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Your search keyword '"Fusella, E."' showing total 7 results
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7 results on '"Fusella, E."'

3. Radon measurements over a natural-gas contaminated aquifer

Author

Palacios, D., primary, Fusella, E., additional, Avila, Y., additional, Salas, J., additional, Teixeira, D., additional, Fernández, G., additional, Salas, A., additional, Sajo-Bohus, L., additional, Greaves, E., additional, Barros, H., additional, Bolívar, M., additional, and Regalado, J., additional

Published
2013
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4. Molecular characterization of bacteria isolated from waste electrical transformer oil.

Author

Sisto, A., Fusella, E., Urbina, H., Leyn, V., and Naranjo, L.

Abstract

Electrical transformer oil (ETO) includes as dielectric fluids hazardous compounds such as PAHs and sometimes PCBs, which are highly toxic and resistant to degradation. Three species of bacteria, belonging to Acinetobacter lwoffii, Bacillus amyloliquefaciens, and Bacillus pumilus, were isolated from waste ETO. Phenotypic and molecular assays revealed a high potential of A. lwoffii for catabolism of phenanthrene and ETO as a sole carbon and energy source. This article reports for the first time the isolation, identification, and characterization of bacterial diversity hidden in ETO. [ABSTRACT FROM AUTHOR]

Published
2008
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5. Improving Deep Learning with a customizable GPU-like FPGA-based accelerator

Author

Alessandro Cilardo, Edoardo Fusella, Mirko Gagliardi, Gagliardi, Mirko, Fusella, E., and Cilardo, A.

Subjects
Computer science, business.industry, Deep learning, 020206 networking & telecommunications, 02 engineering and technology, Parallel computing, Execution time, Multithreading, 0202 electrical engineering, electronic engineering, information engineering, Deep neural networks, 020201 artificial intelligence & image processing, Artificial intelligence, SIMD, business, Field-programmable gate array
Abstract

An ever increasing number of challenging appli- cations are being approached using Deep Learning, obtaining impressive results in a variety of different domains. However, state-of-the-art accuracy requires deep neural networks with a larger number of layers and a huge number of different filters with millions of weights. GPU- and FPGA-based architectures have been proposed as a possible solution for facing this enormous demand of computing resources. In this paper, we investigate the adoption of different architectural features, i.e., SIMD paradigm, multithreading, and non-coherent on-chip memory for Deep Learning oriented FPGA-based accelerator designs. Experimental results on a Xilinx Virtex-7 FPGA show that the SIMD paradigm and multithreading can lead to an improvement in the execution time up to $5{\times }$and $3 . 5{\times }$, respectively. A further enhancement up to $1 . 75{\times }$can be obtained using a non-coherent on-chip memory.

Published
2018
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6. Understanding turn models for adaptive routing: The modular approach

Author

Alessandro Cilardo, Edoardo Fusella, Fusella, E., and Cilardo, A.

Subjects
020203 distributed computing, business.industry, Computer science, Distributed computing, Turn (geometry), 0202 electrical engineering, electronic engineering, information engineering, Topology (electrical circuits), 02 engineering and technology, Routing (electronic design automation), Modular design, Adaptive routing, business, 020202 computer hardware & architecture
Abstract

Routing algorithms were extensively studied first in multi-computer systems, then in multi- and many-core architectures. Among the commonly used routing techniques, the turn model seems the most promising solution when targeting adaptiveness. Based on the turn model, several alternative approaches with different turn prohibition schemes were proposed. This paper gives a new theoretical background for designing deadlock-free partially adaptive logic-based distributed routing algorithms that are based on the turn model. Two properties are presented, including a necessary and sufficient condition to prove that a routing algorithm is deadlock-free as long as turn restrictions follow a modular distribution. Existing approaches can be considered a subset of the solution space identified by this work. Finally, we propose a novel routing algorithm exhibiting encouraging performance improvements over state-of-the-art approaches.

Published
2018
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7. Potential role of oxidative exoenzymes of the extremophilic fungus Pestalotiopsis palmarum BM-04 in biotransformation of extra-heavy crude oil.

Author

Naranjo-Briceño L, Pernía B, Guerra M, Demey JR, De Sisto A, Inojosa Y, González M, Fusella E, Freites M, and Yegres F

Subjects
Biodegradation, Environmental, Biotransformation, Fungal Proteins genetics, Industrial Waste analysis, Laccase genetics, Oxidation-Reduction, Petroleum analysis, Petroleum microbiology, Xylariales genetics, Xylariales growth & development, Xylariales metabolism, Fungal Proteins metabolism, Laccase metabolism, Petroleum metabolism, Xylariales enzymology
Abstract

Large amount of drilling waste associated with the expansion of the Orinoco Oil Belt (OOB), the biggest proven reserve of extra-heavy crude oil (EHCO) worldwide, is usually impregnated with EHCO and highly salinized water-based drilling fluids. Oxidative exoenzymes (OE) of the lignin-degrading enzyme system (LDS) of fungi catalyse the oxidation of a wide range of toxic pollutants. However, very little evidences on fungal degradation or biotransformation of EHCO have been reported, which contain high amounts of asphaltenes and its biodegradation rate is very limited. The aims of this work were to study the ability of Pestalotiopsis palmarum BM-04 to synthesize OE, its potential to biotransform EHCO and to survive in extreme environmental conditions. Enzymatic studies of the LDS showed the ability of this fungus to overproduce high amounts of laccase (LACp) in presence of wheat bran or lignin peroxidase (LIPp) with EHCO as sole carbon and energy source (1300 U mgP(-1) in both cases). FT-IR spectroscopy with Attenuated Total Reflectance (ATR) analysis showed the enzymatic oxidation of carbon and sulfur atoms in both maltenes and asphaltenes fractions of biotreated EHCO catalysed by cell-free laccase-enriched OE using wheat bran as inducer. UV-visible spectrophotometry analysis revealed the oxidation of the petroporphyrins in the asphaltenes fraction of biotreated EHCO. Tolerance assays showed the ability of this fungus to grow up to 50,000 p.p.m. of EHCO and 2000 mM of NaCl. These results suggest that P. palmarum BM-04 is a hopeful alternative to be used in remediation processes in extreme environmental conditions of salinity and EHCO contamination, such as the drilling waste from the OOB., (© 2013 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.)

Published
2013
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