Multi-Label Continual Learning using Augmented Graph Convolutional Network

Multi-Label Continual Learning (MLCL) builds a class-incremental framework in a sequential multi-label image recognition data stream. The critical challenges of MLCL are the construction of label relationships on past-missing and future-missing partial labels of training data and the catastrophic forgetting on old classes, resulting in poor generalization. To solve the problems, the study proposes an Augmented Graph Convolutional Network (AGCN++) that can construct the cross-task label relationships in MLCL and sustain catastrophic forgetting. First, we build an Augmented Correlation Matrix (ACM) across all seen classes, where the intra-task relationships derive from the hard label statistics. In contrast, the inter-task relationships leverage hard and soft labels from data and a constructed expert network. Then, we propose a novel partial label encoder (PLE) for MLCL, which can extract dynamic class representation for each partial label image as graph nodes and help generate soft labels to create a more convincing ACM and suppress forgetting. Last, to suppress the forgetting of label dependencies across old tasks, we propose a relationship-preserving constrainter to construct label relationships. The inter-class topology can be augmented automatically, which also yields effective class representations. The proposed method is evaluated using two multi-label image benchmarks. The experimental results show that the proposed way is effective for MLCL image recognition and can build convincing correlations across tasks even if the labels of previous tasks are missing

Structural basis for concerted recruitment and activation of IRF-3 by innate immune adaptor proteins

Type I IFNs are key cytokines mediating innate antiviral immunity. cGMP-AMP synthase, ritinoic acid-inducible protein 1 (RIG-I)–like receptors, and Toll-like receptors recognize microbial double-stranded (ds)DNA, dsRNA, and LPS to induce the expression of type I IFNs. These signaling pathways converge at the recruitment and activation of the transcription factor IRF-3 (IFN regulatory factor 3). The adaptor proteins STING (stimulator of IFN genes), MAVS (mitochondrial antiviral signaling), and TRIF (TIR domain-containing adaptor inducing IFN-β) mediate the recruitment of IRF-3 through a conserved pLxIS motif. Here we show that the pLxIS motif of phosphorylated STING, MAVS, and TRIF binds to IRF-3 in a similar manner, whereas residues upstream of the motif confer specificity. The structure of the IRF-3 phosphomimetic mutant S386/396E bound to the cAMP response element binding protein (CREB)-binding protein reveals that the pLxIS motif also mediates IRF-3 dimerization and activation. Moreover, rotavirus NSP1 (nonstructural protein 1) employs a pLxIS motif to target IRF-3 for degradation, but phosphorylation of NSP1 is not required for its activity. These results suggest a concerted mechanism for the recruitment and activation of IRF-3 that can be subverted by viral proteins to evade innate immune responses

Gaze control for a two-eyed robot head

As a first step towards building a two-eyed active vision system, gaze control is discussed in this paper. Instead of using separate subcontrollers for each of the subfunctions, loosely corresponding to saccade, pursuit, vergence, VOR(vestibulo-ocular reflex), and 0KR ( op to-kinetic reflex), that most previous work has done, a potentially parallel gaze controller is proposed whose structure is supervising-planning-adaptation. Based on simulation, the cooperations and interactions in gaze control and the consequence of delays due to image processing and the local controllers are discussed.

Synthesis and Structure of Two Acentric Heterometallic Inorganic–Organic Hybrid Frameworks with Both Nonlinear Optical and Ferroelectric Properties

Solvothermal reactions of Cd­(NO₃)₂·4H₂O with aromatic polycarboxylic acids in the presence of sodium nitrate led to two acentric three-dimensional (3D) heterometallic inorganic–organic hybrid frameworks, namely, [Me₂NH₂]­[Cd₂Na₃(2,4-PYDC)₄]·2H₂O (<b>1</b>) and [Me₂NH₂] [CdNa­(OH-<i>m</i>-BDC)₂(H₂O)₂]·2H₂O (<b>2</b>) (2,4-H₂PYDC = 2,4-pyridinedicarboxylic acid, OH-<i>m</i>-H₂BDC = 5-hydroxyisophthalic acid). The framework of <b>1</b> is constructed by a 3D inorganic Cd–Na connectivity, which resembles a concrete reinforcement structure and features a {CdNa}_<i>n</i> rod-shaped chain, a {CdNa₂}_<i>n</i> helical chain, and a 20-membered {Cd₆Na₁₄} ring. Compound <b>2</b> is built up by one-dimensional inorganic {CdNa}_<i>n</i> rod-shaped chains which are further connected by OH-<i>m</i>-BDC^2– ligands, affording a 3D polymeric framework. Compounds <b>1</b> and <b>2</b> crystallize in acentric space groups, and both display powder second harmonic generation efficiencies approximately 0.8 and 0.7 times, respectively, than that of the potassium dihydrogen phosphate (KDP) powder. In addition, they also exhibit luminescence and potential ferroelectric properties

Synthesis and Structure of Two Acentric Heterometallic Inorganic–Organic Hybrid Frameworks with Both Nonlinear Optical and Ferroelectric Properties

Solvothermal reactions of Cd­(NO₃)₂·4H₂O with aromatic polycarboxylic acids in the presence of sodium nitrate led to two acentric three-dimensional (3D) heterometallic inorganic–organic hybrid frameworks, namely, [Me₂NH₂]­[Cd₂Na₃(2,4-PYDC)₄]·2H₂O (<b>1</b>) and [Me₂NH₂] [CdNa­(OH-<i>m</i>-BDC)₂(H₂O)₂]·2H₂O (<b>2</b>) (2,4-H₂PYDC = 2,4-pyridinedicarboxylic acid, OH-<i>m</i>-H₂BDC = 5-hydroxyisophthalic acid). The framework of <b>1</b> is constructed by a 3D inorganic Cd–Na connectivity, which resembles a concrete reinforcement structure and features a {CdNa}_<i>n</i> rod-shaped chain, a {CdNa₂}_<i>n</i> helical chain, and a 20-membered {Cd₆Na₁₄} ring. Compound <b>2</b> is built up by one-dimensional inorganic {CdNa}_<i>n</i> rod-shaped chains which are further connected by OH-<i>m</i>-BDC^2– ligands, affording a 3D polymeric framework. Compounds <b>1</b> and <b>2</b> crystallize in acentric space groups, and both display powder second harmonic generation efficiencies approximately 0.8 and 0.7 times, respectively, than that of the potassium dihydrogen phosphate (KDP) powder. In addition, they also exhibit luminescence and potential ferroelectric properties

Quantitative trait loci and candidate genes for yield-related traits of upland cotton revealed by genome-wide association analysis under drought conditions

Abstract Background Due to the influence of extreme weather, the environment in China’s main cotton-producing areas is prone to drought stress conditions, which affect the growth and development of cotton and lead to a decrease in cotton yield. Results In this study, 188 upland cotton germplasm resources were phenotyped for data of 8 traits (including 3 major yield traits) under drought conditions in three environments for two consecutive years. Correlation analysis revealed significant positive correlations between the three yield traits. Genetic analysis showed that the estimated heritability of the seed cotton index (SC) under drought conditions was the highest (80.81%), followed by that of boll weight (BW) (80.64%) and the lint cotton index (LC) (70.49%) With genome-wide association study (GWAS) analysis, a total of 75 quantitative trait loci (QTLs) were identified, including two highly credible new QTL hotspots. Three candidate genes (Gh_D09G064400, Gh_D10G261000 and Gh_D10G254000) located in the two new QTL hotspots, QTL51 and QTL55, were highly expressed in the early stage of fiber development and showed significant correlations with SC, LC and BW. The expression of three candidate genes in two extreme materials after drought stress was analyzed by qRT-PCR, and the expression of these two materials in fibers at 15, 20 and 25 DPA. The expression of these three candidate genes was significantly upregulated after drought stress and was significantly higher in drought-tolerant materials than in drought-sensitive materials. In addition, the expression levels of the three candidate genes were higher in the early stage of fiber development (15 DPA), and the expression levels in drought-tolerant germplasm were higher than those in drought-sensitive germplasm. These three candidate genes may play an important role in determining cotton yield under drought conditions. Conclusions This study is helpful for understanding the regulatory genes affecting cotton yield under drought conditions and provides germplasm and candidate gene resources for breeding high-yield cotton varieties under these conditions

Abacus Training Modulates the Neural Correlates of Exact and Approximate Calculations in Chinese Children: An fMRI Study

Exact (EX) and approximate (AP) calculations rely on distinct neural circuits. However, the training effect on the neural correlates of EX and AP calculations is largely unknown, especially for the AP calculation. Abacus-based mental calculation (AMC) is a particular arithmetic skill that can be acquired by long-term abacus training. The present study investigated whether and how the abacus training modulates the neural correlates of EX and AP calculations by functional magnetic resonance imaging (fMRI). Neural activations were measured in 20 abacus-trained and 19 nontrained Chinese children during AP and EX calculation tasks. Our results demonstrated that: (1) in nontrained children, similar neural regions were activated in both tasks, while the size of activated regions was larger in AP than those in the EX; (2) in abacus-trained children, no significant difference was found between these two tasks; (3) more visuospatial areas were activated in abacus-trained children under the EX task compared to the nontrained. These results suggested that more visuospatial strategies were used by the nontrained children in the AP task compared to the EX; abacus-trained children adopted a similar strategy in both tasks; after long-term abacus training, children were more inclined to apply a visuospatial strategy during processing EX calculations

Efficient Use of Graphene Oxide in Layered Cement Mortar

Graphene oxide (GO) has been found to be an attractive nanomaterial to improve the properties of cementitious composites. However, the use of GO in the industry is limited by its high cost. To achieve a higher cost/performance ratio, GO can be strategically applied in certain parts of cementitious composites structure according to the principle of functionally graded materials. In this study, graded distribution of GO in cement mortar was achieved by sequentially casting a fresh GO-incorporated cement layer on another cement mortar layer. The mechanical properties, especially flexural strength, of layered cement mortar were found to be dependent on the GO content, the delay time, and the interface formed due to layering fabrication. With the GO incorporated in the tensile region only (30% of the total depth), the flexural strength of the layered beam attained 90.91% of that of the beam, with GO uniformly distributed throughout the sample. Based on the results of rapid chloride migration tests, when 12 mm GO-incorporated cement mortar layer was used, the chloride migration coefficient was reduced by 21.45%. It was also found that the measured chloride migration coefficient of layered cement mortar agreed with the series model. The present investigation provides an efficient approach to use GO in cement-based materials from the perspective of mechanical and durability properties