On manifolds supporting quasi Anosov diffeomorphisms

Let $M$ be an $n$-dimensional manifold supporting a quasi Anosov diffeomorphism. If $n=3$ then either $M={\mathbb T}^3$, in which case the diffeomorphisms is Anosov, or else its fundamental group contains a copy of ${\mathbb Z} ^6$. If $n=4$ then $\Pi_1(M)$ contains a copy of ${\mathbb Z} ^4$, provided that the diffeomorphism is not Anosov.Comment: 5 page

Effect of phosphorous groups on the stabilization and activation of low-cost lignin fibers prepared by electrospinning

The feasible wider use of carbon fibers in many of their current and potential applications demands a reduction of their manufacturing costs. In this sense, the use of lignin as an abundant, renewable and low-cost carbonaceous precursor and a simple and versatile production technique, such as the electrospinning, represents an advantageous and promising approach [1-3]. Particularly, the devIlopment of high-value co-products from lignocellulosic biomass-derived industries, such as biorefineries and pulp and paper mills, could suppose a significant opportunity to reduce their associated costs and environmental impacts. However, the use of lignin itself in the production of carbon fibers requires of successive stabilization and carbonization steps that currently slow down, raises the price and, therefore, limits their commercialization and industrial application. In this work, a new method to produce novel sub-micrometer carbon fibers by electrospinning of phosphorous-containing lignin solutions is proposed.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Distributed Correlation-Based Feature Selection in Spark

CFS (Correlation-Based Feature Selection) is an FS algorithm that has been successfully applied to classification problems in many domains. We describe Distributed CFS (DiCFS) as a completely redesigned, scalable, parallel and distributed version of the CFS algorithm, capable of dealing with the large volumes of data typical of big data applications. Two versions of the algorithm were implemented and compared using the Apache Spark cluster computing model, currently gaining popularity due to its much faster processing times than Hadoop's MapReduce model. We tested our algorithms on four publicly available datasets, each consisting of a large number of instances and two also consisting of a large number of features. The results show that our algorithms were superior in terms of both time-efficiency and scalability. In leveraging a computer cluster, they were able to handle larger datasets than the non-distributed WEKA version while maintaining the quality of the results, i.e., exactly the same features were returned by our algorithms when compared to the original algorithm available in WEKA.Comment: 25 pages, 5 figure

Novel lignin-based fibrous carbon materials

Lignin is (and will be) an important co-product in many lignocellulosic biomass-derived industries, such as pulp and paper mills (and the future biorefineries, when the concept of bio-economy be developed). The development of high-value products from lignin could mean a significant opportunity to reduce the associated costs and the environmental impacts of these industries [1]. In this sense, a new method to produce novel sub-micrometer carbon fibers and interconnected fibrous carbon webs materials (FCMs), showing unique advanced properties for different applications, by electrospinning [2] of phosphorous-containing lignin solutions is studied in this work. The different FCMs were prepared by electrospinning of Alcell lignin solutions with and without P–containing compounds, followed by stabilization and carbonization at different temperatures. For comparison purposes, equivalent lignin-based powdery carbon materials (PCMs) were also prepared from lignin powder without the electrospinning step. The different samples were characterized by N2 and CO2 adsorption, SEM, TEM, XRD, Raman, XPS, TPD and TG analysis. In the absence of P-containing groups, electrospun carbon fibers are continuous and linear (Fig 1.a), and show a specific surface area of 700 m2/g, much higher than that of carbon prepared in powdery shape (70 m2/g). The presence of P precursors in the lignin solution re-markably affects the electrospinning, sta-bilization and carbo-nization processes. By a suitable control of the stabilization heating rate, continuous and curly carbon fibers (Fig 1.b) or interconnected carbon fibrous webs (Fig 1.c) can be produced. In addition, the presence of 30wt% of P-containing compound in the lignin solution increases the specific surface area up to 1500 m2/g and enhances the oxidation resistance of the FCMs at high temperatures, what have been found very interesting for different applications, such as catalysis, adsorption and energy storage and conversion. These properties cannot be obtained in lignin-based carbon powders, even by using an 80wt% of P-containing compound for their chemical activation (1100 m2/g).Universidad de Málaga. Campus de Excelencia Andalucía Tech

Efecto del H3PO4 en la preparación de fibras de carbono a partir de lignina. Mejoras en el proceso de estabilización y propiedades finales

El presente trabajo propone un nuevo método de preparación de fibras de carbono mediante electrohilado de mezclas de lignina/H3PO4, en el que se obtienen resultados que aceleran el proceso de preparación de estos materiales así como sus propiedades físico-químicas en una sola etapa de preparación. Será objeto de estudio la temperatura, tiempo y velocidad de calentamiento en la etapa de estabilización así como la atmósfera (inerte u oxidante) de estabilización y carbonización.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

ROM-Based Stochastic Optimization for a Continuous Manufacturing Process

This paper proposes a model-based optimization method for the production of automotive seals in an extrusion process. The high production throughput, coupled with quality constraints and the inherent uncertainty of the process, encourages the search for operating conditions that minimize nonconformities. The main uncertainties arise from the process variability and from the raw material itself. The proposed method, based on Bayesian optimization, takes these factors into account and obtains a robust set of process parameters. Due to the high computational cost and complexity of performing detailed simulations, a reduced order model is used to address the optimization. The proposal has been evaluated in a virtual environment where it is shown that the performance of the solution found minimizes the effects of process uncertainties.Comment: 7 pages, 8 figure

Performance measurement in Judo: main KPIs, cluster categorization and causal relationships

[EN] Performance measurement in Judo usually focuses on some KPIs whose values indicate the final performance of the athlete. This paper deals with firstly identifying which these main Key Performance Indicators (KPIs) in Judo are. Once this is done, the KPIs are classified into four different clusters: Physical training, Specific training, Psychology and Lifestyle. Then, it moves into analyzing possible quantitative techniques to identify cause-effect relationships between KPIs in order to link not only the impact of the Judo KPIs with the achievement of the judoka’s strategic objectives but also to identify both the relative and the global importance of each of these KPIs. Finally, it points out the Analytic Network Technique as the one that could be ideally applied in this context and offers future research actions.Uriarte Marcos, S.; Rodriguez-Rodriguez, R.; Uriarte Marcos, M.; Alfaro-Saiz, J. (2019). Performance measurement in Judo: main KPIs, cluster categorization and causal relationships. International Journal of Production Management and Engineering. 7(2):145-150. https://doi.org/10.4995/ijpme.2019.12035SWORD1451507

Electrochemical behavior of pt- a d pd-supported activated carbons with different functionalities

Due to their relatively low price, high surface area and versatile physic-chemical properties, conductive carbon materials are considered among the most promising supports of electroactive species and/or catalysts for different electrochemical devices, like supercapacitors, fuel cells, batteries, sensors, etc. [1]. However, in these applications, carbon supports are usually subjected to oxidation and/or corrosion processes, which can be promoted by the supported electroactive species and/or catalysts [2]. In this sense, although the surface functionalities of carbons seem to play a key role on their electrochemical response and stability, their influence in the presence of electroactive catalysts is still controversial. Particularly, the effect of phosphorous groups has been never reported. In this work, the influence of different oxygen and phosphorous functionalities on the electrochemical behavior of Pt- and Pd-supported activated carbons (ACs) has been studied. Various ACs showing similar surface areas (ca. 1400-1500 m2/g) and a rich variety of surface chemistry, with oxygen and phosphorous-like surface groups, were obtained by physical (CO2) (HAG800 support) or chemical (H3PO4) (HA3500 support) activation of olive stone. The ACs were used as support of Pd, Pt and Pd/Pt catalysts (Fig 1a), with nominal loadings of 0.5-1.0 wt%, by using the incipient-wetting impregnation method. The samples were characterized by N2 and CO2 adsorption, TEM, XRD, XPS, TPD experiments and different electrochemical techniques. Although the supported metals promote carbon electroxidation and/or corrosion (see the higher oxidation currents for the metalloaded sample – Fig 1b), the presence of surface phosphorous groups (HA3500-M samples) results in lower oxidation currents than in the case of P-free samples (HAG800-M samples) (Fig. 1.b). These results are in agreement with the oxidation resistance induced by phosphorous groups in oxidizing gas phase at high temperatures [3], and may support the statement that these phosphorous groups could enhance the durability of carbon-supported metal electrocatalysts for different electrochemical applications.Universidad de Málaga. Campus de Excelencia Andalucía Tech