Unsaturated polyester resin: kinetics of the cross-linking reaction by pulsed NMR

Summary Pulsed NMR at 20 MHz has been used to monitor the time course of the intermediate-final stage of the radical crosslinking reaction (cure of unsaturated polyester-styrene resins.) The measurement of Spin lattice relaxation time T₁ allowed us to follow the hardening process having as a parameter the loss of general mobility of the system at the molecular level.The degree of cure as a function of time, the kinetic constant as well as the activation energy for the crosslinking reaction in isothermal conditions has been evaluated using the semiempirical kinetic equation proposed by Kamal and coworkers. The activation energy was estimated to be 13.6 Kcal per mole of double bonds in the components.     

Digital innovation and the fourth industrial revolution: epochal social changes?

ITC technologies have come to comprehensively represent images and expectations of the future. Hopes of ongoing progress, economic growth, skill upgrading and possibly also democratisation are attached to new ICTs as well as fears of totalitarian control, alienation, job loss and insecurity. Currently, with the terms "Industry 4.0." and ‘Fourth Industrial Revolution” (FIR), public institutions (such as the national governments of Germany, Us, Italy, France, and Hollande), private institutions (the World Economic Forum, Hedge Funds, commercial banks), and literature refer to the inchoate transformation of production of goods and services resulting from the application of a new wave of technological innovations: interconnected collaborative robots; machine learning; Artificial Intelligence; 3D printers connected to digital development software; simulation of interconnected machines; integration of the information flow along the value chain; multidirectional communication between manufacturing processes and products (Internet of Things). According to the main representations of Industry 4.0. by private and public institutions, its effects are expected to be mainly positive, for what regards productivity, economic opportunities and the future of work. The positive potentials now attributed to the new cycle of innovation evoke and expand those attributed to the previous waves of innovation linked to ITC technologies, and, even before, to the transition from Fordism to Post-Fordism. However, these transformations have so far not achieved any of the promises they raised. Improvements for workers in terms of work conditions, work performance and work relationships cannot be determined by any technical innovation in itself, being technological innovation always socially shaped.     

An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring

In this paper, we investigate the performance of several systems based on ensemble of classifiers for bankruptcy prediction and credit scoring.The obtained results are very encouraging, our results improved the performance obtained using the stand-alone classifiers. We show that the method “Random Subspace” outperforms the other ensemble methods tested in this paper. Moreover, the best stand-alone method is the multi-layer perceptron neural net, while the best method tested in this work is the Random Subspace of Levenberg–Marquardt neural net.In this work, three financial datasets are chosen for the experiments: Australian credit, German credit, and Japanese credit.     

Input Decimated Ensemble based on Neighborhood Preserving Embedding for spectrogram classification

In this work a novel technique for building ensembles of classifiers for spectrogram classification is presented. We propose a simple approach for classifying signals from a large database of plant echoes, these echoes are highly complex stochastic signals, anyway their spectrograms contain enough information for extracting a good set of features for training the proposed ensemble of classifiers.The proposed ensemble of classifiers is a novel modified version of a recent feature transform based ensemble method: the Input Decimated Ensemble. In the proposed variant different subsets of randomly extracted training patterns are used to create a set of different Neighborhood Preserving Embedding subspace projections. These feature transformations are applied to the whole dataset and a set of decision trees are trained using these transformed spaces. Finally, the scores of this set of classifiers are combined by sum rule.Experiments carried out on a yet proposed dataset show the superiority of this method with respect to other approaches. The proposed approach outperforms the yet proposed, for the tested dataset, combination of principal component analysis and support vector machine (SVM). Moreover, we show that the fusion between the proposed ensemble and the system based on SVM outperforms both the stand-alone methods.     

Continuous control actions learning and adaptation for robotic manipulation through reinforcement learning

Autonomous Robots - This paper presents a learning-based method that uses simulation data to learn an object manipulation task using two model-free reinforcement learning (RL) algorithms. The...     

Fusion of multi‐spectral SPOT‐5 images and very high resolution texture information extracted from digital orthophotos for automatic classification of complex Alpine areas

In areas with complex three‐dimensional features, slope and aspect interact with light conditions and significantly affect the spatial structure of images acquired by remote sensing instruments (for example, by changing the distribution of shadows and affecting the texture of high resolution imagery). In this scenario, this paper analyses the potential and the effectiveness of an automatic classification system to identify three fundamental vegetation classes (forest, grassland and crops) in the complex topography of the Italian Alps (Autonomous Province of Trento, Italy). This classification system is based on the fusion of spectral information provided by the SPOT‐5 multi‐spectral channels (Ground Instantaneous Field of View, GIFOV, equal to 10 m) and textural information extracted from airborne digital orthophotos (GIFOV equal to 1 m) and is designed to be user‐friendly. The texture of the digital orthophotos was modelled using defined bidirectional variograms, thereby extracting additional information unavailable in first‐order texture analyses. Using SPOT‐5 multi‐spectral information alone, the classification accuracy in the investigated alpine area was equal to 87.5%, but increased to 92.1% when texture information was included. In particular, the texture information significantly increased the classification accuracy for crops (from 68.9% to 87.9%), especially orchards that tend to be classified as lowland deciduous forests, and herbaceous crops (such as maize) that are often misclassified as grasslands. A further simple majority analysis increased the ability of detecting grassland, crops and urban zones. The combination of the majority analysis and the proposed automatic classification system seems an effective approach to classifying vegetation types in highly fragmented and complex Alpine landscapes on a regional scale.     

Sustainable Electric Arc Furnace Steel Production: GREENEAF

In the modern electric arc furnace (EAF), more than 40 % of energy comes from chemical sources by fossil fuels: natural gas is used in dedicated burners during the melting of the scrap, while lump coal (mainly anthracite) is added to the basket and pulverized coal is injected as a foaming agent. Within the frame of the European Research Fund for Coal and Steel (RFCS), the ongoing project GREENEAF (RFSR-CT-2009-004) is studying the possibility to replace coal and natural gas in EAF with char and syngas produced by biomass pyrolysis. The best pyrolysis conditions to obtain the proper syngas and char quality have been defined by laboratory tests using biomass available in the surrounding of the partners steel shops. Industrial trials have been performed in three different EAF plants. The results demonstrated the technical feasibility of the approaches, while the economical evaluation has showed the sustainability of replacing the coal with char from biomass in addition to environmental benefits due to CO₂ reduction.     

Scheduling streaming applications on a complex multicore platform

In this paper, we consider the problem of scheduling streaming applications described by complex task graphs on a heterogeneous multicore platform, the IBM QS 22 platform, embedding two STI Cell Broadband Engine processor. We first derive a complete computation and communication model of the platform on the basis of comprehensive benchmarks. Then we use this model to express the problem of maximizing the throughput of a streaming application on this platform. Although the problem is proven NP‐complete, we present an optimal solution based on mixed linear programming. We also propose simpler scheduling heuristics to compute mapping of the application task graph on the platform. We then come back to the platform and propose a scheduling software to deploy streaming applications on this platform. This allows us to thoroughly test our scheduling strategies on the real platform. We thus show that we are able to achieve a good speed‐up either with the mixed linear programming solution or using involved scheduling heuristics. Copyright © 2011 John Wiley & Sons, Ltd.     

The 3,4-Quinones of Estrone and Estradiol Are the Initiators of Cancer whereas Resveratrol and N-acetylcysteine Are the Preventers

This article reviews evidence suggesting that a common mechanism of initiation leads to the development of many prevalent types of cancer. Endogenous estrogens, in the form of catechol estrogen-3,4-quinones, play a central role in this pathway of cancer initiation. The catechol estrogen-3,4-quinones react with specific purine bases in DNA to form depurinating estrogen-DNA adducts that generate apurinic sites. The apurinic sites can then lead to cancer-causing mutations. The process of cancer initiation has been demonstrated using results from test tube reactions, cultured mammalian cells, and human subjects. Increased amounts of estrogen-DNA adducts are found not only in people with several different types of cancer but also in women at high risk for breast cancer, indicating that the formation of adducts is on the pathway to cancer initiation. Two compounds, resveratrol, and N-acetylcysteine, are particularly good at preventing the formation of estrogen-DNA adducts in humans and are, thus, potential cancer-prevention compounds.