Evolution of galaxy groups in the Illustris simulation

We present the first study of evolution of galaxy groups in the Illustris simulation. We focus on dynamically relaxed and unrelaxed galaxy groups representing dynamically evolved and evolving galaxy systems, respectively. The evolutionary state of a group is probed from its luminosity gap and separation between the brightest group galaxy and the center of mass of the group members. We find that the Illustris simulation, over-produces large luminosity gap galaxy systems, known as fossil systems, in comparison to observations and the probed semi-analytical predictions. However, this simulation is equally successful in recovering the correlation between luminosity gap and luminosity centroid offset, in comparison to the probed semi-analytic model. We find evolutionary tracks based on luminosity gap which indicate that a large luminosity gap group is rooted in a small luminosity gap group, regardless of the position of the brightest group galaxy within the halo. This simulation helps, for the first time, to explore the black hole mass and its accretion rate in galaxy groups. For a given stellar mass of the brightest group galaxies, the black hole mass is larger in dynamically relaxed groups with a lower rate of mass accretion. We find this consistent with the latest observational studies of the radio activities in the brightest group galaxies in fossil groups. We also find that the IGM in dynamically evolved groups is hotter for a given halo mass than that in evolving groups, again consistent with earlier observational studies.Comment: 10 pages, 10 figures. Accepted for publication in Ap

Reinforcement Learning for Self Organization and Power Control of Two-Tier Heterogeneous Networks

Self-organizing networks (SONs) can help manage the severe interference in dense heterogeneous networks (HetNets). Given their need to automatically configure power and other settings, machine learning is a promising tool for data-driven decision making in SONs. In this paper, a HetNet is modeled as a dense two-tier network with conventional macrocells overlaid with denser small cells (e.g. femto or pico cells). First, a distributed framework based on multi-agent Markov decision process is proposed that models the power optimization problem in the network. Second, we present a systematic approach for designing a reward function based on the optimization problem. Third, we introduce Q-learning based distributed power allocation algorithm (Q-DPA) as a self-organizing mechanism that enables ongoing transmit power adaptation as new small cells are added to the network. Further, the sample complexity of the Q-DPA algorithm to achieve ϵ-optimality with high probability is provided. We demonstrate, at density of several thousands femtocells per km2, the required quality of service of a macrocell user can be maintained via the proper selection of independent or cooperative learning and appropriate Markov state models

Genomic and neuroimaging approaches to bipolar disorder

BACKGROUND: To date, besides genome-wide association studies, a variety of other genetic analyses (e.g. polygenic risk scores, whole-exome sequencing and whole-genome sequencing) have been conducted, and a large amount of data has been gathered for investigating the involvement of common, rare and very rare types of DNA sequence variants in bipolar disorder. Also, non-invasive neuroimaging methods can be used to quantify changes in brain structure and function in patients with bipolar disorder. AIMS: To provide a comprehensive assessment of genetic findings associated with bipolar disorder, based on the evaluation of different genomic approaches and neuroimaging studies. METHOD: We conducted a PubMed search of all relevant literatures from the beginning to the present, by querying related search strings. RESULTS: ANK3, CACNA1C, SYNE1, ODZ4 and TRANK1 are five genes that have been replicated as key gene candidates in bipolar disorder pathophysiology, through the investigated studies. The percentage of phenotypic variance explained by the identified variants is small (approximately 4.7%). Bipolar disorder polygenic risk scores are associated with other psychiatric phenotypes. The ENIGMA-BD studies show a replicable pattern of lower cortical thickness, altered white matter integrity and smaller subcortical volumes in bipolar disorder. CONCLUSIONS: The low amount of explained phenotypic variance highlights the need for further large-scale investigations, especially among non-European populations, to achieve a more complete understanding of the genetic architecture of bipolar disorder and the missing heritability. Combining neuroimaging data with genetic data in large-scale studies might help researchers acquire a better knowledge of the engaged brain regions in bipolar disorder

The Genetics of Response to and Side Effects of Lithium Treatment in Bipolar Disorder: Future Research Perspectives

Although the mood stabilizer lithium is a first-line treatment in bipolar disorder, a substantial number of patients do not benefit from it and experience side effects. No clinical tool is available for predicting lithium response or the occurrence of side effects in everyday clinical practice. Multiple genetic research efforts have been performed in this field because lithium response and side effects are considered to be multifactorial endophenotypes. Available results from linkage and segregation, candidate-gene, and genome-wide association studies indicate a role of genetic factors in determining response and side effects. For example, candidate-gene studies often report GSK3β, brain-derived neurotrophic factor, and SLC6A4 as being involved in lithium response, and the latest genome-wide association study found a genome-wide significant association of treatment response with a locus on chromosome 21 coding for two long non-coding RNAs. Although research results are promising, they are limited mainly by a lack of replicability and, despite the collaboration of consortia, insufficient sample sizes. The need for larger sample sizes and “multi-omics” approaches is apparent, and such approaches are crucial for choosing the best treatment options for patients with bipolar disorder. In this article, we delineate the mechanisms of action of lithium and summarize the results of genetic research on lithium response and side effects

Heavy Charged Gauge Bosons with General CP Violating Couplings

Heavy gauge bosons such as $W^{\prime}$ are expected to exist in many extensions of the Standard Model. In this paper, it is shown that the most general Lagrangian for the interaction of $W^{\prime}$ with top and bottom quarks which consists of V-A and V+A structure with in general complex couplings produces an Electric Dipole Moment (EDM) for the top quark at one loop level. We predict the allowed ranges for the mass and couplings of $W^{\prime}$ by using the upper limit on the top quark EDM