Celebrity endorsers' performance on the “ground” and on the “floor”

This article analyzes the relationship between two types of performances, one on the ground (of a tennis court) and the other on the floor (of the stock market). The empirical application looks into the tennis player, Rafael Nadal, and his endorsing firms. The findings show a positive reaction in the market value when the tennis player wins matches in the Grand Slams, the intriguing effect being the diminishing sensitivity pattern that such reaction shows and the absence of loss aversion.

Refinery Nonconventional Feedstocks: Influence of the Coprocessing of Vacuum Gas Oil and Low Density Polyethylene in Fluid Catalytic Cracking Unit on Full Range Gasoline Composition

Gasoline coming from refinery fluid catalytic cracking (FCC) unit is a major contributor to the total commercial grade gasoline pool. The contents of the FCC gasoline are primarily paraffins, naphthenes, olefins, aromatics, and undesirables such as sulfur and sulfur containing compounds in low quantities. The proportions of these components in the FCC gasoline invariable determine its quality as well as the performance of the associated downstream units. The increasing demand for cleaner and lighter fuels significantly influences the need not only for novel processing technologies but also for alternative refinery and petrochemical feedstocks. Current and future clean gasoline requirements include increased isoparaffins contents, reduced olefin contents, reduced aromatics, reduced benzene, and reduced sulfur contents. The present study is aimed at investigating the effect of processing an unconventional refinery feedstock, composed of blend of vacuum gas oil (VGO) and low density polyethylene (LDPE) on FCC full range gasoline yields and compositional spectrum including its paraffins, isoparaffins, olefins, napthenes, and aromatics contents distribution within a range of operating variables of temperature (500–700 °C) and catalyst-feed oil ratio (CFR 5–10) using spent equilibrium FCC Y-zeolite based catalyst in a FCC pilot plant operated at the University of Alicante’s Research Institute of Chemical Process Engineering (RICPE). The coprocessing of the oil-polymer blend led to the production of gasoline with very similar yields and compositions as those obtained from the base oil, albeit, in some cases, the contribution of the feed polymer content as well as the processing variables on the gasoline compositional spectrum were appreciated. Carbon content analysis showed a higher fraction of the C9–C12 compounds at all catalyst rates employed and for both feedstocks. The gasoline’s paraffinicity, olefinicity, and degrees of branching of the paraffins and olefins were also affected in various degrees by the scale of operating severity. In the majority of the cases, the gasoline aromatics tended toward the decrease as the reactor temperature was increased. While the paraffins and iso-paraffins gasoline contents were relatively stable at around 5 % wt, the olefin contents on the other hand generally increased with increase in the FCC reactor temperature.

Catalytic performance of CuO/Ce0.8Zr0.2O2 loaded onto SiC-DPF in NOx-assisted combustion of diesel soot

This work presents a comparative study between the catalytic performance of the 2% CuO/ceria-zirconia powder catalyst and the same catalyst supported on silicon carbide DPF (Diesel Particulate Filter) towards NO oxidation reaction and soot combustion reaction. The ceria-zirconia catalyst was prepared by the co-precipitation method and 2 wt% copper was incorporated by the incipient wetness impregnation method. The catalyst was incorporated onto the ceramic support using a simple and organic solvent-free procedure by a simply dipping the DPF into an aqueous solution of the catalyst. The powder catalyst has been characterized using N2 adsorption at −196 °C, XRD and Raman Spectroscopy; whereas the catalytic coating morphology has been evaluated by SEM and the mechanical stability by an adherence test. Both catalyst configurations were tested for NO oxidation to NO2 and for soot combustion under NOx/O2. The results revealed that incorporation of the very active copper/ceria-zirconia catalyst onto SiC-DPF has been successfully achieved by a simple coating procedure. Furthermore, the catalytic coating has shown suitable mechanical, chemical and thermal stability. A satisfactory catalytic performance of the catalytic-coated filter was reached towards the NO oxidation reaction. Moreover, it was proved that the catalytic coating is stable and the corresponding coated DPF can be reused for several cycles of NO oxidation without a significant decrease in its activity. Finally, it was verified that the loose-contact mode is a good choice to simulate the catalytic performance of this active phase in a real diesel particulate filter.

Convergence analysis and validation of low cost distance metrics for computational cost reduction of the Iterative Closest Point algorithm

The Iterative Closest Point algorithm (ICP) is commonly used in engineering applications to solve the rigid registration problem of partially overlapped point sets which are pre-aligned with a coarse estimate of their relative positions. This iterative algorithm is applied in many areas such as the medicine for volumetric reconstruction of tomography data, in robotics to reconstruct surfaces or scenes using range sensor information, in industrial systems for quality control of manufactured objects or even in biology to study the structure and folding of proteins. One of the algorithm’s main problems is its high computational complexity (quadratic in the number of points with the non-optimized original variant) in a context where high density point sets, acquired by high resolution scanners, are processed. Many variants have been proposed in the literature whose goal is the performance improvement either by reducing the number of points or the required iterations or even enhancing the complexity of the most expensive phase: the closest neighbor search. In spite of decreasing its complexity, some of the variants tend to have a negative impact on the final registration precision or the convergence domain thus limiting the possible application scenarios. The goal of this work is the improvement of the algorithm’s computational cost so that a wider range of computationally demanding problems from among the ones described before can be addressed. For that purpose, an experimental and mathematical convergence analysis and validation of point-to-point distance metrics has been performed taking into account those distances with lower computational cost than the Euclidean one, which is used as the de facto standard for the algorithm’s implementations in the literature. In that analysis, the functioning of the algorithm in diverse topological spaces, characterized by different metrics, has been studied to check the convergence, efficacy and cost of the method in order to determine the one which offers the best results. Given that the distance calculation represents a significant part of the whole set of computations performed by the algorithm, it is expected that any reduction of that operation affects significantly and positively the overall performance of the method. As a result, a performance improvement has been achieved by the application of those reduced cost metrics whose quality in terms of convergence and error has been analyzed and validated experimentally as comparable with respect to the Euclidean distance using a heterogeneous set of objects, scenarios and initial situations.