1,242 research outputs found
Impact of Investor's Varying Risk Aversion on the Dynamics of Asset Price Fluctuations
While the investors' responses to price changes and their price forecasts are
well accepted major factors contributing to large price fluctuations in
financial markets, our study shows that investors' heterogeneous and dynamic
risk aversion (DRA) preferences may play a more critical role in the dynamics
of asset price fluctuations. We propose and study a model of an artificial
stock market consisting of heterogeneous agents with DRA, and we find that DRA
is the main driving force for excess price fluctuations and the associated
volatility clustering. We employ a popular power utility function,
with agent specific and
time-dependent risk aversion index, , and we derive an approximate
formula for the demand function and aggregate price setting equation. The
dynamics of each agent's risk aversion index, (i=1,2,...,N), is
modeled by a bounded random walk with a constant variance . We show
numerically that our model reproduces most of the ``stylized'' facts observed
in the real data, suggesting that dynamic risk aversion is a key mechanism for
the emergence of these stylized facts.Comment: 17 pages, 7 figure
Improving the Louvain Algorithm for Community Detection with Modularity Maximization
International audienc
Network segregation in a model of misinformation and fact checking
Misinformation under the form of rumor, hoaxes, and conspiracy theories
spreads on social media at alarming rates. One hypothesis is that, since social
media are shaped by homophily, belief in misinformation may be more likely to
thrive on those social circles that are segregated from the rest of the
network. One possible antidote is fact checking which, in some cases, is known
to stop rumors from spreading further. However, fact checking may also backfire
and reinforce the belief in a hoax. Here we take into account the combination
of network segregation, finite memory and attention, and fact-checking efforts.
We consider a compartmental model of two interacting epidemic processes over a
network that is segregated between gullible and skeptic users. Extensive
simulation and mean-field analysis show that a more segregated network
facilitates the spread of a hoax only at low forgetting rates, but has no
effect when agents forget at faster rates. This finding may inform the
development of mitigation techniques and overall inform on the risks of
uncontrolled misinformation online
Kerr-Newman Black Hole Thermodynamical State Space: Blockwise Coordinates
A coordinate system that blockwise-simplifies the Kerr-Newman black hole's
thermodynamical state space Ruppeiner metric geometry is constructed, with
discussion of the limiting cases corresponding to simpler black holes. It is
deduced that one of the three conformal Killing vectors of the
Reissner-Nordstrom and Kerr cases (whose thermodynamical state space metrics
are 2 by 2 and conformally flat) survives generalization to the Kerr-Newman
case's 3 by 3 thermodynamical state space metric.Comment: 4 pages incl 2 figs. Accepted by Gen. Rel. Grav. Replaced with
Accepted version (minor corrections
The Nuts and Bolts of Einstein-Maxwell Solutions
We find new non-supersymmetric solutions of five-dimensional ungauged
supergravity coupled to two vector multiplets. The solutions are regular,
horizonless and have the same asymptotic charges as non-extremal charged black
holes. An essential ingredient in our construction is a four-dimensional
Euclidean base which is a solution to Einstein-Maxwell equations. We construct
stationary solutions based on the Euclidean dyonic Reissner-Nordstrom black
hole as well as a six-parameter family with a dyonic Kerr-Newman-NUT base.
These solutions can be viewed as compactifications of eleven-dimensional
supergravity on a six-torus and we discuss their brane interpretation.Comment: 29 pages, 3 figure
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The combined diabetes and renal control trial (C-DIRECT) - a feasibility randomised controlled trial to evaluate outcomes in multi-morbid patients with diabetes and on dialysis using a mixed methods approach
Background: This cluster randomised controlled trial set out to investigate the feasibility and acceptability of the “Combined Diabetes and Renal Control Trial” (C-DIRECT) intervention, a nurse-led intervention based on motivational interviewing and self-management in patients with coexisting end stage renal diseases and diabetes mellitus (DM ESRD). Its efficacy to improve glycaemic control, as well as psychosocial and self-care outcomes were also evaluated as secondary outcomes.
Methods: An assessor-blinded, clustered randomised-controlled trial was conducted with 44 haemodialysis patients with DM ESRD and ≥ 8% glycated haemoglobin (HbA1c), in dialysis centres across Singapore. Patients were randomised according to dialysis shifts. 20 patients were assigned to intervention and 24 were in usual care. The C-DIRECT intervention consisted of three weekly chair-side sessions delivered by diabetes specialist nurses. Data on recruitment, randomisation, and retention, and secondary outcomes such as clinical endpoints, emotional distress, adherence, and self-management skills measures were obtained at baseline and at 12 weeks follow-up. A qualitative evaluation using interviews was conducted at the end of the trial.
Results: Of the 44 recruited at baseline, 42 patients were evaluated at follow-up. One patient died, and one discontinued the study due to deteriorating health. Recruitment, retention, and acceptability rates of C-DIRECT were generally satisfactory HbA1c levels decreased in both groups, but C-DIRECT had more participants with HbA1c < 8% at follow up compared to usual care. Significant improvements in role limitations due to physical health were noted for C-DIRECT whereas levels remained stable in usual care. No statistically significant differences between groups were observed for other clinical markers and other patient-reported outcomes. There were no adverse effects.
Conclusions: The trial demonstrated satisfactory feasibility. A brief intervention delivered on bedside as part of routine dialysis care showed some benefits in glycaemic control and on QOL domain compared with usual care, although no effect was observed in other secondary outcomes. Further research is needed to design and assess interventions to promote diabetes self-management in socially vulnerable patients
Atypical onset of diabetes in a teenage girl: a case report
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens
Optimizing topological cascade resilience based on the structure of terrorist networks
Complex socioeconomic networks such as information, finance and even
terrorist networks need resilience to cascades - to prevent the failure of a
single node from causing a far-reaching domino effect. We show that terrorist
and guerrilla networks are uniquely cascade-resilient while maintaining high
efficiency, but they become more vulnerable beyond a certain threshold. We also
introduce an optimization method for constructing networks with high passive
cascade resilience. The optimal networks are found to be based on cells, where
each cell has a star topology. Counterintuitively, we find that there are
conditions where networks should not be modified to stop cascades because doing
so would come at a disproportionate loss of efficiency. Implementation of these
findings can lead to more cascade-resilient networks in many diverse areas.Comment: 26 pages. v2: In review at Public Library of Science ON
Systematic Reviews in Educational Research: Methodology, Perspectives and Application
This chapter explores the processes of reviewing literature as a research method. The logic of the family of research approaches called systematic review is analysed and the variation in techniques used in the different approaches explored using examples from existing reviews. The key distinctions between aggregative and configurative approaches are illustrated and the chapter signposts further reading on key issues in the systematic review process
Languages cool as they expand: Allometric scaling and the decreasing need for new words
We analyze the occurrence frequencies of over 15 million words recorded in millions of books published during the past two centuries in seven different languages. For all languages and chronological subsets of the data we confirm that two scaling regimes characterize the word frequency distributions, with only the more common words obeying the classic Zipf law. Using corpora of unprecedented size, we test the allometric scaling relation between the corpus size and the vocabulary size of growing languages to demonstrate a decreasing marginal need for new words, a feature that is likely related to the underlying correlations between words. We calculate the annual growth fluctuations of word use which has a decreasing trend as the corpus size increases, indicating a slowdown in linguistic evolution following language expansion. This ‘‘cooling pattern’’ forms the basis of a third statistical regularity, which unlike the Zipf and the Heaps law, is dynamical in nature
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