1,097 research outputs found
Spectral plots and the representation and interpretation of biological data
It is basic question in biology and other fields to identify the char-
acteristic properties that on one hand are shared by structures from a
particular realm, like gene regulation, protein-protein interaction or neu- ral
networks or foodwebs, and that on the other hand distinguish them from other
structures. We introduce and apply a general method, based on the spectrum of
the normalized graph Laplacian, that yields repre- sentations, the spectral
plots, that allow us to find and visualize such properties systematically. We
present such visualizations for a wide range of biological networks and compare
them with those for networks derived from theoretical schemes. The differences
that we find are quite striking and suggest that the search for universal
properties of biological networks should be complemented by an understanding of
more specific features of biological organization principles at different
scales.Comment: 15 pages, 7 figure
Heterogeneous Delays in Neural Networks
We investigate heterogeneous coupling delays in complex networks of excitable
elements described by the FitzHugh-Nagumo model. The effects of discrete as
well as of uni- and bimodal continuous distributions are studied with a focus
on different topologies, i.e., regular, small-world, and random networks. In
the case of two discrete delay times resonance effects play a major role:
Depending on the ratio of the delay times, various characteristic spiking
scenarios, such as coherent or asynchronous spiking, arise. For continuous
delay distributions different dynamical patterns emerge depending on the width
of the distribution. For small distribution widths, we find highly synchronized
spiking, while for intermediate widths only spiking with low degree of
synchrony persists, which is associated with traveling disruptions, partial
amplitude death, or subnetwork synchronization, depending sensitively on the
network topology. If the inhomogeneity of the coupling delays becomes too
large, global amplitude death is induced
Discovering universal statistical laws of complex networks
Different network models have been suggested for the topology underlying
complex interactions in natural systems. These models are aimed at replicating
specific statistical features encountered in real-world networks. However, it
is rarely considered to which degree the results obtained for one particular
network class can be extrapolated to real-world networks. We address this issue
by comparing different classical and more recently developed network models
with respect to their generalisation power, which we identify with large
structural variability and absence of constraints imposed by the construction
scheme. After having identified the most variable networks, we address the
issue of which constraints are common to all network classes and are thus
suitable candidates for being generic statistical laws of complex networks. In
fact, we find that generic, not model-related dependencies between different
network characteristics do exist. This allows, for instance, to infer global
features from local ones using regression models trained on networks with high
generalisation power. Our results confirm and extend previous findings
regarding the synchronisation properties of neural networks. Our method seems
especially relevant for large networks, which are difficult to map completely,
like the neural networks in the brain. The structure of such large networks
cannot be fully sampled with the present technology. Our approach provides a
method to estimate global properties of under-sampled networks with good
approximation. Finally, we demonstrate on three different data sets (C.
elegans' neuronal network, R. prowazekii's metabolic network, and a network of
synonyms extracted from Roget's Thesaurus) that real-world networks have
statistical relations compatible with those obtained using regression models
Identification of plastic constitutive parameters at large deformations from three dimensional displacement fields
The aim of this paper is to provide a general procedure to extract the constitutive parameters of a plasticity model starting from displacement measurements and using the Virtual Fields Method. This is a classical inverse problem which has been already investigated in the literature, however several new features are developed here. First of all the procedure applies to a general three-dimensional displacement field which leads to large plastic deformations, no assumptions are made such as plane stress or plane strain although only pressure-independent plasticity is considered. Moreover the equilibrium equation is written in terms of the deviatoric stress tensor that can be directly computed from the strain field without iterations. Thanks to this, the identification routine is much faster compared to other inverse methods such as finite element updating. The proposed method can be a valid tool to study complex phenomena which involve severe plastic deformation and where the state of stress is completely triaxial, e.g. strain localization or necking occurrence. The procedure has been validated using a three dimensional displacement field obtained from a simulated experiment. The main potentialities as well as a first sensitivity study on the influence of measurement errors are illustrated
Multifocal peliosis hepatis: MR and diffusion-weighted MR-imaging findings of an atypical case
Peliosis is a rare benign disorder that is characterized by the presence of diffuse blood-filled cystic spaces and can occur in the liver, spleen, bone-marrow, and lungs. We present a 10-year-old boy with Fanconi anemia who presented with peliosis hepatis due to androgen treatment. Magnetic resonance (MR) imaging revealed multiple non-enhancing masses. Some of the lesions revealed fluid-fluid levels and extrahepatic extension on MR images. Diffusion-weighted (DW) imaging showed restricted diffusion. Fluid-fluid levels and extrahepatic extensions are unusual findings for hepatic peliotic lesions. In addition, DW imaging findings of peliosis hepatis have not been reported previously
Atomic-scale confinement of optical fields
In the presence of matter there is no fundamental limit preventing
confinement of visible light even down to atomic scales. Achieving such
confinement and the corresponding intensity enhancement inevitably requires
simultaneous control over atomic-scale details of material structures and over
the optical modes that such structures support. By means of self-assembly we
have obtained side-by-side aligned gold nanorod dimers with robust
atomically-defined gaps reaching below 0.5 nm. The existence of
atomically-confined light fields in these gaps is demonstrated by observing
extreme Coulomb splitting of corresponding symmetric and anti-symmetric dimer
eigenmodes of more than 800 meV in white-light scattering experiments. Our
results open new perspectives for atomically-resolved spectroscopic imaging,
deeply nonlinear optics, ultra-sensing, cavity optomechanics as well as for the
realization of novel quantum-optical devices
Modeling Brain Resonance Phenomena Using a Neural Mass Model
Stimulation with rhythmic light flicker (photic driving) plays an important role in the diagnosis of schizophrenia, mood disorder, migraine, and epilepsy. In particular, the adjustment of spontaneous brain rhythms to the stimulus frequency (entrainment) is used to assess the functional flexibility of the brain. We aim to gain deeper understanding of the mechanisms underlying this technique and to predict the effects of stimulus frequency and intensity. For this purpose, a modified Jansen and Rit neural mass model (NMM) of a cortical circuit is used. This mean field model has been designed to strike a balance between mathematical simplicity and biological plausibility. We reproduced the entrainment phenomenon observed in EEG during a photic driving experiment. More generally, we demonstrate that such a single area model can already yield very complex dynamics, including chaos, for biologically plausible parameter ranges. We chart the entire parameter space by means of characteristic Lyapunov spectra and Kaplan-Yorke dimension as well as time series and power spectra. Rhythmic and chaotic brain states were found virtually next to each other, such that small parameter changes can give rise to switching from one to another. Strikingly, this characteristic pattern of unpredictability generated by the model was matched to the experimental data with reasonable accuracy. These findings confirm that the NMM is a useful model of brain dynamics during photic driving. In this context, it can be used to study the mechanisms of, for example, perception and epileptic seizure generation. In particular, it enabled us to make predictions regarding the stimulus amplitude in further experiments for improving the entrainment effect
Resonances On-Demand for Plasmonic Nano-Particles
A method for designing plasmonic particles with desired resonance spectra is
presented. The method is based on repetitive perturbations of an initial
particle shape while calculating the eigenvalues of the various quasistatic
resonances. The method is rigorously proved, assuring a solution exists for any
required spectral resonance location. Resonances spanning the visible and the
near-infrared regimes, as designed by our method, are verified using
finite-difference time-domain simulations. A novel family of particles with
collocated dipole-quadrupole resonances is designed, demonstrating the unique
power of the method. Such on-demand engineering enables strict realization of
nano-antennas and metamaterials for various applications requiring specific
spectral functions
Gender Inequality in a Globalizing World
Emphasis on market-friendly macroeconomic and development strategies in recent years has resulted in deleterious effects on growth and well-being, and has done little to promote greater gender equality. This paper argues that the example of East Asia states, which recognized their position as late industrializers, relied on a managed-market approach with the state that employed a wide variety of policy instruments to promote industrialization. Nevertheless, while Asian growth was rapid, it was not enough to produce greater gender equality. A concentration of women in mobile export industries that face severe competition from other low-wage countries reduces their bargaining power and inhibits closure of gender-wage gaps. Gender-equitable macroeconomic and development policies are thus required, including financial market regulation, regulation of trade and investment flows, and gender-sensitive public sector spending
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