ALBERT

Description: The high flame-retardant loading required for ethylene-vinyl acetate copolymer blends with polyethylene (EVA-PE) employed for insulation and sheathing of electric cables represents a significant limitation in processability and final mechanical properties. In this work, melamine triazine (TRZ) and modified bentonite clay have been investigated in combination with aluminum trihydroxide (ATH) for the production of EVA-PE composites with excellent fire safety and improved mechanical properties. Optimized formulations with only 120 parts per hundred resin (phr) of ATH can achieve self-extinguishing behavior according to the UL94 classification (V0 rating), as well as reduced combustion kinetics and smoke production. Mechanical property evaluation shows reduced stiffness and improved elongation at break with respect to commonly employed EVA-PE/ATH composites. The reduction in filler content also provides improved processability and cost reductions. The results presented here allow for a viable and halogen-free strategy for the preparation of high performing EVA-PE composites.

Description: The Canary Islands are a well known tourist destination with generally stable and clement weather conditions. However, occasionally extreme weather conditions occur, which although very unusual, may cause severe damage to the local economy. The ViMetRi-MAC EU funded project has among its goals, managing climate-change-associated risks. The Spanish National Meteorology Agency (AEMET) has a network of weather stations across the eight Canary Islands. Using data from those stations, we propose a novel methodology for the prediction of maximum wind speed in order to trigger an early alert for extreme weather conditions. The methodology proposed has the added value of using an innovative kind of machine learning that is based on the data stream mining paradigm. This type of machine learning system relies on two important features: models are learned incrementally and adaptively. That means the learner tunes the models gradually and endlessly as new observations are received and also modifies it when there is concept drift (statistical instability), in the modeled phenomenon. The results presented seem to prove that this data stream mining approach is a good fit for this kind of problem, clearly improving the results obtained with the accumulative non-adaptive version of the methodology.

Description: The objective of this study is to describe the impact of the Advanced Practice Nurse role on the clinical practice and patient benefit, as well as to provide reasons for its implementation and expansion in Spain. Through the scoping review method, this study has been carried out according to five thematic blocks: life quality, cost-effectiveness, health results, satisfaction, and accessibility. The critical appraisal was performed with the Critical Appraisal Skills Programme (CASP) tool and the level of evidence and strength of recommendation have been analysed following the Oxford Centre for Evidence-Based Medicine (OCEBM) system. The results show that it is possible to formally implement advanced practice nursing in the Spanish context. The analysis of the Spanish regulatory framework reveals that the generalisation of the Case Manager Nurse is the starting point for the development of advanced practice nursing in Spain. This implementation would have a positive impact on patients in terms of health results, satisfaction, and life quality, given that the advanced practice nurse performs a more effective follow-up of chronic patients with a better control of risk factors, symptoms and health outcomes, and an earlier detection of complications. Considering these results, regional governments should promote the role of the Advanced Practice Nurse to contribute to its expansion.

Description: Urban transport drivers, specifically taxi and motorcycle taxi drivers, are exposed to particular environmental, societal, and health situations related to their occupation. To compare work capacity and quality of life of taxi and motorcycle taxi drivers, and correlate quality of life and work ability, a cross-sectional descriptive study was conducted among 232 motorcycle taxi drivers and 60 male taxi drivers in urban cities of Brazil. Three instruments were used for evaluation: a questionnaire on sociodemographic and occupational issues, the Work Capacity Index (WCI), and the WHOQOL-bref (World Health Organization Quality of Life–Bref). Taxi drivers presented better evaluation scores in the physical and psychological domains and general quality of life (QOL) (p 〈 0.01), and better self-perceived work ability (lower physical and mental demands, fewer diagnosed diseases, less incapacity for professional practice, p 〈 0.001). In addition, there was a positive relationship between QOL and WCI (p = 0.001). Motorcycle taxi drivers had worse self-perceived QOL and of work ability, and there was a positive correlation between QOL and work ability.

Description: The verification of remotely sensed estimates of surface variables is essential for any remote sensing study. The objective of this study was to compare leaf area index (LAI), surface temperature (Ts), and actual evapotranspiration (ETa), estimated using the remote sensing-based METRIC model and in situ measurements collected at the satellite overpass time. The study was carried out at a commercial corn field in eastern South Dakota. Six clear-sky images from Landsat 7 and Landsat 8 (Path 29, Row 29) were processed and used for the assessment. LAI and Ts were measured in situ, and ETa was estimated using an atmometer and independent crop coefficients. The results revealed good agreement between the variables measured in situ and estimated by the METRIC model. LAI showed r2 = 0.76, and RMSE = 0.59 m2 m−2, the Ts comparison had an agreement of r2 = 0.87 and RMSE 1.24 °C, and ETa presented r2 = 0.89 and RMSE = 0.71 mm day−1.

Description: In recent years, Online Social Networks (OSNs) have received a great deal of attention for their potential use in the spatial and temporal modeling of events owing to the information that can be extracted from these platforms. Within this context, one of the most latent applications is the monitoring of natural disasters. Vital information posted by OSN users can contribute to relief efforts during and after a catastrophe. Although it is possible to retrieve data from OSNs using embedded geographic information provided by GPS systems, this feature is disabled by default in most cases. An alternative solution is to geoparse specific locations using language models based on Named Entity Recognition (NER) techniques. In this work, a sensor that uses Twitter is proposed to monitor natural disasters. The approach is intended to sense data by detecting toponyms (named places written within the text) in tweets with event-related information, e.g., a collapsed building on a specific avenue or the location at which a person was last seen. The proposed approach is carried out by transforming tokenized tweets into word embeddings: a rich linguistic and contextual vector representation of textual corpora. Pre-labeled word embeddings are employed to train a Recurrent Neural Network variant, known as a Bidirectional Long Short-Term Memory (biLSTM) network, that is capable of dealing with sequential data by analyzing information in both directions of a word (past and future entries). Moreover, a Conditional Random Field (CRF) output layer, which aims to maximize the transition from one NER tag to another, is used to increase the classification accuracy. The resulting labeled words are joined to coherently form a toponym, which is geocoded and scored by a Kernel Density Estimation function. At the end of the process, the scored data are presented graphically to depict areas in which the majority of tweets reporting topics related to a natural disaster are concentrated. A case study on Mexico’s 2017 Earthquake is presented, and the data extracted during and after the event are reported.

Description: Continuous authentication systems for mobile devices focus on identifying users according to their behaviour patterns when they interact with mobile devices. Among the benefits provided by these systems, we highlight the enhancement of the system security, having permanently authenticated the users; and the improvement of the users’ quality of experience, minimising the use of authentication credentials. Despite the benefits of these systems, they also have open challenges such as the authentication accuracy and the adaptability to new users’ behaviours. Continuous authentication systems should manage these challenges without forgetting critical aspects of mobile devices such as battery consumption, computational limitations and response time. With the goal of improving these previous challenges, the main contribution of this paper is the design and implementation of an intelligent and adaptive continuous authentication system for mobile devices. The proposed system enables the real-time users’ authentication by considering statistical information from applications, sensors and Machine Learning techniques based on anomaly detection. Several experiments demonstrated the accuracy, adaptability, and resources consumption of our solution. Finally, its utility is validated through the design and implementation of an online bank application as proof of concept, which allows users to perform different actions according to their authentication level.

Description: The existence of a green premium in house (asking) prices in Alicante province, Spain, are analyzed using circa 9000 property observations. In developing the sample, information from energy efficiency certificates was matched with two other databases. The model tests for green premium by climatic zones using pool Ordinary Least Squares (pool-OLS) and Instrumental Variables (IV) hedonic models, adds new knowledge concerning the existence of green premiums from Southern Europe, explores differences in their estimation by climatic zone, debates the nature of the estimated green parameters, and explains the role of endogeneity in hedonic green premium models. The empirical evidence assesses the sensitivity of asking price to either energy consumption (KWh) or carbon dioxide emissions (CO2) with an apparent premium of 3%, and captures an association with efficiency rating from G to F of 1.8% and from F to E of 1.1%. Significantly, the results relating to price responses show a distinct variation between the coast and the cooler climatic zone of the interior. The paper shows that energy efficiency incentive policies should discriminate by climatic areas, and provides a price reference by which to assess the amount of incentives needed to achieve European Union (EU) objectives.

Description: Nitrate vulnerable zones (NVZs) are areas considered to be at high risk of water pollution due to an excess of nitrates and, according to European regulations, codes of good agricultural practice are to be implemented by farmers, such as reducing doses of the applied fertilizers, or the use of fertilizers that minimize nitrate leaching. In this work, the influence of organic fertilization with dried pig manure (DPM) as compared to mineral fertilization with ammonium sulfate nitrate with 3,4-dimethylpyrazole phosphate nitrification inhibitor was studied in a barley crop planted in a NVZ in Fompedraza (Valladolid, Spain). Organic and mineral fertilizers were applied at different rates (85, 133 and 170 kg N·ha−1·year−1 vs. 90 and 108 kg N·ha−1·year−1, respectively) over a three-year period, in a randomized complete block design with six treatments and four blocks. DPM-based fertilization resulted in a 65% increase in crop yield as compared to the control soil, reaching 1800 kg·ha−1 for an application rate of 85 kg N·ha−1·year−1. Higher DPM rates were found to increase the electrical conductivity and assimilable phosphorus, potassium, magnesium and organic matter contents, but did not lead to yield enhancements. Final nitrate and ammonium concentrations were lower than 10 mg·kg−1 and 20 mg·kg−1, respectively, and no increase in soil salinity or heavy metal pollution was observed. DPM fertilization should be supplemented with small doses of inorganic fertilizers to obtain crop yields similar to those attained with mineral fertilization.

Description: After almost a decade of crisis, the housing market in Spain shows significant signs of recovery, with increases in both the average price and the number of sales transactions. Housing is the main asset for the majority of households, and it also has the most resources devoted to it, thus, when it comes to buying a residence, people do not only look at the asset’s intrinsic characteristics, but also consider other particularities such as the neighbourhood, accessibility to services, availability of public transport or adequate funding. The study aimed to analyse and quantify the relationship that exists between the asking price of second-hand housing on the market in Alicante and the attributes that characterise them. This was done using a multivariate analysis to estimate a hedonic pricing model by ordinary least squares and a quantile regression to analyse the impact of the characteristics in different price ranges. The results show the segmentation of the prices in the Alicante market, with higher prices in the northern coastal area over the southern and inland comarcas.