Hit Identification for PKCζ Inhibitors: Structure-Based Optimization, Virtual Screening, and Biological Evaluation

Protein kinase C ζ (PKCζ) is believed to be a promising target for the treatment of some diseases, including inflammatory diseases, obesity and diabetes. Hit identification of PKCζ inhibitors was conducted by structure-based modification, virtual screening and biological evaluation. Among all the compounds selected and synthesized, compound JW-1-60A showed moderate activity against PKCζ at 30 μM and 100 μM. The molecular modeling studies showed that the binding mode of JW-1-61A was very close to the binding mode of JP-3-149, a reported PKCζ inhibitor with very potent activity, which might partially explain the moderate activity of JW-1-61A. Based on the structure of JW-1-60A, we will synthesize a series of its analogs and investigate their selectivity against other kinases in the future

Traveling Wave Solutions for Planar Lattice Differential Systems with Applications to Neural Networks

AbstractWe obtain some existence results for traveling wave fronts and slowly oscillatory spatially periodic traveling waves of planar lattice differential systems with delay. Our approach is via Schauder's fixed-point theorem for the existence of traveling wave fronts and via S1-degree and equivarant bifurcation theory for the existence of periodic traveling waves. As examples, the obtained abstract results will be applied to a model arising from neural networks and explicit conditions for traveling wave fronts and global continuation of periodic waves will be obtained

A Multi-stage Scheme Decision Model for Complex Products Based on Prospect Theory and Earned Value Method

The development process of complex products is highly uncertain and risky, cause the balance among progress, cost and technology needs to be comprehensively considered. Therefore, how to make decisions on key development plans becomes a problem that needs to be studied and solved. The existing multistage decision model needs to determine the complete stage division, quantity and attribute value of all alternatives in each stage of the development process at the beginning of the decision. However, actually, given the characteristics of long cycle of complex products, high technical risks, and many uncertainties, it is difficult to give the above information in advance in practical work. Therefore, in view of the above shortcomings, this paper proposes a multi-stage scheme decision-making method based on prospect theory and earned value method. First, based on the current progress and cost performance of the project, the dynamic reference point is set by analyzing the deviation between the actual implementation and the plan; Then, the dynamic prospect values of the schedule, cost and technical indicators of each alternative are calculated, and the optimal attribute weights and the comprehensive prospect values of each alternative are obtained by constructing a linear programming model; Finally, the advantages and innovation of the proposed model are further demonstrated through specific application examples

The effect of abusive supervision variability on work–family conflict: The role of psychological detachment and optimism

Although a number of studies have examined the effects of abusive supervision variability, which refers to leaders engaging in differential abuse toward different subordinates within the team on work-related outcomes, scant research has investigated whether and how abusive supervision variability affects non-work outcomes. Drawing on the conservation of resources theory, the current study explores how abusive supervision variability affects work–family conflict through psychological detachment, as well as the moderating role of optimism. Results based on a survey of 260 employees from nine companies show that abusive supervision variability is significantly and positively related to work–family conflict. Psychological detachment mediates the effect of abusive supervision variability on work–family conflict. Optimism moderates the relationship between abusive supervision variability and psychological detachment and the indirect effects of abusive supervision variability on work–family conflict through psychological detachment. This study extends the literature on the effects of abusive supervision variability and provides several important practical implications

DPL: Decoupled Prompt Learning for Vision-Language Models

Prompt learning has emerged as an efficient and effective approach for transferring foundational Vision-Language Models (e.g., CLIP) to downstream tasks. However, current methods tend to overfit to seen categories, thereby limiting their generalization ability for unseen classes. In this paper, we propose a new method, Decoupled Prompt Learning (DPL), which reformulates the attention in prompt learning to alleviate this problem. Specifically, we theoretically investigate the collaborative process between prompts and instances (i.e., image patches/text tokens) by reformulating the original self-attention into four separate sub-processes. Through detailed analysis, we observe that certain sub-processes can be strengthened to bolster robustness and generalizability by some approximation techniques. Furthermore, we introduce language-conditioned textual prompting based on decoupled attention to naturally preserve the generalization of text input. Our approach is flexible for both visual and textual modalities, making it easily extendable to multi-modal prompt learning. By combining the proposed techniques, our approach achieves state-of-the-art performance on three representative benchmarks encompassing 15 image recognition datasets, while maintaining parameter-efficient. Moreover, our DPL does not rely on any auxiliary regularization task or extra training data, further demonstrating its remarkable generalization ability.Comment: 11 pages, 5 figures, 8 table