Strigolactones shape the assembly of root-associated microbiota in response to phosphorus availability.

Plants rely on strigolactones (SLs) to regulate their development and form symbiotic relationships with microbes as part of the adaptive phosphorus (P) efficiency strategies. However, the impact of SLs on root-associated microbial communities in response to P availability remains unknown. Here, root microbiota of SL biosynthesis (max3-11) and perception (d14-1) were compared to wild-type Col-0 plants under different P concentrations. Using high-throughput sequencing, the relationship between SLs, P concentrations, and the root-associated microbiota was investigated to reveal the variation in microbial diversity, composition, and interaction. Plant genotypes and P availability played important but different roles in shaping the root-associated microbial community. Importantly, SLs were found to attract Acinetobacter in low P conditions, which included an isolated CP-2 (Acinetobacter soli) that could promote plant growth in cocultivation experiments. Moreover, SLs could change the topologic structure within co-occurrence networks and increase the number of keystone taxa (e.g., Rhizobiaceae and Acidobacteriaceae) to enhance microbial community stability. This study reveals the key role of SLs in mediating root-associated microbiota interactions.IMPORTANCEStrigolactones (SLs) play a crucial role in plant development and their symbiotic relationships with microbes, particularly in adapting to phosphorus levels. Using high-throughput sequencing, we compared the root microbiota of plants with SL biosynthesis and perception mutants to wild-type plants under different phosphorus concentrations. These results found that SLs can attract beneficial microbes in low phosphorus conditions to enhance plant growth. Additionally, SLs affect microbial network structures, increasing the stability of microbial communities. This study highlights the key role of SLs in shaping root-associated microbial interactions, especially in response to phosphorus availability.

Cross-Layer Contrastive Learning of Latent Semantics for Facial Expression Recognition.

Convolutional neural networks (CNNs) have achieved significant improvement for the task of facial expression recognition. However, current training still suffers from the inconsistent learning intensities among different layers, i.e., the feature representations in the shallow layers are not sufficiently learned compared with those in deep layers. To this end, this work proposes a contrastive learning framework to align the feature semantics of shallow and deep layers, followed by an attention module for representing the multi-scale features in the weight-adaptive manner. The proposed algorithm has three main merits. First, the learning intensity, defined as the magnitude of the backpropagation gradient, of the features on the shallow layer is enhanced by cross-layer contrastive learning. Second, the latent semantics in the shallow-layer and deep-layer features are explored and aligned in the contrastive learning, and thus the fine-grained characteristics of expressions can be taken into account for the feature representation learning. Third, by integrating the multi-scale features from multiple layers with an attention module, our algorithm achieved the state-of-the-art performances, i.e. 92.21%, 89.50%, 62.82%, on three in-the-wild expression databases, i.e. RAF-DB, FERPlus, SFEW, and the second best performance, i.e. 65.29% on AffectNet dataset. Our codes will be made publicly available.

Enhancing perovskite solar cells efficiency through cesium fluoride mediated surface lead iodide modulation.

The presence of an excessive amount of lead iodide on the surface of perovskite solar cells (PSCs) is a significant contributing factor that adversely affects the stability of these devices when exposed to continuous light. To address this issue, we developed an effective strategy involving polishing PbI2 on a perovskite surface using CsF. In this study, we investigated the effects of CsF post-treatment on perovskite films and their photovoltaic properties. The results of the time-resolved photoluminescence and ultraviolet photoelectron spectroscopy tests reveal the significant positive impact of our passivation method based on CsF, which reduces the valence band offset between the perovskite and hole transport layers while simultaneously enhancing the carrier interface transport. PSCs treated with CsF exhibited a photoelectric conversion efficiency (PCE) of 24.25% and an increased fill factor (FF) of 81.72%, which surpassed those of the original PSCs (PCE = 22.12% and FF = 77.40%). Furthermore, after aging for over 2500 h at room temperature and in 30 ± 10% humidity, the PCE of the unpacked PSCs reduced to only 42% of the initial value. Furthermore, the devices treated with CsF maintained their impressive performance, with the PCE maintaining optimal levels at 91% of the initial efficiency.

Style attention based global-local aware GAN for personalized facial caricature generation.

Introduction: Caricature is an exaggerated pictorial representation of a person, which is widely used in entertainment and political media. Recently, GAN-based methods achieved automatic caricature generation through transferring caricature style and performing shape exaggeration simultaneously. However, the caricature synthesized by these methods cannot perfectly reflect the characteristics of the subject, whose shape exaggeration are not reasonable and requires facial landmarks of caricature. In addition, the existing methods always produce the bad cases in caricature style due to the simpleness of their style transfer method. Methods: In this paper, we propose a Style Attention based Global-local Aware GAN to apply the characteristics of a subject to generate personalized caricature. To integrate the facial characteristics of a subject, we introduce a landmark-based warp controller for personalized shape exaggeration, which employs the facial landmarks as control points to warp image according to its facial features, without requirement of the facial landmarks of caricature. To fuse the facial feature with caricature style appropriately, we introduce a style-attention module, which adopts an attention mechanism, instead of the simple Adaptive Instance Normalization (AdaIN) for style transfer. To reduce the bad cases and increase the quality of generated caricatures, we propose a multi-scale discriminator to both globally and locally discriminate the synthesized and real caricature, which improves the whole structure and realistic details of the synthesized caricature. Results: Experimental results on two publicly available datasets, the WebCaricature and the CaVINet datasets, validate the effectiveness of our proposed method and suggest that our proposed method achieves better performance than the existing methods. Discussion: The caricatures generated by the proposed method can not only preserve the identity of input photo but also the characteristic shape exaggeration for each person, which are highly close to the real caricatures drawn by real artists. It indicates that our method can be adopted in the real application.

Engineering NiCo2S4 nanoparticles anchored on carbon nanotubes as superior energy-storage materials for supercapacitors.

Fabricating high-capacity electrode materials toward supercapacitors has attracted increasing attention. Here we report a three-dimensional CNTs/NiCo2S4 nanocomposite material synthesized successfully by a facile one-step hydrothermal technique. As expected, a CNTs/NiCo2S4 electrode shows remarkable capacitive properties with a high specific capacitance of 890 C g-1 at 1 A g-1. It also demonstrates excellent cycle stability with an 83.5% capacitance retention rate after 5000 cycles at 10 A g-1. Importantly, when assembled into a asymmetric supercapacitor, it exhibits a high energy density (43.3 W h kg-1) and power density (800 W kg-1). The exceptional electrochemical capacity is attributed to the structural features, refined grains, and enhanced conductivity. The above results indicate that CNTs/NiCo2S4 composite electrode materials have great potential application in energy-storage devices.

Adaptive Weighting of Handcrafted Feature Losses for Facial Expression Recognition.

Due to the importance of facial expressions in human-machine interaction, a number of handcrafted features and deep neural networks have been developed for facial expression recognition. While a few studies have shown the similarity between the handcrafted features and the features learned by deep network, a new feature loss is proposed to use feature bias constraint of handcrafted and deep features to guide the deep feature learning during the early training of network. The feature maps learned with and without the proposed feature loss for a toy network suggest that our approach can fully explore the complementarity between handcrafted features and deep features. Based on the feature loss, a general framework for embedding the traditional feature information into deep network training was developed and tested using the FER2013, CK+, Oulu-CASIA, and MMI datasets. Moreover, adaptive loss weighting strategies are proposed to balance the influence of different losses for different expression databases. The experimental results show that the proposed feature loss with adaptive weighting achieves much better accuracy than the original handcrafted feature and the network trained without using our feature loss. Meanwhile, the feature loss with adaptive weighting can provide complementary information to compensate for the deficiency of a single feature.

Serum miR-22 is a novel prognostic marker for acute myeloid leukemia.

BACKGROUND: It has been demonstrated that aberrant expression of serum microRNAs is potential markers for the prognostic prediction of acute myeloid leukemia (AML). However, the clinical significance of serum miR-22 remained uncovered. In this study, we aimed to explore the potential prognostic value of serum miR-22 for AML. METHODS: Blood samples were collected from 124 patients with AML and 60 healthy individuals. Serum miR-22 level was detected by quantitative reverse transcription-polymerase chain reaction (qRT-PCR), and its potential clinical value was investigated. RESULTS: Our results showed that serum miR-22 expression was significantly downregulated in AML subjects compared to healthy controls. Serum miR-22 levels were lowest in AML patients with M4/M5 subtypes, and low serum miR-22 expression occurred more frequently in AML patients with higher white blood cell counts or poor cytogenetic risk. Receiver operating characteristic (ROC) analysis revealed that serum miR-22 well differentiated AML cases from healthy controls. In addition, serum miR-22 downregulation was closely associated with worse clinical features and shorter survival. Low serum miR-22 expression was confirmed to be an independent predictor for overall survival and relapse-free survival in AML patients. Moreover, the expression level of serum miR-22 was dramatically increased following treatment. In addition, serum miR-22 levels were significantly higher in AML patients achieving complete remission (CR) than those without CR. CONCLUSION: Collectively, serum miR-22 might serve as a novel and promising prognostic biomarker for AML.

Cobalt-Tungsten Bimetallic Carbide Nanoparticles as Efficient Catalytic Material for High-Performance Lithium-Sulfur Batteries.

Lithium-sulfur (Li-S) batteries are promising candidates for next-generation energy storage devices owing to their advantages such as high theoretical specific capacity and energy density. However, the shuttle effect of polysulfide intermediates and the slow electrochemical kinetics have a severe passive effect on the cycling stability and rate performance. A Co3 W3 C@C composite was prepared through a simple one-pot pyrolysis method and used as a modifying layer on a commercial separator. The obtained modified separator not only prevented the shuttle effect through both strong chemical interaction and a physical barrier toward polysulfides, but also acted as a catalytic membrane to catalyze the electrochemical redox of active sulfur species. By employing the coated separator, the cathode with 60 wt % sulfur delivered a high initial capacity of 1345 mAh g-1 at 0.1 A g-1 , excellent rate performance with a high capacity of 670 mAh g-1 even at 7 A g-1 , and outstanding cycle performance with a low decay rate of 0.06 % per cycle and an average Coulombic efficiency of 99.3 % within 500 cycles at 1 A g-1 . Even at a sulfur loading of 3 mg cm-1 , a high initial capacity of 869 mAh g-1 and 632 mAh g-1 after 200 cycles at 1 A g-1 were obtained. The results demonstrate the advantages of Co-W bimetallic carbide in preventing the shuttle effect and promoting the redox kinetics for high performance Li-S batteries.

3D Interpenetrating Network for High-Performance Nonfullerene Acceptors via Asymmetric Chlorine Substitution.

Two chlorine-substituted isomers, ITIC-2Cl-ß and a-ITIC-2Cl, were synthesized for potential use as nonfullerene acceptors. The two molecules differ in the position of chlorine atoms, leading to symmetric (ITIC-2Cl-ß) and asymmetric (a-ITIC-2Cl) molecular configuration. In single crystals, the two molecules exhibit a completely different arrangement and stacking as derived from X-ray diffraction analysis. Whereas ITIC-2Cl-ß has a linear packing structure, a-ITIC-2Cl forms a 3D interpenetrating network structure with shorter π-π distances and better molecular planarity. Therefore, a high power conversion efficiency of >12% is obtained by a-ITIC-2Cl-based devices. It is ∼10% higher than that of ITIC-2Cl-ß-based devices due to the chlorine substituent effect. Thus the fine-tuning of the Cl-substituted position seems to be a promising strategy to construct a 3D interpenetrating charge transportation network and achieve higher performance organic solar cells (OSCs).

Effectiveness and potential risk of CaO application in Cd-contaminated paddy soil.

In this study, the accurate effectiveness of CaO in mitigating Cd bioavailability in paddy soil-rice system was investigated and moreover, the potential for reversibility of CaO liming process was provided. Increasing soil pH to ≥6.5 by CaO was determined to be the minimal threshold for minimizing Cd transfer into rice in historically contaminated soils across light to severe Cd levels, while an elevated CaO ratio was needed for soil with recent input of Cd. In CaO remediation treatment, a reduced pool of bioavailable Cd in rhizosphere soil coupled with an increased Cd retention by Fe plaque and an inhibited planta Cd transfer was determined consistently and proposed to be largely responsible for the significant reduction in brown rice Cd. Under continuous simulated acid precipitation test, a negligible level of Cd in eluate with ∼1 unit higher pH than control was recorded with CaO. Significant acidification, however, increased Cd solubilization in the limed soil than in unlimited control, notably at pH 5.5-6.5. As indicated by Visual MINTEQ, a higher Cd-carbonate solubility and much decreased Cd complexation on Fe-(hydr)-oxides across this pH range occurred as a result of elevated Ca input. This suggests that a high soil pH (≥6.5) needs to be permanently maintained once liming has been performed to minimize Cd mobilization. Therefore, amending Cd-contaminated soils with CaO is a cost-effective remedial measure for reducing Cd bioavailability to paddy rice, while a high soil pH need to be permanently maintained to sustain this beneficial effect.

Active AU Based Patch Weighting for Facial Expression Recognition.

Facial expression has many applications in human-computer interaction. Although feature extraction and selection have been well studied, the specificity of each expression variation is not fully explored in state-of-the-art works. In this work, the problem of multiclass expression recognition is converted into triplet-wise expression recognition. For each expression triplet, a new feature optimization model based on action unit (AU) weighting and patch weight optimization is proposed to represent the specificity of the expression triplet. The sparse representation-based approach is then proposed to detect the active AUs of the testing sample for better generalization. The algorithm achieved competitive accuracies of 89.67% and 94.09% for the Jaffe and Cohn-Kanade (CK+) databases, respectively. Better cross-database performance has also been observed.