Classificação multivariada de ervas medicinais da Região Amazônica e suas infusões de acordo com sua composição mineral

In this study, the mineral composition of leaves and teas of medicinal plants was evaluated. Ca, Cu, Fe, Mg, Mn e Zn were determined in the samples using flame atomic absorption spectrometry. Principal component analysis was applied to discriminate the samples studied. The samples were divided within the 2 groups according to their mineral composition. Copper and iron were the variables that contributed most to the separation of the samples followed by Ca, Mg, Mn and Zn. The information in the principal component analysis was confirmed by the dendrogram obtained by hierarchical cluster analysis.

Chemical composition of volatiles from male and female specimens of Baccharis trimera collected in two distant regions of southern brazil: a comparative study using chemometrics

GC/MS/FID analyses of volatile compounds from cladodes and inflorescences from male and female specimens of Baccharis trimera (Less.) DC. collected in the states of Paraná and Santa Catarina, Brazil, showed that carquejyl acetate was the primary volatile component (38% to 73%), while carquejol and ledol were identified in lower concentrations. Data were subjected to hierarchical cluster analysis and principal component analysis, which confirmed that the chemical compositions of all samples were similar. The results presented here highlight the occurrence of the same chemotype of B. trimera in three southern states of Brazil.

Análise exploratória aplicada a espectros de reflexão total atenuada no infravermelho com transformada de Fourier (ATR-FTIR) de blendas de biodiesel/diesel

In this study, hierarchical cluster analysis (HCA) and principal component analysis (PCA) were used to classify blends produced from diesel S500 and different kinds of biodiesel produced by the TDSP methodology. The different kinds of biodiesel studied in this work were produced from three raw materials: soybean oil, waste cooking oil and hydrogenated vegetable oil. Methylic and ethylic routes were employed for the production of biodiesel. HCA and PCA were performed on the data from attenuated total reflectance Fourier transform infrared spectroscopy, showing the separation of the blends into groups according to biodiesel content present in the blends and to the kind of biodiesel used to form the mixtures.

Variation of essential oil composition of Tapirira guianensis Aubl. (Anacardiaceae) from two sandbank forests, north of Brazil

Tapirira guianensis (Anacardiaceae) is used in traditional medicine and is important for the recovery of degraded areas and riparian forests because the T. guianensis fruits are highly consumed by wildlife. Volatile components from dried leaves and branches of five individual plants of T. guianensis were collected in two sandbank forests of the State of Pará (Extractive Reserve Maracanã and Area of Environmental Protection Algodoal/Maiandeua), extracted by hydrodistillation using a Clevenger-type apparatus, and analyzed by GC/MS. The ten oils obtained are comprised mostly of sesquiterpene hydrocarbons (58.49 to 100%), with (E)-caryophyllene, β-selinene, α-selinene, β-sesquiphellandrene, and α-zingiberene being the most prominent. The results of the oil compositions were processed by Hierarchical Component Analysis (HCA) allowing the establishment of three groups of essential oils for T. guianensis differentiated by the content of β-selinene/α-selinene (Type I), (E)-caryophyllene (Type II), and β-sesquiphellandrene/α-zingiberene (Type III).

Resolução multivariada de curvas com mínimos quadrados alternantes: descrição, funcionamento e aplicações

Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS) is a resolution method that has been efficiently applied in many different fields, such as process analysis, environmental data and, more recently, hyperspectral image analysis. When applied to second order data (or to three-way data) arrays, recovery of the underlying basis vectors in both measurement orders (i.e. signal and concentration orders) from the data matrix can be achieved without ambiguities if the trilinear model constraint is considered during the ALS optimization. This work summarizes different protocols of MCR-ALS application, presenting a case study: near-infrared image spectroscopy.

CHEMOSTAT, UM SOFTWARE GRATUITO PARA ANÁLISE EXPLORATÓRIA DE DADOS MULTIVARIADOS

The objective of this work was to develop a free access exploratory data analysis software application for academic use that is easy to install and can be handled without user-level programming due to extensive use of chemometrics and its association with applications that require purchased licenses or routines. The developed software, called Chemostat, employs Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA), intervals Principal Component Analysis (iPCA), as well as correction methods, data transformation and outlier detection. The data can be imported from the clipboard, text files, ASCII or FT-IR Perkin-Elmer “.sp” files. It generates a variety of charts and tables that allow the analysis of results that can be exported in several formats. The main features of the software were tested using midinfrared and near-infrared spectra in vegetable oils and digital images obtained from different types of commercial diesel. In order to validate the software results, the same sets of data were analyzed using Matlab© and the results in both applications matched in various combinations. In addition to the desktop version, the reuse of algorithms allowed an online version to be provided that offers a unique experience on the web. Both applications are available in English.

ANÁLISE EXPLORATÓRIA DAS CONCENTRAÇÕES DOS METAIS NA, CA, MG, SR E FE EM EXTRATO AQUOSO DE PETRÓLEO, DETERMINADOS POR ICP OES, APÓS OTIMIZAÇÃO EMPREGANDO PLANEJAMENTO DE EXPERIMENTOS

AbstractThe purpose of this study was to evaluate the best operating conditions of ICP OES for the determination of Na, Ca, Mg, Sr and Fe in aqueous extract of crude oil obtained after hot extraction with organic solvents (ASTM D 6470-99 modified). Thus, the full factorial design and central composite design were used to optimize the best conditions for the flow of nebulization gas, the flow of auxiliary gas, and radio frequency power. After optimization of variables, a study to obtain correct classification of the 18 samples of aqueous extract of crude oils (E1 to E18) from three production and refining fields was carried out. Exploratory analysis of these extracts was performed by principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA), using the original variables as the concentration of the metals Na, Ca, Mg, Sr and Fe determined by ICP OES.

Imaging and Characterisation of Dirt Particles in Pulp and Paper

Dirt counting and dirt particle characterisation of pulp samples is an important part of quality control in pulp and paper production. The need for an automatic image analysis system to consider dirt particle characterisation in various pulp samples is also very critical. However, existent image analysis systems utilise a single threshold to segment the dirt particles in different pulp samples. This limits their precision. Based on evidence, designing an automatic image analysis system that could overcome this deficiency is very useful. In this study, the developed Niblack thresholding method is proposed. The method defines the threshold based on the number of segmented particles. In addition, the Kittler thresholding is utilised. Both of these thresholding methods can determine the dirt count of the different pulp samples accurately as compared to visual inspection and the Digital Optical Measuring and Analysis System (DOMAS). In addition, the minimum resolution needed for acquiring a scanner image is defined. By considering the variation in dirt particle features, the curl shows acceptable difference to discriminate the bark and the fibre bundles in different pulp samples. Three classifiers, called k-Nearest Neighbour, Linear Discriminant Analysis and Multi-layer Perceptron are utilised to categorize the dirt particles. Linear Discriminant Analysis and Multi-layer Perceptron are the most accurate in classifying the segmented dirt particles by the Kittler thresholding with morphological processing. The result shows that the dirt particles are successfully categorized for bark and for fibre bundles.

Holocene Varved Lake Sediments as Records of Palaeoenvironmental Change and Geomagnetic Palaeosecular Variation in Eastern Finland

This dissertation discusses Holocene palaeoenvironmental and palaeomagnetic secular variation (PSV) records reconstructed from sediments preserved in Lake Lehmilampi (63º37´N, 29º06´E) and Lake Kortejärvi (63º37´N, 28º56´E) in eastern Finland. Several piston and freeze cores were obtained from both lakes for varve and magnetic analyses. Sediment samples were impregnated in low-viscosity epoxy and physical parameters of varves, including varve thickness and relative grey-scale values, were recorded using x-ray densitometry combined with semiautomatic digital image analysis. On average, varve records of Lehmilampi and Kortejärvi cover 5122 and 3902 years, respectively. Past solar activity, as estimated by residual ₁₄C data, compares favourably with varve thicknesses from Lehmilampi during the last 2000 years. This indicates the potential of clastic-organic varves to record sensitively climatic variations. Bulk magnetic parameters, including magnetic susceptibility together with natural, anhysteretic and isothermal remanent magnetizations, were measured to describe mineral magnetic properties and geomagnetic palaeosecular variation recorded in the sediments. Main stages in the development of the investigated lakes are reflected in the variations in the mineral magnetic records, sediment lithology and composition. Similar variations in magnetic parameters and sediment organic matter suggest contribution of bacterial magnetite in the magnetic assemblages of Lehmilampi. Inclination and relative declination records yielded largely consistent results, attesting to the great potential of these sediments to preserve directional palaeosecular variation in high resolution. The PSV data from Lehmilampi and Kortejärvi were stacked into North Karelian PSV stack, which may be used for dating homogenous lake sediments in the same regional context. Reconstructed millennial variations in relative palaeointensity results are approximately in agreement with those seen in the absolute palaeointensity data from Europe. Centennial variations in the relative palaeointensity, however, are influenced by environmental changes. Caution is recommended when using varved lake sediments in reconstructing relative palaeointensity.

The Role of Tactical Marketing Decisions on New Product Performance: The Moderating Effect of Entry Timing

This study focuses on observing how Finnish companies execute their new product launch processes. The main objective was to find out how entry timing moderates the relationship between launch tactics (namely product innovativeness, price and emotional advertising) and new product performance (namely sales volume and customer profitability). The empirical analysis was based on data collected in Lappeenranta University of Technology. The sample consisted of Finnish companies representing different industries and innovation activities. Altogether 272 usable responses were received representing a response rate of 37.67%. The measures were first assessed by using exploratory factor analysis (EFA) in PASW Statistics 18 and then further verified with confirmatory factor analysis (CFA) in LISREL 8.80. To test the hypotheses of the moderating effects of entry timing, hierarchical regression analysis was used in PASW Statistics 18. The results of the study revealed that the effect of product innovativeness on new product sales volume is dependent on entry timing. This implies that companies should carefully consider what would be the best time for entering the market when launching highly innovative new products. The results also depict a positive relationship between emotional advertising and new product sales volume. In addition, partial support was found for a positive relationship between pricing and new product customer profitability.

Digital surface area assessment of broiler chickens

Surface area (SA) of poultry is an important parameter for heat and mass transfer calculations. Optical approaches, such as the moiré technique (MT), are non-destructive, result in accuracy and speed gains, and preserve the object integrity. The objective of this research was to develop and validate a new protocol for estimating the surface area (SA) of broiler chickens based on the MT. Sixty-six Ross breed broiler chickens (twenty-seven male, thirty-nine female, ages spanning all growth phases) were used in this study. The dimensions (length, width and height) and body mass of randomly selected broiler chickens were evaluated in the laboratory. Chickens were illuminated by a light source, and grids were projected onto the chickens to allow their shape to be determined and recorded. Next, the skin and feathers of the chickens were removed to allow SA to be determined by conventional means. These measurements were then used for calibration and validation. The MT for image analysis was a reliable means of evaluating the three-dimensional shape and SA of broiler chickens. This technique, which is neither invasive nor destructive, is a good alternative to the conventional destructive methods.

Detection of soybean planted areas through orbital images based on culture spectral dynamics

The soybean is important to the economy of Brazil, so the estimation of the planted area and the production with higher antecedence and reliability becomes essential. Techniques related to Remote Sensing may help to obtain this information at lower cost and less subjectivity in relation to traditional surveys. The aim of this study is to estimate the planted area with soybean culture in the crop of 2008/2009 in cities in the west of the state of Paraná, in Brazil, based on the spectral dynamics of the culture and through the use of the specific system of analysis for images of Landsat 5/TM satellite. The obtained results were satisfactory, because the classification supervised by Maximum Verisimilitude - MaxVer along with the techniques of the specific system of analysis for satellite images has allowed an estimate of soybean planted area (soybean mask), obtaining values ​​of the metrics of Global Accuracy with an average of 79.05% and Kappa Index over 63.50% in all cities. The monitoring of a reference area was of great importance for determining the vegetative phase in which the culture is more different from the other targets, facilitating the choice of training samples (ROIs) and avoiding misclassifications.

Management zones in agriculture acording to the soil and landscape variables

The study of spatial variability of soil and plants attributes, or precision agriculture, a technique that aims the rational use of natural resources, is expanding commercially in Brazil. Nevertheless, there is a lack of mathematical analysis that supports the correlation of these independent variables and their interactions with the productivity, identifying scientific standards technologically applicable. The aim of this study was to identify patterns of soil variability according to the eleven physical and seven chemical indicators in an agricultural area. It was used two multivariate techniques: the hierarchical cluster analysis (HCA) and the principal component analysis (PCA). According to the HCA, the area was divided into five management zones: zone 1 with 2.87ha, zone 2 with 0.8ha, zone 3 with 1.84ha, zone 4 with 1.33ha and zone 5 with 2.76ha. By the PCA, it was identified the most important variables within each zone: V% for the zone 1, CTC in the zone 2, levels of H+Al in the zone 4 and sand content and altitude in the zone 5. The zone 3 was classified as an intermediate zone with characteristics of all others. According to the results it is concluded that it is possible to separate into groups (management zones) samples with the same patterns of variability by the multivariate statistical techniques.

Biopolttoaineiden leijutusominaisuuksien karakterisointi

Tässä diplomityössä selvitettiin biopolttoaineiden ominaisuuksia leijutuksen kannalta. Ensiksi tutkittavat biopolttoaineet, hake ja turve, seulottiin ja seulotut näytteet analysoitiin. Seuraavaksi turvetta ja haketta leijutettiin eri nopeuksilla ja eri leijutusnopeuksilla saadut näytteet analysoitiin kuva-analysilla. Partikkeleista selvitettiin runsaasti mittoja, kuten keskihalkaisija, pinta-ala ja muotokerroin. Kirjallisuudesta löytyvien korrelaatioiden avulla laskettiin leijutettujen partikkelien vastuskertoimet ja terminaalinopeudet. Korrelaatioiden tuloksia verrattiin mittaustuloksiin. Tässä työssä myös laskettiin kyseisiin biopolttoaineisiin vaikuttavat ominaisvoimat leijutuksessa sekä laskettiin korjauskerroin, jota käytettiin ominaisvoimien korjaamiseen. Referenssiaineina käytettiin hiekkaa ja lasikuulia.

A Farewell to Flat Biology. Three-dimensional Cell Culture Models in Cancer Drug Target Identification and Validation

Cells of epithelial origin, e.g. from breast and prostate cancers, effectively differentiate into complex multicellular structures when cultured in three-dimensions (3D) instead of conventional two-dimensional (2D) adherent surfaces. The spectrum of different organotypic morphologies is highly dependent on the culture environment that can be either non-adherent or scaffold-based. When embedded in physiological extracellular matrices (ECMs), such as laminin-rich basement membrane extracts, normal epithelial cells differentiate into acinar spheroids reminiscent of glandular ductal structures. Transformed cancer cells, in contrast, typically fail to undergo acinar morphogenic patterns, forming poorly differentiated or invasive multicellular structures. The 3D cancer spheroids are widely accepted to better recapitulate various tumorigenic processes and drug responses. So far, however, 3D models have been employed predominantly in the Academia, whereas the pharmaceutical industry has yet to adopt a more widely and routine use. This is mainly due to poor characterisation of cell models, lack of standardised workflows and high throughput cell culture platforms, and the availability of proper readout and quantification tools. In this thesis, a complete workflow has been established entailing well-characterised 3D cell culture models for prostate cancer, a standardised 3D cell culture routine based on high-throughput-ready platform, automated image acquisition with concomitant morphometric image analysis, and data visualisation, in order to enable large-scale high-content screens. Our integrated suite of software and statistical analysis tools were optimised and validated using a comprehensive panel of prostate cancer cell lines and 3D models. The tools quantify multiple key cancer-relevant morphological features, ranging from cancer cell invasion through multicellular differentiation to growth, and detect dynamic changes both in morphology and function, such as cell death and apoptosis, in response to experimental perturbations including RNA interference and small molecule inhibitors. Our panel of cell lines included many non-transformed and most currently available classic prostate cancer cell lines, which were characterised for their morphogenetic properties in 3D laminin-rich ECM. The phenotypes and gene expression profiles were evaluated concerning their relevance for pre-clinical drug discovery, disease modelling and basic research. In addition, a spontaneous model for invasive transformation was discovered, displaying a highdegree of epithelial plasticity. This plasticity is mediated by an abundant bioactive serum lipid, lysophosphatidic acid (LPA), and its receptor LPAR1. The invasive transformation was caused by abrupt cytoskeletal rearrangement through impaired G protein alpha 12/13 and RhoA/ROCK, and mediated by upregulated adenylyl cyclase/cyclic AMP (cAMP)/protein kinase A, and Rac/ PAK pathways. The spontaneous invasion model tangibly exemplifies the biological relevance of organotypic cell culture models. Overall, this thesis work underlines the power of novel morphometric screening tools in drug discovery.