943 resultados para Higher Order Spectra, Heart Rate Variability, Cardiac State, Signal Analysis, Classification
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This paper examines modern economic growth according to the multidimensional scaling (MDS) method and state space portrait (SSP) analysis. Electing GDP per capita as the main indicator for economic growth and prosperity, the long-run perspective from 1870 to 2010 identifies the main similarities among 34 world partners’ modern economic growth and exemplifies the historical waving mechanics of the largest world economy, the USA. MDS reveals two main clusters among the European countries and their old offshore territories, and SSP identifies the Great Depression as a mild challenge to the American global performance, when compared to the Second World War and the 2008 crisis.
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OBJECTIVE: To analyze the frequency and prevalence of congenital heart defects in a tertiary care center for children with heart diseases. METHODS: We carried out an epidemiological assessment of the first medical visit of 4,538 children in a pediatric hospital from January 1995 to December 1997. All patients with congenital heart defects had their diagnoses confirmed at least on echocardiography. The frequency and prevalence of the anomalies were computed according to the classification of sequential analysis. Age, weight, and sex were compared between the groups of healthy individuals and those with congenital heart defects after distribution according to the age group. RESULTS: Of all the children assessed, 2,017 (44.4%) were diagnosed with congenital heart disease, 201 (4.4%) with acquired heart disease, 52 (1.2%) with arrhythmias, and 2,268 (50%) were healthy children. Congenital heart diseases predominated in neonates and infants, corresponding to 71.5% of the cases. Weight and age were significantly lower in children with congenital heart defects. Ventricular septal defect was the most frequent acyanotic anomaly, and tetralogy of Fallot was the most frequent cyanotic anomaly. CONCLUSION: Children with congenital heart defects are mainly referred during the neonatal period and infancy with impairment in gaining weight. Ventricular septal defect is the most frequent heart defect.
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The aim of this work is to evaluate the capabilities and limitations of chemometric methods and other mathematical treatments applied on spectroscopic data and more specifically on paint samples. The uniqueness of the spectroscopic data comes from the fact that they are multivariate - a few thousands variables - and highly correlated. Statistical methods are used to study and discriminate samples. A collection of 34 red paint samples was measured by Infrared and Raman spectroscopy. Data pretreatment and variable selection demonstrated that the use of Standard Normal Variate (SNV), together with removal of the noisy variables by a selection of the wavelengths from 650 to 1830 cm−1 and 2730-3600 cm−1, provided the optimal results for infrared analysis. Principal component analysis (PCA) and hierarchical clusters analysis (HCA) were then used as exploratory techniques to provide evidence of structure in the data, cluster, or detect outliers. With the FTIR spectra, the Principal Components (PCs) correspond to binder types and the presence/absence of calcium carbonate. 83% of the total variance is explained by the four first PCs. As for the Raman spectra, we observe six different clusters corresponding to the different pigment compositions when plotting the first two PCs, which account for 37% and 20% respectively of the total variance. In conclusion, the use of chemometrics for the forensic analysis of paints provides a valuable tool for objective decision-making, a reduction of the possible classification errors, and a better efficiency, having robust results with time saving data treatments.
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Accomplish high quality of final products in pharmaceutical industry is a challenge that requires the control and supervision of all the manufacturing steps. This request created the necessity of developing fast and accurate analytical methods. Near infrared spectroscopy together with chemometrics, fulfill this growing demand. The high speed providing relevant information and the versatility of its application to different types of samples lead these combined techniques as one of the most appropriated. This study is focused on the development of a calibration model able to determine amounts of API from industrial granulates using NIR, chemometrics and process spectra methodology.
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Free-living energy expenditure (EE) was assessed in 37 young pregnant Gambian women at the 12th (n = 11, 53.5 +/- 1.7 kg), 24th (n = 14, 54.7 +/- 2.1 kg), and 36th (n = 12, 65.0 +/- 2.6 kg) wk of pregnancy and was compared with nonpregnant nonlactating (NPNL) control women (n = 12, 50.3 +/- 1.6 kg). The following two methods were used to assess EE: 1) the heart rate (HR) method using individual regression lines (HR vs EE) established at different activity levels in a respiration chamber and 2) the doubly labeled water (2H2(18)O) method in a subgroup of 25 pregnant and 7 control women. With the HR method the EE during the agricultural rainy season was found to be 2,408 +/- 87, 2,293 +/- 122, and 2,782 +/- 130 kcal/day at 12, 24, and 36 wk of gestation and were not significantly different from the control group (2,502 +/- 133 kcal/day). These findings were confirmed by the 2H2(18)O measurements, which failed to show any effect of pregnancy on EE. Expressed per unit body weight, the free-living EE was found to be lower (P less than 0.01 with 2H2(18)O method) at 36 wk of gestation than in the NPNL group. It is concluded that, in these Gambian women, energy-sparing mechanisms that contribute to meet the additional energy stress of gestation are operating during pregnancy (e.g., diminished spontaneous physical activity).
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The brain with its highly complex structure made up of simple units,imterconnected information pathways and specialized functions has always been an object of mystery and sceintific fascination for physiologists,neuroscientists and lately to mathematicians and physicists. The stream of biophysicists are engaged in building the bridge between the biological and physical sciences guided by a conviction that natural scenarios that appear extraordinarily complex may be tackled by application of principles from the realm of physical sciences. In a similar vein, this report aims to describe how nerve cells execute transmission of signals ,how these are put together and how out of this integration higher functions emerge and get reflected in the electrical signals that are produced in the brain.Viewing the E E G Signal through the looking glass of nonlinear theory, the dynamics of the underlying complex system-the brain ,is inferred and significant implications of the findings are explored.
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The aim of this article is to assess the role of real effective exchange rate volatility on long-run economic growth for a set of 82 advanced and emerging economies using a panel data set ranging from 1970 to 2009. With an accurate measure for exchange rate volatility, the results for the two-step system GMM panel growth models show that a more (less) volatile RER has significant negative (positive) impact on economic growth and the results are robust for different model specifications. In addition to that, exchange rate stability seems to be more important to foster long-run economic growth than exchange rate misalignment
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Astronauts performing extravehicular activities (EVA) are at risk for occupational hazards due to a hypobaric environment, in particular Decompression Sickness (DCS). DCS results from nitrogen gas bubble formation in body tissues and venous blood. Denitrogenation achieved through lengthy staged decompression protocols has been the mainstay of prevention of DCS in space. Due to the greater number and duration of EVAs scheduled for construction and maintenance of the International Space Station, more efficient alternatives to accomplish missions without compromising astronaut safety are desirable. ^ This multi-center, multi-phase study (NASA-Prebreathe Reduction Protocol study, or PRP) was designed to identify a shorter denitrogenation protocol that can be implemented before an EVA, based on the combination of adynamia and exercise enhanced oxygen prebreathe. Human volunteers recruited at three sites (Texas, North Carolina and Canada) underwent three different combinations (“PRP phases”) of intense and light exercise prior to decompression in an altitude chamber. The outcome variables were detection of venous gas embolism (VGE) by precordial Doppler ultrasound, and clinical manifestations of DCS. Independent variables included age, gender, body mass index, oxygen consumption peak, peak heart rate, and PRP phase. Data analysis was performed both by pooling results from all study sites, and by examining each site separately. ^ Ten percent of the subjects developed DCS and 20% showed evidence of high grade VGE. No cases of DCS occurred in one particular PRP phase with use of the combination of dual-cycle ergometry (10 minutes at 75% of VO2 peak) plus 24 minutes of light EVA exercise (p = 0.04). No significant effects were found for the remaining independent variables on the occurrence of DCS. High grade VGE showed a strong correlation with subsequent development of DCS (sensitivity, 88.2%; specificity, 87.2%). In the presence of high grade VGE, the relative risk for DCS ranged from 7.52 to 35.0. ^ In summary, a good safety level can be achieved with exercise-enhanced oxygen denitrogenation that can be generalized to the astronaut population. Exercise is beneficial in preventing DCS if a specific schedule is followed, with an individualized VO2 prescription that provides a safety level that can then be applied to space operations. Furthermore, VGE Doppler detection is a useful clinical tool for prediction of altitude DCS. Because of the small number of high grade VGE episodes, the identification of a high probability DCS situation based on the presence of high grade VGE seems justified in astronauts. ^
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Birth defects are the leading cause of infant mortality in the United States and are a major cause of lifetime disability. However, efforts to understand their causes have been hampered by a lack of population-specific data. During 1990–2004, 22 state legislatures responded to this need by proposing birth defects surveillance legislation (BDSL). The contrast between these states and those that did not pass BDSL provides an opportunity to better understand conditions associated with US public health policy diffusion. ^ This study identifies key state-specific determinants that predict: (1) the introduction of birth defects surveillance legislation (BDSL) onto states' formal legislative agenda, and (2) the successful adoption of these laws. Secondary aims were to interpret these findings in a theoretically sound framework and to incorporate evidence from three analytical approaches. ^ The study begins with a comparative case study of Texas and Oregon (states with divergent BDSL outcomes), including a review of historical documentation and content analysis of key informant interviews. After selecting and operationalizing explanatory variables suggested by the case study, Qualitative Comparative Analysis (QCA) was applied to publically available data to describe important patterns of variation among 37 states. Results from logistic regression were compared to determine whether the two methods produced consistent findings. ^ Themes emerging from the comparative case study included differing budgetary conditions and the significance of relationships within policy issue networks. However, the QCA and statistical analysis pointed to the importance of political parties and contrasting societal contexts. Notably, state policies that allow greater access to citizen-driven ballot initiatives were consistently associated with lower likelihood of introducing BDSL. ^ Methodologically, these results indicate that a case study approach, while important for eliciting valuable context-specific detail, may fail to detect the influence of overarching, systemic variables, such as party competition. However, QCA and statistical analyses were limited by a lack of existing data to operationalize policy issue networks, and thus may have downplayed the impact of personal interactions. ^ This study contributes to the field of health policy studies in three ways. First, it emphasizes the importance of collegial and consistent relationships among policy issue network members. Second, it calls attention to political party systems in predicting policy outcomes. Finally, a novel approach to interpreting state data in a theoretically significant manner (QCA) has been demonstrated.^
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This study empirically analyzes the sources of the exchange rate fluctuations in India by employing the structural VAR model. The VAR system consists of three variables, i.e., the nominal exchange rate, the real exchange rate, and the relative output of India and a foreign country. Consistent with most previous studies, the empirical evidence demonstrates that real shocks are the main drives of the fluctuations in real and nominal exchange rates, indicating that the central bank cannot maintain the real exchange rate at its desired level over time.
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A unified solution framework is presented for one-, two- or three-dimensional complex non-symmetric eigenvalue problems, respectively governing linear modal instability of incompressible fluid flows in rectangular domains having two, one or no homogeneous spatial directions. The solution algorithm is based on subspace iteration in which the spatial discretization matrix is formed, stored and inverted serially. Results delivered by spectral collocation based on the Chebyshev-Gauss-Lobatto (CGL) points and a suite of high-order finite-difference methods comprising the previously employed for this type of work Dispersion-Relation-Preserving (DRP) and Padé finite-difference schemes, as well as the Summationby- parts (SBP) and the new high-order finite-difference scheme of order q (FD-q) have been compared from the point of view of accuracy and efficiency in standard validation cases of temporal local and BiGlobal linear instability. The FD-q method has been found to significantly outperform all other finite difference schemes in solving classic linear local, BiGlobal, and TriGlobal eigenvalue problems, as regards both memory and CPU time requirements. Results shown in the present study disprove the paradigm that spectral methods are superior to finite difference methods in terms of computational cost, at equal accuracy, FD-q spatial discretization delivering a speedup of ð (10 4). Consequently, accurate solutions of the three-dimensional (TriGlobal) eigenvalue problems may be solved on typical desktop computers with modest computational effort.
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The European Union and Singapore are vastly different entities, each with its own regional and global priorities and policies. Both actors employ a range of tools and instruments to aid in their foreign policy objectives, including in the projection of their soft power. It is worth analysing and comparing the specific instruments of these two actors’ soft power strategies, including but not limited to their stated objectives and perceived effectiveness. This paper will compare the role of higher education and scholarships in diffusing soft power through a comparative case study of the Erasmus Mundus scholarship program and the Singapore Scholarship administered by the Ministry of Foreign Affairs. It will look at the ways in which these programs have shaped the standing of the actors in diffusing their norms and objectives in the regional and international arena. A comparative analysis of these programs will hopefully provide some insight into the proximity between foreign policy-making and higher education internationalisation. This paper will begin with an overview of the aforementioned programs and related schemes, before dissecting and comparing the intent and the policy-making processes behind these, and concludes with a discussion on the present and future role of higher education as a strategic soft power tool.
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"References by chapters": p. 147-152.