Sentiment and emotion embody intrinsic experience of human cognition, both of which profoundly influences cognitive processes in humans. The commonality between sentiment and emotion leads to a fact that sentiment classification and emotion recognition are two correlated tasks in cognitive science and artificial intelligence. One task improves its performance by leveraging similarities and differences across tasks. However, recent works have often treated them as two separately different tasks, where their commonalities are largely neglected. To fill this gap, we propose a multi-task interactive graph attention network with position encodings, termed MIP-GAT. The main proposal is a multi-interactive graph layer where syntactic dependency connection, cross-task connection and position encodings are constructed and incorporated into a unified graphical structure. Empirical evaluation on two benchmarking datasets, i.e., CMU-MOSEI and GoEmotions, shows the effectiveness of the proposed model over state-of-the-art baselines. In addition, we also explore the superiority and limitations of the proposed model.

Durum wheat is an important food crop used primarily for pasta production. High-molecular-weight glutenin subunits (HMW-GS) encoded by the closely linked genes Glu-B1x and Glu-B1y are known for their combined effects on pasta quality, but their individual contributions and interactions remain poorly understood. In this study, we show that individual loss-of-function mutants of Glu-B1x (ΔBx6) and Glu-B1y (ΔBy8) were associated with significant reductions in gluten strength compared to the wildtype, with stronger effects in the ΔBxy double mutant. Reductions in gluten strength were reflected in reduced mixograph and alveograph parameters, gluten index, faster extrusion flow rates and increased cooking loss. Interestingly, the Glu-B1x mutation was also associated with significant increases in grain and semolina protein content, increased pasta firmness, reduced starch viscosity and increased amylose in ΔBx6 and ΔBxy. In general, the ΔBx6 mutation had stronger effects than the ΔBy8 mutation, and significant interactions between the two genes were frequent. In addition to the basic knowledge gained on the individual effects of the Bx6 and By8 subunits and their interactions, the genetic stocks developed in this study provide useful tools to study the effects of natural or synthetic HMW-GS on pasta quality parameters in a background lacking endogenous HMW-GS.