Chemotaxonomic relationships in Celastraceae inferred from principal component analysis (PCA) and partial least squares (PLS)

This paper describes a chemotaxonomic analysis of a database of triterpenoid compounds from the Celastraceae family using principal component analysis (PCA). The numbers of occurrences of thirty types of triterpene skeleton in different tribes of the family were used as variables. The study shows that PCA applied to chemical data can contribute to an intrafamilial classification of Celastraceae, once some questionable taxa affinity was observed, from chemotaxonomic inferences about genera and they are in agreement with the phylogeny previously proposed. The inclusion of Hippocrateaceae within Celastraceae is supported by the triterpene chemistry.

Improving the GNSS positioning stochastic model in the presence of ionospheric scintillation

Ionospheric scintillations are caused by time-varying electron density irregularities in the ionosphere, occurring more often at equatorial and high latitudes. This paper focuses exclusively on experiments undertaken in Europe, at geographic latitudes between similar to 50 degrees N and similar to 80 degrees N, where a network of GPS receivers capable of monitoring Total Electron Content and ionospheric scintillation parameters was deployed. The widely used ionospheric scintillation indices S4 and sigma(phi) represent a practical measure of the intensity of amplitude and phase scintillation affecting GNSS receivers. However, they do not provide sufficient information regarding the actual tracking errors that degrade GNSS receiver performance. Suitable receiver tracking models, sensitive to ionospheric scintillation, allow the computation of the variance of the output error of the receiver PLL (Phase Locked Loop) and DLL (Delay Locked Loop), which expresses the quality of the range measurements used by the receiver to calculate user position. The ability of such models of incorporating phase and amplitude scintillation effects into the variance of these tracking errors underpins our proposed method of applying relative weights to measurements from different satellites. That gives the least squares stochastic model used for position computation a more realistic representation, vis-a-vis the otherwise 'equal weights' model. For pseudorange processing, relative weights were computed, so that a 'scintillation-mitigated' solution could be performed and compared to the (non-mitigated) 'equal weights' solution. An improvement between 17 and 38% in height accuracy was achieved when an epoch by epoch differential solution was computed over baselines ranging from 1 to 750 km. The method was then compared with alternative approaches that can be used to improve the least squares stochastic model such as weighting according to satellite elevation angle and by the inverse of the square of the standard deviation of the code/carrier divergence (sigma CCDiv). The influence of multipath effects on the proposed mitigation approach is also discussed. With the use of high rate scintillation data in addition to the scintillation indices a carrier phase based mitigated solution was also implemented and compared with the conventional solution. During a period of occurrence of high phase scintillation it was observed that problems related to ambiguity resolution can be reduced by the use of the proposed mitigated solution.

Micro-Raman spectroscopy and SEM/EDX applied to improve the zircon fission track method used for dating geological formations

The zircon mineral is widely studied in geochronology. In the case of the fission track method (FTM), the age is determined by the density of fission tracks at the zircon surface, which can be observed with an optical microscope after an appropriate chemical treatment (etching). The etching must be isotropic at the zircon grain surface to be used in the FTM, which leads those zircon grains whose etching is anisotropic to be discarded. The only reason for this discarding is the nonuniform morphology of the surface grain seen by optical microscopy, that is, no further physicochemical analysis is performed. In this work, combining micro-Raman and scanning electron microscopy (SEM) to study the etching anisotropy, it was shown that zircon grains that present at least one area at the surface where the density of fission track is uniform can be used in the FTM. The micro-Raman showed characteristic spectra of the standard zircon sample either from the areas where there are tracks or from where there are not. The only difference found was in the Raman bandwidths, which were broader for the areas with higher density of fission tracks. This suggests simply a decrease in the relative percentage of the crystalline/amorphous phases at these areas. The SEM/energy dispersive spectrometry (EDX) showed that there were no significant differences in the principal chemical composition at the areas with and without fission tracks. Copyright (c) 2008 John Wiley & Sons, Ltd.

DETERMINATION of SILICON IN LUBRICANT OIL BY HIGH-RESOLUTION CONTINUUM SOURCE FLAME ATOMIC ABSORPTION SPECTROMETRY USING LEAST-SQUARE BACKGROUND CORRECTION and INTERNAL STANDARDIZATION

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Carbon Nuclear Magnetic Resonance Spectroscopic Profiles coupled to Partial Least-Squares Multivariate Regression for Prediction of Several Physicochemical Parameters of Brazilian Commercial Gasoline

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A partial least squares and principal component regression study of quinone compounds with trypanocidal activity

A quantitative structure-activity relationship (QSAR) study of 19 quinone compounds with trypanocidal activity was performed by Partial Least Squares (PLS) and Principal Component Regression (PCR) methods with the use of leave-one-out crossvalidation procedure to build the regression models. The trypanocidal activity of the compounds is related to their first cathodic potential (Ep(c1)). The regression PLS and PCR models built in this study were also used to predict the Ep(c1) of six new quinone compounds. The PLS model was built with three principal components that described 96.50% of the total variance and present Q(2) = 0.83 and R-2 = 0.90. The results obtained with the PCR model were similar to those obtained with the PLS model. The PCR model was also built with three principal components that described 96.67% of the total variance with Q(2) = 0.83 and R-2 = 0.90. The most important descriptors for our PLS and PCR models were HOMO-1 (energy of the molecular orbital below HOMO), Q4 (atomic charge at position 4), MAXDN (maximal electrotopological negative difference), and HYF (hydrophilicity index).

Precision of yule-walker methods for the arma spectral model

In this work a new method is proposed of separated estimation for the ARMA spectral model based on the modified Yule-Walker equations and on the least squares method. The proposal of the new method consists of performing an AR filtering in the random process generated obtaining a new random estimate, which will reestimate the ARMA model parameters, given a better spectrum estimate. Some numerical examples will be presented in order to ilustrate the performance of the method proposed, which is evaluated by the relative error and the average variation coefficient.

Identification of transmission line parameters from temporal measurements of currents and voltages in their terminals: Influence oh the length line

The objective of this paper is to show a methodology to estimate transmission line parameters. The method is applied in a single-phase transmission line using the method of least squares. In this method the longitudinal and transversal parameters of the line are obtained as a function of a set of measurements of currents and voltages (as well as their derivatives with respect to time) at the terminals of the line during the occurrence of a short-circuit phase-ground near the load. The method is based on the assumption that a transmission line can be represented by a single circuit π. The results show that the precision of the method depends on the length of the line, where it has a better performance for short lines and medium length. © 2012 IEEE.

Comparison between known propagation models using least squares tuning algorithm on 5.8 GHz in Amazon region cities

ABSTRACT: This paper presents a performance comparison between known propagation Models through least squares tuning algorithm for 5.8 GHz frequency band. The studied environment is based on the 12 cities located in Amazon Region. After adjustments and simulations, SUI Model showed the smaller RMS error and standard deviation when compared with COST231-Hata and ECC-33 models.

Strategies in identifying individuals in a segregant population of common bean and implications of genotype x environment interaction in the success of selection

The objective of this study was to compare the BLUP selection method with different selection strategies in F-2:4 and assess the efficiency of this method on the early choice of the best common bean (Phaseolus vulgaris) lines. Fifty-one F-2:4 progenies were produced from a cross between the CVIII8511 x RP-26 lines. A randomized block design was used with 20 replications and one-plant field plots. Character data on plant architecture and grain yield were obtained and then the sum of the standardized variables was estimated for simultaneous selection of both traits. Analysis was carried out by mixed models (BLUP) and the least squares method to compare different selection strategies, like mass selection, stratified mass selection and between and within progeny selection. The progenies selected by BLUP were assessed in advanced generations, always selecting the greatest and smallest sum of the standardized variables. Analyses by the least squares method and BLUP procedure ranked the progenies in the same way. The coincidence of the individuals identified by BLUP and between and within progeny selection was high and of the greatest magnitude when BLUP was compared with mass selection. Although BLUP is the best estimator of genotypic value, its efficiency in the response to long term selection is not different from any of the other methods, because it is also unable to predict the future effect of the progenies x environments interaction. It was inferred that selection success will always depend on the most accurate possible progeny assessment and using alternatives to reduce the progenies x environments interaction effect.

Determination of chlorine in food samples via the AlCl molecule using high-resolution continuum source molecular absorption spectrometry in a graphite furnace

Determination of chlorine using the molecular absorption of aluminum mono-chloride (AlCl) at the 261.418 nm wavelength was accomplished by high-resolution continuum source molecular absorption spectrometry using a transversely heated graphite tube furnace with an integrated platform. For the analysis. 10 mu L of the sample followed by 10 mu L of a solution containing Al-Ag-Sr modifier, (1 g L-1 each), were directly injected onto the platform. A spectral interference due to the use of Al-Ag-Sr as mixed modifier was easily corrected by the least-squares algorithm present in the spectrometer software. The pyrolysis and vaporization temperatures were 500 degrees C and 2200 degrees C, respectively. To evaluate the feasibility of a simple procedure for the determination of chlorine in food samples present in our daily lives, two different digestion methods were applied, namely (A) an acid digestion method using HNO3 only at room temperature, and (B) a digestion method with Ag, HNO3 and H2O2, where chlorine is precipitated as a low-solubility salt (AgCl), which is then dissolved with ammonia solution. The experimental results obtained with method B were in good agreement with the certified values and demonstrated that the proposed method is more accurate than method A. This is because the formation of silver chloride prevented analyte losses by volatilization. The limit of detection (LOD, 3 sigma/s) for Cl in methods A and B was 18 mu g g(-1) and 9 mu g g(-1), respectively, 1.7 and 3.3 times lower compared to published work using inductively coupled plasma optical emission spectrometry, and absolute LODs were 2.4 and 1.2 ng, respectively. (C) 2012 Elsevier B.V. All rights reserved.

Classification Using Generalized Partial Least Squares

The advances in computational biology have made simultaneous monitoring of thousands of features possible. The high throughput technologies not only bring about a much richer information context in which to study various aspects of gene functions but they also present challenge of analyzing data with large number of covariates and few samples. As an integral part of machine learning, classification of samples into two or more categories is almost always of interest to scientists. In this paper, we address the question of classification in this setting by extending partial least squares (PLS), a popular dimension reduction tool in chemometrics, in the context of generalized linear regression based on a previous approach, Iteratively ReWeighted Partial Least Squares, i.e. IRWPLS (Marx, 1996). We compare our results with two-stage PLS (Nguyen and Rocke, 2002A; Nguyen and Rocke, 2002B) and other classifiers. We show that by phrasing the problem in a generalized linear model setting and by applying bias correction to the likelihood to avoid (quasi)separation, we often get lower classification error rates.

A Measurement System Experiment to Evaluate the Nosing-to-nosing Method for Measuring Dimensions of Steps

Non-uniformity of steps within a flight is a major risk factor for falls. Guidelines and requirements for uniformity of step risers and tread depths assume the measurement system provides precise dimensional values. The state-of-the-art measurement system is a relatively new method, known as the nosing-to-nosing method. It involves measuring the distance between the noses of adjacent steps and the angle formed with the horizontal. From these measurements, the effective riser height and tread depth are calculated. This study was undertaken for the purpose of evaluating the measurement system to determine how much of total measurement variability comes from the step variations versus that due to repeatability and reproducibility (R&R) associated with the measurers. Using an experimental design quality control professionals call a measurement system experiment, two measurers measured all steps in six randomly selected flights, and repeated the process on a subsequent day. After marking each step in a flight in three lateral places (left, center, and right), the measurers took their measurement. This process yielded 774 values of riser height and 672 values of tread depth. Results of applying the Gage R&R ANOVA procedure in Minitab software indicated that the R&R contribution to riser height variability was 1.42%; and to tread depth was 0.50%. All remaining variability was attributed to actual step-to-step differences. These results may be compared with guidelines used in the automobile industry for measurement systems that consider R&R less than 1% as an acceptable measurement system; and R&R between 1% and 9% as acceptable depending on the application, the cost of the measuring device, cost of repair, or other factors.

Comparison of partial least squares regression and principal component regression for pelvic shape prediction.

This paper studied two different regression techniques for pelvic shape prediction, i.e., the partial least square regression (PLSR) and the principal component regression (PCR). Three different predictors such as surface landmarks, morphological parameters, or surface models of neighboring structures were used in a cross-validation study to predict the pelvic shape. Results obtained from applying these two different regression techniques were compared to the population mean model. In almost all the prediction experiments, both regression techniques unanimously generated better results than the population mean model, while the difference on prediction accuracy between these two regression methods is not statistically significant (α=0.01).

Interrelationships between the structural and functional aspects of social relationships, comorbidity and health related quality of life in breast cancer survivors

It is widely acknowledged in theoretical and empirical literature that social relationships, comprising of structural measures (social networks) and functional measures (perceived social support) have an undeniable effect on health outcomes. However, the actual mechanism of this effect has yet to be clearly understood or explicated. In addition, comorbidity is found to adversely affect social relationships and health related quality of life (a valued outcome measure in cancer patients and survivors). ^ This cross sectional study uses selected baseline data (N=3088) from the Women's Healthy Eating and Living (WHEL) study. Lisrel 8.72 was used for the latent variable structural equation modeling. Due to the ordinal nature of the data, Weighted Least Squares (WLS) method of estimation using Asymptotic Distribution Free covariance matrices was chosen for this analysis. The primary exogenous predictor variables are Social Networks and Comorbidity; Perceived Social Support is the endogenous predictor variable. Three dimensions of HRQoL, physical, mental and satisfaction with current quality of life were the outcome variables. ^ This study hypothesizes and tests the mechanism and pathways between comorbidity, social relationships and HRQoL using latent variable structural equation modeling. After testing the measurement models of social networks and perceived social support, a structural model hypothesizing associations between the latent exogenous and endogenous variables was tested. The results of the study after listwise deletion (N=2131) mostly confirmed the hypothesized relationships (TLI, CFI >0.95, RMSEA = 0.05, p=0.15). Comorbidity was adversely associated with all three HRQoL outcomes. Strong ties were negatively associated with perceived social support; social network had a strong positive association with perceived social support, which served as a mediator between social networks and HRQoL. Mental health quality of life was the most adversely affected by the predictor variables. ^ This study is a preliminary look at the integration of structural and functional measures of social relationships, comorbidity and three HRQoL indicators using LVSEM. Developing stronger social networks and forming supportive relationships is beneficial for health outcomes such as HRQoL of cancer survivors. Thus, the medical community treating cancer survivors as well as the survivor's social networks need to be informed and cognizant of these possible relationships. ^