1,959 research outputs found
Interface of the transport systems research vehicle monochrome display system to the digital autonomous terminal access communication data bus
An upgrade of the transport systems research vehicle (TSRV) experimental flight system retained the original monochrome display system. The original host computer was replaced with a Norden 11/70, a new digital autonomous terminal access communication (DATAC) data bus was installed for data transfer between display system and host, while a new data interface method was required. The new display data interface uses four split phase bipolar (SPBP) serial busses. The DATAC bus uses a shared interface ram (SIR) for intermediate storage of its data transfer. A display interface unit (DIU) was designed and configured to read from and write to the SIR to properly convert the data from parallel to SPBP serial and vice versa. It is found that separation of data for use by each SPBP bus and synchronization of data tranfer throughout the entire experimental flight system are major problems which require solution in DIU design. The techniques used to accomplish these new data interface requirements are described
Social Ranking Techniques for the Web
The proliferation of social media has the potential for changing the
structure and organization of the web. In the past, scientists have looked at
the web as a large connected component to understand how the topology of
hyperlinks correlates with the quality of information contained in the page and
they proposed techniques to rank information contained in web pages. We argue
that information from web pages and network data on social relationships can be
combined to create a personalized and socially connected web. In this paper, we
look at the web as a composition of two networks, one consisting of information
in web pages and the other of personal data shared on social media web sites.
Together, they allow us to analyze how social media tunnels the flow of
information from person to person and how to use the structure of the social
network to rank, deliver, and organize information specifically for each
individual user. We validate our social ranking concepts through a ranking
experiment conducted on web pages that users shared on Google Buzz and Twitter.Comment: 7 pages, ASONAM 201
Voter model with non-Poissonian interevent intervals
Recent analysis of social communications among humans has revealed that the
interval between interactions for a pair of individuals and for an individual
often follows a long-tail distribution. We investigate the effect of such a
non-Poissonian nature of human behavior on dynamics of opinion formation. We
use a variant of the voter model and numerically compare the time to consensus
of all the voters with different distributions of interevent intervals and
different networks. Compared with the exponential distribution of interevent
intervals (i.e., the standard voter model), the power-law distribution of
interevent intervals slows down consensus on the ring. This is because of the
memory effect; in the power-law case, the expected time until the next update
event on a link is large if the link has not had an update event for a long
time. On the complete graph, the consensus time in the power-law case is close
to that in the exponential case. Regular graphs bridge these two results such
that the slowing down of the consensus in the power-law case as compared to the
exponential case is less pronounced as the degree increases.Comment: 18 pages, 8 figure
Energy metabolism in human pluripotent stem cells and their differentiated counterparts
Background: Human pluripotent stem cells have the ability to generate all cell types present in the adult organism, therefore harboring great potential for the in vitro study of differentiation and for the development of cell-based therapies. Nonetheless their use may prove challenging as incomplete differentiation of these cells might lead to tumoregenicity. Interestingly, many cancer types have been reported to display metabolic modifications with features that might be similar to stem cells. Understanding the metabolic properties of human pluripotent stem cells when compared to their differentiated counterparts can thus be of crucial importance. Furthermore recent data has stressed distinct features of different human pluripotent cells lines, namely when comparing embryo-derived human embryonic stem cells (hESCs) and induced pluripotent stem cells (IPSCs) reprogrammed from somatic cells. Methodology/Principal Findings: We compared the energy metabolism of hESCs, IPSCs, and their somatic counterparts. Focusing on mitochondria, we tracked organelle localization and morphology. Furthermore we performed gene expression analysis of several pathways related to the glucose metabolism, including glycolysis, the pentose phosphate pathway and the tricarboxylic acid (TCA) cycle. In addition we determined oxygen consumption rates (OCR) using a metabolic extracellular flux analyzer, as well as total intracellular ATP levels by high performance liquid chromatography (HPLC). Finally we explored the expression of key proteins involved in the regulation of glucose metabolism. Conclusions/Findings: Our results demonstrate that, although the metabolic signature of IPSCs is not identical to that of hESCs, nonetheless they cluster with hESCs rather than with their somatic counterparts. ATP levels, lactate production and OCR revealed that human pluripotent cells rely mostly on glycolysis to meet their energy demands. Furthermore, our work points to some of the strategies which human pluripotent stem cells may use to maintain high glycolytic rates, such as high levels of hexokinase II and inactive pyruvate dehydrogenase (PDH). © 2011 Varum et al
Multiple agency perspective, family control, and private information abuse in an emerging economy
Using a comprehensive sample of listed companies in Hong Kong this paper investigates how family control affects private information abuses and firm performance in emerging economies. We combine research on stock market microstructure with more recent studies of multiple agency perspectives and argue that family ownership and control over the board increases the risk of private information abuse. This, in turn, has a negative impact on stock market performance. Family control is associated with an incentive to distort information disclosure to minority shareholders and obtain private benefits of control. However, the multiple agency roles of controlling families may have different governance properties in terms of investors’ perceptions of private information abuse. These findings contribute to our understanding of the conflicting evidence on the governance role of family control within a multiple agency perspectiv
The Routing of Complex Contagion in Kleinberg's Small-World Networks
In Kleinberg's small-world network model, strong ties are modeled as
deterministic edges in the underlying base grid and weak ties are modeled as
random edges connecting remote nodes. The probability of connecting a node
with node through a weak tie is proportional to , where
is the grid distance between and and is the
parameter of the model. Complex contagion refers to the propagation mechanism
in a network where each node is activated only after neighbors of the
node are activated.
In this paper, we propose the concept of routing of complex contagion (or
complex routing), where we can activate one node at one time step with the goal
of activating the targeted node in the end. We consider decentralized routing
scheme where only the weak ties from the activated nodes are revealed. We study
the routing time of complex contagion and compare the result with simple
routing and complex diffusion (the diffusion of complex contagion, where all
nodes that could be activated are activated immediately in the same step with
the goal of activating all nodes in the end).
We show that for decentralized complex routing, the routing time is lower
bounded by a polynomial in (the number of nodes in the network) for all
range of both in expectation and with high probability (in particular,
for and
for in expectation),
while the routing time of simple contagion has polylogarithmic upper bound when
. Our results indicate that complex routing is harder than complex
diffusion and the routing time of complex contagion differs exponentially
compared to simple contagion at sweetspot.Comment: Conference version will appear in COCOON 201
Reconstructing dynamical networks via feature ranking
Empirical data on real complex systems are becoming increasingly available.
Parallel to this is the need for new methods of reconstructing (inferring) the
topology of networks from time-resolved observations of their node-dynamics.
The methods based on physical insights often rely on strong assumptions about
the properties and dynamics of the scrutinized network. Here, we use the
insights from machine learning to design a new method of network reconstruction
that essentially makes no such assumptions. Specifically, we interpret the
available trajectories (data) as features, and use two independent feature
ranking approaches -- Random forest and RReliefF -- to rank the importance of
each node for predicting the value of each other node, which yields the
reconstructed adjacency matrix. We show that our method is fairly robust to
coupling strength, system size, trajectory length and noise. We also find that
the reconstruction quality strongly depends on the dynamical regime
Size-Dependent Surface Plasmon Dynamics in Metal Nanoparticles
We study the effect of Coulomb correlations on the ultrafast optical dynamics
of small metal particles. We demonstrate that a surface-induced dynamical
screening of the electron-electron interactions leads to quasiparticle
scattering with collective surface excitations. In noble-metal nanoparticles,
it results in an interband resonant scattering of d-holes with surface
plasmons. We show that this size-dependent many-body effect manifests itself in
the differential absorption dynamics for frequencies close to the surface
plasmon resonance. In particular, our self-consistent calculations reveal a
strong frequency dependence of the relaxation, in agreement with recent
femtosecond pump-probe experiments.Comment: 8 pages + 4 figures, final version accepted to PR
Analyzing Ideological Communities in Congressional Voting Networks
We here study the behavior of political party members aiming at identifying
how ideological communities are created and evolve over time in diverse
(fragmented and non-fragmented) party systems. Using public voting data of both
Brazil and the US, we propose a methodology to identify and characterize
ideological communities, their member polarization, and how such communities
evolve over time, covering a 15-year period. Our results reveal very distinct
patterns across the two case studies, in terms of both structural and dynamic
properties
The signalling channel of Central Bank interventions:modelling the Yen/US dollar exchange rate
This paper presents a theoretical framework analysing the signalling channel of exchange rate interventions as an informational trigger. We develop an implicit target zone framework with learning in order to model the signalling channel. The theoretical premise of the model is that interventions convey signals that communicate information about the exchange rate objectives of the central bank. The model is used to analyse the impact of Japanese FX interventions during the period 1999--2011 on the yen/US dollar dynamics
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