Spectral Analysis of Protein-Protein Interactions in Drosophila melanogaster

Within a case study on the protein-protein interaction network (PIN) of Drosophila melanogaster we investigate the relation between the network's spectral properties and its structural features such as the prevalence of specific subgraphs or duplicate nodes as a result of its evolutionary history. The discrete part of the spectral density shows fingerprints of the PIN's topological features including a preference for loop structures. Duplicate nodes are another prominent feature of PINs and we discuss their representation in the PIN's spectrum as well as their biological implications.Comment: 9 pages RevTeX including 8 figure

Study of an Alternate Mechanism for the Origin of Fermion Generations

In usual extended technicolor (ETC) theories based on the group ${\rm{SU}(N_{ETC}})_{ETC}$, the quarks of charge 2/3 and -1/3 and the charged leptons of all generations arise from ETC fermion multiplets transforming according to the fundamental representation. Here we investigate a different idea for the origin of SM fermion generations, in which quarks and charged leptons of different generations arise from ETC fermions transforming according to different representations of ${\rm{SU}(N_{ETC}})_{ETC}$. Although this mechanism would have the potential, {\it a priori}, to allow a reduction in the value of $N_{ETC}$ relative to conventional ETC models, we show that, at least in simple models, it is excluded by the fact that the technicolor sector is not asymptotically free or by the appearance of fermions with exotic quantum numbers which are not observed.Comment: 6 pages, late

Bayesian inference on compact binary inspiral gravitational radiation signals in interferometric data

Presented is a description of a Markov chain Monte Carlo (MCMC) parameter estimation routine for use with interferometric gravitational radiational data in searches for binary neutron star inspiral signals. Five parameters associated with the inspiral can be estimated, and summary statistics are produced. Advanced MCMC methods were implemented, including importance resampling and prior distributions based on detection probability, in order to increase the efficiency of the code. An example is presented from an application using realistic, albeit fictitious, data.Comment: submitted to Classical and Quantum Gravity. 14 pages, 5 figure

Universality of Electron Mobility in LaAlO3_3/SrTiO3_3 and bulk SrTiO3_3

Metallic LaAlO$_3$/SrTiO$_3$ (LAO/STO) interfaces attract enormous attention, but the relationship between the electron mobility and the sheet electron density, $n_s$, is poorly understood. Here we derive a simple expression for the three-dimensional electron density near the interface, $n_{3D}$, as a function of $n_s$ and find that the mobility for LAO/STO-based interfaces depends on $n_{3D}$ in the same way as it does for bulk doped STO. It is known that undoped bulk STO is strongly compensated with $N \simeq 5 \times 10^{18}~\rm{cm^{-3}}$ background donors and acceptors. In intentionally doped bulk STO with a concentration of electrons $n_{3D} < N$ background impurities determine the electron scattering. Thus, when $n_{3D} < N$ it is natural to see in LAO/STO the same mobility as in the bulk. On the other hand, in the bulk samples with $n_{3D} > N$ the mobility collapses because scattering happens on $n_{3D}$ intentionally introduced donors. For LAO/STO the polar catastrophe which provides electrons is not supposed to provide equal number of random donors and thus the mobility should be larger. The fact that the mobility is still the same implies that for the LAO/STO the polar catastrophe model should be revisited.Comment: 4 pages and 1 figur

ML-SIM: universal reconstruction of structured illumination microscopy images using transfer learning.

Structured illumination microscopy (SIM) has become an important technique for optical super-resolution imaging because it allows a doubling of image resolution at speeds compatible with live-cell imaging. However, the reconstruction of SIM images is often slow, prone to artefacts, and requires multiple parameter adjustments to reflect different hardware or experimental conditions. Here, we introduce a versatile reconstruction method, ML-SIM, which makes use of transfer learning to obtain a parameter-free model that generalises beyond the task of reconstructing data recorded by a specific imaging system for a specific sample type. We demonstrate the generality of the model and the high quality of the obtained reconstructions by application of ML-SIM on raw data obtained for multiple sample types acquired on distinct SIM microscopes. ML-SIM is an end-to-end deep residual neural network that is trained on an auxiliary domain consisting of simulated images, but is transferable to the target task of reconstructing experimental SIM images. By generating the training data to reflect challenging imaging conditions encountered in real systems, ML-SIM becomes robust to noise and irregularities in the illumination patterns of the raw SIM input frames. Since ML-SIM does not require the acquisition of experimental training data, the method can be efficiently adapted to any specific experimental SIM implementation. We compare the reconstruction quality enabled by ML-SIM with current state-of-the-art SIM reconstruction methods and demonstrate advantages in terms of generality and robustness to noise for both simulated and experimental inputs, thus making ML-SIM a useful alternative to traditional methods for challenging imaging conditions. Additionally, reconstruction of a SIM stack is accomplished in less than 200 ms on a modern graphics processing unit, enabling future applications for real-time imaging. Source code and ready-to-use software for the method are available at http://ML-SIM.github.io

Calcium imaging analysis - how far have we come?

Techniques for calcium imaging were first demonstrated in the mid-1970s, whilst tools to analyse these markers of cellular activity are still being developed and improved today. For image analysis, custom tools were developed within labs and until relatively recently, software packages were not widely available between researchers. We will discuss some of the most popular methods for calcium imaging analysis that are now widely available and describe why these protocols are so effective. We will also describe some of the newest innovations in the field that are likely to benefit researchers, particularly as calcium imaging is often an inherently low signal-to-noise method. Although calcium imaging analysis has seen recent advances, particularly following the rise of machine learning, we will end by highlighting the outstanding requirements and questions that hinder further progress and pose the question of how far we have come in the past sixty years and what can be expected for future development in the field

Spin liquid in a single crystal of the frustrated diamond lattice antiferromagnet CoAl2O4

We study spin liquid in the frustrated diamond lattice antiferromagnet CoAl2O4 by means of single crystal neutron scattering in zero and applied magnetic field. The magnetically ordered phase appearing below TN=8 K remains nonconventional down to 1.5 K. The magnetic Bragg peaks at the q=0 positions remain broad and their profiles have strong Lorentzian contribution. Additionally, they are connected by weak diffuse streaks along the directions. These observations are explained within the spiral spin liquid model as short-range magnetic correlations of spirals populated at these finite temperatures, as the energy minimum around q=0 is flat and the energy of excited states with q=(111) is low. The agreement is only qualitative, leading us to suspect that microstructure effects are also important. Magnetic field significantly perturbs spin correlations. The 1.5 K static magnetic moment increases from 1.58 mB/Co at zero field to 2.08 mB/Co at 10 T, while the magnetic peaks, being still broad, acquire almost Gaussian profile. Spin excitations are rather conventional spin waves at zero field, resulting in the exchange parameters J1=0.92(1) meV, J2=0.101(2) meV and the anisotropy term D=-0.0089(2) meV for CoAl2O4. The application of a magnetic field leads to a pronounced broadening of the excitations at the zone center, which at 10 T appear gapless and nearly featureless

Using the average spectrum method to extract dynamics from quantum Monte Carlo simulations

We apply the Average Spectrum Method to the problem of getting the excitation spectrum from imaginary-time quantum Monte Carlo simulations. We show that with high quality QMC data this method reproduces the dominant spectral features very well. It is also capable of giving information on the spectrum in regions dominated by the many-particle continuum of excitations.Comment: v2: Major revision. Title and abstract as well as the focus of the paper have been changed. Added a figure about the dynamics of 1D Heisenberg chai