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This contribution presents a field study in which the long-term behaviour of two a−Si photovoltaic plants is studied. Two grid-connected a−Si:H photovoltaic plants located in Valencia (Spain) have been monitored during their first eight years of operation under real outdoor conditions. A per-unit approach and an STC normalisation have been made to analyse and compare photovoltaic plants with differences in electrical characteristics. An averaging process of the filtered and normalised data produces a monthly averaged value that is used to evaluate the ageing and seasonal effects experienced by the two photovoltaic plants. An analysis of the variations in the per unit output power finds that a seasonal effect is superimposed on the long-term stabilisation process. The study concludes that the long-term average stabilisation factor is equal to 1,35% per year, with a seasonal effect that shows a sinusoidal variation with an average amplitude of the sinusoidal oscillation equal to 2,71% per year. An estimation of the energy yield is performed considering the different ageing approaches presented in the study. Using the factors obtained from the experimental values, the ageing and seasonal effects are modelized, and a linear and an exponential expression is proposed to fit the long-term behaviour of both a−Si photovoltaic plants. Results obtained with the statistical analysis are compared with the experimental data and it is found that the exponential behaviour matches the experimental values. [Display omitted] • Long-term variations in PV efficiency in a−Si:H modules. • Ageing and seasonal effects in a−Si:H modules. • Linear and exponential expressions for a long-term fitting model of PV behaviour. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: To assess the association between baseline CT-based volumetric parameters and biochemical hepatic evaluations, such as, Child-Pugh, MELD score, and modified MELD-Na score, on the prediction of outcomes of patients with HCC undergoing transarterial chemoembolization (TACE).Materials and Methods: A retrospective of a prospectively maintained database, single arm, and single center study was performed including 41 patients with diagnosis of hepatocellular carcinoma treated with TACE. Study endpoints included liver dysfunction (new events of ascites, encephalopathy, and/or death) and overall survival rate. Multi-phase CT-based volumetric analysis was performed to calculate total liver volume and tumor volume using portal and late arterial phases, respectively. Residual volume was calculated subtracting the tumor volume minus the total liver volume. Child-Pugh, MELD score, and MELD-Na score were measured during the baseline evaluation.Results: At a median follow-up time of 8 months (IQR, 5-14), 16 patients (39%) were diagnosed with hepatic dysfunction. In patients with hepatic dysfunction, the median residual hepatic volume was 1002.1 cc (IQR, 633-1077.1 cc) compared to patients with normal liver function post-TACE with a median residual volume of 1233 cc (IQR, 1018.7-1437.6 cc) (p = 0.02). Survival analysis demonstrated an overall survival rate of 95%, 90%, 85% at 30 days, 12 months, and 24 months, respectively. The overall survival rate in patients with Child-Pugh A was 100%, 97%, and 97% at 6, 12, and 24 months, respectively; compared to patients with Child Pugh B with an overall survival of rate of 86%, 78%, and 78% at 6, 12, and 24 months, respectively (p = 0.07). Median baseline MELD-Na score was higher in patients that died during the study period compared to patients that survived (6.7 [IQR, 5-14.2] versus 4.1 [IQR, 2.14-6.85]) (p = 0.09).Conclusion: Low baseline CT-based residual volume is associated with the occurrence of hepatic dysfunction at a median time of 8 months. Baseline Child-Pugh A patients were found to have higher survival rate than Child-Pugh B. Interestingly, higher baseline MELD-Na score was associated with mortality. [ABSTRACT FROM AUTHOR]

• A problem of global solar regression from satellite data and physical models is tackled. • Machine Learning regression techniques are applied. • Comparison of Neural networks, SVRs and Gaussian Processes is carried out. • Machine Learning techniques improves the performance of physical models in solar radiation estimation. In this paper we evaluate the performance of several Machine Learning regression techniques in a problem of global solar radiation estimation from geostationary satellite data. Different types of neural networks, Support Vector Regression and Gaussian Processes have been selected as regression techniques to be evaluated, due to their good performance in similar problems in the past. The study area is located in the surroundings of the radiometric station of Toledo, Spain. In order to train the regression techniques considered, one complete year of hourly global solar radiation data is used as the target of the experiments, and different input variables are considered: a cloud index, a clear-sky solar radiation model and several reflectivity values from Meteosat visible images. To assess the results obtained by the Machine Learning algorithms, we have selected as a reference three different physical-based methods, a model based on the Heliosat-2 method (Heliosat-2), the Copernicus Atmosphere Monitoring Service (CAMS) and the SolarGIS model (Soevaluate the performance of Machine Learning regressors when the physical models are included as input variables, in a class of post-processing of these physical approaches. The results obtained show the capacity of Machine Learning regressors to obtain reliable global solar radiation estimation by using satellite measurements. [ABSTRACT FROM AUTHOR]

This contribution presents a field study in which the initial stabilization of thin-film amorphous silicon (a-Si:H) is investigated. Two grid-connected a-Si:H photovoltaic plants have been monitored and analyzed under real outdoor conditions. A per-unit approach is proposed to compare PV plants with differences in their electrical characteristic and the start-up date. The representation of a normalized per-unit PV power versus the accumulated incoming irradiation reveals an evolution that can be characterized through an exposure-response function. By this function, two populations of defects in the cells are detected. It is found that the stabilization process in the first year of operation produces a decrease of 10% in the peak power, equivalent to a decrease of 0.5% in cell efficiency. The use of the accumulated PSH for conducting the analysis of the initial stabilization produces similarities that cannot be obtained if a time scale is used. These results provide a powerful tool for PV plant designers because they enable a prediction to be made of the time-scale stabilization response in terms of unitary power, correlated with the peak sun hours received. [ABSTRACT FROM AUTHOR]

Recent studies reveal physical, economical, and socio-technical barriers when measuring performance of sustainable urban ration projects with existing assessment tools. This reality, enlarged in the Spanish context, has revealed the need of a friendly-user and holistic tool that can assist the agents involved in the decision-making process of urban regeneration projects. This paper presents the Guide of strategies for urban regeneration; a design-support tool developed by demand of the Government of the Valencian Community (Spain). Along this paper we describe how the Guide has been designed by integrating: in first place measures of exiting urban assessment tools, secondly lesson learned coming from the application of urban assessment tools to selected and rewarded urban best practices at European level, and thirdly the opinion of regional decision-makers and urban experts. As a result, this Guide offers strategies and recommendations on a self-questioning format that makes easy its implementation by any urban planner regardless of its expertise on the topic. It is based on an open-source philosophy with a nonprofit orientation, using transparent and easy-to-understand technical criteria. It can be applied to any kind of urban fabric and proposes equal representation of the thematic categories needed to be considered during an urban regeneration project design. [ABSTRACT FROM AUTHOR]

Experimental evidence indicates that bainitic ferrite formed by transformation at low temperatures (200–350 °C) contains quantities of carbon in solid solution far beyond those expected from para-equilibrium. A change in the conventional symmetry of the bainitic ferrite lattice from cubic to tetragonal explains the abnormal solid solubility detected. This carbon supersaturation was measured by atom probe tomography, and the tetragonality of the bainitic ferrite, was characterized by means of X-ray diffraction analysis and high resolution transmission electron microscopy. [ABSTRACT FROM AUTHOR]

Highlights: [•] This paper presents a hybrid CRO–ELM algorithm for solar radiation prediction. [•] Novel predictive meteorological variables are considered in this problem. [•] The CRO is a novel meta-heuristic search algorithm based on simulation of Coral Reefs. [•] The Extreme Learning Machine (ELM) is a state of the art method for training neural networks. [•] The proposed hybrid approach has shown excellent results in real data in Spain. [Copyright &y& Elsevier]

It is possible by means of high-resolution dilatometry, together with a model based on isotropic dilatation and atomic volumes, to estimate the dislocation density introduced in the microstructure as a consequence of the isothermal decomposition of austenite into bainitic ferrite. The relatively high dislocation density associated with this microstructure is attributed to the fact that the shape deformation accompanying this displacive transformation is accommodated by plastic relaxation. [Copyright &y& Elsevier]

Abstract: In this work, the carbon distribution in austenite during isothermal bainite formation and the incomplete reaction phenomenon was analyzed by means of X-ray diffraction and atom-probe tomography in high-silicon, manganese-alloyed steels. The results provide new evidence on the temporary cessation of bainitic ferrite formation at abnormally low transformation temperatures. [Copyright &y& Elsevier]

Abstract: Different approaches to predicting the M s temperatures of steels are reviewed and discussed with the objective of summarising the main characteristics, advantages and difficulties of each method, mostly from a practical point of view. Empirical methods, and methods based on thermodynamics are then assessed against published data. [Copyright &y& Elsevier]