Specific consumption of liquid biofuels in gasoline fuelled engines

Oxygenated fuels increase fuel consumption due to their low enthalpy of combustion; however, their high antiknock index renders them suitable for use in engines with a high compression rate, increasing their thermal yield. This study evaluated the performance of biorenewable oxygenated fuels (ethanol and isoamyl alcohol) and partially renewable fuels (ETBE: ethyl tert-butyl ether, TAEE: tert-amyl ethyl ether and di-TAE: di-tert-amyl ether) with high degree of purity and in mixtures with automotive gasoline, based on tests with Otto cycle engines. Among the oxygenated fuels evaluated here, di-TAE was found to present the best characteristics of performance, both individually and in mixtures with gasoline.     

Carbonaceous adsorbents from sewage sludge and their application in a combined activated sludge-powdered activated carbon (AS-PAC) treatment

In this study, waste biological sludge is converted to an adsorbent by chemical activation with sulphuric acid. The adsorbent obtained is then applied to the aerated vessel of an activated sludge process treating glucose and phenol to improve the quality of the treated effluent. The sludge-based carbonaceous adsorbent was found to be mesoporous in nature, with a good adsorption capacity for large molecular weight compounds and limited removal efficiency for smaller molecules such as phenol. The addition of carbon, either sludge-based or commercial, enhanced phenol removal from 58% to 98.7% and from 87% to 93% the organic matter removal as measured by the chemical oxygen demand (COD) when operated with feed concentrations of 100 mg phenol/l and 2500 mg COD/l. No differences were found between the activated sludge-activated carbon bench scale continuous reactors operating with either commercial or sludge-based adsorbents in spite of the higher adsorption capacity of the former. It is suggested that powdered adsorbent bioregeneration in the combined AS-PAC system may be impaired by the obstruction of pores due to bacterial growth, the effect being more important for the commercial activated carbon with a narrower pore size distribution.     

Experimental design to evaluate properties of electrospun fibers of zein/poly (ethylene oxide) for biomaterial applications

The production of polymer fibers from the combination of zein and PEO might have great potential in the field of biomaterial. Zein/PEO fibers were obtained in this work through solution electrospinning. An experimental design, 2^4-1, was used for evaluating the influences of PEO content in the blend, distance from the needle tip to the collector, applied electric voltage and solution flow for average fiber diameter and relative-yield process. Beyond this, the relationship between PEO content in the blend and the fiber properties were evaluated through FTIR, DSC, TG, tensile tests, and cytotoxic tests. The factor that exerts the greatest effect on the average fiber diameter response was the electrical voltage. The increase in PEO content in the blend decreased the thermal stability and increased the degree of the fibers' crystallinity. The mechanical tests showed that fibers with higher elongation were obtained at richer PEO blends. The fibers presented cytocompatible characteristics.     

Signage Versus Environmental Affordances: Is the Explicit Information Strong Enough to Guide Human Behavior During a Wayfinding Task?

This study aims to explore how people behave when they have to find a location within a complex building and are confronted with situations where directional signage (i.e., explicit information) is in opposition to environmental affordances that naturally direct users towards a specific path, creating a situation with conflicting information (e.g., a brighter corridor vs. a darker corridor but with a directional sign indicating to follow the darker one). A virtual reality–based methodology was used and a between‐subject design was considered. Thus, participants were given the tasks of finding three publicly accessible central points in a virtual hotel and confronted with a two forced‐choice task of local scenes in which environmental variables (i.e., corridor width and brightness) and signage varied systematically, in two experimental conditions (i.e., neutral and signage). For the signage condition, signs were inserted to explicitly point in the opposite direction than that implicitly suggested by the environmental affordances, creating situations with conflicting information. Results indicate that environmental variables were able to direct people indoors acting as environmental affordances. Users preferred to follow the wider and brighter paths. However, when directional signage pointed in the opposite direction of the paths preferred by the participants, most of them complied with signage.     

Cartogram visualization for nonlinear manifold learning models

Real-world applications of multivariate data analysis often stumble upon the barrier of interpretability. Simple data analysis methods are usually easy to interpret, but they risk providing poor data models. More involved methods may instead yield faithful data models, but limited interpretability. This is the case of linear and nonlinear methods for multivariate data visualization through dimensionality reduction. Even though the latter have provided some of the most exciting visualization developments, their practicality is hindered by the difficulty of explaining them in an intuitive manner. The interpretability, and therefore the practical applicability, of data visualization through nonlinear dimensionality reduction (NLDR) methods would improve if, first, we could accurately calculate the distortion introduced by these methods in the visual representation and, second, if we could faithfully reintroduce this distortion into such representation. In this paper, we describe a technique for the reintroduction of the distortion into the visualization space of NLDR models. It is based on the concept of density-equalizing maps, or cartograms, recently developed for the representation of geographic information. We illustrate it using Generative Topographic Mapping (GTM), a nonlinear manifold learning method that can provide both multivariate data visualization and a measure of the local distortion that the model generates. Although illustrated here with GTM, it could easily be extended to other NLDR visualization methods, provided a local distortion measure could be calculated. It could also serve as a guiding tool for interactive data visualization.     

Two proposals for the inclusion of directory information in the last-level private caches of glueless shared-memory multiprocessors

In glueless shared-memory multiprocessors where cache coherence is usually maintained using a directory-based protocol, the fast access to the on-chip components (caches and network router, among others) contrasts with the much slower main memory. Unfortunately, directory-based protocols need to obtain the sharing status of every memory block before coherence actions can be performed. This information has traditionally been stored in main memory, and therefore these cache coherence protocols are far from being optimal. In this work, we propose two alternative designs for the last-level private cache of glueless shared-memory multiprocessors: the lightweight directory and the SGluM cache. Our proposals completely remove directory information from main memory and store it in the home node’s L2 cache, thus reducing both the number of accesses to main memory and the directory memory overhead. The main characteristics of the lightweight directory are its simplicity and the significant improvement in the execution time for most applications. Its drawback, however, is that the performance of some particular applications could be degraded. On the other hand, the SGluM cache offers more modest improvements in execution time for all the applications by adding some extra structures that cope with the cases in which the lightweight directory fails.