Effects of extremely low-frequency electromagnetic fields on morphine-induced conditioned place preferences in rats

In the present study, we examined the effects of extremely low-frequency (ELF) electromagnetic fields on morphine-induced conditioned place preferences in rats. During the conditioning phase (12 days), three groups of rats were placed in a sensory cue-defined environment paired with morphine (10 mg/kg, i.p.) following exposure to either 20 Hz (1.80 mT) or 50 Hz (2.20 mT) or sham electromagnetic fields for 60 min/day, respectively, and were placed in another sensory cue-defined environment paired with physiological saline (1 ml/kg, i.p.) without exposure to electromagnetic fields. After finishing 12 days of conditioning, preference tests for the morphine-paired place were performed during a 10-day withdrawal period. The exposure to electromagnetic fields substantially potentiated morphine-induced place preferences in rodents, suggesting that ELF electromagnetic fields can increase the propensity for morphine-induced conditioned behaviors. (C) 2005 Elsevier Ireland Ltd. All rights reserved.

semantic oriented ontology cohesion metrics for ontology-based systems

Ontologies play a core role to provide shared knowledge models to semantic-driven applications targeted by Semantic Web. Ontology metrics become an important area because they can help ontology engineers to assess ontology and better control project management and development of ontology based systems, and therefore reduce the risk of project failures. In this paper, we propose a set of ontology cohesion metrics which focuses on measuring (possibly inconsistent) ontologies in the context of dynamic and changing Web. They are: Number of Ontology Partitions (NOP), Number of Minimally Inconsistent Subsets (NMIS) and Average Value of Axiom Inconsistencies (AVAI). These ontology metrics are used to measure ontological semantics rather than ontological structure. They are theoretically validated for ensuring their theoretical soundness, and further empirically validated by a standard test set of debugging ontologies. The related algorithms to compute these ontology metrics also are discussed. These metrics proposed in this paper can be used as a very useful complementarity of existing ontology cohesion metrics.