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Preferential localization of a vesicular monoamine transporter to dense core vesicles in PC12 cells.
Neurons and endocrine cells have two types of secretory vesicle that undergo regulated exocytosis. Large dense core vesicles (LDCVs) store neural peptides whereas small clear synaptic vesicles store classical neurotransmitters such as acetylcholine, gamma-aminobutyric acid (GABA), glycine, and glutamate. However, monoamines differ from other classical transmitters and have been reported to appear in both LDCVs and smaller vesicles. To localize the transporter that packages monoamines into secretory vesicles, we have raised antibodies to a COOH-terminal sequence from the vesicular amine transporter expressed in the adrenal gland (VMAT1). Like synaptic vesicle proteins, the transporter occurs in endosomes of transfected CHO cells, accounting for the observed vesicular transport activity. In rat pheochromocytoma PC12 cells, the transporter occurs principally in LDCVs by both immunofluorescence and density gradient centrifugation. Synaptic-like microvesicles in PC12 cells contain relatively little VMAT1. The results appear to account for the storage of monoamines by LDCVs in the adrenal medulla and indicate that VMAT1 provides a novel membrane protein marker unique to LDCVs
Maximum Likelihood Estimation of Closed Queueing Network Demands from Queue Length Data
Resource demand estimation is essential for the application of analyical models, such as queueing networks, to real-world systems. In this paper, we investigate maximum likelihood (ML) estimators for service demands in closed queueing networks with load-independent and load-dependent service times. Stemming from a characterization of necessary conditions for ML estimation, we propose new estimators that infer demands from queue-length measurements, which are inexpensive metrics to collect in real systems. One advantage of focusing on queue-length data compared to response times or utilizations is that confidence intervals can be rigorously derived from the equilibrium distribution of the queueing network model. Our estimators and their confidence intervals are validated against simulation and real system measurements for a multi-tier application
Landau level broadening in graphene with long-range disorder -- Robustness of the n=0 level
Broadening of the Landau levels in graphene and the associated quantum Hall
plateau-to-plateau transition are investigated numerically. For correlated bond
disorder, the graphene-specific n=0 Landau level of the Dirac fermions becomes
anomalously sharp accompanied by the Hall transition exhibiting a
fixed-point-like criticality. Similarly anomalous behavior for the n=0 Landau
level is also shown to occur in correlated random magnetic fields, which
suggests that the anomaly is generic to disorders that preserve the chiral
symmetry.Comment: 4 pages, 5 figures, submitted to EP2DS-18 Conference proceeding
Sentiment cascades in the 15M movement
Recent grassroots movements have suggested that online social networks might
play a key role in their organization, as adherents have a fast, many-to-many,
communication channel to help coordinate their mobilization. The structure and
dynamics of the networks constructed from the digital traces of protesters have
been analyzed to some extent recently. However, less effort has been devoted to
the analysis of the semantic content of messages exchanged during the protest.
Using the data obtained from a microblogging service during the brewing and
active phases of the 15M movement in Spain, we perform the first large scale
test of theories on collective emotions and social interaction in collective
actions. Our findings show that activity and information cascades in the
movement are larger in the presence of negative collective emotions and when
users express themselves in terms related to social content. At the level of
individual participants, our results show that their social integration in the
movement, as measured through social network metrics, increases with their
level of engagement and of expression of negativity. Our findings show that
non-rational factors play a role in the formation and activity of social
movements through online media, having important consequences for viral
spreading.Comment: EPJ Data Science vol 4 (2015) (forthcoming
A k-shell decomposition method for weighted networks
We present a generalized method for calculating the k-shell structure of
weighted networks. The method takes into account both the weight and the degree
of a network, in such a way that in the absence of weights we resume the shell
structure obtained by the classic k-shell decomposition. In the presence of
weights, we show that the method is able to partition the network in a more
refined way, without the need of any arbitrary threshold on the weight values.
Furthermore, by simulating spreading processes using the
susceptible-infectious-recovered model in four different weighted real-world
networks, we show that the weighted k-shell decomposition method ranks the
nodes more accurately, by placing nodes with higher spreading potential into
shells closer to the core. In addition, we demonstrate our new method on a real
economic network and show that the core calculated using the weighted k-shell
method is more meaningful from an economic perspective when compared with the
unweighted one.Comment: 17 pages, 6 figure
Statistical Mechanics of Canonical-Dissipative Systems and Applications to Swarm Dynamics
We develop the theory of canonical-dissipative systems, based on the
assumption that both the conservative and the dissipative elements of the
dynamics are determined by invariants of motion. In this case, known solutions
for conservative systems can be used for an extension of the dynamics, which
also includes elements such as the take-up/dissipation of energy. This way, a
rather complex dynamics can be mapped to an analytically tractable model, while
still covering important features of non-equilibrium systems. In our paper,
this approach is used to derive a rather general swarm model that considers (a)
the energetic conditions of swarming, i.e. for active motion, (b) interactions
between the particles based on global couplings. We derive analytical
expressions for the non-equilibrium velocity distribution and the mean squared
displacement of the swarm. Further, we investigate the influence of different
global couplings on the overall behavior of the swarm by means of
particle-based computer simulations and compare them with the analytical
estimations.Comment: 14 pages incl. 13 figures. v2: misprints in Eq. (40) corrected, ref.
updated. For related work see also:
http://summa.physik.hu-berlin.de/~frank/active.htm
Reduction Techniques for Graph Isomorphism in the Context of Width Parameters
We study the parameterized complexity of the graph isomorphism problem when
parameterized by width parameters related to tree decompositions. We apply the
following technique to obtain fixed-parameter tractability for such parameters.
We first compute an isomorphism invariant set of potential bags for a
decomposition and then apply a restricted version of the Weisfeiler-Lehman
algorithm to solve isomorphism. With this we show fixed-parameter tractability
for several parameters and provide a unified explanation for various
isomorphism results concerned with parameters related to tree decompositions.
As a possibly first step towards intractability results for parameterized graph
isomorphism we develop an fpt Turing-reduction from strong tree width to the a
priori unrelated parameter maximum degree.Comment: 23 pages, 4 figure
La prévention durable des TMS : Quels freins ? Quels leviers d'action ?
L’objectif de cette recherche-action est d’éclairer, à travers des interventions dans un nombre significatif d’entreprises, les freins à une prévention durable des TMS, mais aussi les leviers d’action les plus pertinents. Le présent document constitue le rapport final de cette recherche-action
Active motions of Brownian particles in a generalized energy-depot model
We present a generalized energy-depot model in which the conversion rate of
the internal energy into motion can be dependent on the position and the
velocity of a particle. When the conversion rate is a general function of the
velocity, the active particle exhibits diverse patterns of motion including a
braking mechanism and a stepping motion. The phase trajectories of the motion
are investigated in a systematic way. With a particular form of the conversion
rate dependent on the position and velocity, the particle shows a spontaneous
oscillation characterizing a negative stiffness. These types of active
behaviors are compared with the similar phenomena observed in biology such as
the stepping motion of molecular motors and the amplification in hearing
mechanism. Hence, our model can provide a generic understanding of the active
motion related to the energy conversion and also a new control mechanism for
nano-robots. We also investigate the noise effect, especially on the stepping
motion and observe the random walk-like behavior as expected.Comment: to appear in New J. Phy
Systemic Risk in a Unifying Framework for Cascading Processes on Networks
We introduce a general framework for models of cascade and contagion
processes on networks, to identify their commonalities and differences. In
particular, models of social and financial cascades, as well as the fiber
bundle model, the voter model, and models of epidemic spreading are recovered
as special cases. To unify their description, we define the net fragility of a
node, which is the difference between its fragility and the threshold that
determines its failure. Nodes fail if their net fragility grows above zero and
their failure increases the fragility of neighbouring nodes, thus possibly
triggering a cascade. In this framework, we identify three classes depending on
the way the fragility of a node is increased by the failure of a neighbour. At
the microscopic level, we illustrate with specific examples how the failure
spreading pattern varies with the node triggering the cascade, depending on its
position in the network and its degree. At the macroscopic level, systemic risk
is measured as the final fraction of failed nodes, , and for each of
the three classes we derive a recursive equation to compute its value. The
phase diagram of as a function of the initial conditions, thus allows
for a prediction of the systemic risk as well as a comparison of the three
different model classes. We could identify which model class lead to a
first-order phase transition in systemic risk, i.e. situations where small
changes in the initial conditions may lead to a global failure. Eventually, we
generalize our framework to encompass stochastic contagion models. This
indicates the potential for further generalizations.Comment: 43 pages, 16 multipart figure
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