Tomorrow's Leaders and Today's Agents of Change? Children,Sustainability Education and Environmental Governance

Children are central to the rhetoric supporting global climate agreements, yet they are also envisaged to play a strategic role in materialising such agreements. Along with other household actors, children are implicated in localised efforts to manage global resource sustainability. As learners in educational systems that are being redesigned to encompass messages of sustainability, children are moreover positioned as ‘agents of change’ through sustainability education. Drawing on theoretical work on children's agency and interdependence, this review calls for greater attention to the structural and relational dimensions of environmental knowledge transmission to inform sustainability education. This is presented as one move towards constructing what Middlemiss (2014) terms a more ‘socially sensitive’ model of sustainable development.     

Optimal design of repetitive group sampling plans for Weibull and gamma distributions with applications and comparison to the Birnbaum–Saunders distribution

In this paper, we propose a multiple deferred state repetitive group sampling plan which is a new sampling plan developed by incorporating the features of both multiple deferred state sampling plan and repetitive group sampling plan, for assuring Weibull or gamma distributed mean life of the products. The quality of the product is represented by the ratio of true mean life and specified mean life of the products. Two points on the operating characteristic curve approach is used to determine the optimal parameters of the proposed plan. The plan parameters are determined by formulating an optimization problem for various combinations of producer's risk and consumer's risk for both distributions. The sensitivity analysis of the proposed plan is discussed. The implementation of the proposed plan is explained using real-life data and simulated data. The proposed plan under Weibull distribution is compared with the existing sampling plans. The average sample number (ASN) of the proposed plan and failure probability of the product are obtained under Weibull, gamma and Birnbaum–Saunders distributions for a specified value of shape parameter and compared with each other. In addition, a comparative study is made between the ASN of the proposed plan under Weibull and gamma distributions.     

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.     

HR systems and leadership attachment affecting idea generation and implementation: An experiment and two-source multi-level study

This paper focuses on the direct and interactive influence of leadership attachment styles (secure, anxious, and avoidant) and commitment HR system on two distinct stages of the individual innovation process—idea generation and implementation. We test our hypotheses in two studies. An experimental study of undergraduate students establishes a positive effect of secure attachment on idea implementation. The interplay between commitment HR system and avoidant attachment marginally predict idea generation; commitment HR system and neither secure nor anxious attachment predict implementation. A multisource multi-level field study in three EU-based private firms replicates the direct role of commitment HR system in stimulating idea implementation (but not generation) and suggests that secure attachment fosters both generation and implementation, whereas anxious attachment hinders both. Moderation analyses support only a marginal interaction between commitment HR system and secure attachment in fostering idea generation. We discuss theoretical, practical, and future research implications.     

Parameters estimation for weibull distributed lifetimes under progressive censoring with random removeals

This paper considers the estimation problem when lifetimes are Weibull distributed and are collected under a Type-II progressive censoring with random removals, where the number of units removed at each failure time follows a uniform discrete distribution. The expected time of this censoring plan is discussed and compared numerically to that under a Type II censoring without removal. Maximum likelihood estimator of the parameters and their asymptotic variances are derived.     

Assessing respondent-driven sampling: A simulation study across different networks

The purpose was to assess RDS estimators in populations simulated with diverse connectivity characteristics, incorporating the putative influence of misreported degrees and transmission processes. Four populations were simulated using different random graph models. Each population was “infected” using four different transmission processes. From each combination of population x transmission, one thousand samples were obtained using a RDS-like sampling strategy. Three estimators were used to predict the population-level prevalence of the “infection”. Several types of misreported degrees were simulated. Also, samples were generated using the standard random sampling method and the respective prevalence estimates, using the classical frequentist estimator. Estimation biases in relation to population parameters were assessed, as well as the variance. Variability was associated with the connectivity characteristics of each simulated population. Clustered populations yield greater variability and no RDS-based strategy could address the estimation biases. Misreporting degrees had modest effects, especially when RDS estimators were used. The best results for RDS-based samples were observed when the “infection” was randomly attributed, without any relation with the underlying network structure.     

“90后”大学生入学教育新模式探索

高校应针对"90后"大学生的特点及独特的个性,探索新的教育途径和方法。     

Variable Selection via Regression Trees in the Presence of Irrelevant Variables

Many tree algorithms have been developed for regression problems. Although they are regarded as good algorithms, most of them suffer from loss of prediction accuracy when there are many irrelevant variables and the number of predictors exceeds the number of observations. We propose the multistep regression tree with adaptive variable selection to handle this problem. The variable selection step and the fitting step comprise the multistep method.

The multistep generalized unbiased interaction detection and estimation (GUIDE) with adaptive forward selection (fg) algorithm, as a variable selection tool, performs better than some of the well-known variable selection algorithms such as efficacy adaptive regression tube hunting (EARTH), FSR (false selection rate), LSCV (least squares cross-validation), and LASSO (least absolute shrinkage and selection operator) for the regression problem. The results based on simulation study show that fg outperforms other algorithms in terms of selection result and computation time. It generally selects the important variables correctly with relatively few irrelevant variables, which gives good prediction accuracy with less computation time.     

政府监管与企业加入第三方国际环境审计的模糊博弈分析

针对政府环境监管与企业实施环境行为博弈分析中无法对双方的损益情况做出判断的问题,文章结合三角模糊数构建了政府监管和企业加入第三方国际环境审计的博弈模型,分别指出了纯策略纳什均衡和混合策略均衡情况需要满足的条件,讨论了政府与污染环境企业博弈策略的影响因素及作用机制,为政府监管与企业加入第三方国际环境审计顺利实施提供了相关建议。然后通过三角结构元方法对算例进行求解,验证了结论的正确性和可行性,引入三角模糊概念更加符合实际应用情况,拓展了第三方国际环境审计的应用背景。研究结果表明,政府对消费者消费的引导和对污染企业的惩罚对企业是否决定加入第三方国际环境审计起着举足轻重的作用。