988 resultados para Geographic Regression Discontinuity


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Large outliers break down linear and nonlinear regression models. Robust regression methods allow one to filter out the outliers when building a model. By replacing the traditional least squares criterion with the least trimmed squares (LTS) criterion, in which half of data is treated as potential outliers, one can fit accurate regression models to strongly contaminated data. High-breakdown methods have become very well established in linear regression, but have started being applied for non-linear regression only recently. In this work, we examine the problem of fitting artificial neural networks (ANNs) to contaminated data using LTS criterion. We introduce a penalized LTS criterion which prevents unnecessary removal of valid data. Training of ANNs leads to a challenging non-smooth global optimization problem. We compare the efficiency of several derivative-free optimization methods in solving it, and show that our approach identifies the outliers correctly when ANNs are used for nonlinear regression.

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Following the recent success in quantitative analysis of essential fatty acid compositions in a commercial microencapsulated fish oil (?EFO) supplement, we extended the application of portable attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopic technique and partial least square regression (PLSR) analysis for rapid determination of total protein contents-the other major component in most commercial ?EFO powders. In contrast to the traditional chromatographic methodology used in a routine amino acid analysis (AAA), the ATR-FTIR spectra of the ?EFO powder can be acquired directly from its original powder form with no requirement of any sample preparation, making the technique exceptionally fast, noninvasive, and environmentally friendly as well as being cost effective and hence eminently suitable for routine use by industry. By optimizing the spectral region of interest and number of latent factors through the developed PLSR strategy, a good linear calibration model was produced as indicated by an excellent value of coefficient of determination R2 = 0.9975, using standard ?EFO powders with total protein contents in the range of 140-450 mg/g. The prediction of the protein contents acquired from an independent validation set through the optimized PLSR model was highly accurate as evidenced through (1) a good linear fitting (R2 = 0.9759) in the plot of predicted versus reference values, which were obtained from a standard AAA method, (2) lowest root mean square error of prediction (11.64 mg/g), and (3) high residual predictive deviation (6.83) ranked in very good level of predictive quality indicating high robustness and good predictive performance of the achieved PLSR calibration model. The study therefore demonstrated the potential application of the portable ATR-FTIR technique when used together with PLSR analysis for rapid online monitoring of the two major components (i.e., oil and protein contents) in finished ?EFO powders in the actual manufacturing setting.

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Background
Women living in socio-economically disadvantaged neighbourhoods are at increased risk for physical inactivity and associated health outcomes and are difficult to reach through personally tailored interventions. Targeting the built environment may be an effective strategy in this population subgroup. The aim of this study was to examine the mediating role of environmental perceptions in the relationship between the objective environment and walking for transportation/recreation among women from socio-economically disadvantaged neighbourhoods.

Methods
Baseline data of the Resilience for Eating and Activity Despite Inequality (READI) study were used. In total, 4139 women (18–46 years) completed a postal survey assessing physical environmental perceptions (aesthetics, neighbourhood physical activity environment, personal safety, neighbourhood social cohesion), physical activity, and socio-demographics. Objectively-assessed data on street connectivity and density of destinations were collected using a Geographic Information System database and based on the objective z-scores, an objective destinations/connectivity score was calculated. This index was positively scored, with higher scores representing a more favourable environment. Two-level mixed models regression analyses were conducted and the MacKinnon product-of-coefficients test was used to examine the mediating effects.

Results
The destinations/connectivity score was positively associated with transport-related walking. The perceived physical activity environment mediated 6.1% of this positive association. The destinations/connectivity score was negatively associated with leisure-time walking. Negative perceptions of aesthetics, personal safety and social cohesion of the neighbourhood jointly mediated 24.1% of this negative association.

Conclusion

For women living in socio-economically disadvantaged neighbourhoods, environmental perceptions were important mediators of the relationship between the objective built environment and walking. To increase both transport-related and leisure-time walking, it is necessary to improve both objective walkability-related characteristics (street connectivity and proximity of destinations), and perceptions of personal safety, favourable aesthetics and neighbourhood social cohesion.

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The paper provides a systematic and quantitative review of the empirical evidence on the effects of development aid on democracy and governance. We find that aid has had, on average, a zero or negative effect on democracy, except that it has had a positive effect on democratization in European transitional economies. Aid had a positive effect on governance during the Cold War period but has had no effect on governance in the post-Cold War period.