7,685 research outputs found
Directed network modules
A search technique locating network modules, i.e., internally densely
connected groups of nodes in directed networks is introduced by extending the
Clique Percolation Method originally proposed for undirected networks. After
giving a suitable definition for directed modules we investigate their
percolation transition in the Erdos-Renyi graph both analytically and
numerically. We also analyse four real-world directed networks, including
Google's own webpages, an email network, a word association graph and the
transcriptional regulatory network of the yeast Saccharomyces cerevisiae. The
obtained directed modules are validated by additional information available for
the nodes. We find that directed modules of real-world graphs inherently
overlap and the investigated networks can be classified into two major groups
in terms of the overlaps between the modules. Accordingly, in the
word-association network and among Google's webpages the overlaps are likely to
contain in-hubs, whereas the modules in the email and transcriptional
regulatory networks tend to overlap via out-hubs.Comment: 21 pages, 10 figures, version 2: added two paragaph
Calculating energy storage due to topological changes in emerging active region NOAA AR 11112
The Minimum Current Corona (MCC) model provides a way to estimate stored
coronal energy using the number of field lines connecting regions of positive
and negative photospheric flux. This information is quantified by the net flux
connecting pairs of opposing regions in a connectivity matrix. Changes in the
coronal magnetic field, due to processes such as magnetic reconnection,
manifest themselves as changes in the connectivity matrix. However, the
connectivity matrix will also change when flux sources emerge or submerge
through the photosphere, as often happens in active regions. We have developed
an algorithm to estimate the changes in flux due to emergence and submergence
of magnetic flux sources. These estimated changes must be accounted for in
order to quantify storage and release of magnetic energy in the corona. To
perform this calculation over extended periods of time, we must additionally
have a consistently labeled connectivity matrix over the entire observational
time span. We have therefore developed an automated tracking algorithm to
generate a consistent connectivity matrix as the photospheric source regions
evolve over time. We have applied this method to NOAA Active Region 11112,
which underwent a GOES M2.9 class flare around 19:00 on Oct.16th, 2010, and
calculated a lower bound on the free magnetic energy buildup of ~8.25 x 10^30
ergs over 3 days.Comment: 36 pages, 14 figures. Published in 2012 ApJ, 749, 64. Published
version available at http://stacks.iop.org/0004-637X/749/64 Animation
available at http://solar.physics.montana.edu/tarrl/data/AR11112.mp
Optimal scan planning for surveying large sites with static and mobile mapping systems
Since the last two decades, the use of laser scanners for generating accurate and dense 3D models has been rapidly growing in multiple disciplines. The reliance on human-expertise to perform an efficient scanning in terms of completeness and quality encouraged the researchers to develop strategies for carrying out an optimized and automated scan planning. Nevertheless, due to the predominant use of static terrestrial laser scanners (TLS), the most of developed methods have been focused on scan optimization by fixing standpoints on basis of static scanning. The increasing use of portable mobile laser scanning systems (MLS) enables faster non-stop acquisition which demands the planning of optimal scan trajectories. Therefore, a novel method addressing the absence of dynamic scan planning is proposed considering specific MLS constraints such as maximum acquisition time or closed-loops requirement. First, an initial analysis is carried out to determinate key-positions to reach during data acquisition. From these positions a navigable graph is generated to compute routes satisfying specific MLS constraints by a three-step process. This starts by estimating the number of routes necessary to subsequently carry out a coarse graph partition based on Kmedoids clustering. Next, a balancing algorithm was implemented to compute a balanced graph partition by node exchanging. Finally, partitions are extended by adding key nodes from their adjacent ones in order to provide a desirable overlapping between scans. The method was tested by simulating three laser scanner configurations in four indoor and outdoor real case studies. The acquisition quality of the computed scan planning was evaluated in terms of 3D completeness and point cloud density with the simulator Helios++
Semi Automatic Segmentation of a Rat Brain Atlas
A common approach to segment an MRI dataset is to use a standard atlas to identify different regions of interest. Existing 2D atlases, prepared by freehand tracings of templates, are seldom complete for 3D volume segmentation. Although many of these atlases are prepared in graphics packages like Adobe Illustrator® (AI), which present the geometrical entities based on their mathematical description, the drawings are not numerically robust. This work presents an automatic conversion of graphical atlases suitable for further usage such as creation of a segmented 3D numerical atlas. The system begins with DXF (Drawing Exchange Format) files of individual atlas drawings. The drawing entities are mostly in cubic spline format. Each segment of the spline is reduced to polylines, which reduces the complexity of data. The system merges overlapping nodes and polylines to make the database of the drawing numerically integrated, i.e. each location within the drawing is referred by only one point, each line is uniquely defined by only two nodes, etc. Numerous integrity diagnostics are performed to eliminate duplicate or overlapping lines, extraneous markers, open-ended loops, etc. Numerically intact closed loops are formed using atlas labels as seed points. These loops specify the boundary and tissue type for each area. The final results preserve the original atlas with its 1272 different neuroanatomical regions which are complete, non-overlapping, contiguous sub-areas whose boundaries are composed of unique polyline
Multi-loop open string amplitudes and their field theory limit
JHEP is an open-access journal funded by SCOAP3 and licensed under CC BY 4.0This work
was supported by STFC (Grant ST/J000469/1, ‘String theory, gauge theory & duality’)
and by MIUR (Italy) under contracts 2006020509 004 and 2010YJ2NYW 00
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