High-resolution restoration of 3D structures from widefield images with extreme low signal-to-noise-ratio

Four-dimensional fluorescence microscopy-which records 3D image information as a function of time-provides an unbiased way of tracking dynamic behavior of subcellular components in living samples and capturing key events in complex macromolecular processes. Unfortunately, the combination of phototoxicity and photobleaching can severely limit the density or duration of sampling, thereby limiting the biological information that can be obtained. Although widefield microscopy provides a very light-efficient way of imaging, obtaining high-quality reconstructions requires deconvolution to remove optical aberrations. Unfortunately, most deconvolution methods perform very poorly at low signal-to-noise ratios, thereby requiring moderate photon doses to obtain acceptable resolution. We present a unique deconvolution method that combines an entropy-based regularization function with kernels that can exploit general spatial characteristics of the fluorescence image to push the required dose to extreme low levels, resulting in an enabling technology for high-resolution in vivo biological imaging.

Fractional Hilbert transform extensions and associated analytic signal construction

The analytic signal (AS) was proposed by Gabor as a complex signal corresponding to a given real signal. The AS has a one-sided spectrum and gives rise to meaningful spectral averages. The Hilbert transform (HT) is a key component in Gabor's AS construction. We generalize the construction methodology by employing the fractional Hilbert transform (FrHT), without going through the standard fractional Fourier transform (FrFT) route. We discuss some properties of the fractional Hilbert operator and show how decomposition of the operator in terms of the identity and the standard Hilbert operators enables the construction of a family of analytic signals. We show that these analytic signals also satisfy Bedrosian-type properties and that their time-frequency localization properties are unaltered. We also propose a generalized-phase AS (GPAS) using a generalized-phase Hilbert transform (GPHT). We show that the GPHT shares many properties of the FrHT, in particular, selective highlighting of singularities, and a connection with Lie groups. We also investigate the duality between analyticity and causality concepts to arrive at a representation of causal signals in terms of the FrHT and GPHT. On the application front, we develop a secure multi-key single-sideband (SSB) modulation scheme and analyze its performance in noise and sensitivity to security key perturbations. (C) 2013 Elsevier B.V. All rights reserved.

A three-component protocol for the enantiodifferentiation of amines using triphenyl borate and BINOL: is it an ion pair or an amine-coordinated complex?

The structure of the borate complex responsible for the enantiodifferentiation of amines using a previously reported three-component protocol has been established. The choice between an ion pair and an amine-coordinated complex with the N atom of the amine coordinated to the B atom is favored for the former structure based on the DFT-calculated B-11 NMR chemical shifts. In contrast to expectations, the anisotropies of the quadrupolar B-11 nucleus for the two structures were calculated to be indistinguishable with regard to their effect on the linewidth of the NMR signal. (C) 2014 Elsevier Ltd. All rights reserved.

Lack of Critical Slowing Down Suggests that Financial Meltdowns Are Not Critical Transitions, yet Rising Variability Could Signal Systemic Risk

Complex systems inspired analysis suggests a hypothesis that financial meltdowns are abrupt critical transitions that occur when the system reaches a tipping point. Theoretical and empirical studies on climatic and ecological dynamical systems have shown that approach to tipping points is preceded by a generic phenomenon called critical slowing down, i.e. an increasingly slow response of the system to perturbations. Therefore, it has been suggested that critical slowing down may be used as an early warning signal of imminent critical transitions. Whether financial markets exhibit critical slowing down prior to meltdowns remains unclear. Here, our analysis reveals that three major US (Dow Jones Index, S&P 500 and NASDAQ) and two European markets (DAX and FTSE) did not exhibit critical slowing down prior to major financial crashes over the last century. However, all markets showed strong trends of rising variability, quantified by time series variance and spectral function at low frequencies, prior to crashes. These results suggest that financial crashes are not critical transitions that occur in the vicinity of a tipping point. Using a simple model, we argue that financial crashes are likely to be stochastic transitions which can occur even when the system is far away from the tipping point. Specifically, we show that a gradually increasing strength of stochastic perturbations may have caused to abrupt transitions in the financial markets. Broadly, our results highlight the importance of stochastically driven abrupt transitions in real world scenarios. Our study offers rising variability as a precursor of financial meltdowns albeit with a limitation that they may signal false alarms.

Aspects of quality control of wind profiler measurements in complex topography

It is well known in the scientific community that some remote sensing instruments assume that sample volumes present homogeneous conditions within a defined meteorological profile. At complex topographic sites and under extreme meteorological conditions, this assumption may be fallible depending on the site, and it is more likely to fail in the lower layers of the atmosphere. This piece of work tests the homogeneity of the wind field over a boundary layer wind profiler radar located in complex terrain on the coast under different meteorological conditions. The results reveal the qualitative importance of being aware of deviations in this homogeneity assumption and evaluate its effect on the final product. Patterns of behavior in data have been identified in order to simplify the analysis of the complex signal registered. The quality information obtained from the homogeneity study under different meteorological conditions provides useful indicators for the best alternatives the system can offer to build wind profiles. Finally, the results are also to be considered in order to integrate them in a quality algorithm implemented at the product level.