考虑项目关联关系的R&D网络风险传播建模与仿真

考虑同一企业内不同项目间关联关系的情况下，基于研发项目的数量将研发网络分为不同子网络。借鉴SIS模型构建了R&D网络风险传播动力学模型，并对该模型进行了数理解析与仿真分析。结果表明：R&D网络风险传播阈值是由不同子网络的拓扑结构以及企业内不同项目间的关联程度共同决定的；考虑项目关联的研发网络风险传播阈值小于不考虑关联关系的研发网络风险传播阈值；项目间关联关系的企业个数及项目间的关联程度对风险在不同子网络上的传播速度与传播范围均具有影响。该研究成果对于提高研发网络抗风险能力具有重要意义。     

提升中小学生阅读兴趣的实证研究——基于MIMIC模型的教学效能分析

提升学生的阅读素养是当前我国阅读课程教学改革的重要目标之一。本研究首次尝试将群文阅读这种新兴的阅读教学方式与传统的单本阅读教学方式进行对比研究，主要从提升学生阅读兴趣的效能方面进行分析与探讨。实验涉及我国中西部5个省市、6个区县共计1 231名中小学生，并使用MIMIC模型，在有效控制测量误差的基础上，对实证数据进行了量化建模与分析，通过分析发现，群文阅读教学对激发学生阅读的“情境兴趣”有更加显著的作用，具体表现为对学生阅读注意力、情感体验、探索意愿、价值感知的影响更大，同时也验证了Knogler提出的“情境兴趣模型”在阅读教学领域的适用性，从而为进一步推进我国中小学阅读课程教学改革提供了科学的数据支撑。因此，为提升中小学生阅读素养，在阅读教学中引入群文阅读这一新兴的教学方式，具有重要的实践价值和现实意义。     

Providing a secure base for LGBTQ young people in foster care: The role of foster carers

The experiences and needs of lesbian, gay, bisexual, trans and queer/questioning (LGBTQ) young people in care have been overlooked in England, in both policy and research. This paper reports on findings from the first study of LGBTQ young people in care in England and focuses on the nature of foster carers' experiences and perspectives on caring for LGBTQ young people. Qualitative interviews regarding the fostering role in caring for LGBTQ young people were conducted with a sample of foster carers (n = 26) and analysed thematically. Foster carers described the importance of offering LGBTQ young people not only the nurturing relationships that all children in care need but also availability, sensitivity and acceptance to help young people manage stigma and other challenges associated with minority sexual orientation and gender identity. The Secure Base caregiving model provided a framework for analysing the different dimensions of these relationships. Understanding caregiving roles and relationships for LGBTQ young people in care has important implications for recruiting, training, matching and supporting foster carers to care for LGBTQ young people effectively.     

Multivariate Return Decomposition: Theory and Implications

In this paper, we propose a model based on multivariate decomposition of multiplicative – absolute values and signs – components of asset returns. In the m-variate case, the marginals for the m absolute values and the binary marginals for the m directions are linked through a 2m-dimensional copula. The approach is detailed in the case of a bivariate decomposition. We outline the construction of the likelihood function and the computation of different conditional measures. The finite-sample properties of the maximum likelihood estimator are assessed by simulation. An application to predicting bond returns illustrates the usefulness of the proposed method.     

Separation and Post‐Separation Parenting within Lesbian and Gay Co‐parenting (Guild Parented) Families

Gay men and lesbian women have a long history of jointly creating families and co‐parenting their children together. This qualitative study aims to explore the experiences of separation and post‐separation parenting within same‐sex parented families. This involved semi‐structured in‐depth interviews with 22 separated same‐sex parents in Adelaide, Melbourne, Sydney, Brisbane, and regional Victoria. An adaptive theory approach was used for the collection and analysis of the data. The paper explores data from a cohort of six participants who came from three different multi‐parent families who had experienced a separation – either their own, or that of other parents in their parenting group. The term ‘co‐parenting families’ was found to be confusing due to the different connotations within separation/divorce and same‐sex parent literature. Consequently, the term ‘guild parented families’ was created to describe these families. Participants from these multi‐parent families had very different experiences of family formation and separation compared to others within the wider separated same‐sex parent study. Separation of one or more of the parent couples within these families complicated their original plans and kinship ideals. Each of the families resolved this differently in their post‐separation arrangements. After separation, whole family narratives and/or the role of individual parents, were either questioned or revised as a way of resolving the complexity of their new kinship situation. Following separation, parents often relied on Western kinship norms that privilege biological kinship and the dual‐parent family to construct their post‐separation kinship arrangements. More awareness of families that begin with more than two parents is needed within separation research and amongst separation services and service providers.     

Perceived Inflation Persistence

This article constructs and estimates a measure called perceived inflation persistence that can be used to determine if professional forecasters’ inflation forecasts indicate there has been a change in inflation persistence. This measure is built via the implied autocorrelation function that follows from the estimates obtained using a forecaster-specific state-space model. Findings indicate that U.S. perceived inflation persistence has changed since the mid-1990s with more consensus among forecasters at lower levels of persistence. When compared to the autocorrelation function for actual inflation, forecasters typically react less to shocks to inflation than the actual inflation data would suggest.     

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。     

Smoothed bootstrap bandwidth selection for nonparametric hazard rate estimation

A smoothed bootstrap method is presented for the purpose of bandwidth selection in nonparametric hazard rate estimation for iid data. In this context, two new bootstrap bandwidth selectors are established based on the exact expression of the bootstrap version of the mean integrated squared error of some approximations of the kernel hazard rate estimator. This is very useful since Monte Carlo approximation is no longer needed for the implementation of the two bootstrap selectors. A simulation study is carried out in order to show the empirical performance of the new bootstrap bandwidths and to compare them with other existing selectors. The methods are illustrated by applying them to a diabetes data set.     

Estimation of the smallest scale parameter of two-parameter exponential distributions

Improved point and interval estimation of the smallest scale parameter of n independent populations following two-parameter exponential distributions are studied. The model is formulated in such a way that allows for treating the estimation of the smallest scale parameter as a problem of estimating an unrestricted scale parameter in the presence of a nuisance parameter. The classes of improved point and interval estimators are enriched with Stein-type, Brewster and Zidek-type, Maruyama-type and Strawderman-type improved estimators under both quadratic and entropy losses, whereas using as a criterion the coverage probability, with Stein-type, Brewster and Zidek-type, and Maruyama-type improved intervals. The sampling framework considered incorporates important life-testing schemes such as i.i.d. sampling, type-II censoring, progressive type-II censoring, adaptive progressive type-II censoring, and record values.     

A reflected feature space for CART

We present an algorithm for learning oblique decision trees, called HHCART(G). Our decision tree combines learning concepts from two classification trees, HHCART and Geometric Decision Tree (GDT). HHCART(G) is a simplified HHCART algorithm that uses linear structure in the training examples, captured by a modified GDT angle bisector, to define splitting directions. At each node, we reflect the training examples with respect to the modified angle bisector to align this linear structure with the coordinate axes. Searching axis parallel splits in this reflected feature space provides an efficient and effective way of finding oblique splits in the original feature space. Our method is much simpler than HHCART because it only considers one reflected feature space for node splitting. HHCART considers multiple reflected feature spaces for node splitting making it more computationally intensive to build. Experimental results show that HHCART(G) is an effective classifier, producing compact trees with similar or better results than several other decision trees, including GDT and HHCART trees.