25 resultados para Análise de seqüência com séries de oligonucleotídeos


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Peng was the first to work with the Technical DFA (Detrended Fluctuation Analysis), a tool capable of detecting auto-long-range correlation in time series with non-stationary. In this study, the technique of DFA is used to obtain the Hurst exponent (H) profile of the electric neutron porosity of the 52 oil wells in Namorado Field, located in the Campos Basin -Brazil. The purpose is to know if the Hurst exponent can be used to characterize spatial distribution of wells. Thus, we verify that the wells that have close values of H are spatially close together. In this work we used the method of hierarchical clustering and non-hierarchical clustering method (the k-mean method). Then compare the two methods to see which of the two provides the best result. From this, was the parameter � (index neighborhood) which checks whether a data set generated by the k- average method, or at random, so in fact spatial patterns. High values of � indicate that the data are aggregated, while low values of � indicate that the data are scattered (no spatial correlation). Using the Monte Carlo method showed that combined data show a random distribution of � below the empirical value. So the empirical evidence of H obtained from 52 wells are grouped geographically. By passing the data of standard curves with the results obtained by the k-mean, confirming that it is effective to correlate well in spatial distribution

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Analogous to sunspots and solar photospheric faculae, which visibility is modulated by stellar rotation, stellar active regions consist of cool spots and bright faculae caused by the magnetic field of the star. Such starspots are now well established as major tracers used to estimate the stellar rotation period, but their dynamic behavior may also be used to analyze other relevant phenomena such as the presence of magnetic activity and its cycles. To calculate the stellar rotation period, identify the presence of active regions and investigate if the star exhibits or not differential rotation, we apply two methods: a wavelet analysis and a spot model. The wavelet procedure is also applied here to study pulsation in order to identify specific signatures of this particular stellar variability for different types of pulsating variable stars. The wavelet transform has been used as a powerful tool for treating several problems in astrophysics. In this work, we show that the time-frequency analysis of stellar light curves using the wavelet transform is a practical tool for identifying rotation, magnetic activity, and pulsation signatures. We present the wavelet spectral composition and multiscale variations of the time series for four classes of stars: targets dominated by magnetic activity, stars with transiting planets, those with binary transits, and pulsating stars. We applied the Morlet wavelet (6th order), which offers high time and frequency resolution. By applying the wavelet transform to the signal, we obtain the wavelet local and global power spectra. The first is interpreted as energy distribution of the signal in time-frequency space, and the second is obtained by time integration of the local map. Since the wavelet transform is a useful mathematical tool for nonstationary signals, this technique applied to Kepler and CoRoT light curves allows us to clearly identify particular signatures for different phenomena. In particular, patterns were identified for the temporal evolution of the rotation period and other periodicity due to active regions affecting these light curves. In addition, a beat-pattern vii signature in the local wavelet map of pulsating stars over the entire time span was also detected. The second method is based on starspots detection during transits of an extrasolar planet orbiting its host star. As a planet eclipses its parent star, we can detect physical phenomena on the surface of the star. If a dark spot on the disk of the star is partially or totally eclipsed, the integrated stellar luminosity will increase slightly. By analyzing the transit light curve it is possible to infer the physical properties of starspots, such as size, intensity, position and temperature. By detecting the same spot on consecutive transits, it is possible to obtain additional information such as the stellar rotation period in the planetary transit latitude, differential rotation, and magnetic activity cycles. Transit observations of CoRoT-18 and Kepler-17 were used to implement this model.

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The objective of this research was to investigate monthly climatological, seasonal, annual and interdecadal of the reference evapotranspiration (ETo) in Acre state in order to better understand its spatial and temporal variability and identify possible trends in the region. The study was conducted with data from Rio Branco municipalities, the state capital, Tarauacá and Cruzeiro do Sul considering a 30-year period (1985-2014), from monthly data from weather stations surface of the National Institute of Meteorology. The methodology was held, first, the consistency of meteorological data. Thus, it was made the gap filling in the time series by means of multivariate techniques. Subsequently were performed statistical tests trend (Mann-Kendall) and homogeneity, by Sen's estimator of the magnitude of this trend is estimated, as well as computational algorithms containing parametric and non-parametric tests for two samples to identify from that year the trend has become significant. Finally, analysis of variance technique (ANOVA) was adopted in order to verify whether there were significant differences in average annual evapotranspiration between locations. The indirect method of Penman-Montheith parameterized by FAO was used to calculate the ETo. The results of this work through examination of the descriptive statistics showed that the ETo the annual average was 3.80, 2.92 and 2.86 mm day-1 year, to Rio Branco, Tarauacá and Cruzeiro do Sul, respectively. Featuring quite remarkable seasonal pattern with a minimum in June and a maximum in October, with Rio Branco to town one with the strongest signal (amplitudes) on the other hand, the Southern Cross presented the highest variability among the studied locations. By ANOVA it was found that the average annual statistically different for a significance level of 1% between locations, but the annual average between Cruzeiro do Sul and Tarauacá no statistically significant differences. For the three locations, the 2000s was the one with the highest ETo values associated with warmer waters of the North Atlantic basin and the 80s to lower values, associated with cooler waters of this basin. By analyzing the Mann-kendall and Sen estimator test, there was a trend of increasing the seasonal reference evapotranspiration (fall, winter and spring) on the order of 0.11 mm per decade and that from the years of 1990, 1996 and 2001 became statistically significant to the localities of Cruzeiro do Sul Tarauacá and Rio Branco, respectively. For trend analysis of meteorological parameters was observed positive trend in the 5% level of significance, for average temperature, minimum temperature and solar radiation.

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The variability / climate change has generated great concern worldwide, is one of the major issues as global warming, which can is affecting the availability of water resources in irrigated perimeters. In the semiarid region of Northeastern Brazil it is known that there is a predominance of drought, but it is not enough known about trends in climate series of joint water loss by evaporation and transpiration (evapotranspiration). Therefore, this study aimed to analyze whether there is increase and / or decrease evidence in the regime of reference evapotranspiration (ETo), for the monthly, annual and interdecadal scales in irrigated polo towns of Juazeiro, BA (9 ° 24'S, 40 ° 26'W and 375,5m) and Petrolina, PE (09 ° 09'S, 40 ° 22'W and 376m), which is the main analysis objective. The daily meteorological data were provided by EMBRAPA Semiárido for the period from 01.01.1976 to 31.12.2014, estimated the daily ETo using the standard method of Penman-Monteith (EToPM) parameterized by Smith (1991). Other methods of more simplified estimatives were calculated and compared to EToPM, as the ones following: Solar Radiation (EToRS), Linacre (EToL), Hargreaves and Samani (EToHS) and the method of Class A pan (EToTCA). The main statistical analysis were non-parametric tests of homogeneity (Run), trend (Mann-kendall), magnitude of the trend (Sen) and early trend detection (Mann-Whitney). The statistical significance adopted was 5 and / or 1%. The Analysis of Variance - ANOVA was used to detect if there is a significant difference in mean interdecadal mean. For comparison between the methods of ETo, it were used the correlation test (r), the Student t test and Tukey levels of 5% significance. Finally, statistics Willmott et al. (1985) statistics was used to evaluate the concordance index and performance of simplified methods compared to the standard method. It obtained as main results that there was a decrease in the time series of EToPM in irrigated areas of Juazeiro, BA and Petrolina, PE, significant respectively at 1 and 5%, with an annual magnitude of -14.5 mm (Juazeiro) and -7.7 mm (Petrolina) and early trend in 1996. The methods which had better for better agreement with EToPM were EToRS with very good performance, in both locations, followed by the method of EToL with good performance (Juazeiro) and median (Petrolina). EToHS had the worst performance (bad) for both locations. It is suggested that this decrease of EToPM can be associated with the increase in irrigated agricultural areas and the construction of Sobradinho lake upstream of the perimeters.

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The great amount of data generated as the result of the automation and process supervision in industry implies in two problems: a big demand of storage in discs and the difficulty in streaming this data through a telecommunications link. The lossy data compression algorithms were born in the 90’s with the goal of solving these problems and, by consequence, industries started to use those algorithms in industrial supervision systems to compress data in real time. These algorithms were projected to eliminate redundant and undesired information in a efficient and simple way. However, those algorithms parameters must be set for each process variable, becoming impracticable to configure this parameters for each variable in case of systems that monitor thousands of them. In that context, this paper propose the algorithm Adaptive Swinging Door Trending that consists in a adaptation of the Swinging Door Trending, as this main parameters are adjusted dynamically by the analysis of the signal tendencies in real time. It’s also proposed a comparative analysis of performance in lossy data compression algorithms applied on time series process variables and dynamometer cards. The algorithms used to compare were the piecewise linear and the transforms.

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The characteristics profile of individuals who develop AIDS in Brazil has changed over time. Among these modifications, a worrying finding is the increased incidence of AIDS in the elderly across the country. But, however, is not yet clear whether the increase in AIDS cases is sufficient to produce a change in the trend of measures in recent years in the Brazilian states, and this increase has an effect from the socioeconomic and demographic indicators. In this sense, the objective of this study is to analyze the AIDS incidence rates among the elderly in Brazil and its effect on socioeconomic and demographic inequalities in the period 2000 to 2012. This is an ecological time-series study to meet behavior of the time series of the incidence rates of AIDS in the elderly from 2000 to 2012. the rates were calculated using the secondary data from Diseases Information System Notification and the Brazilian Institute of Geography and Statistics. Data were analyzed statistically to know the trends in incidence rates, by polynomial regression model and joinpoint log-linear regression model, but also the simple linear regression analysis to find the relationship of trends with variables socioeconomic and demographic. SPSS 20.0® and Joinpoint 4.1.1 programs were used. All tests were carried out considering a significance of 5%. After the analysis, in Brazil were reported 62,052 new cases of AIDS in the elderly from 2000 to 2012. During this period, a significant increase was found for males, both aged 50-59 years (APPC: 3.46 %, p <0.001), such as above 59 years (AAPC: 4.38%; p <0.001). For females, the increase was significant and has the largest increments in the time series, when compared to males in both age groups (AAPC: 4.62%, p <0.001 and AAPC: 6.53%; p <0.001) respectively. The largest increases are observed in women and in the states of North and Northeast. In the Southeast Region is observed stabilization of rates throughout the series. The reason of trends between the sexes had a significant reduction, but also an approach in both age groups of the study, reaching a ratio of 1.7 males for every female in the youngest age group. The trends were related to illiteracy rates, with increasing social inequality and the lowest human development in the Brazilian states. We conclude that in Brazil the incidence of AIDS in the elderly follows an increasing trend in individuals over 50 years. Noteworthy are the highest rates of study in women and in the states of North and Northeast. In this sense, the country needs to enhance policies towards older people with STD / AIDS, training health professionals and developing effective measures for the prevention and early diagnosis of infected people, especially in places with limited resources and high social inequality. In the long term, it is developing new studies to understand whether the measures taken were effective in reducing the trends identified in this study.

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The present paper has the purpose of investigate the dynamics of the volatility structure in the shrimp prices in the Brazilian fish market. Therefore, a description of the initial aspects of the shrimp price series was made. From this information, statistics tests were made and selected univariate models to be price predictors. Then, it was verified the existence of relationship of long-term equilibrium between the Brazilian and American imported shrimp and if, confirmed the relationship, whether or not there is a causal link between these assets, considering that the two countries had presented trade relations over the years. It is presented as an exploratory research of applied nature with quantitative approach. The database was collected through direct contact with the Companhia de Entrepostos e Armazéns Gerais de São Paulo (CEAGESP) and on the official website of American import, National Marine Fisheries Service - National Oceanic and Atmospheric Administration (NMFS- NOAA). The results showed that the great variability in the active price is directly related with the gain and loss of the market agents. The price series presents a strong seasonal and biannual effect. The average structure of price of shrimp in the last 12 years was R$ 11.58 and external factors besides the production and marketing (U.S. antidumping, floods and pathologies) strongly affected the prices. Among the tested models for predicting prices of shrimp, four were selected, which through the prediction methodologies of one step forward of horizon 12, proved to be statistically more robust. It was found that there is weak evidence of long-term equilibrium between the Brazilian and American shrimp, where equivalently, was not found a causal link between them. We concluded that the dynamic pricing of commodity shrimp is strongly influenced by external productive factors and that these phenomena cause seasonal effects in the prices. There is no relationship of long-term stability between the Brazilian and American shrimp prices, but it is known that Brazil imports USA production inputs, which somehow shows some dependence productive. To the market agents, the risk of interferences of the external prices cointegrated to Brazilian is practically inexistent. Through statistical modeling is possible to minimize the risk and uncertainty embedded in the fish market, thus, the sales and marketing strategies for the Brazilian shrimp can be consolidated and widespread

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One Kunitz-type trypsin inhibitors (PmTI) was purified from Piptadenia moniliformis seeds, a tree of the sub-family Mimosoideae, by TCA precipitation, affinity chromatography on immobilized trypsin-Sepharose, DEAE cellulose (ion exchange) and Superose 12 (molecular exclusion) column FPLC/AKTA. The inhibitor has Mr of 25 kDa by SDS-PAGE and chromatography molecular exclusion. The N-terminal sequence of this inhibitor showed high homology with other family Kunitz inhibitors. This also stable variations in temperature and pH and showed a small decrease in its activity when incubated with DDT in the concentration of 100mM for 120 minutes. The inhibition of trypsin by PmTI was competitive, with Ki of 1.57 x10-11 M. The activity of trypsin was effectively inhibited by percentage of inhibition of 100%, among enzymes tested, was not detected inhibition for the bromelain, was weak inhibitor of pancreatic elastase (3.17% of inhibition) and inhibited by 76.42% elastase of neutrophils, and inhibited in a moderate, chymotrypsin and papain with percentage of inhibition of 42.96% and 23.10% respectively. In vitro assays against digestive proteinases from Lepidoptera, Diptera and Coleoptera pests were carried out. Several degrees of inhibition were found. For Anthonomus grandis and Ceratitis capitata the inhibition was 89.93% and 70.52%, respectively, and the enzymes of Zabrotes subfasciatus and Callosobruchus maculatus were inhibited by 5.96% and 9.41%, respectively, and the enzymes of Plodia. interpunctella and Castnia licus were inhibited by 59.94% and 23.67, respectively. In vivo assays, was observed reduction in the development of larvae in 4rd instar of C. capitata, when PmTI was added to the artificial diet, getting WD50 and LD50 of 0.30% and 0.33%, respectively. These results suggest that this inhibitor could be a strong candidate to plant management programs cross transgenic

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The main objective of this study is to apply recently developed methods of physical-statistic to time series analysis, particularly in electrical induction s profiles of oil wells data, to study the petrophysical similarity of those wells in a spatial distribution. For this, we used the DFA method in order to know if we can or not use this technique to characterize spatially the fields. After obtain the DFA values for all wells, we applied clustering analysis. To do these tests we used the non-hierarchical method called K-means. Usually based on the Euclidean distance, the K-means consists in dividing the elements of a data matrix N in k groups, so that the similarities among elements belonging to different groups are the smallest possible. In order to test if a dataset generated by the K-means method or randomly generated datasets form spatial patterns, we created the parameter Ω (index of neighborhood). High values of Ω reveals more aggregated data and low values of Ω show scattered data or data without spatial correlation. Thus we concluded that data from the DFA of 54 wells are grouped and can be used to characterize spatial fields. Applying contour level technique we confirm the results obtained by the K-means, confirming that DFA is effective to perform spatial analysis

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In recent years, the DFA introduced by Peng, was established as an important tool capable of detecting long-range autocorrelation in time series with non-stationary. This technique has been successfully applied to various areas such as: Econophysics, Biophysics, Medicine, Physics and Climatology. In this study, we used the DFA technique to obtain the Hurst exponent (H) of the profile of electric density profile (RHOB) of 53 wells resulting from the Field School of Namorados. In this work we want to know if we can or not use H to spatially characterize the spatial data field. Two cases arise: In the first a set of H reflects the local geology, with wells that are geographically closer showing similar H, and then one can use H in geostatistical procedures. In the second case each well has its proper H and the information of the well are uncorrelated, the profiles show only random fluctuations in H that do not show any spatial structure. Cluster analysis is a method widely used in carrying out statistical analysis. In this work we use the non-hierarchy method of k-means. In order to verify whether a set of data generated by the k-means method shows spatial patterns, we create the parameter Ω (index of neighborhood). High Ω shows more aggregated data, low Ω indicates dispersed or data without spatial correlation. With help of this index and the method of Monte Carlo. Using Ω index we verify that random cluster data shows a distribution of Ω that is lower than actual cluster Ω. Thus we conclude that the data of H obtained in 53 wells are grouped and can be used to characterize space patterns. The analysis of curves level confirmed the results of the k-means