Inference for Weibull distribution under adaptive Type-I progressive hybrid censored competing risks data

In this paper, a competing risks model is considered under adaptive type-I progressive hybrid censoring scheme (AT-I PHCS). The lifetimes of the latent failure times have Weibull distributions with the same shape parameter. We investigate the maximum likelihood estimation of the parameters. Bayes estimates of the parameters are obtained based on squared error and LINEX loss functions under the assumption of independent gamma priors. We propose to apply Markov Chain Monte Carlo (MCMC) techniques to carry out a Bayesian estimation procedure and in turn calculate the credible intervals. To evaluate the performance of the estimators, a simulation study is carried out.     

Response‐adaptive designs for binary responses: How to offer patient benefit while being robust to time trends?

Response‐adaptive randomisation (RAR) can considerably improve the chances of a successful treatment outcome for patients in a clinical trial by skewing the allocation probability towards better performing treatments as data accumulates. There is considerable interest in using RAR designs in drug development for rare diseases, where traditional designs are not either feasible or ethically questionable. In this paper, we discuss and address a major criticism levelled at RAR: namely, type I error inflation due to an unknown time trend over the course of the trial. The most common cause of this phenomenon is changes in the characteristics of recruited patients—referred to as patient drift. This is a realistic concern for clinical trials in rare diseases due to their lengthly accrual rate. We compute the type I error inflation as a function of the time trend magnitude to determine in which contexts the problem is most exacerbated. We then assess the ability of different correction methods to preserve type I error in these contexts and their performance in terms of other operating characteristics, including patient benefit and power. We make recommendations as to which correction methods are most suitable in the rare disease context for several RAR rules, differentiating between the 2‐armed and the multi‐armed case. We further propose a RAR design for multi‐armed clinical trials, which is computationally efficient and robust to several time trends considered.     

The struggle for Via Bologna street market: crisis,racial denial and speaking back to power in Naples Italy

This paper is based on ethnographic research conducted with migrant and Italian street vendors in Naples, southern Italy, in 2012. It tells the story of Via Bologna market which was nearly closed down by the City Hall at the time. Naples is a city where issues of poverty and unemployment pre‐date and have been exacerbated by manifold narratives of crisis now unfolding across Europe regarding the economy, political legitimacy, security and migration. Street markets have always been an important and visible economic survival strategy for both Neapolitans and migrants there. This article shows how the Via Bologna street vendors appropriated and adapted discourses about crisis to form their own cosmopolitan social movement that halted the closure of the market. It argues that, in the age of globalized migration, the multilingual nature of such collective action is central to understanding social struggles that must be organized between marginalized groups of people divided by race, religion, politics and legal status. This, frequently ambiguous, transcultural solidarity speaks back against a mainstream post‐racial discourse – often articulated by the Neapolitan street vendors at the market – that would reduce the complexity of such collective action to questions of poverty and class struggle.     

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.     

An Agent‐Based Model for Pathogen Persistence and Cross‐Contamination Dynamics in a Food Facility

We used an agent‐based modeling (ABM) framework and developed a mathematical model to explain the complex dynamics of microbial persistence and spread within a food facility and to aid risk managers in identifying effective mitigation options. The model explicitly considered personal hygiene practices by food handlers as well as their activities and simulated a spatially explicit dynamic system representing complex interaction patterns among food handlers, facility environment, and foods. To demonstrate the utility of the model in a decision‐making context, we created a hypothetical case study and used it to compare different risk mitigation strategies for reducing contamination and spread of Listeria monocytogenes in a food facility. Model results indicated that areas with no direct contact with foods (e.g., loading dock and restroom) can serve as contamination niches and recontaminate areas that have direct contact with food products. Furthermore, food handlers’ behaviors, including, for example, hygiene and sanitation practices, can impact the persistence of microbial contamination in the facility environment and the spread of contamination to prepared foods. Using this case study, we also demonstrated benefits of an ABM framework for addressing food safety in a complex system in which emergent system‐level responses are predicted using a bottom‐up approach that observes individual agents (e.g., food handlers) and their behaviors. Our model can be applied to a wide variety of pathogens, food commodities, and activity patterns to evaluate efficacy of food‐safety management practices and quantify contamination reductions associated with proposed mitigation strategies in food facilities.     

Agent‐Based Recovery Model for Seismic Resilience Evaluation of Electrified Communities

In this article, an agent‐based framework to quantify the seismic resilience of an electric power supply system (EPSS) and the community it serves is presented. Within the framework, the loss and restoration of the EPSS power generation and delivery capacity and of the power demand from the served community are used to assess the electric power deficit during the damage absorption and recovery processes. Damage to the components of the EPSS and of the community‐built environment is evaluated using the seismic fragility functions. The restoration of the community electric power demand is evaluated using the seismic recovery functions. However, the postearthquake EPSS recovery process is modeled using an agent‐based model with two agents, the EPSS Operator and the Community Administrator. The resilience of the EPSS–community system is quantified using direct, EPSS‐related, societal, and community‐related indicators. Parametric studies are carried out to quantify the influence of different seismic hazard scenarios, agent characteristics, and power dispatch strategies on the EPSS–community seismic resilience. The use of the agent‐based modeling framework enabled a rational formulation of the postearthquake recovery phase and highlighted the interaction between the EPSS and the community in the recovery process not quantified in resilience models developed to date. Furthermore, it shows that the resilience of different community sectors can be enhanced by different power dispatch strategies. The proposed agent‐based EPSS–community system resilience quantification framework can be used to develop better community and infrastructure system risk governance policies.     

Smoking during pregnancy,stigma and secrets: Visual methods exploration in the UK

BackgroundMoral judgements are commonly directed towards mothers through reference to health behaviour in pregnancy, and working-class mothers are particularly subject to this moral gaze.AimTo gain an in-depth understanding of the health issues affecting 10 low income pregnant women from deprived areas of south Wales, UK.MethodsParticipants completed visual activities (timelines, collaging or thought bubbles and dyad sandboxing) prior to each interview. Participants’ visual representations were used in place of a topic guide, to direct the interview. Guided by feminist principles, 28 interviews were completed with 10 women. Data were analysed thematically.FindingsSmoking was discussed at length during interviews, and this paper focuses on this issue alone. Five of the participants had smoked during pregnancy. Negative reactions were directed towards pregnant women who smoked in public, resulting in maternal smoking being undertaken in private. Participants also reported awkward relationships with midwives and other health professionals, including receipt of public health advice in a judgemental tone.DiscussionSmoking during pregnancy is a particularly demonised and stigmatised activity. This stigma is not always related to the level of risk to the foetus, and instead can be seen as a moral judgement about women. We urgently need to move from individualised neo-liberal discourses about the failure of individual smokers, to a more socio-ecological view which avoids victim blaming.ConclusionStigma from friends, family, strangers and health professionals may lead to hidden smoking. This is a barrier to women obtaining evidence based stop smoking support.     

The (non-)application of blockchain technology in the Greek shipping industry

The implementation of blockchain technology (BCT) is gaining traction in supply chain networks, revolutionising the operation of contemporary supply chains and reshaping the potential of business relationships. Empirical studies on blockchain adoption are scant because implementation across networks is in fairly early phase of development, yet evidence from empirical studies is highly desirable. This is one of the first studies of blockchain adoption in the Greek shipping industry, which has not so far been examined by the literature, in direct comparison to early adopters in other European countries such as Norway. The research examined eight Greek shipping companies using workshops with experienced supply chain personnel. Qualitative analysis identified the current position of these organisations in terms of blockchain adoption, by considering possible benefits and inhibitors to implementation. Despite benefits of automated processes and reduced paperwork as a result of smart contracts, findings show a reluctance to adopt BCT. That is, enterprise resource planning (ERP) transformations have left organisations fatigued and disinclined towards further systems development and resistant to subsequent change. Also, the exposure of shared information in the shipping nexus is considered to cause a threat to competitive survival.     

Changes in the Factors Influencing Public Acceptance of Nuclear Power Generation in Japan Since the 2011 Fukushima Daiichi Nuclear Disaster

Public support for nuclear power generation has decreased in Japan since the Fukushima Daiichi nuclear accident in March 2011. This study examines how the factors influencing public acceptance of nuclear power changed after this event. The influence factors examined are perceived benefit, perceived risk, trust in the managing bodies, and pro‐environmental orientation (i.e., new ecological paradigm). This study is based on cross‐sectional data collected from two online nationwide surveys: one conducted in November 2009, before the nuclear accident, and the other in October 2011, after the accident. This study's target respondents were residents of Aomori, Miyagi, and Fukushima prefectures in the Tohoku region of Japan, as these areas were the epicenters of the Great East Japan Earthquake and the locations of nuclear power stations. After the accident, trust in the managing bodies was found to have a stronger influence on perceived risk, and pro‐environmental orientation was found to have a stronger influence on trust in the managing bodies; however, perceived benefit had a weaker positive influence on public acceptance. We also discuss the theoretical and practical implications of these findings.     

数字经济供给使用表:概念架构与编制实践研究

数字经济供给使用表是数字经济卫星账户的核心表式,具有统计协调和分析工具的双重作用,能够准确监测数字经济产业发展规模及传统产业与数字经济的融合程度。目前,国际上对数字经济供给使用表的研究尚处于初期探索阶段,还未有国家编制出基于实际数据的数字经济供给使用表,经济合作与发展组织(OECD)对数字经济供给使用表的理论框架进行了前瞻性探索,但系统的数字经济供给使用表构建指南还亟待完善。本文首先从供给和使用层面构建数字经济供给使用表概念框架,界定数字经济特征活动的概念和范围,梳理OECD 划分的数字经济供给使用表中的产品清单和数字经济产业分类;阐释数字经济最终消费、固定资本形成、贸易活动的内涵和种类。其次,围绕“产品×产业×特征活动”三重维度,设计数字经济供给使用表整体架构、阐明其核心指标。再次,编制数字经济供给使用表实例,剖析编制流程、总结编制要点。最后,提出结论和建议。本文尝试完善数字经济统计核算体系,为提出促进我国数字经济高质量发展的政策建议提供核算方法参考。