Environmental weathering of natural and artificial stones used in historical architecture: influence of microstructure and new restoration methods

For some study cases (the Cathedral of Modena, Italy, XII-XIV century; the Ducal Palace in Mantua, Italy, XVI century; the church of San Francesco in Fano, Italy, XIV-XIX century), considered as representative of the use of natural and artificial stones in historical architecture, the complex interaction between environ-mental aggressiveness, materials’ microstructural characteristics and degradation was investigated. From the results of such analyses, it was found that materials microstructure plays a fundamental role in the actual extent to which weathering mechanisms affect natural and artificial stones. Consequently, the need of taking into account the important role of material microstructure, when evaluating the environmental aggressiveness to natural and artificial stones, was highlighted. Therefore, a possible quantification of the role of microstructure on the resistance to environmental attack was investigated. By exposing stone samples, with significantly different microstructural features, to slightly acidic aqueous solutions, simulating clean and acid rain, a good correlation between weight losses and the product of carbonate content and specific surface area (defined as the “vulnerable specific surface area”) was found. Alongside the evaluation of stone vulnerability, the development of a new consolidant for weathered carbonate stones was undertaken. The use of hydroxya-patite, formed by reacting the calcite of the stone with an aqueous solution of di-ammonium hydrogen phosphate, was found to be a promising consolidating tech-nique for carbonates stones. Indeed, significant increases in the mechanical prop-erties can be achieved after the treatment, which has the advantage of simply con-sisting in a non-hazardous aqueous solution, able to penetrate deeply into the stone (> 2 cm) and bring significant strengthening after just 2 days of reaction. Furthermore, the stone sorptivity is not eliminated after treatment, so that water and water vapor exchanges between the stone and the environment are not com-pletely blocked.

Cantor lectures on the modern methods of artificial illumination : delivered before the Royal Society of Arts on February 15, 22, and March 1 and 8, 1909 /

Mode of access: Internet.

Flora scotica; or, a description of Scottish plants, arranged both according to the artificial and natural methods. In two parts.

Mode of access: Internet.

Artificial vs. natural methods of incubation and brooding of the ringneck pheasant.

Thesis (M. S.) - Cornell Univ., 1921.

A practical treatise on warming buildings by hot water; on ventilation, and the various methods of distributing artificial heat, and their effects on animal and vegetable physiology. To which are added, an inquiry into the laws of radiant and conducted heat, the chemical constitution of coal, and the combustion of smoke.

"In the present work there have been incorporated several papers ... which have been read before the Institution of Civil Engineers; and also the author's articles on 'Stoves' and 'Ventilation,' published in the Encyclopædia metropolitana."--Pref.

Flora scotia; or a description of Scottish plants arranged both according to the artificial and natural methods.

Mode of access: Internet.

Improving modern apparatuses for prolonged artificial respiration,

"Translation of an article ... in the Russian-language journal vestnik khirurgii (Herald of surgery), vol. 90, no. 3, March 1963, pages 81-87."

Application of Artificial Intelligence Methods to Computer Design of Inorganic Compounds

In this paper the main problems for computer design of materials, which would have predefined properties, with the use of artificial intelligence methods are presented. The DB on inorganic compound properties and the system of DBs on materials for electronics with completely assessed information: phase diagram DB of material systems with semiconducting phases and DB on acousto-optical, electro-optical, and nonlinear optical properties are considered. These DBs are a source of information for data analysis. Using the DBs and artificial intelligence methods we have predicted thousands of new compounds in ternary, quaternary and more complicated chemical systems and estimated some of their properties (crystal structure type, melting point, homogeneity region etc.). The comparison of our predictions with experimental data, obtained later, showed that the average reliability of predicted inorganic compounds exceeds 80%. The perspectives of computational material design with the use of artificial intelligence methods are considered.

Distribution of respiratory droplets in enclosed environments under different air distribution methods

Dispersion characteristics of respiratory droplets in indoor environments are of special interest in controlling transmission of airborne diseases. This study adopts an Eulerian method to investigate the spatial concentration distribution and temporal evolution of exhaled and sneezed/coughed droplets within the range of 1.0~10.0μm in an office room with three air distribution methods, i.e. mixing ventilation (MV), displacement ventilation (DV), and under-floor air distribution (UFAD). The diffusion, gravitational settling, and deposition mechanism of particulate matters are well accounted in the one-way coupling Eulerian approach. The simulation results find that exhaled droplets with diameters up to 10.0μm from normal respiration process are uniformly distributed in MV, while they are trapped in the breathing height by thermal stratifications in DV and UFAD, resulting in a high droplet concentration and a high exposure risk to other occupants. Sneezed/coughed droplets are diluted much slower in DV/UFAD than in MV. Low air speed in the breathing zone in DV/UFAD can lead to prolonged residence of droplets in the breathing zone.

A differential kinetic spectrophotometric method for determination of three sulphanilamide artificial sweeteners with the aid of chemometrics

A simple and sensitive spectrophotometric method for the simultaneous determination of acesulfame-K, sodium cyclamate and saccharin sodium sweeteners in foodstuff samples has been researched and developed. This analytical method relies on the different kinetic rates of the analytes in their oxidative reaction with KMnO4 to produce the green manganate product in an alkaline solution. As the kinetic rates of acesulfame-K, sodium cyclamate and saccharin sodium were similar and their kinetic data seriously overlapped, chemometrics methods, such as partial least squares (PLS), principal component regression (PCR) and classical least squares (CLS), were applied to resolve the kinetic data. The results showed that the PLS prediction model performed somewhat better. The proposed method was then applied for the determination of the three sweeteners in foodstuff samples, and the results compared well with those obtained by the reference HPLC method.

Design optimisation using advanced artificial intelligent system coupled to hybrid-game strategies

One of the main aims in artificial intelligent system is to develop robust and efficient optimisation methods for Multi-Objective (MO) and Multidisciplinary Design (MDO) design problems. The paper investigates two different optimisation techniques for multi-objective design optimisation problems. The first optimisation method is a Non-Dominated Sorting Genetic Algorithm II (NSGA-II). The second method combines the concepts of Nash-equilibrium and Pareto optimality with Multi-Objective Evolutionary Algorithms (MOEAs) which is denoted as Hybrid-Game. Numerical results from the two approaches are compared in terms of the quality of model and computational expense. The benefit of using the distributed hybrid game methodology for multi-objective design problems is demonstrated.

GYAN: A methodology for rule extraction from artificial neural networks

Artificial neural network (ANN) learning methods provide a robust and non-linear approach to approximating the target function for many classification, regression and clustering problems. ANNs have demonstrated good predictive performance in a wide variety of practical problems. However, there are strong arguments as to why ANNs are not sufficient for the general representation of knowledge. The arguments are the poor comprehensibility of the learned ANN, and the inability to represent explanation structures. The overall objective of this thesis is to address these issues by: (1) explanation of the decision process in ANNs in the form of symbolic rules (predicate rules with variables); and (2) provision of explanatory capability by mapping the general conceptual knowledge that is learned by the neural networks into a knowledge base to be used in a rule-based reasoning system. A multi-stage methodology GYAN is developed and evaluated for the task of extracting knowledge from the trained ANNs. The extracted knowledge is represented in the form of restricted first-order logic rules, and subsequently allows user interaction by interfacing with a knowledge based reasoner. The performance of GYAN is demonstrated using a number of real world and artificial data sets. The empirical results demonstrate that: (1) an equivalent symbolic interpretation is derived describing the overall behaviour of the ANN with high accuracy and fidelity, and (2) a concise explanation is given (in terms of rules, facts and predicates activated in a reasoning episode) as to why a particular instance is being classified into a certain category.