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2,2,6,6-tetramethylpiperidine-N-oxyl (TEMPO) and its derivatives are well-established catalysts for various oxidation processes, despite its hazardous nature, causing harm to aquatic ecosystems. Thus, the reuse of TEMPO with a sustained high activity has gained significant importance for its industrial application, which has led to the development of supported TEMPO catalyst. In this context, the efficiency of the support process acquires high relevance. Therefore, this research is aimed at the improvement of the TEMPO supported on silica magnetically modified with Fe3O4 through the application of an online Fourier transform infrared spectroscopy (FTIR) probe to monitor its synthesis. FTIR effectively controlled the synthesis of supported TEMPO, by tracking online the concentration of 3-aminopropyltriethoxysilane (APTES) and tetraethyl orthosilicate (TEOS). Additionally, the presence of Fe3O4 particles in the core of the catalyst allowed its convenient recovery and subsequent reuse. Furthermore, the supported TEMPO catalyst was successfully applied in the oxidation of cellulose to produce nano/microfibrils. The carboxyl groups of the initial untreated cellulose increase from 0.05 mmol/g to 0.68 mmol/g with the supported TEMPO catalyst in presence of sodium hypochlorite and sodium bromide at 50 °C.

The exponential growth in information on the Internet, particularly within social networks, highlights the importance of sentiment and opinion analysis. The intrinsic characteristics of the Spanish language coupled with the short length and lack of context of messages on social media pose a challenge for sentiment analysis in social networks. In this study, we present a hybrid deep learning model combining convolutional and long short-term memory layers to detect polarity levels in Twitter for the Spanish language. Our model significantly improved the accuracy of existing approaches by up to 20%, achieving accuracies of around 76% for three polarities (positive, negative, neutral) and 91% for two polarities (positive, negative).

La transformación constante del perfil de la audiencia y sus hábitos informativos obliga a mantener un estudio actualizado para conocer nuevos usos y segmentos de mercado, un aspecto más destacado en las generaciones jóvenes debido a su dieta informativa cambiante, lo que afecta a la enseñanza periodística. Esta investigación ofrece una aproximación sobre el uso informativo de aplicaciones móviles que realizan los estudiantes universitarios. A su vez, se vincula con un estudio de caso de la aplicación universitaria UVaNow, en el marco de aplicación hiperlocal y de aprendizaje electrónico móvil. Esta aplicación ha sido impulsada desde el proyecto de innovación docente LabcomUva, con un desarrollo tecnológico interdisciplinario entre las áreas de Periodismo y Telecomunicación de la Universidad de Valladolid. El estudio recurre a una doble metodología cuantitativa y cualitativa mediante la utilización de una encuesta (N = 294) y un grupo focal. Los resultados confirman que los universitarios descargan una media de 20 aplicaciones y que, pese a que su principal fuente de noticias son las redes sociales, se siguen informando a través de las aplicaciones mediáticas debido a la profesionalidad, la veracidad y la reputación de estas. Respecto al análisis empírico sobre nuevas aplicaciones en el aula, este indica que prefieren hacer un uso utilitario de las aplicaciones universitarias antes que informativo y que ofrezcan información multimedia y servicios personalizables.

The integration of Software Defined Networking (SDN) technologies in Passive Optical Networks (PONs) would provide great advantages to Internet Service Providers (ISPs) and Network Operators, since they can optimize the network operation and reduce its complexity. However, some tasks regarding online service and network configuration strategies are difficult to move to external SDN-controllers since they are time-critical operations. However, the control of some of these policies by SDN techniques could lead to better network and management configuration in a centralized and automatic way. As a consequence, we propose and experimentally test the integration of an OpenFlow approach over legacy Gigabit Passive Optical Networks (GPONs), which allows moving some global service configuration policies to an external SDN controller implementing an SDN management layer that adjust these strategies according to dynamic Quality of Service (QoS) requirements of services in residential users. The viability and efficiency of our approach are demonstrated using a GPON testbed and proposing a new business scenario for ISPs and Network Operators.

Corn stalk, an agricultural waste, was valorized by the production of cellulose nanofibers (CNF), which were tested for improving recycled paper properties. CNF from eucalyptus kraft pulp (E-CNF) was used as a reference. Addition of 0.5% wt. CNF produced from corn organosolv pulp (C-CNF) to recycled paper increased the tensile index by 20%, whereas the same improvement with E-CNF was achieved at 1.5% wt. Tensile index was further enhanced by increasing the E-CNF, whereas C-CNF achieved its maximum effect at this dose. Different recycled furnish compositions were studied to evaluate C-CNF as a product additive. C-CNF improved tensile strength in all the different recycled furnishes studied. The tensile index improvement caused by C-CNF did not depend on the proportions of old newspaper and old magazine paper used. Addition of C-CNF to recycled corrugated board fluting increased the tensile strength, but to a slightly lower extent than in the case of recycled newsprint paper.

5G technologies promise to bring new network and service capacities and are expected to introduce significant architectural and service deployment transformations. The Cloud-Radio Access Networks (C-RAN) architecture, enabled by the combination of Software Defined Networking (SDN), Network Function Virtualization (NFV) and Mobile Edge Computing (MEC) technologies, play a key role in the development of 5G. In this context, this paper addresses the problems of Virtual Network Functions (VNF) provisioning (VNF-placement and service chain allocation) in a 5G network. In order to solve that problem, we propose a genetic algorithm that, considering both computing resources and optical network capacity, minimizes both the service blocking rate and CPU usage. In addition, we present an algorithm extension that adds a learning stage and evaluate the algorithm performance benefits in those scenarios where VNF allocations can be reconfigured. Results reveal and quantify the advantages of reconfiguring the VNF mapping depending on the current demands. Our methods outperform previous proposals in the literature, reducing the service blocking ratio while saving energy by reducing the number of active core CPUs.

The presence of hazardous chemicals in wastewater produced by industrial activities and human metropoles is threating the availability of safe drinking water. The development of a multifunctional material coupling adsorption and photocatalytic activity is hereby particularly promising for the removal of pollutants. We have proved the adsorption and catalytic activity of NiFe2O4-layered double hydroxide (LDH) composite through the degradation of methyl orange (MO) at room temperature under visible light. This degradation is enhanced by using a set of small light-emitting diodes (LEDs) providing a uniform 405 nm UV light. The remediation process is based on a first-step rapid adsorption of MO molecules by the LDH structures followed by the photocatalytic oxidation of the pollutant by the (·OH) radicals produced by the NiFe2O4 semiconductor nanoparticles (NPs). The magnetic properties of the ferrite NPs allow a facile separation of the composite from the liquid media via a simple magnet. NiFe2O4-LDH composite could find wide application as a highly effective adsorbent/oxidizing catalyst operating under visible or near UV light.