1,036 research outputs found
Community Aliveness: Discovering Interaction Decay Patterns in Online Social Communities
Online Social Communities (OSCs) provide a medium for connecting people,
sharing news, eliciting information, and finding jobs, among others. The
dynamics of the interaction among the members of OSCs is not always growth
dynamics. Instead, a or dynamics often
happens, which makes an OSC obsolete. Understanding the behavior and the
characteristics of the members of an inactive community help to sustain the
growth dynamics of these communities and, possibly, prevents them from being
out of service. In this work, we provide two prediction models for predicting
the interaction decay of community members, namely: a Simple Threshold Model
(STM) and a supervised machine learning classification framework. We conducted
evaluation experiments for our prediction models supported by a of decayed communities extracted from the StackExchange platform. The
results of the experiments revealed that it is possible, with satisfactory
prediction performance in terms of the F1-score and the accuracy, to predict
the decay of the activity of the members of these communities using
network-based attributes and network-exogenous attributes of the members. The
upper bound of the prediction performance of the methods we used is and
for the F1-score and the accuracy, respectively. These results indicate
that network-based attributes are correlated with the activity of the members
and that we can find decay patterns in terms of these attributes. The results
also showed that the structure of the decayed communities can be used to
support the alive communities by discovering inactive members.Comment: pre-print for the 4th European Network Intelligence Conference -
11-12 September 2017 Duisburg, German
A Tribute to Justice Byron R. White
Of 107 Justices in 205 years, only twelve have served longer than thirty years, and every long-serving Justice has made a substantial contribution to the institution - offering a steady and dedicated response to the judicial challenges of an era, asserting leadership at a time of national crisis, or articulating a large constitutional vision. The personal qualities and life experiences that a new Justice brings to the Court contain the seeds of the individual\u27s judicial service. Justice White, a skeptical but unflinching democrat, was no exception
Web technologies and trends of SCADA-systems development in the field of APCS
This article discusses the use of Internet technologies for modern automated process control systems. As a result of the analysis, the author defines Scada systems and the Industrial Internet of Things. The main advantage of using Internet technologies in APCS is the ability to control and monitor from anywhere using a computer or mobile phone
Modeling bursts and heavy tails in human dynamics
Current models of human dynamics, used from risk assessment to
communications, assume that human actions are randomly distributed in time and
thus well approximated by Poisson processes. We provide direct evidence that
for five human activity patterns the timing of individual human actions follow
non-Poisson statistics, characterized by bursts of rapidly occurring events
separated by long periods of inactivity. We show that the bursty nature of
human behavior is a consequence of a decision based queuing process: when
individuals execute tasks based on some perceived priority, the timing of the
tasks will be heavy tailed, most tasks being rapidly executed, while a few
experiencing very long waiting times. We discuss two queueing models that
capture human activity. The first model assumes that there are no limitations
on the number of tasks an individual can hadle at any time, predicting that the
waiting time of the individual tasks follow a heavy tailed distribution with
exponent alpha=3/2. The second model imposes limitations on the queue length,
resulting in alpha=1. We provide empirical evidence supporting the relevance of
these two models to human activity patterns. Finally, we discuss possible
extension of the proposed queueing models and outline some future challenges in
exploring the statistical mechanisms of human dynamics.Comment: RevTex, 19 pages, 8 figure
The influence of anesthetics, neurotransmitters and antibiotics on the relaxation processes in lipid membranes
In the proximity of melting transitions of artificial and biological
membranes fluctuations in enthalpy, area, volume and concentration are
enhanced. This results in domain formation, changes of the elastic constants,
changes in permeability and slowing down of relaxation processes. In this study
we used pressure perturbation calorimetry to investigate the relaxation time
scale after a jump into the melting transition regime of artificial lipid
membranes. This time corresponds to the characteristic rate of domain growth.
The studies were performed on single-component large unilamellar and
multilamellar vesicle systems with and without the addition of small molecules
such as general anesthetics, neurotransmitters and antibiotics. These drugs
interact with membranes and affect melting points and profiles. In all systems
we found that heat capacity and relaxation times are related to each other in a
simple manner. The maximum relaxation time depends on the cooperativity of the
heat capacity profile and decreases with a broadening of the transition. For
this reason the influence of a drug on the time scale of domain formation
processes can be understood on the basis of their influence on the heat
capacity profile. This allows estimations of the time scale of domain formation
processes in biological membranes.Comment: 12 pages, 6 figure
Nonequilibrium transitions in complex networks: a model of social interaction
We analyze the non-equilibrium order-disorder transition of Axelrod's model
of social interaction in several complex networks. In a small world network, we
find a transition between an ordered homogeneous state and a disordered state.
The transition point is shifted by the degree of spatial disorder of the
underlying network, the network disorder favoring ordered configurations. In
random scale-free networks the transition is only observed for finite size
systems, showing system size scaling, while in the thermodynamic limit only
ordered configurations are always obtained. Thus in the thermodynamic limit the
transition disappears. However, in structured scale-free networks, the phase
transition between an ordered and a disordered phase is restored.Comment: 7 pages revtex4, 10 figures, related material at
http://www.imedea.uib.es/PhysDept/Nonlinear/research_topics/Social
Potts Model On Random Trees
We study the Potts model on locally tree-like random graphs of arbitrary
degree distribution. Using a population dynamics algorithm we numerically solve
the problem exactly. We confirm our results with simulations. Comparisons with
a previous approach are made, showing where its assumption of uniform local
fields breaks down for networks with nodes of low degree.Comment: 10 pages, 3 figure
Signatures of currency vertices
Many real-world networks have broad degree distributions. For some systems,
this means that the functional significance of the vertices is also broadly
distributed, in other cases the vertices are equally significant, but in
different ways. One example of the latter case is metabolic networks, where the
high-degree vertices -- the currency metabolites -- supply the molecular groups
to the low-degree metabolites, and the latter are responsible for the
higher-order biological function, of vital importance to the organism. In this
paper, we propose a generalization of currency metabolites to currency
vertices. We investigate the network structural characteristics of such
systems, both in model networks and in some empirical systems. In addition to
metabolic networks, we find that a network of music collaborations and a
network of e-mail exchange could be described by a division of the vertices
into currency vertices and others.Comment: to appear in Journal of the Physical Society of Japa
Measuring individual overpotentials in an operating solid-oxide electrochemical cell
We use photo-electrons as a non-contact probe to measure local electrical
potentials in a solid-oxide electrochemical cell. We characterize the cell in
operando at near-ambient pressure using spatially-resolved X-ray photoemission
spectroscopy. The overpotentials at the interfaces between the Ni and Pt
electrodes and the yttria-stabilized zirconia (YSZ) electrolyte are directly
measured. The method is validated using electrochemical impedance spectroscopy.
Using the overpotentials, which characterize the cell's inefficiencies, we
compare without ambiguity the electro-catalytic efficiencies of Ni and Pt,
finding that on Ni H_2O splitting proceeds more rapidly than H2 oxidation,
while on Pt, H2 oxidation proceeds more rapidly than H2O splitting.Comment: corrected; Phys. Chem. Chem. Phys., 201
Exploring the Chemical Space of Macro- and Micro-Algae Using Comparative Metabolomics
With more than 156,000 described species, eukaryotic algae (both macro- and micro-algae) are a rich source of biological diversity, however their chemical diversity remains largely unexplored. Specialised metabolites with promising biological activities have been widely reported for seaweeds, and more recently extracts from microalgae have exhibited activity in anticancer, antimicrobial, and antioxidant screens. However, we are still missing critical information on the distinction of chemical profiles between macro- and microalgae, as well as the chemical space these metabolites cover. This study has used an untargeted comparative metabolomics approach to explore the chemical diversity of seven seaweeds and 36 microalgal strains. A total of 1390 liquid chromatography-mass spectrometry (LC-MS) features were detected, representing small organic algal metabolites, with no overlap between the seaweeds and microalgae. An in-depth analysis of four Dunaliella tertiolecta strains shows that environmental factors may play a larger role than phylogeny when classifying their metabolomic profile
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