525 research outputs found
Deducing topology of protein-protein interaction networks from experimentally measured sub-networks.
BackgroundProtein-protein interaction networks are commonly sampled using yeast two hybrid approaches. However, whether topological information reaped from these experimentally-measured sub-networks can be extrapolated to complete protein-protein interaction networks is unclear.ResultsBy analyzing various experimental protein-protein interaction datasets, we found that they are not random samples of the parent networks. Based on the experimental bait-prey behaviors, our computer simulations show that these non-random sampling features may affect the topological information. We tested the hypothesis that a core sub-network exists within the experimentally sampled network that better maintains the topological characteristics of the parent protein-protein interaction network. We developed a method to filter the experimentally sampled network to result in a core sub-network that more accurately reflects the topology of the parent network. These findings have fundamental implications for large-scale protein interaction studies and for our understanding of the behavior of cellular networks.ConclusionThe topological information from experimental measured networks network as is may not be the correct source for topological information about the parent protein-protein interaction network. We define a core sub-network that more accurately reflects the topology of the parent network
Double-exciton component of the cyclotron spin-flip mode in a quantum Hall ferromagnet
We report on the calculation of the cyclotron spin-flip excitation (CSFE) in
a spin-polarized quantum Hall system at unit filling. This mode has a
double-exciton component which contributes to the CSFE correlation energy but
can not be found by means of a mean field approach. The result is compared with
available experimental data.Comment: 9 pages, 2 figure
High temperature strength retention of Cu/Nb nanolaminates through dynamic strain ageing
The mechanical properties of Cu/Nb metallic nanolaminates with different
layer thickness (7, 16, 34 and 63 nm) were studied by means of micropillar
compression tests from room temperature to 400 C. Both strain-rate jump and
constant strain rate tests were carried out and they showed evidence of dynamic
strain ageing in the nanolaminates with 7, 16 and 34 nm layer thickness
deformed at 200 C. Dynamic strain ageing was accompanied by a reduction of the
strain rate sensitivity to 0, high strength retention at 200 C and the
development of shear localization of the deformation at low strains (5%-6%)
that took place along the Nb layers in the nanolaminates. Atom probe tomography
of the deformed specimens revealed the presence of O in solid solution in the
Nb layers but not in the Cu layers. Thus, diffusion of O atoms to the mobile
dislocations in Nb was found to be the origin of the dynamic strain ageing in
the Cu/Nb nanolaminates around 200 C. This mechanism was not found at higher
temperatures (400 C) because deformation was mainly controlled by
stress-assisted diffusion in the Cu layers. This discovery shows a novel
strategy to enhance the strength retention at high temperature of metallic
nanolaminates through dynamic strain ageing of one the phases
Diffusion-induced vortex filament instability in 3-dimensional excitable media
We studied the stability of linear vortex filaments in 3-dimensional (3D)
excitable media, using both analytical and numerical methods. We found an
intrinsic 3D instability of vortex filaments that is diffusion-induced, and is
due to the slower diffusion of the inhibitor. This instability can result
either in a single helical filament or in chaotic scroll breakup, depending on
the specific kinetic model. When the 2-dimensional dynamics were in the chaotic
regime, filament instability occurred via on-off intermittency, a failure of
chaos synchronization in the third dimension.Comment: 5 pages, 5 figures, to appear in PRL (September, 1999
Magnetophonon resonance in photoluminescence excitation spectra of magnetoexcitons in GaAs/Al0.3Ga0.7As superlattice
Strong increase in the intensity of the peaks of excited magneto-exciton (ME)
states in the photoluminescence excitation (PLE) spectra recorded for the
ground heavy-hole magneto-excitons (of the 1sHH type) has been found in a
GaAs/AlGaAs superlattice in strong magnetic field B applied normal to the
sample layers. While varying B the intensities of the PLE peaks have been
measured as functions of energy separation between excited ME peaks
and the ground state of the system. The resonance profiles have been found to
have maxima at close to the energy of the GaAs LO-phonon.
However, the value of depends on quantum numbers of the
excited ME state. The revealed very low quantum efficiency of the investigated
sample allows us to ascribe the observed resonance to the enhancement of the
non-radiative magneto-exciton relaxation rate arising due to LO-phonon
emission. The presented theoretical model, being in a good agreement with
experimental observations, provides a method to extract 1sHH magneto-exciton
``in-plane" dispersion from the dependence of on the
excited ME state quantum numbers.Comment: 9 pages, 6 figure
Empirical linkages between ICT, tourism, and trade towards sustainable environment: evidence from BRICS countries
There is a growing utilisation of information and communication
technologies (ICT) in the recent digital era. Trade and tourism
have also attained attention as determinants of environmental
sustainability. Therefore, this study investigates linkages between
ICT, tourism, trade, economic growth, and environmental sustainability
in BRICS economies. Advanced panel estimation entitled
cross-sectionally augmented autoregressive distributed lags (CSARDL)
was applied from 1990 to 2019. Findings suggest the
adverse effect of tourism, trade, and growth factors on environmental
sustainability, whereas ICT helps promote a sustainable
environment among the targeted economies. Likewise, the shortrun
results prove that economic growth and tourism are prone to
ecological health, while trade possesses an insignificant influence
on ecological sustainability. These results suggest the integration
of ICT in trade and tourism sectors to mitigate their negative ecological
consequences
Relaxed Softmax for learning from Positive and Unlabeled data
In recent years, the softmax model and its fast approximations have become
the de-facto loss functions for deep neural networks when dealing with
multi-class prediction. This loss has been extended to language modeling and
recommendation, two fields that fall into the framework of learning from
Positive and Unlabeled data. In this paper, we stress the different drawbacks
of the current family of softmax losses and sampling schemes when applied in a
Positive and Unlabeled learning setup. We propose both a Relaxed Softmax loss
(RS) and a new negative sampling scheme based on Boltzmann formulation. We show
that the new training objective is better suited for the tasks of density
estimation, item similarity and next-event prediction by driving uplifts in
performance on textual and recommendation datasets against classical softmax.Comment: 9 pages, 5 figures, 2 tables, published at RecSys 201
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