Probabilistic population projections for countries with generalized HIV/AIDS epidemics

In 2015, the United Nations (UN) issued probabilistic population projections for all countries up to 2100, by simulating future levels of total fertility and life expectancy and combining the results using a standard cohort component projection method. For the 40 countries with generalized HIV/AIDS epidemics, the mortality projections used the Spectrum/Estimation and Projection Package (EPP) model, a complex, multistate model designed for short-term projections of policy-relevant quantities for the epidemic. We propose a simpler approach that is more compatible with existing UN projection methods for other countries. Changes in life expectancy are projected probabilistically using a simple time series regression and then converted to age- and sex-specific mortality rates using model life tables designed for countries with HIV/AIDS epidemics. These are then input to the cohort component method, as for other countries. The method performed well in an out-of-sample cross-validation experiment. It gives similar short-run projections to Spectrum/EPP, while being simpler and avoiding multistate modelling.     

互联网时代媒体融合发展的未来模式探索

以互联网技术为引领的新技术为传统媒体的发展带来了新的机遇与挑战.从历史的角度看,传播媒介的发展轨迹与技术变革的历史脉络相互印合.媒体融合的层次与内涵日渐丰富,产业实践中呈现出复杂的博弈与协作关系.传统媒体独特的版权资源与人才储备优势,与新兴媒体的传播渠道及传播效率优势相结合,互相推动,深入协作,通过媒介融合渠道,实现优秀的人才、优质的内容与优化的传播平台的整合,以形成迸发式的传播威力,推动传播层次的迭代发展.面向技术发展前景的媒体融合,应当秉承开放与共享的新思维、立体与互动的新路径,注重以用户为中心,充分利用技术的便捷性,实现媒介传播渠道的多层次性与互动性,超越阶段性的固有技术模式,以踏准未来的节拍.     

信息时代高校外语教师职业发展新模式

文章简要陈述了信息时代高校外语教师职业发展趋势和信息时代对高校外语教师职业发展的挑战,并再对信息时代高校外语教师职业发展新模式的实现途径进行了有效探究。     

Mediation Role of Dyadic Coping on Parenting Stress and Relational Resilience in Couples

This study aims to explore the mediating role of dyadic coping between relational resilience and parenting stress on married couples. The study participants comprised 229 married couples with at least one child and who have had a major life event. The relational resilience scale, parenting stress inventory, dyadic coping scale and personal information, and life events forms were used to collect data for this study. Data were analyzed with the actor–partner interdependence mediation model. The results revealed that dyadic coping actor–partner effects did not mediate between relational resilience and parenting stress. The results were discussed in relation to the social-ecological model and relevant literature. Based on the current findings, recommendations and implications for further research and practice were also proposed.     

Heating up the debate? Measuring fragmentation and polarisation in a German climate change hyperlink network

Research into polarisation on the internet has so far primarily focused on contentious issues and yielded contradictory results. Shifting the focus to a non-contentious setting, this article combines community detection with brokerage analysis and exponential random graph models to assess the degree of polarisation at different levels of a German hyperlink network on climate change. Although homophily accounts for a moderate degree of polarisation at the top level of the network, the communities reveal that other factors prove more decisive in shaping its structure and the article thus contributes to a more refined understanding of the nature of online polarisation.     

Testing an Integrative Contextual Career Development Model With Adolescents From High‐Poverty Urban Areas

Variations in the economic recovery rate across the United States have led to even greater chasms that separate the employed, unemployed, and underemployed (DeSilver, 2017 ). Therefore, understanding and supporting the career development of future generations is critical—especially for those who live outside the context of social privilege. The authors examined the applicability of the integrative contextual model of career development (ICM; Lapan, 2004 ) to a sample of 220 adolescents (129 boys, 91 girls) from a high‐poverty urban area. Results indicated that a canonical variate comprising foundational ICM skills (e.g., career exploration, goal setting) predicted a variate composed of ICM outcomes (e.g., self‐efficacy, vocational identity), thus supporting the usefulness of the ICM framework for this population. The skill of setting viable career goals was an especially strong predictor of outcomes. Implications for career counseling with adolescents living in high‐poverty urban areas and directions for future research are discussed.     

The additive hazards model with high-dimensional regressors

This paper considers estimation and prediction in the Aalen additive hazards model in the case where the covariate vector is high-dimensional such as gene expression measurements. Some form of dimension reduction of the covariate space is needed to obtain useful statistical analyses. We study the partial least squares regression method. It turns out that it is naturally adapted to this setting via the so-called Krylov sequence. The resulting PLS estimator is shown to be consistent provided that the number of terms included is taken to be equal to the number of relevant components in the regression model. A standard PLS algorithm can also be constructed, but it turns out that the resulting predictor can only be related to the original covariates via time-dependent coefficients. The methods are applied to a breast cancer data set with gene expression recordings and to the well known primary biliary cirrhosis clinical data.     

Accelerated test system strength models based on Birnbaum–Saunders distribution: a complete Bayesian analysis and comparison

Several models for studies related to tensile strength of materials are proposed in the literature where the size or length component has been taken to be an important factor for studying the specimens’ failure behaviour. An important model, developed on the basis of cumulative damage approach, is the three-parameter extension of the Birnbaum–Saunders fatigue model that incorporates size of the specimen as an additional variable. This model is a strong competitor of the commonly used Weibull model and stands better than the traditional models, which do not incorporate the size effect. The paper considers two such cumulative damage models, checks their compatibility with a real dataset, compares them with some of the recent toolkits, and finally recommends a model, which appears an appropriate one. Throughout the study is Bayesian based on Markov chain Monte Carlo simulation.     

ASSOCIATIONS BETWEEN AIR POLLUTION AND HOSPITAL VISITS FOR CARDIOVASCULAR DISEASES IN THE ELDERLY IN SYDNEY USING BAYESIAN STATISTICAL METHODS

Using generalized linear models (GLMs), Jalaludin  et al. (2006;  J. Exposure Analysis and Epidemiology   16 , 225–237) studied the association between the daily number of visits to emergency departments for cardiovascular disease by the elderly (65+) and five measures of ambient air pollution. Bayesian methods provide an alternative approach to classical time series modelling and are starting to be more widely used. This paper considers Bayesian methods using the dataset used by Jalaludin  et al.  (2006) , and compares the results from Bayesian methods with those obtained by Jalaludin  et al.  (2006) using GLM methods.     

VARIATIONAL BAYESIAN ANALYSIS FOR HIDDEN MARKOV MODELS

The variational approach to Bayesian inference enables simultaneous estimation of model parameters and model complexity. An interesting feature of this approach is that it also leads to an automatic choice of model complexity. Empirical results from the analysis of hidden Markov models with Gaussian observation densities illustrate this. If the variational algorithm is initialized with a large number of hidden states, redundant states are eliminated as the method converges to a solution, thereby leading to a selection of the number of hidden states. In addition, through the use of a variational approximation, the deviance information criterion for Bayesian model selection can be extended to the hidden Markov model framework. Calculation of the deviance information criterion provides a further tool for model selection, which can be used in conjunction with the variational approach.