iterative projection algorithms are proposed as a tool for ab initio phasing in virus crystallography. The good global convergence properties of these algorithms, coupled with the spherical shape and high structural r...
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iterative projection algorithms are proposed as a tool for ab initio phasing in virus crystallography. The good global convergence properties of these algorithms, coupled with the spherical shape and high structural redundancy of icosahedral viruses, allows high resolution phases to be determined with no initial phase information. This approach is demonstrated by determining the electron density of a virus crystal with 5-fold non-crystallographic symmetry, starting with only a spherical shell envelope. The electron density obtained is sufficiently accurate for model building. The results indicate that iterative projection algorithms should be routinely applicable in virus crystallography, without the need for ancillary phase information. (C) 2016 Elsevier Inc. All rights reserved.
Coherent diffraction imaging (CDI) enables diffraction-limited high-resolution imaging without using high-quality lenses. It will be desirable to combine it with multiple spectral light sources to achieve chemically r...
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In an iterative projection algorithm proposed for ab initio phasing, the error metrics typically exhibit little improvement until a sharp decrease takes place as the iteration converges to the correct high-resolution ...
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In an iterative projection algorithm proposed for ab initio phasing, the error metrics typically exhibit little improvement until a sharp decrease takes place as the iteration converges to the correct high-resolution structure. Related to that is the small convergence probability for certain structures. As a remedy, a variable weighting scheme on the diffraction data is proposed. It focuses on phasing low-and medium-resolution data first. The weighting shifts to incorporate more high-resolution reflections when the iteration proceeds. It is found that the precipitous drop in error metrics is replaced by a less dramatic drop at an earlier stage of the iteration. It seems that once a good configuration is formed at medium resolution, convergence towards the correct high-resolution structure is almost guaranteed. The original problem of phasing all diffraction data at once is reduced to a much more manageable one due to the dramatically smaller number of reflections involved. As a result, the success rate is significantly enhanced and the speed of convergence is raised. This is illustrated by applying the new algorithm to several structures, some of which are very difficult to solve without data weighting.
The idiosyncratic components of a tensor time series factor model can exhibit serial correlations, (e.g., finance or economic data), ruling out many ponents. While the traditional higher order orthogonal iteration (HO...
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The idiosyncratic components of a tensor time series factor model can exhibit serial correlations, (e.g., finance or economic data), ruling out many ponents. While the traditional higher order orthogonal iteration (HOOI) is proved to be convergent to a set of factor loading matrices, the closeness of them to the true underlying factor loading matrices are in general not established, or only under i.i.d. Gaussian noises. Under the presence of serial and cross-correlations in the idiosyncratic components and time series variables with only bounded fourth-order moments, for tensor time series data with tensor order two or above, we propose a pre-averaging procedure that can be considered a random projection method. The estimated directions corresponding to the strongest factors are then used for projecting the data for a potentially improved re-estimation of the factor loading spaces themselves, with theoretical guarantees and rate of convergence spelt out when not all factors are pervasive. We also propose a new rank estimation method, which utilizes correlation information from the projected data. Extensive simulations are performed and compared to other state-of-the-art or traditional alternatives. A set of tensor-valued NYC taxi data is also analyzed.
This paper describes the construction of chirp-like constant-modulus transmit waveforms designed so as to possess multiple notches in their frequency spectra at user-specified frequencies. We propose an iterative proj...
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ISBN:
(纸本)9781424489022
This paper describes the construction of chirp-like constant-modulus transmit waveforms designed so as to possess multiple notches in their frequency spectra at user-specified frequencies. We propose an iterative projection algorithm with low computational complexity. In wide-band radar systems, such frequency-notched transmit waveforms are needed so as to avoid transmitting into frequency bands that are used by other systems such as for communication, navigation, etc.
This paper studies the realizing progress of data mining in psychological evaluation. Based on the matrix of evaluation data and the actual evaluation work, we propose a kind of generalized linear regression model wit...
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ISBN:
(纸本)9780769534985
This paper studies the realizing progress of data mining in psychological evaluation. Based on the matrix of evaluation data and the actual evaluation work, we propose a kind of generalized linear regression model with convex constraint, named as Evaluation Model, in which the dependent variable and regression coefficients all are unknown. We analyze the algorithm of the model with linear regression method. Then the least square estimate of parameters using the iterative projection algorithm is presented. At last, we use this least square iterative method to work out the parameters of the evaluation model. Our work could be a useful guide for the further research of data mining in psychological evaluation.
High resolution imaging of biological macromolecules using x-ray crystallography is a key component of modern molecular biology, the results of which are essential for understanding biological processes in health and ...
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ISBN:
(数字)9781510621169
ISBN:
(纸本)9781510621169
High resolution imaging of biological macromolecules using x-ray crystallography is a key component of modern molecular biology, the results of which are essential for understanding biological processes in health and disease, and for drug design. Macromolecular imaging is currently undergoing a revolution as a result of the recent availability of x-ray free-electron lasers (XFELs). XFELs produce extremely intense, ultra-short x-ray pulses which offer the possibility of imaging specimens that are different to the 3D crystals used in conventional x-ray crystallography. The application of XFEL imaging to nano-crystalline fibrous specimens - long, slender systems that are periodic in their axial direction exhibit partial lateral crystallinity - is investigated. It is shown that individual Fourier amplitudes can be measured from XFEL data from such specimens. It is demonstrated that the image reconstruction problem from diffraction data for specimens with reduced crystallinity, specifically 2D membranes, is achievable. Although such specimens are weakly diffracting, they potentially offer more information in their diffraction than do 3D crystals. Image reconstruction is demonstrated by simulation.
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