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The breakthrough in cryo-electron microscopy (cryo-EM) technology has led to an increasing number of density maps of biological macromolecules. However, constructing accurate protein complex atomic structures from cryo-EM maps remains a challenge. In this study, we extend our previously developed DEMO-EM to present DEMO-EM2, an automated method for constructing protein complex models from cryo-EM maps through an iterative assembly procedure intertwining chain- and domain-level matching and fitting for predicted chain models. The method was carefully evaluated on 27 cryo-electron tomography (cryo-ET) maps and 16 single-particle EM maps, where DEMO-EM2 models achieved an average TM-score of 0.92, outperforming those of state-of-the-art methods. The results demonstrate an efficient method that enables the rapid and reliable solution of challenging cryo-EM structure modeling problems.

 

Vitrimers have the characteristics of shape-reforming and surface-welding, and have the same excellent mechanical properties as thermosets; so vitrimers hold the promise of a broad alternative to traditional plastics. Since their initial introduction in 2011, vitrimers have been applied to many unique applications such as reworkable composites and liquid crystal elastomer actuators. A series of experiments have investigated the effects of reprocessing conditions (such as temperature, time, and pressure) on recycled materials. However, the effect of particle size on the mechanical properties of recycled materials has not been reported. In this paper, we conducted an experimental study on the recovery of epoxy-acid vitrimers of different particle sizes. Epoxy-acid vitrimer powders with different particle size distributions were prepared and characterized. The effects of particle size on the mechanical properties of regenerated epoxy-acid vitrimers were investigated by dynamic mechanical analysis and uniaxial tensile tests. In addition, other processing parameters such as temperature, time, and pressure are discussed, as well as their interaction with particle size. This study helped to refine the vitrimer reprocessing condition parameter toolbox, providing experimental support for the easy and reliable control of the kinetics of the bond exchange reaction. 

Tropical cyclones (TC) transfer kinetic energy to the upper ocean and thus accelerate the ocean mixed layer (OML) currents. However, the quantitative link between near‐surface currents and high wind speeds, under extreme weather conditions, remains poorly understood. In this study, we use multi‐mission satellites and drifting‐buoy observations to investigate the connections between TC surface winds and currents, including their spatial distribution characteristics. Observed ageostrophic current speeds in the OML increase linearly with wind speeds (for the range 20–50 m/s). The ratios of the ageostrophic current speeds to the wind speeds are found to vary with TC quadrants. In particular, the mean ratio is around 2% in the left‐front and left‐rear quadrants with relatively small variability, compared to between 2% and 4% in the right‐front and right‐rear quadrants, with much higher variations. Surface winds and currents both exhibit strong asymmetric features, with the largest wind speeds and currents on the TC right side. In the eyewall region of Hurricane Igor, high winds (e.g., about 47 m/s) induce strong currents (about 2 m/s). The directional rotations of surface winds and currents are resonant and dependent on the location within the storm. Wind directions are approximately aligned with current directions in the right‐front quadrant; a difference of about 90° occurs in the left‐front and left‐rear quadrants. The directional discrepancy between winds and currents in the right‐rear quadrant is smaller. Reliable observations of the wind‐current relation, including asymmetric features, support published theories developed in idealized numerical experiments to explain the upper ocean response to TCs.

 

The chemically crosslinked network structures make epoxies, the most common thermosets, unable or hard to be recycled, causing environmental problems and economic losses. Epoxy‐based vitrimers, polymer networks deriving from epoxy resins, can be thermally malleable according to bond exchange reactions (BERs), opening the door to recycle epoxy thermosets. Here a series of experiments were carried out to study the effects of processing conditions (such as particle size distributions, temperature, time, and pressure) on recycling of an epoxy‐anhydride vitrimer. Polymer powders from the epoxy‐anhydride vitrimer with different size distributions were prepared and characterized, and the influence of particle size on the mechanical performance of recycled epoxy‐anhydride vitrimers was investigated by dynamic mechanical analysis and uniaxial tensile test. Experimental results demonstrated that finer polymer powders can increase the contacting surfaces of recycled materials and thus result in high quality of recycled materials. In addition, the influences of other treating parameters, such as temperature, time, and pressure, were also discussed in this study. Adjusting these treating parameters can help the design of an optimized reprocessing procedure to meet practical engineering applications.

 

There is a large literature on methods of analysis for randomized trials with noncompliance which focuses on the effect of treatment on the average outcome. The paper considers evaluating the effect of treatment on the entire distribution and general functions of this effect. For distributional treatment effects, fully non-parametric and fully parametric approaches have been proposed. The fully non-parametric approach could be inefficient but the fully parametric approach is not robust to the violation of distribution assumptions. We develop a semiparametric instrumental variable method based on the empirical likelihood approach. Our method can be applied to general outcomes and general functions of outcome distributions and allows us to predict a subject’s latent compliance class on the basis of an observed outcome value in observed assignment and treatment received groups. Asymptotic results for the estimators and likelihood ratio statistic are derived. A simulation study shows that our estimators of various treatment effects are substantially more efficient than the currently used fully non-parametric estimators. The method is illustrated by an analysis of data from a randomized trial of an encouragement intervention to improve adherence to prescribed depression treatments among depressed elderly patients in primary care practices.

 

Recently there has been a surge in econometric and epidemiologic works focusing on estimating average treatment effects under various sets of assumptions. Estimation of average treatment effects in observational studies often requires adjustment for differences in pretreatment variables. Rosenbaum and Rubin have proposed the propensity score method for estimating the average treatment effect by adjusting pretreatment variables. In this paper, the empirical likelihood method is used to estimate average treatment effects on the treated under the difference-in-differences framework. The advantage of this approach is that the common marginal covariate information can be incorporated naturally to enhance the estimation of average treatment effects. Compared with other approaches in the literature, the method proposed can provide more efficient estimation. A simulation study and a real economic data analysis are presented.