Statistical analysis of eight surface ozone measurement series for various sites in Ireland

Data from various stations having different measurement record periods between 1988 and 2007 are analyzed to investigate the surface ozone concentration, long-term trends, and seasonal changes in and around Ireland. Time series statistical analysis is performed on the monthly mean data using seasonal and trend decomposition procedures and the Box-Jenkins approach (autoregressive integrated moving average). In general, ozone concentrations in the Irish region are found to have a negative trend at all sites except at the coastal sites of Mace Head and Valentia. Data from the most polluted Dublin city site have shown a very strong negative trend of −0.33 ppb/yr with a 95% confidence limit of 0.17 ppb/yr (i.e., −0.33 ± 0.17) for the period 2002−2007, and for the site near the city of Cork, the trend is found to be −0.20 ± 0.11 ppb/yr over the same period. The negative trend for other sites is more pronounced when the data span is considered from around the year 2000 to 2007. Rural sites of Wexford and Monaghan have also shown a very strong negative trend of −0.99 ± 0.13 and −0.58 ± 0.12, respectively, for the period 2000−2007. Mace Head, a site that is representative of ozone changes in the air advected from the Atlantic to Europe in the marine planetary boundary layer, has shown a positive trend of about +0.16 ± 0.04 ppb per annum over the entire period 1988−2007, but this positive trend has reduced during recent years (e.g., in the period 2001−2007). Cluster analysis for back trajectories are performed for the stations having a long record of data, Mace Head and Lough Navar. For Mace Head, the northern and western clean air sectors have shown a similar positive trend (+0.17 ± 0.02 ppb/yr for the northern sector and +0.18 ± 0.02 ppb/yr for the western sector) for the whole period, but partial analysis for the clean western sector at Mace Head shows different trends during different time periods with a decrease in the positive trend since 1988 indicating a deceleration in the ozone trend for Atlantic air masses entering Europe.

Thermodynamic and statistical analysis of soybean oil extraction process using renewable solvent

The main goal of this work was to evaluate thermodynamic parameters of the soybean oil extraction process using ethanol as solvent. The experimental treatments were as follows: aqueous solvents with water contents varying from 0 to 13% (mass basis) and extraction temperature varying from 50 to 100 degrees C. The distribution coefficients of oil at equilibrium have been used to calculate enthalpy, entropy and free energy changes. The results indicate that oil extraction process with ethanol is feasible and spontaneous, mainly under higher temperature. Also, the influence of water level in the solvent and temperature were analysed using the response surface methodology (RSM). It can be noted that the extraction yield was highly affected by both independent variables. A joint analysis of thermodynamic and RSM indicates the optimal level of solvent hydration and temperature to perform the extraction process.

Statistical analysis of proficiency testing results under elliptical distributions

The use of inter-laboratory test comparisons to determine the performance of individual laboratories for specific tests (or for calibration) [ISO/IEC Guide 43-1, 1997. Proficiency testing by interlaboratory comparisons - Part 1: Development and operation of proficiency testing schemes] is called Proficiency Testing (PT). In this paper we propose the use of the generalized likelihood ratio test to compare the performance of the group of laboratories for specific tests relative to the assigned value and illustrate the procedure considering an actual data from the PT program in the area of volume. The proposed test extends the test criteria in use allowing to test for the consistency of the group of laboratories. Moreover, the class of elliptical distributions are considered for the obtained measurements. (C) 2008 Elsevier B.V. All rights reserved.

Statistical analysis of the Doppler broadening coincidence spectrum of electron-positron annihilation radiation in silicon

We report a statistical analysis of Doppler broadening coincidence data of electron-positron annihilation radiation in silicon using a (22)Na source. The Doppler broadening coincidence spectrum was fit using a model function that included positron annihilation at rest with 1s, 2s, 2p, and valence band electrons. In-flight positron annihilation was also fit. The response functions of the detectors accounted for backscattering, combinations of Compton effects, pileup, ballistic deficit, and pulse-shaping problems. The procedure allows the quantitative determination of positron annihilation with core and valence electron intensities as well as their standard deviations directly from the experimental spectrum. The results obtained for the core and valence band electron annihilation intensities were 2.56(9)% and 97.44(9)%, respectively. These intensities are consistent with published experimental data treated by conventional analysis methods. This new procedure has the advantage of allowing one to distinguish additional effects from those associated with the detection system response function. (C) 2009 Elsevier B.V. All rights reserved.

Identifying cis-regulatory elements by statistical analysis and phylogenetic footprinting and analyzing their coexistence and related gene ontology

Discovery of cis-regulatory elements in gene promoters is a highly challenging research issue in computational molecular biology. This paper presents a novel approach to searching putative cis-regulatory elements in human promoters by first finding 8-mer sequences of high statistical significance from gene promoters of humans, mice, and Drosophila melanogaster, respectively, and then identifying the most conserved ones across the three species (phylogenetic footprinting). In this study, a conservation analysis on both closely related species (humans and mice) and distantly related species (humans/mice and Drosophila) is conducted not only to examine more candidates but also to improve the prediction accuracy. We have found 124 putative cis-regulatory elements and grouped these into 20 clusters. The investigation on the coexistence of these clusters in human gene promoters reveals that SP1, EGR, and NRF-1 are the dominant clusters appearing in the combinatorial combination of up to five clusters. Gene Ontology (GO) analysis also shows that many GO categories of transcription factors binding to these cis-regulatory elements match the GO categories of genes whose promoters contain these elements. Compared with previous research, the contribution of this study lies not only in the finding of new cis-regulatory elements, but also in its pioneering exploration on the coexistence of discovered elements and the GO relationship between transcription factors and regulated genes. This exploration verifies the putative cis-regulatory elements that have been found from this study and also gives new insight on the regulation mechanisms of gene expression.

Statistical analysis of finite element modeling in sheet metal forming and springback analysis

This work focuses on development of a method to statistically study forming and springback problems of TRansformation Induced Plasticity (TRIP) through an industrial case study. A Design of Experiments (DOE) approach was used to study the sensitivity of predictions to four user input parameters in implicit and explicit sheet metal forming codes. Numerical results were compared to experimental measurements of parts stamped in an industrial production line. The accuracy of forming strain predictions for TRIP steel were comparable with conventional steel, but the springback predictions of TRIP steel were far less accurate. The statistical importance of selected parameters for forming and springback prediction is also discussed. Changes of up to ±10% in Young's modulus and coefficient of friction were found to be insignificant in improving or deteriorating the statistical correlation of springback accuracies.

Support vector machine (SVM) based multiclass prediction with basic statistical analysis of plasminogen activators

Plasminogen (Pg), the precursor of the proteolytic and fibrinolytic enzyme of blood, is converted to the active enzyme plasmin (Pm) by different plasminogen activators (tissue plasminogen activators and urokinase), including the bacterial activators streptokinase and staphylokinase, which activate Pg to Pm and thus are used clinically for thrombolysis. The identification of Pg-activators is therefore an important step in understanding their functional mechanism and derives new therapies.

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.

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.

Quantitative Chemical Profile and Multivariate Statistical Analysis of Alembic Distilled Sugarcane Spirit Fractions

Concentrations of 39 organic compounds were determined in three fractions (head, heart and tail) obtained from the pot still distillation of fermented sugarcane juice. The results were evaluated using analysis of variance (ANOVA), Tukey's test, principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA). According to PCA and HCA, the experimental data lead to the formation of three clusters. The head fractions give rise to a more defined group. The heart and tail fractions showed some overlap consistent with its acid composition. The predictive ability of calibration and validation of the model generated by LDA for the three fractions classification were 90.5 and 100%, respectively. This model recognized as the heart twelve of the thirteen commercial cachacas (92.3%) with good sensory characteristics, thus showing potential for guiding the process of cuts.

Quantitative chemical profile and multivariate statistical analysis of alembic distilled sugarcane spirit fractions

As concentrações de 39 compostos orgânicos foram determinadas em três frações (cabeça, coração e cauda) obtidas da destilação em alambique do caldo de cana fermentado. Os resultados foram avaliados utilizando-se análise de variância (ANOVA), teste de Tukey, análise de componentes principais (PCA), agrupamento hierárquico (HCA) e análise discriminante linear (LDA). De acordo com PCA e HCA, os dados experimentais conduzem à formação de três agrupamentos. As frações de cabeça deram origem a um grupo mais definido. As frações coração e cauda apresentaram alguma sobreposição coerente com sua composição em ácidos. As habilidades preditivas de calibração e validação dos modelos gerados pela LDA para a classificação das três frações foram de 90,5 e 100%, respectivamente. Este modelo reconheceu como coração doze de treze cachaças comerciais (92,3%) com boas características sensoriais, apresentando potencial para a orientação do processo de cortes.