on polyester fabrics by esterase treatment

NASA Astrophysics Data System (ADS)

Wu, Jindan; Cai, Guoqiang; Liu, Jinqiang; Ge, Huayun; Wang, Jiping

2014-03-01

Currently, traditional alkali deweighting technology is widely used to improve the hydrophilicity of polyester fabrics. However, the wastewater and heavy chemicals in the effluent cause enormous damage to the environment. Esterase treatment, which is feasible in mild conditions with high selectivity, can provide a clean and efficient way for polyester modification. Under the optimum conditions, the polyester fabric hydrolysis process of esterase had a linear kinetics. X-ray photoelectron spectrometry (XPS) results showed that hydroxyl and carboxyl groups were produced only on the surface of modified fiber without changing the chemical composition of the bulk. These fibers exhibited much improved fabric wicking, as well as greatly improved oily stain removal performance. Compared to the harsh alkali hydrolysis, the enzyme treatment led to smaller weight loss and better fiber integrity. The esterase treatment technology is promising to produce higher-quality polyester textiles with an environmental friendly approach.

Optogenetic Assessment of Horizontal Interactions in Primary Visual Cortex

PubMed Central

Huang, Xiaoying; Elyada, Yishai M.; Bosking, William H.; Walker, Theo

2014-01-01

Columnar organization of orientation selectivity and clustered horizontal connections linking orientation columns are two of the distinctive organizational features of primary visual cortex in many mammalian species. However, the functional role of these connections has been harder to characterize. Here we examine the extent and nature of horizontal interactions in V1 of the tree shrew using optical imaging of intrinsic signals, optogenetic stimulation, and multi-unit recording. Surprisingly, we find the effects of optogenetic stimulation depend primarily on distance and not on the specific orientation domains or axes in the cortex, which are stimulated. In addition, across a wide range of variation in both visual and optogenetic stimulation we find linear addition of the two inputs. These results emphasize that the cortex provides a rich substrate for functional interactions that are not limited to the orientation-specific interactions predicted by the monosynaptic distribution of horizontal connections. PMID:24695715

Spectral and angular characteristics of dielectric resonator metasurface at optical frequencies

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

Zou, Longfang; Department of Electrical and Electronic Engineering, The University of Bristol, Bristol, BS8 1TH; López-García, Martin

2014-11-10

The capability of manipulating light at subwavelength scale has fostered the applications of flat metasurfaces in various fields. Compared to metallic structure, metasurfaces made of high permittivity low-loss dielectric resonators hold the promise of high efficiency by avoiding high conductive losses of metals at optical frequencies. This letter investigates the spectral and angular characteristics of a dielectric resonator metasurface composed of periodic sub-arrays of resonators with a linearly varying phase response. The far-field response of the metasurface can be decomposed into the response of a single grating element (sub-array) and the grating arrangement response. The analysis also reveals that couplingmore » between resonators has a non-negligible impact on the angular response. Over a wide wavelength range, the simulated and measured angular characteristics of the metasurface provide a definite illustration of how different grating diffraction orders can be selectively suppressed or enhanced through antenna sub-array design.« less

Parameters selection in gene selection using Gaussian kernel support vector machines by genetic algorithm.

PubMed

Mao, Yong; Zhou, Xiao-Bo; Pi, Dao-Ying; Sun, You-Xian; Wong, Stephen T C

2005-10-01

In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying results by using conventional linear statistical methods. Recursive feature elimination based on support vector machine (SVM RFE) is an effective algorithm for gene selection and cancer classification, which are integrated into a consistent framework. In this paper, we propose a new method to select parameters of the aforementioned algorithm implemented with Gaussian kernel SVMs as better alternatives to the common practice of selecting the apparently best parameters by using a genetic algorithm to search for a couple of optimal parameter. Fast implementation issues for this method are also discussed for pragmatic reasons. The proposed method was tested on two representative hereditary breast cancer and acute leukaemia datasets. The experimental results indicate that the proposed method performs well in selecting genes and achieves high classification accuracies with these genes.

Inference of directed climate networks: role of instability of causality estimation methods

NASA Astrophysics Data System (ADS)

Hlinka, Jaroslav; Hartman, David; Vejmelka, Martin; Paluš, Milan

2013-04-01

Climate data are increasingly analyzed by complex network analysis methods, including graph-theoretical approaches [1]. For such analysis, links between localized nodes of climate network are typically quantified by some statistical measures of dependence (connectivity) between measured variables of interest. To obtain information on the directionality of the interactions in the networks, a wide range of methods exists. These can be broadly divided into linear and nonlinear methods, with some of the latter having the theoretical advantage of being model-free, and principally a generalization of the former [2]. However, as a trade-off, this generality comes together with lower accuracy - in particular if the system was close to linear. In an overall stationary system, this may potentially lead to higher variability in the nonlinear network estimates. Therefore, with the same control of false alarms, this may lead to lower sensitivity for detection of real changes in the network structure. These problems are discussed on the example of daily SAT and SLP data from the NCEP/NCAR reanalysis dataset. We first reduce the dimensionality of data using PCA with VARIMAX rotation to detect several dozens of components that together explain most of the data variability. We further construct directed climate networks applying a selection of most widely used methods - variants of linear Granger causality and conditional mutual information. Finally, we assess the stability of the detected directed climate networks by computing them in sliding time windows. To understand the origin of the observed instabilities and their range, we also apply the same procedure to two types of surrogate data: either with non-stationarity in network structure removed, or imposed in a controlled way. In general, the linear methods show stable results in terms of overall similarity of directed climate networks inferred. For instance, for different decades of SAT data, the Spearman correlation of edge weights in the networks is ~ 0.6. The networks constructed using nonlinear measures were in general less stable both in real data and stationarized surrogates. Interestingly, when the nonlinear method parameters are optimized with respect to temporal stability of the networks, the networks seem to converge close to those detected by linear Granger causality. This provides further evidence for the hypothesis of overall sparsity and weakness of nonlinear coupling in climate networks on this spatial and temporal scale [3] and sufficient support for the use of linear methods in this context, unless specific clearly detectable nonlinear phenomena are targeted. Acknowledgement: This study is supported by the Czech Science Foundation, Project No. P103/11/J068. [1] Boccaletti, S.; Latora, V.; Moreno, Y.; Chavez, M. & Hwang, D. U.: Complex networks: Structure and dynamics, Physics Reports, 2006, 424, 175-308 [2] Barnett, L.; Barrett, A. B. & Seth, A. K.: Granger Causality and Transfer Entropy Are Equivalent for Gaussian Variables, Physical Review Letters, 2009, 103, 238701 [3] Hlinka, J.; Hartman, D.; Vejmelka, M.; Novotná, D.; Paluš, M.: Non-linear dependence and teleconnections in climate data: sources, relevance, nonstationarity, submitted preprint (http://arxiv.org/abs/1211.6688)

Survey of organosilicone compounds, including cyclic and linear siloxanes, in personal-care and household products.

PubMed

Horii, Yuichi; Kannan, Kurunthachalam

2008-11-01

The determination of organosiloxanes in consumer products is important for the evaluation and characterization of sources of human and environmental exposures. In this study, we determined concentrations of cyclic siloxanes [octamethylcyclotetrasiloxane (D(4)), decamethylcyclopentasiloxane (D(5)), dodecamethylcyclohexasiloxane (D(6))], tetradecamethylcycloheptasiloxane (D(7))] and linear siloxanes (L(4) to L(14)) in a variety of consumer products (n = 76), including hair-care products, skin lotions, body washes, cosmetics, nursing nipples (i.e., pacifiers), cookware, and household sanitation products such as cleansers and furniture polishes, using gas chromatography-mass spectrometry with selected ion monitoring. Prior to the analysis of samples, a method was developed to reduce the contamination arising from organosiloxanes present in certain gas chromatograph (GC) parts, such as the inlet septum; use of a Restek BTO septum at an inlet temperature of 200 degrees C gave the lowest background level (D(4): 0.8 pg; D(5): 0.3 pg; D(6): 0.2 pg). Concentrations of cyclic siloxanes in consumer products analyzed ranged from <0.35 to 9380 microg/g, from <0.39 to 81,800 microg/g, from <0.33 to 43,100 microg/g, and from <0.42 to 846 microg/g for D(4), D(5), D(6), and D(7), respectively. Concentrations of linear siloxanes varied from <0.059 to 73,000 microg/g. More than 50% of the samples analyzed contained D(4), D(5), or D(6). Cyclic siloxanes were predominant in most of the sample categories; D(5) was predominant in hair-care products, skin lotions, and cosmetics; D(6) or D(7) was predominant in rubber products, including nipples, cookware, and sealants. Potential daily exposure to total organosiloxanes (sum of cyclic and linear siloxanes) from the use of personal-care products by adult women in the United States has been estimated to be 307 mg. Significant positive correlations (p < 0.01) existed in our study between D(4) and D(7), D(4) and linear siloxanes, D(5) and D(6), and D(5) and linear siloxanes. The correlations can be related to the composition of organosiloxanes used in consumer products. The results of our study suggest that a wide variety of consumer products that are used on a daily basis contain cyclic and linear siloxanes and these products can contribute considerably to human exposures.

Hierarchical hybrid film of MnO2 nanoparticles/multi-walled fullerene nanotubes-graphene for highly selective sensing of hydrogen peroxide.

PubMed

Pan, Yang; Hou, Zhaohui; Yi, Wei; Zhu, Wei; Zeng, Fanyan; Liu, You-Nian

2015-08-15

Hierarchical hybrid films of MnO2 nanoparticles/multi-walled fullerene nanotubes-graphene (MNPs/MWFNTs-GS) have been prepared via a simple wet-chemical method. For this purpose, MWFNTs (~300nm in length) are fabricated from tailoring multi-walled carbon nanotubes (MWCNTs), and then inserted into GS to pile up into a hierarchical hybrid film with the in situ formative MNPs. Scanning electron microscope, transmission electron microscope and X-ray diffraction are used to confirm the morphology and structure of the as-obtained film. The electrochemical studies reveal that MNPs/MWFNTs-GS exhibit significantly enhanced electrocatalytic activity compared with MNPs/GS, and show a rapid response to H2O2 over a wide linear range of 2.0μM-8.44mM with a high sensitivity of 206.3μA mM(-1)cm(-2) and an excellent selectivity. These favorable electrochemical detection properties may be mainly attributed to the introduction of MWFNTs, which helps to promote the electron/ion transport between MNPs and GS and form the hierarchical film structure. Copyright © 2015 Elsevier B.V. All rights reserved.

A sensitive plasmonic copper(II) sensor based on gold nanoparticles deposited on ITO glass substrate.

PubMed

Ding, Lijun; Gao, Yan; Di, Junwei

2016-09-15

Gold nanoparticles (Au NPs) based plasmonic probe was developed for sensitive and selective detection of Cu(2+) ion. The Au NPs were self-assembled on transparent indium tin oxide (ITO) film coated glass substrate using poly dimethyl diallyl ammonium chloride (PDDA) as a linker and then calcined at 400°C to obtain pure Au NPs on ITO surface (ITO/Au NPs). The probe was fabricated by functionalizing l-cysteine (Cys) on to gold surface (ITO/Au NPs/Cys). The strong chelation of Cu(2+) with Cys formed a stable Cys-Cu complex, and resulted in the red-shift of localized surface plasmon resonance (LSPR) peak of the Au NPs. The introduction of bovine serum albumin (BSA) as the second complexant could form complex of Cys-Cu-BAS and further markedly enhanced the red-shift of the LSPR peak. This plasmonic probe provided a highly sensitive and selective detection towards Cu(2+) ions, with a wide linear detection range (10(-11)-10(-5)M) over 6 orders of magnitude. The simple and cost-effective probe was successfully applied to the determination of Cu(2+) in real samples. Copyright © 2016 Elsevier B.V. All rights reserved.

The effects of run-of-river hydroelectric power schemes on invertebrate community composition in temperate streams and rivers.

PubMed

Bilotta, Gary S; Burnside, Niall G; Turley, Matthew D; Gray, Jeremy C; Orr, Harriet G

2017-01-01

Run-of-river (ROR) hydroelectric power (HEP) schemes are often presumed to be less ecologically damaging than large-scale storage HEP schemes. However, there is currently limited scientific evidence on their ecological impact. The aim of this article is to investigate the effects of ROR HEP schemes on communities of invertebrates in temperate streams and rivers, using a multi-site Before-After, Control-Impact (BACI) study design. The study makes use of routine environmental surveillance data collected as part of long-term national and international monitoring programmes at 22 systematically-selected ROR HEP schemes and 22 systematically-selected paired control sites. Five widely-used family-level invertebrate metrics (richness, evenness, LIFE, E-PSI, WHPT) were analysed using a linear mixed effects model. The analyses showed that there was a statistically significant effect (p<0.05) of ROR HEP construction and operation on the evenness of the invertebrate community. However, no statistically significant effects were detected on the four other metrics of community composition. The implications of these findings are discussed in this article and recommendations are made for best-practice study design for future invertebrate community impact studies.

The effects of run-of-river hydroelectric power schemes on invertebrate community composition in temperate streams and rivers

PubMed Central

2017-01-01

Run-of-river (ROR) hydroelectric power (HEP) schemes are often presumed to be less ecologically damaging than large-scale storage HEP schemes. However, there is currently limited scientific evidence on their ecological impact. The aim of this article is to investigate the effects of ROR HEP schemes on communities of invertebrates in temperate streams and rivers, using a multi-site Before-After, Control-Impact (BACI) study design. The study makes use of routine environmental surveillance data collected as part of long-term national and international monitoring programmes at 22 systematically-selected ROR HEP schemes and 22 systematically-selected paired control sites. Five widely-used family-level invertebrate metrics (richness, evenness, LIFE, E-PSI, WHPT) were analysed using a linear mixed effects model. The analyses showed that there was a statistically significant effect (p<0.05) of ROR HEP construction and operation on the evenness of the invertebrate community. However, no statistically significant effects were detected on the four other metrics of community composition. The implications of these findings are discussed in this article and recommendations are made for best-practice study design for future invertebrate community impact studies. PMID:28158282

Fluorographene based Ultrasensitive Ammonia Sensor

PubMed Central

Tadi, Kiran Kumar; Pal, Shubhadeep; Narayanan, Tharangattu N.

2016-01-01

Single molecule detection using graphene can be brought by tuning the interactions via specific dopants. Electrostatic interaction between the most electronegative element fluorine (F) and hydrogen (H) is one of the strong interactions in hydrogen bonding, and here we report the selective binding of ammonia/ammonium with F in fluorographene (FG) resulting to a change in the impedance of the system. Very low limit of detection value of ~0.44 pM with linearity over wide range of concentrations (1 pM–0.1 μM) is achieved using the FG based impedance sensor, andthisscreen printed FG sensor works in both ionized (ammonium) and un-ionized ammonia sensing platforms. The interaction energies of FG and NH3/NH4+ are evaluated using density functional theory calculations and the interactions are mapped. Here FGs with two different amounts of fluorinecontents −~5 atomic% (C39H16F2) and ~24 atomic% (C39H16F12) - are theoretically and experimentally studied for selective, high sensitive and ultra-low level detection of ammonia. Fast responding, high sensitive, large area patternable FG based sensor platform demonstrated here can open new avenues for the development of point-of-care devices and clinical sensors. PMID:27142522

The REgolith X-Ray Imaging Spectrometer (REXIS) for OSIRIS-REx: identifying regional elemental enrichment on asteroids

NASA Astrophysics Data System (ADS)

Allen, Branden; Grindlay, Jonathan; Hong, Jaesub; Binzel, Richard P.; Masterson, Rebecca; Inamdar, Niraj K.; Chodas, Mark; Smith, Matthew W.; Bautz, Marshall W.; Kissel, Steven E.; Villasenor, Joel; Oprescu, Miruna; Induni, Nicholas

2013-09-01

The OSIRIS-REx Mission was selected under the NASA New Frontiers program and is scheduled for launch in September of 2016 for a rendezvous with, and collection of a sample from the surface of asteroid Bennu in 2019. 101955 Bennu (previously 1999 RQ36) is an Apollo (near-Earth) asteroid originally discovered by the LINEAR project in 1999 which has since been classified as a potentially hazardous near-Earth object. The REgolith X-Ray Imaging Spectrometer (REXIS) was proposed jointly by MIT and Harvard and was subsequently accepted as a student led instrument for the determination of the elemental composition of the asteroid's surface as well as the surface distribution of select elements through solar induced X-ray fluorescence. REXIS consists of a detector plane that contains 4 X-ray CCDs integrated into a wide field coded aperture telescope with a focal length of 20 em for the detection of regions with enhanced abundance in key elements at 50 m scales. Elemental surface distributions of approximately 50-200 m scales can be detected using the instrument as a simple collimator. An overview of the observation strategy of the REXIS instrument and expected performance are presented here.

Functional CuO Microstructures for Glucose Sensing

NASA Astrophysics Data System (ADS)

Ali, Gulzar; Tahira, Aneela; Mallah, Arfana Begum; Mallah, Sarfraz Ahmed; Ibupoto, Akila; Khand, Aftab Ahmed; Baradi, Waryani; Willander, Magnus; Yu, Cong; Ibupoto, Zafar Hussain

2018-02-01

CuO microstructures are produced in the presence of water-soluble amino acids by hydrothermal method. The used amino acids include isoleucine, alpha alanine, and arginine as a soft template and are used for tuning the morphology of CuO nanostructures. The crystalline and morphological investigations were carried out by x-ray diffraction (XRD) and scanning electron microscopy techniques. The XRD study has shown that CuO material obtained in the presence of different amino acids is of high purity and all have the same crystal phase. The CuO microstructures prepared in the presence of arginine were used for the development of sensitive and selective glucose biosensor. The linear range for the glucose detection are from 0.001 mM to 30 mM and limit of detection was found to be 0.0005 mM. The sensitivity was estimated around 77 mV/decade. The developed biosensor is highly selective, sensitive, stable and reproducible. The glucose biosensor was used for the determination of real human blood samples and the obtained results are satisfactory. The CuO material is functional therefore can be capitalized in wide range of applications such as lithium ion batteries, all oxide solar cells and supercapacitors.

Two-dimensional ytterbium oxide nanodisks based biosensor for selective detection of urea.

PubMed

Ibrahim, Ahmed A; Ahmad, Rafiq; Umar, Ahmad; Al-Assiri, M S; Al-Salami, A E; Kumar, Rajesh; Ansari, S G; Baskoutas, S

2017-12-15

Herein, we demonstrate synthesis and application of two-dimensional (2D) rectangular ytterbium oxide (Yb 2 O 3 ) nanodisks via a facile hydrothermal method. The structural, morphological, compositional, crystallinity, and phase properties of as-synthesized nanodisks were carried out using several analytical techniques that showed well defined 2D rectangular nanodisks/sheet like morphologies. The average thickness and edge length of the nanosheet structures were 20 ± 5nm and 600 ± 50nm, respectively. To develop urea biosensor, glassy carbon electrodes (GCE) were modified with Yb 2 O 3 nanodisks, followed by urease immobilization and Nafion membrane covering (GCE/Yb 2 O 3 /Urease/Nafion). The fabricated biosensor showed sensitivity of 124.84μAmM -1 cm -2 , wide linear range of 0.05-19mM, detection limit down to ~ 2μM, and fast response time of ~ 3s. The developed biosensor was also used for the urea detection in water samples through spike-recovery experiments, which illustrates satisfactory recoveries. In addition, the obtained desirable selectivity towards specific interfering species, long-term stability, reproducibility, and repeatability further confirm the potency of as-fabricated urea biosensor. Copyright © 2017 Elsevier B.V. All rights reserved.

Simultaneous determination of multiclass preservatives including isothiazolinones and benzophenone-type UV filters in household and personal care products by micellar electrokinetic chromatography.

PubMed

Lopez-Gazpio, Josu; Garcia-Arrona, Rosa; Millán, Esmeralda

2015-04-01

In this work, a simple and reliable micellar electrokinetic chromatography method for the separation and quantification of 14 preservatives, including isothiazolinones, and two benzophenone-type UV filters in household, cosmetic and personal care products was developed. The selected priority compounds are widely used as ingredients in many personal care products, and are included in the European Regulation concerning cosmetic products. The electrophoretic separation parameters were optimized by means of a modified chromatographic response function in combination with an experimental design, namely a central composite design. After optimization of experimental conditions, the BGE selected for the separation of the targets consisted of 60 mM SDS, 18 mM sodium tetraborate, pH 9.4 and 10% v/v methanol. The MEKC method was checked in terms of linearity, LODs and quantification, repeatability, intermediate precision, and accuracy, providing appropriate values (i.e. R(2) ≥ 0.992, repeatability RSD values ˂9%, and accuracy 90-115%). Applicability of the validated method was successfully assessed by quantifying preservatives and UV filters in commercial consumer products. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An efficient empirical Bayes method for genomewide association studies.

PubMed

Wang, Q; Wei, J; Pan, Y; Xu, S

2016-08-01

Linear mixed model (LMM) is one of the most popular methods for genomewide association studies (GWAS). Numerous forms of LMM have been developed; however, there are two major issues in GWAS that have not been fully addressed before. The two issues are (i) the genomic background noise and (ii) low statistical power after Bonferroni correction. We proposed an empirical Bayes (EB) method by assigning each marker effect a normal prior distribution, resulting in shrinkage estimates of marker effects. We found that such a shrinkage approach can selectively shrink marker effects and reduce the noise level to zero for majority of non-associated markers. In the meantime, the EB method allows us to use an 'effective number of tests' to perform Bonferroni correction for multiple tests. Simulation studies for both human and pig data showed that EB method can significantly increase statistical power compared with the widely used exact GWAS methods, such as GEMMA and FaST-LMM-Select. Real data analyses in human breast cancer identified improved detection signals for markers previously known to be associated with breast cancer. We therefore believe that EB method is a valuable tool for identifying the genetic basis of complex traits. © 2015 Blackwell Verlag GmbH.

Spanish normative studies in young adults (NEURONORMA young adults project): norms for the Rey-Osterrieth Complex Figure (copy and memory) and Free and Cued Selective Reminding Test.

PubMed

Palomo, R; Casals-Coll, M; Sánchez-Benavides, G; Quintana, M; Manero, R M; Rognoni, T; Calvo, L; Aranciva, F; Tamayo, F; Peña-Casanova, J

2013-05-01

The Rey-Osterrieth Complex Figure (ROCF) and the Free and Cued Selective Reminding Test (FCSRT) are widely used in clinical practice. The ROCF assesses visual perception, constructional praxis, and visuo-spatial memory. The FCSRT assesses verbal learning and memory. In this study, as part of the Spanish normative studies project in young adults (NEURONORMA young adults), we present age- and education-adjusted normative data for both tests obtained by using linear regression techniques. The sample consisted of 179 healthy participants ranging in age from 18 to 49 years. We provide tables for converting raw scores to scaled scores in addition to tables with scores adjusted by socio-demographic factors. The results showed that education affects scores for some of the memory tests and the figure-copying task. Age was only found to have an effect on the performance of visuo-spatial memory tests, and the effect of sex was negligible. The normative data obtained will be extremely useful in the clinical neuropsychological evaluation of young Spanish adults. Copyright © 2011 Sociedad Española de Neurología. Published by Elsevier Espana. All rights reserved.

Solution Process Synthesis of High Aspect Ratio ZnO Nanorods on Electrode Surface for Sensitive Electrochemical Detection of Uric Acid

NASA Astrophysics Data System (ADS)

Ahmad, Rafiq; Tripathy, Nirmalya; Ahn, Min-Sang; Hahn, Yoon-Bong

2017-04-01

This study demonstrates a highly stable, selective and sensitive uric acid (UA) biosensor based on high aspect ratio zinc oxide nanorods (ZNRs) vertical grown on electrode surface via a simple one-step low temperature solution route. Uricase enzyme was immobilized on the ZNRs followed by Nafion covering to fabricate UA sensing electrodes (Nafion/Uricase-ZNRs/Ag). The fabricated electrodes showed enhanced performance with attractive analytical response, such as a high sensitivity of 239.67 μA cm-2 mM-1 in wide-linear range (0.01-4.56 mM), rapid response time (~3 s), low detection limit (5 nM), and low value of apparent Michaelis-Menten constant (Kmapp, 0.025 mM). In addition, selectivity, reproducibility and long-term storage stability of biosensor was also demonstrated. These results can be attributed to the high aspect ratio of vertically grown ZNRs which provides high surface area leading to enhanced enzyme immobilization, high electrocatalytic activity, and direct electron transfer during electrochemical detection of UA. We expect that this biosensor platform will be advantageous to fabricate ultrasensitive, robust, low-cost sensing device for numerous analyte detection.

Chemically modified carbon paste and membrane sensors for the determination of benzethonium chloride and some anionic surfactants (SLES, SDS, and LABSA): Characterization using SEM and AFM.

PubMed

Issa, Yousry M; Mohamed, Sabrein H; Baset, Mohamed Abd-El

2016-08-01

Chemically modified carbon-paste (CMCP) and membrane- sensors based on incorporating benzothonium-tetraphenylborate (BT-TPB) were constructed for the analysis of benzethonium chloride, and some other surfactants such as sodium lauryl ether sulphate (SLES), sodium dodecyl sulphate (SDS), and linear alkylbenzene sulphonic acid (LABSA). All sensors showed good sensitivity and reverse wide linearity over a concentration range of 5.97×10(-7) to 1.00×10(-3) and 5.96×10(-7) to 3.03×10(-3)molL(-1) with limit of detection of 3.92×10(-7)and 3.40×10(-7)molL(-1) for membrane and chemically modified carbon paste sensors, respectively, with respect to benzethonium chloride (BT.Cl). They could be used over a wide pH range of 2.0-10.0. The thermal coefficients of membrane and CMCP sensors are 5.40×10(-4), 1.17×10(-4)V/°C, respectively. The sensors indicated a wide selectivity over different inorganic cations. The effect of soaking on the surface morphology of the membrane sensor was studied using EDX-SEM and AFM techniques. The response time was <10s The freshly prepared, exhausted membrane, and CMCP sensors were successfully applied for the potentiometric determination of the pure BT.Cl solution. They were also used for the determination of its pharmaceutical formulation Dermoplast(®) antibacterial spray (20% benzocaine+0.2% benzethonium chloride) with recovery values ranging from 97.54±1.70 to 101.25±1.12 and from 96.32±2.49 to 101.23±2.15%. The second goal of these sensors is the potentiometric determination of different surfactants such as SLES, SDS, and LABSA with good recovery values using BT.Cl as a titrant in their pure forms, and in samples containing one of them (shampoo, Touri(®) dishwashing liquid, and waste water). The statistical analysis of the obtained data was studied. Copyright © 2016 Elsevier B.V. All rights reserved.

Performance Testing of a High Temperature Linear Alternator for Stirling Convertors

NASA Technical Reports Server (NTRS)

Metscher, Jonathan; Geng, Steven

2016-01-01

The NASA Glenn Research Center has conducted performance testing of a high temperature linear alternator (HTLA) in support of Stirling power convertor development for potential future Radioisotope Power Systems (RPS). The high temperature linear alternator is a modified version of that used in Sunpowers Advanced Stirling Convertor (ASC), and is capable of operation at temperatures up to 200 C. Increasing the temperature capability of the linear alternator could expand the mission space of future Stirling RPS designs. High temperature Neodymium-Iron-Boron (Nd-Fe-B) magnets were selected for the HTLA application, and were fully characterized and tested prior to uses. Higher temperature epoxy for alternator assembly was also selected and tested for thermal stability and strength. A characterization test was performed on the HTLA to measure its performance at various amplitudes, loads, and temperatures. HTLA endurance testing at 200 C is currently underway.

Performance Testing of a High Temperature Linear Alternator for Stirling Convertors

NASA Technical Reports Server (NTRS)

Metscher, Jonathan F.; Geng, Steven M.

2016-01-01

The NASA Glenn Research Center has conducted performance testing of a high temperature linear alternator (HTLA) in support of Stirling power convertor development for potential future Radioisotope Power Systems (RPS). The high temperature linear alternator is a modified version of that used in Sunpower's Advanced Stirling Convertor (ASC), and is capable of operation at temperatures up to 200 deg. Increasing the temperature capability of the linear alternator could expand the mission set of future Stirling RPS designs. High temperature Neodymium-Iron-Boron (Nd-Fe-B) magnets were selected for the HTLA application, and were fully characterized and tested prior to use. Higher temperature epoxy for alternator assembly was also selected and tested for thermal stability and strength. A characterization test was performed on the HTLA to measure its performance at various amplitudes, loads, and temperatures. HTLA endurance testing at 200 deg is currently underway.

LINEAR COUNT-RATE METER

DOEpatents

Henry, J.J.

1961-09-01

A linear count-rate meter is designed to provide a highly linear output while receiving counting rates from one cycle per second to 100,000 cycles per second. Input pulses enter a linear discriminator and then are fed to a trigger circuit which produces positive pulses of uniform width and amplitude. The trigger circuit is connected to a one-shot multivibrator. The multivibrator output pulses have a selected width. Feedback means are provided for preventing transistor saturation in the multivibrator which improves the rise and decay times of the output pulses. The multivibrator is connected to a diode-switched, constant current metering circuit. A selected constant current is switched to an averaging circuit for each pulse received, and for a time determined by the received pulse width. The average output meter current is proportional to the product of the counting rate, the constant current, and the multivibrator output pulse width.

Genomic and pedigree-based prediction for leaf, stem, and stripe rust resistance in wheat.

PubMed

Juliana, Philomin; Singh, Ravi P; Singh, Pawan K; Crossa, Jose; Huerta-Espino, Julio; Lan, Caixia; Bhavani, Sridhar; Rutkoski, Jessica E; Poland, Jesse A; Bergstrom, Gary C; Sorrells, Mark E

2017-07-01

Genomic prediction for seedling and adult plant resistance to wheat rusts was compared to prediction using few markers as fixed effects in a least-squares approach and pedigree-based prediction. The unceasing plant-pathogen arms race and ephemeral nature of some rust resistance genes have been challenging for wheat (Triticum aestivum L.) breeding programs and farmers. Hence, it is important to devise strategies for effective evaluation and exploitation of quantitative rust resistance. One promising approach that could accelerate gain from selection for rust resistance is 'genomic selection' which utilizes dense genome-wide markers to estimate the breeding values (BVs) for quantitative traits. Our objective was to compare three genomic prediction models including genomic best linear unbiased prediction (GBLUP), GBLUP A that was GBLUP with selected loci as fixed effects and reproducing kernel Hilbert spaces-markers (RKHS-M) with least-squares (LS) approach, RKHS-pedigree (RKHS-P), and RKHS markers and pedigree (RKHS-MP) to determine the BVs for seedling and/or adult plant resistance (APR) to leaf rust (LR), stem rust (SR), and stripe rust (YR). The 333 lines in the 45th IBWSN and the 313 lines in the 46th IBWSN were genotyped using genotyping-by-sequencing and phenotyped in replicated trials. The mean prediction accuracies ranged from 0.31-0.74 for LR seedling, 0.12-0.56 for LR APR, 0.31-0.65 for SR APR, 0.70-0.78 for YR seedling, and 0.34-0.71 for YR APR. For most datasets, the RKHS-MP model gave the highest accuracies, while LS gave the lowest. GBLUP, GBLUP A, RKHS-M, and RKHS-P models gave similar accuracies. Using genome-wide marker-based models resulted in an average of 42% increase in accuracy over LS. We conclude that GS is a promising approach for improvement of quantitative rust resistance and can be implemented in the breeding pipeline.

On the Linear Relation between the Mean and the Standard Deviation of a Response Time Distribution

ERIC Educational Resources Information Center

Wagenmakers, Eric-Jan; Brown, Scott

2007-01-01

Although it is generally accepted that the spread of a response time (RT) distribution increases with the mean, the precise nature of this relation remains relatively unexplored. The authors show that in several descriptive RT distributions, the standard deviation increases linearly with the mean. Results from a wide range of tasks from different…

Two Hop Adaptive Vector Based Quality Forwarding for Void Hole Avoidance in Underwater WSNs

PubMed Central

Javaid, Nadeem; Ahmed, Farwa; Wadud, Zahid; Alrajeh, Nabil; Alabed, Mohamad Souheil; Ilahi, Manzoor

2017-01-01

Underwater wireless sensor networks (UWSNs) facilitate a wide range of aquatic applications in various domains. However, the harsh underwater environment poses challenges like low bandwidth, long propagation delay, high bit error rate, high deployment cost, irregular topological structure, etc. Node mobility and the uneven distribution of sensor nodes create void holes in UWSNs. Void hole creation has become a critical issue in UWSNs, as it severely affects the network performance. Avoiding void hole creation benefits better coverage over an area, less energy consumption in the network and high throughput. For this purpose, minimization of void hole probability particularly in local sparse regions is focused on in this paper. The two-hop adaptive hop by hop vector-based forwarding (2hop-AHH-VBF) protocol aims to avoid the void hole with the help of two-hop neighbor node information. The other protocol, quality forwarding adaptive hop by hop vector-based forwarding (QF-AHH-VBF), selects an optimal forwarder based on the composite priority function. QF-AHH-VBF improves network good-put because of optimal forwarder selection. QF-AHH-VBF aims to reduce void hole probability by optimally selecting next hop forwarders. To attain better network performance, mathematical problem formulation based on linear programming is performed. Simulation results show that by opting these mechanisms, significant reduction in end-to-end delay and better throughput are achieved in the network. PMID:28763014

Collagen-Gold Nanoparticle Conjugates for Versatile Biosensing

PubMed Central

Unser, Sarah; Holcomb, Samuel; Cary, ReJeana; Sagle, Laura

2017-01-01

Integration of noble metal nanoparticles with proteins offers promising potential to create a wide variety of biosensors that possess both improved selectivity and versatility. The multitude of functionalities that proteins offer coupled with the unique optical properties of noble metal nanoparticles can allow for the realization of simple, colorimetric sensors for a significantly larger range of targets. Herein, we integrate the structural protein collagen with 10 nm gold nanoparticles to develop a protein-nanoparticle conjugate which possess the functionality of the protein with the desired colorimetric properties of the nanoparticles. Applying the many interactions that collagen undergoes in the extracellular matrix, we are able to selectively detect both glucose and heparin with the same collagen-nanoparticle conjugate. Glucose is directly detected through the cross-linking of the collagen fibrils, which brings the attached nanoparticles into closer proximity, leading to a red-shift in the LSPR frequency. Conversely, heparin is detected through a competition assay in which heparin-gold nanoparticles are added to solution and compete with heparin in the solution for the binding sites on the collagen fibrils. The collagen-nanoparticle conjugates are shown to detect both glucose and heparin in the physiological range. Lastly, glucose is selectively detected in 50% mouse serum with the collagen-nanoparticle devices possessing a linear range of 3–25 mM, which is also within the physiologically relevant range. PMID:28212282

Two Hop Adaptive Vector Based Quality Forwarding for Void Hole Avoidance in Underwater WSNs.

PubMed

Javaid, Nadeem; Ahmed, Farwa; Wadud, Zahid; Alrajeh, Nabil; Alabed, Mohamad Souheil; Ilahi, Manzoor

2017-08-01

Underwater wireless sensor networks (UWSNs) facilitate a wide range of aquatic applications in various domains. However, the harsh underwater environment poses challenges like low bandwidth, long propagation delay, high bit error rate, high deployment cost, irregular topological structure, etc. Node mobility and the uneven distribution of sensor nodes create void holes in UWSNs. Void hole creation has become a critical issue in UWSNs, as it severely affects the network performance. Avoiding void hole creation benefits better coverage over an area, less energy consumption in the network and high throughput. For this purpose, minimization of void hole probability particularly in local sparse regions is focused on in this paper. The two-hop adaptive hop by hop vector-based forwarding (2hop-AHH-VBF) protocol aims to avoid the void hole with the help of two-hop neighbor node information. The other protocol, quality forwarding adaptive hop by hop vector-based forwarding (QF-AHH-VBF), selects an optimal forwarder based on the composite priority function. QF-AHH-VBF improves network good-put because of optimal forwarder selection. QF-AHH-VBF aims to reduce void hole probability by optimally selecting next hop forwarders. To attain better network performance, mathematical problem formulation based on linear programming is performed. Simulation results show that by opting these mechanisms, significant reduction in end-to-end delay and better throughput are achieved in the network.

Selection of phage-displayed peptides for the detection of imidacloprid in water and soil.

PubMed

Liu, Zhiping; Liu, Jianfeng; Wang, Kai; Li, Wenhui; Shelver, Weilin L; Li, Qing X; Li, Ji; Xu, Ting

2015-09-15

Imidacloprid is the most widely used neonicotinoid insecticide in the world and shows widespread environment and human exposures. A phage clone designated L7-1 that selectively binds to imidacloprid was selected from a commercial phage display library containing linear 7-mer randomized amino acid residues. Using the clone L7-1, a competitive enzyme-linked immunosorbent assay (ELISA) for imidacloprid was developed. The half-maximum signal inhibition concentration (IC50) and the limit of detection (LOD) of the phage ELISA for imidacloprid were 96 and 2.3 ng ml(-1), respectively. This phage ELISA showed relatively low cross-reactivity with all of the tested compounds structurally similar to imidacloprid, less than 2% with the exception of 6-chloronicotinic acid, a metabolite of imidacloprid that showed 11.5%. The average recoveries of the phage ELISA for imidacloprid in water and soil samples were in the ranges of 74.6 to 86.3% and 72.5 to 93.6%, respectively. The results of the competitive phage ELISA for imidacloprid in the fortified samples agreed well with those of a high-performance liquid chromatography (HPLC) method. The simple phage-displayed peptide technology has been proven to be a convenient and efficient method for the development of an alternative format of ELISA for small molecules. Copyright © 2015 Elsevier Inc. All rights reserved.

Bridging Scales: A Model-Based Assessment of the Technical Tidal-Stream Energy Resource off Massachusetts, USA

NASA Astrophysics Data System (ADS)

Cowles, G. W.; Hakim, A.; Churchill, J. H.

2016-02-01

Tidal in-stream energy conversion (TISEC) facilities provide a highly predictable and dependable source of energy. Given the economic and social incentives to migrate towards renewable energy sources there has been tremendous interest in the technology. Key challenges to the design process stem from the wide range of problem scales extending from device to array. In the present approach we apply a multi-model approach to bridge the scales of interest and select optimal device geometries to estimate the technical resource for several realistic sites in the coastal waters of Massachusetts, USA. The approach links two computational models. To establish flow conditions at site scales ( 10m), a barotropic setup of the unstructured grid ocean model FVCOM is employed. The model is validated using shipboard and fixed ADCP as well as pressure data. For device scale, the structured multiblock flow solver SUmb is selected. A large ensemble of simulations of 2D cross-flow tidal turbines is used to construct a surrogate design model. The surrogate model is then queried using velocity profiles extracted from the tidal model to determine the optimal geometry for the conditions at each site. After device selection, the annual technical yield of the array is evaluated with FVCOM using a linear momentum actuator disk approach to model the turbines. Results for several key Massachusetts sites including comparison with theoretical approaches will be presented.

Update on MTTF figures for linear and rotary coolers of Thales Cryogenics

NASA Astrophysics Data System (ADS)

van de Groep, W.; van der Weijden, H.; van Leeuwen, R.; Benschop, T.; Cauquil, J. M.; Griot, R.

2012-06-01

Thales Cryogenics has an extensive background in delivering linear and rotary coolers for military, civil and space programs. During the last years several technical improvements have increased the lifetime of all Thales coolers resulting in significantly higher Mean Time To Failure (MTTF) figures. In this paper not only updated MTTF values for most of the products in our portfolio will be presented but also the methodology used to come to these reliability figures will be explained. The differences between rotary and linear coolers will be highlighted including the different failure modes influencing the lifetime under operational conditions. These updated reliability figures are based on extensive test results for both rotary and linear coolers as well as Weibull analysis, failure mode identifications, various types of lifetime testing and field results of operational coolers. The impact of the cooler selection for typical applications will be outlined. This updated reliability approach will enable an improved tradeoff for cooler selection in applications where MTTF and a correct reliability assessment is key. Improbing on cooler selection and an increased insight in cooler reliability will result in a higher uptime and operability of equipment, less risk on unexpected failures and lower costs of ownership.

Estimating monotonic rates from biological data using local linear regression.

PubMed

Olito, Colin; White, Craig R; Marshall, Dustin J; Barneche, Diego R

2017-03-01

Accessing many fundamental questions in biology begins with empirical estimation of simple monotonic rates of underlying biological processes. Across a variety of disciplines, ranging from physiology to biogeochemistry, these rates are routinely estimated from non-linear and noisy time series data using linear regression and ad hoc manual truncation of non-linearities. Here, we introduce the R package LoLinR, a flexible toolkit to implement local linear regression techniques to objectively and reproducibly estimate monotonic biological rates from non-linear time series data, and demonstrate possible applications using metabolic rate data. LoLinR provides methods to easily and reliably estimate monotonic rates from time series data in a way that is statistically robust, facilitates reproducible research and is applicable to a wide variety of research disciplines in the biological sciences. © 2017. Published by The Company of Biologists Ltd.

Non-linear dynamical classification of short time series of the rössler system in high noise regimes.

PubMed

Lainscsek, Claudia; Weyhenmeyer, Jonathan; Hernandez, Manuel E; Poizner, Howard; Sejnowski, Terrence J

2013-01-01

Time series analysis with delay differential equations (DDEs) reveals non-linear properties of the underlying dynamical system and can serve as a non-linear time-domain classification tool. Here global DDE models were used to analyze short segments of simulated time series from a known dynamical system, the Rössler system, in high noise regimes. In a companion paper, we apply the DDE model developed here to classify short segments of encephalographic (EEG) data recorded from patients with Parkinson's disease and healthy subjects. Nine simulated subjects in each of two distinct classes were generated by varying the bifurcation parameter b and keeping the other two parameters (a and c) of the Rössler system fixed. All choices of b were in the chaotic parameter range. We diluted the simulated data using white noise ranging from 10 to -30 dB signal-to-noise ratios (SNR). Structure selection was supervised by selecting the number of terms, delays, and order of non-linearity of the model DDE model that best linearly separated the two classes of data. The distances d from the linear dividing hyperplane was then used to assess the classification performance by computing the area A' under the ROC curve. The selected model was tested on untrained data using repeated random sub-sampling validation. DDEs were able to accurately distinguish the two dynamical conditions, and moreover, to quantify the changes in the dynamics. There was a significant correlation between the dynamical bifurcation parameter b of the simulated data and the classification parameter d from our analysis. This correlation still held for new simulated subjects with new dynamical parameters selected from each of the two dynamical regimes. Furthermore, the correlation was robust to added noise, being significant even when the noise was greater than the signal. We conclude that DDE models may be used as a generalizable and reliable classification tool for even small segments of noisy data.

Non-Linear Dynamical Classification of Short Time Series of the Rössler System in High Noise Regimes

PubMed Central

Lainscsek, Claudia; Weyhenmeyer, Jonathan; Hernandez, Manuel E.; Poizner, Howard; Sejnowski, Terrence J.

2013-01-01

Time series analysis with delay differential equations (DDEs) reveals non-linear properties of the underlying dynamical system and can serve as a non-linear time-domain classification tool. Here global DDE models were used to analyze short segments of simulated time series from a known dynamical system, the Rössler system, in high noise regimes. In a companion paper, we apply the DDE model developed here to classify short segments of encephalographic (EEG) data recorded from patients with Parkinson’s disease and healthy subjects. Nine simulated subjects in each of two distinct classes were generated by varying the bifurcation parameter b and keeping the other two parameters (a and c) of the Rössler system fixed. All choices of b were in the chaotic parameter range. We diluted the simulated data using white noise ranging from 10 to −30 dB signal-to-noise ratios (SNR). Structure selection was supervised by selecting the number of terms, delays, and order of non-linearity of the model DDE model that best linearly separated the two classes of data. The distances d from the linear dividing hyperplane was then used to assess the classification performance by computing the area A′ under the ROC curve. The selected model was tested on untrained data using repeated random sub-sampling validation. DDEs were able to accurately distinguish the two dynamical conditions, and moreover, to quantify the changes in the dynamics. There was a significant correlation between the dynamical bifurcation parameter b of the simulated data and the classification parameter d from our analysis. This correlation still held for new simulated subjects with new dynamical parameters selected from each of the two dynamical regimes. Furthermore, the correlation was robust to added noise, being significant even when the noise was greater than the signal. We conclude that DDE models may be used as a generalizable and reliable classification tool for even small segments of noisy data. PMID:24379798

User's manual for interactive LINEAR: A FORTRAN program to derive linear aircraft models

NASA Technical Reports Server (NTRS)

Antoniewicz, Robert F.; Duke, Eugene L.; Patterson, Brian P.

1988-01-01

An interactive FORTRAN program that provides the user with a powerful and flexible tool for the linearization of aircraft aerodynamic models is documented in this report. The program LINEAR numerically determines a linear system model using nonlinear equations of motion and a user-supplied linear or nonlinear aerodynamic model. The nonlinear equations of motion used are six-degree-of-freedom equations with stationary atmosphere and flat, nonrotating earth assumptions. The system model determined by LINEAR consists of matrices for both the state and observation equations. The program has been designed to allow easy selection and definition of the state, control, and observation variables to be used in a particular model.

Externally resonated linear microvibromotor for microassembly

NASA Astrophysics Data System (ADS)

Saitou, Kazuhiro; Wou, Soungjin J.

1998-10-01

A new design of a linear micro vibromotor for on-substrate fine positioning of micro-scale components is presented where a micro linear slider is actuated by vibratory impacts exerted by micro cantilever impacters. These micro cantilever impacters are selectively resonated by shaking the entire substrate with a piezoelectric vibrator, requiring no need for built-in driving mechanisms such as electrostatic comb actuators as reported previously. This selective resonance of the micro cantilever impacters via an external vibration energy field provides with a very simple means of controlling forward and backward motion of the micro linear slider, facilitating assembly and disassembly of a micro component on a substrate. The double-V beam suspension design is employed in the micro cantilever impacters for larger displacement in the lateral direction while achieving higher stiffness in the transversal direction. An analytical model of the device is derived in order to obtain, through the Simulated Annealing algorithm, an optimal design which maximizes translation speed of the linear slider at desired external input frequencies. Prototypes of the externally-resonated linear micro vibromotor are fabricated using the three-layer polysilicon surface micro machining process provided by the MCNC MUMPS service.

Formation of Linear Amplicons with Inverted Duplications in Leishmania Requires the MRE11 Nuclease

PubMed Central

Laffitte, Marie-Claude N.; Genois, Marie-Michelle; Mukherjee, Angana; Légaré, Danielle; Masson, Jean-Yves; Ouellette, Marc

2014-01-01

Extrachromosomal DNA amplification is frequent in the protozoan parasite Leishmania selected for drug resistance. The extrachromosomal amplified DNA is either circular or linear, and is formed at the level of direct or inverted homologous repeated sequences that abound in the Leishmania genome. The RAD51 recombinase plays an important role in circular amplicons formation, but the mechanism by which linear amplicons are formed is unknown. We hypothesized that the Leishmania infantum DNA repair protein MRE11 is required for linear amplicons following rearrangements at the level of inverted repeats. The purified LiMRE11 protein showed both DNA binding and exonuclease activities. Inactivation of the LiMRE11 gene led to parasites with enhanced sensitivity to DNA damaging agents. The MRE11−/− parasites had a reduced capacity to form linear amplicons after drug selection, and the reintroduction of an MRE11 allele led to parasites regaining their capacity to generate linear amplicons, but only when MRE11 had an active nuclease activity. These results highlight a novel MRE11-dependent pathway used by Leishmania to amplify portions of its genome to respond to a changing environment. PMID:25474106

Time-dependent Fracture Behaviour of Polyampholyte Hydrogels

NASA Astrophysics Data System (ADS)

Sun, Tao Lin; Luo, Feng; Nakajima, Tasuku; Kurokawa, Takayuki; Gong, Jian Ping

Recently, we report that polyampholytes, polymers bearing randomly dispersed cationic and anionic repeat groups, form tough and self-healing hydrogels with excellent multiple mechanical functions. The randomness makes ionic bonds with a wide distribution of strength, via inter and intra chain complexation. As the breaking and reforming of ionic bonds are time dependent, the hydrogels exhibit rate dependent mechanical behaviour. We systematically studied the tearing energy by tearing test with various tearing velocity under different temperature, and the linear viscoelastic behaviour over a wide range of frequency and temperature. Results have shown that the tearing energy markedly increase with the crack velocity and decrease with the measured temperature. In accordance with the prediction of Williams, Landel, and Ferry (WLF) rate-temperature equivalence, a master curve of tearing energy dependence of crack velocity can be well constructed using the same shift factor from the linear viscoelastic data. The scaling relation of tearing energy as a function of crack velocity can be predicted well by the rheological data according to the developed linear fracture mechanics.

Theoretical and Experimental Study on Wide Range Optical Fiber Turbine Flow Sensor.

PubMed

Du, Yuhuan; Guo, Yingqing

2016-07-15

In this paper, a novel fiber turbine flow sensor was proposed and demonstrated for liquid measurement with optical fiber, using light intensity modulation to measure the turbine rotational speed for converting to flow rate. The double-circle-coaxial (DCC) fiber probe was introduced in frequency measurement for the first time. Through the divided ratio of two rings light intensity, the interference in light signals acquisition can be eliminated. To predict the characteristics between the output frequency and flow in the nonlinear range, the turbine flow sensor model was built. Via analyzing the characteristics of turbine flow sensor, piecewise linear equations were achieved in expanding the flow measurement range. Furthermore, the experimental verification was tested. The results showed that the flow range ratio of DN20 turbine flow sensor was improved 2.9 times after using piecewise linear in the nonlinear range. Therefore, combining the DCC fiber sensor and piecewise linear method, it can be developed into a strong anti-electromagnetic interference(anti-EMI) and wide range fiber turbine flowmeter.

Theoretical and Experimental Study on Wide Range Optical Fiber Turbine Flow Sensor

PubMed Central

Du, Yuhuan; Guo, Yingqing

2016-01-01

In this paper, a novel fiber turbine flow sensor was proposed and demonstrated for liquid measurement with optical fiber, using light intensity modulation to measure the turbine rotational speed for converting to flow rate. The double-circle-coaxial (DCC) fiber probe was introduced in frequency measurement for the first time. Through the divided ratio of two rings light intensity, the interference in light signals acquisition can be eliminated. To predict the characteristics between the output frequency and flow in the nonlinear range, the turbine flow sensor model was built. Via analyzing the characteristics of turbine flow sensor, piecewise linear equations were achieved in expanding the flow measurement range. Furthermore, the experimental verification was tested. The results showed that the flow range ratio of DN20 turbine flow sensor was improved 2.9 times after using piecewise linear in the nonlinear range. Therefore, combining the DCC fiber sensor and piecewise linear method, it can be developed into a strong anti-electromagnetic interference(anti-EMI) and wide range fiber turbine flowmeter. PMID:27428976

The risk equivalent of an exposure to-, versus a dose of radiation

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

Bond, V.P.

The long-term potential carcinogenic effects of low-level exposure (LLE) are addressed. The principal point discussed is linear, no-threshold dose-response curve. That the linear no-threshold, or proportional relationship is widely used is seen in the way in which the values for cancer risk coefficients are expressed - in terms of new cases, per million persons exposed, per year, per unit exposure or dose. This implies that the underlying relationship is proportional, i.e., ''linear, without threshold''. 12 refs., 9 figs., 1 tab.

Genome-wide selection components analysis in a fish with male pregnancy.

PubMed

Flanagan, Sarah P; Jones, Adam G

2017-04-01

A major goal of evolutionary biology is to identify the genome-level targets of natural and sexual selection. With the advent of next-generation sequencing, whole-genome selection components analysis provides a promising avenue in the search for loci affected by selection in nature. Here, we implement a genome-wide selection components analysis in the sex role reversed Gulf pipefish, Syngnathus scovelli. Our approach involves a double-digest restriction-site associated DNA sequencing (ddRAD-seq) technique, applied to adult females, nonpregnant males, pregnant males, and their offspring. An F ST comparison of allele frequencies among these groups reveals 47 genomic regions putatively experiencing sexual selection, as well as 468 regions showing a signature of differential viability selection between males and females. A complementary likelihood ratio test identifies similar patterns in the data as the F ST analysis. Sexual selection and viability selection both tend to favor the rare alleles in the population. Ultimately, we conclude that genome-wide selection components analysis can be a useful tool to complement other approaches in the effort to pinpoint genome-level targets of selection in the wild. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Prediction of Bacillus weihenstephanensis acid resistance: the use of gene expression patterns to select potential biomarkers.

PubMed

Desriac, N; Postollec, F; Coroller, L; Sohier, D; Abee, T; den Besten, H M W

2013-10-01

Exposure to mild stress conditions can activate stress adaptation mechanisms and provide cross-resistance towards otherwise lethal stresses. In this study, an approach was followed to select molecular biomarkers (quantitative gene expressions) to predict induced acid resistance after exposure to various mild stresses, i.e. exposure to sublethal concentrations of salt, acid and hydrogen peroxide during 5 min to 60 min. Gene expression patterns of unstressed and mildly stressed cells of Bacillus weihenstephanensis were correlated to their acid resistance (3D value) which was estimated after exposure to lethal acid conditions. Among the twenty-nine candidate biomarkers, 12 genes showed expression patterns that were correlated either linearly or non-linearly to acid resistance, while for the 17 other genes the correlation remains to be determined. The selected genes represented two types of biomarkers, (i) four direct biomarker genes (lexA, spxA, narL, bkdR) for which expression patterns upon mild stress treatment were linearly correlated to induced acid resistance; and (ii) nine long-acting biomarker genes (spxA, BcerKBAB4_0325, katA, trxB, codY, lacI, BcerKBAB4_1716, BcerKBAB4_2108, relA) which were transiently up-regulated during mild stress exposure and correlated to increased acid resistance over time. Our results highlight that mild stress induced transcripts can be linearly or non-linearly correlated to induced acid resistance and both approaches can be used to find relevant biomarkers. This quantitative and systematic approach opens avenues to select cellular biomarkers that could be incremented in mathematical models to predict microbial behaviour. Copyright © 2013 Elsevier B.V. All rights reserved.

A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis.

PubMed

Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga

2006-08-01

A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.

Preliminary Survey on TRY Forest Traits and Growth Index Relations - New Challenges

NASA Astrophysics Data System (ADS)

Lyubenova, Mariyana; Kattge, Jens; van Bodegom, Peter; Chikalanov, Alexandre; Popova, Silvia; Zlateva, Plamena; Peteva, Simona

2016-04-01

Forest ecosystems provide critical ecosystem goods and services, including food, fodder, water, shelter, nutrient cycling, and cultural and recreational value. Forests also store carbon, provide habitat for a wide range of species and help alleviate land degradation and desertification. Thus they have a potentially significant role to play in climate change adaptation planning through maintaining ecosystem services and providing livelihood options. Therefore the study of forest traits is such an important issue not just for individual countries but for the planet as a whole. We need to know what functional relations between forest traits exactly can express TRY data base and haw it will be significant for the global modeling and IPBES. The study of the biodiversity characteristics at all levels and functional links between them is extremely important for the selection of key indicators for assessing biodiversity and ecosystem services for sustainable natural capital control. By comparing the available information in tree data bases: TRY, ITR (International Tree Ring) and SP-PAM the 42 tree species are selected for the traits analyses. The dependence between location characteristics (latitude, longitude, altitude, annual precipitation, annual temperature and soil type) and forest traits (specific leaf area, leaf weight ratio, wood density and growth index) is studied by by multiply regression analyses (RDA) using the statistical software package Canoco 4.5. The Pearson correlation coefficient (measure of linear correlation), Kendal rank correlation coefficient (non parametric measure of statistical dependence) and Spearman correlation coefficient (monotonic function relationship between two variables) are calculated for each pair of variables (indexes) and species. After analysis of above mentioned correlation coefficients the dimensional linear regression models, multidimensional linear and nonlinear regression models and multidimensional neural networks models are built. The strongest dependence between It and WD was obtained. The research will support the work on: Strategic Plan for Biodiversity 2011-2020, modelling and implementation of ecosystem-based approaches to climate change adaptation and disaster risk reduction. Key words: Specific leaf area (SLA), Leaf weight ratio (LWR), Wood density (WD), Growth index (It)

Characterization of single chain antibody targets through yeast two hybrid

PubMed Central

2010-01-01

Background Due to their unique ability to bind their targets with high fidelity, antibodies are used widely not only in biomedical research, but also in many clinical applications. Recombinant antibodies, including single chain variable fragments (scFv), are gaining momentum because they allow powerful in vitro selection and manipulation without loss of function. Regardless of the ultimate application or type of antibody used, precise understanding of the interaction between the antibody's binding site and its specific target epitope(s) is of great importance. However, such data is frequently difficult to obtain. Results We describe an approach that allows detailed characterization of a given antibody's target(s) using the yeast two-hybrid system. Several recombinant scFv were used as bait and screened against highly complex cDNA libraries. Systematic sequencing of all retained clones and statistical analysis allowed efficient ranking of the prey fragments. Multiple alignment of the obtained cDNA fragments provided a selected interacting domain (SID), efficiently narrowing the epitope-containing region. Interactions between antibodies and their respective targets were characterized for several scFv. For AA2 and ROF7, two conformation-specific sensors that exclusively bind the activated forms of the small GTPases Rab6 and Rab1 respectively, only fragments expressing the entire target protein's core region were retained. This strongly suggested interaction with a non-linear epitope. For two other scFv, TA10 and SF9, which recognize the large proteins giantin and non-muscle myosin IIA, respectively, precise antibody-binding regions within the target were defined. Finally, for some antibodies, secondary targets within and across species could be revealed. Conclusions Our method, utilizing the yeast two-hybrid technology and scFv as bait, is a simple yet powerful approach for the detailed characterization of antibody targets. It allows precise domain mapping for linear epitopes, confirmation of non-linear epitopes for conformational sensors, and detection of secondary binding partners. This approach may thus prove to be an elegant and rapid method for the target characterization of newly obtained scFv antibodies. It may be considered prior to any research application and particularly before any use of such recombinant antibodies in clinical medicine. PMID:20727208

Relativistic electron scattering by magnetosonic waves: Effects of discrete wave emission and high wave amplitudes

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

Artemyev, A. V., E-mail: ante0226@gmail.com; Mourenas, D.; Krasnoselskikh, V. V.

2015-06-15

In this paper, we study relativistic electron scattering by fast magnetosonic waves. We compare results of test particle simulations and the quasi-linear theory for different spectra of waves to investigate how a fine structure of the wave emission can influence electron resonant scattering. We show that for a realistically wide distribution of wave normal angles θ (i.e., when the dispersion δθ≥0.5{sup °}), relativistic electron scattering is similar for a wide wave spectrum and for a spectrum consisting in well-separated ion cyclotron harmonics. Comparisons of test particle simulations with quasi-linear theory show that for δθ>0.5{sup °}, the quasi-linear approximation describes resonantmore » scattering correctly for a large enough plasma frequency. For a very narrow θ distribution (when δθ∼0.05{sup °}), however, the effect of a fine structure in the wave spectrum becomes important. In this case, quasi-linear theory clearly fails in describing accurately electron scattering by fast magnetosonic waves. We also study the effect of high wave amplitudes on relativistic electron scattering. For typical conditions in the earth's radiation belts, the quasi-linear approximation cannot accurately describe electron scattering for waves with averaged amplitudes >300 pT. We discuss various applications of the obtained results for modeling electron dynamics in the radiation belts and in the Earth's magnetotail.« less

Development and validation of a general purpose linearization program for rigid aircraft models

NASA Technical Reports Server (NTRS)

Duke, E. L.; Antoniewicz, R. F.

1985-01-01

A FORTRAN program that provides the user with a powerful and flexible tool for the linearization of aircraft models is discussed. The program LINEAR numerically determines a linear systems model using nonlinear equations of motion and a user-supplied, nonlinear aerodynamic model. The system model determined by LINEAR consists of matrices for both the state and observation equations. The program has been designed to allow easy selection and definition of the state, control, and observation variables to be used in a particular model. Also, included in the report is a comparison of linear and nonlinear models for a high performance aircraft.

Electrolytes for Wide Operating Temperature Lithium-Ion Cells

NASA Technical Reports Server (NTRS)

Smart, Marshall C. (Inventor); Bugga, Ratnakumar V. (Inventor)

2016-01-01

Provided herein are electrolytes for lithium-ion electrochemical cells, electrochemical cells employing the electrolytes, methods of making the electrochemical cells and methods of using the electrochemical cells over a wide temperature range. Included are electrolyte compositions comprising a lithium salt, a cyclic carbonate, a non-cyclic carbonate, and a linear ester and optionally comprising one or more additives.

EEG-based mild depressive detection using feature selection methods and classifiers.

PubMed

Li, Xiaowei; Hu, Bin; Sun, Shuting; Cai, Hanshu

2016-11-01

Depression has become a major health burden worldwide, and effectively detection of such disorder is a great challenge which requires latest technological tool, such as Electroencephalography (EEG). This EEG-based research seeks to find prominent frequency band and brain regions that are most related to mild depression, as well as an optimal combination of classification algorithms and feature selection methods which can be used in future mild depression detection. An experiment based on facial expression viewing task (Emo_block and Neu_block) was conducted, and EEG data of 37 university students were collected using a 128 channel HydroCel Geodesic Sensor Net (HCGSN). For discriminating mild depressive patients and normal controls, BayesNet (BN), Support Vector Machine (SVM), Logistic Regression (LR), k-nearest neighbor (KNN) and RandomForest (RF) classifiers were used. And BestFirst (BF), GreedyStepwise (GSW), GeneticSearch (GS), LinearForwordSelection (LFS) and RankSearch (RS) based on Correlation Features Selection (CFS) were applied for linear and non-linear EEG features selection. Independent Samples T-test with Bonferroni correction was used to find the significantly discriminant electrodes and features. Data mining results indicate that optimal performance is achieved using a combination of feature selection method GSW based on CFS and classifier KNN for beta frequency band. Accuracies achieved 92.00% and 98.00%, and AUC achieved 0.957 and 0.997, for Emo_block and Neu_block beta band data respectively. T-test results validate the effectiveness of selected features by search method GSW. Simplified EEG system with only FP1, FP2, F3, O2, T3 electrodes was also explored with linear features, which yielded accuracies of 91.70% and 96.00%, AUC of 0.952 and 0.972, for Emo_block and Neu_block respectively. Classification results obtained by GSW + KNN are encouraging and better than previously published results. In the spatial distribution of features, we find that left parietotemporal lobe in beta EEG frequency band has greater effect on mild depression detection. And fewer EEG channels (FP1, FP2, F3, O2 and T3) combined with linear features may be good candidates for usage in portable systems for mild depression detection. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.