Developing high-performance film dielectrics for capacitive energy storage has been a great challenge for modern electrical devices. Despite good results obtained in lead titanate-based dielectrics, ...lead-free alternatives are strongly desirable due to environmental concerns. Here we demonstrate that giant energy densities of ~70 J cm
, together with high efficiency as well as excellent cycling and thermal stability, can be achieved in lead-free bismuth ferrite-strontium titanate solid-solution films through domain engineering. It is revealed that the incorporation of strontium titanate transforms the ferroelectric micro-domains of bismuth ferrite into highly-dynamic polar nano-regions, resulting in a ferroelectric to relaxor-ferroelectric transition with concurrently improved energy density and efficiency. Additionally, the introduction of strontium titanate greatly improves the electrical insulation and breakdown strength of the films by suppressing the formation of oxygen vacancies. This work opens up a feasible and propagable route, i.e., domain engineering, to systematically develop new lead-free dielectrics for energy storage.
Surface reactions constitute the foundation of various energy conversion/storage technologies, such as the lithium–sulfur (Li‐S) batteries. To expedite surface reactions for high‐rate battery ...applications demands in‐depth understanding of reaction kinetics and rational catalyst design. Now an in situ extrinsic‐metal etching strategy is used to activate an inert monometal nitride of hexagonal Ni3N through iron‐incorporated cubic Ni3FeN. In situ etched Ni3FeN regulates polysulfide‐involving surface reactions at high rates. Electron microscopy was used to unveil the mechanism of in situ catalyst transformation. The Li‐S batteries modified with Ni3FeN exhibited superb rate capability, remarkable cycling stability at a high sulfur loading of 4.8 mg cm−2, and lean‐electrolyte operability. This work opens up the exploration of multimetallic alloys and compounds as kinetic regulators for high‐rate Li‐S batteries and also elucidates catalytic surface reactions and the role of defect chemistry.
Inert hexagonal Ni3N can be activated by an extrinsic metal‐incorporating strategy with in situ etching that uses cubic Ni3FeN. Vacancy‐rich Ni3FeN catalysts kinetically regulate polysulfide‐involving reactions at high rates for use in advanced lithium–sulfur batteries.
Summary
NAC transcription factors play important roles in plant growth, development and stress responses. Previously, we identified multiple NAC genes in soybean (Glycine max). Here, we identify the ...roles of two genes, GmNAC11 and GmNAC20, in stress responses and other processes. The two genes were differentially induced by multiple abiotic stresses and plant hormones, and their transcripts were abundant in roots and cotyledons. Both genes encoded proteins that localized to the nucleus and bound to the core DNA sequence CGTG/A. In the protoplast assay system, GmNAC11 acts as a transcriptional activator, whereas GmNAC20 functions as a mild repressor; however, the C‐terminal end of GmANC20 has transcriptional activation activity. Over‐expression of GmNAC20 enhances salt and freezing tolerance in transgenic Arabidopsis plants; however, GmNAC11 over‐expression only improves salt tolerance. Over‐expression of GmNAC20 also promotes lateral root formation. GmNAC20 may regulate stress tolerance through activation of the DREB/CBF–COR pathway, and may control lateral root development by altering auxin signaling‐related genes. GmNAC11 probably regulates DREB1A and other stress‐related genes. The roles of the two GmNAC genes in stress tolerance were further analyzed in soybean transgenic hairy roots. These results provide a basis for genetic manipulation to improve the agronomic traits of important crops.
Dysregulated prefrontal control over amygdala is engaged in the pathogenesis of psychiatric diseases including depression and anxiety disorders. Here we show that, in a rodent anxiety model induced ...by chronic restraint stress (CRS), the dysregulation occurs in basolateral amygdala projection neurons receiving mono-directional inputs from dorsomedial prefrontal cortex (dmPFC→BLA PNs) rather than those reciprocally connected with dmPFC (dmPFC↔BLA PNs). Specifically, CRS shifts the dmPFC-driven excitatory-inhibitory balance towards excitation in the former, but not latter population. Such specificity is preferential to connections made by dmPFC, caused by enhanced presynaptic glutamate release, and highly correlated with the increased anxiety-like behavior in stressed mice. Importantly, low-frequency optogenetic stimulation of dmPFC afferents in BLA normalizes the enhanced prefrontal glutamate release onto dmPFC→BLA PNs and lastingly attenuates CRS-induced increase of anxiety-like behavior. Our findings thus reveal a target cell-based dysregulation of mPFC-to-amygdala transmission for stress-induced anxiety.
The click feature of an image, defined as the user click frequency vector of the image on a predefined word vocabulary, is known to effectively reduce the semantic gap for fine-grained image ...recognition. Unfortunately, user click frequency data are usually absent in practice. It remains challenging to predict the click feature from the visual feature, because the user click frequency vector of an image is always noisy and sparse. In this paper, we devise a H ierarchical D eep W ord E mbedding (HDWE) model by integrating sparse constraints and an improved RELU operator to address click feature prediction from visual features. HDWE is a coarse-to-fine click feature predictor that is learned with the help of an auxiliary image dataset containing click information. It can therefore discover the hierarchy of word semantics. We evaluate HDWE on three dog and one bird image datasets, in which Clickture-Dog and Clickture-Bird are utilized as auxiliary datasets to provide click data, respectively. Our empirical studies show that HDWE has 1) higher recognition accuracy, 2) a larger compression ratio, and 3) good one-shot learning ability and scalability to unseen categories.
Objective
To assess the accuracy of dynamic computer‐assisted implant surgery.
Materials and methods
An electronic search up to March 2020 was conducted using PubMed, Embase, and the Cochrane Central ...Register of Controlled Trial to identify studies using dynamic navigation in implant surgery, and additional manual search was performed as well. Clinical trials and model studies were selected. The primary outcome was accuracy. A single‐arm meta‐analysis of continuous data was conducted. Meta‐regression was utilized for comparison on study design, guidance method, jaw, and systems.
Results
Ten studies, four randomized controlled trials (RCT) and six prospective studies, met the inclusion criteria. A total of 1,298 drillings and implants were evaluated. The meta‐analysis of the accuracy (five clinical trials and five model studies) revealed average global platform deviation, global apex deviation, and angular deviation were 1.02 mm, 95% CI (0.83, 1.21), 1.33 mm, 95% CI (0.98, 1.67), and 3.59°, 95% CI (2.09, 5.09). Meta‐regression shown no difference between model studies and clinical trials (p = .295, 0.336, 0.185), drilling holes and implant (p = .36, 0.279, 0.695), maxilla and mandible (p = .875, 0.632, 0.281), and five different systems (p = .762, 0.342, 0.336).
Conclusion
Accuracy of dynamic computer‐aided implant surgery reaches a clinically acceptable range and has potential in clinical usage, but more patient‐centered outcomes and socio‐economic benefits should be reported.
Controlled morphology modulation of graphene carbon nitride (g‐C3N4) is successfully realized from bulk to 3D loose foam architecture via the blowing effect of a bubble, which can be controlled by ...heating rate. The loose foam network is comprised by spatially scaffolded few‐atom‐layer interconnected flakes with the large specific surface area, as supporters to prevent agglomeration and provide a pathway for electron/phonon transports. The photocatalytic performance of 3D foam strutted g‐C3N4 toward RhB decomposition and hydrogen evolution is significantly enhanced with the morphology optimization while its excellent optoelectronic properties are maintained simultaneously. Herein, the ultrathin, mono‐, and high‐quality foam g‐C3N4 interconnected flakes with controlled layer are facilely obtained through ultrasonic, thus overcoming the drawbacks of a traditional top–down approach, opening a wide horizon for diverse practical usages. Additionally, the layer control mechanism of 3D hierarchical structure has been explored by means of bubble growth kinetics analysis and the density functional theory calculations.
3D foam strutted g‐C3N4 synthesized upon bubble template shows effective photocatalytic activity as well as highly stable optoelectronic properties, overcoming the problem of its photoluminescence degradation when applied as a photocatalyst. Kinetic characterization and theoretical calculations reveal ultrathin foam growth and a layer control mechanism, which is crucial for the application of this promising class of materials.
The lithium–sulfur (Li–S) battery is regarded as a promising high‐energy‐density battery system, in which the dissolution–precipitation redox reactions of the S cathode are critical. However, soluble ...Li polysulfides (LiPSs), as the indispensable intermediates, easily diffuse to the Li anode and react with the Li metal severely, thus depleting the active materials and inducing the rapid failure of the battery, especially under practical conditions. Herein, an organosulfur‐containing solid electrolyte interphase (SEI) is tailored for the stabilizaiton of the Li anode in Li–S batteries by employing 3,5‐bis(trifluoromethyl)thiophenol as an electrolyte additive. The organosulfur‐containing SEI protects the Li anode from the detrimental reactions with LiPSs and decreases its corrosion. Under practical conditions with a high‐loading S cathode (4.5 mgS cm−2), a low electrolyte/S ratio (5.0 µL mgS−1), and an ultrathin Li anode (50 µm), a Li–S battery delivers 82 cycles with an organosulfur‐containing SEI in comparison to 42 cycles with a routine SEI. This work provokes the vital insights into the role of the organic components of SEI in the protection of the Li anode in practical Li–S batteries.
An organosulfur‐containing solid electrolyte interphase (SEI) is tailored for the stabilization of the Li anode in Li–S batteries by employing 3,5‐bis(trifluoromethyl)thiophenol as an electrolyte additive. The organosulfur‐containing SEI protects the Li anode from the detrimental reactions with Li polysulfides (LiPSs). A Li–S battery delivers 82 cycles with an organosulfur‐containing SEI in comparison to 42 cycles with a routine SEI under practical conditions.
This paper presents an unsupervised deep-learning framework named local deep-feature alignment (LDFA) for dimension reduction. We construct neighbourhood for each data sample and learn a local ...stacked contractive auto-encoder (SCAE) from the neighbourhood to extract the local deep features. Next, we exploit an affine transformation to align the local deep features of each neighbourhood with the global features. Moreover, we derive an approach from LDFA to map explicitly a new data sample into the learned low-dimensional subspace. The advantage of the LDFA method is that it learns both local and global characteristics of the data sample set: the local SCAEs capture local characteristics contained in the data set, while the global alignment procedures encode the interdependencies between neighbourhoods into the final low-dimensional feature representations. Experimental results on data visualization, clustering, and classification show that the LDFA method is competitive with several well-known dimension reduction techniques, and exploiting locality in deep learning is a research topic worth further exploring.
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