Magnonics, i.e. the artificial manipulation of spin waves, is a flourishingfield of research with many potential uses in data processing within reach.Apart from the technological applications the possibility to directly influenceand observe these types of waves is of great interest for fundamental research.Guidance and steering of spin waves has been previously shown and lateral spinwave confinement has been achieved. However, true spin wave focusing with bothlateral confinement and increase in amplitude has not been shown before. Here,we show for the first time spin wave focusing by realizing a Fresnel zone platetype lens. Using x-ray microscopy we are able to directly image the propagationof spin waves into the nanometer sized focal spot. Furthermore, we observe thatthe focal spot can be freely moved in a large area by small variations of thebias field. Thus, this type of lens provides a steerable intense nanometersized spin wave source. Potentially, this could be used to selectivelyilluminate magnonic devices like nano oscillators with a steerable spin wavebeam.
We study fluctuations around equilibrium in a class of strongly interactingnon-conformal plasmas using holographic techniques. In particular we calculatethe quasi-normal mode spectrum of black hole backgrounds that approach toChamblin-Reall plasmas in the IR. In a specific limit, related to the exactlinear-dilaton background in string theory, we observe that the plasmaapproaches criticality and we obtain the quasi-normal spectrum analytically. Weregulate the critical limit by gluing the IR geometry that corresponds to thenon-conformal plasma to a part of AdS space-time in the UV. Near criticality,we find two sets of quasi-normal modes, related to the IR and UV parts of thegeometry. In the critical limit, the quasi-normal modes accumulate to form abranch cut in the correlators of the energy-momentum tensor on the real axis ofthe complex frequency plane.
Neurotransmitter receptor molecules, concentrated in synaptic membranedomains along with scaffolds and other kinds of proteins, are crucial forsignal transmission across chemical synapses. In common with other membraneprotein domains, synaptic domains are characterized by low protein copy numbersand protein crowding, with rapid stochastic turnover of individual molecules.We study here in detail a stochastic lattice model of the receptor-scaffoldreaction-diffusion dynamics at synaptic domains that was found previously tocapture, at the mean-field level, the self-assembly, stability, andcharacteristic size of synaptic domains observed in experiments. We show thatour stochastic lattice model yields quantitative agreement with mean-fieldmodels of nonlinear diffusion in crowded membranes. Through a combination ofanalytic and numerical solutions of the master equation governing the reactiondynamics at synaptic domains, together with kinetic Monte Carlo simulations, wefind substantial discrepancies between mean-field and stochastic models for thereaction dynamics at synaptic domains. Based on the reaction and diffusionproperties of synaptic receptors and scaffolds suggested by previousexperiments and mean-field calculations, we show that the stochasticreaction-diffusion dynamics of synaptic receptors and scaffolds provide asimple physical mechanism for collective fluctuations in synaptic domains, themolecular turnover observed at synaptic domains, key features of the observedsingle-molecule trajectories, and spatial heterogeneity in the effective ratesat which receptors and scaffolds are recycled at the cell membrane. Our worksheds light on the physical mechanisms and principles linking the collectiveproperties of membrane protein domains to the stochastic dynamics that ruletheir molecular~components.
Diffusion can be conceptualized, at microscopic scales, as the random hoppingof particles between neighboring lattice sites. In the case of diffusion ininhomogeneous media, distinct spatial domains in the system may yield distinctparticle hopping rates. Starting from the master equations (MEs) governingdiffusion in inhomogeneous media we derive here, for arbitrary spatialdimensions, the deterministic lattice equations (DLEs) specifying the averageparticle number at each lattice site for randomly diffusing particles ininhomogeneous media. We consider the case of free diffusion with no stericconstraints on the maximum particle number per lattice site as well as the caseof diffusion under steric constraints imposing a maximum particleconcentration. We find, for both transient and asymptotic regimes, excellentagreement between the DLEs and kinetic Monte Carlo simulations of the MEs. TheDLEs provide a computationally efficient method for predicting the (average)distribution of randomly diffusing particles in inhomogeneous media, with thenumber of DLEs associated with a given system being independent of the numberof particles in the system. From the DLEs we obtain general analyticexpressions for the steady-state particle distributions for free diffusion and,in special cases, diffusion under steric constraints in inhomogeneous media. Wefind that, in the steady state of the system, the average fraction of particlesin a given domain is independent of most system properties, such as thearrangement and shape of domains, and only depends on the number of latticesites in each domain, the hopping rates, the number of distinct particlespecies, and the total number of particles of each particle species in thesystem. Our results provide general insights into the role of spatiallyinhomogeneous particle hopping rates in setting the particle distributions ininhomogeneous media.
This paper presents an algorithm to calibrate the center‐of‐rotation for X‐ray tomography by using a machine learning approach, the Convolutional Neural Network (CNN). The algorithm shows excellent accuracy from the evaluation of synthetic data with various noise ratios. It is further validated with experimental data of four different shale samples measured at the Advanced Photon Source and at the Swiss Light Source. The results are as good as those determined by visual inspection and show better robustness than conventional methods. CNN has also great potential for reducing or removing other artifacts caused by instrument instability, detector non‐linearity, etc . An open‐source toolbox, which integrates the CNN methods described in this paper, is freely available through GitHub at tomography/xlearn and can be easily integrated into existing computational pipelines available at various synchrotron facilities. Source code, documentation and information on how to contribute are also provided.
The development of new methods or utilization of current X‐ray computed tomography methods is impeded by the substantial amount of expertise required to design an X‐ray computed tomography experiment from beginning to end. In an attempt to make material models, data acquisition schemes and reconstruction algorithms more accessible to researchers lacking expertise in some of these areas, a software package is described here which can generate complex simulated phantoms and quantitatively evaluate new or existing data acquisition schemes and image reconstruction algorithms for targeted applications.
Increased apoptotic cell death in uremic patients has been confirmed by a variety of studies. The present study aimed to investigate the effect of uremic toxins and duration of hemodialysis (HD) therapy on apoptosis by means of measuring serum caspase cleaved CK18 (CCCK‐18) levels. Seventy chronic HD patients were recruited and divided into three groups with differing periods of HD, from 6 months to 10 years. Twelve healthy subjects served as controls. Serum CCCK‐18 level was found significantly higher in HD patient groups (Group 2; 189 ± 71 IU/L, Group 3; 182 ± 65 IU/L, Group 4; 204 ± 111 IU/L) as compared to the control group (122 ± 20 U/L) ( P < 0.05). When all hemodialysis patients considered together serum CCCK‐18 showed positive correlation with serum uric acid and phosphorus ( P < 0.05). In conclusion, our results suggest that apoptosis is enhanced in HD patients, phosphorus and uric acid might play a role in this increment, but duration of HD therapy has no effect on apoptosis.