882 resultados para non-linear regression
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA
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The research aimed to estimate body contents of protein and energy and net requirements of energy for maintenance of buffaloes, slaughtered at different stages of maturity. There were used 14 Mediterranean intact males with initial average body weight of 352.2 +/- 24.3 kg and average age of 24 months. The animais were randomly divided into four experimental groups. One group was designed to slaughter at the beginning of the experimental period (IS). The animals of another group were restricting fed, receiving, individually, levels of protein and energy 15% above maintenance (RF). The animals of the two remaining groups were individually fed ad libitum (SW450 and SW500) to reach weights corresponding to 100 and 110 percent of the mature weight of the buffalo cows (respectively 450 and 550 kg). The ration contained ground-corn cobs, soybean meal, urea, minerals, and signal-grass (Brachiaria decumbens) hay, with a concentrate: roughage ratio of 50: 50 and 13% of crude protein on a dry matter basis. To estimate changes in body composition inside the range of weights included in the trial, linear regression equations of log protein (kg), fat (kg) and energy (Mcal) as a function of log empty-body-weight (EBW), in kg, were fitted. Energy requirements for maintenance were obtained as estimated heat production at zero level of energy intake. Buffaloes submitted to fattening in feedlot presented early body fat deposition, and had with the same live weight lower protein content and higher fat content and energy per unit weight than european-zebu crossbred cattle.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In this paper, we deal with the research of a vibrating model of an energy harvester device, including the nonlinearities in the model of the piezoelectric coupling and the non-ideal excitation. We show, using numerical simulations, in the analysis of the dynamic responses, that the harvested power is influenced by non-linear vibrations of the structure. Chaotic behavior was also observed, causing of the loss of energy throughout the simulation time. Using a perturbation technique, we find an approximate analytical solution for the non-ideal system. Then, we apply both two control techniques, to keep the considered system, into a stable condition. Both the State Dependent Ricatti Equation (SDRE) control as the feedback control by changing the energy of the oscillator, were efficient in controlling of the considered non-ideal system.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Background: Frailty in older adults is a multifactorial syndrome defined by low metabolic reserve, less resistance to stressors, and difficulty in maintaining organic homeostasis due to cumulative decline of multiple physiological systems. The relationship between frailty and cognition remains unclear and studies about Mini-Mental State Examination (MMSE) performance and frailty are scarce. The objective was to examine the association between frailty and cognitive functioning as assessed by the MMSE and its subdomains. Methods: A cross-sectional population-based study (FIBRA) was carried out in Ermelino Matarazzo, a poor subdistrict of the city of Sao Paulo, Brazil. Participants were 384 community dwelling older adults, 65 years and older who completed the MMSE and a protocol to assess frailty criteria as described in the Cardiovascular Health Study (CHS). Results: Frail older adults had significantly worse performance on the MMSE (p < 0.001 for total score). Linear regression analyses showed that the MMSE total score was influenced by age (p < 0.001), education (p < 0.001), family income (p < 0.001), and frailty status (p < 0.036). Being frail was associated more significantly with worse scores in Time Orientation (p < 0.004) and Immediate Memory (p < 0.001). Conclusions: Our data suggest that being frail is associated with worse cognitive performance, as assessed by the MMSE. It is recommended that the assessment of frail older adults should include the investigation of their cognitive status.
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Long-term endurance sports are associated with atrial remodeling and an increased risk for atrial fibrillation (AF) and atrial flutter. Pro-atrial natriuretic peptide (pro-ANP) is a marker of atrial wall tension and elevated in patients with AF. The aim of this study was to test the hypothesis that atrial remodeling would be perpetuated by repetitive episodes of atrial stretching during strenuous competitions, reflected by elevated levels of pro-ANP. A cross-sectional study was performed on nonelite runners scheduled to participate in the 2010 Grand Prix of Bern, a 10-mile race. Four hundred ninety-two marathon and nonmarathon runners applied for participation, 70 were randomly selected, and 56 entered the final analysis. Subjects were stratified according to former marathon participations: a control group (nonmarathon runners, n = 22), group 1 (1 to 4 marathons, n = 16), and group 2 (≥5 marathons, n = 18). Results were adjusted for age, training years, and average weekly endurance training hours. The mean age was 42 ± 7 years. Compared to the control group, marathon runners in groups 1 and 2 had larger left atria (25 ± 6 vs 30 ± 6 vs 34 ± 7 ml/m(2), p = 0.002) and larger right atria (27 ± 7 vs 31 ± 8 vs 35 ± 5 ml/m(2), p = 0.024). Pro-ANP levels at baseline were higher in marathon runners (1.04 ± 0.38 vs 1.42 ± 0.74 vs 1.67 ± 0.69 nmol/L, p = 0.006). Pro-ANP increased significantly in all groups after the race. In multiple linear regression analysis, marathon participation was an independent predictor of left atrial (β = 0.427, p <0.001) and right atrial (β = 0.395, p = 0.006) remodeling. In conclusion, marathon running was associated with progressive left and right atrial remodeling, possibly induced by repetitive episodes of atrial stretching. The altered left and right atrial substrate may facilitate atrial arrhythmias.
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INTRODUCTION: Winter sports have evolved from an upper class activity to a mass industry. Especially sledging regained popularity at the start of this century, with more and more winter sports resorts offering sledge runs. This study investigated the rates of sledging injuries over the last 13 years and analysed injury patterns specific for certain age groups, enabling us to make suggestions for preventive measures. METHODS: We present a retrospective analysis of prospectively collected data. From 1996/1997 to 2008/2009, all patients involved in sledging injuries were recorded upon admission to a Level III trauma centre. Injuries were classified into body regions according to the Abbreviated Injury Scale (AIS). The Injury Severity Score (ISS) was calculated. Patients were stratified into 7 age groups. Associations between age and injured body region were tested using the chi-squared test. The slope of the linear regression with 95% confidence intervals was calculated for the proportion of patients with different injured body regions and winter season. RESULTS: 4956 winter sports patients were recorded. 263 patients (5%) sustained sledging injuries. Sledging injury patients had a median age of 22 years (interquartile range [IQR] 14-38 years) and a median ISS of 4 (IQR 1-4). 136 (51.7%) were male. Injuries (AIS≥2) were most frequent to the lower extremities (n=91, 51.7% of all AIS≥2 injuries), followed by the upper extremities (n=48, 27.3%), the head (n=17, 9.7%), the spine (n=7, 4.0%). AIS≥2 injuries to different body regions varied from season to season, with no significant trends (p>0.19). However, the number of patients admitted with AIS≥2 injuries increased significantly over the seasons analysed (p=0.031), as did the number of patients with any kind of sledging injury (p=0.004). Mild head injuries were most frequent in the youngest age group (1-10 years old). Injuries to the lower extremities were more often seen in the age groups from 21 to 60 years (p<0.001). CONCLUSION: Mild head trauma was mainly found in very young sledgers, and injuries to the lower extremities were more frequent in adults. In accordance with the current literature, we suggest that sledging should be performed in designated, obstacle-free areas that are specially prepared, and that children should always be supervised by adults. The effect of routine use of helmets and other protective devices needs further evaluation, but it seems evident that these should be obligatory on official runs.
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The aims of this study were to assess and compare the methodological quality of Cochrane and non-Cochrane systematic reviews (SRs) published in leading orthodontic journals and the Cochrane Database of Systematic Reviews (CDSR) using AMSTAR and to compare the prevalence of meta-analysis in both review types. A literature search was undertaken to identify SRs that consisted of hand-searching five major orthodontic journals [American Journal of Orthodontics and Dentofacial Orthopedics, Angle Orthodontist, European Journal of Orthodontics, Journal of Orthodontics and Orthodontics and Craniofacial Research (February 2002 to July 2011)] and the Cochrane Database of Systematic Reviews from January 2000 to July 2011. Methodological quality of the included reviews was gauged using the AMSTAR tool involving 11 key methodological criteria with a score of 0 or 1 given for each criterion. A cumulative grade was given for the paper overall (0-11); an overall score of 4 or less represented poor methodological quality, 5-8 was considered fair and 9 or greater was deemed to be good. In total, 109 SRs were identified in the five major journals and on the CDSR. Of these, 26 (23.9%) were in the CDSR. The mean overall AMSTAR score was 6.2 with 21.1% of reviews satisfying 9 or more of the 11 criteria; a similar prevalence of poor reviews (22%) was also noted. Multiple linear regression indicated that reviews published in the CDSR (P < 0.01); and involving meta-analysis (β = 0.50, 95% confidence interval 0.72, 2.07, P < 0.001) showed greater concordance with AMSTAR.
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Interaction effect is an important scientific interest for many areas of research. Common approach for investigating the interaction effect of two continuous covariates on a response variable is through a cross-product term in multiple linear regression. In epidemiological studies, the two-way analysis of variance (ANOVA) type of method has also been utilized to examine the interaction effect by replacing the continuous covariates with their discretized levels. However, the implications of model assumptions of either approach have not been examined and the statistical validation has only focused on the general method, not specifically for the interaction effect.^ In this dissertation, we investigated the validity of both approaches based on the mathematical assumptions for non-skewed data. We showed that linear regression may not be an appropriate model when the interaction effect exists because it implies a highly skewed distribution for the response variable. We also showed that the normality and constant variance assumptions required by ANOVA are not satisfied in the model where the continuous covariates are replaced with their discretized levels. Therefore, naïve application of ANOVA method may lead to an incorrect conclusion. ^ Given the problems identified above, we proposed a novel method modifying from the traditional ANOVA approach to rigorously evaluate the interaction effect. The analytical expression of the interaction effect was derived based on the conditional distribution of the response variable given the discretized continuous covariates. A testing procedure that combines the p-values from each level of the discretized covariates was developed to test the overall significance of the interaction effect. According to the simulation study, the proposed method is more powerful then the least squares regression and the ANOVA method in detecting the interaction effect when data comes from a trivariate normal distribution. The proposed method was applied to a dataset from the National Institute of Neurological Disorders and Stroke (NINDS) tissue plasminogen activator (t-PA) stroke trial, and baseline age-by-weight interaction effect was found significant in predicting the change from baseline in NIHSS at Month-3 among patients received t-PA therapy.^
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Strategies are compared for the development of a linear regression model with stochastic (multivariate normal) regressor variables and the subsequent assessment of its predictive ability. Bias and mean squared error of four estimators of predictive performance are evaluated in simulated samples of 32 population correlation matrices. Models including all of the available predictors are compared with those obtained using selected subsets. The subset selection procedures investigated include two stopping rules, C$\sb{\rm p}$ and S$\sb{\rm p}$, each combined with an 'all possible subsets' or 'forward selection' of variables. The estimators of performance utilized include parametric (MSEP$\sb{\rm m}$) and non-parametric (PRESS) assessments in the entire sample, and two data splitting estimates restricted to a random or balanced (Snee's DUPLEX) 'validation' half sample. The simulations were performed as a designed experiment, with population correlation matrices representing a broad range of data structures.^ The techniques examined for subset selection do not generally result in improved predictions relative to the full model. Approaches using 'forward selection' result in slightly smaller prediction errors and less biased estimators of predictive accuracy than 'all possible subsets' approaches but no differences are detected between the performances of C$\sb{\rm p}$ and S$\sb{\rm p}$. In every case, prediction errors of models obtained by subset selection in either of the half splits exceed those obtained using all predictors and the entire sample.^ Only the random split estimator is conditionally (on $\\beta$) unbiased, however MSEP$\sb{\rm m}$ is unbiased on average and PRESS is nearly so in unselected (fixed form) models. When subset selection techniques are used, MSEP$\sb{\rm m}$ and PRESS always underestimate prediction errors, by as much as 27 percent (on average) in small samples. Despite their bias, the mean squared errors (MSE) of these estimators are at least 30 percent less than that of the unbiased random split estimator. The DUPLEX split estimator suffers from large MSE as well as bias, and seems of little value within the context of stochastic regressor variables.^ To maximize predictive accuracy while retaining a reliable estimate of that accuracy, it is recommended that the entire sample be used for model development, and a leave-one-out statistic (e.g. PRESS) be used for assessment. ^
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Authors discuss the effects that economic crises generate on the global market shares of tourism destinations, through a series of potential transmission mechanisms based on the main economic competitiveness determinants identified in the previous literature using a non-linear approach. Specifically a Markov Switching Regression approach is used to estimate the effect of two basic transmission mechanisms: reductions of internal and external tourism demands and falling investment.
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The significant gains in export market shares made in a number of vulnerable euro-area crisis countries have not been accompanied by an appropriate improvement in price competitiveness. This paper argues that, under certain conditions, firms consider export activity as a substitute for serving domestic demand. The strength of the link between domestic demand and exports is dependent on capacity constraints. Our econometric model for six euro-area countries suggests domestic demand pressure and capacity-constraint restrictions as additional variables of a properly specified export equation. As an innovation to the literature, we assess the empirical significance through the logistic and the exponential variant of the non-linear smooth transition regression model. We find that domestic demand developments are relevant for the short-run dynamics of exports in particular during more extreme stages of the business cycle. A strong substitutive relationship between domestic and foreign sales can most clearly be found for Spain, Portugal and Italy, providing evidence of the importance of sunk costs and hysteresis in international trade.
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Thesis (Ph.D.)--University of Washington, 2016-06
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Background: Indigenous Australians are at high risk for cardiovascular disease and type 2 diabetes. Carotid artery intimal medial thickness (CIMT) and brachial artery flow-mediated vasodilation (FMD) are ultrasound imaging based surrogate markers of cardiovascular risk. This study examines the relative contributions of traditional cardiovascular risk factors on CIMT and FMD in adult Indigenous Australians with and without type 2 diabetes mellitus. Method: One hundred and nineteen Indigenous Australians were recruited. Physical and biochemical markers of cardiovascular risk, together with CIMT and FMD were meausred for all subjects. Results: Fifty-three Indigenous Australians subjects (45%) had type 2 diabetes mellitus. There was a significantly greater mean CIMT in diabetic versus non-diabetic subjects (p = 0.049). In the non-diabetic group with non-parametric analyses, there were significant correlations between CIMT and: age (r = 0.64, p < 0.001), systolic blood pressure (r = 0.47, p < 0.001) and non-smokers (r = -0.30, p = 0.018). In the diabetic group, non-parametric analysis showed correlations between CIMT, age (r = 0.36, p = 0.009) and duration of diabetes (r = 0.30, p = 0.035) only. Adjusting forage, sex, smoking and history of cardiovascular disease, Hb(A1c) became the sole significant correlate of CIMT (r = 0.35,p = 0.01) in the diabetic group. In non-parametric analysis, age was the sole significant correlate of FMD (r = -0.31,p = 0.013), and only in non-diabetic subjects. Linear regression analysis showed significant associations between CIMT and age (t = 4.6,p < 0.001), systolic blood pressure (t = 2.6, p = 0.010) and Hb(A1c) (t = 2.6, p = 0.012), smoking (t = 2.1, p = 0.04) and fasting LDL-cholesterol (t = 2.1, p = 0.04). There were no significant associations between FMD and examined cardiovascular risk factors with linear regression analysis Conclusions: CIMT appears to be a useful surrogate marker of cardiovascular risk in this sample of Indigenous Australian subjects, correlating better than FMD with established cardiovascular risk factors. A lifestyle intervention programme may alleviate the burden of cardiovascular disease in Indigenous Australians by reducing central obesity, lowering blood pressure, correcting dyslipidaemia and improving glycaemic control. CIMT may prove to be a useful tool to assess efficacy of such an intervention programme. (c) 2004 Elsevier Ireland Ltd. All rights reserved.