The structure and regulation of Cullin 2 based E3 ubiquitin ligases and their biological functions.

BACKGROUND: Cullin-RING E3 ubiquitin ligase complexes play a central role in targeting cellular proteins for ubiquitination-dependent protein turnover through 26S proteasome. Cullin-2 is a member of the Cullin family, and it serves as a scaffold protein for Elongin B and C, Rbx1 and various substrate recognition receptors to form E3 ubiquitin ligases. MAIN BODY OF THE ABSTRACT: First, the composition, structure and the regulation of Cullin-2 based E3 ubiquitin ligases were introduced. Then the targets, the biological functions of complexes that use VHL, Lrr-1, Fem1b, Prame, Zyg-11, BAF250, Rack1 as substrate targeting subunits were described, and their involvement in diseases was discussed. A small molecule inhibitor of Cullins as a potential anti-cancer drug was introduced. Furthermore, proteins with VHL box that might bind to Cullin-2 were described. Finally, how different viral proteins form E3 ubiquitin ligase complexes with Cullin-2 to counter host viral defense were explained. CONCLUSIONS: Cullin-2 based E3 ubiquitin ligases, using many different substrate recognition receptors, recognize a number of substrates and regulate their protein stability. These complexes play critical roles in biological processes and diseases such as cancer, germline differentiation and viral defense. Through the better understanding of their biology, we can devise and develop new therapeutic strategies to treat cancers, inherited diseases and viral infections

Herding Effect based Attention for Personalized Time-Sync Video Recommendation

Time-sync comment (TSC) is a new form of user-interaction review associated with real-time video contents, which contains a user's preferences for videos and therefore well suited as the data source for video recommendations. However, existing review-based recommendation methods ignore the context-dependent (generated by user-interaction), real-time, and time-sensitive properties of TSC data. To bridge the above gaps, in this paper, we use video images and users' TSCs to design an Image-Text Fusion model with a novel Herding Effect Attention mechanism (called ITF-HEA), which can predict users' favorite videos with model-based collaborative filtering. Specifically, in the HEA mechanism, we weight the context information based on the semantic similarities and time intervals between each TSC and its context, thereby considering influences of the herding effect in the model. Experiments show that ITF-HEA is on average 3.78\% higher than the state-of-the-art method upon F1-score in baselines.Comment: ACCEPTED for ORAL presentation at IEEE ICME 201

Ultrashort-pulse laser calligraphy

Control of structural modifications inside silica glass by changing the front tilt of an ultrashort pulse is demonstrated, achieving a calligraphic style of laser writing. The phenomena of anisotropic bubble formation at the boundary of an irradiated region and modification transition from microscopic bubbles formation to self-assembled form birefringence are observed, and the physical mechanisms are discussed. The results provide the comprehensive evidence that the light beam with centrosymmetric intensity distribution can produce noncentrosymmetric material modifications

Extremal properties of the first eigenvalue and the fundamental gap of a sub-elliptic operator

We consider the problems of extreming the first eigenvalue and the fundamental gap of a sub-elliptic operator with Dirichlet boundary condition, when the potential $V$ is subjected to a $p$-norm constraint. The existence results for weak solutions, compact embedding theorem and spectral theory for sub-elliptic equation are given. Moreover, we provide the specific characteristics of the corresponding optimal potential function

Optimal Actuator Location of the Norm Optimal Controls for Degenerate Parabolic Equations

This paper focuses on investigating the optimal actuator location for achieving minimum norm controls in the context of approximate controllability for degenerate parabolic equations. We propose a formulation of the optimization problem that encompasses both the actuator location and its associated minimum norm control. Specifically, we transform the problem into a two-person zero-sum game problem, resulting in the development of four equivalent formulations. Finally, we establish the crucial result that the solution to the relaxed optimization problem serves as an optimal actuator location for the classical problem

Null controllability of two kinds of coupled parabolic systems with switching control

The focus of this paper is on the null controllability of two kinds of coupled systems including both degenerate and non-degenerate equations with switching control. We first establish the observability inequality for measurable subsets in time for such coupled system, and then by the HUM method to obtain the null controllability. Next, we investigate the null controllability of such coupled system for segmented time intervals. Notably, these results are obtained through spectral inequalities rather than using the method of Carleman estimates. Such coupled systems with switching control, to the best of our knowledge, are among the first to discuss

A Scope Sensitive and Result Attentive Model for Multi-Intent Spoken Language Understanding

Multi-Intent Spoken Language Understanding (SLU), a novel and more complex scenario of SLU, is attracting increasing attention. Unlike traditional SLU, each intent in this scenario has its specific scope. Semantic information outside the scope even hinders the prediction, which tremendously increases the difficulty of intent detection. More seriously, guiding slot filling with these inaccurate intent labels suffers error propagation problems, resulting in unsatisfied overall performance. To solve these challenges, in this paper, we propose a novel Scope-Sensitive Result Attention Network (SSRAN) based on Transformer, which contains a Scope Recognizer (SR) and a Result Attention Network (RAN). Scope Recognizer assignments scope information to each token, reducing the distraction of out-of-scope tokens. Result Attention Network effectively utilizes the bidirectional interaction between results of slot filling and intent detection, mitigating the error propagation problem. Experiments on two public datasets indicate that our model significantly improves SLU performance (5.4\% and 2.1\% on Overall accuracy) over the state-of-the-art baseline