Partisan amplification of risk: American perceptions of nuclear energy risk in the wake of the Fukushima Daiichi disaster

AimThis study examines risk perceptions toward nuclear power before and after the Fukushima Daiichi disaster using nationally representative survey samples of American adults.ScopeOn March 11, 2011, a magnitude 8.4 earthquake, the largest in the nation's history, occurred off the coast of Japan. The earthquake produced a devastating tsunami that flooded areas of the Fukushima Daiichi nuclear plant and resulted in a loss of power to the plant's cooling system. In the weeks that followed, the world watched as Japanese and international nuclear power safety experts scrambled to contain the damage and prevent a full meltdown. Although the Fukushima Daiichi disaster was heavily covered in media, there is little empirical research on how this coverage impacted audience risk perceptions. Our analysis goes beyond examining aggregate risk perceptions, instead focusing on how specific sub-populations responded to the disaster.ConclusionWe found that ideological groups responded differently to the events in Japan. In particular, risk perceptions among conservatives decreased following the incident. Moreover, we found that media use exacerbated these effects. We discuss possible explanations for these findings.     

动态信息网络中基于角色的结构演化与预测

动态信息网络是当前复杂网络领域一个极具挑战的新问题,其动态的演化过程具有时序、复杂、多变的特点.结构是网络最基本的特征,也是进行网络建模和分析的基础,研究网络结构的演化过程对全面认识复杂系统的行为倾向具有重要意义.使用“角色”来量化动态网络的结构,得到动态网络的角色模型,应用并改进多类标分类问题的“问题转换”思想,将动态网络的角色预测问题视为多目标回归问题,以历史网络数据作为训练数据构建模型,预测未来时刻网络可能的角色分布情况,提出基于多目标回归思想的动态网络角色预测方法MTR-RP.该方法不仅克服了基于转移矩阵方法忽略时间因素的不足,并且考虑了多个预测目标之间可能存在的依赖关系,实验结果表明,本文提出的MTR-RP方法具有更准确且更稳定的预测效果.     

Surface tuning of halloysite nanotubes with Fe3O4 and 3-D MnO2 nanoflakes for highly selective and sensitive acetone gas sensing

Nanosized M-HNTs-MnO₂ (Magnetic halloysite nanotubes-manganese dioxide) nanocomposite was synthesized by the reduction-precipitation method followed by the hydrothermal process. The existence of MnO₂ nanoflakes on M-HNTs represents 3-D nanostructures without stacking of nanotubes and agglomeration. The sensor-based on M-HNTs-MnO₂ nanocomposites exhibits higher sensor response (R_air/R_gas = 35.6) to 100 ppm of acetone gas at operating temperature (150 °C), with a short response-recovery time (3 s/7 s). The M-HNTs-MnO₂ nanocomposite sensor shows excellent potential to act as a low cost, low-temperature sensor for acetone gas, with high acetone selectivity under high humidity conditions and with the interference of other gases. The high surface to volume ratio, three-dimensional nanostructure, and strong interactions between M-HNTs and MnO₂ nanoflakes are accountable for the improvement of acetone sensing performance. Based on the high acetone selectivity, high stability and fast dynamic response, the M-HNTs and MnO₂ sensor is an extremely appropriate candidate for a low-cost acetone sensor, and the projected approach offers a way to develop gas sensors that can be function at low temperatures for a wide variety of applications.     

Promoting effect of high-silica zeolites on a metal-containing alumina matrix (process of hydrodesulphurization of thiophene)

• 1.1. Metal-containing (Me, Ni, Fe, Mo) boro- and ferrosilicate zeolites without a binder have high initial activities in hydrodesulphurization, similar to the activity of an industrial AlCoMo contact, but lower activities (by a factor of 2–3) in the stable process.
• 2.2. In catalysts consisting of γ-Al₂O₃ and group VI and VIII metal oxides, with low contents of active metals (Ni/Mo = 0·4−0·8) the addition of Ni and Na forms of boro- and ferrosilicates has a promoting effect, increasing stable values of activity by a factor of 2–3 and the apparent effective rate constant byb a factor of 4–7.
• 3.3. Introduction of sodium forms of boro- and ferrosilicates into an alumina matrix with a high content of active metals (Ni/Mo = 1·4−1·5) leads to inhibition hydrodesulphurization, reducing significantly (by a factor of 2·5−3) the stable values of activity and the apparent effective rate constant by comparison with the initial composition Al₂O₃ + NiO + MoO₃.
• 4.4. The addition of 5–10% promoter (high-silica borosilicate zeolite) is optimum for modyfying the catalytic composition Al₂O₃ + NiO + MoO₃.

     

Performance and mechanism of standard nano-TiO2 (P-25) in photocatalytic disinfection of foodborne microorganisms – Salmonella typhimurium and Listeria monocytogenes

Under UV light, nano-TiO₂ is effective in photocatalytic disinfection. In this paper, we studied the disinfection effects of nano-TiO₂ on the two typical food-borne microorganisms, Gram-negative bacterium-Salmonella typhimurium and Gram-positive bacterium-Listeria monocytogenes, in meat products. Results show that nano-TiO₂ had a strong disinfecting activity against both Gram-negative and Gram-positive pathogens in a suspension under UV light. L. monocytogenes was more resistant to nano-TiO₂ treatment than Salmonella under UV light. Nano-TiO₂ concentrations and initial bacteria populations had significant influence on the photocatalytic disinfection effectiveness against S. typhimurium. The optimum concentration (1.0 g/L) was between 0.2 g/L and 1.5 g/L. Increasing S. typhimurium population from 10⁴ to 10⁷ CFU/mL resulted in reduced photocatalytic disinfecting effectiveness by nano-TiO₂. Electron microscope images revealed that nano-TiO₂ photocatalytic disinfection starts with damaging the cell walls of bacteria. With serious destructions of cell walls, cell components released or defused out of cell from the damaged areas, and finally the cells completely lost their integrity and dissolved. These results demonstrate that nano-TiO₂ is very effective against pathogens that can grow well on meat products and the effectiveness can be significantly influenced by nano-TiO₂ contents and pathogen populations. The findings by these experiments provide the essential information for further developing a nano-metal-based, antimicrobial packaging system to improve safety of meat products.     

Combination of Low- and Medium-Temperature Catalysts for the Selective Catalytic Reduction of NOx with NH3

Topics in Catalysis - In this study, we developed a novel combination model for different types of catalysts, which could generate synergistic effects for the catalysts with different functions. A...     

Formaldehyde Oxidation on Pd/TiO2 Catalysts at Room Temperature: The Effects of Surface Oxygen Vacancies

Topics in Catalysis - High reduction temperature generally induces the agglomeration of supported noble metals. Howerve, we found that high temperature reduction did not induce Pd particles...     

Multi-mode acid concentration prediction models of cold-rolled strip steel pickling process

In the steel strip pickling process, the control of the acid concentration is an important part for ensuring the strip surface quality. Now only X-ray method is used to detect the acid concentration online, but the price is very high and the maintenance is very hard. The acid concentration is not measured in most of the steel strip pickling lines online. In this paper, a soft measurement of acid concentration is developed. The pressure differential, conductivity and temperature are used to calculate the acid concentration including ferrous chloride (FeCl₂) and hydrogen chloride (HCl) concentration. The real pickling process is under a multi-mode condition. First, the spectral clustering based on geodesic distance is used to cluster the data into some groups. There are clearly linear relationship between the condition variables and the acid concentration. Then, orthogonal signal correction-iteratively reweighted least squares (OSC-IRLS) models based on the cluster data set are built to predict the acid concentration. The real field data set from cold-rolled strip steel pickling process is used to validate the model. The results demonstrate that the clustering method can improve the prediction result.