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The dynamic interaction between phonons and dislocations in LiF has been studied using molecular dynamics simulations. The simulations have captured the strong dynamic interactions between low-frequency slow transverse acoustic phonons and dislocations that were observed in experiments. Simulation results reveal that the strong dynamic interaction is attributed to resonant interactions between dislocations and slow transverse acoustic phonons. Each dislocation segment is found to possess a set of resonant modes characterized by large-amplitude out-of-phase vibrations of atoms on both sides of the dislocation slip plane. The resonant frequencies associated with these modes exhibit a nearly linear distribution with respect to the mode order. Contrary to previous beliefs, the resonant frequencies of dislocations exhibit only a weak correlation with the dislocation length. Additionally, each dislocation exhibits a dominant resonant mode that corresponds to the strongest vibration mode in response to phonons. This dominant resonant mode is not always the first resonant mode with the lowest frequency. Its specific order depends on the dislocation length. Simulation results have also demonstrated that the resonant modes of dislocations can be influenced by the interactions from neighboring dislocations. 

RNAs are fundamental in living cells and perform critical functions determined by their tertiary architectures. However, accurate modeling of 3D RNA structure remains a challenging problem. We present a novel method, DRfold, to predict RNA tertiary structures by simultaneous learning of local frame rotations and geometric restraints from experimentally solved RNA structures, where the learned knowledge is converted into a hybrid energy potential to guide RNA structure assembly. The method significantly outperforms previous approaches by >73.3% in TM-score on a sequence-nonredundant dataset containing recently released structures. Detailed analyses showed that the major contribution to the improvements arise from the deep end-to-end learning supervised with the atom coordinates and the composite energy function integrating complementary information from geometry restraints and end-to-end learning models. The open-source DRfold program with fast training protocol allows large-scale application of high-resolution RNA structure modeling and can be further improved with future expansion of RNA structure databases.

 

Leveraging iterative alignment search through genomic and metagenome sequence databases, we report the DeepMSA2 pipeline for uniform protein single- and multichain multiple-sequence alignment (MSA) construction. Large-scale benchmarks show that DeepMSA2 MSAs can remarkably increase the accuracy of protein tertiary and quaternary structure predictions compared with current state-of-the-art methods. An integrated pipeline with DeepMSA2 participated in the most recent CASP15 experiment and created complex structural models with considerably higher quality than the AlphaFold2-Multimer server (v.2.2.0). Detailed data analyses show that the major advantage of DeepMSA2 lies in its balanced alignment search and effective model selection, and in the power of integrating huge metagenomics databases. These results demonstrate a new avenue to improve deep learning protein structure prediction through advanced MSA construction and provide additional evidence that optimization of input information to deep learning-based structure prediction methods must be considered with as much care as the design of the predictor itself.

 

The paper presents a multiscale study of the kinetic processes of the heteroepitaxial growth of the PbSe/PbTe (111) and PbTe/PbSe(001) systems, using the Concurrent Atomistic-Continuum (CAC) method as the simulation tool. The CAC simulations have reproduced the Stranski–Krastanov growth mode and the layer-by-layer growth mode of the two systems, respectively; the pyramid-shaped island morphology of the PbSe epilayer on PbTe (111), the square-like misfit dislocation networks within the PbTe/PbSe(001) interface, and the critical thickness for the PbTe/PbSe(001) system at which coherent interfaces transit to semi-coherent interfaces with the formation of misfit dislocations, all in good agreement with experimental observations. Four types of misfit dislocations are found to form during the growth of the two PbTe/PbSe heterosystems, and hexagonal-like misfit dislocation networks are observed within the PbSe/PbTe(111) interfaces. The growth processes, including the formation of misfit dislocations, have been visualized. Dislocation half-loops have been observed to nucleate from the epilayer surfaces. These half-loops extend towards the interface by climb or glide motions, interact with other half-loops, and form misfit dislocation networks at the interfaces and threading dislocations extending from interfaces to epilayer surfaces. The dominant types of misfit dislocations in both systems are found to be those with Burgers vectors parallel to the interfaces, whereas the misfit dislocations with Burgers vectors inclined to the interface have a low likelihood of generation and tend to annihilate. The size of the substrate is demonstrated to have a significant effect on the formation, evolution, and distribution of dislocations on the growth of PbSe on PbTe(111). 

Clustering is a critical component of single-cell RNA sequencing (scRNA-seq) data analysis and can help reveal cell types and infer cell lineages. Despite considerable successes, there are few methods tailored to investigating cluster-specific genes contributing to cell heterogeneity, which can promote biological understanding of cell heterogeneity. In this study, we propose a zero-inflated negative binomial mixture model (ZINBMM) that simultaneously achieves effective scRNA-seq data clustering and gene selection. ZINBMM conducts a systemic analysis on raw counts, accommodating both batch effects and dropout events. Simulations and the analysis of five scRNA-seq datasets demonstrate the practical applicability of ZINBMM.

 

We study the collapsing of Calabi–Yau metrics and of Kähler–Ricci flows on fiber spaces where the base is smooth.We identify the collapsed Gromov–Hausdorff limit of the Kähler–Ricci flow when the divisorial part of the discriminant locus has simple normal crossings.In either setting, we also obtain an explicit bound for the real codimension-2 Hausdorff measure of the Cheeger–Colding singular set and identify a sufficient condition from birational geometry to understand the metric behavior of the limiting metric on the base. 

The Granada Basin in southeast Spain is an area of moderate seismicity. Yet, it hosts some of the highest seismic hazards in the Iberian Peninsula due to the presence of shallow soft sediments amplifying local ground motion. In urban areas, seismic measurements often suffer from sparse instrumentation. An enticing alternative to conventional seismometers is the distributed acoustic sensing (DAS) technology that can convert fibre-optic telecommunication cables into dense arrays of seismic sensors. In this study, we perform a shallow structure analysis using the ambient seismic field interferometry method. We conduct a DAS array field test in the city of Granada on the 26 and 27 August 2020, using a telecommunication fibre. In addition to the existing limitations of using DAS with unknown fibre-ground coupling conditions, the complex geometry of the fibre and limited data recording duration further challenge the extraction of surface-wave information from the ambient seismic field in such an urban environment. Therefore, we develop a processing scheme that incorporates a frequency–wavenumber (f−k) filter to enhance the quality of the virtual shot gathers and related multimode dispersion images. We are able to use this data set to generate several shear-wave velocity (VS) profiles for different sections of the cable. The shallow VS structure shows a good agreement with different geological conditions of soil deposits. This study demonstrates that DAS could provide insights into soil characterization and seismic microzonation in urban areas. In addition, the results contribute to a better understanding of local site response to ground motion.