Assessing the cost-effectiveness of electric vehicles in European countries using integrated modeling

Electric vehicles (EVs) are considered alternatives to internal combustion engines due to their energy efficiency and contribution to CO₂ mitigation. The adoption of EVs depends on consumer preferences, including cost, social status and driving habits, although it is agreed that current and expected costs play a major role. We use a partial equilibrium model that minimizes total energy system costs to assess whether EVs can be a cost-effective option for the consumers of each EU27 member state up to 2050, focusing on the impact of different vehicle investment costs and CO₂ mitigation targets. We found that for an EU-wide greenhouse gas emission reduction cap of 40% and 70% by 2050 vis-à-vis 1990 emissions, battery electric vehicles (BEVs) are cost-effective in the EU only by 2030 and only if their costs are 30% lower than currently expected. At the EU level, vehicle costs and the capability to deliver both short- and long-distance mobility are the main drivers of BEV deployment. Other drivers include each state’s national mobility patterns and the cost-effectiveness of alternative mitigation options, both in the transport sector, such as plug-in hybrid electric vehicles (PHEVs) or biofuels, and in other sectors, such as renewable electricity.     

Electrocatalytic Reduction of CO2 to Ethylene by Molecular Cu‐Complex Immobilized on Graphitized Mesoporous Carbon

The electrochemical reduction of carbon dioxide (CO₂) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO₂ to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO₂ to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO₂ in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions.     

Size-controlled synthesis of Mo powders via hydrogen reduction of MoO2 powders with the assistance of Mo nuclei

The size-controlled preparation of Mo powders is always a challenge and important task in the molybdenum metallurgy. In the current study, Mo powders with controllable sizes are synthesized by hydrogen reduction of MoO₂ powders with the assistance of Mo nuclei in the range of 900–1100 °C. The influences of the particle sizes of Mo nuclei, the additive amount as well as reaction temperature on the morphology and particle sizes of the final products are studied. For the hydrogen reduction of MoO₂ without any additive, the obtained Mo powders always have large particle sizes. However, the addition of small amounts of nuclei in MoO₂ can help Mo nucleate dispersedly, and the growth of Mo could be also controlled by adjusting the sizes of added nuclei, amount of addition and the reaction temperature. With the addition of Mo nuclei, the different sizes of Mo powders with the good dispersity can be prepared. As adding commercial Mo powders with the particle size of about 2.03 μm, the micron-sized Mo powders ranged from 2.11 μm to 3.25 μm could be prepared. While for the case of adding ultrafine Mo nuclei of about 170 nm, Mo powders from 0.28 μm to 0.88 μm can be obtained. Moreover, the more the amounts of nuclei added and the lower the reaction temperature (in the range of 900–1100 °C) is, the smaller the particle size of the prepared Mo powder will be. The current method is a facile and feasible method, and is potential to be used for industrial production of Mo powder with controllable particle sizes.     

Type II fuzzy set-based data analytics to explore amino acid associations in protein sequences of Swine Influenza Virus

The veracity present in molecular data available in biological databases possesses new challenges for data analytics. The analysis of molecular data of various diseases can provide vital information for developing better understanding of the molecular mechanism of a disease. In this paper, an attempt has been made to propose a model that addresses the issue of veracity in data analytics for amino acid association patterns in protein sequences of Swine Influenza Virus. The veracity is caused by intra-sequential and inter-sequential biases present in the sequences due to varying degrees of relationships among amino acids. A complete dataset of 63,682 protein sequences is downloaded from NCBI and is refined. The refined dataset consists of 26,594 sequences which are employed in the present study. The type I fuzzy set is employed to explore amino acid association patterns in the dataset. The type I fuzzy support is refined to partially remove the inter-sequential biases causing veracity in data. The remaining inter-sequential biases present in refined fuzzy support are evaluated and eliminated using type II fuzzy set. Hence, it is concluded that a combination of type II fuzzy & refined fuzzy approach is the optimal approach for extracting a better picture of amino acid association patterns in the molecular dataset.     

Learning fuzzy controllers in mobile robotics with embedded preprocessing

The automatic design of controllers for mobile robots usually requires two stages. In the first stage, sensorial data are preprocessed or transformed into high level and meaningful values of variables which are usually defined from expert knowledge. In the second stage, a machine learning technique is applied to obtain a controller that maps these high level variables to the control commands that are actually sent to the robot. This paper describes an algorithm that is able to embed the preprocessing stage into the learning stage in order to get controllers directly starting from sensorial raw data with no expert knowledge involved. Due to the high dimensionality of the sensorial data, this approach uses Quantified Fuzzy Rules (QFRs), that are able to transform low-level input variables into high-level input variables, reducing the dimensionality through summarization. The proposed learning algorithm, called Iterative Quantified Fuzzy Rule Learning (IQFRL), is based on genetic programming. IQFRL is able to learn rules with different structures, and can manage linguistic variables with multiple granularities. The algorithm has been tested with the implementation of the wall-following behavior both in several realistic simulated environments with different complexity and on a Pioneer 3-AT robot in two real environments. Results have been compared with several well-known learning algorithms combined with different data preprocessing techniques, showing that IQFRL exhibits a better and statistically significant performance. Moreover, three real world applications for which IQFRL plays a central role are also presented: path and object tracking with static and moving obstacles avoidance.     

Significant population genetic structuring in Rhyzopertha dominica across Turkey: Biogeographic and practical implications

Rhyzopertha dominica is a key pest of stored grain. Understanding the movement of this beetle on broad geographic scales is crucial, particularly when developing strategies to prevent the spread of phosphine resistance. We assessed population genetic structuring in this pest across Turkey, using a combination of mitochondrial (cytochrome oxidase I) and microsatellite markers. In addition, we screened samples for Wolbachia, as this endosymbiont has previously been suggested to be associated with low mitochondrial genetic diversity in this beetle. Mitochondrial genetic diversity was low, with only six haplotypes identified. The genetic diversity was, however, substantially higher than that previously found in Australia or India, suggesting that R. dominica may have originated in the Middle East. Wolbachia were detected only at a single site, indicating they are not impacting the mitochondrial genetic diversity of R. dominica across Turkey. Microsatellite markers indicated there is significant geographic genetic structuring across Turkey, even among sites less than 100 km apart, suggesting there is little movement of beetles across regions within the country. This contrasts with the significantly higher levels of gene-flow found in Australia and the United States. We suggest that the limited movement of beetles across Turkey may be due to a combination of the historically localised agricultural practices (which limits anthropogenic movement among regions), and the mountainous landscape (which limits active flight among regions). Our results demonstrate that the movement of stored product pests may differ significantly across studies conducted in different countries. As a consequence, phosphine resistance management strategies must incorporate region specific information on the extent of beetle movement.     

A Lattice Approach to Image Segmentation

After a formal definition of segmentation as the largest partition of the space according to a criterion σ and a function f, the notion of a morphological connection is reminded. It is used as an input to a central theorem of the paper (Theorem 8), that identifies segmentation with the connections that are based on connective criteria. Just as connections, the segmentations can then be regrouped by suprema and infima. The generality of the theorem makes it valid for functions from any space to any other one. Two propositions make precise the AND and OR combinations of connective criteria. The soundness of the approach is demonstrated by listing a series of segmentation techniques. One considers first the cases when the segmentation under study does not involve initial seeds. Various modes of regularity are discussed, which all derive from Lipschitz functions. A second category of examples involves the presence of seeds around which the partition of the space is organized. An overall proposition shows that these examples are a matter for the central theorem. Watershed and jump connection based segmentations illustrate this type of situation. The third and last category of examples deals with cases when the segmentation occurs in an indirect space, such as an histogram, and is then projected back on the actual space under study. The relationships between filtering and segmentation are then investigated. A theoretical chapter introduces and studies the two notions of a pulse opening and of a connected operator. The conditions under which a family of pulse openings can yield a connected filter are clarified. The ability of segmentations to generate pyramids, or hierarchies, is analyzed. A distinction is made between weak hierarchies where the partitions increase when going up in the pyramid, and the strong hierarchies where the various levels are structured as semi-groups, and particularly as granulometric semi-groups. The last section is based on one example, and goes back over the controversy about “lattice” versus “functional” optimization. The problem is now tackled via a case of colour segmentation, where the saturation serves as a cursor between luminance and hue. The emphasis is put on the difficulty of grouping the various necessary optimizations into a single one.     

林达大型低压甲醇合成塔在内蒙天野20万吨/年装置上的应用

简要介绍了林达均温型甲醇塔在内蒙天野20万t/a甲醇装置开车及初步运行情况。运行情况验证了该反应器的先进性,其催化剂床层测温点多、温度分布均匀、运行稳定。     

Fatigue crack propagation of multiple coplanar cracks with the coupled extended finite element/fast marching method

A numerical technique for modeling fatigue crack propagation of multiple coplanar cracks is presented. The proposed method couples the extended finite element method (X-FEM) [Int. J. Numer. Meth. Engng. 48 (11) (2000) 1549] to the fast marching method (FMM) [Level Set Methods & Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science, Cambridge University Press, Cambridge, UK, 1999]. The entire crack geometry, including one or more cracks, is represented by a single signed distance (level set) function. Merging of distinct cracks is handled naturally by the FMM with no collision detection or mesh reconstruction required. The FMM in conjunction with the Paris crack growth law is used to advance the crack front. In the X-FEM, a discontinuous function and the two-dimensional asymptotic crack-tip displacement fields are added to the finite element approximation to account for the crack using the notion of partition of unity [Comput. Meth. Appl. Mech. Engng. 139 (1996) 289]. This enables the domain to be modeled by a single fixed finite element mesh with no explicit meshing of the crack surfaces. In an earlier study [Engng. Fract. Mech. 70 (1) (2003) 29], the methodology, algorithm, and implementation for three-dimensional crack propagation of single cracks was introduced. In this paper, simulations for multiple planar cracks are presented, with crack merging and fatigue growth carried out without any user-intervention or remeshing.     

基于粗糙集信息观的决策表属性约简方法

粗糙集理论是近年来发展起来的一种有效的处理不精确、不确定、含糊信息的数学理论方法，它被广泛应用于相容和不相容决策表的属性约简和核属性计算。利用反例指出目前基于粗糙集信息观[2、6]的决策表属性约简和核属性计算方法的局限性。对决策表的性质作了深入的研究，研究发现文献[2、6]方法的不足原因是：它们没有考虑U／ind（C）中等价类的相客性。给出了基于U／ind（C）中等价类相客性的属性约简定义和核属性定义，并给出了一种新的基于粗糙集信息观的决策表属性约简和核属性计算方法。讨论了该方法同文献[2、6]方法的区别。最后用相同实例验证了该方法的有效性。