Correction: Ferreira, P.M., et al. A neural network based intelligent predictive sensor for cloudiness, solar radiation and air temperature. Sensors 2012, 12, 15750–15777

Accurate measurements of global solar radiation and atmospheric temperature, as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight and portable sensor was developed, using artificial neural network models as the time-series predictor mechanisms. These have been identified with the aid of a procedure based on the multi-objective genetic algorithm. As cloudiness is the most significant factor affecting the solar radiation reaching a particular location on the Earth surface, it has great impact on the performance of predictive solar radiation models for that location. This work also represents one step towards the improvement of such models by using ground-to-sky hemispherical colour digital images as a means to estimate cloudiness by the fraction of visible sky corresponding to clouds and to clear sky. The implementation of predictive models in the prototype has been validated and the system is able to function reliably, providing measurements and four-hour forecasts of cloudiness, solar radiation and air temperature

Non-perturbative quark mass renormalisation and running in Nf = 3 QCD

We determine from first principles the quark mass anomalous dimension in Nf= 3 QCD between the electroweak and hadronic scales. This allows for a fully non-perturbative connection of the perturbative and non-perturbative regimes of the Standard Model in the hadronic sector. The computation is carried out to high accuracy, employing massless O(a)-improved Wilson quarks and finite-size scaling techniques. We also provide the matching factors required in the renormalisation of light quark masses from lattice computations with O(a)-improved Wilson fermions and a tree-level Symanzik improved gauge action. The total uncertainty due to renormalisation and running in the determination of light quark masses in the SM is thus reduced to about 1

Position paper - progress towards standards in integrated (aerobic) MBR modelling

Membrane bioreactor (MBR) models are useful tools for both design and management. The system complexity is high due to the involved number of processes which can be clustered in biological and physical ones. Literature studies are present and need to be harmonized in order to gain insights from the different studies and allow system optimization by applying a control. This position paper aims at defining the current state of the art of the main integrated MBR models reported in the literature. On the basis of a modelling review, a standardized terminology is proposed to facilitate the further development and comparison of integrated membrane fouling models for aerobic MBRs

UV assisted photo reactive polyether-polyesteramide resin for future applications in 3D printing

Among additive manufacturing, photocuring 3D printing technologies are very relevant because of its high printing speed and high precision. However, the limited performance of photosensitive thermoset polymers is the bottleneck for the application of photocuring 3D printing in some fields, particularly in the biomedical sector. Thus, the development of biodegradable and biocompatible materials is highly desirable and of utmost importance. In this work, a biodegradable and non-cytotoxic thermoset polymer for photocuring 3D printing is reported. It consists of an unsaturated polyesteramide bearing phenylalanine, 2-butene-1,4-diol and fumarate building blocks, which is photocured under UV irradiation using a low molecular weight poly(ethylene glycol) diacrylate as crosslinker. The main characteristics of the new thermoset are: (1) very high volumetric and mechanical integrity stabilities, comparable to that of photocured epoxides; (2) very high degradation temperature; (3) very low water absorption capacity; (4) relatively fast enzymatic degradation, reaching 16.5% after 3¿months; and (5) non-cytotoxic response in presence of epithelial cells, even when soluble molecular fragments coming from biodegradation are considered. These properties favor the future utilization of the new polyether-polyesteramide resin in the manufacturing of more sustainable products via 3D printing methods, such as stereolithography, that uses UV sources.Postprint (published version

Gelatin-based nanoparticles as DNA delivery systems: synthesis, physicochemical and biocompatible characterization

The rapidly rising demand for therapeutic grade DNA molecules requires associated improvements in encapsulation and delivery technologies. One of the challenges for the efficient intracellular delivery of therapeutic biomolecules after their cell internalization by endocytosis is to manipulate the non-productive trafficking from endosomes to lysosomes, where degradation may occur. The combination of the endosomal acidity with the endosomolytic capability of the nanocarrier can increase the intracellular delivery of many drugs, genes and proteins, which, therefore, might enhance their therapeutic efficacy. Among the suitable compounds, the gelification properties of gelatin as well as the strong dependence of gelatin ionization with pH makes this compound an interesting candidate to be used to the effective intracellular delivery of active biomacromolecules. In the present work, gelatin (either high or low gel strength) and protamine sulfate has been selected to form particles by interaction of oppositely charged compounds. Particles in the absence of DNA (binary system) and in the presence of DNA (ternary system) have been prepared. The physicochemical characterization (particle size, polydispersity index and degree of DNA entrapment) have been evaluated. Cytotoxicity experiments have shown that the isolated systems and the resulting gelatin-based nanoparticles are essentially non-toxic. The pH-dependent hemolysis assay and the response of the nanoparticles co-incubated in buffers at defined pHs that mimic extracellular, early endosomal and late endo-lysosomal environments demonstrated that the nanoparticles tend to destabilize and DNA can be successfully released. It was found that, in addition to the imposed compositions, the gel strength of gelatin is a controlling parameter of the final properties of these nanoparticles. The results indicate that these gelatin-based nanoparticles have excellent properties as highly potent and non-toxic intracellular delivery systems, rendering them promising DNA vehicles to be used as non-viral gene delivery system

Control and soft sensing strategies for a wastewater treatment plant using a neuro-genetic approach

During the last years, machine learning-based control and optimization systems are playing an important role in the operation of wastewater treatment plants in terms of reduced operational costs and improved effluent quality. In this paper, a machine learning-based control strategy is proposed for optimizing both the consumption and the number of regulation violations of a biological wastewater treatment plant. The methodology proposed in this study uses neural networks as a soft-sensor for on-line prediction of the effluent quality and as an identification model of the plant dynamics, all under a neuro-genetic optimum model-based control approach. The complete scheme was tested on a simulation model of the activated sludge process of a large-scale municipal wastewater treatment plant running under the GPS-X simulation frame and validated with operational gathered data, showing optimal control performance by minimizing operational costs while satisfying the effluent requirements, thus reducing the investment in expensive sensor devices.info:eu-repo/semantics/publishedVersio

Novel Multi-Feature Bag-of-Words Descriptor via Subspace Random Projection for Efficient Human-Action Recognition

Human-action recognition through local spatio-temporal features have been widely applied because of their simplicity and its reasonable computational complexity. The most common method to represent such features is the well-known Bag-of-Words approach, which turns a Multiple-Instance Learning problem into a supervised learning one, which can be addressed by a standard classifier. In this paper, a learning framework for human-action recognition that follows the previous strategy is presented. First, spatio-temporal features are detected. Second, they are described by HOG-HOF descriptors, and then represented by a Bag of Words approach to create a feature vector representation. The resulting high dimensional features are reduced by means of a subspace-random-projection technique that is able to retain almost all the original information. Lastly, the reduced feature vectors are delivered to a classifier called Citation K-Nearest Neighborhood, especially adapted to Multiple-Instance Learning frameworks. Excellent results have been obtained, outperforming other state-of-the art approaches in a public database

El valor percibido de las marcas del distribuidor y del fabricante: un análisis comparativo de su posicionamiento en los canales de distribución

Cuando surgieron las marcas de distribuidor, se consideraba que estas tenían una calidad considerablemente inferior a la de las marcas del fabricante. Además, estas últimas aportaban un valor añadido al cliente y tenían cierto prestigio en el mercado, por lo que su precio más elevado se veía justificado. Pero, con el paso de los años, las marcas del distribuidor fueron desarrollándose y ganando terreno en los diferentes mercados en los que operan. Las circunstancias de los consumidores hicieron que cada vez fueran más aquellos que apostaban por el consumo de estas marcas. Actualmente el mercado se encuentra dividido entre aquellos que defienden la calidad y el valor que les aportan los productos de marca del fabricante y los que defienden que los productos de marcas del distribuidor ofrecen las mismas prestaciones a un precio menor.When label brands emerged, they were considered to have significantly lower quality than manufacturer brands. Furthermore, the latter provided added value to the customer and had a certain prestige in the market, so their higher price was justified. But, over the years, the distributor's brands were developing and gaining ground in the different markets in which they operate. The circumstances of the consumers made that more and more people were betting on the consumption of these brands. Currently the market is divided between those who defend the quality and value provided by the manufacturer's brand products and those who defend that the distributor's brand products offer the same benefits at a lower pric

Insights of Active Extension Within a Collisional Orogen From GNSS (Central Betic Cordillera, S Spain)

The coexistence of shortening and extensional tectonic regimes is a common feature in orogenic belts. The westernmost end of the Western Mediterranean is an area undergoing shortening related to the 5 mm/ yr NNW‒SSE convergence of the Nubia and Eurasia Plates. In this region, the Central Betic Cordillera shows a regional ENE‒WSW extension. Here, we present GNSS-derived geodetic data along a 170 km-long transect orthogonal to the main active normal faults of the Central Betic Cordillera. Our data indicate that the total extension rate along the Central Betic Cordillera is 2.0 ± 0.3 mm/yr. Extension is accommodated in the eastern (0.8 ± 0.3 mm/yr in the Guadix-Baza Basin) and western (1.3 ± 0.3 mm/yr in the Granada Basin) parts of the Central Betic Cordillera, while no extension is recorded in the central part of the study area. Moreover, our data permit us to quantify, for the first time, short-term fault slip rates of the Granada Fault System, which is one of the main seismogenic sources of the Iberian Peninsula. We deduce a fault slip rate of ∼1.3 ± 0.3 mm/ yr for the whole Granada Basin, with 0.9 ± 0.3 mm/yr being accommodated in the Granada Fault System and 0.4 ± 0.3 mm/yr being accommodated in the southwestern sector of the Granada Basin, where no active faults have been previously described at the surface. The heterogeneous extension in the Central Betic Cordillera could be accommodated by shallow high-angle normal faults that merge with a detachment at depth. Part of the active extension could be derived from gravitational instability because of underlying over-thickened crustThe Generalitat Valenciana (Valencian Regional GovernmentResearch project AICO/2021/196), Spanish Ministry of ScienceInnovation and University (Research Projects RTI2018-100737- B-I00 and PID2021-127967NB-I00),The University of Alicante (Research Project VIGROB053)The University of Jaén (POAIUJA 2021–2022, CEACTEMA and Programa Operativo FEDER Andalucía, 2014–2020—call made by UJA, 2018, Ref. 1263446), P18-RT- 3275 (Junta de Andalucía/FEDER),Junta de Andalucía regional government (RNM282 and RNM 148 research groups)The Institut Cartogràfic Valencià, Agencia Valenciana de Seguridad y Respuesta a las Emergencias (Generalitat Valenciana)Consorcio Provincial para el Servicio de Prevención y Extinción de Incendios y Salvamento de AlicanteDiputaciones Provinciales de Alicante y CastellónAyuntamiento de Almorad