ALBERT

Description: This paper describes a new method for predicting trihalomethanes (THMs) presence in networks of water supply systems, using a low-cost device that permits a fast monitoring of concentrations without need of complex analysis made in laboratories. This method, based on statistical models, allows the estimation of THM concentration by monitoring parameters whose determination is direct and easy, and therefore, THM presence can be carried out in real-time. These parameters values are introduced in a multiple regression model resulting in the concentration of THMs levels. This model has taken into account parameters compulsory in water quality analysis and it has been shown that six parameters are enough to determine accurately THM concentration. In addition, the feasibility of a low-cost device that directly gives THM concentration is demonstrated. This device can be easily designed to be transported to different points of the water supply network where it is intended to make control campaigns.

Description: Ecosystem state can be characterized by a set of attributes that are related to the ecosystem functionality, which is a relevant issue in understanding the quality and quantity of ecosystem services and goods, adaptive capacity and resilience to perturbations. This study proposes a major identification of Ecosystem Functional Types (EFTs) in Spain to characterize the patterns of ecosystem functional diversity and status, from several functional attributes as the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST) and Albedo. For this purpose, several metrics, related to the spatial variability in seasonal and annual patterns (e.g., relative range), have been derived from remote sensing time series of 1 km MODIS over the period 2000–2009. Moreover, precipitation maps from data provided by the AEMet (Agencia Estatal de Meteorología) and the corresponding aridity and humidity indices were also included in the analysis. To create the EFTs, the potential of the joint use of Kohonen’s Self-Organizing Map (SOM) and the k-means clustering algorithm was tested. The EFTs were analyzed using different remote sensing (i.e., Gross Primary Production) and climatic variables. The relationship of the EFTs with existing land cover datasets and climatic data were analyzed through a correspondence analysis (CA). The trained SOM have shown feasible in providing a comprehensive view on the functional attributes patterns and a remarkable potential for the quantification of ecosystem function. The results highlight the potential of this technique to delineate ecosystem functional types as well as to monitor the spatial pattern of the ecosystem status as a reference for changes due to human or climate impacts.

Description: Materials, Vol. 11, Pages 1580: Demineralized Bone Matrix Coating Si-Ca-P Ceramic Does Not Improve the Osseointegration of the Scaffold Materials doi: 10.3390/ma11091580 Authors: Andrés Parrilla-Almansa Nuria García-Carrillo Patricia Ros-Tárraga Carlos M. Martínez Francisco Martínez-Martínez Luis Meseguer-Olmo Piedad N. De Aza The aim of this study was to manufacture and evaluate the effect of a biphasic calcium silicophosphate (CSP) scaffold ceramic, coated with a natural demineralized bone matrix (DBM), to evaluate the efficiency of this novel ceramic material in bone regeneration. The DBM-coated CSP ceramic was made by coating a CSP scaffold with gel DBM, produced by the partial sintering of different-sized porous granules. These scaffolds were used to reconstruct defects in rabbit tibiae, where CSP scaffolds acted as the control material. Micro-CT and histological analyses were performed to evaluate new bone formation at 1, 3, and 5 months post-surgery. The present research results showed a correlation among the data obtained by micro-CT and the histomorphological results, the gradual disintegration of the biomaterial, and the presence of free scaffold fragments dispersed inside the medullary cavity occupied by hematopoietic bone marrow over the 5-month study period. No difference was found between the DBM-coated and uncoated implants. The new bone tissue inside the implants increased with implantation time. Slightly less new bone formation was observed in the DBM-coated samples, but it was not statistically significant. Both the DBM-coated and the CSP scaffolds gave excellent bone tissue responses and good osteoconductivity.

Description: Water, Vol. 9, Pages 595: Applications of Hydro-Chemical and Isotopic Tools to Improve Definitions of Groundwater Catchment Zones in a Karstic Aquifer: A Case Study Water doi: 10.3390/w9080595 Authors: Alberto Jiménez-Madrid Silvino Castaño Iñaki Vadillo Carlos Martinez Francisco Carrasco Albert Soler Some researchers have proposed the groundwater protection zone (GPZ) method as a methodological framework for defining safeguard zones of groundwater bodies. Its goal is to protect the quality of water intended for human consumption and to facilitate a common implementation of this method in all European Union member states. One of the criteria used to establish GPZs is to define contributing catchment areas (CCAs). This methodology has been applied to the Sierra de Cañete, a region comprising a carbonate aquifer in the province of Malaga, Spain. The tools used to define CCAs are hydro-chemical and isotopic characterizations, namely water isotopes (i.e., 2H, 18O and tritium) and the isotopes of dissolved sulfates (i.e., 34S and 18O). Traditionally, the Sierra de Cañete aquifer has been divided into six sectors. Hydro-chemical and isotopic characterization differentiated between two large areas in the carbonate aquifer. The southern part presents younger water that is the result of faster recharge and that shows a high level of karstification, while the northern area has a slower flow, and recharge is produced over several years. In addition, the northern part is hydraulically connected to an alluvial aquifer (i.e., Llanos de Almargen) that borders the Sierra de Cañete to the north. This aquifer has high levels of pollution due to agricultural and livestock activities carried out in the Llanos de Almargen area. This pollution is transmitted to the carbonate aquifer when groundwater depletion occurs. Therefore, the Sierra de Cañete GPZ needs to be extended to include the Llanos de Almargen aquifer.

Description: Materials, Vol. 11, Pages 591: Effect of Atmospheric Corrosion on the Mechanical Properties of SAE 1020 Structural Steel Materials doi: 10.3390/ma11040591 Authors: Carola Martínez Francisco Briones María Villarroel Rosa Vera Resistance to atmospheric corrosion in different environments located in Chile and the corrosion’s effect on the mechanical properties of SAE 1020 steel were studied. Atmospheric corrosivity categories at each station under study were determined. These categories were C2, for Laja; C3 and C4, for the Arica and Antarctic stations, respectively; and the most aggressive, C5 and higher at Quintero. These specific environments significantly influenced the mechanical responses of steel exposed for 36 months. Rupture elongation, the modulus of toughness, ultimate tensile strength, and hardness of the material all decreased as a function of environmental atmospheric aggressiveness. Lowered ductility is the result of the increased corrosion rate due to the high deposition of chlorides. This is due to the morphology of material degradation, which consequently occurs as pores, microstrains, and other defects that promote early rupture of the steel.

Description: Remote Sensing, Vol. 10, Pages 1167: Global Estimation of Biophysical Variables from Google Earth Engine Platform Remote Sensing doi: 10.3390/rs10081167 Authors: Manuel Campos-Taberner Álvaro Moreno-Martínez Francisco Javier García-Haro Gustau Camps-Valls Nathaniel P. Robinson Jens Kattge Steven W. Running This paper proposes a processing chain for the derivation of global Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fraction Vegetation Cover (FVC), and Canopy water content (CWC) maps from 15-years of MODIS data exploiting the capabilities of the Google Earth Engine (GEE) cloud platform. The retrieval chain is based on a hybrid method inverting the PROSAIL radiative transfer model (RTM) with Random forests (RF) regression. A major feature of this work is the implementation of a retrieval chain exploiting the GEE capabilities using global and climate data records (CDR) of both MODIS surface reflectance and LAI/FAPAR datasets allowing the global estimation of biophysical variables at unprecedented timeliness. We combine a massive global compilation of leaf trait measurements (TRY), which is the baseline for more realistic leaf parametrization for the considered RTM, with large amounts of remote sensing data ingested by GEE. Moreover, the proposed retrieval chain includes the estimation of both FVC and CWC, which are not operationally produced for the MODIS sensor. The derived global estimates are validated over the BELMANIP2.1 sites network by means of an inter-comparison with the MODIS LAI/FAPAR product available in GEE. Overall, the retrieval chain exhibits great consistency with the reference MODIS product (R2 = 0.87, RMSE = 0.54 m2/m2 and ME = 0.03 m2/m2 in the case of LAI, and R2 = 0.92, RMSE = 0.09 and ME = 0.05 in the case of FAPAR). The analysis of the results by land cover type shows the lowest correlations between our retrievals and the MODIS reference estimates (R2 = 0.42 and R2 = 0.41 for LAI and FAPAR, respectively) for evergreen broadleaf forests. These discrepancies could be attributed mainly to different product definitions according to the literature. The provided results proof that GEE is a suitable high performance processing tool for global biophysical variable retrieval for a wide range of applications.

Description: Aging infrastructure is the main challenge currently faced by water suppliers. Estimation of assets lifetime requires reliable criteria to plan assets repair and renewal strategies. To do so, pipe break prediction is one of the most important inputs. This paper analyzes the statistical dependence of pipe breaks on explanatory variables, determining their optimal combination and quantifying their influence on failure prediction accuracy. A large set of registered data from Madrid water supply network, managed by Canal de Isabel II, has been filtered, classified and studied. Several statistical Bayesian models have been built and validated from the available information with a technique that combines reference periods of time as well as geographical location. Statistical models of increasing complexity are built from zero up to five explanatory variables following two approaches: a set of independent variables or a combination of two joint variables plus an additional number of independent variables. With the aim of finding the variable combination that provides the most accurate prediction, models are compared following an objective validation procedure based on the model skill to predict the number of pipe breaks in a large set of geographical locations. As expected, model performance improves as the number of explanatory variables increases. However, the rate of improvement is not constant. Performance metrics improve significantly up to three variables, but the tendency is softened for higher order models, especially in trunk mains where performance is reduced. Slight differences are found between trunk mains and distribution lines when selecting the most influent variables and models.

Description: Materials, Vol. 10, Pages 830: Sliding Wear Behavior of UNS R56400 Titanium Alloy Samples Thermally Oxidized by Laser Materials doi: 10.3390/ma10070830 Authors: Juan Manuel Vazquez Martinez Francisco J. Botana Pedemonte Marta Botana Galvin Jorge Salguero Gomez Mariano Marcos Barcena Wear of elements subjected to friction and sliding is among the main causes of low tribological performance and short lifetime of strategic materials such as titanium alloys. These types of alloys are widely used in different areas such as aerospace and the biomechanics industry. In this sense, surface modification treatments allow for the overcoming of limitations and improvement of features and properties. In the case of titanium alloys, improvements in the main weaknesses of these materials can be obtained. Laser texturing of UNS R56400 (Ti6Al4V) alloy, according to Unified Numbering System designation, surface layers in a non-protective atmosphere produces an increase of the oxides, especially of titanium dioxide (TiO2) species. The presence of oxides in the alloy results in color tonality variations as well as hardness increases. In addition, specific roughness topographies may be produced by the track of laser beam irradiation. In this research, thermochemical oxidation of UNS R56400 alloy has been developed through laser texturing, using scan speed of the beam (Vs) as the process control variable, and its influence on the sliding wear behavior was analyzed. For this purpose, using pin on disc tribological tests, wear was evaluated from the friction coefficient, and wear mechanisms involved in the process were analyzed. Combined studies of wear mechanisms and the friction coefficient verified that by means of specific surface treatments, an increase in the wear resistance of this type of alloys is generated. The most advantageous results for the improvement of tribological behavior have been detected in textured surfaces using a Vs of 150 mm/s, resulting in a decrease in the friction coefficient values by approximately 20%.

Description: In the last years, many passive electromagnetic sensors have been reported. Some of these sensors are used for measuring harmful substances. Moreover, the response of these sensors is usually obtained with laboratory equipment. This approach highly increases the total cost and complexity of the sensing system. In this work, a novel low-cost and portable Internet-of-Things (IoT) reader for passive wireless electromagnetic sensors is proposed. The reader is used to interrogate the sensors within a short-range wireless link avoiding the direct contact with the substances under test. The IoT functionalities of the reader allows remote sensing from computers and handheld devices. For that purpose, the proposed design is based on four functional layers: the radiating layer, the RF interface, the IoT mini-computer and the power unit. In this paper a demonstrator of the proposed reader is designed and manufactured. The demonstrator shows, through the remote measurement of different substances, that the proposed system can estimate the dielectric permittivity. It has been demonstrated that a linear approximation with a small error can be extracted from the reader measurements. It is remarkable that the proposed reader can be used with other type of electromagnetic sensors, which transduce the magnitude variations in the frequency domain.