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.     

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。     

学习分析视域下S-ISAL在大学英语混合式教学中的构建与评估

学习分析技术在教育教学中的应用，其根本目的是为了构建新的教学法，更新教学与管理的方式。针对高校大学英语线上、线下混合教学无法有机融合的现状，S-ISAL（Space-based Information search and Analysis Learning）应运而生，它是基于网络学习空间的信息搜集与分析的教学模式，将学习分析技术引入大学英语混合式课程中。探究该教学模式在大学英语教学中的适切性和实效性是文章的研究重点，目的是为了实现大学英语线上、线下教学优势互补，为大学生在线英语学习提供更具个性化的学习内容和路径，并提升大学生自适应学习能力和在线学习绩效。     

Validation of the Australian Midwifery Standards Assessment Tool (AMSAT): A tool to assess midwifery competence

Background

There is no current validated clinical assessment tool to measure the attainment of midwifery student competence in the midwifery practice setting. The lack of a valid assessment tool has led to a proliferation of tools and inconsistency in assessment of, and feedback on student learning.

Decision‐making under uncertainty in child protection: Creating a just and learning culture

The argument is made for having a positive error culture in child protection to improve decision‐making and risk management. This requires organizations to accept that mistakes are likely and to treat them as opportunities for learning and improving. In contrast, in many organizations, a punitive reaction to errors leads to workers hiding them and developing a defensive approach to their practice with children and families. The safety management literature has shown how human error is generally not simply due to a “bad apple” but made more or less likely by the work context that helps or hinders good performance. Improving safety requires learning about the weaknesses in the organization that contribute to poor performance. To create a learning culture, people need to feel that when they talk about mistakes or weak practice, there will be a constructive response from their organization. One aspect of reducing the blame culture is to develop a shared understanding of how practice will be judged and how those appraising practice will avoid the hindsight bias. To facilitate a positive error culture, a set of risk principles are presented that offer a set of criteria by which practice should be appraised.     

汇率货币模型的非线性协整关系检验——基于深度GRU神经网络

本文采用深度门控循环单元（GRU）神经网络探讨三种汇率货币模型（弹性价格、前瞻性和实际利率差模型）的非线性协整关系。GRU技术在深度学习中具有智能记忆、自主学习和强逼近能力等优点。为此，本文运用该技术对6组典型浮动汇率制国别数据进行了非线性Johansen协整检验。结果表明，汇率与宏观经济基本面之间存在非线性协整关系，从而说明了货币模型在非线性条件下的有效性，以及先进的深度学习工具在检验经济理论中的优势。     

源自文学典故的英语词汇

单词在英语学习中起着建筑材料的作用。很多人在阅读英美书刊或文章时常常被一些寓意深刻的词汇难住,即使查过字典后往往也只知其然而不知其所以然。本文旨在探讨一部分出自文学典故的英语词汇的来龙去脉及其用法,从而使学习者加深印象,记得牢固,用得恰当。除此之外,本文希望有助于提高学习者的兴趣,开阔视野,了解英美文化,进而领略英语原文的真谛。     

The University: An Agent of Social Change?

Can universities be agents of progressive social change? How would we know if a university was acting as an agent of social change? Drawing on four case studies, I raise a number of questions to problematize our understanding of the university as an agent of social change. I outline a number of contributing factors that appear to explain successful cases. I conclude by arguing the relevancy of these cases for larger, and more traditional, sociological projects.