895 resultados para discriminant analysis and cluster analysis
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BACKGROUND: Non-invasive diagnostic strategies aimed at identifying biomarkers of cancer are of great interest for early cancer detection. Urine is potentially a rich source of volatile organic metabolites (VOMs) that can be used as potential cancer biomarkers. Our aim was to develop a generally reliable, rapid, sensitive, and robust analytical method for screening large numbers of urine samples, resulting in a broad spectrum of native VOMs, as a tool to evaluate the potential of these metabolites in the early diagnosis of cancer. METHODS: To investigate urinary volatile metabolites as potential cancer biomarkers, urine samples from 33 cancer patients (oncological group: 14 leukaemia, 12 colorectal and 7 lymphoma) and 21 healthy (control group, cancer-free) individuals were qualitatively and quantitatively analysed. Dynamic solid-phase microextraction in headspace mode (dHS-SPME) using a carboxenpolydimethylsiloxane (CAR/PDMS) sorbent in combination with GC-qMS-based metabolomics was applied to isolate and identify the volatile metabolites. This method provides a potential non-invasive method for early cancer diagnosis as a first approach. To fulfil this objective, three important dHS-SPME experimental parameters that influence extraction efficiency (fibre coating, extraction time and temperature of sampling) were optimised using a univariate optimisation design. The highest extraction efficiency was obtained when sampling was performed at 501C for 60min using samples with high ionic strengths (17% sodium chloride, wv 1) and under agitation. RESULTS: A total of 82 volatile metabolites belonging to distinct chemical classes were identified in the control and oncological groups. Benzene derivatives, terpenoids and phenols were the most common classes for the oncological group, whereas ketones and sulphur compounds were the main classes that were isolated from the urine headspace of healthy subjects. The results demonstrate that compound concentrations were dramatically different between cancer patients and healthy volunteers. The positive rates of 16 patients among the 82 identified were found to be statistically different (Po0.05). A significant increase in the peak area of 2-methyl3-phenyl-2-propenal, p-cymene, anisole, 4-methyl-phenol and 1,2-dihydro-1,1,6-trimethyl-naphthalene in cancer patients was observed. On average, statistically significant lower abundances of dimethyl disulphide were found in cancer patients. CONCLUSIONS: Gas chromatographic peak areas were submitted to multivariate analysis (principal component analysis and supervised linear discriminant analysis) to visualise clusters within cases and to detect the volatile metabolites that are able to differentiate cancer patients from healthy individuals. Very good discrimination within cancer groups and between cancer and control groups was achieved.
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In this study the effect of the cultivar on the volatile profile of five different banana varieties was evaluated and determined by dynamic headspace solid-phase microextraction (dHS-SPME) combined with one-dimensional gas chromatography–mass spectrometry (1D-GC–qMS). This approach allowed the definition of a volatile metabolite profile to each banana variety and can be used as pertinent criteria of differentiation. The investigated banana varieties (Dwarf Cavendish, Prata, Maçã, Ouro and Platano) have certified botanical origin and belong to the Musaceae family, the most common genomic group cultivated in Madeira Island (Portugal). The influence of dHS-SPME experimental factors, namely, fibre coating, extraction time and extraction temperature, on the equilibrium headspace analysis was investigated and optimised using univariate optimisation design. A total of 68 volatile organic metabolites (VOMs) were tentatively identified and used to profile the volatile composition in different banana cultivars, thus emphasising the sensitivity and applicability of SPME for establishment of the volatile metabolomic pattern of plant secondary metabolites. Ethyl esters were found to comprise the largest chemical class accounting 80.9%, 86.5%, 51.2%, 90.1% and 6.1% of total peak area for Dwarf Cavendish, Prata, Ouro, Maçã and Platano volatile fraction, respectively. Gas chromatographic peak areas were submitted to multivariate statistical analysis (principal component and stepwise linear discriminant analysis) in order to visualise clusters within samples and to detect the volatile metabolites able to differentiate banana cultivars. The application of the multivariate analysis on the VOMs data set resulted in predictive abilities of 90% as evaluated by the cross-validation procedure.
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The volatile composition of different apple varieties of Malus domestica Borkh. species from different geographic regions at Madeira Islands, namely Ponta do Pargo (PP), Porto Santo (PS), and Santo da Serra (SS) was established by headspace solid-phase microextraction (HS-SPME) procedure followed by GC-MS (GC-qMS) analysis. Significant parameters affecting sorption process such as fiber coating, extraction temperature,extractiontime,sampleamount,dilutionfactor,ionicstrength,anddesorption time,wereoptimizedanddiscussed.TheSPMEfibercoatedwith50/30 lmdivinylbenzene/carboxen/PDMS (DVB/CAR/PDMS) afforded highest extraction efficiency of volatile compounds, providing the best sensitivity for the target volatiles, particularly whenthesampleswereextractedat508Cfor30 minwithconstantmagneticstirring. A qualitative and semi-quantitative analysis between the investigated apple species has been established. It was possible to identify about 100 of volatile compounds amongpulp(46,45,and39),peel(64,60,and64),andentirefruit(65,43,and50)inPP, PS,andSSapples,respectively.Ethylesters,terpenes,andhigheralcoholswerefound tobethemostrepresentativevolatiles. a-Farnesene,hexan-1-olandhexyl2-methylbutyratewerethecompoundsfoundinthevolatileprofileofstudiedappleswiththelargestGCarea,representing,onaverage,24.71,14.06,and10.80%ofthetotalvolatilefractionfromPP,PS,andSSapples.InPPentireapple,themostabundantcompoundsidentified were a-farnesene (30.49%), the unknown compound m/z (69, 101, 157) (21.82%) andhexylacetate(6.57%).RegardingPSentireapplethemajorcompoundswere a-farnesene(16.87%),estragole(15.43%),hexan-1-ol(10.94),andE-2-hexenal(10.67).a-Farnesene(30.3%),hexan-1-ol(18.90%),2-methylbutanoicacid(4.7%),andpentan-1-ol(4.6%) werealsofoundasSSentireapplevolatilespresentinahigherrelativecontent.Principal component analysis (PCA) of the results clustered the apples into three groups according to geographic origin. Linear discriminant analysis (LDA) was performed in order to detect the volatile compounds able to differentiate the three kinds of apples investigated. The most important contributions to the differentiation of the PP, PS, and SS apples were ethyl hexanoate, hexyl 2-methylbutyrate, E,E-2,4-heptadienal, pethylstyrene,andE-2-hexenal.
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Allergic asthma represents an important public health issue, most common in the paediatric population, characterized by airway inflammation that may lead to changes in volatiles secreted via the lungs. Thus, exhaled breath has potential to be a matrix with relevant metabolomic information to characterize this disease. Progress in biochemistry, health sciences and related areas depends on instrumental advances, and a high throughput and sensitive equipment such as comprehensive two-dimensional gas chromatography–time of flight mass spectrometry (GC × GC–ToFMS) was considered. GC × GC–ToFMS application in the analysis of the exhaled breath of 32 children with allergic asthma, from which 10 had also allergic rhinitis, and 27 control children allowed the identification of several hundreds of compounds belonging to different chemical families. Multivariate analysis, using Partial Least Squares-Discriminant Analysis in tandem with Monte Carlo Cross Validation was performed to assess the predictive power and to help the interpretation of recovered compounds possibly linked to oxidative stress, inflammation processes or other cellular processes that may characterize asthma. The results suggest that the model is robust, considering the high classification rate, sensitivity, and specificity. A pattern of six compounds belonging to the alkanes characterized the asthmatic population: nonane, 2,2,4,6,6-pentamethylheptane, decane, 3,6-dimethyldecane, dodecane, and tetradecane. To explore future clinical applications, and considering the future role of molecular-based methodologies, a compound set was established to rapid access of information from exhaled breath, reducing the time of data processing, and thus, becoming more expedite method for the clinical purposes.
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This study examines the complex hotel buyer decision process in front of the tourism distribution channels. Its objective is to describe the influence level of the tourism marketing intermediaries, mainly the travel agents and tour operators, over the hotel decision process by the buyer-tourist. The data collection process was done trough a survey with three hundred brazilian tourists hosted in nineteen hotels of Natal, capital of Rio Grande do Norte, Brazil. The data analysis was done using some multivariate statistic techniques as correlation analysis, multiple regression analysis, factor analysis and multiple discriminant analysis. The research characterizes the hotel services consumers profile and his trip, and identifying the distribution channels used by them. Furthermore, the research verifies the intermediaries influence exercised over hotel buyer decision process, looking for identify causality relations between the influence level and the buyer profile. Verifies that information about hotels available on internet reduces the probability that this influence can be practiced; however it was possible identifying those consumers considers this information complementary and non-substitutes than the information from intermediaries. The characteristics of the data do not allow indentifying the factors that constraint the intermediaries influence neither identifying discriminant functions of the specific distribution channel choice by consumers. The study concludes that consumers don t agree in have been influenced by intermediaries or don t know if they have, still considering important to consult them and internet doesn t substitute their function as information source
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The principal purpose of this research was to investigate discriminant factors of survival and failure of micro and small businesses, and the impacts of these factors in the public politics for entrepreneurship in the State of Rio Grande do Norte. The data were ceded by SEBRAE/RN and the Commercial Committee of the Rio Grande do Norte State and it included the businesses that were registered in 2000, 2001 and 2002. According to the theoretical framework 3 groups of factors were defined Business Financial Structure, Entrepreneurial Preparation and Entrepreneurial Behavior , and the factors were studied in order to determine whether they are discriminant or not of the survival and business failure. A quantitative research was applied and advanced statistical techniques were used multivariate data analysis , beginning with the factorial analysis and after using the discriminant analysis. As a result, canonical discriminant functions were found and they partially explained the survival and business failure in terms of the factors and groups of factors. The analysis also permitted the evaluation of the public politics for entrepreneurship and it was verified, according to the view of the entrepreneurs, that these politics were weakly effective to avoid business failure. Some changes in the referred politics were suggested based on the most significant factors found.
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The Behavioral Finance develop as it is perceived anomalies in these markets efficient. This fields of study can be grouped into three major groups: heuristic bias, tying the shape and inefficient markets. The present study focuses on issues concerning the heuristics of representativeness and anchoring. This study aimed to identify the then under-reaction and over-reaction, as well as the existence of symmetry in the active first and second line of the Brazilian stock market. For this, it will be use the Fuzzy Logic and the indicators that classify groups studied from the Discriminant Analysis. The highest present, indicator in the period studied, was the Liabilities / Equity, demonstrating the importance of the moment to discriminate the assets to be considered "winners" and "losers." Note that in the MLCX biases over-reaction is concentrated in the period of financial crisis, and in the remaining periods of statistically significant biases, are obtained by sub-reactions. The latter would be in times of moderate levels of uncertainty. In the Small Caps the behavioral responses in 2005 and 2007 occur in reverse to those observed in the Mid-Large Cap. Now in times of crisis would have a marked conservatism while near the end of trading on the Bovespa speaker, accompanied by an increase of negotiations, there is an overreaction by investors. The other heuristics in SMLL occurred at the end of the period studied, this being a under-reaction and the other a over-reaction and the second occurring in a period of financial-economic more positive than the first. As regards the under / over-reactivity in both types, there is detected a predominance of either, which probably be different in the context in MLCX without crisis. For the period in which such phenomena occur in a statistically significant to note that, in most cases, such phenomena occur during the periods for MLCX while in SMLL not only biases are less present as there is no concentration of these at any time . Given the above, it is believed that while detecting the presence of bias behavior at certain times, these do not tend to appear to a specific type or heuristics and while there were some indications of a seasonal pattern in Mid- Large Caps, the same behavior does not seem to be repeated in Small Caps. The tests would then suggest that momentary failures in the Efficient Market Hypothesis when tested in semistrong form as stated by Behavioral Finance. This result confirms the theory by stating that not only rationality, but also human irrationality, is limited because it would act rationally in many circumstances
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Ecomorphology is a science based on the idea that morphological differences among species could be associated with distinct biological and environmental pressures suffered by them. These differences can be studied employing morphological and biometric indexes denominated Ecomorphological attributes , representing standards that express characteristics of the individual in relation to its environment, and can be interpreted as indicators of life habits or adaptations suffered due its occupation of different habitats. This work aims to contribute for the knowledge of the ecomorphology of the Brazilian marine ichthyofauna, specifically from Galinhos, located at Rio Grande do Norte state. 10 different species of fish were studied, belonging the families Gerreidae (Eucinostomus argenteus), Haemulidae (Orthopristis ruber,Pomadasyscorvinaeformis,Haemulonaurolineatum,Haemulonplumieri,Haemulonsteindachneri), Lutjanidae (Lutjanus synagris), Paralichthyidae (Syaciummicrurum), Bothidae (Bothus ocellatus) and Tetraodontidae (Sphoeroidestestudineus), which were obtained during five collections, in the period time of September/2004 to April/2005, utilizing three special nets. The ecomorphological study was performed at the laboratory. Eight to ten samples of each fish specie were measured. Fifteen morphological aspects were considered to calculate twelve ecomorphological attributes. Multivariate statistical analysis methods such as Principal Component Analysis (PCA) and Cluster Analysis were done to identify ecmorphological patterns to describe the data set obtained. As results, H.aurolineatumwas the most abundant specie found (23,03%) and S.testudineusthe less one with 0,23%. The 1st Principal component showed variation of 60,03% with influence of the ecomorphological attribute related to body morphology, while the 2nd PC with 23,25% variation had influence of the ecomorphological attribute related to oral morphology. The Cluster Analiysis promoted the identification of three distinct groups Perciformes, Pleuronectiformes and Tetraodontiformes. Based on the obtained data, considering morphological characters differences among the species studied, we suggest that all of them live at the medium (E.argenteus,O.rubber, P.corvinaeformis,H.aurolineatum,H.plumieri,H.steindachneri,L.synagris) and bottom (S.micrurum,B.ocellatus,S.testudineus) region of column water.
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Waste generated during the exploration and production of oil, water stands out due to various factors including the volume generated, the salt content, the presence of oil and chemicals and the water associated with oil is called produced water. The chemical composition of water is complex and depends strongly on the field generator, because it was in contact with the geological formation for thousands of years. This work aims to characterize the hydrochemical water produced in different areas of a field located in the Potiguar Basin. We collected 27 samples from 06 zones (400, 600, 400/600, 400/450/500, 350/400, A) the producing field called S and measured 50 required parameter divided between physical and chemical parameters, cations and anions. In hydrochemical characterization was used as tools of reasons ionic calculations, diagrams and they hydrochemical classification diagram Piper and Stiff diagram and also the statistic that helped in the identification of signature patterns for each production area including the area that supplies water injected this field for secondary oil recovery. The ionic balance error was calculated to assess the quality of the results of the analysis that was considered good, because 89% of the samples were below 5% error. Hydrochemical diagrams classified the waters as sodium chloride, with the exception of samples from Area A, from the injection well, which were classified as sodium bicarbonate. Through descriptive analysis and discriminant analysis was possible to obtain a function that differs chemically production areas, this function had a good hit rate of classification was 85%
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Produced water is characterized as one of the most common wastes generated during exploration and production of oil. This work aims to develop methodologies based on comparative statistical processes of hydrogeochemical analysis of production zones in order to minimize types of high-cost interventions to perform identification test fluids - TIF. For the study, 27 samples were collected from five different production zones were measured a total of 50 chemical species. After the chemical analysis was applied the statistical data, using the R Statistical Software, version 2.11.1. Statistical analysis was performed in three steps. In the first stage, the objective was to investigate the behavior of chemical species under study in each area of production through the descriptive graphical analysis. The second step was to identify a function that classify production zones from each sample, using discriminant analysis. In the training stage, the rate of correct classification function of discriminant analysis was 85.19%. The next stage of processing of the data used for Principal Component Analysis, by reducing the number of variables obtained from the linear combination of chemical species, try to improve the discriminant function obtained in the second stage and increase the discrimination power of the data, but the result was not satisfactory. In Profile Analysis curves were obtained for each production area, based on the characteristics of the chemical species present in each zone. With this study it was possible to develop a method using hydrochemistry and statistical analysis that can be used to distinguish the water produced in mature fields of oil, so that it is possible to identify the zone of production that is contributing to the excessive elevation of the water volume.
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The increase in ultraviolet radiation (UV) at surface, the high incidence of non-melanoma skin cancer (NMSC) in coast of Northeast of Brazil (NEB) and reduction of total ozone were the motivation for the present study. The overall objective was to identify and understand the variability of UV or Index Ultraviolet Radiation (UV Index) in the capitals of the east coast of the NEB and adjust stochastic models to time series of UV index aiming make predictions (interpolations) and forecasts / projections (extrapolations) followed by trend analysis. The methodology consisted of applying multivariate analysis (principal component analysis and cluster analysis), Predictive Mean Matching method for filling gaps in the data, autoregressive distributed lag (ADL) and Mann-Kendal. The modeling via the ADL consisted of parameter estimation, diagnostics, residuals analysis and evaluation of the quality of the predictions and forecasts via mean squared error and Pearson correlation coefficient. The research results indicated that the annual variability of UV in the capital of Rio Grande do Norte (Natal) has a feature in the months of September and October that consisting of a stabilization / reduction of UV index because of the greater annual concentration total ozone. The increased amount of aerosol during this period contributes in lesser intensity for this event. The increased amount of aerosol during this period contributes in lesser intensity for this event. The application of cluster analysis on the east coast of the NEB showed that this event also occurs in the capitals of Paraiba (João Pessoa) and Pernambuco (Recife). Extreme events of UV in NEB were analyzed from the city of Natal and were associated with absence of cloud cover and levels below the annual average of total ozone and did not occurring in the entire region because of the uneven spatial distribution of these variables. The ADL (4, 1) model, adjusted with data of the UV index and total ozone to period 2001-2012 made a the projection / extrapolation for the next 30 years (2013-2043) indicating in end of that period an increase to the UV index of one unit (approximately), case total ozone maintain the downward trend observed in study period
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Objetivou-se, com este trabalho, avaliar a influência de alguns genótipos de couve (Brassica oleracea L. var. acephala DC.) no desenvolvimento de Plutella xylostella (L., 1758) (Lepidoptera: Plutellidae). Os genótipos avaliados foram: Manteiga de Ribeirão Pires I-2620, Roxa I-919, Manteiga de São José, Manteiga de Monte Alegre, Pires 2 de Campinas, Couve Comum, Couve de Arthur Nogueira 2, Couve de Arthur Nogueira 1. Lagartas recém-eclodidas foram mantida em discos foliares de 8 cm de diâmetro para cada genótipo. Foram analisados os seguintes parâmetros: duração e viabilidade das fases larval e pupal, longevidade e fecundidade de adultos, utilizando análises paramétricas e de agrupamentos para interpretação dos dados. Observou-se um prolongamento em dias no ciclo de P. xylostella, aumento no peso de pupa e maiores valores de viabilidade e fecundidade, durante a segunda geração. O genótipo Couve de Arthur Nogueira 2 foi menos favorável ao desenvolvimento de P. xylostella nas duas gerações, e Couve Comum demonstrou maior influência negativa ao inseto na segunda geração. Manteiga de Ribeirão Pires I-2620 foi o mais suscetível nas duas gerações, agrupando com este na segunda geração Pires 2 de Campinas e Manteiga de São José.
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The methods of analysis of the selection system sports talent sometimes do not consider the biological age of the athletes, since that the assessment of maturational moment have several limitations The aim of this work is to develop a predictive equation of pubertal assessment in male subjects, based on anthropometric measurements. We evaluated 206 young boys, aged between eight and 18 years, and studing in public and private schools in Natal, Brazil. The sample selection was done randomly, being used the anthropometric measurements and pubertal maturation evaluation according to the Tanner stages. Statistical analysis followed the presentation of central tendency measures and their derivatives. The inferential analysis was performed according to the ANOVA test, multivariate discriminant analysis and weighted Kappa. The advancement of pubertal stages was accompanied by significant changes in anthropometric variables, demonstrating the relationship presented in both. For this purpose, discriminant analysis selected eight variables with the highest prediction of pubertal maturation, and created an equation with a significance level of 75%. and concordance level of 0.840, considered as excellent. This shows that the prediction of pubertal maturation from anthropometric variables presented as a valid method, being used as a practical tool in sports talents selection
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O presente trabalho objetivou verificar a possibilidade da utilização de métodos estatísticos multivariados na caracterização das fases do desenvolvimento do mosaico sucessional de um trecho de floresta estacional semidecidual, através de variáveis estruturais. Foram alocadas parcelas de 10 m x 10 m, em que se procedeu à análise estrutural, ou seja, levantamento fitossociológico acrescido das variáveis Porcentagem de Cobertura (PC), Altura do Dossel (AD) e Cobertura por Lianas (CL). Os métodos estatísticos empregados foram Análise de Componentes Principais e Análise de Agrupamento, mais especificamente Classificação Hierárquica Ascendente. O primeiro componente principal explicou 43,96% da variância total, enquanto o segundo, 25,66%. As variáveis Área Basal (AB), Diâmetro Médio (DM) e Dominância Média (DOM) apresentaram correlações positivas entre si superiores a 0,75, podendo ser DM e DOM consideradas como um grupo de variáveis. As variáveis Número de Indivíduos (NI) e Número de Espécies (NE) apresentaram correlação 0,60, enquanto AD, CL e PC baixas correlações com as demais, indicando a importância da inclusão destas na análise. A classificação hierárquica e a partição dos grupos em quatro foram feitas considerando os dois primeiros eixos fatoriais. Os resultados indicaram dois comportamentos diferenciados: 1) valores baixos para AD e AB: Grupo 1, com valores baixos também para NI, NE e PC (fase de clareira); e Grupo 2, com valores elevados para NI e CL e baixos para DOM e DM (fase de construção); e 2) valores altos para AD e AB: Grupo 3, com valores altos também para NI, NE e PC e valor baixo para CL (fase madura); e Grupo 4, com valores elevados para DOM e DM e mais baixos para CL (fase de degradação). Os métodos estatísticos multivariados permitiram caracterizar as fases do desenvolvimento do mosaico sucessional, através das variáveis estruturais. A forma como foram estimadas as variáveis AD, CL e PC, porém, deve ser aprimorada, assim como é preciso incluir variáveis que discriminem melhor cada fase.