463 research outputs found
Dynamical properties of model communication networks
We study the dynamical properties of a collection of models for communication
processes, characterized by a single parameter representing the relation
between information load of the nodes and its ability to deliver this
information. The critical transition to congestion reported so far occurs only
for . This case is well analyzed for different network topologies. We
focus of the properties of the order parameter, the susceptibility and the time
correlations when approaching the critical point. For no transition to
congestion is observed but it remains a cross-over from a low-density to a
high-density state. For the transition to congestion is discontinuous
and congestion nuclei arise.Comment: 8 pages, 8 figure
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Air itinerary shares estimation using multinomial logit models
The main goal of this study is the development of an aggregate air itinerary market share model. In order to achieve this, multinomial logit models are applied to distribute the city-pair passenger demand across the available itineraries. The models are developed at an aggregate level using open-source booking data for a large group of city-pairs within the US air transport system. Although there is a growing trend in the use of discrete choice models in the aviation industry, existing air itinerary share models are mostly focused on supporting carrier decision-making. Consequently, those studies define itineraries at a more disaggregate level using variables describing airlines and time preferences. In this study, we define itineraries at a more aggregate level, i.e. as a combination of flight segments between an origin and destination, without further insight into service preferences. Although results show some potential for this approach, there are challenges associated with prediction performance and computational intensity
Improving signal stability in a multi-electrode array (MEA) system for cardiac biopsies
This work evaluates the performance of a microelectrode array (MEA) to be used in a specific platform dedicated for measuring field potentials of small human cardiac samples. A test bench has been developed to characterize the electrodes by measuring their impedance as well as to modify their characteristic curve using a replatinization process, where black platinum is deposited on the indicated areas of the MEA flex-pcb. This set-up consists of the array of microelectrodes made of gold, together with its corresponding electronic adapter board, a potentiostat and an electrochemical interface. Phosphate buffered saline (PBS), which is commonly considered for this type of analysis, has been used for impedance characterization. Initially, the impedance presents a highly variable behavior at different frequencies as well as between the different channels of the array. Once the platinization process has been carried out, the impedance in all the recording channels is very similar and has decreased over a large part of the frequency range under study. A complete electrical model of the electrodes has been proposed and analyzed, achieving better results by including the mathematical constant phase element (CPE) associated with capacitive behavior (model fitting error < 2%). Finally, the characterization of the different noise contributions has been carried out. Based on the obtained results, it can be concluded that the evaluated system allows the recording of field potential signals from small human cardiac tissues
Multilayer stochastic block models reveal the multilayer structure of complex networks
In complex systems, the network of interactions we observe between system's
components is the aggregate of the interactions that occur through different
mechanisms or layers. Recent studies reveal that the existence of multiple
interaction layers can have a dramatic impact in the dynamical processes
occurring on these systems. However, these studies assume that the interactions
between systems components in each one of the layers are known, while typically
for real-world systems we do not have that information. Here, we address the
issue of uncovering the different interaction layers from aggregate data by
introducing multilayer stochastic block models (SBMs), a generalization of
single-layer SBMs that considers different mechanisms of layer aggregation.
First, we find the complete probabilistic solution to the problem of finding
the optimal multilayer SBM for a given aggregate observed network. Because this
solution is computationally intractable, we propose an approximation that
enables us to verify that multilayer SBMs are more predictive of network
structure in real-world complex systems
Persistence and Uncertainty in the Academic Career
Understanding how institutional changes within academia may affect the
overall potential of science requires a better quantitative representation of
how careers evolve over time. Since knowledge spillovers, cumulative advantage,
competition, and collaboration are distinctive features of the academic
profession, both the employment relationship and the procedures for assigning
recognition and allocating funding should be designed to account for these
factors. We study the annual production n_{i}(t) of a given scientist i by
analyzing longitudinal career data for 200 leading scientists and 100 assistant
professors from the physics community. We compare our results with 21,156
sports careers. Our empirical analysis of individual productivity dynamics
shows that (i) there are increasing returns for the top individuals within the
competitive cohort, and that (ii) the distribution of production growth is a
leptokurtic "tent-shaped" distribution that is remarkably symmetric. Our
methodology is general, and we speculate that similar features appear in other
disciplines where academic publication is essential and collaboration is a key
feature. We introduce a model of proportional growth which reproduces these two
observations, and additionally accounts for the significantly right-skewed
distributions of career longevity and achievement in science. Using this
theoretical model, we show that short-term contracts can amplify the effects of
competition and uncertainty making careers more vulnerable to early
termination, not necessarily due to lack of individual talent and persistence,
but because of random negative production shocks. We show that fluctuations in
scientific production are quantitatively related to a scientist's collaboration
radius and team efficiency.Comment: 29 pages total: 8 main manuscript + 4 figs, 21 SI text + fig
Extracting the hierarchical organization of complex systems
Extracting understanding from the growing ``sea'' of biological and
socio-economic data is one of the most pressing scientific challenges facing
us. Here, we introduce and validate an unsupervised method that is able to
accurately extract the hierarchical organization of complex biological, social,
and technological networks. We define an ensemble of hierarchically nested
random graphs, which we use to validate the method. We then apply our method to
real-world networks, including the air-transportation network, an electronic
circuit, an email exchange network, and metabolic networks. We find that our
method enables us to obtain an accurate multi-scale descriptions of a complex
system.Comment: Figures in screen resolution. Version with full resolution figures
available at
http://amaral.chem-eng.northwestern.edu/Publications/Papers/sales-pardo-2007.pd
Detecting rich-club ordering in complex networks
Uncovering the hidden regularities and organizational principles of networks
arising in physical systems ranging from the molecular level to the scale of
large communication infrastructures is the key issue for the understanding of
their fabric and dynamical properties [1-5]. The ``rich-club'' phenomenon
refers to the tendency of nodes with high centrality, the dominant elements of
the system, to form tightly interconnected communities and it is one of the
crucial properties accounting for the formation of dominant communities in both
computer and social sciences [4-8]. Here we provide the analytical expression
and the correct null models which allow for a quantitative discussion of the
rich-club phenomenon. The presented analysis enables the measurement of the
rich-club ordering and its relation with the function and dynamics of networks
in examples drawn from the biological, social and technological domains.Comment: 1 table, 3 figure
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