9,946 research outputs found
A new paradigm for deep sustainability: biourbanism
Biourbanism introduces new conceptual and planning models for a new kind of city, valuing social and economical regeneration of the built environment through developing and healthy communities. Thus, it combines technical aspects, such as zero-emission, energy efficiency, information technology, etc. and the promotion of social sustainability and human well being. In effect, this new paradigm endorses principles of geometrical coherence, Biophilic design, BioArchitecture, Biomimesis, etc. in practices of design and also new urban policies and, especially Biopolitics to promote urban revitalization by ensuring that man-made changes do not have harmful effects to humans. Green city standards start inside the designs of each building and continue either in unbuilt spaces surrounding buildings or inside complex infrastructural networks, connecting buildings and people. The proposed presentation should illustrate how new exciting developments recently, such as fractals, complexity theory, evolutionary biology and artificial intelligence are interrelated and constantly stimulate interaction between human beings and the surrounding environment. New Biophilic solutions in designs of buildings have been proved as attractive opportunities for new markets of housing. Thus, some new infrastructural projects start embracing Biophilic advanced solutions which finally aim at energy efficiency and optimal performance. As parallel activity we can now see emerging new innovative monitoring systems of building health not only in small scale, but also in large scale buildings, such as rail stations, for example, and commercial centres or even sometimes entire educational complexes integrated to new infrastructural projects. Some important case studies are going to be presented; they have been analysed and evaluated by Biourbanism and Biophilia principles and applied methods of design
Horizontal visibility graphs transformed from fractional Brownian motions: Topological properties versus Hurst index
Nonlinear time series analysis aims at understanding the dynamics of
stochastic or chaotic processes. In recent years, quite a few methods have been
proposed to transform a single time series to a complex network so that the
dynamics of the process can be understood by investigating the topological
properties of the network. We study the topological properties of horizontal
visibility graphs constructed from fractional Brownian motions with different
Hurst index . Special attention has been paid to the impact of Hurst
index on the topological properties. It is found that the clustering
coefficient decreases when increases. We also found that the mean
length of the shortest paths increases exponentially with for fixed
length of the original time series. In addition, increases linearly
with respect to when is close to 1 and in a logarithmic form when
is close to 0. Although the occurrence of different motifs changes with ,
the motif rank pattern remains unchanged for different . Adopting the
node-covering box-counting method, the horizontal visibility graphs are found
to be fractals and the fractal dimension decreases with . Furthermore,
the Pearson coefficients of the networks are positive and the degree-degree
correlations increase with the degree, which indicate that the horizontal
visibility graphs are assortative. With the increase of , the Pearson
coefficient decreases first and then increases, in which the turning point is
around . The presence of both fractality and assortativity in the
horizontal visibility graphs converted from fractional Brownian motions is
different from many cases where fractal networks are usually disassortative.Comment: 12 pages, 8 figure
Assessment of long-range correlation in animal behaviour time series: the temporal pattern of locomotor activity of Japanese quail (Coturnix coturnix) and mosquito larva (Culex quinquefasciatus)
The aim of this study was to evaluate the performance of a classical method
of fractal analysis, Detrended Fluctuation Analysis (DFA), in the analysis of
the dynamics of animal behavior time series. In order to correctly use DFA to
assess the presence of long-range correlation, previous authors using
statistical model systems have stated that different aspects should be taken
into account such as: 1) the establishment by hypothesis testing of the absence
of short term correlation, 2) an accurate estimation of a straight line in the
log-log plot of the fluctuation function, 3) the elimination of artificial
crossovers in the fluctuation function, and 4) the length of the time series.
Taking into consideration these factors, herein we evaluated the presence of
long-range correlation in the temporal pattern of locomotor activity of
Japanese quail ({\sl Coturnix coturnix}) and mosquito larva ({\sl Culex
quinquefasciatus}). In our study, modeling the data with the general ARFIMA
model, we rejected the hypothesis of short range correlations (d=0) in all
cases. We also observed that DFA was able to distinguish between the artificial
crossover observed in the temporal pattern of locomotion of Japanese quail, and
the crossovers in the correlation behavior observed in mosquito larvae
locomotion. Although the test duration can slightly influence the parameter
estimation, no qualitative differences were observed between different test
durations
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