Validation, analysis and annotation of cryo-EM structures

The process of turning 2D micrographs into 3D atomic models of the imaged macromolecules has been under rapid development and scrutiny in the field of cryo-EM. Here, some important methods for validation at several stages in this process are described. Firstly, how Fourier shell correlation of two independent maps and phase randomization beyond a certain frequency address the assessment of map resolution is reviewed. Techniques for local resolution estimation and map sharpening are also touched upon. The topic of validating models which are either built de novo or based on a known atomic structure fitted into a cryo-EM map is then approached. Map–model comparison using Q-scores and Fourier shell correlation plots is used to assure the agreement of the model with the observed map density. The importance of annotating the model with B factors to account for the resolvability of individual atoms in the map is illustrated. Finally, the timely topic of detecting and validating water molecules and metal ions in maps that have surpassed ∼2 Å resolution is described.

Dollar’s Influence on Crude Oil and Gold Based on MF-DPCCA Method

This paper analyzed the influence of dollar on crude oil and gold based on the multifractal detrended partial cross-correlation analysis method. It showed that affected by the dollar, the crude oil and gold markets have a partial cross-correlation relationship which is stronger than their own cross-correlation. The partial cross-correlation is long-term and has multifractal characteristics. Through shuffled and Fourier-phase randomization, it is found that this multifractal feature is caused by the combined effect of the long-term cross-correlation between the returns and the fluctuation fat-tailed distribution, where the influence of the fat-tailed distribution is slightly greater than that of the long-term cross-correlation between the returns.

Tight finite-key analysis for quantum key distribution without monitoring signal disturbance

Unlike traditional communication, quantum key distribution (QKD) can reach unconditional security and thus attracts intensive studies. Among all existing QKD protocols, round-robin-differential-phase-shift (RRDPS) protocol can be running without monitoring signal disturbance, which significantly simplifies its flow and improves its tolerance of error rate. Although several security proofs of RRDPS have been given, a tight finite-key analysis with a practical phase-randomized source is still missing. In this paper, we propose an improved security proof of RRDPS against the most general coherent attack based on the entropic uncertainty relation. What’s more, with the help of Azuma’s inequality, our proof can tackle finite-key effects primely. The proposed finite-key analysis keeps the advantages of phase randomization source and indicates experimentally acceptable numbers of pulses are sufficient to approach the asymptotical bound closely. The results shed light on practical QKD without monitoring signal disturbance.

Phase-Matching Quantum Key Distribution with Discrete Phase Randomization

The twin-field quantum key distribution (TF-QKD) protocol and its variations have been proposed to overcome the linear Pirandola–Laurenza–Ottaviani–Banchi (PLOB) bound. One variation called phase-matching QKD (PM-QKD) protocol employs discrete phase randomization and the phase post-compensation technique to improve the key rate quadratically. However, the discrete phase randomization opens a loophole to threaten the actual security. In this paper, we first introduce the unambiguous state discrimination (USD) measurement and the photon-number-splitting (PNS) attack against PM-QKD with imperfect phase randomization. Then, we prove the rigorous security of decoy state PM-QKD with discrete phase randomization. Simulation results show that, considering the intrinsic bit error rate and sifting factor, there is an optimal discrete phase randomization value to guarantee security and performance. Furthermore, as the number of discrete phase randomization increases, the key rate of adopting vacuum and one decoy state approaches infinite decoy states, the key rate between discrete phase randomization and continuous phase randomization is almost the same.

Design of a wideband random phase gradient metasurface by using line-shaped element

Based on phase randomization theory, a method for manufacturing metasurface with diffuse scatter performance is proposed. By using the line-shaped elements with random rotate angles and random distributing positions, the metasurface can achieve good diffusion scatter performance with polarization independent characteristic. This paper studies the effects of the length of line-shaped elements on the metasurface response frequency and the radar cross section (RCS) reduction bandwidth. The simulated result shows that the wideband properties of metasurface benefit from two different length line-shaped elements. The proposed metasurface can reduce the RCS significantly for both normal and oblique incident waves. The line-shaped element is suitable for all sizes of detected objects and it can be directly sprayed on the detected object surface. To demonstrate the effectiveness of the proposed method, the metasurface prototype is fabricated and measured. Experimental results show that the fabricated metasurface can effectively reduce RCS, and it has great application prospects in stealth technology.

Nonsense correlations in neuroscience

Many neurophysiological signals exhibit slow continuous trends over time. Because standard correlation analyses assume that all samples are independent, they can yield apparently significant “nonsense correlations” even for signals that are completely unrelated. Here we compare the performance of several methods for assessing correlations between timeseries, using simulated slowly drifting signals with and without genuine correlations. The best performance was obtained from a “pseudosession method”, which relies on one of the signals being randomly generated by the experimenter, or a “session perturbation” method which requires multiple recordings under the same conditions. If neither of these is applicable, we find that a “linear shift” method can work well, but only when one of the signals is stationary. Methods based on cross-validation, circular shifting, phase randomization, or detrending gave up to 100% false positive rates in our simulations. We conclude that analysis of neural timeseries is best performed when stationarity and randomization is built into the experimental design.

Mitigating Quantization Lobes in mmWave Low-bit Reconfigurable Reflective Surfaces

We present a method for the mitigation of quantization lobes in single-bit reconfigurable reflective surfaces (RRSs). Typically, RRSs are planar beamforming structures consisting of hundreds or thousands of antennas with integrated tunable switches. Under plane-wave illumination, single-bit RRSs suffer from undesired side lobes or quantization lobes, which are caused by the periodicity of the errors due to the limited number of bits used in phase quantization. In this work, we present a topology that suppresses the quantization lobes using single-layer, 1-bit RRSs, by implementing a fixed but random phase delay in every unit-cell. The introduction of phase randomization breaks the periodicity of the quantization errors, thus reducing the quantization lobe level (QLL). We carry out a theoretical analysis to demonstrate the effect of phase randomization in RRSs, and for the first time, provide the condition for choosing the range of randomization required to achieve the lowest sidelobe level (SLL). Leveraging this condition, we design a single-layer, 1-bit 30×30 randomized RRS at 222.5 GHz. The reflective surface is fabricated on a thin, low-loss alumina ribbon ceramic wafer from Corning Inc. using a simplified fabrication technique suitable for large-scale production of mmWave/THz RRSs. Finally, we present the radar cross-section (RCS) characterization results obtained from a quasi-optical measurement setup validating the mitigation of quantization lobes using the proposed randomization technique.

Mitigating Quantization Lobes in mmWave Low-bit Reconfigurable Reflective Surfaces

We present a method for the mitigation of quantization lobes in single-bit reconfigurable reflective surfaces (RRSs). Typically, RRSs are planar beamforming structures consisting of hundreds or thousands of antennas with integrated tunable switches. Under plane-wave illumination, single-bit RRSs suffer from undesired side lobes or quantization lobes, which are caused by the periodicity of the errors due to the limited number of bits used in phase quantization. In this work, we present a topology that suppresses the quantization lobes using single-layer, 1-bit RRSs, by implementing a fixed but random phase delay in every unit-cell. The introduction of phase randomization breaks the periodicity of the quantization errors, thus reducing the quantization lobe level (QLL). We carry out a theoretical analysis to demonstrate the effect of phase randomization in RRSs, and for the first time, provide the condition for choosing the range of randomization required to achieve the lowest sidelobe level (SLL). Leveraging this condition, we design a single-layer, 1-bit 30×30 randomized RRS at 222.5 GHz. The reflective surface is fabricated on a thin, low-loss alumina ribbon ceramic wafer from Corning Inc. using a simplified fabrication technique suitable for large-scale production of mmWave/THz RRSs. Finally, we present the radar cross-section (RCS) characterization results obtained from a quasi-optical measurement setup validating the mitigation of quantization lobes using the proposed randomization technique.

Stochastic simulation of streamflow and spatial extremes: a continuous, wavelet-based approach

Stochastically generated streamflow time series are used for various water management and hazard estimation applications. They provide realizations of plausible but as yet unobserved streamflow time series with the same temporal and distributional characteristics as the observed data. However, the representation of non-stationarities and spatial dependence among sites remains a challenge in stochastic modeling. We investigate whether the use of frequency-domain instead of time-domain models allows for the joint simulation of realistic, continuous streamflow time series at daily resolution and spatial extremes at multiple sites. To do so, we propose the stochastic simulation approach called Phase Randomization Simulation using wavelets (PRSim.wave) which combines an empirical spatio-temporal model based on the wavelet transform and phase randomization with the flexible four-parameter kappa distribution. The approach consists of five steps: (1) derivation of random phases, (2) fitting of the kappa distribution, (3) wavelet transform, (4) inverse wavelet transform, and (5) transformation to kappa distribution. We apply and evaluate PRSim.wave on a large set of 671 catchments in the contiguous United States. We show that this approach allows for the generation of realistic time series at multiple sites exhibiting short- and long-range dependence, non-stationarities, and unobserved extreme events. Our evaluation results strongly suggest that the flexible, continuous simulation approach is potentially valuable for a diverse range of water management applications where the reproduction of spatial dependencies is of interest. Examples include the development of regional water management plans, the estimation of regional flood or drought risk, or the estimation of regional hydropower potential. Highlights. Stochastic simulation of continuous streamflow time series using an empirical, wavelet-based, spatio-temporal model in combination with the parametric kappa distribution. Generation of stochastic time series at multiple sites showing temporal short- and long-range dependence, non-stationarities, and spatial dependence in extreme events. Implementation of PRSim.wave in R package PRSim: Stochastic Simulation of Streamflow Time Series using Phase Randomization.