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 $\Delta E$ between excited ME peaks and the ground state of the system. The resonance profiles have been found to have maxima at $\Delta E_{\rm max}$ close to the energy of the GaAs LO-phonon. However, the value of $\Delta E_{\rm max}$ 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 $\Delta E_{\rm max}$ 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