Life cycle cost of conventional,battery electric,and fuel cell electric vehicles considering traffic and environmental policies in China

Electric vehicles (EVs) are considered a promising alternative to conventional vehicles (CVs) to alleviate the oil crisis and reduce urban air pollution and carbon emissions. Consumers usually focus on the tangible cost when choosing an EV or CV but overlook the time cost for restricting purchase or driving and the environmental cost from gas emissions, falling to have a comprehensive understanding of the economic competitiveness of CVs and EVs. In this study, a life cycle cost model for vehicles is conducted to express traffic and environmental policies in monetary terms, which are called intangible cost and external cost, respectively. Battery electric vehicles (BEVs), fuel cell electric vehicles (FCEVs), and CVs are compared in four first-tier, four new first-tier, and 4 s-tier and below cities in China. The comparison shows that BEVs and FCEVs in most cities are incomparable with CVs in terms of tangible cost. However, the prominent traffic and environmental policies in first-tier cities, especially in Beijing and Shanghai, greatly increase the intangible and external costs of CVs, making consumers more inclined to purchase BEVs and FCEVs. The main policy benefits of BEVs and FCEVs come from three aspects: government subsidies, purchase and driving restrictions, and environmental taxes. With the predictable reduction in government subsidies, traffic and environmental policies present important factors influencing the competitiveness of BEVs and FCEVs. In first-tier cities, BEVs and FCEVs already have a competitive foundation for large-scale promotion. In new first-tier and second-tier and below cities, stricter traffic and environmental policies need to be formulated to offset the negative impact of the reduction in government subsidies on the competitiveness of BEVs and FCEVs. Additionally, a sensitivity analysis reveals that increasing the mileage and reducing fuel prices can significantly improve the competitiveness of BEVs and FCEVs, respectively.     

Effects of (Li0.5Sm0.5)/W co-substitution and sintering temperature on the structure and electrical properties of ultrahigh Curie temperature piezoceramics,Ca0.92(Li0.5Sm0.5)0.08Bi2Nb2-xWxO9

With co-substitution of (Li_0.5Sm_0.5) at A site and W at B site, the electrical properties of modified Ca_0.92(Li_0.5Sm_0.5)_0.08Bi₂Nb_2-xW_xO₉ [(CLS)BN-xW, x = 0, 0.015 and 0.03] piezoceramics with ultrahigh Curie temperature (T_C) of > 930 °C were enhanced dramatically. The increased resistivity induced by the co-substitution ensure them to be polarized under an enough high field. Combined with the increase of spontaneous ferroelectric polarization (P_S), the significant enhancements in the piezoelectric, dielectric and ferroelectric properties can be obtained in the composition x = 0.015. Furthermore, the piezoelectric activity (d₃₃) and bulk resistivity (ρ_b) of (CLS)BN-0.015 W can be further enhanced at an appropriate sintering temperature. This optimum composition sintered at 1170 °C shows ultrahigh T_C of ～948 °C, d₃₃ of ～17.3 pC/N and ρ_b of ～6.9 MΩ cm at 600 °C, which are comparable to those of the reported high-temperature Aurivillius piezoceramics with T_C > 850 °C.     

Scanning tunneling spectroscopic study of monolayer 1T-TaS2 and 1T-TaSe2

Nano Research - The isostructural and isoelectronic transition-metal-dichalcogenides 1T-TaS2 and 1T-TaSe2 are layered materials with intricate electronic structures. Combining the molecular beam...     

一种北斗联合低轨星座的导航增强方法研究

单纯依靠北斗导航系统提供定位导航授时服务,存在卫星信号落地功率低、易受遮蔽和阻断的不足。针对此问题,研究了一种北斗联合低轨星座实现导航增强的系统架构;提出了一种新的适应严重遮蔽或干扰条件下,基于到达时间(TOA)和到达频率(FOA)联合观测的定位解算算法;对高中低轨混合星座条件下的覆盖特性和精度衰减因子进行了仿真分析。分析结果表明,用户可见星数平均增加了64.2%,位置精度衰减因子(PDOP)平均改善了28.7%。研究结果可为下一代北斗的论证设计与研制建设提供参考借鉴。     

原子吸收光谱法测定保护渣中锰含量

采用原子吸收光谱法测定保护渣中锰含量,进行了酸度对测定的影响、试样分解、共存离子干扰、加标回收、精密度分析等试验。结果表明,锰可完全溶解于混合酸溶液中;加入氯化锶,可以消除钠、钙对锰测定的干扰;锰质量浓度在0~12.0μg/mL的范围,工作曲线线性关系良好;加标回收率较高,在97%~102%;测定结果准确度较高,与高碘酸钠光度法分析结果一致性较好。     

Human responses to high levels of carbon dioxide and air temperature

In this study, 30 subjects were exposed to different combinations of air temperature (T_a: 24, 27, and 30°C) and CO₂ level (8000, 10 000, and 12 000 ppm) in a high-humidity (RH: 85%) underground climate chamber. Subjective assessments, physiological responses, and cognitive performance were investigated. The results showed that as compared with exposure to T_a = 24°C, exposure to 30°C at all CO₂ levels caused subjects to feel uncomfortably warm and experience stronger odor intensity, while increased mental effort and greater intensity of acute health symptoms were reported. However, no significant effects of T_a on task performance or physiological responses were found. This indicated that subjects had to exert more effort to maintain their performance in an uncomfortably warm environment. Increasing CO₂ from 8000 to 12 000 ppm at all T_a caused subjects to report higher rates of headache, fatigue, agitation, and feeling depressed, although the results were statistically significant only at 24 and 27°C. The text typing performance and systolic blood pressure (SBP) decreased significantly at this exposure, whereas diastolic blood pressure (DBP) and thermal discomfort increased significantly. These effects suggest higher arousal/stress. No significant interaction effect of T_a and CO₂ concentration on human responses was identified.     

Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.