An ensemble of support vector machines for predicting virulent proteins

It is important to develop a reliable system for predicting bacterial virulent proteins for finding novel drug/vaccine and for understanding virulence mechanisms in pathogens.In this work we have proposed a bacterial virulent protein prediction method based on an ensemble of classifiers where the features are extracted directly from the amino acid sequence of a given protein. It is well known in the literature that the features extracted from the evolutionary information of a given protein are better than the features extracted from the amino acid sequence. Our method tries to fill the gap between the amino acid sequence based approaches and the evolutionary information based approaches.An extensive evaluation according to a blind testing protocol, where the parameters of the system are calculated using the training set and the system is validated in three different independent datasets, has demonstrated the validity of the proposed method.     

Software radio: The challenges for reconfigurable terminals

The Software Defined Radio (Sdr) has always been considered as a promising solution for the future of wireless communications because of its ability to provide flexible architecture, enabling multimode and multistandard devices. On the network side, this technology seems to be achievable in a short-term visibility (we even are currently knowing the very beginnings ofSdr solutions in the field of network equipments), but applied to terminals, this technology is likely to reach later its maturity because the embedded issue is synonymous with high constrained architecture. The implementation of software radio terminals requires, for instance, the use of high calculation capability Digital Signal Processors (Dsp) or deeply integrated multiband rf transceiver, whose power consumption quality acts as a brake for the current development of such solutions. Nevertheless, the microelectronic industry will still provide more and more powerful components and, within a few years, theSdr dream will come true for terminal manufacturers. Furthermore, software radio is also a good opportunity to merge computer science and telecommunications technologies, in order to develop smart terminals, which may integrate software components like an operating system or Java virtual machine, etc. Hence, the software radio concept within mobile terminal is still an R&D issue, which requires effort combination in different fields but which also represents a great opportunity for the future of terminals.     

Microscopic polyangiitis: a case report]

Vertebral osteomyelitis arising from an enteric fistula in patients with inflammatory bowel disease is rare. We report on a patient with Crohn's disease who developed an enteric fistula, resulting in a presacral abscess and vertebral osteomyelitis involving the L4 and L5 vertebral bodies and related disc spaces. This was managed by a defunctioning colostomy with drainage of the pre-sacral abscess. The vertebral lesion was successfully managed non-operatively.     

Renal interstitial sclerosis in aging: effects of enalapril and nifedipine

Microwave effects on drosophila morphogenesis were studied. Drosophila embryo were exposed by continuous wave 460 MHz at SAR = 1-5 Wt/kg. It was found that irradiation induced some morphosis such as imago legs and wings form alterations. These effects depended on embryo age, SAR and period exposure. It was proposed that the local microwave heating is responsible for describe effects.     

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.     

Towards a solution for hepatitis C virus hypervariability: mimotopes of the hypervariable region 1 can induce antibodies cross-reacting with a large number of viral variants

The hypervariable region 1 (HVR1) of the putative envelope protein E2 of hepatitis C virus (HCV) is the most variable antigenic fragment in the whole viral genome and is mainly responsible for the large inter-and intra-individual heterogeneity of the infecting virus. It contains a principal neutralization epitope and has been proposed as the major player in the mechanism of escape from host immune response. Since anti-HVR1 antibodies are the only species shown to possess protective activity up to date, developing an effective prevention therapy is a very difficult task. We have approached the problem of HVR1 variability by deriving a consensus profile from >200 HVR1 sequences from different viral isolates and used it as a template to generate a vast repertoire of synthetic HVR1 surrogates displayed on M13 bacteriophage. This library was affinity selected using many different sera from infected patients. Phages were identified which react very frequently with patients' sera and bind serum antibodies that cross-react with a large panel of HVR1 peptides derived from natural HCV variants. When injected into experimental animals, the 'mimotopes' with the highest cross-reactivity induced antibodies which recognized the same panel of natural HVR1 variants. In these mimotopes we identified a sequence pattern responsible for the observed cross-reactivity. These data may hold the key for future development of a prophylactic vaccine against HCV.     

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.