904 resultados para linear stability 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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The present report is the result of an applied research in the educational entities of the third sector, aiming to demonstrate whether the financial influences the perception of users on the image of those entities. For both used the prospect of integrative marketing relationship adapting to and developing a set of indicators which bore the measurement of images from the model of Machado et al (2005) and Kotler and Fox (1994). The sample included a total of 187 parents and financial responsibility in 03 (three) institutions of education in Natal / RN. These data were processed by multivariate statistical analysis, factor analysis, linear regression, analysis of cluster and discriminant analysis. The factor analysis also identified 6 images perceived by users of services. Next were the relationships of cause and effect between the financial and images formed. In discriminant analysis, was identified two distinct groups of parents and guardians with financial perceptions similar and well defined. The result of the work shows that the differential level of financial participation of parents and guardians not influence the formation of the images formed from educational institutions of the third sector
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This research aims to understand the factors that influence intention to online purchase of consumers, and to identify between these factors those that influence the users and the nonusers of electronic commerce. Thus, it is an applied, exploratory and descriptive research, developed in a quantitative model. Data collection was done through a questionnaire administered to a sample of 194 graduate students from the Centre for Applied Social Sciences of UFRN and data analysis was performed using descriptive statistics, confirmatory factorial analysis and simple and multiple linear regression analysis. The results of descriptive statistics revealed that respondents in general and users of electronic commerce have positive perceptions of ease of use, usefulness and social influence about buying online, and intend to make purchases on Internet over the next six months. As for the non-users of electronic commerce, they do not trust the Internet to transact business, have negative perceptions of risk and social influence over purchasing online, and does not intend to make purchases on Internet over the next six months. Through confirmatory factorial analysis six factors were set up: behavioral intention, perceived ease of use, perceived usefulness, perceived risk, trust and social influence. Through multiple regression analysis, was observed that all these factors influence online purchase intentions of respondents in general, that only the social influence does not influence the intention to continue buying on the Internet from users of electronic commerce, and that only trust and social influence affect the intention to purchase online from non-users of electronic commerce. Through simple regression analysis, was found that trust influences perceptions of ease of use, usefulness and risk of respondents in general and users of electronic commerce, and that trust does not influence the perceptions of risk of non-users of electronic commerce. Finally, it was also found that the perceived ease of use influences perceived usefulness of the three groups. Given this scenario, it was concluded that it is extremely important that organizations that work with online sales know the factors that influence consumers purchasing intentions in order to gain space in their market
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A área foliar é uma das principais características usadas para avaliar o crescimento vegetal. O objetivo desta pesquisa foi determinar uma equação matemática para estimar a área foliar de Synedrellopsis grisebachii - uma importante planta daninha no Brasil - a partir de dimensões lineares dos limbos foliares. Duzentas folhas foram medidas em comprimento (C), largura máxima (L) e área foliar real (AF). Os dados de AF e CxL foram submetidos à análise de regressão linear, determinando-se uma equação matemática para estimar a área foliar da espécie. A correlação entre os valores de área foliar real e estimada foi significativa. Portanto, a área foliar de S. grisebachii pode ser estimada satisfatoriamente pela equação: AF = 0,730829(C×L).
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The herbal medicine Sanativo® is produced by the Pernambucano Laboratory since 1888 with indications of healing and hemostasis. It is composed of a fluid extract about Piptadenia colubrina, Schinus terebinthifolius, Cereus peruvianus and Physalis angulata. Among the plants in their composition, S. terebinthifolius and P. colubrina have in common phenolic compounds which are assigned most of its pharmacological effects. The tannins, gallic acid and catechin were selected as markers for quality control. The aim of this study was the development and validation of analytical method by HPLC/UV/DAD for the separation and simultaneous quantification of gallic acid (GAC) and catechin (CTQ) in Sanativo®. The chromatographic system was to stationary phase, C-18 RP column, 4,6 x 150 mm (5 mm) under a temperature of 35 ° C, detection at 270 and 210 nm. The mobile phase consisted of 0.05% trifluoroacetic acid and methanol in the proportions 88:12 (v/v), a flow rate of 1 ml/min. The analytical method presented a retention factor of 0.30 and 1.36, tail factor of 1.8 and 1.63 for gallic acid and catechin, respectively, resolution of 18.2, and theoretical plates above 2000. The method validation parameters met the requirements of Resolution n º 899 of May 29, 2003, ANVISA. The correlation coefficient of linear regression analysis for GAC and CTQ from the standard solution was 0.9958 and 0.9973 and when performed from the Sanativo® 0.9973 and 0.9936, the matrix does not interfere in the range 70 to 110 %. The limits of detection and quantification for GAC and CQT were 3.25 and 0.863, and 9.57 and 2.55 mg/mL, respectively. The markers, GAC and CQT, showed repetibility (coefficient of variation of 0.94 % and 2.36 %) and satisfactory recovery (100.02 ± 1.11 % and 101.32 ± 1.36 %). The method has been characterized selective and robust quantification of GAC and CTQ in the Sanativo® and was considered validated
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A área foliar é uma das principais características para avaliar o crescimento vegetal. Objetivou-se neste trabalho determinar uma equação matemática para estimar a área foliar de Pistia stratiotes a partir de dimensões lineares dos limbos foliares. A pesquisa foi desenvolvida na Universidade Estadual Paulista, Jaboticabal-SP, Brasil. Cem folhas, coletadas no ambiente natural, foram eletronicamente medidas em comprimento (C), largura máxima (L) e área foliar (AF). Os dados de AF e C × L foram submetidos à análise de regressão linear, determinando-se uma equação matemática para estimar a área foliar da espécie. A análise de variância sobre a regressão linear e a análise de correlação entre os valores de área foliar e estimada foram significativas (p < 0,01). A área foliar de P. stratiotes pode ser estimada pela equação: AF = 0,79499 (CL).
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Este trabalho foi realizado com o objetivo de conhecer a influência que algumas variáveis meteorológicas exercem na razão entre sólidos solúveis totais e acidez total titulável (ratio) e no índice tecnológico dos frutos da primeira florada das laranjeiras-'Natal' e 'Valência', na região de Bebedouro-SP, mediante a utilização de métodos estatísticos de regressão. Foram utilizados dados de amostragens de rotina para o processamento industrial durante 4 anos, os quais permitiram desenvolver equações de regressão linear e quadrática, com a soma térmica (graus-dia) como variável independente, e de regressão múltipla, utilizando graus-dia e chuva como variáveis independentes. A equação de melhor ajuste para o índice tecnológico foi a quadrática, enquanto para o ratio a equação linear apresentou o melhor ajuste. A temperatura do ar, representada por graus-dia, foi a variável que exerceu maior influência nos indicadores de qualidade dos frutos.
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We investigated the population dynamics of Triozoida limbata (Hemiptera: Triozidae) and Costalimaita ferruginea (Coleoptera: Chrysomelidae) and its correlation with the population of natural enemies in organic and conventional orchard of guava. The experiments were performed in two distinct orchards of guava in the 2010/2011 harvest. For monitoring pests and natural enemies, we installed five yellow sticky traps in each orchard. To obtain the correlation between population densities of pests with natural enemies, we used Pearson linear correlation analysis (SAS). The population density of T. limbata remained low, and reaches the top in October in organic orchard of guava. The main pest in conventional orchard of guava was T. limbata and population reaches the top several times. The damage caused by T. limbata in new leaves of guava was more pronounced in conventional orchard. There was a low population density of C. ferruginea in both orchards; however we observed that the population reaches the top in November in organic orchard. The species C. ferruginea caused higher damage in young leaves of guava tree in organic orchard. The highest population density of natural enemies was observed in organic orchard, which presented positive correlation between T. limbata and the coccinellid predator Scymnus spp.
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This study intended to evaluate the maze test accuracy in cognitive deficit screening in elderly with or without neuropsychological pathology. The sample included 40 healthy young (18-25 years old; mean- 21 ± 1.6), 40 healthy old (60-77 years old; mean- 67 ± 5.1) and 18 patients with probable diagnosis of Alzheimer s disease initial stage (52-90 years old; mean- 78 ± 9.2). Data analysis was made using Anova with Tukey s post hoc, multiple linear regression analysis and ROC curve analysis. According to Tukey s test Alzheimer patients spent more time (46843 ± 37926 ms) to execute the test than healthy young (5482 ± 2873 ms; p= 0.0001) and elderly (17978 ± 13700; p= 0.0001); healthy young executed test n lower time (p= 0.035). According to the regression analysis of age, education level and cognitive performance of the three groups, the cognitive performance was the predictor of the execution time. When analyzing young and elderly only age was the predictor and the cognitive performance was the only factor to influence the test of old aged healthy and patients. The ROC curve analysis indicated 72% accuracy for young and elderly and 36% for healthy and elderly patients. The maze execution time represented a better balance between sensibility (75%) and the specificity (61%) was near 13575 ms, indicating that those subjects that execute the maze in a time higher to this value may show cognitive deficit related to the executive function. According to the results it is suggested that the maze test used in this study shows a good accuracy in the cognitive deficit tracking and may discriminate age changes
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The spread of the Web boosted the dissemination of Information Systems (IS) based on the Web. In order to support the implementation of these systems, several technologies came up or evolved with this purpose, namely the programming languages. The Technology Acceptance Model TAM (Davis, 1986) was conceived aiming to evaluate the acceptance/use of information technologies by their users. A lot of studies and many applications have used the TAM, however, in the literature it was not found a mention of the use of such model related to the use of programming languages. This study aims to investigate which factors influence the use of programming languages on the development of Web systems by their developers, applying an extension of the TAM, proposed in this work. To do so, a research was done with Web developers in two Yahoo groups: java-br and python-brasil, where 26 Java questionnaires and 39 Python questionnaires were fully answered. The questionnaire had general questions and questions which measured intrinsic and extrinsic factors of the programming languages, the perceived usefulness, the perceived ease of use, the attitude toward the using and the programming language use. Most of the respondents were men, graduate, between 20 and 30 years old, working in the southeast and south regions. The research was descriptive in the sense of its objectives. Statistical tools, descriptive statistics, main components and linear regression analysis were used for the data analysis. The foremost research results were: Java and Python have machine independence, extensibility, generality and reliability; Java and Python are more used by corporations and international organizations than supported by the government or educational institutions; there are more Java programmers than Python programmers; the perceived usefulness is influenced by the perceived ease of use; the generality and the extensibility are intrinsic factors of programming languages which influence the perceived ease of use; the perceived ease of use influences the attitude toward the using of the programming language
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This study presents an investigation of the influence of Corporate Social Responsibility (CSR) in customer s satisfaction and loyalty through a study with car s buyers, besides that, it aims to contribute to conceptual models of satisfaction and loyalty analysis by applying the model of Johnson et al. (2001), adapted for the introduction of variables of CSR and conscious consumption, in a car dealership in Natal / RN. The methodology has a descriptive quantitative approach and for the analysis results were applied statistical methods of simple and multiple linear regression analysis, descriptive analysis and exploratory analysis. The field research provided 90 valid forms. The results show that CSR affects the image of the company studied and is also one of the elements of the compound of satisfaction and loyalty. This study concludes that CSR should be considered in the strategic and marketing actions of firms
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This work develops a robustness analysis with respect to the modeling errors, being applied to the strategies of indirect control using Artificial Neural Networks - ANN s, belong to the multilayer feedforward perceptron class with on-line training based on gradient method (backpropagation). The presented schemes are called Indirect Hybrid Control and Indirect Neural Control. They are presented two Robustness Theorems, being one for each proposed indirect control scheme, which allow the computation of the maximum steady-state control error that will occur due to the modeling error what is caused by the neural identifier, either for the closed loop configuration having a conventional controller - Indirect Hybrid Control, or for the closed loop configuration having a neural controller - Indirect Neural Control. Considering that the robustness analysis is restrict only to the steady-state plant behavior, this work also includes a stability analysis transcription that is suitable for multilayer perceptron class of ANN s trained with backpropagation algorithm, to assure the convergence and stability of the used neural systems. By other side, the boundness of the initial transient behavior is assured by the assumption that the plant is BIBO (Bounded Input, Bounded Output) stable. The Robustness Theorems were tested on the proposed indirect control strategies, while applied to regulation control of simulated examples using nonlinear plants, and its results are presented
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)