Toward an Application Guide for Safety Integrity Level Allocation in Railway Systems

The work in the article presents the development of an application guide based on feedback and comments stemming from various railway actors on their practices of SIL allocation to railway safety‐related functions. The initial generic methodology for SIL allocation has been updated to be applied to railway rolling stock safety‐related functions in order to solve the SIL concept application issues. Various actors dealing with railway SIL allocation problems are the intended target of the methodology; its principles will be summarized in this article with a focus on modifications and precisions made in order to establish a practical guide for railway safety authorities. The methodology is based on the flowchart formalism used in CSM (common safety method) European regulation. It starts with the use of quantitative safety requirements, particularly tolerable hazard rates (THR). THR apportioning rules are applied. On the one hand, the rules are related to classical logical combinations of safety‐related functions preventing hazard occurrence. On the other hand, to take into account technical conditions (last safety weak link, functional dependencies, technological complexity, etc.), specific rules implicitly used in existing practices are defined for readjusting some THR values. SIL allocation process based on apportioned and validated THR values is finally illustrated through the example of “emergency brake” subsystems. Some specific SIL allocation rules are also defined and illustrated.     

Interview schedule development for a Sequential explanatory mixed method design: complementary-alternative medicine (CAM) study among Indonesian psychologists

Sequential explanatory mixed method design is the most frequently applied in both health and social sciences literature. It is denoted by ‘QUAN → qual’ which represents the quantitative study occurs first and has greater weight in addressing the study’s aims, and the qualitative study follows to explain quantitative results. Despite the extensive use of sequential explanatory design, there are limited references to this design. Therefore, this methodological paper attempts to fill the gap by providing an illustration in developing a sequential explanatory interview schedule based on complementary-alternative medicine (CAM) study among clinical psychologists in Indonesia. The most important step to develop sequential explanatory interview schedule was the construction of aspects and questions that were immensely grounded on the most notable quantitative results. In this study, eight aspects of interview schedule were constructed after analyses of the nationwide survey. The interview schedule then piloted among participants with fairly similar characteristics to the participants in the main interviews. This process enhanced the quality of questions through feedback from participants and improved the interviewer’s skills through familiarization with questions. It is expected that this reflection report could be adopted as a practical guideline in developing interview schedule for sequential explanatory mixed method design, particularly in the field of psychology.     

Conditional design of the EWMA median chart with estimated parameters

The exponentially weighted moving average (EWMA) chart is often designed assuming the process parameters are known. In practice, the parameters are rarely known and need to be estimated from Phase I samples. Different Phase I samples are used when practitioners construct their own control chart's limits, which leads to the “Phase I between-practitioners” variability in the in-control average run length (ARL) of control charts. The standard deviation of the ARL (SDARL) is a good alternative to quantify this variability in control charts. Based on the SDARL metric, the performance of the EWMA median chart with estimated parameters is investigated in this paper. Some recommendations are given based on the SDARL metric. The results show that the EWMA median chart requires a much larger amount of Phase I data in order to reduce the variation in the in-control ARL up to a reasonable level. Due to the limitation of the amount of the Phase I data, the suggested EWMA median chart is designed with the bootstrap method which provides a good balance between the in-control and out-of-control ARL values.     

Evaluating and Visualizing the Economic Impact of Commercial Districts Due to an Electric Power Network Disruption

Critical infrastructure networks enable social behavior, economic productivity, and the way of life of communities. Disruptions to these cyber–physical–social networks highlight their importance. Recent disruptions caused by natural phenomena, including Hurricanes Harvey and Irma in 2017, have particularly demonstrated the importance of functioning electric power networks. Assessing the economic impact (EI) of electricity outages after a service disruption is a challenging task, particularly when interruption costs vary by the type of electric power use (e.g., residential, commercial, industrial). In contrast with most of the literature, this work proposes an approach to spatially evaluate EIs of disruptions to particular components of the electric power network, thus enabling resilience‐based preparedness planning from economic and community perspectives. Our contribution is a mix‐method approach that combines EI evaluation, component importance analysis, and GIS visualization for decision making. We integrate geographic information systems and an economic evaluation of sporadic electric power outages to provide a tool to assist with prioritizing restoration of power in commercial areas that have the largest impact. By making use of public data describing commercial market value, gross domestic product, and electric area distribution, this article proposes a method to evaluate the EI experienced by commercial districts. A geospatial visualization is presented to observe and compare the areas that are more vulnerable in terms of EI based on the areas covered by each distribution substation. Additionally, a heat map is developed to observe the behavior of disrupted substations to determine the important component exhibiting the highest EI. The proposed resilience analytics approach is applied to analyze outages of substations in the boroughs of New York City.     

基于理想解和灰关联度的动态评价方法及其应用研究

为了对多个多属性（指标）待评价对象（方案）在多个时间点的发展状态和该时间段内的总体发展水平进行比较分析，根据理想解法和灰关联度法优缺点，提出基于理想解和灰关联度的动态评价方法。该方法基于三维数据，将欧氏距离和灰色关联度相结合，提出一种新贴近度，同时反映了位置关系和数据曲线的相似性差异，兼顾评价指标值差异程度和增长程度。最后将该方法应用于"十二五"期间省域循环经济生态效益评价，通过实例验证该方法实际应用上的有效性。     

Graduating Out of Poverty Across Generations: Unpacking Children’s Well‐being Trajectories in Burundi

Graduation model interventions represent a new wave of anti‐poverty programming that seeks to offer a sustainable pathway out of poverty. An expanding evidence base points towards positive economic outcomes at household level but little is known about impacts on child well‐being. This paper investigates children’s well‐being in Burundi during and after participation in a graduation model programme using a longitudinal mixed‐methods approach. The programme is found to improve child well‐being, particularly in relation to housing, food security and education. Covariate shocks undermine sustainability of effects but greater knowledge, experience and prioritisation of children’s needs contribute to harnessing improved outcomes.     

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.     

将生命还给社会:传记法作为一种总体叙事方式

在田野民族志和历史编纂学中，传记法是一种重要的叙事方式。本文从分析林耀华的作品入手，将其置于20世纪20年代以来的社会学和人类学思想脉络中，并在此基础上探讨传记法在中国历史和社会研究中的潜力与可能性。本文将谱系法、个人生命史和社会生命论归纳为“传记法三角”。在（扩展）谱系法和社会结构论的基础上，生命传记法可以呈现一个或多个人的生命历史，作为大历史中的片段。不过，现象学路径有其自身的限度，不能离开对中央政权本身和总体结构的考察。在“时势”和“社会结构”的变迁过程中呈现生命传记，才不会只是个体的故事，而有希望成为一种对中国“总体”社会生活的有力叙事方式。     

基于犹豫直觉模糊语言集均值-标准差偏好距离的多属性决策研究

在犹豫直觉模糊语言集和语言尺度函数的基础上定义了均值-标准差偏好的Hamming距离，并提出了基于犹豫直觉模糊语言集距离TOPSIS和TODIM的多属性决策方法，进一步利用这两种方法对实例问题建筑商的招标方案进行排序，并讨论了偏好参数对排序结果的灵敏度分析。为验证上述方法的有效性，与已有方法对同一实例的排序结果进行了比较分析。     

基于最新统计分类标准的数字经济发展水平测度

随着信息技术的发展,数字经济已经成为经济增长的"新引擎"。但由于缺乏权威的产业统计分类标准,学者们一直面临"数字经济研究缺乏数字依据"的尴尬境地。文章基于国家统计局公布并实施的《数字经济及其核心产业统计分类(2021)》中的分类标准,对各省份统计年鉴的数据进行重新整理,利用熵权法构建数字经济发展指数,测度了我国30个省份的数字经济发展水平,分析了各省份数字经济发展的差异以及时空特征。研究发现,2009—2019年我国数字经济产业发展迅猛,各项子产业都取得了长足的进步。相比较而言,数字要素驱动业发展速度略低于其他三个子产业;数字经济发展存在着明显的区域不平衡。东中部地区的数字经济发展状况明显优于西部地区,南方优于北方,而且区域不平衡有持续扩大趋势。