Post-processing partitions to identify domains of modularity optimization

We introduce the Convex Hull of Admissible Modularity Partitions (CHAMP) algorithm to prune and prioritize different network community structures identified across multiple runs of possibly various computational heuristics. Given a set of partitions, CHAMP identifies the domain of modularity optimization for each partition ---i.e., the parameter-space domain where it has the largest modularity relative to the input set---discarding partitions with empty domains to obtain the subset of partitions that are "admissible" candidate community structures that remain potentially optimal over indicated parameter domains. Importantly, CHAMP can be used for multi-dimensional parameter spaces, such as those for multilayer networks where one includes a resolution parameter and interlayer coupling. Using the results from CHAMP, a user can more appropriately select robust community structures by observing the sizes of domains of optimization and the pairwise comparisons between partitions in the admissible subset. We demonstrate the utility of CHAMP with several example networks. In these examples, CHAMP focuses attention onto pruned subsets of admissible partitions that are 20-to-1785 times smaller than the sets of unique partitions obtained by community detection heuristics that were input into CHAMP.Comment: http://www.mdpi.com/1999-4893/10/3/9

From Dendritic Compartments to Neuronal Networks: A Multilevel Analysis of Motion Vision

Animals typically rely on vision to direct their locomotion through the environment. Flies, who move in three dimensions while in flight, have evolved the fastest visual system in the animal kingdom to help them stabilize their flight posture and trajectories (Autrum, 1958). Partly for this reason, they have been the subject of extensive research on the neuronal basis of motion vision, the component of visual function involved in detecting movement within a scene. Using a variety of techniques, including electrophysiology, genetic manipulation, and behavioral analysis, researchers have started to unravel the earliest stages of motion processing (Clark et al., 2011; Eichner et al., 2011). Visual motion processing in the fly begins with the elementary motion detectors (EMDs), which are units sensitive to one direction of motion over a small receptive field. The identities of the cells involved in this computation are under active research, and a complete picture has yet to emerge. For over four decades, however, the identity of one set of downstream cells that receive input from the EMDs has been known (Braitenberg, 1972). These cells, located in the lobula plate of the optic lobe of the fly, are called the horizontal system (HS) and vertical system (VS) cells

Functional divisions for visual processing in the central brain of flying Drosophila

Although anatomy is often the first step in assigning functions to neural structures, it is not always clear whether architecturally distinct regions of the brain correspond to operational units. Whereas neuroarchitecture remains relatively static, functional connectivity may change almost instantaneously according to behavioral context. We imaged panneuronal responses to visual stimuli in a highly conserved central brain region in the fruit fly, Drosophila, during flight. In one substructure, the fan-shaped body, automated analysis revealed three layers that were unresponsive in quiescent flies but became responsive to visual stimuli when the animal was flying. The responses of these regions to a broad suite of visual stimuli suggest that they are involved in the regulation of flight heading. To identify the cell types that underlie these responses, we imaged activity in sets of genetically defined neurons with arborizations in the targeted layers. The responses of this collection during flight also segregated into three sets, confirming the existence of three layers, and they collectively accounted for the panneuronal activity. Our results provide an atlas of flight-gated visual responses in a central brain circuit

Public to private transactions, private equity and financial health in the UK: an empirical analysis of the impact of going private.

Using a hand collected data set of 138 buy-outs, this paper presents the first analysis of the impact effects of public to private transactions (PTPs) in the UK during a period (1998-2004) in which PTPs became a significant part of the market for corporate control. We find that for all PTPs there is a significant improvement in financial health in the post deal years relative to the year before going private. We also find that there is a significant improvement in the financial health of PTPs relative to firms remaining public. The analysis of the individual elements of the z-score shows that there are significant improvements in working capital and liquidity post deal. Profitability, however, shows significant declines in a number of the post deal years. We also find that both private equity (PE) and non PE-backed deals produce improvements in financial health but that there is no difference between the two types of deal. These outcomes provide some support for the Jensen (Am Econ Rev 76:323-329, 1986, Harv Bus Rev 67:61-74, 1989) arguments that going private creates an organizational structure that reduces agency costs. However, they do suggest that the claims that the financial and governance mechanisms imposed by PE providers will produce better outcomes are strictly limited in the second wave of PTPs

Flying Drosophila maintain arbitrary but stable headings relative to the angle of polarized light

Animals must use external cues to maintain a straight course over long distances. In this study, we investigated how the fruit fly Drosophila melanogaster selects and maintains a flight heading relative to the axis of linearly polarized light, a visual cue produced by the atmospheric scattering of sunlight. To track flies' headings over extended periods, we used a flight simulator that coupled the angular velocity of dorsally presented polarized light to the stroke amplitude difference of the animals’ wings. In the simulator, most flies actively maintained a stable heading relative to the axis of polarized light for the duration of 15 min flights. We found that individuals selected arbitrary, unpredictable headings relative to the polarization axis, which demonstrates that D. melanogaster can perform proportional navigation using a polarized light pattern. When flies flew in two consecutive bouts separated by a 5 min gap, the two flight headings were correlated, suggesting individuals retain a memory of their chosen heading. We found that adding a polarized light pattern to a light intensity gradient enhanced flies' orientation ability, suggesting D. melanogaster use a combination of cues to navigate. For both polarized light and intensity cues, flies' capacity to maintain a stable heading gradually increased over several minutes from the onset of flight. Our findings are consistent with a model in which each individual initially orients haphazardly but then settles on a heading which is maintained via a self-reinforcing process. This may be a general dispersal strategy for animals with no target destination