Screening Brazilian commercial gasoline quality by hydrogen nuclear magnetic resonance spectroscopic fingerprintings and pattern-recognition multivariate chemometric analysis

The identification of gasoline adulteration by organic solvents is not an easy task, because compounds that constitute the solvents are already in gasoline composition. In this work, the combination of Hydrogen Nuclear Magnetic Resonance ((1)H NMR) spectroscopic fingerprintings with pattern-recognition multivariate Soft Independent Modeling of Class Analogy (SIMCA) chemometric analysis provides an original and alternative approach to screening Brazilian commercial gasoline quality in a Monitoring Program for Quality Control of Automotive Fuels. SIMCA was performed on spectroscopic fingerprints to classify the quality of representative commercial gasoline samples selected by Hierarchical Cluster Analysis (HCA) and collected over a 6-month period from different gas stations in the São Paulo state, Brazil. Following optimized the (1)H NMR-SIMCA algorithm, it was possible to correctly classify 92.0% of commercial gasoline samples, which is considered acceptable. The chemometric method is recommended for routine applications in Quality-Control Monitoring Programs, since its measurements are fast and can be easily automated. Also, police laboratories could employ this method for rapid screening analysis to discourage adulteration practices. (C) 2010 Elsevier B.V. All rights reserved.

A statistical analysis of loss factor to determine the energy losses

Given that the total amount of losses in a distribution system is known, with a reliable methodology for the technical loss calculation, the non-technical losses can be obtained by subtraction. A usual method of calculation technical losses in the electric utilities uses two important factors: load factor and the loss factor. The load factor is usually obtained with energy and demand measurements, whereas, to compute the loss factor it is necessary the learning of demand and energy loss, which are not, in general, prone of direct measurements. In this work, a statistical analysis of this relationship using the curves of a sampling of consumers in a specific company is presented. These curves will be summarized in different bands of coefficient k. Then, it will be possible determine where each group of consumer has its major concentration of points. ©2008 IEEE.

Determination of disease biomarkers in Eucalyptus by comprehensive two-dimensional gas chromatography and multivariate data analysis

In this paper is reported the use of the chromatographic profiles of volatiles to determine disease markers in plants - in this case, leaves of Eucalyptus globulus contaminated by the necrotroph fungus Teratosphaeria nubilosa. The volatile fraction was isolated by headspace solid phase microextraction (HS-SPME) and analyzed by comprehensive two-dimensional gas chromatography-fast quadrupole mass spectrometry (GC. ×. GC-qMS). For the correlation between the metabolic profile described by the chromatograms and the presence of the infection, unfolded-partial least squares discriminant analysis (U-PLS-DA) with orthogonal signal correction (OSC) were employed. The proposed method was checked to be independent of factors such as the age of the harvested plants. The manipulation of the mathematical model obtained also resulted in graphic representations similar to real chromatograms, which allowed the tentative identification of more than 40 compounds potentially useful as disease biomarkers for this plant/pathogen pair. The proposed methodology can be considered as highly reliable, since the diagnosis is based on the whole chromatographic profile rather than in the detection of a single analyte. © 2013 Elsevier B.V..

Comprehensive two-dimensional gas chromatography combined to multivariate data analysis for detection of disease-resistant clones of Eucalyptus

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

Influence of Tapered and External Hexagon Connections on Bone Stresses Around Tilted Dental Implants: Three-Dimensional Finite Element Method With Statistical Analysis

Background: The purpose of this study is to analyze the tension distribution on bone tissue around implants with different angulations (0 degrees, 17 degrees, and 30 degrees) and connections (external hexagon and tapered) through the use of three-dimensional finite element and statistical analyses.Methods: Twelve different configurations of three-dimensional finite element models, including three inclinations of the implants (0 degrees, 17 degrees, and 30 degrees), two connections (an external hexagon and a tapered), and two load applications (axial and oblique), were simulated. The maximum principal stress values for cortical bone were measured at the mesial, distal, buccal, and lingual regions around the implant for each analyzed situation, totaling 48 groups. Loads of 200 and 100 N were applied at the occlusal surface in the axial and oblique directions, respectively. Maximum principal stress values were measured at the bone crest and statistically analyzed using analysis of variance. Stress patterns in the bone tissue around the implant were analyzed qualitatively.Results: The results demonstrated that under the oblique loading process, the external hexagon connection showed significantly higher stress concentrations in the bone tissue (P < 0.05) compared with the tapered connection. Moreover, the buccal and mesial regions of the cortical bone concentrated significantly higher stress (P < 0.005) to the external hexagon implant type. Under the oblique loading direction, the increased external hexagon implant angulation induced a significantly higher stress concentration (P = 0.045).Conclusions: The study results show that: 1) the oblique load was more damaging to bone tissue, mainly when associated with external hexagon implants; and 2) there was a higher stress concentration on the buccal region in comparison to all other regions under oblique load.

The effect of power-ultrasound on the pretreatment of acidified aqueous solutions of banana flower-stalk: Structural, chemical and statistical analysis

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Statistical analysis of texture in trunk images for biometric identification of tree species

The identification of tree species is a key step for sustainable management plans of forest resources, as well as for several other applications that are based on such surveys. However, the present available techniques are dependent on the presence of tree structures, such as flowers, fruits, and leaves, limiting the identification process to certain periods of the year Therefore, this article introduces a study on the application of statistical parameters for texture classification of tree trunk images. For that, 540 samples from five Brazilian native deciduous species were acquired and measures of entropy, uniformity, smoothness, asymmetry (third moment), mean, and standard deviation were obtained from the presented textures. Using a decision tree, a biometric species identification system was constructed and resulted to a 0.84 average precision rate for species classification with 0.83accuracy and 0.79 agreement. Thus, it can be considered that the use of texture presented in trunk images can represent an important advance in tree identification, since the limitations of the current techniques can be overcome.

Multivariate morphometrics and allometry and allometry in a polymorphic ant

In this paper we describe how morphological castes can be distinguished using multivariate statistical methods combined with jackknife estimators of the allometric coefficients. Data from the polymorphic ant, Camponotus rufipes, produced two distinct patterns of allometric variation, and thus two morphological castes. Morphometric analysis distinguished different allometric patterns within the two castes, with overall variability being greater in the major workers. Caste-specific scaling variabilities were associated with the relative importance of first principal component. The static multivariate allometric coefficients for each of 10 measured characters were different between castes, but their relative magnitudes within castes were similar. Multivariate statistical analysis of worker polymorphism in ants is a more complete descriptor of shape variation than, and provides statistical and conceptual advantages over, the standard bivariate techniques commonly used.

PXRF and multivariate statistics analysis of pre-colonial pottery from northeast of Brazil

Portable system of energy dispersive X-ray fluorescence was used to determine the elemental composition of 68 pottery fragments from Sambaqui do Bacanga, an archeological site in Sao Luis, Maranhao, Brazil. This site was occupied from 6600 BP until 900 BP. By determining the element chemical composition of those fragments, it was possible to verify the existence of engobe in 43 pottery fragments. Obtained from two-dimensional graphs and hierarchical cluster analysis performed in fragments of stratigraphies from surface and 113-cm level, and 10 to 20, 132 and 144-cm level, it was possible to group these fragments in five distinct groups, according to their stratigraphies. The results of data grouping (two-dimensional graphics) are in agreement with hierarchical cluster analysis by Ward method. Copyright (C) 2011 John Wiley & Sons, Ltd.

From "wet biology" to statistical analysis of structural features with bioinformatics tools

Many new Escherichia coli outer membrane proteins have recently been identified by proteomics techniques. However, poorly expressed proteins and proteins expressed only under certain conditions may escape detection when wild-type cells are grown under standard conditions. Here, we have taken a complementary approach where candidate outer membrane proteins have been identified by bioinformatics prediction, cloned and overexpressed, and finally localized by cell fractionation experiments. Out of eight predicted outer membrane proteins, we have confirmed the outer membrane localization for five—YftM, YaiO, YfaZ, CsgF, and YliI—and also provide preliminary data indicating that a sixth—YfaL—may be an outer membrane autotransporter.

Statistical analysis and simulation techniques in wall-bounded turbulence

The present work is devoted to the assessment of the energy fluxes physics in the space of scales and physical space of wall-turbulent flows. The generalized Kolmogorov equation will be applied to DNS data of a turbulent channel flow in order to describe the energy fluxes paths from production to dissipation in the augmented space of wall-turbulent flows. This multidimensional description will be shown to be crucial to understand the formation and sustainment of the turbulent fluctuations fed by the energy fluxes coming from the near-wall production region. An unexpected behavior of the energy fluxes comes out from this analysis consisting of spiral-like paths in the combined physical/scale space where the controversial reverse energy cascade plays a central role. The observed behavior conflicts with the classical notion of the Richardson/Kolmogorov energy cascade and may have strong repercussions on both theoretical and modeling approaches to wall-turbulence. To this aim a new relation stating the leading physical processes governing the energy transfer in wall-turbulence is suggested and shown able to capture most of the rich dynamics of the shear dominated region of the flow. Two dynamical processes are identified as driving mechanisms for the fluxes, one in the near wall region and a second one further away from the wall. The former, stronger one is related to the dynamics involved in the near-wall turbulence regeneration cycle. The second suggests an outer self-sustaining mechanism which is asymptotically expected to take place in the log-layer and could explain the debated mixed inner/outer scaling of the near-wall statistics. The same approach is applied for the first time to a filtered velocity field. A generalized Kolmogorov equation specialized for filtered velocity field is derived and discussed. The results will show what effects the subgrid scales have on the resolved motion in both physical and scale space, singling out the prominent role of the filter length compared to the cross-over scale between production dominated scales and inertial range, lc, and the reverse energy cascade region lb. The systematic characterization of the resolved and subgrid physics as function of the filter scale and of the wall-distance will be shown instrumental for a correct use of LES models in the simulation of wall turbulent flows. Taking inspiration from the new relation for the energy transfer in wall turbulence, a new class of LES models will be also proposed. Finally, the generalized Kolmogorov equation specialized for filtered velocity fields will be shown to be an helpful statistical tool for the assessment of LES models and for the development of new ones. As example, some classical purely dissipative eddy viscosity models are analyzed via an a priori procedure.

Statistical analysis of written languages

La tesi presenta una serie di risultati dell'analisi quantitativa sulla linguistica. Inizialmente sono studiate due fra le leggi empiriche più famose di questo campo, le leggi di Zipf e Heaps, e vengono esposti vari modelli sullo sviluppo del linguaggio. Nella seconda parte si giunge alla discussione di risultati più specifici sulla presenza di fenomeni di burstiness e di correlazioni a lungo raggio nei testi. Tutti questi studi teorici sono affiancati da analisi sperimentali, svolte utilizzando varie traduzioni del libro "Guerra e pace" di Leo Tolstoj e concentrate principalmente sulle eventuali differenze riscontrabili tra le diverse lingue.

Geomorphological and statistical analysis on Ravenna dune fields changes, based on Terrestrial Laser Technology

Coastal sand dunes represent a richness first of all in terms of defense from the sea storms waves and the saltwater ingression; moreover these morphological elements constitute an unique ecosystem of transition between the sea and the land environment. The research about dune system is a strong part of the coastal sciences, since the last century. Nowadays this branch have assumed even more importance for two reasons: on one side the born of brand new technologies, especially related to the Remote Sensing, have increased the researcher possibilities; on the other side the intense urbanization of these days have strongly limited the dune possibilities of development and fragmented what was remaining from the last century. This is particularly true in the Ravenna area, where the industrialization united to the touristic economy and an intense subsidence, have left only few dune ridges residual still active. In this work three different foredune ridges, along the Ravenna coast, have been studied with Laser Scanner technology. This research didn’t limit to analyze volume or spatial difference, but try also to find new ways and new features to monitor this environment. Moreover the author planned a series of test to validate data from Terrestrial Laser Scanner (TLS), with the additional aim of finalize a methodology to test 3D survey accuracy. Data acquired by TLS were then applied on one hand to test some brand new applications, such as Digital Shore Line Analysis System (DSAS) and Computational Fluid Dynamics (CFD), to prove their efficacy in this field; on the other hand the author used TLS data to find any correlation with meteorological indexes (Forcing Factors), linked to sea and wind (Fryberger's method) applying statistical tools, such as the Principal Component Analysis (PCA).

Statistical analysis of the error associated with the simplification of the stratigraphy in geotechnical models

The uncertainties in the determination of the stratigraphic profile of natural soils is one of the main problems in geotechnics, in particular for landslide characterization and modeling. The study deals with a new approach in geotechnical modeling which relays on a stochastic generation of different soil layers distributions, following a boolean logic – the method has been thus called BoSG (Boolean Stochastic Generation). In this way, it is possible to randomize the presence of a specific material interdigitated in a uniform matrix. In the building of a geotechnical model it is generally common to discard some stratigraphic data in order to simplify the model itself, assuming that the significance of the results of the modeling procedure would not be affected. With the proposed technique it is possible to quantify the error associated with this simplification. Moreover, it could be used to determine the most significant zones where eventual further investigations and surveys would be more effective to build the geotechnical model of the slope. The commercial software FLAC was used for the 2D and 3D geotechnical model. The distribution of the materials was randomized through a specifically coded MatLab program that automatically generates text files, each of them representing a specific soil configuration. Besides, a routine was designed to automate the computation of FLAC with the different data files in order to maximize the sample number. The methodology is applied with reference to a simplified slope in 2D, a simplified slope in 3D and an actual landslide, namely the Mortisa mudslide (Cortina d’Ampezzo, BL, Italy). However, it could be extended to numerous different cases, especially for hydrogeological analysis and landslide stability assessment, in different geological and geomorphological contexts.