外语能力与科学研究的密切联系——周立伟院士访谈

近日对我国著名电子光学和光电子成像专家周立伟院士进行了访谈。访谈中，周院士首先分享了自己学习英语和俄语的经历，强调了自主学习能力的重要性；其次，周院士详细论述了外语教学，尤其是英语教学的必要性，指出英语能力与科学研究紧密相关，英语教学不可或缺；之后周院士分析了研究生在英语学习和科学研究方面存在的问题，并讨论了大学中开设人文课程的迫切性；最后，周院士对上理工师生提出了建议与期望。     

Improved Transferability of Data‐Driven Damage Models Through Sample Selection Bias Correction

Damage models for natural hazards are used for decision making on reducing and transferring risk. The damage estimates from these models depend on many variables and their complex sometimes nonlinear relationships with the damage. In recent years, data‐driven modeling techniques have been used to capture those relationships. The available data to build such models are often limited. Therefore, in practice it is usually necessary to transfer models to a different context. In this article, we show that this implies the samples used to build the model are often not fully representative for the situation where they need to be applied on, which leads to a “sample selection bias.” In this article, we enhance data‐driven damage models by applying methods, not previously applied to damage modeling, to correct for this bias before the machine learning (ML) models are trained. We demonstrate this with case studies on flooding in Europe, and typhoon wind damage in the Philippines. Two sample selection bias correction methods from the ML literature are applied and one of these methods is also adjusted to our problem. These three methods are combined with stochastic generation of synthetic damage data. We demonstrate that for both case studies, the sample selection bias correction techniques reduce model errors, especially for the mean bias error this reduction can be larger than 30%. The novel combination with stochastic data generation seems to enhance these techniques. This shows that sample selection bias correction methods are beneficial for damage model transfer.     

Consolidation and fragmentation in environmental scanning: A review and research agenda

Environmental scanning is a broadly defined concept, having first received attention from scholars in the late 1960s. Over the years a number of similar and overlapping constructs have emerged in management literature. The aim of this study, via a systematic review and thematic analysis of relevant empirical research, is to consolidate foundation environmental scanning knowledge, demonstrate how scanning research has developed and fragmented over time, and propose an agenda for future research. The first contribution of our review is a new typology of environmental scanning research made up of five discrete research views, which provides a more comprehensive and contemporary overview of the field than previous studies. The second is a proposed agenda for future research that explicitly acknowledges the role of technology, an area that is presently underdeveloped in foundation scanning literature. The third contribution is to signpost future directions for research on scanning and organisational performance using a number of theoretical perspectives. The overall outcome of our review is to move scanning research on from increasingly incremental contributions concerned with context to a place where the changing role of technology and the mechanisms through which environmental scanning contributes to competitive advantage can be more thoroughly understood.     

Checking validity of monotone domain mean estimators

Estimates of population characteristics such as domain means are often expected to follow monotonicity assumptions. Recently, a method to adaptively pool neighbouring domains was proposed, which ensures that the resulting domain mean estimates follow monotone constraints. The method leads to asymptotically valid estimation and inference, and can lead to substantial improvements in efficiency, in comparison with unconstrained domain estimators. However, assuming incorrect shape constraints may lead to biased estimators. Here, we develop the Cone Information Criterion for Survey Data as a diagnostic method to measure monotonicity departures on population domain means. We show that the criterion leads to a consistent methodology that makes an asymptotically correct decision choosing between unconstrained and constrained domain mean estimators. The Canadian Journal of Statistics 47: 315–331; 2019 © 2019 Statistical Society of Canada     

美国中小学的体验式学习及启示

体验式学习的内涵随着时代的发展而逐渐丰富和深化，但无论其如何演变，直接经验和反思始终是体验式学习这一概念的内核。体验式学习理念渗透于美国教育文化之中。具体表现在：小学阶段的教育以学生的真实感知为基础，注重为学生提供真实体验的机会和激发学生的学习兴趣；中学尤其是高中阶段的教育以学生的真实体验为基础，注重为学生提供在新情境中检验所学知识的机会，注重学生知识、技能的内化吸收。美国中小学体验式学习的实施经验可为我国基础教育课程改革提供如下启示：（1）进一步树立和推广体验式学习理念；（2）创设学生进行真实体验的教学环境；（3）注重实施基于学生体验式学习的表现性评价。     

Generational conflict and provisions for the elderly in Hong Kong: The relevance of position‐based interest and values

Respect for the elderly and hence the associated rights support a generational contract. Nevertheless, the case of the recent debate on the universal retirement scheme in Hong Kong has raised concerns about its strength. We identify relevant items from the sixth wave of the World Values Survey to explore the orientations of different generations toward others. The analysis shows differences between younger and older generations. Regression analyses show that values are not significant in explaining the differences, but various positions, including sex, marital status, and education, and perceptions of the elderly are relevant. Such differences across generations might weaken the generational contract and potentially engender conflicts as shown in the recent debate about the retirement scheme. We suggest short‐ and long‐term interest calculations, informed by their positions, play a more significant role in policy discussions and decisions, rather than simply appealing to values.     

A comparative study of confidence intervals to assess biosimilarity from analytical data

Assessment of analytical similarity of tier 1 quality attributes is based on a set of hypotheses that tests the mean difference of reference and test products against a margin adjusted for standard deviation of the reference product. Thus, proper assessment of the biosimilarity hypothesis requires statistical tests that account for the uncertainty associated with the estimations of the mean differences and the standard deviation of the reference product. Recently, a linear reformulation of the biosimilarity hypothesis has been proposed, which facilitates development and implementation of statistical tests. These statistical tests account for the uncertainty in the estimation process of all the unknown parameters. In this paper, we survey methods for constructing confidence intervals for testing the linearized reformulation of the biosimilarity hypothesis and also compare the performance of the methods. We discuss test procedures using confidence intervals to make possible comparison among recently developed methods as well as other previously developed methods that have not been applied for demonstrating analytical similarity. A computer simulation study was conducted to compare the performance of the methods based on the ability to maintain the test size and power, as well as computational complexity. We demonstrate the methods using two example applications. At the end, we make recommendations concerning the use of the methods.     

Flood Risk Perceptions and Insurance Choice: Do Decisions in the Floodplain Reflect Overoptimism?

In the presence of rare disasters, risk perceptions may not always align with actual risks. These perceptions can nevertheless influence an individual's willingness to mitigate risks through activities such as purchasing flood insurance. In a survey of Maryland floodplain residents, we find that stated risk perceptions predict voluntary flood insurance take‐up, while perceptions themselves varied widely among surveyed residents, owing in large part to differences in past flood experience. We use a formal test for overoptimism in risk perceptions and find that, on aggregate, floodplain residents are overly optimistic about flood risks.     

The Use of Telematics Devices to Improve Automobile Insurance Rates

Most automobile insurance databases contain a large number of policyholders with zero claims. This high frequency of zeros may reflect the fact that some insureds make little use of their vehicle, or that they do not wish to make a claim for small accidents in order to avoid an increase in their premium, but it might also be because of good driving. We analyze information on exposure to risk and driving habits using telematics data from a pay‐as‐you‐drive sample of insureds. We include distance traveled per year as part of an offset in a zero‐inflated Poisson model to predict the excess of zeros. We show the existence of a learning effect for large values of distance traveled, so that longer driving should result in higher premiums, but there should be a discount for drivers who accumulate longer distances over time due to the increased proportion of zero claims. We confirm that speed limit violations and driving in urban areas increase the expected number of accident claims. We discuss how telematics information can be used to design better insurance and to improve traffic safety.     

A user’s guide to Lisbon: mobilities,spatial apprenticeship and migrant urban integration*

This paper engages with the ‘mobility turn’ scholarship in order to provide tools for the study of migrants’ integration to urban space. The analysis of urban mobilities draws attention to the practical know-how that underlies mobility practices. I argue that migrants’ urban apprenticeship – that is, the ways migrants learn (to use) city spaces – shape their access to urban resources and their participation in urban life. Based on fieldwork conducted in Lisbon, Portugal, I explore how migrants’ urban knowledges play out in their everyday practices and resonate with broader concerns over migrant integration.