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We report the mechanical properties of cubic boron nitride (c-BN) and diamond under the combined impact of dynamical pressure and temperature, calculated using ab initio molecular dynamics. Our study revealed a pronounced sensitivity of the mechanical properties of c-BN to applied pressure. Notably, c-BN undergoes a brittle-to-ductile transition at ∼220 GPa, consistent across various dynamical temperatures, while diamond exhibits no such transition. Furthermore, the Vickers hardness profile for c-BN closely mirrors that of diamond across a spectrum of temperature–pressure conditions, highlighting c-BN's significant mechanical robustness. These results underscore the superior resilience and adaptability of c-BN compared to diamond, suggesting its potential as an ideal candidate for applications in extreme environments. 

Postsynaptic cytosolic Cl − concentration determines whether GABAergic and glycinergic synapses are inhibitory or excitatory. We have shown that nitric oxide (NO) initiates the release of Cl − from acidic internal stores into the cytosol of retinal amacrine cells (ACs) thereby elevating cytosolic Cl − . In addition, we found that cystic fibrosis transmembrane conductance regulator (CFTR) expression and Ca 2+ elevations are necessary for the transient effects of NO on cytosolic Cl − levels, but the mechanism remains to be elucidated. Here, we investigated the involvement of TMEM16A as a possible link between Ca 2+ elevations and cytosolic Cl − release. TMEM16A is a Ca 2+ -activated Cl − channel that is functionally coupled with CFTR in epithelia. Both proteins are also expressed in neurons. Based on this and its Ca 2+ dependence, we test the hypothesis that TMEM16A participates in the NO-dependent elevation in cytosolic Cl − in ACs. Chick retina ACs express TMEM16A as shown by Western blot analysis, single-cell PCR, and immunocytochemistry. Electrophysiology experiments demonstrate that TMEM16A functions in amacrine cells. Pharmacological inhibition of TMEM16A with T16inh-AO1 reduces the NO-dependent Cl − release as indicated by the diminished shift in the reversal potential of GABA A receptor-mediated currents. We confirmed the involvement of TMEM16A in the NO-dependent Cl − release using CRISPR/Cas9 knockdown of TMEM16A. Two different modalities targeting the gene for TMEM16A ( ANO1 ) were tested in retinal amacrine cells: an all-in-one plasmid vector and crRNA/tracrRNA/Cas9 ribonucleoprotein. The all-in-one CRISPR/Cas9 modality did not change the expression of TMEM16A protein and produced no change in the response to NO. However, TMEM16A-specific crRNA/tracrRNA/Cas9 ribonucleoprotein effectively reduces both TMEM16A protein levels and the NO-dependent shift in the reversal potential of GABA-gated currents. These results show that TMEM16A plays a role in the NO-dependent Cl − release from retinal ACs. 

Abstract Ultrahigh surface-to-volume ratio in nanoscale materials, could dramatically facilitate mass transport, leading to surface-mediated diffusion similar to Coble-type creep in polycrystalline materials. Unfortunately, the Coble creep is just a conceptual model, and the associated physical mechanisms of mass transport have never been revealed at atomic scale. Akin to the ambiguities in Coble creep, atomic surface diffusion in nanoscale crystals remains largely unclear, especially when mediating yielding and plastic flow. Here, by using in situ nanomechanical testing under high-resolution transmission electron microscope, we find that the diffusion-assisted dislocation nucleation induces the transition from a normal to an inverse Hall-Petch-like relation of the strength-size dependence and the surface-creep leads to the abnormal softening in flow stress with the reduction in size of nanoscale silver, contrary to the classical “alternating dislocation starvation” behavior in nanoscale platinum. This work provides insights into the atomic-scale mechanisms of diffusion-mediated deformation in nanoscale materials, and impact on the design for ultrasmall-sized nanomechanical devices. 

Fresh samples of basalts were collected by dredging from the Nanyue intraplate seamount in the Southwest sub-basin of the South China Sea (SCS). These are alkali basalts displaying right-sloping, chondrite-normalized rare earth element (REE) profiles. The investigated basalts are characterized by low Os content (60.37–85.13 ppt) and radiogenic 187Os/188Os ratios (~0.19 to 0.21). Furthermore, 40Ar/39Ar dating of the Nanyue basalts showed they formed during the Tortonian (~8.3 Ma) and, thus, are products of (Late Cenozoic) post-spreading volcanism. The Sr–Nd–Pb–Hf isotopic compositions of the Nanyue basalts indicate that their parental melts were derived from an upper mantle reservoir possessing the so-called Dupal isotopic anomaly. Semiquantitative isotopic modeling demonstrates that the isotopic compositions of the Nanyue basalts can be reproduced by mixing three components: the average Pacific midocean ridge basalt (MORB), the lower continental crust (LCC), and the average Hainan ocean island basalt (OIB). Our preferred hypothesis for the genesis of the Nanyue basalts is that their parental magmas were produced from an originally depleted mantle (DM) source that was much affected by the activity of the Hainan plume. Initially, the Hainan diapir caused a thermal perturbation in the upper mantle under the present-day Southwest sub-basin of the SCS that led to erosion of the overlying LCC. Eventually, the resultant suboceanic lithospheric mantle (SOLM) interacted with OIB-type components derived from the nearby Hainan plume. Collectively, these processes contributed crustal- and plume-type components to the upper mantle underlying the Southwest sub-basin of the SCS. This implies that the Dupal isotopic signature in the upper mantle beneath the SCS was an artifact of in situ geological processes rather than a feature inherited from a Southern Hemispheric, upper mantle source. 

In this paper, we propose a deep learning approach to tackle the automatic summarization tasks by incorporating topic information into the convolutional sequence-to-sequence (ConvS2S) model and using self-critical sequence training (SCST) for optimization. Through jointly attending to topics and word-level alignment, our approach can improve coherence, diversity, and informativeness of generated summaries via a biased probability generation mechanism. On the other hand, reinforcement training, like SCST, directly optimizes the proposed model with respect to the non-differentiable metric ROUGE, which also avoids the exposure bias during inference. We carry out the experimental evaluation with state-of-the-art methods over the Gigaword, DUC-2004, and LCSTS datasets. The empirical results demonstrate the superiority of our proposed method in the abstractive summarization.