Bad News Has Wings: Dread Risk Mediates Social Amplification in Risk Communication

Social diffusion of information amplifies risk through processes of birth, death, and distortion of message content. Dread risk—involving uncontrollable, fatal, involuntary, and catastrophic outcomes (e.g., terrorist attacks and nuclear accidents)—may be particularly susceptible to amplification because of the psychological biases inherent in dread risk avoidance. To test this, initially balanced information about high or low dread topics was given to a set of individuals who then communicated this information through diffusion chains, each person passing a message to the next. A subset of these chains were also reexposed to the original information. We measured prior knowledge, perceived risk before and after transmission, and, at each link, number of positive and negative statements. Results showed that the more a message was transmitted the more negative statements it contained. This was highest for the high dread topic. Increased perceived risk and production of negative messages was closely related to the amount of negative information that was received, with domain knowledge mitigating this effect. Reexposure to the initial information was ineffectual in reducing bias, demonstrating the enhanced danger of socially transmitted information.     

Another economy: towards a cultural dialectics between energy and society

The looming oil crisis, pollution, and climate change have pushed governments, corporations, and individuals to think of new policies, new objects/products and new manners to market them – usually under the label of “green economy” (or the shifting towards a sustainable economy).

The changes that are on the way as a result of the envisaged “green revolution” need a broad vision that couples the economy of energetic techniques with the related socio-cultural economy that is induced by, and at the same time reciprocally influences, the mere technical transformations.

Based on previous analysis of theories of socio-technological change and putting at its center the concept of subjectivation in social sciences, this article proposes a theoretical understanding of cultural shifts and their relationship with changes in the practices of production, transfer and use of energy.

First part presents a schema of subjectivation in triangulation, that links the biological level with the material culture and with the representational realm of normativities in our society. It will be developed through the example of electric vehicle as metaphor of the energetic transition. Through this understanding, second part deals with the modeling of the three items as a processual energetic system by using the concepts of surplus and expenditure. Within this frame, we show how disruptions in one of the poles of this model influences the others and bring about changes in the entire Anthropo-Social level. Third part proposes possible types of emerging subjectivities and advances the idea of extending the realm of consciousness to the energetic transfers and their potentiality.     

Catch-up as a Survival Strategy in the Solar Power Industry

We evaluate the strategies of the emerging market firms in the context of nascent industries. We use the Indian solar power industry as the empirical setting, against the backdrop of the evolution of the global industry, While in traditional industries emerging market firms learn from advanced economy multinational enterprises (MNEs) and slowly upgrade their capabilities, in the intensely competitive environment of nascent innovative industries, emerging market firms are exposed to global competition in their home market right from the early years. This shortens their catch-up clock. As a result, their long-term survival depends on their ability to catch-up fast, both in output and innovation capabilities. In the solar power industry, we find that innovations stem, in the main, from advanced economy firms. Further, Chinese firms are beginning to move from cost-based imitation to innovation. In contrast, with a few key exceptions, most firms in the Indian solar industry remain locked within a narrow niche of downstream site-based installation. Their operations are opportunistic, short term, and without specific catch-up goals, a scenario that does not bode well for the industry's future in India.     

服务型制造网络的Holon协同需求评价方法

依据复杂网络理论分析服务型制造网络Holon协同需求问题，给出一种考虑以直觉正态模糊数表示且多Holon协同的服务型制造网络协同需求评价方法。首先，在区分Holon复合协同和递归协同基础上构建服务型制造网络协同需求评价指标体系；其次，考虑基于网络结构特征的Holon相似稳定性，根据服务型制造网络节点相似性测度分析Holon协同需求特征，并测算不同相似性测度修正的Holon网络结构熵；再次，建立面向服务型制造网络和Holon的有专家信息双向触动反馈机制，反馈包括评价指标和网络协同状况，反馈Holon信息包括基于服务型制造网络演化方向的Holon间协同需求建议和基于服务型制造网络现有状态的网络连通性Holon协同需求建议；最后由INFCWA（INFCWA_R）算子或INFCWG（INFCWG_R）算子分别对复合协同和递归协同评价信息集结并得出评价结论。方法设计过程通过例证分析说明根据服务型制造网络目标控制的Holon协同需求评价改进了群组评价效率。     

国家级新区义务教育资源供需矛盾及消解路径——基于N市J区12345政务热线数据分析

成立国家级新区对迅速改善欠发达地区经济环境、改变落后的民生状态进而促进城市区域发展具有重要意义。国家级新区应努力推动社会公共服务体系与产业发展体系协同共进。义务教育资源是社会公共服务体系的重要组成部分，不容忽视。国家级新区在初创的关键时期需要打好义务教育资源均衡分配的基础，为后续义务教育资源的优化升级提供坚实保障。本文以N市J区为例，通过对12345政务热线服务平台的数据分析和对关键人物的访谈，探讨国家级新区初创期义务教育资源需求特征，同时发现实际存在着义务教育资源供不应求、供需脱节、配置失衡、提质升级乏力等供需矛盾，并依据新区初创阶段的实际需求，从制定规划、资金支持、供需互动、创新升级等方面进一步探讨国家级新区义务教育资源供需矛盾的消解路径。     

A Data‐Driven Approach to Assessing Supply Inadequacy Risks Due to Climate‐Induced Shifts in Electricity Demand

The U.S. electric power system is increasingly vulnerable to the adverse impacts of extreme climate events. Supply inadequacy risk can result from climate‐induced shifts in electricity demand and/or damaged physical assets due to hydro‐meteorological hazards and climate change. In this article, we focus on the risks associated with the unanticipated climate‐induced demand shifts and propose a data‐driven approach to identify risk factors that render the electricity sector vulnerable in the face of future climate variability and change. More specifically, we have leveraged advanced supervised learning theory to identify the key predictors of climate‐sensitive demand in the residential, commercial, and industrial sectors. Our analysis indicates that variations in mean dew point temperature is the common major risk factor across all the three sectors. We have also conducted a statistical sensitivity analysis to assess the variability in the projected demand as a function of the key climate risk factor. We then propose the use of scenario‐based heat maps as a tool to communicate the inadequacy risks to stakeholders and decisionmakers. While we use the state of Ohio as a case study, our proposed approach is equally applicable to all other states.     

从主权国家的兴衰看权力博弈形态的转型

传统的国际关系理论,无论是现实主义、自由主义、建构主义还是科学行为主义理论,都是把主权国家抽象成一个统一的国际关系行为体。这一行为主体有一致的利益,也自然要有一致的对外政策目标和手段。在20世纪,尤其是在两次世界大战和冷战期间,这一概念抽象是非常准确的。但冷战结束以后,尤其是进入21世纪以后,这一概念抽象逐渐与国际关系的现实相违背。一方面,国家综合实力并不能直接转化为具体领域的竞争优势;另一方面,很多国家,包括超级大国在内,其对外政策的主要阻力可能不是所谓的竞争对手,而是其国内不同的利益集团。这导致传统的国际关系理论,从假设到概念和推理层面,都已经无法解释和预测今天的世界,而权力小博弈理论可以为认识多元复杂互动博弈时代的国际关系提供一个新的解释框架。     

中国智能经济的涌现机制

我国智能经济的发展内生于经济转型升级过程中创造的智能化需求。与AI 1.0不同，新一代人工智能(AI 2.0)不再是简单用计算机模拟人的智能，而是基于网络空间发展的数据智能，即智能机器、人和网络相互融合的智能系统。智能经济是以数据和计算为“关键生产要素”的新经济形态，包括人工智能的产业化和产业的智能化过程中创造的新产品、新技术、新模式和新业态。互联网，尤其是移动互联网发展中创造出的数据生态优势是中国人工智能科技产业发展的前提和基础。在拥有数据生态优势的条件下，强烈的需求牵引、产学研协同创新、创新生态系统的高度开放性和核心产业部门与融合产业部门的融合发展，共同构成了中国智能经济发展的关键机制。     

On the power of goodness-of-fit tests for the exponential distribution under progressive Type-II censoring

The aim of this article is to review existing goodness-of-fit tests for the exponential distribution under progressive Type-II censoring and to provide some new ideas and adjustments. In particular, we consider two-parameter exponentially distributed random variables and adapt the proposed test procedures to our scenario if necessary. Then, we compare their power by an extensive simulation study. Furthermore, we propose five new test procedures that provide reasonable alternatives to those already known.     

Some count-based nonparametric tests for circular symmetry of a bivariate distribution

In this paper, we revisit the problem of testing of the hypothesis of circular symmetry of a bivariate distribution. We propose some nonparametric tests based on sector counts. These include tests based on chi-square goodness-of-fit test, the classical likelihood ratio, mean deviation, and the range. The proposed tests are easy to implement and the exact null distributions for small sample sizes of the test statistics are obtained. Two examples with small and large data sets are given to illustrate the application of the tests proposed. For small and moderate sample sizes, the performances of the proposed tests are evaluated using empirical powers (empirical sizes are also reported). Also, we evaluate the performance of these count-based tests with adaptations of several well-known tests such as the Kolmogorov–Smirnov-type tests, tests based on kernel density estimator, and the Wilcoxon-type tests. It is observed that among the count-based tests the likelihood ratio test performs better.