Search

In this paper, based on the law of motion, combining the spherical coordinate system representation with the drama art of action feature recognition in the process of theatrical performance, the joint points of wrist, elbow and shoulder and the corresponding feature vectors as well as the school angular velocity are calculated. The affine invariant domain of feature matching is constructed, and the algorithms of dynamic frame difference merging and dynamic detection of human-computer interaction are applied to obtain similar feature components of the recognition of body movements and gesture commands in the process of theatrical performance. The harmony factor, emotion factor and contrast factor in the stage scene are used as evaluation parameters to derive the color evaluation function and keyframes of theatrical stage lighting combined with drama art. For the research purpose, the research on the stage influence of the theatrical performance of combining drama is designed, and the example analysis of the stage influence of the theatrical performance of combining drama is analyzed by using origin software. The results show that the level of the audience’s arousal dimension is significantly higher than its level in CSP, t(1, 29)=3.959, p

Remembering software library components and mastering their application programming interfaces (APIs) is a daunting task for programmers, due to the sheer volume of available libraries. API completion tools, which predict subsequent APIs based on code context, are essential for improving development efficiency. Existing API completion techniques, however, face specific weaknesses that limit their performance. Pattern-based code completion methods that rely on statistical information excel in extracting common usage patterns of API sequences. However, they often struggle to capture the semantics of the surrounding code. In contrast, deep-learning-based approaches excel in understanding the semantics of the code but may miss certain common usages that can be easily identified by pattern-based methods. Our insight into overcoming these challenges is based on the complementarity between these two types of approaches. This paper proposes a combinatorial method of API completion that aims to exploit the strengths of both pattern-based and deep-learning-based approaches. The basic idea is to utilize a confidence-based selector to determine which type of approach should be utilized to generate predictions. Pattern-based approaches will only be applied if the frequency of a particular pattern exceeds a pre-defined threshold, while in other cases, deep learning models will be utilized to generate the API completion results. The results showed that our approach dramatically improved the accuracy and mean reciprocal rank (MRR) in large-scale experiments, highlighting its utility. [ABSTRACT FROM AUTHOR]

The cystathionine-β-synthase (CBS) domain is present in the proteins of all living organisms and functions as an energy sensor, regulating protein activity through the binding capacity of its adenosine ligands. The role of the CBS gene in plant growth and development, as well as tolerance to abiotic stresses, remains largely unknown, especially in grapevine. In our study, 32 members of the CBS gene family were obtained that were distributed on 15 chromosomes. The results of the structural and evolutionary tree analyses indicated that the VvCBS gene family exhibits diverse intron-exon patterns and highly conserved motifs. Furthermore, the phylogenetic classification of the VvCBS genes revealed the presence of three subfamilies. Subcellular localization analyses showed that the VvCBS genes are mainly located in the plasma membrane region. The secondary structure of the VvCBS protein mainly consists of α-helices, extended strands, β-turns, and random coils. The VvCBS gene family exhibited four co-linear gene pairs, while the numbers for Arabidopsis thaliana and rice were 21 and 7, respectively. The promoter cis-acting element analysis revealed the presence of light-responsive, hormone-responsive, stress-responsive, and growth- and development-related elements in the VvCBS family. The expression characterization demonstrated that 12 VvCBS genes exhibited high expression levels in all grape tissues. Additionally, the RT-qPCR expression analyses showed that the 32 VvCBS exhibited different responses to a variety of abiotic stresses (cold, drought, salt), suggesting that they were functionally differentiated. VvCBS27 was cloned from 'Pinot Noir' of grapevine with a coding sequence of 624 bp. Subcellular localization showed that VvCBS27 protein was mainly located in the cytoplasm, cell membrane, and nucleus. This study lays a foundation for elucidating the function of grape CBS protein. [ABSTRACT FROM AUTHOR]