Parental smoking and children's respiratory health: independent effects of prenatal and postnatal exposure

Objectives

Adverse effects have been reported of prenatal and/or postnatal passive exposure to smoking on children''s health. Uncertainties remain about the relative importance of smoking at different periods in the child''s life. We investigate this in a pooled analysis, on 53 879 children from 12 cross‐sectional studies—components of the PATY study (Pollution And The Young).

Methods

Effects were estimated, within each study, of three exposures: mother smoked during pregnancy, parental smoking in the first two years, current parental smoking. Outcomes were: wheeze, asthma, “woken by wheeze”, bronchitis, nocturnal cough, morning cough, “sensitivity to inhaled allergens” and hay fever. Logistic regressions were used, controlling for individual risk factors and study area. Heterogeneity between study‐specific results, and mean effects (allowing for heterogeneity) were estimated using meta‐analytical tools.

Results

There was strong evidence linking parental smoking to wheeze, asthma, bronchitis and nocturnal cough, with mean odds ratios all around 1.15, with independent effects of prenatal and postnatal exposures for most associations.

Conclusions

Adverse effects of both pre‐ and postnatal parental smoking on children''s respiratory health were confirmed. Asthma was most strongly associated with maternal smoking during pregnancy, but postnatal exposure showed independent associations with a range of other respiratory symptoms. All tobacco smoke exposure has serious consequences for children''s respiratory health and needs to be reduced urgently.     

Schlafhorst捻接技术的模块化

通过Autoconer338产品系列，Schlafhorst（赐来福）公司向纺织行业提供了能够高效率卷绕各种规格纱线卷装的成熟、先进技术。而灵活、创新的模块技术为纱线自动络筒工艺提高经济效益奠定了基础。络筒机的主要工作之一是当纱线出现断头，或换纱管，或清纱之后，将两个纱头接在一起．形成一个几乎与正常纱线无区别的接头。这是Schlafhorst公司研发工作的重点之一，因此．该公司一直致力于对纱线捻接工艺的深入研究。     

Visual Analysis of Flow Features Using Information Theory

Unsteady scientific data is one of the top challenges in visualization, because a huge amount of information must be displayed. ϵ-machines are an information-theoretic concept; they compress the dynamics in the data set to a finite-state machine, in which nodes represent local flow patterns and edges represent transitions between them. Several enhancements to the fundamental ϵ-machine representation can help users identify interesting time intervals, analyze the evolution of unusual local dynamics, and track features over time. Automatically abstracting information from the original data is a first step toward knowledge-assisted visualization. Successive findings from analysis can help provide subsequent users with knowledge gained in earlier research, resulting in a knowledge-assisted system for the analysis of unsteady-flow features based on information theory. This article is part of a special issue on knowledge-assisted visualization.     

Employing industrial standards in software engineering for W7X

The stellarator W7X is a large complex experiment designed for continuous operation and planned to be operated for about 20 years. Software support is highly demanded for experiment preparation, operation and data analysis which in turn induces serious non-functional requirements on the software quality like, e.g.:

• high availability, stability, maintainability vs.

• high flexibility concerning change of functionality, technology, personnel

• high versatility concerning the scale of system size and performance

These challenges are best met by exploiting industrial experience in quality management and assurance (QM/QA), e.g. focusing on top-down development methods, developing an integral functional system model, using UML as a diagramming standard, building vertical prototypes, support for distributed development, etc., which have been used for W7X, however on an ‘as necessary’ basis. Proceeding in this manner gave significant results for control, data acquisition, corresponding database-structures and user applications over many years.As soon as production systems started using the software in the labs or on a prototype the development activity demanded to be organized in a more rigorous process mainly to provide stable operation conditions. Thus a process improvement activity was started for stepwise introduction of quality assuring processes with tool support taking standards like CMMI, ISO-15504 (SPICE) as a guideline. Experiences obtained so far will be reported.We conclude software engineering and quality assurance has to be an integral part of systems engineering right from the beginning of projects and be organized according to industrial standards to be prepared for the challenges of nuclear fusion research.     

Fabrication and observation of a standard sample for near-field optical microscopy

We fabricated a standard sample for a near-field optical microscope using scanning probe lithography. The sample contains a wedged pattern, which allows the measurement of various sizes within one image. The optical resolution of our near-field optical microscope has been evaluated as 40 nm, which was obtained by measuring the narrowest separable gap width of the wedged pattern. Thus a standard sample containing the wedged pattern enables clear evaluation of the resolution.     

Brushing of attribute clouds for the visualization of multivariate data

The visualization and exploration of multivariate data is still a challenging task. Methods either try to visualize all variables simultaneously at each position using glyph-based approaches or use linked views for the interaction between attribute space and physical domain such as brushing of scatterplots. Most visualizations of the attribute space are either difficult to understand or suffer from visual clutter. We propose a transformation of the high-dimensional data in attribute space to 2D that results in a point cloud, called attribute cloud, such that points with similar multivariate attributes are located close to each other. The transformation is based on ideas from multivariate density estimation and manifold learning. The resulting attribute cloud is an easy to understand visualization of multivariate data in two dimensions. We explain several techniques to incorporate additional information into the attribute cloud, that help the user get a better understanding of multivariate data. Using different examples from fluid dynamics and climate simulation, we show how brushing can be used to explore the attribute cloud and find interesting structures in physical space.