How do policy levers shape the quality of a national health system?

Poor quality of care may have a detrimental effect on access and take-up and can become a serious barrier to the universality of health services. This consideration is of particular interest in view of the fact that health systems in many countries must address a growing public-sector deficit and respond to increasing pressures due to COVID-19 and aging population, among other factors. In line with a rapidly emerging literature, we focus on patient satisfaction as a proxy for quality of health care. Drawing on rich longitudinal and cross-sectional data for Spain and multilevel estimation techniques, we show that in addition to individual level differences, policy levers (such as public health spending and the patient-doctor ratio, in particular) exert a considerable influence on the quality of a health care system. Our results suggest that policymakers seeking to enhance the quality of care should be cautious when compromising the level of health resources, and in particular, health personnel, as a response to economic downturns in a sector that traditionally had insufficient human resources in many countries, which have become even more evident in the light of the current health crisis. Additionally, we provide evidence that the increasing reliance on the private health sector may be indicative of inefficiencies in the public system and/or the existence of features of private insurance which are deemed important by patients.     

Modelling daily multivariate pollutant data at multiple sites

Summary. This paper considers the spatiotemporal modelling of four pollutants measured daily at eight monitoring sites in London over a 4-year period. Such multiple-pollutant data sets measured over time at multiple sites within a region of interest are typical. Here, the modelling was carried out to provide the exposure for a study investigating the health effects of air pollution. Alternative objectives include the design problem of the positioning of a new monitoring site, or for regulatory purposes to determine whether environmental standards are being met. In general, analyses are hampered by missing data due, for example, to a particular pollutant not being measured at a site, a monitor being inactive by design (e.g. a 6-day monitoring schedule) or because of an unreliable or faulty monitor. Data of this type are modelled here within a dynamic linear modelling framework, in which the dependences across time, space and pollutants are exploited. Throughout the approach is Bayesian, with implementation via Markov chain Monte Carlo sampling.     

分形理论在计算机辅助图案造型中的应用研究

本文简单介绍了分形理论的概念和特征，着重阐述了分形理论在图案艺术设计方面的应用和方法。研究设计了计算机辅助图案艺术设计系统的功能和构成。     

Discrete time modelling of disease incidence time series by using Markov chain Monte Carlo methods

Summary.  A stochastic discrete time version of the susceptible–infected–recovered model for infectious diseases is developed. Disease is transmitted within and between communities when infected and susceptible individuals interact. Markov chain Monte Carlo methods are used to make inference about these unobserved populations and the unknown parameters of interest. The algorithm is designed specifically for modelling time series of reported measles cases although it can be adapted for other infectious diseases with permanent immunity. The application to observed measles incidence series motivates extensions to incorporate age structure as well as spatial epidemic coupling between communities.     

ELICITING A DIRECTED ACYCLIC GRAPH FOR A MULTIVARIATE TIME SERIES OF VEHICLE COUNTS IN A TRAFFIC NETWORK

The problem of modelling multivariate time series of vehicle counts in traffic networks is considered. It is proposed to use a model called the linear multiregression dynamic model (LMDM). The LMDM is a multivariate Bayesian dynamic model which uses any conditional independence and causal structure across the time series to break down the complex multivariate model into simpler univariate dynamic linear models. The conditional independence and causal structure in the time series can be represented by a directed acyclic graph (DAG). The DAG not only gives a useful pictorial representation of the multivariate structure, but it is also used to build the LMDM. Therefore, eliciting a DAG which gives a realistic representation of the series is a crucial part of the modelling process. A DAG is elicited for the multivariate time series of hourly vehicle counts at the junction of three major roads in the UK. A flow diagram is introduced to give a pictorial representation of the possible vehicle routes through the network. It is shown how this flow diagram, together with a map of the network, can suggest a DAG for the time series suitable for use with an LMDM.     

中外合资企业创新体系应纳入中国国家创新体系——将建设学习型国家作为建设创新型国家的前提

当前，中外合资企业的创新体系已经或可能对中国建设创新型国家发挥一定的作用，这表现在现代化的先进的生产体系与制造平台的模式输入、部分先进的核心技术的引进与共同研发的新的核心技术的产生、作为创新的基础的知识的输入、创新型人才的培养、供应链管理和配套体系的形成等方面。要进一步充分发挥中外合资企业对于中国建设创新型国家的积极作用，就应把中外合资企业的创新纳入中国国家创新体系，建立“所有制中性”的鼓励创新的政策体系。     

Improved Monte Carlo inference for models with additive error

Some statistical models defined in terms of a generating stochastic mechanism have intractable distribution theory, which renders parameter estimation difficult. However, a Monte Carlo estimate of the log-likelihood surface for such a model can be obtained via computation of nonparametric density estimates from simulated realizations of the model. Unfortunately, the bias inherent in density estimation can cause bias in the resulting log-likelihood estimate that alters the location of its maximizer. In this paper a methodology for radically reducing this bias is developed for models with an additive error component. An illustrative example involving a stochastic model of molecular fragmentation and measurement is given.     

Pathways between education and health: a causal modelling approach

Summary.  The association of poor education and poor health has been consistently observed in many studies and in various countries. Thus far, studies examining the mechanisms underlying this association have looked at only a limited set of potential pathways. This study simultaneously examines six distinctive pathways, which have been hypothesized to link education and health and found support from previous studies. A causal analysis of education and health was performed using structural equation models. Data were used from six phases of the National Child Development Study, which is based on following up an initial sample of 17416 children who were born in 1958. The association between education and health appears to be explained by a combination of mechanisms: adolescent health and adult health behaviours for men and women, adult social class among men and parental social class among women. We conclude that improvements in population educational attainment may not automatically lead to improvements in population health, and that health policies for improving health and reducing health inequalities need to target specific causal pathways.     

Joint impact of multiple observations on a subset of variables in multiple linear regression

In multiple linear regression analysis, each observation affects the fitted regression equation differently and has varying influences on the regression coefficients of the different variables. Chatterjee & Hadi (1988) have proposed some measures such as DSSE_ij (Impact on Residual Sum of Squares of simultaneously omitting the ith observation and the jth variable), F_j (Partial F-test for the jth variable) and F_j(i) (Partial F-test for the jth variable omitting the ith observation) to show the joint impact and the interrelationship that exists among a variable and an observation. In this paper we have proposed more extended form of those measures DSSE_IJ, F_J and F_J(I) to deal with the interrelationships that exist among the multiple observations and a subset of variables by monitoring the effects of the simultaneous omission of multiple variables and multiple observations.     

新时代中华优秀传统文化进教材的理性审思

中华优秀传统文化是中华民族的精神命脉。推动中华优秀传统文化融入教材,对于建设培根铸魂、启智增慧的新时代中国特色高质量教材体系,培养具有高度文化自信的社会主义建设者与接班人具有重要意义。中华传统文化教材建设百年来经历了从“沉寂”到“复兴”的曲折发展历程,反映出中华优秀传统文化顽强的生命力。在中国特色社会主义新时代,中华优秀传统文化“进教材”既是一种注重文化传承与精神引领的知识建构,也是一种凝聚文化教育合力的协同发展。新时代中华优秀传统文化教材建设,应以习近平新时代中国特色社会主义思想为指导,坚持创造性转化与创新性发展的基本方向,探索教材基于新时代语境的现代化诠释、基于全球化语境的本土化编写的发展向度,塑造中华民族优秀文化形象,开发数字教材资源,让中华优秀传统文化渗透、融入教材。新时代中华优秀传统文化教材建设也应强化规范意识,积极规避“人文关怀式微”的价值危机、“学科视野窄化”的认识误区、“教材泛德育化”的理念偏差以及“教育逻辑缺失”的路向偏移等失范问题,增强责任之心,勇于担当作为,落实立德树人根本任务,在固本与创新中肩负起推动中华优秀传统文化传承和发展的历史使命。