3,128 research outputs found
Delayed information flow effect in economy systems. An ACP model study
Applying any strategy requires some knowledge about the past state of the
system. Unfortunately in the case of economy collecting information is a
difficult, expensive and time consuming process. Therefore the information
about the system is known at the end of some well defined intervals, e. g.
company reports, inflation data, GDP etc. They describe a (market) situation in
the past. The time delay is specific to the market branch. It can be very short
(e.g. stock market offer is updated every minute or so and this information is
immediately available) or long, like months in the case of agricultural market,
when the decisions are taken based on the results from the previous harvest.
The analysis of the information flow delay can be based on the ACP model of
spatial evolution of economic systems. The entities can move on a square
lattice and when meeting take one of the two following decisions: merge or
create a new entity. The decision is based on the system state, which is known
with some time delay. The effect of system's feedback is investigated. We
consider the case of company distribution evolution in a heterogenous field.
The information flow time delay implies different final states, including
cycles.Comment: Presented at APFA
Coherent measures of the impact of co-authors in peer review journals and in proceedings publications
This paper focuses on the coauthor effect in different types of publications,
usually not equally respected in measuring research impact. {\it A priori}
unexpected relationships are found between the total coauthor core value,
, of a leading investigator (LI), and the related values for their
publications in either peer review journals () or in proceedings (). A
surprisingly linear relationship is found: . Furthermore, another relationship is found concerning the measure
of the total number of citations, , i.e. the surface of the citation
size-rank histogram up to . Another linear relationship exists :
. These empirical findings
coefficients (0.4 and 1.36) are supported by considerations based on an
empirical power law found between the number of joint publications of an author
and the rank of a coauthor. Moreover, a simple power law relationship is found
between and the number () of coauthors of a LI: ; the power law exponent depends on the type ( or ) of
publications. These simple relations, at this time limited to publications in
physics, imply that coauthors are a "more positive measure" of a principal
investigator role, in both types of scientific outputs, than the Hirsch index
could indicate. Therefore, to scorn upon co-authors in publications, in
particular in proceedings, is incorrect. On the contrary, the findings suggest
an immediate test of coherence of scientific authorship in scientific policy
processes.Comment: 22 pages; 2 Tables; 6 Figures; 38 references; prepared for Physica
Zipf-Mandelbrot-Pareto model for co-authorship popularity
Each co-author (CA) of any scientist can be given a rank () of importance
according to the number () of joint publications which the authors have
together. In this paper, the Zipf-Mandelbrot-Pareto law, i.e. is shown to reproduce the empirical relationship between
and and shown to be preferable to a mere power law, . The CA core value, i.e. the core number of CAs, is unaffected,
of course. The demonstration is made on data for two authors, with a high
number of joint publications, recently considered by Bougrine (2014) and for 7
authors, distinguishing between their "journal" and "proceedings" publications
as suggested by Miskiewicz (2013).
The rank-size statistics is discussed and the and exponents
are compared. The correlation coefficient is much improved ( 0.99,
instead of 0.92). There are marked deviations of such a co-authorship
popularity law depending on sub-fields. On one hand, this suggests an
interpretation of the parameter . On the other hand, it suggests a novel
model on the (likely time dependent) structural and publishing properties of
research teams. Thus, one can propose a scenario for how a research team is
formed and grows. This is based on a hierarchy utility concept, justifying the
empirical Zipf-Mandelbrot-Pareto law, assuming a simple form for the CA
publication/cost ratio, . In conclusion, such a law
and model can suggest practical applications on measures of research teams.
In Appendices, the frequency-size cumulative distribution function is
discussed for two sub-fields, with other technicalitiesComment: 30 pages, 39 refs., 15 figures; to be published in Scientometric
Influence of information flow in the formation of economic cycles
A microscopic approach to macroeconomic features is intended. A model for
macroeconomic behavior based on the Ausloos-Clippe-Pekalski model is built and
investigated. The influence of a discrete time information transfer is
investigated. The formation of economic cycles is observed as a function of the
time of information delay. Three regions of delay time are recognized: short
(IS - iteration steps) - the system evolves toward a
unique stable equilibrium state, medium or , the
system undergoes oscillations: stable concentration cycles appear in the
system. For long information flow delay times, , the systems may
crash for most initial concentrations. However, even in the case of long delay
time the crash time may be long enough to allow observation of the system
evolution and to introduce an appropriate strategy in order to avoid the
collapse of the e.g. company concentration. In the long time delay it is also
possible to observe an "economy resonance" where despite a long delay time the
system evolves for a long time or can even reach a stable state, which insures
its existence.Comment: 18 pages,16 figures, to be published in Verhulst 200 Proceedings, M.
Ausloos and M. Dirickx, Eds. (in press
Electrical and thermal transport properties in high T_c superconductors : effects of a magnetic field
Experimental studies of the electric and heat currents in the normal,
superconducting and mixed states of high T superconductors (HTcS) lead to
characterization, complementary to data obtained from equilibrium property
based techniques. A magnetic field superimposed on the superconducting sample
generates {\it magneto-transport phenomena}, from which an excess electrical
resistivity, an excess thermoelectric power, the Hall or the Nernst effect.
Different behavioral effects allow one to distinguish various dissipation
mechanisms, like quasi particle scattering, vortex motion dissipation and
superconductivity fluctuations, in particular when the Corbino geometry is
used. Moreover bulk measurements of the thermal conductivity and the
electrothermal conductivity in a magnetic field give us sure indications of the
order parameter symmetry. The location of the mixed state phase transition
lines in the technological phase diagram of HTcS are briefly pointed out
through precise measurements performed over broad temperature and magnetic
field ranges. The results are mainly reviewed with the aim of defining further
investigation lines.Comment: 9 pages, no figures; to appear in Physica
Empirical Analysis of Time Series
Time series occur in many fields of biology, physics, chemistry, engineering. Much work has been recently performed in statistical physics using specific mathematical techniques on various time series pertaining to so-called nonlinear phenomena. Several methods, beyond the Fourier transform, are presented here. To distinguish between noise and deterministic content is the major challenge. Various phenomena are used for illustration. Some emphasis on findings and still questions will be drawn from problems in finance due to the existence (or not) of long-, medium-, short-range (power-law or not) correlations in such economic systems. The Fourier transform, the Hurst rescaled range, the instantaneous detrended fluctuations, the moving averages, and the Zipf-plots analysis methods will be recalled. They raise questions about fractional Brownian motion properties, or in sorting out correlation ranges and predictability. Among spectacular results, the possibility of crash predictions will be indicated when there is an underlying discrete scale invariance. Other time series for meteorology and electronics phenomena are also presented in order to discuss stratus cloud breaking and dielectric breakdown through avalanches for illustration purpose and to indicate that there are other widely open fields of possible investigations.time series; finance; fourier transform; Hurst exponenet; multifractal; detrended fluctuation analysis; moving average; Zipf; crashes
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