Proactive defragmentation in elastic optical networks under dynamic load conditions

The final publication is available at Springer via http://dx.doi.org/10.1007/s11107-018-0767-7The main weakness of elastic optical networks (EON), under dynamic traffic conditions, stems from spectrum fragmentation. A lot of research efforts have been dedicated during recent years to spectrum defragmentation. In this work, a thorough study about proactive defragmentation is carried out. Effects of the different defragmentation parameters on the EON performance are analyzed, and appropriate values of the defragmentation period, which guarantee suitable network performance while keeping the network control complexity at reasonable values, are obtained by means of extensive simulations. Benefit obtained by applying different defragmentation strategies, in terms of increase in the supported load at a given bandwidth blocking probability, is also reported. Different traffic conditions and network topologies are simulated to assess the validity of the obtained results.Peer ReviewedPostprint (author's final draft

Computational studies of Brønsted acid-catalyzed transannular cycloadditions of cycloalkenone hydrazones

The contribution to the energy barrier of a series of tethers in transannular cycloadditions of cycloalkenes with hydrazones has been computationally studied by using DFT. The Houk's distortion model has been employed to evaluate the influence of the tether in the cycloaddition reaction. That model has been extended to determine the contribution of each tether and, more importantly, the effect exerted between them. In addition to the distortion induced by the tethers, the entropy effects caused by them has also been studied. The analysis of the evolution of the electron localization function along the reaction revealed the highly concerted character of the reaction

The Role of Serotonin in Fear Learning and Memory: A Systematic Review of Human Studies

Fear is characterized by distinct behavioral and physiological responses that are essential for the survival of the human species. Fear conditioning (FC) serves as a valuable model for studying the acquisition, extinction, and expression of fear. The serotonin (5-hydroxytryptamine, 5-HT) system is known to play a significant role in emotional and motivational aspects of human behavior, including fear learning and expression. Accumulating evidence from both animal and human studies suggests that brain regions involved in FC, such as the amygdala, hippocampus, and prefrontal cortex, possess a high density of 5-HT receptors, implicating the crucial involvement of serotonin in aversive learning. Additionally, studies exploring serotonin gene polymorphisms have indicated their potential influence on FC. Therefore, the objective of this work was to review the existing evidence linking 5-HT with fear learning and memory in humans. Through a comprehensive screening of the PubMed and Web of Science databases, 29 relevant studies were included in the final review. These studies investigated the relationship between serotonin and fear learning using drug manipulations or by studying 5-HT-related gene polymorphisms. The results suggest that elevated levels of 5-HT enhance aversive learning, indicating that the modulation of serotonin 5-HT2A receptors regulates the expression of fear responses in humans. Understanding the role of this neurochemical messenger in associative aversive learning can provide insights into psychiatric disorders such as anxiety and post-traumatic stress disorder (PTSD), among others