Electrochemical anticorrosion performance evaluation of Al2O3 coatings deposited by MOCVD on an industrial brass substrate

Alumina (Al₂O₃) coatings of different thickness were deposited on OT59 brass substrate (BS) using the metal organic chemical vapour deposition (MOCVD) technique to evaluate the corrosion performance by EIS measurements. The used precursor was dimethyl-aluminium-isopropoxide. Electrochemical characterizations of the deposited films were performed in a standard very aggressive acidic solution (aerated 1N H₂SO₄ at 25 °C up to 168 h of immersion time) by means of direct current method (Tafel curves) and electrochemical impedance spectroscopy (EIS). The Rutherford backscattering spectroscopy (RBS) indicated that the films are very pure with the correct Al₂O₃ stoichiometry, while the IR absorption spectra showed that the films did not contain any OH groups. The surface film morphology was investigated by atomic force microscopy (AFM) and displayed a globular texture. The films were very smooth, with a maximum root mean square roughness, for example, of 14 nm for a 0.96 μm thick coating. The EIS data confirmed, as expected, that a 2.40 μm Al₂O₃ layer ensures the best corrosion protection after 168 h of immersion in the very acidic environment used.     

Collective decision making: a great opportunity for constraint reasoning

Collective decision making is an area of increasingly growing interest, mainly due to the rise of many IT-enabled environments where people connect and share information with others. We believe that constraint reasoning can have a major impact in this field, by providing general and flexible frameworks to model agents’ preferences over the alternative decisions, efficient algorithms to compute the best individual and collective decisions, and innovative approaches to deal with missing information. However, in order to do this, we claim that constraint reasoning should increase its efforts to open up to other research areas, such as voting and game theory, multi-agent systems, machine learning, and reasoning under uncertainty.     

Accurate determination of hexanal in beef bouillons by headspace solid‐phase microextraction gas‐chromatography mass‐spectrometry

Lipid oxidation has great impact on the quality of food products through flavor and taste deterioration, reduction in nutritive value, and potential toxicity of the oxidized food components. Flavor and taste deterioration can be easily perceived and it represents one of the major causes of consumer complaints in the food industry. The deterioration of sensory properties is due to the decomposition products of hydroperoxides that easily isomerize and degrade into volatile compounds. Volatile products are responsible for flavor and taste deterioration. In this study, we present the development of the solid‐phase microextraction gas chromatography‐mass spectrometry (SPME‐GC‐MS) technique to quantify low amounts (μg/g range) of secondary oxidation products, i.e. hexanal. The optimization of SPME parameters is a difficult task because of the possibility of further formation of volatile products during analysis. Different parameters such as type of fiber, exposure time of the fiber to the sample headspace and the optimal temperature of absorption have also been investigated. The complete validation of the method was achieved by the determination of linearity, limits of detection and quantification and repeatability. We demonstrated that the SPME method is a valuable tool for the quantification of low amounts of secondary oxidation products such as hexanal. Therefore, this technique can be used to detect early formation of volatiles.     

Stay with the flow: How macroinvertebrate communities recover during the rewetting phase in Alpine streams affected by an exceptional drought

Droughts are affecting an increasing number of lotic ecosystems worldwide due to the combined effects of climatic and anthropogenic pressures. Unlike naturally intermittent rivers, where the drying phase is a part of the annual flow regime, water scarcity in Alpine rivers represents a relatively recent phenomenon and, therefore, a major threat for the biodiversity of these lotic ecosystems. However, Alpine stream community response to drought is still poorly investigated. Here, we assess the recovery of macroinvertebrates in two Alpine streams after a supraseasonal drought. As water returned, a total of 10 sampling sessions were carried out, and temporal patterns in diversity, density, and taxonomic composition of benthic communities, as well as in the percentage of functional feeding groups, were investigated. We found that the resistance of invertebrate communities in Alpine streams is generally low: drought markedly reduced the diversity and density of macroinvertebrates. Conversely, our results suggest that the passive dispersal by drift from the upstream river sections seems the most probable mechanism promoting the post‐drought recovery. Nevertheless, this resilience ability appears to be stream specific and influenced by intrinsic stream characteristics, including the flow permanence and distance from the nearest upstream perennial reach. This work sheds light on the ecological consequences of droughts on macroinvertebrate communities. As flow intermittency in Alpine areas is expected to intensify under current global change scenarios, results of this study provide important information to predict changes in the taxonomic composition and diversity of macroinvertebrate communities.     

Compatibilization of an immiscible blend of EPDM and POM with an Ionomer

Immiscible blends of ethylene-propylene-diene-monomer (EPDM) and polyoxymethylene (POM), when EPDM is the major phase were compatibilized on the addition of an ionomer, poly(ethylene-co-methacrylic acid). The inclusion of the ionomer reduced the interfacial tension between the two phases, such that the diameter of the POM domains were significantly reduced to between 0.5 and 2 μm, typical of that required to toughen ductile polymers. The mechanical properties of the resultant compatibilized blends were significantly enhanced with increases in Young's modulus (↑54%), tensile strength (σ, ↑139%), elongation at break (ε, ↑97%), and tensile toughness (↑500%) with increasing ionomer content, relative to EPDM rubber alone. The ShoreA hardness of the compatibilized blend was 70.1 compared with 56.8 for the immiscible binary blend and, 50.2 for neat EPDM rubber.     

Comparing and experimenting machine learning techniques for code smell detection

Several code smell detection tools have been developed providing different results, because smells can be subjectively interpreted, and hence detected, in different ways. In this paper, we perform the largest experiment of applying machine learning algorithms to code smells to the best of our knowledge. We experiment 16 different machine-learning algorithms on four code smells (Data Class, Large Class, Feature Envy, Long Method) and 74 software systems, with 1986 manually validated code smell samples. We found that all algorithms achieved high performances in the cross-validation data set, yet the highest performances were obtained by J48 and Random Forest, while the worst performance were achieved by support vector machines. However, the lower prevalence of code smells, i.e., imbalanced data, in the entire data set caused varying performances that need to be addressed in the future studies. We conclude that the application of machine learning to the detection of these code smells can provide high accuracy (>96 %), and only a hundred training examples are needed to reach at least 95 % accuracy.     

Bribery in voting with CP-nets

We investigate the computational complexity of finding optimal bribery schemes in voting domains where the candidate set is the Cartesian product of a set of variables and voters use CP-nets, an expressive and compact way to represent preferences. To do this, we generalize the traditional bribery problem to take into account several issues over which agents vote, and their inter-dependencies. We consider five voting rules, three kinds of bribery actions, and five cost schemes. For most of the combinations of these parameters, we find that bribery in this setting is computationally easy.     

Exploring creative intersections: Ernest Edmonds and his time-based generative art

This article focuses on the experience of British artist Ernest Edmonds and the influences that have informed his art practice in the past forty years. How are these influences connected? The article has an historical focus. It develops the themes within Edmonds's art and shows his connections with the ‘Systems’ artists and their forebears. In particular, the article concentrates on the encounter of Edmonds with artistic thinking about systems and process in the broad sense, as well as digital and interactive work developed from the early 1980s. As the article will demonstrate, a passion for colour, time and structure, the encounter with a number of artists inspired by Constructivism in the early 1980s, and the educational context in which Edmonds has worked from the late 1960s until the present, have offered great opportunities of interdisciplinary exchanges and ideas that had a profound impact upon the nature of his art. These influences have enabled Edmonds to explore new constructs in art through the use of technology that are a constant stimulus in his creative research, both as an artist and as an academic.