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Abstract Ribosomal protein genes encode products that are essential for cellular protein biosynthesis and are major components of ribosomes. Canonically, they are involved in the complex system of ribosome biogenesis pivotal to the catalysis of protein translation. Amid this tightly organised process, some ribosomal proteins have unique spatial and temporal physiological activity giving rise to their extra-ribosomal functions. Many of these extra-ribosomal roles pertain to cellular growth and differentiation, thus implicating the involvement of some ribosomal proteins in organogenesis. Consequently, dysregulated functions of these ribosomal proteins could be linked to oncogenesis or neoplastic transformation of human cells. Their suspected roles in carcinogenesis have been reported but not specifically explained for malignancy of the nasopharynx. This is despite the fact that literature since one and half decade ago have documented the association of ribosomal proteins to nasopharyngeal cancer. In this review, we explain the association and contribution of dysregulated expression among a subset of ribosomal proteins to nasopharyngeal oncogenesis. The relationship of these ribosomal proteins with the cancer are explained. We provide information to indicate that the dysfunctional extra-ribosomal activities of specific ribosomal proteins are tightly involved with the molecular pathogenesis of nasopharyngeal cancer albeit mechanisms yet to be precisely defined. The complete knowledge of this will impact future applications in the effective management of nasopharyngeal cancer.

This paper proposes a convolutional neural network (CNN) model of the signal distribution control algorithm (SDCA) to maximize the dynamic vehicular traffic signal flow for each junction phase. The aim of the proposed algorithm is to determine the reward value and new state. It deconstructs the routing components of the current multi-directional queuing system (MDQS) architecture to identify optimal policies for every traffic scenario. Initially, the state value is divided into a function value and a parameter value. Combining these two scenarios updates the resulting optimized state value. Ultimately, an analogous criterion is developed for the current dataset. Next, the error or loss value for the present scenario is computed. Furthermore, utilizing the Deep Q-learning methodology with a quad agent enhances previous study discoveries. The recommended method outperforms all other traditional approaches in effectively optimizing traffic signal timing. [ABSTRACT FROM AUTHOR]

Domination plays an indispensable role in graph theory. Various types of domination explore various types of applications. Equal-status people work together and interlace with each other easily. In this paper, the paired equitable domination of a graph, its inflated graph, and its complement of an inflated graph were studied. The relationship between the domination number of the graph, the equitable domination number, and the paired equitable domination number of complements of the inflated graph were established. Furthermore, we proved the Nordhaus–Gaddum-type inequality, that is, γ p r e (H) + γ p r e (H) ≤ 6 if H is a graph with m nodes where m ≡ 0 ,   2 (m o d   8) and d (a i) = (m/2) for all a i . The challenges and limitations of this parameter of paired equitable and equitable domination depends on the degree of the vertex of the graph. Practical applications are discussed in various fields and illustrated using the studied parameter. [ABSTRACT FROM AUTHOR]

Let Heff (Veff, Eeff) be a finite simple connected graph of order m with vertex set Veff and edge set Eeff. A dominating set S d s ⊆ V e f f is called an efficiently dominating set if, for every vertex u a ∈ V G ,   N G u a ∩ S d s = 1 —where NG [ua] denotes the closed neighborhood of the vertex ua. Using efficient domination techniques and labelling, we constructed the fuzzy network. An algorithm has been framed to encrypt and decrypt the secret information present in the network, and furthermore, the algorithm has been given in pseudocode. The mathematical modelling of a strong fuzzy network is defined and constructed to elude the burgeoning intruder. Using the study of the efficient domination of fuzzy graphs, this domination parameter plays a nuanced role in encrypting and decrypting the framed network. One of the main purposes of fuzzy networks is encryption, so one of our contributions to this research is to build a novel combinatorial technique to encrypt and decode the built-in fuzzy network with a secret number utilizing effective domination. An illustration with an appropriate secret message is provided along with the encryption and decryption algorithms. Furthermore, we continued this study in intuitionistic fuzzy networks. [ABSTRACT FROM AUTHOR]