102 resultados para Univariate Analysis box-jenkins methodology
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Objective To assess the effectiveness of Problem-Solving Therapy (PST) on family caregivers through the use of scales to measure anxiety, depression and emotional distress; and to explore facilitating factors and obstacles for its use based on the narrative of nurses. Method A clinical trial and an exploratory focus group with the use of mixed analysis methodology. The study was conducted in a primary health care center in Tarragona, Spain, and the sample consisted of 122 family caregivers who were included in the home care service, and 10 nurses who participated in the intervention group. Family caregivers with evident symptoms of anxiety, depression and emotional distress received PST in the intervention group. The intervention group also consisted of a discussion with eight nurses, which was transcribed and submitted to content analysis. Conclusion Problem-Solving Therapy proved to be effective in reducing perceived anxiety, depression and emotional distress. We identified its strong points and obstacles as described by nurses.
Principal components analysis for quality evaluation of cooled banana 'Nanicão' in different packing
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This work aims determinate the evaluation of the quality of 'Nanicão' banana, submitted to two conditions of storage temperature and three different kinds of package, using the technique of the Analysis of Principal Components (ACP), as a basis for an Analysis of Variance. The fruits used were 'Nanicão' bananas, at ripening degree 3, that is, more green than yellow. The packages tested were: "Torito" wood boxes, load capacity: 18 kg; "½ box" wood boxes, load capacity: 13 kg; and cardboard boxes, load capacity: 18 kg. The temperatures assessed were: room temperature (control); and (13±1ºC), with humidity controlled to 90±2,5%. Fruits were discarded when a sensory analysis determined they had become unfit for consumption. Peel coloration, percentages of imperfection, fresh mass, total acidity, pH, total soluble solids and percentages of sucrose were assessed. A completely randomized design with a 2-factorial treatment structure (packing X temperature) was used. The obtained data were analyzed through a multivariate analysis known as Principal Components Analysis, using S-plus 4.2. The conclusion was that the best packages to preserve the fruit were the ½ box ones, which proves that it is necessary to reduce the number of fruits per package to allow better ventilation and decreases mechanical injuries and ensure quality for more time.
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This work proposes a sequential injection analysis (SIA) system for the spectrophotometric determination of norfloxacin (NOR) and ciprofloxacin (CIP) in pharmaceutical formulations. The methodology was based on the reaction of these drugs with p-(dimethylamino)cinnamaldehyde in micellar medium, producing orange colored products (λmax = 495 nm). Beer´s law was obeyed in the concentration range from 2.75x10-5 to 3.44x10-4 mol L-1 and 3.26x10-5 to 3.54x10-4 mol L-1 for NOR and CIP, respectively and sampling rate was 25 h-1. Commercial samples were analyzed and results obtained through the proposed method were in good agreement with those obtained using the reference procedure for a 95% confidence level.
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Methane combustion was studied by the Westbrook and Dryer model. This well-established simplified mechanism is very useful in combustion science, for computational effort can be notably reduced. In the inversion procedure to be studied, rate constants are obtained from [CO] concentration data. However, when inherent experimental errors in chemical concentrations are considered, an ill-conditioned inverse problem must be solved for which appropriate mathematical algorithms are needed. A recurrent neural network was chosen due to its numerical stability and robustness. The proposed methodology was compared against Simplex and Levenberg-Marquardt, the most used methods for optimization problems.
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An experiment was proposed applying the Chemometric approach of Multivariate Analysis for inclusion in undergraduate Chemistry courses to promote and expand the use of this analytical-statistical tool. The experiment entails the determination of the acid dissociation constant of dyes via UV-Vis electronic spectrophotometry. The dyes used show from simple equilibrium to very complex systems involving up to four protolytic species with high spectral overlap. The Chemometric methodology was more efficient than univariate methods. For use in classes, it is up to the teacher to decide which systems should be utilized given the time constraints and laboratory conditions.
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In general, laboratory activities are costly in terms of time, space, and money. As such, the ability to provide realistically simulated laboratory data that enables students to practice data analysis techniques as a complementary activity would be expected to reduce these costs while opening up very interesting possibilities. In the present work, a novel methodology is presented for design of analytical chemistry instrumental analysis exercises that can be automatically personalized for each student and the results evaluated immediately. The proposed system provides each student with a different set of experimental data generated randomly while satisfying a set of constraints, rather than using data obtained from actual laboratory work. This allows the instructor to provide students with a set of practical problems to complement their regular laboratory work along with the corresponding feedback provided by the system's automatic evaluation process. To this end, the Goodle Grading Management System (GMS), an innovative web-based educational tool for automating the collection and assessment of practical exercises for engineering and scientific courses, was developed. The proposed methodology takes full advantage of the Goodle GMS fusion code architecture. The design of a particular exercise is provided ad hoc by the instructor and requires basic Matlab knowledge. The system has been employed with satisfactory results in several university courses. To demonstrate the automatic evaluation process, three exercises are presented in detail. The first exercise involves a linear regression analysis of data and the calculation of the quality parameters of an instrumental analysis method. The second and third exercises address two different comparison tests, a comparison test of the mean and a t-paired test.
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Flow injection (FI) methodology, using diffuse reflectance in the visible region of the spectrum, for the analysis of total sulfur in the form of sulfate, precipitated in the form of barium sulfate, is presented. The method was applied to biodiesel, to plant leaves and to natural waters analysis. The analytical signal (S) correlates linearly with sulfate concentration (C) between 20 and 120 ppm, through the equation S=-1.138+0.0934 C (r = 0.9993). The experimentally observed limit of detection is about 10 ppm. The mean R.S.D. is about 3.0 %. Real samples containing sulfate were analyzed and the results obtained by the FI and by the reference batch turbidimetric method using the statistical Student's t-test and F-test were compared.
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The application of multivariate calibration techniques to multicomponent analysis by UV-VIS molecular absorption spectrometry is a powerful tool for simultaneous determination of several chemical species. However, when this methodology is accomplished manually, it is slow and laborious, consumes high amounts of reagents and samples, is susceptible to contaminations and presents a high operational cost. To overcome these drawbacks, a flow-batch analyser is proposed in this work. This analyser was developed for automatic preparation of standard calibration and test (or validation) mixtures. It was applied to the simultaneous determination of Cu2+, Mn2+ and Zn2+ in polyvitaminic and polymineral pharmaceutical formulations, using 4-(2-piridilazo) resorcinol as reagent and a UV-VIS spectrophotometer with a photodiode array detector. The results obtained with the proposed system are in good agreement with those obtained by flame atomic absorption spectrometry, which was employed as reference method. With the proposed analyser, the preparation of calibration and test mixtures can be accomplished about four hours, while the manual procedure requires at least two days. Moreover, it consumes smaller amounts of reagents and samples than the manual procedure. After the preparation of calibration and test mixtures, 60 samples h-1 can be carried out with the proposed flow-batch analyser.
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The culture and commercialization of ornamental plants have considerably increased in the last years. To supply the commercial demand, several Hemerocallis and Impatiens varieties have been bred for appreciated qualities such as flowers with a diversity of shapes and colors. With the aim of characterizing the tobamovirus isolated from Hemerocallis sp. (tobamo-H) and Impatiens hawkeri (tobamo-I) from the USA and São Paulo, respectively, as well as to establish phylogenetic relationships between them and other Tobamovirus species, the viruses were submitted to RNA extraction, RT-PCR amplification, coat-protein gene sequencing and phylogenetic analyses. Comparison of tobamovirus homologous sequences yielded values superior to 98.5% of identity with Tomato mosaic virus (ToMV) isolates at the nucleotide level. In relation to tobamo-H, 100% of identity with ToMV from tomatoes from Australia and Peru was found. Based on maximum likelihood (ML) analysis it was suggested that tobamo-H and tobamo-I share a common ancestor with ToMV, Tobacco mosaic virus, Odontoglossum ringspot virus and Pepper mild mottle virus. The tree topology reconstructed under ML methodology shows a monophyletic group, supported by 100% of bootstrap, consisting of various ToMV isolates from different hosts, including some ornamentals, from different geographical locations. The results indicate that Hemerocallis sp. and I. hawkeri are infected by ToMV. This is the first report of the occurrence of this virus in ornamental species in Brazil.
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ABSTRACT Permanent Preservation Areas (PPAs) along watercourses have been the focus of numerous studies, not only because of the fragility and ecological relevance of riverine vegetation, but also because of the inefficiency demonstrated in conforming to the legislation protecting it. One of the major difficulties encountered in terms of guaranteeing the effective conservation of these riverside areas is the absence of methodologies that can be used to define them rapidly and accurately without manually determining the widths of the rivers or assigning only uniform linear values for the entire watercourse. The present work sought to develop a spatial analysis methodology capable of automatically defining permanent preservation areas along watercourses using geographic information system (GIS) software. The present study was undertaken in the Sergipe River basin, "considering the river itself and its principal affluents. We used the database of the Digital Atlas of Hydrological Resources (SEMARH/SE), and the delimitations of the PPAs were performed using ArcGIS 10.1 and the XToolPro 9.0 extension. A total of 5,003.82 hectares of Permanent Preservation Areas were delimited along the margins of the rivers analyzed, with a margin of error of <1% in delimiting the widths of the rivers within the entire area considered. The methodology described here can be used to define PPAs efficiently, relatively rapidly, and with very small margins of error, thus representing a technological advance in terms of using GIS for land management.
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The research proposes a methodology for assessing broiler breeder response to changes in rearing thermal environment. The continuous video recording of a flock analyzed may offer compelling evidences of thermal comfort, as well as other indications of welfare. An algorithm for classifying specific broiler breeder behavior was developed. Videos were recorded over three boxes where 30 breeders were reared. The boxes were mounted inside an environmental chamber were ambient temperature varied from cold to hot. Digital images were processed based on the number of pixels, according to their light intensity variation and binary contrast allowing a sequence of behaviors related to welfare. The system used the default of x, y coordinates, where x represents the horizontal distance from the top left of the work area to the point P, and y is the vertical distance. The video images were observed, and a grid was developed for identifying the area the birds stayed and the time they spent at that place. The sequence was analyzed frame by frame confronting the data with specific adopted thermal neutral rearing standards. The grid mask overlapped the real bird image. The resulting image allows the visualization of clusters, as birds in flock behave in certain patterns. An algorithm indicating the breeder response to thermal environment was developed.
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ABSTRACT This study aimed to develop a methodology based on multivariate statistical analysis of principal components and cluster analysis, in order to identify the most representative variables in studies of minimum streamflow regionalization, and to optimize the identification of the hydrologically homogeneous regions for the Doce river basin. Ten variables were used, referring to the river basin climatic and morphometric characteristics. These variables were individualized for each of the 61 gauging stations. Three dependent variables that are indicative of minimum streamflow (Q7,10, Q90 and Q95). And seven independent variables that concern to climatic and morphometric characteristics of the basin (total annual rainfall – Pa; total semiannual rainfall of the dry and of the rainy season – Pss and Psc; watershed drainage area – Ad; length of the main river – Lp; total length of the rivers – Lt; and average watershed slope – SL). The results of the principal component analysis pointed out that the variable SL was the least representative for the study, and so it was discarded. The most representative independent variables were Ad and Psc. The best divisions of hydrologically homogeneous regions for the three studied flow characteristics were obtained using the Mahalanobis similarity matrix and the complete linkage clustering method. The cluster analysis enabled the identification of four hydrologically homogeneous regions in the Doce river basin.
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This paper investigates defect detection methodologies for rolling element bearings through vibration analysis. Specifically, the utility of a new signal processing scheme combining the High Frequency Resonance Technique (HFRT) and Adaptive Line Enhancer (ALE) is investigated. The accelerometer is used to acquire data for this analysis, and experimental results have been obtained for outer race defects. Results show the potential effectiveness of the signal processing technique to determine both the severity and location of a defect. The HFRT utilizes the fact that much of the energy resulting from a defect impact manifests itself in the higher resonant frequencies of a system. Demodulation of these frequency bands through use of the envelope technique is then employed to gain further insight into the nature of the defect while further increasing the signal to noise ratio. If periodic, the defect frequency is then present in the spectra of the enveloped signal. The ALE is used to enhance the envelope spectrum by reducing the broadband noise. It provides an enhanced envelope spectrum with clear peaks at the harmonics of a characteristic defect frequency. It is implemented by using a delayed version of the signal and the signal itself to decorrelate the wideband noise. This noise is then rejected by the adaptive filter that is based upon the periodic information in the signal. Results have been obtained for outer race defects. They show the effectiveness of the methodology to determine both the severity and location of a defect. In two instances, a linear relationship between signal characteristics and defect size is indicated.
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This work presents recent results concerning a design methodology used to estimate the positioning deviation for a gantry (Cartesian) manipulator, related mainly to structural elastic deformation of components during operational conditions. The case-study manipulator is classified as gantry type and its basic dimensions are 1,53m x 0,97m x 1,38m. The dimensions used for the calculation of effective workspace due to end-effector path displacement are: 1m x 0,5m x 0,5m. The manipulator is composed by four basic modules defined as module X, module Y, module Z and terminal arm, where is connected the end-effector. Each module controlled axis performs a linear-parabolic positioning movement. The planning path algorithm has the maximum velocity and the total distance as input parameters for a given task. The acceleration and deceleration times are the same. Denavit-Hartemberg parameterization method is used in the manipulator kinematics model. The gantry manipulator can be modeled as four rigid bodies with three degrees-of-freedom in translational movements, connected as an open kinematics chain. Dynamic analysis were performed considering inertial parameters specification such as component mass, inertia and center of gravity position of each module. These parameters are essential for a correct manipulator dynamic modelling, due to multiple possibilities of motion and manipulation of objects with different masses. The dynamic analysis consists of a mathematical modelling of the static and dynamic interactions among the modules. The computation of the structural deformations uses the finite element method (FEM).
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Two different pathogenetic mechanisms are proposed for colorectal cancers. One, the so-called "classic pathway", is the most common and depends on multiple additive mutational events (germline and/or somatic) in tumor suppressor genes and oncogenes, frequently involving chromosomal deletions in key genomic regions. Methodologically this pathway is recognizable by the phenomenon of loss of heterozygosity. On the other hand, the "mutator pathway" depends on early mutational loss of the mismatch repair system (germline and/or somatic) leading to accelerated accumulation of gene mutations in critical target genes and progression to malignancy. Methodologically this second pathway is recognizable by the phenomenon of microsatellite instability. The distinction between these pathways seems to be more than academic since there is evidence that the tumors emerging from the mutator pathway have a better prognosis. We report here a very simple methodology based on a set of tri-, tetra- and pentanucleotide repeat microsatellites allowing the simultaneous study of microsatellite instability and loss of heterozygosity which could allocate 70% of the colorectal tumors to the classic or the mutator pathway. The ease of execution of the methodology makes it suitable for routine clinical typing