The Generalife. First works of management and conservation

[EN] After the restitution of the Generalife to the Spanish State in 1921, Benigno de la Vega Inclán (1858-1942) the Marquis de la Vega-Inclán organized a board of trustees independent from that of the Alhambra to open the Nasrid complex to future visitors. Eladio Laredo and Carranza (1864-1941) became the architect in charge of the first surveys, the study of access, irrigation, and recovery of the deteriorated areas until 1925, when the architect Leopoldo Torres Balbás took over the task.[ES] Tras la restitución del Generalife al Estado español en 1921, Benigno de la Vega Inclán (1858-1942), el marqués de la Vega-Inclán organizó un patronato independiente del de la Alhambra para atender la apertura del conjunto nazarí a los futuros visitantes. Eladio Laredo y Carranza (1864-1941) fue el arquitecto encargado de avanzar los primeros levantamientos, estudio de accesos, riegos y recuperación de las zonas degradadas, hasta 1925, en que se unifican las competencias en la figura del arquitecto Leopoldo Torres Balbás.Ordieres Díez, I.; Lara García, J. (2023). El Generalife. Primeros trabajos de gestión y conservación. Loggia, Arquitectura & Restauración. (36):26-39. https://doi.org/10.4995/loggia.2023.1962326393

The computer in a roofing slate quarry

[Resumen] Sencillas configuraciones informáticas en base a ordenadores personales con programas comerciales de modelización y diseño asistido por ordenador, facilitan el reiterativo trabajo de planificación minera de una explotación de pizarra a cielo abierto. Su utilización es aplicable a tres fases del proyecto minero: Modelización del yacimiento (investigación), proyecto de explotación (viabilidad) y labores mineras (ejecución).[Abstract] Simple integrated systems based on personal computers and cornmercial programmes about modelling and CAD, make easy the reiterative work on exploitation planning in roofing slate quarries. We can use this systems in the three phases of the mining project: bed modelling (Research), exploitation (Viability)wand mining (Performance)

Atmospheric plasma-polymerization of hydrophobic and wear-resistant coatings on glass substrates

In order to find a coating that promotes both the wear resistance and the hydrophobicity of glass, a non-thermal atmospheric jet plasma-polymerization system with mixtures of two precursors at different proportions were used. (Heptadecafluoro-1,1,2,2-tetrahydrodecyl)trimethoxysilane (FLUSI) was used to promote the hydrophobicity, due to its fluorocarbon chain. Aminopropyltriethoxysilane (APTES) was used to enhance the wear resistance of the surface. The key aspect of the present work consists of determining the optimal mixture of precursors that produces a satisfactory coating in both characteristics; since coatings based on FLUSI have a low wear resistance and those based on APTES have a hydrophilic character. Scanning electron microscopy (SEM), atomic force microscopy (AFM), Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), lap-shear tests, static water contact angle (WCA), tribological tests, profilometry measurements and energy dispersive X-ray spectroscopy (EDX) were used to analyze the coatings. It is believed that the upper limit of hydrophobicity that can be attained by modifying of the surface chemistry (WCA of ~120°) has been achieved. It was observed that the wear resistance depends on the thickness and the SiOSi content of the coatings. These appear to be directly related to the proportion of APTES in the mixture. The sample that was coated with 50% of APTES and 50% of FLUSI provided the best combination of hydrophobicity and wear resistance. It showed the highest WCA (123.2°±1.5) because it has a high fluorocarbon content and the highest CF3 content. Its wear resistance is considerably better than that of the uncoated glass and is one of the highest exhibited by the hydrophobic samples

From controlling single processes to the complex automation of process chains by artificially intelligent control systems: the ControlInSteel project

The ControlInSteel project, a cooperation of four research institutes, revisited research projects of the last 20 years focusing on automation and control solutions applied to the downstream steel production route. During this investigation we found hints to those solutions, which were beneficial for specific problems. For our analysis, 46 projects were systematically reviewed. Taxonomies for the problem space, the solution space, the barriers and issues and the impact were developed and each project categorized along these taxonometrical dimensions. As a result, the interdependencies between solutions and impact could be analysed in a quantifiable way, which led to a new way of evaluating project success. It also brought new insights about the most promising techniques already applied and those techniques, that have been apparently not yet been applied to steel production, although being highly successful in other domains. This leads to potential future research chances for the steel production and their complex process chains. The paper will also finally demonstrate how a similar taxonometrical approach can be used to conserve expert knowledge in automation to feed a truly artificially intelligent control solution - not only exploiting machine learning methods but essentially using machine reasoning on top of the digitized expert knowledge to achieve improved process automation

Advanced predictive quality control strategy involving different facilities

There are many industries that use highly technological solutions to improve quality in all of their products. The steel industry is one example. Several automatic surface-inspection systems are used in the steel industry to identify various types of defects and to help operators decide whether to accept, reroute, or downgrade the material, subject to the assessment process. This paper focuses on promoting a strategy that considers all defects in an integrated fashion. It does this by managing the uncertainty about the exact position of a defect due to different process conditions by means of Gaussian additive influence functions. The relevance of the approach is in making possible consistency and reliability between surface inspection systems. The results obtained are an increase in confidence in the automatic inspection system and an ability to introduce improved prediction and advanced routing models. The prediction is provided to technical operators to help them in their decision-making process. It shows the increase in improvement gained by reducing the 40 % of coils that are downgraded at the hot strip mill because of specific defects. In addition, this technology facilitates an increase of 50 % in the accuracy of the estimate of defect survival after the cleaning facility in comparison to the former approach. The proposed technology is implemented by means of software-based, multi-agent solutions. It makes possible the independent treatment of information, presentation, quality analysis, and other relevant functions

DNA-based biosensor for the electrocatalytic determination of antioxidant capacity in beverages

Reactive oxygen species (ROS) are produced as a consequence of normal aerobic metabolism and are able to induce DNA oxidative damage. At the cellular level, the evaluation of the protective effect of antioxidants can be achieved by examining the integrity of the DNA nucleobases using electrochemical techniques. Herein, the use of an adenine-rich oligonucleotide (dA21) adsorbed on carbon paste electrodes for the assessment of the antioxidant capacity is proposed. The method was based on the partial damage of a DNA layer adsorbed on the electrode surface by OH• radicals generated by Fenton reaction and the subsequent electrochemical oxidation of the intact adenine bases to generate an oxidation product that was able to catalyze the oxidation of NADH. The presence of antioxidant compounds scavenged hydroxyl radicals leaving more adenines unoxidized, and thus, increasing the electrocatalytic current of NADHmeasured by differential pulse voltammetry (DPV). Using ascorbic acid (AA) as a model antioxidant species, the detection of as low as 50nMof AA in aqueous solution was possible. The protection efficiency was evaluated for several antioxidant compounds. The biosensor was applied to the determination of the total antioxidant capacity (TAC) in beverages

Fault diagnosis and comparing risk for the steel coil manufacturing process using statistical models for binary data

[EN] Advanced statistical models can help industry to design more economical and rational investment plans. Fault detection and diagnosis is an important problem in continuous hot dip galvanizing. Increasingly stringent quality requirements in the automotive industry also require ongoing efforts in process control to make processes more robust. Robust methods for estimating the quality of galvanized steel coils are an important tool for the comprehensive monitoring of the performance of the manufacturing process. This study applies different statistical regression models: generalized linear models, generalized additive models and classification trees to estimate the quality of galvanized steel coils on the basis of short time histories. The data, consisting of 48 galvanized steel coils, was divided into sets of conforming and nonconforming coils. Five variables were selected for monitoring the process: steel strip velocity and four bath temperatures. The present paper reports a comparative evaluation of statistical models for binary data using Receiver Operating Characteristic (ROC) curves. A ROC curve is a graph or a technique for visualizing, organizing and selecting classifiers based on their performance. The purpose of this paper is to examine their use in research to obtain the best model to predict defective steel coil probability. In relation to the work of other authors who only propose goodness of fit statistics, we should highlight one distinctive feature of the methodology presented here, which is the possibility of comparing the different models with ROC graphs which are based on model classification performance. Finally, the results are validated by bootstrap procedures.The authors are indebted to the anonymous referees whose suggestions improved the original manuscript. This work was supported by a grant from PAID-06-08 (Programa de Apoyo a la Investigacion y Desarrollo) of the Universitat Politecnica de Valencia.Debón Aucejo, AM.; García-Díaz, JC. (2012). Fault diagnosis and comparing risk for the steel coil manufacturing process using statistical models for binary data. Reliability Engineering and System Safety. 100:102-114. https://doi.org/10.1016/j.ress.2011.12.022S10211410

Electrocatalytic evaluation of DNA damage by superoxide radical for antioxidant capacity assessment

The integrity of DNA purine bases was herein used to evaluate the antioxidant capacity. Unlike other DNA-based antioxidant sensors reported so far, the damaging agent chosen was the O 2 radical enzymatically generated by the xanthine/xanthine oxidase system. An adenine-rich oligonucleotide was adsorbed on carbon paste electrodes and subjected to radical damage in the presence/absence of several antioxidant compounds. As a result, partial damage on DNA was observed. A minor product of the radical oxidation was identified by cyclic voltammetry as a diimine adenine derivative also formed during the electrochemical oxidation of adenine/guanine bases. The protective efficiency of several antioxidant compounds was evaluated after electrochemical oxidation of the remaining unoxidized adenine bases, by measuring the electrocatalytic current of NADH mediated by the adsorbed catalyst species generated. A comparison between O 2 and OH radicals as a source of DNA lesions and the scavenging efficiency of various antioxidant compounds against both of them is discussed. Finally, the antioxidant capacity of beverages was evaluated and compared with the results obtained with an optical method