Dopamine controls whether new declarative information updates reactivated memories through reconsolidation

Consolidation and reconsolidation are independent memory processes. Consolidation stabilizes new memories, whereas reconsolidation restabilizes memories destabilized when reactivated during recall. However, the biological role of the destabilization/reconsolidation cycle is still unknown. It has been hypothesized that reconsolidation links new information with reactivated memories, but some reports suggest that new and old memories are associated through consolidation mechanisms instead. Object-recognition memory (ORM) serves to judge the familiarity of items and is essential for remembering previous events. We took advantage of the fact that ORM consolidation, destabilization, and reconsolidation can be pharmacologically dissociated to demonstrate that, depending on the activation state of hippocampal dopamine D1/D5 receptors, the memory of a novel object presented during recall of the memory of a familiar one can be formed via reconsolidation or consolidation, but only reconsolidation can link them. We also found that recognition memories formed through reconsolidation can be destabilized even if indirectly reactivated. Our results indicate that dopamine couples novelty detection with memory destabilization to determine whether a new recognition trace is associated with an active network and suggest that declarative reminders should be used with caution during reconsolidation-based psychotherapeutic interventions.

Does Re-Partnering Behavior Spread Among Former Spouses?

This study focused on individuals’ re-partnering behavior following a divorce and asked whether divorcees influence each other’s new union formation. By exploiting the System of Social statistical Datasets (SSD) of Statistics Netherlands, I identified divorced dyads and examined interdependencies in their re-partnering behavior. Discrete-time event history models accounting for shared characteristics of divorcees that are likely to influence their divorce and re-partnering behavior simultaneously were estimated. Findings showed that the probability of re-partnering increased within the first two years following a former spouse’s new union formation. Further analyses focusing on formerly cohabiting couples rather than divorcees also revealed significant associations in re-partnering behavior. Following a former romantic partner’s new union formation, women were exposed to risk longer than men, due to men’s quicker re-partnering. These results were robust to the falsification tests. Overall, findings indicate that the consequences of a divorce or breakup are not limited to the incidence itself and former romantic partners remain important in each other’s life courses even after a breakup. With the increasing number of divorcees and changing family structures, it is important to consider former spouses as active network partners that may influence individual life courses.

Integration and control of lithium-ion BESSs for active network management in smart grids: Sundom smart grid backup feeding case

Lithium-ion battery energy storage systems (Li-ion BESS), due to their capability in providing both active and reactive power services, act as a bridging technology for efficient implementation of active network management (ANM) schemes for land-based grid applications. Due to higher integration of intermittent renewable energy sources in the distribution system, transient instability may induce power quality issues, mainly in terms of voltage fluctuations. In such situations, ANM schemes in the power network are a possible solution to maintain operation limits defined by grid codes. However, to implement ANM schemes effectively, integration and control of highly flexible Li-ion BESS play an important role, considering their performance characteristics and economics. Hence, in this paper, an energy management system (EMS) has been developed for implementing the ANM scheme, particularly focusing on the integration design of Li-ion BESS and the controllers managing them. Developed ANM scheme has been utilized to mitigate MV network issues (i.e. voltage stability and adherence to reactive power window). The efficiency of Li-ion BESS integration methodology, performance of the EMS controllers to implement ANM scheme and the effect of such ANM schemes on integration of Li-ion BESS, i.e. control of its grid-side converter (considering operation states and characteristics of the Li-ion BESS) and their coordination with the grid side controllers have been validated by means of simulation studies in the Sundom smart grid network, Vaasa, Finland.

Mivar databases and rules

The multidimensional open epistemological active network MOGAN is the basis for the transition to a qualitatively new level of creating logical artificial intelligence. Mivar databases and rules became the foundation for the creation of MOGAN. The results of the analysis and generalization of data representation structures of various data models are presented: from relational to "Entity — Relationship" (ER-model). On the basis of this generalization, a new model of data and rules is created: the mivar information space "Thing-Property-Relation". The logic-computational processing of data in this new model of data and rules is shown, which has linear computational complexity relative to the number of rules. MOGAN is a development of Rule - Based Systems and allows you to quickly and easily design algorithms and work with logical reasoning in the "If..., Then..." format. An example of creating a mivar expert system for solving problems in the model area "Geometry"is given. Mivar databases and rules can be used to model cause-and-effect relationships in different subject areas and to create knowledge bases of new-generation applied artificial intelligence systems and real-time mivar expert systems with the transition to"Big Knowledge". The textbook in the field of training "Computer Science and Computer Engineering" is intended for students, bachelors, undergraduates, postgraduates studying artificial intelligence methods used in information processing and management systems, as well as for users and specialists who create mivar knowledge models, expert systems, automated control systems and decision support systems. Keywords: cybernetics, artificial intelligence, mivar, mivar networks, databases, data models, expert system, intelligent systems, multidimensional open epistemological active network, MOGAN, MIPRA, KESMI, Wi!Mi, Razumator, knowledge bases, knowledge graphs, knowledge networks, Big knowledge, products, logical inference, decision support systems, decision-making systems, autonomous robots, recommendation systems, universal knowledge tools, expert system designers, logical artificial intelligence.