An Affect-Rich Neural Conversational Model with Biased Attention and Weighted Cross-Entropy Loss

Affect conveys important implicit information in human communication. Having the capability to correctly express affect during human-machine conversations is one of the major milestones in artificial intelligence. In recent years, extensive research on open-domain neural conversational models has been conducted. However, embedding affect into such models is still under explored. In this paper, we propose an end-to-end affect-rich open-domain neural conversational model that produces responses not only appropriate in syntax and semantics, but also with rich affect. Our model extends the Seq2Seq model and adopts VAD (Valence, Arousal and Dominance) affective notations to embed each word with affects. In addition, our model considers the effect of negators and intensifiers via a novel affective attention mechanism, which biases attention towards affect-rich words in input sentences. Lastly, we train our model with an affect-incorporated objective function to encourage the generation of affect-rich words in the output responses. Evaluations based on both perplexity and human evaluations show that our model outperforms the state-of-the-art baseline model of comparable size in producing natural and affect-rich responses.Comment: AAAI-1

EEG-Based Emotion Recognition Using Regularized Graph Neural Networks

Electroencephalography (EEG) measures the neuronal activities in different brain regions via electrodes. Many existing studies on EEG-based emotion recognition do not fully exploit the topology of EEG channels. In this paper, we propose a regularized graph neural network (RGNN) for EEG-based emotion recognition. RGNN considers the biological topology among different brain regions to capture both local and global relations among different EEG channels. Specifically, we model the inter-channel relations in EEG signals via an adjacency matrix in a graph neural network where the connection and sparseness of the adjacency matrix are inspired by neuroscience theories of human brain organization. In addition, we propose two regularizers, namely node-wise domain adversarial training (NodeDAT) and emotion-aware distribution learning (EmotionDL), to better handle cross-subject EEG variations and noisy labels, respectively. Extensive experiments on two public datasets, SEED and SEED-IV, demonstrate the superior performance of our model than state-of-the-art models in most experimental settings. Moreover, ablation studies show that the proposed adjacency matrix and two regularizers contribute consistent and significant gain to the performance of our RGNN model. Finally, investigations on the neuronal activities reveal important brain regions and inter-channel relations for EEG-based emotion recognition

Hydrogen peroxide stimulates nuclear import of the POU homeodomain protein Oct-1 and its repressive effect on the expression of Cdx-2

<p>Abstract</p> <p>Background</p> <p>The ubiquitously expressed POU homeodomain protein Oct-1 serves as a sensor for stress induced by irradiation. We found recently that in pancreatic and intestinal endocrine cells, Oct-1 also functions as a sensor for cyclic AMP (cAMP). The caudal homeobox gene Cdx-2 is a transactivator of proglucagon (gcg) and pro-insulin genes. Oct-1 binds to Cdx-2 promoter and represses its expression. cAMP elevation leads to increased nuclear exclusion of Oct-1, associated with reduced recruitment of nuclear co-repressors to the Cdx-2 promoter and increased Cdx-2 expression.</p> <p>Results</p> <p>We show in this study that inducing oxidative stress by hydrogen peroxide (H₂O₂) increased nuclear Oct-1 content in both pancreatic α and β cell lines, as well as in a battery of other cells. This increase was then attributed to accelerated nuclear import of Oct-1, assessed by Fluorescence Recovery After Photobleaching (FRAP) using green fluorescence protein (EGFP) tagged Oct-1 molecule. H₂O₂treatment was then shown to stimulate the activities of DNA-dependent protein kinase (DNA-PK) and c-jun N-terminal kinase (JNK). Finally, increased Oct-1 nuclear content upon H₂O₂treatment in a pancreatic α cell line was associated with reduced Cdx-2 and gcg mRNA expression.</p> <p>Conclusion</p> <p>These observations suggest that Oct-1 functions as a sensor for both metabolic and stress/survival signaling pathways via altering its nuclear-cytoplasmic shuttling.</p

Tungsten disulfide-gold nanohole hybrid metasurfaces for nonlinear metalens in the visible region

Recently, nonlinear hybrid metasurface comes into an attractive new concept in the research of nanophotonics and nanotechnology. It is composed of semiconductors with an intrinsically large nonlinear susceptibility and traditional plasmonic metasurfaces, offering opportunities for efficiently generating and manipulating nonlinear optical responses. A high second-harmonic generation (SHG) conversion efficiency has been demonstrated in the mid-infrared region by using multi-quantum-well (MQW) based plasmonic metasurfaces. However, it has yet to be demonstrated in the visible region. Here we present a new type of nonlinear hybrid metasurfaces for the visible region, which consists of a single layer of tungsten disulfide (WS2) and a phased gold nanohole array. The results indicate that a large SHG susceptibility of ~0.1 nm/V at 810 nm is achieved, which is 2~3 orders of magnitude larger than that of typical plasmonic metasurfaces. Nonlinear metalenses with the focal lengths of 30 {\mu}m, 50 {\mu}m and 100 {\mu}m are demonstrated experimentally, providing a direct evidence for both generating and manipulating SH signals based on the nonlinear hybrid metasurfaces. It shows great potential applications in designing of integrated, ultra-thin, compacted and efficient nonlinear optical devices, such as frequency converters, nonlinear holography and generation of nonlinear optical vortex beam

Efficient generation of an isolated single-cycle attosecond pulse

A new method for efficiently generating an isolated single-cycle attosecond pulse is proposed. It is shown that the ultraviolet (UV) attosecond pulse can be utilized as a robust tool to control the dynamics of electron wave packets (EWPs). By adding a UV attosecond pulse to an infrared (IR) few-cycle pulse at a proper time, only one return of the EWP to the parent ion is selected to effectively contribute to the harmonics, then an isolated two-cycle 130-as pulse with a bandwidth of 45 eV is obtained. After complementing the chirp, an isolated single-cycle attosecond pulse with a duration less than 100 as seems achievable. In addition, the contribution of the quantum trajectories can be selected by adjusting the delay between the IR and UV fields. Using this method, the harmonic and attosecond pulse yields are efficiently enhanced in contrast to the scheme [G. Sansone {\it et al.}, Science {\bf314}, 443 (2006)] using a few-cycle IR pulse in combination with the polarization gating technique.Comment: 5 pages, 4 figure