972 resultados para Maximum entropy statistical estimate
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The electrocardiogram (ECG) signal has been widely used to study the physiological substrates of emotion. However, searching for better filtering techniques in order to obtain a signal with better quality and with the maximum relevant information remains an important issue for researchers in this field. Signal processing is largely performed for ECG analysis and interpretation, but this process can be susceptible to error in the delineation phase. In addition, it can lead to the loss of important information that is usually considered as noise and, consequently, discarded from the analysis. The goal of this study was to evaluate if the ECG noise allows for the classification of emotions, while using its entropy as an input in a decision tree classifier. We collected the ECG signal from 25 healthy participants while they were presented with videos eliciting negative (fear and disgust) and neutral emotions. The results indicated that the neutral condition showed a perfect identification (100%), whereas the classification of negative emotions indicated good identification performances (60% of sensitivity and 80% of specificity). These results suggest that the entropy of noise contains relevant information that can be useful to improve the analysis of the physiological correlates of emotion.
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The knowledge of the genetic parameters of bromatological traits in forages is essential to support the selection of genotypes that will be released as new cultivars. The objectives of this study were to estimate the heritability coefficients and verify the existence of genetic variability of bromatological traits in Panicum maximum hybrids, evaluated in the Western Amazon in different harvests over the year.
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The objective of this study was to determine the maximum depth, structure, diameter and biomass of the roots of common woody species in two savanna physiognomies (savanna woodland and open woody savanna) in Brazil's Pantanal wetland. The root systems of 37 trees and 34 shrubs of 15 savanna species were excavated to measure their length and depth and estimate the total root biomass through allometric relationships with stem diameter at ground level. In general, statistical regression models between root weight and stem diameter at ground level showed a significance of P < 0.05 and R2 values close to or above 0.8. The average depths of the root system in wetland savanna woodland and open woody savanna are 0.8 ± 0.3 m and 0.7 ± 0.2 m, respectively, and differ from the root systems of savanna woody species in non-flooding areas, whose depth usually ranges from 3 to 19 m.Weattribute this difference to the adaptation of woody plant to the shallow water table, particularly during the wet season. This singularity of woody species in wetland savannas is important when considering biomass and carbon stocks for national and global carbon inventories.
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The present Dissertation shows how recent statistical analysis tools and open datasets can be exploited to improve modelling accuracy in two distinct yet interconnected domains of flood hazard (FH) assessment. In the first Part, unsupervised artificial neural networks are employed as regional models for sub-daily rainfall extremes. The models aim to learn a robust relation to estimate locally the parameters of Gumbel distributions of extreme rainfall depths for any sub-daily duration (1-24h). The predictions depend on twenty morphoclimatic descriptors. A large study area in north-central Italy is adopted, where 2238 annual maximum series are available. Validation is performed over an independent set of 100 gauges. Our results show that multivariate ANNs may remarkably improve the estimation of percentiles relative to the benchmark approach from the literature, where Gumbel parameters depend on mean annual precipitation. Finally, we show that the very nature of the proposed ANN models makes them suitable for interpolating predicted sub-daily rainfall quantiles across space and time-aggregation intervals. In the second Part, decision trees are used to combine a selected blend of input geomorphic descriptors for predicting FH. Relative to existing DEM-based approaches, this method is innovative, as it relies on the combination of three characteristics: (1) simple multivariate models, (2) a set of exclusively DEM-based descriptors as input, and (3) an existing FH map as reference information. First, the methods are applied to northern Italy, represented with the MERIT DEM (∼90m resolution), and second, to the whole of Italy, represented with the EU-DEM (25m resolution). The results show that multivariate approaches may (a) significantly enhance flood-prone areas delineation relative to a selected univariate one, (b) provide accurate predictions of expected inundation depths, (c) produce encouraging results in extrapolation, (d) complete the information of imperfect reference maps, and (e) conveniently convert binary maps into continuous representation of FH.
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To compare time and risk to biochemical recurrence (BR) after radical prostatectomy of two chronologically different groups of patients using the standard and the modified Gleason system (MGS). Cohort 1 comprised biopsies of 197 patients graded according to the standard Gleason system (SGS) in the period 1997/2004, and cohort 2, 176 biopsies graded according to the modified system in the period 2005/2011. Time to BR was analyzed with the Kaplan-Meier product-limit analysis and prediction of shorter time to recurrence using univariate and multivariate Cox proportional hazards model. Patients in cohort 2 reflected time-related changes: striking increase in clinical stage T1c, systematic use of extended biopsies, and lower percentage of total length of cancer in millimeter in all cores. The MGS used in cohort 2 showed fewer biopsies with Gleason score ≤ 6 and more biopsies of the intermediate Gleason score 7. Time to BR using the Kaplan-Meier curves showed statistical significance using the MGS in cohort 2, but not the SGS in cohort 1. Only the MGS predicted shorter time to BR on univariate analysis and on multivariate analysis was an independent predictor. The results favor that the 2005 International Society of Urological Pathology modified system is a refinement of the Gleason grading and valuable for contemporary clinical practice.
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Patients with myofascial pain experience impaired mastication, which might also interfere with their sleep quality. The purpose of this study was to evaluate the jaw motion and sleep quality of patients with myofascial pain and the impact of a stabilization device therapy on both parameters. Fifty women diagnosed with myofascial pain by the Research Diagnostic Criteria were enrolled. Pain levels (visual analog scale), jaw movements (kinesiography), and sleep quality (Epworth Sleepiness Scale; Pittsburgh Sleep Quality Index) were evaluated before (control) and after stabilization device use. Range of motion (maximum opening, right and left excursions, and protrusion) and masticatory movements during Optosil mastication (opening, closing, and total cycle time; opening and closing angles; and maximum velocity) also were evaluated. Repeated-measures analysis of variance in a generalized linear mixed models procedure was used for statistical analysis (α=.05). At baseline, participants with myofascial pain showed a reduced range of jaw motion and poorer sleep quality. Treatment with a stabilization device reduced pain (P<.001) and increased both mouth opening (P<.001) and anteroposterior movement (P=.01). Also, after treatment, the maximum opening (P<.001) and closing (P=.04) velocities during mastication increased, and improvements in sleep scores for the Pittsburgh Sleep Quality Index (P<.001) and Epworth Sleepiness Scale (P=.04) were found. Myofascial pain impairs jaw motion and quality of sleep; the reduction of pain after the use of a stabilization device improves the range of motion and sleep parameters.
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Obstructive lung diseases of different etiologies present with progressive peripheral airway involvement. The peripheral airways, known as the silent lung zone, are not adequately evaluated with conventional function tests. The principle of gas washout has been used to detect pulmonary ventilation inhomogeneity and to estimate the location of the underlying disease process. Volumetric capnography (VC) analyzes the pattern of CO2 elimination as a function of expired volume. To measure normalized phase 3 slopes with VC in patients with non-cystic fibrosis bronchiectasis (NCB) and in bronchitic patients with chronic obstructive pulmonary disease (COPD) in order to compare the slopes obtained for the groups. NCB and severe COPD were enrolled sequentially from an outpatient clinic (Hospital of the State University of Campinas). A control group was established for the NCB group, paired by sex and age. All subjects performed spirometry, VC, and the 6-Minute Walk Test (6MWT). Two comparisons were made: NCB group versus its control group, and NCB group versus COPD group. The project was approved by the ethical committee of the institution. Statistical tests used were Wilcoxon or Student's t-test; P<0.05 was considered to be a statistically significant difference. Concerning the NCB group (N=20) versus the control group (N=20), significant differences were found in body mass index and in several functional variables (spirometric, VC, 6MWT) with worse results observed in the NCB group. In the comparison between the COPD group (N=20) versus the NCB group, although patients with COPD had worse spirometric and 6MWT values, the capnographic variables mean phase 2 slope (Slp2), mean phase 3 slope normalized by the mean expiratory volume, or mean phase 3 slope normalized by the end-tidal CO2 concentration were similar. These findings may indicate that the gas elimination curves are not sensitive enough to monitor the severity of structural abnormalities. The role of normalized phase 3 slope may be worth exploring as a more sensitive index of small airway disease, even though it may not be equally sensitive in discriminating the severity of the alterations.
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In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.
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To investigate the effects of a specific protocol of undulatory physical resistance training on maximal strength gains in elderly type 2 diabetics. The study included 48 subjects, aged between 60 and 85 years, of both genders. They were divided into two groups: Untrained Diabetic Elderly (n=19) with those who were not subjected to physical training and Trained Diabetic Elderly (n=29), with those who were subjected to undulatory physical resistance training. The participants were evaluated with several types of resistance training's equipment before and after training protocol, by test of one maximal repetition. The subjects were trained on undulatory resistance three times per week for a period of 16 weeks. The overload used in undulatory resistance training was equivalent to 50% of one maximal repetition and 70% of one maximal repetition, alternating weekly. Statistical analysis revealed significant differences (p<0.05) between pre-test and post-test over a period of 16 weeks. The average gains in strength were 43.20% (knee extension), 65.00% (knee flexion), 27.80% (supine sitting machine), 31.00% (rowing sitting), 43.90% (biceps pulley), and 21.10% (triceps pulley). Undulatory resistance training used with weekly different overloads was effective to provide significant gains in maximum strength in elderly type 2 diabetic individuals.
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Didanosine-loaded chitosan microspheres were developed applying a surface-response methodology and using a modified Maximum Likelihood Classification. The operational conditions were optimized with the aim of maintaining the active form of didanosine (ddI), which is sensitive to acid pH, and to develop a modified and mucoadhesive formulation. The loading of the drug within the chitosan microspheres was carried out by ionotropic gelation technique with sodium tripolyphosphate (TPP) as cross-linking agent and magnesium hydroxide (Mg(OH)2) to assure the stability of ddI. The optimization conditions were set using a surface-response methodology and applying the Maximum Likelihood Classification, where the initial chitosan concentration, TPP and ddI concentration were set as the independent variables. The maximum ddI-loaded in microspheres (i.e. 1433mg of ddI/g chitosan), was obtained with 2% (w/v) chitosan and 10% TPP. The microspheres depicted an average diameter of 11.42μm and ddI was gradually released during 2h in simulated enteric fluid.
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A flow injection method for the quantitative analysis of ketoconazole in tablets, based on the reaction with iron (III) ions, is presented. Ketoconazole forms a red complex with iron ions in an acid medium, with maximum absorbance at 495 nm. The detection limit was estimated to be 1×10--4 mol L-1; the quantitation limit is about 3×10--4 mol L-1 and approximately 30 determinations can be performed in an hour. The results were compared with those obtained with a reference HPLC method. Statistical comparisons were done using the Student's t procedure and the F test. Complete agreement was found at the 0.95 significance level between the proposed flow injection and the HPLC procedures. The two methods present similar precision, i.e., for HPLC the mean relative standard deviation was ca. 1.2% and for FIA ca. 1.6%.
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Considering intrinsic characteristics of the system exclusively, both statistical and information theory interpretations of the second law are used to provide more comprehensive meanings for the concepts of entropy, temperature, and Helmholtz and Gibbs energies. The coherence of Clausius inequality to these concepts is emphasized. The aim of this work is to re-discuss the second law of thermodynamics in accordance to homogeneous processes thermodynamics, a temporal science which is the very special oversimplification of continuum mechanics for spatially constant intensive properties.
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In Brazil the adoption of several models of cattle confinement leads to special conditions for management methods in dairy production, which can be improved by the use of technology that assures better herd management. Indexes relating environmental variables to production are applied for the prediction of milk production. The values of temperature and relative humidity, rain index, solar radiation and pasture soil temperature are generally considered potential stress agents for cows. The objective of this research was to develop an index for predicting milk production for high productivity Jersey milking cows lodged in semi confinement in tropical conditions. The experiment considered two treatments: A - the cows waited for 30 minutes prior to milking in a room with a shower associated to a fan; B - the cows did not have access to this room (control). Other than the waiting period, the cows had access to pasture. Differences in the effect of average production were not statistically significant. The analysis for studying the effect of the variables and designing the model led to a statistical model relating the variables milk production and rain index, as well as the maximum soil temperature of pasture, and milk production.
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The aim of this study was to investigate the influence of different assessment time periods of submaximal tests on the determination of the maximal accumulated oxygen deficit (MAOD), through the adoption of different time slots of 4 to 6, 6 to 8 and 8 to 10 min. Ten cyclists with mean age of 27.5 ± 4.1 years, body mass 74.4 ± 12.7 kg and time experience of 9.8 ± 4.7 years participated in this study. The athletes underwent an incremental exercise test to determine the peak oxygen consumption (VO2peak), and four submaximal constant work-load test sessions (60, 70, 80 and 90% VO2peak) of 10 min in order to estimate the O2 demand (DEO2). The mean VO2 values obtained on each constant work-load for the 4 to 6, 6 to 8 and 8 to 10 min time-periods intervals were used to perform a linear regression between the intensity and O2 consumption for each time-period. In addition, the subjects performed one supramaximal rectangular test (110% VO2peak) for the quantification of MAOD. There was no significant difference in VO2 between the different time-periods for all submaximal tests (P> 0.05). Similarly, no significant difference was found in DEAO2 and MAOD (P> 0.05). Furthermore, the values of MAOD for the three time-periods intervals showed good agreement and strong correlation. Thus, the data suggest that the submaximal tests used to estimate the values of MAOD can be reduced, at least in this type of sample, and with the use of a cycle simulator.
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Prey size is an important factor in food consumption. In studies of feeding ecology, prey items are usually measured individually using calipers or ocular micrometers. Among amphibians and reptiles, there are species that feed on large numbers of small prey items (e.g. ants, termites). This high intake makes it difficult to estimate prey size consumed by these animals. We addressed this problem by developing and evaluating a procedure for subsampling the stomach contents of such predators in order to estimate prey size. Specifically, we developed a protocol based on a bootstrap procedure to obtain a subsample with a precision error of at the most 5%, with a confidence level of at least 95%. This guideline should reduce the sampling effort and facilitate future studies on the feeding habits of amphibians and reptiles, and also provide a means of obtaining precise estimates of prey size.