Structures in the microwave background radiation

We compare the actual WMAP maps with artificial, purely statistical maps of the same harmonic content to argue that there are, with confidence level 99.7 %, ring-type structures in the observed cosmic microwave background.Comment: 4 pages, 2 figure

Dendritic Spine Shape Analysis: A Clustering Perspective

Functional properties of neurons are strongly coupled with their morphology. Changes in neuronal activity alter morphological characteristics of dendritic spines. First step towards understanding the structure-function relationship is to group spines into main spine classes reported in the literature. Shape analysis of dendritic spines can help neuroscientists understand the underlying relationships. Due to unavailability of reliable automated tools, this analysis is currently performed manually which is a time-intensive and subjective task. Several studies on spine shape classification have been reported in the literature, however, there is an on-going debate on whether distinct spine shape classes exist or whether spines should be modeled through a continuum of shape variations. Another challenge is the subjectivity and bias that is introduced due to the supervised nature of classification approaches. In this paper, we aim to address these issues by presenting a clustering perspective. In this context, clustering may serve both confirmation of known patterns and discovery of new ones. We perform cluster analysis on two-photon microscopic images of spines using morphological, shape, and appearance based features and gain insights into the spine shape analysis problem. We use histogram of oriented gradients (HOG), disjunctive normal shape models (DNSM), morphological features, and intensity profile based features for cluster analysis. We use x-means to perform cluster analysis that selects the number of clusters automatically using the Bayesian information criterion (BIC). For all features, this analysis produces 4 clusters and we observe the formation of at least one cluster consisting of spines which are difficult to be assigned to a known class. This observation supports the argument of intermediate shape types.Comment: Accepted for BioImageComputing workshop at ECCV 201

Loss of neuronal 3d chromatin organization causes transcriptional and behavioural deficits related to serotonergic dysfunction

The interior of the neuronal cell nucleus is a highly organized three-dimensional (3D) structure where regions of the genome that are linearly millions of bases apart establish sub-structures with specialized functions. To investigate neuronal chromatin organization and dynamics in vivo, we generated bitransgenic mice expressing GFP-tagged histone H2B in principal neurons of the forebrain. Surprisingly, the expression of this chimeric histone in mature neurons caused chromocenter declustering and disrupted the association of heterochromatin with the nuclear lamina. The loss of these structures did not affect neuronal viability but was associated with specific transcriptional and behavioural deficits related to serotonergic dysfunction. Overall, our results demonstrate that the 3D organization of chromatin within neuronal cells provides an additional level of epigenetic regulation of gene expression that critically impacts neuronal function. This in turn suggests that some loci associated with neuropsychiatric disorders may be particularly sensitive to changes in chromatin architecture

Relating the microscopic rules in coalescence-fragmentation models to the macroscopic cluster size distributions which emerge

Coalescence-fragmentation problems are of great interest across the physical, biological, and recently social sciences. They are typically studied from the perspective of the rate equations, at the heart of such models are the rules used for coalescence and fragmentation. Here we discuss how changes in these microscopic rules affect the macroscopic cluster-size distribution which emerges from the solution to the rate equation. More generally, our work elucidates the crucial role that the fragmentation rule can play in such dynamical grouping models. We focus on two well-known models whose fragmentation rules lie at opposite extremes setting the models within the broader context of binary coalescence-fragmentation models. Further, we provide a range of generalizations and new analytic results for a well-known model of social group formation [V. M. Eguiluz and M. G. Zimmermann, Phys. Rev. Lett. 85, 5659 (2000)]. We develop analytic perturbation treatment of the original model, and extend the mathematical to the treatment of growing and declining populations

Method for Simulation and Optimization of Underground Gas Storage Performance

Proper simulation and identification of the flow potential of a gas storage plant is only possible if the nonlinear limits related to cavern operation and an optimal strategy (set of decision rules) related to the plant operation mode are considered. An efficient operation of a storage plant is a challenging task due to the complexity of cavern rock mechanical restrictions, as well as other technical restrictions imposed on different plant devices. The scope of this paper is to cater for these challenges by defining a set of different operational strategies, i.e., sets of actions which constitute the predefined high level mechanism that allows for an economic and efficient plant operation. In this paper, one specific strategy example is described in detail. Specifically, we give simulation results and outline an optimization procedure designed to maximize the plant’s performance capabilities. The general plant model and the form of rock mechanical restrictions of cavern operation are reviewed, and the construction of the computational algorithm is analyzed