800 resultados para PREDICTING FALLS


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Introduction: the present study aims to evaluate the association between nocturia and falls in a group of community-living elderly men in the city of Sao Paulo (Brazil). Material and methods: under the coordination of the Pan American Health Organization and World Health Organization, a multicenter study named Health, Welfare and Aging (SABE Study) is being conducted to evaluate the living and health conditions of older people in Latin America and Caribbean. In Brazil, this study is evaluating the elderly population (60 years or more) in Sao Paulo since 2000. The presence of nocturia was taken as the response ""yes"" to the question ""Do you need to void three times or more at night?"". The presence of falls was also taken as the response ""yes"" to the question ""Did you have any fall during the last 12 months?"" The intergroup analysis used was the logistic regression. Results: total of 865 men was interviewed, mean age 68 years. It was observed high prevalence of nocturia and falls in all groups, with higher prevalence of both in the eldest group (p < 0.001), however, the association of nocturia and falls was not statistically significant in any of the groups (p = 0.45). Conclusion: this is one of the pioneering studies that assess only the male population, showing that nocturia was not significantly associated with falls. Nocturia and falls are highly prevalent conditions in the elderly, but no association was found between both, so that these variables may be correlated to age and other clinical conditions. (C) 2010 AEU. Published by Elsevier Espana, S.L. All rights reserved.

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We explore the prospects of predicting emission-line features present in galaxy spectra given broad-band photometry alone. There is a general consent that colours, and spectral features, most notably the 4000 angstrom break, can predict many properties of galaxies, including star formation rates and hence they could infer some of the line properties. We argue that these techniques have great prospects in helping us understand line emission in extragalactic objects and might speed up future galaxy redshift surveys if they are to target emission-line objects only. We use two independent methods, Artificial Neural Networks (based on the ANNz code) and Locally Weighted Regression (LWR), to retrieve correlations present in the colour N-dimensional space and to predict the equivalent widths present in the corresponding spectra. We also investigate how well it is possible to separate galaxies with and without lines from broad-band photometry only. We find, unsurprisingly, that recombination lines can be well predicted by galaxy colours. However, among collisional lines some can and some cannot be predicted well from galaxy colours alone, without any further redshift information. We also use our techniques to estimate how much information contained in spectral diagnostic diagrams can be recovered from broad-band photometry alone. We find that it is possible to classify active galactic nuclei and star formation objects relatively well using colours only. We suggest that this technique could be used to considerably improve redshift surveys such as the upcoming Fibre Multi Object Spectrograph (FMOS) survey and the planned Wide Field Multi Object Spectrograph (WFMOS) survey.

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Prediction of random effects is an important problem with expanding applications. In the simplest context, the problem corresponds to prediction of the latent value (the mean) of a realized cluster selected via two-stage sampling. Recently, Stanek and Singer [Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 119-130] developed best linear unbiased predictors (BLUP) under a finite population mixed model that outperform BLUPs from mixed models and superpopulation models. Their setup, however, does not allow for unequally sized clusters. To overcome this drawback, we consider an expanded finite population mixed model based on a larger set of random variables that span a higher dimensional space than those typically applied to such problems. We show that BLUPs for linear combinations of the realized cluster means derived under such a model have considerably smaller mean squared error (MSE) than those obtained from mixed models, superpopulation models, and finite population mixed models. We motivate our general approach by an example developed for two-stage cluster sampling and show that it faithfully captures the stochastic aspects of sampling in the problem. We also consider simulation studies to illustrate the increased accuracy of the BLUP obtained under the expanded finite population mixed model. (C) 2007 Elsevier B.V. All rights reserved.

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New molecular species HSeCl, HClSe, and SeCl were investigated at a high level of theory, CCSD(T), with a series of correlation consistent basis sets with extrapolation to the CBS limit. Account has been taken for valence-only and core-valence correlation effects, and of anharmonic effects on the vibrational frequencies. HSeCl is 43.25 kcal mol (1) more stable than HClSe. A barrier (Delta G(#)) of 47.20 kcal mol (1) separates these species. Internuclear distances are generally overestimated by 0.008 angstrom in the valence-only correlation calculations. Inclusion of anharmonicity leads to much improved vibrational frequencies. For SeCl, we estimate Delta H(f) (0 K) = 23.96 and Delta H(f) (298.15 K) = 24.64 kcal mol (1); for HSeCl, we had 4.20 and 4.97 kcal mol (1), respectively. (C) 2010 Elsevier B.V. All rights reserved.

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We report a novel method for calculating flash points of acyclic alkanes from flash point numbers, N(FP), which can be calculated from experimental or calculated boiling point numbers (Y(BP)) with the equation N(FP) = 1.020Y(BP) - 1.083 Flash points (FP) are then determined from the relationship FP(K) = 23.369N(FP)(2/3) + 20.010N(FP)(1/3) + 31.901 For it data set of 102 linear and branched alkanes, the correlation of literature and predicted flash points has R(2) = 0.985 and an average absolute deviation of 3.38 K. N(FP) values can also be estimated directly from molecular structure to produce an even closer correspondence of literature and predicted FP values. Furthermore, N(FP) values provide a new method to evaluate the reliability of literature flash point data.

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Structural, vibrational, and energetic properties of new molecular species, HSI and HIS are investigated for the first time using a state-of-the-art theoretical approach. These molecules can be easily differentiated by their geometric parameters and vibrational spectra. HSI is much more stable, and a direct unimolecular isomerization is very unlikely. Kinetics estimates predict that only at low temperatures there is a possibility of isolating HIS. For HS-I, we estimate a bond dissociation energy of 46.25 kcal/mol, and a heat of formation at 298.15 K of 12.84 kcal/mol. For the H(2)S + I(2) -> HSI + HI reaction enthalpy, we found 8.40 kcal/ mol. (C) 2008 Elsevier B.V. All rights reserved.

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Applying microeconomic theory, we develop a forecasting model for firm entry into local markets and test this model using data from the Swedish wholesale industry. The empirical analysis is based on directly estimating the profit function of wholesale firms. As in previous entry studies, profits are assumed to depend on firm- and location-specific factors,and the profit equation is estimated using panel data econometric techniques. Using the residuals from the profit equation estimations, we identify local markets in Sweden where firm profits are abnormally high given the level of all independent variables included in the profit function. From microeconomic theory, we then know that these local markets should have higher net entry than other markets, all else being equal, and we investigate this in a second step,also using a panel data econometric model. The results of estimating the net-entry equation indicate that four of five estimated models have more net entry in high-return municipalities, but the estimated parameter is only statistically significant at conventional levels in one of our estimated models.

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The aim of this study was 1) to validate the 0.5 body-mass exponent for maximal oxygen uptake (V. O2max) as the optimal predictor of performance in a 15 km classical-technique skiing competition among elite male cross-country skiers and 2) to evaluate the influence of distance covered on the body-mass exponent for V. O2max among elite male skiers. Twenty-four elite male skiers (age: 21.4±3.3 years [mean ± standard deviation]) completed an incremental treadmill roller-skiing test to determine their V. O2max. Performance data were collected from a 15 km classicaltechnique cross-country skiing competition performed on a 5 km course. Power-function modeling (ie, an allometric scaling approach) was used to establish the optimal body-mass exponent for V . O2max to predict the skiing performance. The optimal power-function models were found to be race speed = 8.83⋅(V . O2max m-0.53) 0.66 and lap speed = 5.89⋅(V . O2max m-(0.49+0.018lap)) 0.43e0.010age, which explained 69% and 81% of the variance in skiing speed, respectively. All the variables contributed to the models. Based on the validation results, it may be recommended that V. O2max divided by the square root of body mass (mL⋅min−1 ⋅kg−0.5) should be used when elite male skiers’ performance capability in 15 km classical-technique races is evaluated. Moreover, the body-mass exponent for V . O2max was demonstrated to be influenced by the distance covered, indicating that heavier skiers have a more pronounced positive pacing profile (ie, race speed gradually decreasing throughout the race) compared to that of lighter skiers.

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Architecture description languages (ADLs) are used to specify high-level, compositional views of a software application. ADL research focuses on software composed of prefabricated parts, so-called software components. ADLs usually come equipped with rigorous state-transition style semantics, facilitating verification and analysis of specifications. Consequently, ADLs are well suited to configuring distributed and event-based systems. However, additional expressive power is required for the description of enterprise software architectures – in particular, those built upon newer middleware, such as implementations of Java’s EJB specification, or Microsoft’s COM+/.NET. The enterprise requires distributed software solutions that are scalable, business-oriented and mission-critical. We can make progress toward attaining these qualities at various stages of the software development process. In particular, progress at the architectural level can be leveraged through use of an ADL that incorporates trust and dependability analysis. Also, current industry approaches to enterprise development do not address several important architectural design issues. The TrustME ADL is designed to meet these requirements, through combining approaches to software architecture specification with rigorous design-by-contract ideas. In this paper, we focus on several aspects of TrustME that facilitate specification and analysis of middleware-based architectures for trusted enterprise computing systems.

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This paper performs a thorough statistical examination of the time-series properties of the daily market volatility index (VIX) from the Chicago Board Options Exchange (CBOE). The motivation lies not only on the widespread consensus that the VIX is a barometer of the overall market sentiment as to what concerns investors' risk appetite, but also on the fact that there are many trading strategies that rely on the VIX index for hedging and speculative purposes. Preliminary analysis suggests that the VIX index displays long-range dependence. This is well in line with the strong empirical evidence in the literature supporting long memory in both options-implied and realized variances. We thus resort to both parametric and semiparametric heterogeneous autoregressive (HAR) processes for modeling and forecasting purposes. Our main ndings are as follows. First, we con rm the evidence in the literature that there is a negative relationship between the VIX index and the S&P 500 index return as well as a positive contemporaneous link with the volume of the S&P 500 index. Second, the term spread has a slightly negative long-run impact in the VIX index, when possible multicollinearity and endogeneity are controlled for. Finally, we cannot reject the linearity of the above relationships, neither in sample nor out of sample. As for the latter, we actually show that it is pretty hard to beat the pure HAR process because of the very persistent nature of the VIX index.

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This paper develops a model of deforestation pressure in the Amazon. It is based on the determinants of demand for agricultural land, i.e. the interactions between population dynamics, urbanization and the growth of local markets, land prices, and government spending and policies. The mo deI is estimated using data from the period 1970 - 1985, and predictions for the period 1985 - 2010 are made under explicit assumptions about the underlying factors of deforestation. The predictions indicate that economic growth in the Amazon is likely to continue at high rates even if the federal government abandons its aggressive development policy. Deforestation will be much smaller if they do, though, since the active development policies tend to promote wasteful use of land.

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In field experiments with subjects living either inside or outside Brazilian slums (n=955), we show that consumers living in slums are less price sensitive, in opposition with recent price sensitivity research. Comparing slum and non-slum dwellers, we found that negatively stereotyped consumers (e.g. slum dwellers) were more likely to pay higher amounts for friendlier customer service when facing social identity threats (SITs) in marketplaces such as banks. The mechanism which makes them less price sensitive is related to the perception of how other people evaluate their social groups, and we argue that they pay more because they are seeking identity-safe commercial relationships. This work, besides extending the literature in SITs, presents a perspective for the exchange between economics and psychology on price sensitivity, showing that consumers living in slums are willing to pay more to avoid possibly social identity threating experiences.

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This thesis aimed at designing and developing a system that can a) infer individuals’ need for a break from sedentary behaviour in the workplace, and b) persuade them to take a break through the use of different techniques from persuasive psychology. We postulated three variables, namely, individuals’ posture, stress levels and involvement in their computer mediated activity. We developed and field-studied a system that could infer these using a web camera and a key presses and mouse clicks log. We found that the system could predict posture from viewing depth and stress from the movement detected. We then created a general formula that predicts individuals’ need for a break using only the posture and stress predictors. Once the first objective was set, we built and field-studied a system that used three ways to communicate a recommendation for a break to a user: implicit, just-in time and ambient feedback. The implicit feedback was operationalized through changes in the users’ computer wallpaper that provided subtle visual cues. The just-in time feedback employed prompting at the bottom right side of the user’s screen. In addition, we implemented an intuitive behind-screen interaction technique where people can snooze a notification using simple gestures. The ambient feedback mechanism employed an origami sculpture sitting on the user’s desk. This prototype was continuously reflecting the user’s posture and performed rhythmic movements when to recommend breaks. A field study demonstrated the overall success of the system, with 69% of the break recommendations received by users were accepted. The study further revealed the strengths and weaknesses of the three persuasive mechanisms.

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The determination of the chemical composition of body and carcass is important in nutritional and growth regulation studies. The purpose of this study was to develop equations to predict the chemical composition of body and carcass using chemical composition of body components. Twenty 3/4Boer x 1/4Saanen crossbred male kids, weighing from 20 to 35 kg, were used in this study. The empty body chemical composition was measured by grinding all body components and sampling for chemical analyses. The body components used to estimate body and carcass composition were: neck, fore leg, ribs, loin, hind leg, 9-11 th rib section, non-carcass components (head plus feet, organs plus blood, and hide), visceral fat, and kidney fat. The chemical composition of organs plus blood and 9-11 th rib section had the highest precision to estimate percentage of fat, protein, and water in the body (r(2) of 0.94, 0.82, and 0.90, respectively). For carcass composition, the chemical composition of ribs was the best component to predict all carcass chemical components; however, the equations to estimate the percentages of protein and ash showed a low precision (r(2) = 0.48, 0.44, respectively). The 9-11 th rib section was accurate and precise to estimate carcass fat percentage. We concluded the chemical composition of the body of 3/4Boer x 1/4Saanen crossbred male kids was highly correlated with the composition of body parts, specifically organs plus blood and 9-11 th rib section. Further studies should focus on evaluating these body parts for different breeds and genders under different production scenarios. (C) 2007 Elsevier B.V. All rights reserved.