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The dilemma between stability and plasticity is crucial in machine learning, especially when non-stationary input distributions are considered. This issue can be addressed by continual learning in order to alleviate catastrophic forgetting. This strategy has been previously proposed for supervised and reinforcement learning models. However, little attention has been devoted to unsupervised learning. This work presents a dynamic learning rate framework for unsupervised neural networks that can handle non-stationary distributions. In order for the model to adapt to the input as it changes its characteristics, a varying learning rate that does not merely depend on the training step but on the reconstruction error has been proposed. In the experiments, different configurations for classical competitive neural networks, self-organizing maps and growing neural gas with either per-neuron or per-network dynamic learning rate have been tested. Experimental results on document clustering tasks demonstrate the suitability of the proposal for real-world problems.

Exhaust gas recirculation can be achieved by means of two different routes: the high-pressure route (high-pressure exhaust gas recirculation), where exhaust gas is conducted from upstream of the turbine to downstream of the compressor, and the low-pressure one (low-pressure exhaust gas recirculation), where exhaust gas is recirculated from downstream of the turbine and of the aftertreatment system to upstream of the compressor. In this study, the effectiveness of both exhaust gas recirculation systems on the improvement of the NOx-particulate matter emission trade-off has been compared on a Euro 6 turbocharged diesel engine equipped with a diesel oxidation catalyst, a lean-NOx trap, and a diesel particulate filter. Emissions were measured both upstream and downstream of the aftertreatment system, at different combinations of engine speed and torque (corresponding to different vehicle speeds), at transient and steady conditions, and at different coolant temperatures as switch points to change from high-pressure exhaust gas recirculation to low-pressure exhaust gas recirculation. It was shown that low-pressure exhaust gas recirculation was more efficient than high-pressure exhaust gas recirculation to reduce NOx emissions, mainly due to the higher recirculation potential and the lower temperature of the recirculated gas. However, such a differential benefit decreased as the coolant temperature decreased, which suggests the use of high-pressure exhaust gas recirculation during the engine warm-up. It was also shown that the lean-NOx trap storage efficiency decreased more rapidly at high engine load than at medium load and that such reduction in efficiency was much faster when high-pressure exhaust gas recirculation was used than when low-pressure exhaust gas recirculation was used.

Diesel engine vehicles, despite their good fuel economy and reduced CO2, are receiving significant attention and negative publicity in recent years due to their difficulties in achieving the emissions regulations. This has widely been linked to undesirable environmental impact and health effects. The lower exhaust gas temperatures associated with modern and more efficient hybrid powertrain and diesel engines makes current technology catalytic aftertreatment systems less efficient under range of vehicle operating conditions. This study, demonstrates how changes in the commonly used aftertreatment system architecture and changes in fuel composition in this case through the addition of oxygenated fuels (i.e. butanol) in diesel fuel can provide meaningful low temperature catalyst activity improvements. The catalyst oxidation kinetics of CO and HC species were improved (reduced the light-off temperature by around 20 °C) when a diesel particulate filter (DPF) was placed upstream of the DOC, while the combination of DPF and combustion of oxygenated fuel in diesel led to up to 80 °C improvement in catalyst activity. The prevention of soot reaching the DOC active sites increases the rate of reactions and the species accessibility to the active sites of the catalyst, and thereby the oxidation of emissions (CO, HC, and NO) can occur at lower catalyst temperatures. The combustion of diesel-butanol blend further improved the DOC low temperature activity. The major contributors to the improved catalyst light-off, are the reduced level of soot and hydrocarbon emissions as well as the higher reactivity of the hydrocarbons species emitted under butanol blend combustion.

Alcohols produced from waste or lignocellulosic materials with advanced production techniques constitute a sustainable alternative as diesel fuel component. With respect to ethanol, the higher heating value of n-butanol together with its better miscibility with diesel fuel and lower hydrophilic character suggest that butanol is a better option as blending component for diesel fuels. A Euro 6 Nissan Qashqai 1.5 dCi light-duty vehicle was tested following the NEDC (New European Driving Cycle) on a chassis dynamometer located in a climatic chamber with different blends of diesel and n-butanol. Room temperatures were set at 24 °C and −7 °C. Butanol blends up to 16% (volume basis) showed benefits in particle number and particulate matter emissions upstream of the DPF at any ambient condition, this implying a reduction in the frequency of regeneration. Benefits in engine efficiency were observed at cold ambient temperature (−7 °C), just when the efficiency is poorest. Increases in NOx emissions were observed only at cold ambient temperature (−7 °C), while increases in CO and hydrocarbon emissions were found at any temperature. Blends with n-butanol content above 13% led to startability problems at cold ambient conditions. In general, including n-butanol as a blend component is beneficial for both performance and particulate emissions, but the blend concentration is limited by startability problems at very low ambient temperature.

Tests with diesel/n-butanol blends (up to 20% by volume) were carried out in a Euro 6 engine following the New European Driving Cycle in a test bench. No decrease in engine efficiency was observed when n-butanol is used and fuel consumption increased proportionally to its lower heating value. Regarding emissions, total hydrocarbon and carbon monoxide increased when n-butanol is used. On the other hand, the use of n-butanol reduces the particle emissions down to a minimum value (for around 16% of n-butanol content) and then increases particle emissions again. This was observed in both mass and particle number. This trend occurs as a consequence of the compromise between the increase in oxygen content, which inhibits soot formation, and the increase in hydrocarbon emissions, especially under cold-engine conditions, which promotes liquid nucleation. Finally, NOX emissions remained unchanged as a consequence of the compensation between larger ignition delays and shorter combustion durations.

Kinematic viscosities were measured for ethanol and n-butanol blends with diesel and biodiesel fuels, showing that increasing alcohol contents contributed to a non-linear decrease in the viscosity. Only ethanol blends with alcohol content lower than 36% (volume basis) fulfill diesel fuel quality standard, whereas the whole range of n-butanol blends fulfills this standard. Generalized correlations were tested for the estimation of the viscosity of ethanol and butanol blends with diesel and biodiesel fuels in the whole range of alcohol contents. Interaction coefficients were required for an adequate estimation due to strong molecular interactions. Two-parameter equations did not improve, and three-parameter equations improved only slightly, the estimations with respect to the Grunberg-Nissan equation, with only one interaction coefficient. This interaction coefficient decreases when the number of carbon atoms in the n-alcohol molecule increases for both diesel blends and biodiesel blends because the non-polar part of the molecule becomes dominant against the polar hydroxyl group. Original correlations were proposed for the modeling of the interaction coefficient in alcohol-diesel and alcohol biodiesel fuels as a function of the carbon number of the alcohol. Other n-alcohols (methanol, propanol and n-pentanol) were also tested to extend the validity of the correlation proposed. These correlations are useful for the design of transport equipment or pipelines in a scenario where alcohols may constitute a fuel component in diesel blends. Also the decision on feasible blends that fulfill the narrow viscosity ranges set by fuel standards (to avoid loss of vehicle operability) will benefit from the proposed correlations.

Decoupling the dependences between emission reduction technologies and engine fuel economy in order to improve them both simultaneously has been proven a major challenge for the vehicle research communities. Additionally, the lower exhaust gas temperatures associated with the modern and future generation internal combustion engines are challenging the performance of road transport environmental catalysts. Studying how fuel properties and fuel injection strategies affect the combustion characteristics, emissions formation and hence catalysts performance can unveil synergies that can benefit vehicle emissions and fuel economy and as well as guide the design of next generation sustainable fuels. The experimental work presented here was conducted using a modern single-cylinder, common rail fuel injection system diesel engine equipped with a diesel oxidation catalyst (DOC). The impact of the fuel post-injection strategy that is commonly used as part of the aftertreatment system function (i.e. regeneration of diesel particulate filters or activity in hydrocarbon selective reduction of NO X ), combined with butanol-diesel fuel blend (B20) combustion on engine emissions formation, particulate matter characteristics (size distribution, morphology and structure) and oxidation catalyst activity were studied. It was found that post-injection produced lower PM concentration and modified the soot morphological parameters by reducing the number of primary particles (n po ), the radius of gyration (R g ), and the fractal dimension (D f ). The results were compared with the engine operation on diesel fuel. The increased concentration of HC and CO in the exhaust as a result of the diesel fuel post-injection at the studied exhaust conditions (i.e. T = 300 °C) led in the reduction of the DOC activity due to the increased competition of species for active sites. This effect was improved the combustion of B20 when compared to diesel.

Recently, there is increasing interest in using butanol as a renewable component not only for gasoline but also for diesel fuels. This work investigates the effect of its concentration on diesel and biodiesel blends on the autoignition time, comparatively to equivalent blends with ethanol, in a constant-volume combustion chamber. The increase of alcohol content in diesel or biodiesel, led to an increase in autoignition times. Such increase was not linear but sharper for high alcohol contents, and was higher with ethanol than with butanol. For butanol blends, the increase in delay time was very similar when diesel or biodiesel were used. The maximum pressure during combustion decreases as the alcohol content was increased, especially in the case of ethanol, as a consequence of energy, chemical and dilution effects. However, for low ethanol or butanol concentrations, some increases in the pressure peaks were observed by a combination of compensating effects: increase in the amount of premixed combustion and increase in the flame speed. For 10% v/v alcohol blends in diesel or biodiesel, the delay times decreased as both the initial pressure and the initial temperature were increased, the latter effect being slightly higher with biodiesel compared to diesel.

4 Tablas,18 Figuras., The use of advanced fuels must increase from 0.5 to 3.6% of the total fuel consumption in internal combustion engines according to the forthcoming European directive. In this regard, alcohols that can be obtained from waste or lignocellulosic materials with advanced production techniques may play an important role in the future. This work focuses on the effect of the use of butanol as a blend component on the properties of soot emitted from compression ignition engines. This knowledge is essential to decide the strategy to carry out a proper regeneration process in a diesel particle filter. The study was performed in a Euro 6 diesel engine. The engine operating condition used to collect particulate matter was selected as a typical steady mode in urban driving. The blends tested were baseline diesel, Bu10D (10% butanol and 90% diesel v/v), Bu20D (20% butanol and 80% diesel v/v), and Bu10B10D (10% butanol, 10% biodiesel, and 80% diesel v/v). The techniques used to characterize the soot were X-ray diffraction, Raman spectroscopy, transmission electron microscopy, surface area analysis, X-rayphotoelectron spectroscopy, Fourier transform infrared spectroscopy, thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). Among the results shown, most of the structural parameters related to the soot carbon layers did not correlate with reactivity, whereas others such as the concentration of oxygenated functional groups, the surface area (both increasing with butanol content), and the average primary particle diameter, which is reduced with the increasing butanol content, showed good consistency with soot reactivity obtained with TGA and DSC., This research was funded by the European Union Horizon 2020 Research and Innovation Programme under grant agreement no.640462 (ButaNexT project). Nissan, Repsol, and Green Biologics are gratefully acknowledged for the donation of the vehicle, the diesel fuel, and the n-butanol fuel, respectively. Junta de Comunidades de Castilla-La Mancha is also acknowledged for financing the fellowship of Jesús Sánchez-Valdepeñas. T.G. would also like to thank the Regional Government of Aragon (DGA) for the support provided under the research groups support programme.

There is an increasing interest in reducing CO2 as far as it is the main responsible of greenhouse gas (GHG) emissions. Since the contribution of heavy-duty (HD) vehicles to GHG emissions of the road transport sector reaches 24% in the European Union, Liquefied Petroleum Gas (LPG) is suggested as a promising alternative fuel to be introduced in HD vehicles. The main drawback when using LPG in diesel engines is its poor autoignition behavior. To overcome this difficulty is possible to mix LPG with Hydrotreated Vegetable Oil (HVO) or diesel fuel, which acts as an ignition improver. This work has focused on LPG-HVO blends up to 75 %m/m LPG content, with lower LPG content admixtures included. Another measure to promote autoignition is using advanced injection strategies, particularly at low thermal conditions in the combustion chamber. This study concluded that 25LPG-75HVO blend (without any injection strategy modification) and 50LPG-50HVO blend (with advanced injection strategy) show better autoignition behavior than diesel fuel at low thermal conditions. At usual combustion conditions, LPG-HVO blends up to 75 %m/m LPG content can be supplied using an advanced injection strategy, and achieving similar autoignition behavior than diesel. LPG and HVO contents in the blend can be balanced depending on the thermal conditions. Therefore, a novel injection system with an in-line mixing valve capable of managing the instantaneous LPG/HVO ratio for compression ignition engines, is suggested. Testing these blends with advanced injection strategies using the in-line mixing system in a real HD engine would confirm these results.

Traditionally focused on good old-fashioned AI and robotics, the Spanish AI community holds a vigorous computational intelligence substrate. Neuromorphic, evolutionary, or fuzzylike systems have been developed by many research groups in the Spanish computer sciences. It is no surprise, then, that these naturegrounded efforts start to emerge, enriching the AI catalogue of research projects and publications and, eventually, leading to new directions of basic or applied research. In this article, we review the contribution of Melomics in computational creativity. The work on Iamus was partially supported by grants IPT-300000-2010-010 from the Spanish Ministerio de Ciencia e Innovación and TSI-090302-2011-8 from the Spanish Ministerio de Industria, Turismo y Comercio. The first and fourth authors were supported by grant P09-TIC-5123 from the Consejería de Innovación y Ciencia, Junta de Andalucía.

The purpose of the work reported here was to describe the sonoelastographic appearance of the plantar fascia of healthy volunteers and patients with fasciitis. Twenty-three healthy subjects and 21 patients with plantar fasciitis were examined using B-mode and real-time sonoelastography (RTSR) scanning. B-Mode examination included fascia thickness and echotexture. Echogenicity and echovariation of the color histogram were analyzed. Fasciae were classified into type 1, blue (more elastic); type 2, blue/green (intermediate); or type 3, green (less elastic). RTSE revealed 72.7% of fasciae as type 2, with no significant association with fasciitis (c253.6, df 52, p 50.17). Quantitative analysis of the color histogram revealed a significantly greater intensity of green (mean577.8, 95% confidence interval [CI]571.9–83.6) and blue (mean574.2, 95% CI569.7–78.8) in healthy subjects. Echovariation of the color red was 33.4%higher in the fasciitis group than in the healthy group (95% CI516.7–50.1). Sonoelastography with quantitative analysis of echovariation can be a useful tool for evaluation of plantar fascia pathology. Actividad Física y Deporte Medicina Terapia y Rehabilitación