Machine Learning-Based Optimized Link State Routing Protocol for D2D Communication in 5G/B5G

Abstract

Immune responses are widely accepted to be under circadian regulation via a molecular clock, with many practical consequences, but much less is known of how other biological rhythms could affect the immune system. In this study, we search for lunar rhythms (circalunar, circasemilunar, and circatidal cycles) in the immune expression of the recently marine-derived freshwater fish, the low-plate morph of the three-spined stickleback. We employed time series of immune expression (mRNA) measurements for 14 immune-associated genes, representing a variety of immunological pathways. Times series measurements were taken on fish populations in the wild, in seminatural outdoor mesocosms, and in the laboratory, according to sampling regimens originally designed to study circannual variation but with the additional potential to provide information about lunar variation. Our evidence best supported the existence of a very small endogenous tidal rhythm. This is consistent with previous suggestions of the existence of a primordial tidal endogenous clock, some elements of which may be conserved in animals evolving outside the marine environment.

Review on Machine Learning for Intelligent Routing, Key Requirement and Challenges Towards 6G

“…The result shows significantly improvement in bandwidth utilization and throughput. In [66], the author proposed an efficient method to address the issue of call drops due to a lack of resources, which causes an additional network delay. The proposed technique distributes the user's power according to their needs, provides stable connectivity for latency-sensitive applications, and reroutes users if there is network congestion.…”