Magnetic Field Induced Spin Polarization of AlAs Two-dimensional Electrons

Two-dimensional (2D) electrons in an in-plane magnetic field become fully spin polarized above a field B_P, which we can determine from the in-plane magnetoresistance. We perform such measurements in modulation-doped AlAs electron systems, and find that the field B_P increases approximately linearly with 2D electron density. These results imply that the product |g*|m*, where g* is the effective g-factor and m* the effective mass, is a constant essentially independent of density. While the deduced |g*|m* is enhanced relative to its band value by a factor of ~ 4, we see no indication of its divergence as 2D density approaches zero. These observations are at odds with results obtained in Si-MOSFETs, but qualitatively confirm spin polarization studies of 2D GaAs carriers.Comment: 4 pages, 5 figure

Mortality forecasting in Colombia from abridged life tables by sex

[EN] BACKGROUND: An adequate forecasting model of mortality that allows an analysis of different population changes is a topic of interest for countries in demographic transition. Phenomena such as the reduction of mortality, ageing, and the increase in life expectancy are extremely useful in the planning of public policies that seek to promote the economic and social development of countries. To our knowledge, this paper is one of the first to evaluate the performance of mortality forecasting models applied to abridged life tables. OBJECTIVE: Select a mortality model that best describes and forecasts the characteristics of mortality in Colombia when only abridged life tables are available. DATA AND METHOD: We used Colombian abridged life tables for the period 1973-2005 with data from the Latin American Human Mortality Database. Different mortality models to deal with modeling and forecasting probability of death are presented in this study. For the comparison of mortality models, two criteria were analyzed: graphical residuals analysis and the hold-out method to evaluate the predictive performance of the models, applying different goodness of fit measures. RESULTS: Only three models did not have convergence problems: Lee-Carter (LC), Lee-Carter with two terms (LC2), and Age-Period-Cohort (APC) models. All models fit better for women, the improvement of LC2 on LC is mostly for central ages for men, and the APC model's fit is worse than the other two. The analysis of the standardized deviance residuals allows us to deduce that the models that reasonably fit the Colombian mortality data are LC and LC2. The major residuals correspond to children's ages and later ages for both sexes. CONCLUSION: The LC and LC2 models present better goodness of fit, identifying the principal characteristics of mortality for Colombia.Mortality forecasting from abridged life tables by sex has clear added value for studying differences between developing countries and convergence/divergence of demographic changes.Support for the research presented in this paper was provided by a grant from the Ministerio de Economía y Competitividad of Spain, project no. MTM2013-45381-P.Diaz-Rojo, G.; Debón Aucejo, AM.; Giner-Bosch, V. (2018). Mortality forecasting in Colombia from abridged life tables by sex. Genus. Journal of Population Sciences (Online). 74(15):1-23. https://doi.org/10.1186/s41118-018-0038-6S1237415Aburto, J.M., & García-Guerrero, V.M. (2015). El modelo aditivo doble multiplicativo. Una aplicacion a la mortalidad mexicaná. Papeles de Población, 21(84), 9–44.Acosta, K., & Romero, J. (2014). Cambios recientes en las principales causas de mortalidad en Colombia. 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(2014). Demography: forecasting mortality, fertility, migration and population data. R package version 1.18. https://CRAN.R-project.org/package=demography .Hyndman, R.J., & Ullah, M.S (2007). Robust forecasting of mortality and fertility rates: a functional data approach. Computational Statistics & Data Analysis, 51(10), 4942–4956.Kennes, T. (2017). The convergence and robustness of cohort extensions of mortality models. MaRBLe, 1, 36–53.Lee, R., & Carter, L. (1992). Modelling and forecasting U.S. mortality. Journal of the American Statistical Association, 87, 659–671.Lee, R., & Rofman, R. (1994). Modelación y proyección de la mortalidad en Chile. Notas de Poblacion, 6(59), 183–213.Lee, W. (1997). Characterizing exposure-disease association in human populations using the Lorenz curve and Gini index. Statistics in Medicine, 16(7), 729–739.Levitt, S., & Rubio, M. (2000). Understanding crime in Colombia and what can be done about it. 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La mortalidad y la longevidad en la cuantificación del riesgo actuarial para la población de México. PhD thesis: Universitat de Barcelona.Remund, A., Camarda, C.G., Riffe, T., et al. (2017). A cause-of-death decomposition of the young adult mortality hump. Technical report. Rostock, Germany: Max Planck Institute for Demographic Research.Renshaw, A.E., & Haberman, S. (2003). Lee-Carter mortality forecasting with age-specific enhancement. Insurance: Mathematics and Economics, 33(2), 255–272.Renshaw, A.E., & Haberman, S. (2006). A cohort-based extensionto the Lee-Carter model for mortality reduction factors. Insurance: Mathematic and Economics, 38(3), 556–570.Reyes, A.R. (2010). Una aproximación al costo fiscal en pensiones como consecuencia del envejecimiento de la población en Colombia y el efecto de la sobre-mortalidad masculina. Master’s thesis: Universidad Nacional de Colombia.Richards, S. (2008). Detecting year-of-birth mortality patterns with limited data. Journal of the Royal Statistical Society: Series A (Statistics in Society), 171(1), 279–298.Rodríguez, J. (2007). Desigualdades socioeconómicas entre departamentos y su asociación con indicadores de mortalidad en Colombia en 2000. Rev Panam Salud Publica, 21(2/3), 111–124.Shkolnikov, V.M., Andreev, E.M., Begun, A. (2003). Gini coefficient as a life table function: computation from discrete data, decomposition of differences and empirical examples. Demographic Research, 8, 305–358.Singh, A., Shukla, A., Ram, F., Kumar, K. (2017). Trends in inequality in length of life in India: a decomposition analysis by age and causes of death. Genus, 73(1), 5.Tabeau, E. (2001). A review of demographic forecasting models for mortality. In: Tabeau, E., van den Berg Jeths A., Heathcote C. (Eds.) In Forecasting Mortality in Developed Countries. European Studies of Population, vol 9. Springer, Dordrecht, (pp. 1–32).Turner, H., & Firth, D. (2015). gnm: Generalized nonlinear models in R. R package version 1.0-8. https://CRAN.R-project.org/package=gnm .Urdinola, B.P., & Queiroz, B.L. (2017). Latin American Human Mortality Database. http://www.lamortalidad.org . Accessed 21 Nov 2015

Widening socioeconomic differences in mortality among men aged 65 years and older in Germany

<p>Background Although socioeconomic mortality differences in Germany are well documented, trends in group-specific mortality and differences between the eastern and the western parts of the country remain unexplored.</p><p>Methods Population and death counts by level of lifetime earnings (1995-1996 to 2007-2008) and broad occupational groups (1995-1996 to 2003-2004) for men aged 65 years and older were obtained from the German Federal Pension Fund. Directly standardised mortality rates and life expectancy at age 65 were used as mortality measures.</p><p>Results Mortality declined in all socioeconomic groups in eastern and western Germany and these declines tended to be larger in higher status groups. Relative socioeconomic differences in age-standardised mortality rates and in life expectancy at age 65 widened over time. Absolute differences widened over the majority of time periods. The widening was more pronounced in eastern Germany.</p><p>Conclusions Widening socioeconomic mortality differences in Germany, especially in eastern Germany, show that population groups did not benefit equally from the improvements in survival. The results suggest that special efforts have to be taken in order to reduce mortality among people with lower socioeconomic status, especially in eastern Germany. Health equity should be considered a priority when planning policies, practices, and changes in the healthcare system and related sectors.</p>

Dynamics of electrons in gradient nanostructures (exactly solvable model)

03.65.Ge Solutions of wave equations: bound states, 42.25.Bs Wave propagation, transmission and absorption, 73.63.-b Electronic transport in nanoscale materials and structures,