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6G mobile network technology will set new standards to meet performance goals that are too ambitious for 5G networks to satisfy. The limitations of 5G networks have been apparent with the deployment of more and more 5G networks, which certainly encourages the investigation of 6G networks as the answer for the future. This research includes fundamental privacy and security issues related to 6G technology. Keeping an eye on real-time systems requires secure wireless sensor networks (WSNs). Denial of service (DoS) attacks mark a significant security vulnerability that WSNs face, and they can compromise the system as a whole. This research proposes a novel method in blockchain 6G-based wireless network security management and optimization using a machine learning model. In this research, the deployed 6G wireless sensor network security management is carried out using a blockchain user datagram transport protocol with reinforcement projection regression. Then, the network optimization is completed using artificial democratic cuckoo glowworm remora optimization. The simulation results have been based on various network parameters regarding throughput, energy efficiency, packet delivery ratio, end–end delay, and accuracy. In order to minimise network traffic, it also offers the capacity to determine the optimal node and path selection for data transmission. The proposed technique obtained 97% throughput, 95% energy efficiency, 96% accuracy, 50% end–end delay, and 94% packet delivery ratio.

This paper considers a stochastic queueing-inventory system with dual service stations, two groups of heterogeneous multi-servers, two finite waiting halls, and two classes of customers. Station-1 and station-2 provide an inventory sales service and feedback service, respectively. The feedback service option can be given to customers at the service completion epoch. If a customer requires feedback service, moves to an orbit; otherwise, leaves the system permanently. The classical retrial policy is applied to get feedback service. For the replenishment process, the system follows an (S−1,S) base stock ordering policy. This study analyzes the model under four classifications: 1) orbit size is finite and servers have homogeneous service rate; 2) orbit size is finite and servers have heterogeneous service rate; 3) orbit size is infinite and servers have homogeneous service rate; and 4) orbit size is infinite and servers have heterogeneous service rate. The steady-state probability vector for an infinite-size orbit case is computed using the Neuts and Rao truncation method. An expected total cost function is derived with sufficient system indicators for the four classifications. An optimized expected total cost is gained for classifications 2 and 4. The probability that a server is busy, the customer's waiting time, and the customer's loss rate are minimized for classifications 2 and 4.

Let G′ be a simple, connected, and undirected (UD) graph with the vertex set M(G′) and an edge set N(G′). In this article, we define a function f:M∪N⟶0,1 as a fractional mixed dominating function (FMXDF) if it satisfies fRmx=∑yϵRmxfy≥1 for all x∈MG′∪NG′, where Rmx indicates the closed mixed neighbourhood of x, that is the set of all y∈MG′∪NG′ such that y is adjacent to x and y is incident with x and also x itself. Here, pf=∑x∈M∪Nfx is the poundage (or weight) of f. The fractional mixed domination number (FMXDN) is denoted by γfm∗G′ and is designated as the lowest poundage among all FMXDFs of G′. We compute the FMXDN of some common graphs such as paths, cycles, and star graphs, the middle graph of paths and cycles, and shadow graphs. Furthermore, we compute upper bounds for the sum of the two fractional dominating parameters, resulting in the inequality γf1′Τ+γfm∗Τ≤r+p−radΤ−α, where γf1′ and γfm∗ are the fractional edge domination number and FMXDN, respectively. Finally, we compare γfm∗ to other resolvability-related parameters such as metric and fault-tolerant metric dimensions on some families of graphs.

Abstract Aim: The number of micronuclei in oral exfoliated buccal mucosal cells of analog (basic) and smart mobile phone users was evaluated and compared. Materials and Methods: The study population constituted 30 individuals using basic and smartphones within the age group of 45–55 years. They were divided into two groups: Group 1–15 participants using basic mobile phones and Group 2–15 participants using smart mobile phones. Exfoliated buccal mucosal cells were collected from both right and left buccal mucosa, stained with Papanicolaou stain, and evaluated microscopically for the estimation of micronuclei count. Mean micronuclei count was compared statistically between the study groups and also between the sides of frequent usage and opposite sides within the study groups. Results: There was a significant increase in the mean micronuclei count in Group 2 compared to Group 1 and the comparison of mean micronuclei count between the side of frequent phone usage (right side) and opposite side (left side) also showed significant difference in both Groups 1 and 2. Conclusion: Despite technological advance and high-end features, the use of smartphones causes more genotoxicity compared to basic model or analog phones. Although this technology-dominated era mandates use of such phones as a part of routine lifestyle, it is imperative to adopt safety precautions such as use of headphones while talking, carrying a separate pouch for mobile phones to minimize the genotoxic damage.

Tsunami is one of the deadliest natural disasters which can occur, leading to great loss of life and property. This study focuses on predicting tsunamis, using earthquake dataset from the year 1995 to 2023. The research introduces the Hybrid Quantum Neural Network (HQNN), an innovative model that combines Neural Network (NN) architecture with Parameterized Quantum Circuits (PmQC) to tackle complex machine learning (ML) problems where deep learning (DL) models struggle, aiming for higher accuracy in prediction while maintaining a compact model size. The hybrid model's performance is compared with the classical model counterpart to investigate the quantum circuit's effectivity as a layer in a DL model. The model has been implemented using 2-6 features through Principle Component Analysis (PCA) method. HQNN's quantum circuit is a combination of Pennylane's embedding (Angle Embedding (AE) and Instantaneous Quantum Polynomial (IQP) Embedding) and layer circuits (Basic Entangler Layers (BEL), Random Layers (RL), and Strongly Entangling Layers (SEL)), along with the classical layers. Results show that the proposed model achieved high performance, with a maximum accuracy up to 96.03% using 4 features with the combination of AE and SEL, superior to the DL model. Future research could explore the scalability and diverse applications of HQNN, as well as its potential to address practical ML challenges. [ABSTRACT FROM AUTHOR]

The usage of cars has surged dramatically, with individuals preferring personal or rental vehicles for daily commuting and vacations over public transportation due to comfort and convenience. However, this preference has led to an increased risk of drowsy driving, which often results in severe accidents and fatalities, contributing to a rise in mortality rates. To address this recognizing yawning in drivers is a critical safety measure, which poses a unique challenge because of the action's subtlety and variability. This paper proposes a yawning recognition technique utilizing AlexNet, a convolutional neural network recognized for its efficacy in image classification. The approach integrates AlexNet with image pre-processing techniques to enhance the recognition of facial gestures from static, frontal profile-view color images. It also employs various neuron-wise and layer-wise visualization methods on an AlexNet model trained with a publicly available dataset. The results underscore the effectiveness of neural networks in accurately detecting the distinctions of yawning, showcasing the potential of deep learning in improving driver safety. [ABSTRACT FROM AUTHOR]

Background: In the present scenario, competitive sports require athletes to achieve a phenomenal balance between cognitive abilities, motor skills, nutritional intake, and energy deficiencies. Such stability would enable the athletes to excel in their sporting field. Evidence shows that athletes develop specific cognitive abilities based on their sporting field. Nutrition is vital in creating an athlete's cognitive ability and physical needs required to participate in competitive sports. The reduction in the intake of nutrients required before, after and during sports participation could result in relative energy deficiency in sports (RED-S), affecting the parts of the body. Methods: The rationale behind the survey is to understand the role of nutrition and energy deficiency on the athletes' cognitive abilities. The review's research areas were identified as athletes' cognition and nutrition in the context of RED-S. Search keywords were found based on the research area, such as "cognitive", "nutrition", and "energy deficiency/availability" in athletes. The search keywords were combined to form search queries (SQs). SQs were used to carry out the search on the Web of Science and Scopus databases. Results: Sports play an important role in athletes' cognitive abilities, such as decision-making, attention, memory, etc. Nutritional intakes, such as caffeinated, carbohydrate, alkaline, and protein-based supplements and diets, also significantly affect athletes' cognitive and motor abilities. Low energy availability (LEA) causes cognitive and physical health problems in both female and male athletes. Conclusion: The review identified that nutrition and LEA play crucial roles in athletes' cognitive performance. Deficits in nutritional intake and energy availability lead to RED-S. Hence, cognitive performance could be used as an early indication to identify the nutritional and energy deficits in advance, enabling athletes to combat RED-S. [ABSTRACT FROM AUTHOR]

Introduction: Dental stem cells (DSCs) derived from tooth structures refer to adult stem cells. DSCs can be used to regenerate both dental tissues and nondental organs. DSC research is progressing at a rapid pace and hence it is imperative for dental professionals to possess adequate knowledge and a favorable attitude toward the same. The aim of this study was to assess the knowledge and attitude of dental professionals toward DSCs. Methodology: A cross-sectional, descriptive, questionnaire-based survey was conducted on a sample of 200 dental professionals from various dental colleges in Chennai. The questionnaire included a total of 15 questions to assess the knowledge and attitude toward DSCs. The Pearson's Chi-square test and percentages of the total were used for statistical analysis. Results: A total of 200 dental professionals completed the questionnaire survey; of which 42 (21%) were male and 158 (78%) were female. Maximum respondents were intern (n = 92, 46%), followed by dental practitioners (DP) (n = 58, 29%) and postgraduates (n = 50, 25%). Around 182 (91%) dental professionals are aware of the term stem cells. Overall, 66% of dental participants were not aware of ethical considerations and guidelines related to DSCs given by the Indian Council of Medical Research. The majority of dental participants (83%) were interested in attending workshop/conference/Continuing Dental Education (CDE) program on applications of stem cells. Conclusion: This study revealed that there was a generalized awareness of the term “DSCs” among the study participants. However, there was a huge lacuna in the knowledge of its types, ethical considerations, and the concept of stem cell banking and DSC banks in India. The results of the current study emphasize the need for improvement in knowledge of DSCs for dental professionals by promoting more CDE programs focusing on this subject.

In recent times, we have encountered new situations that have imposed restrictions on our ability to visit public places. These changes have affected various aspects of our lives, including limited access to supermarkets, vegetable shops, and other essential establishments. As a response to these circumstances, we have developed a continuous review retrial queueing–inventory system featuring a single server and controlled customer arrivals. In our system, customers arriving to procure a single item follow a Markovian Arrival Process, while the service time for each customer is modeled by an exponential distribution. Inventories are replenished according to the (s,Q) reordering policy with exponentially distributed lead times. The system controls arrival in the waiting space with setup time. The customers who arrive at a not allowed situation decide to enter an orbit of infinite size with predefined probability. Orbiting customers make retrials to claim a place in the waiting space, and their inter-retrial times are exponentially distributed. The server may experience essential interruption (emergency situation) which arrives according to Poisson process. Then, the server goes for an emergency vacation of a random time which is exponentially distributed. In the steady-state case, the joint probability of the number of customers in orbit and the inventory level has been found, and the Matrix Geometric Method has been used to find the steady-state probability vector. In numerical calculations, the convexity of the system and the impact of F-policy and emergency vacation in the system are discussed.

This paper investigates the queue-dependent service rates(QDSR) in the stochastic queueing-inventory system(SQIS). This SQIS consists a single server service channel, S number of inventories, and a finite queue. An arriving customer gets the service immediately if the server is free and there exists a positive stock in the SQIS. When the server is busy, they have to wait in the finite queue. Suppose they find that the waiting hall is full, either they leave the system or enter into an infinite orbit under the Bernoulli trial. The service rate of any arrival is dependent on the number of customers in the queue at present. The orbital customer can compete for the service only through joining into the waiting hall based on the classical retrial policy. Whenever the number of inventories in SQIS is reached a certain limit s, the replenishment of Q(=S−s) items is placed. Due to the structure of rate matrix, the stability analysis, minimal non-negative solutions of the quadratic systems are derived through the Neuts matrix-geometric approximation(MGA). Further, the waiting time distribution(WTD) of arrival and necessary system characteristics are derived. Finally, adequate numerical examples are presented to highlight the proposed SQIS.

Graph theory is a useful mathematical structure used to model pairwise relations between sensor nodes in wireless sensor networks. Graph equations are nothing but equations in which the unknown factors are graphs. Many problems and results in graph theory can be formulated in terms of graph equations. In this paper, we solved some graph equations of detour two-distance graphs, detour three-distance graphs, detour antipodal graphs involving with the line graphs.

The use of a Markovian inventory system is a critical part of inventory management. The purpose of this study is to examine the demand for two commodities in a Markovian inventory system, one of which is designated as a major item (Commodity-I) and the other as a complimentary item (Commodity-II). Demand arrives according to a Poisson process, and service time is exponential at a queue-dependent rate. We investigate a strategy of (s,Q) type control for commodity-I with a random lead time but instantaneous replenishment for commodity-II. If the waiting hall reaches its maximum capacity of N, any arriving primary client may enter an infinite capacity orbit with a specified ratio. For orbiting consumers, the classical retrial policy is used. In a steady-state setting, the joint probability distributions for commodities and the number of demands in the queue and the orbit, are derived. From this, we derive a waiting time analysis and a variety of system performance metrics in the steady-state. Additionally, the physical properties of various performance measures are evaluated using various numerical assumptions associated with diverse stochastic behaviours.

This paper explores the random environment with two classes of suppliers and impulse customers. The system’s greatest inventory size is S, and it has an infinitely large orbit. In this case, there are two categories of suppliers: temporary suppliers and regular suppliers. Whenever the inventory approaches r, we place on order Q1 (=S−r) unit items to a temporary supplier. Similarly, when the inventory level drops to s (s+1) units of items to our regular supplier. Two types of suppliers’ lead times are considered to be exponentially distributed. Here, the customers who arrive from different states of the random environment (RE) are followed by the Markovian arrival process. If there is no inventory in the system when the customer arrives, they are automatically assigned to an orbit. The model was examined in steady state by using the matrix-analytic approach. Finally, the numerical examples for our structural model are discussed.

A set S⊆V of a graph G=V,E is called a co-independent liar’s dominating set of G if (i) for all v∈V, NGv∩S≥2, (ii) for every pair u,v∈V of distinct vertices, NGu∪NGv∩S≥3, and (iii) the induced subgraph of G on V−S has no edge. The minimum cardinality of vertices in such a set is called the co-independent liar’s domination number of G, and it is denoted by γcoiLRG. In this paper, we introduce the concept of co-independent liar’s domination number of the middle graph of some standard graphs such as path and cycle graphs, and we propose some bounds on this new parameter.

In this paper, we introduce the concept of reinforcement number with respect to half-domination and initiate a study on this parameter. Furthermore, we obtain various upper bounds for this parameter. AMS subject classification: 05C38, 05C40, 05C69.

This research analyses the performance of a perishable queueing-inventory system for two commodities with optional customers demands. We assume in the article that all customers who come to the system can only purchase the first item or the second item or service (they do not purchase both items). This is the original aspect of the paper. We show the significance of the impact of optional demands on the system’s performance, which is the purpose of the paper. In this system, customers arrive, using the Markovian arrival process (MAP), to a demand for a single unit. The system is composed of a waiting hall with a limited capacity of F. The arriving customer observes the waiting hall is filled to capacity or the stock stage is zero, and they decide to leave the system. In the steady-state case, the joint probability distribution for the first commodity, the second commodity, and the number of customers in the system are computed using matrix geometric methods. We evaluate diverse system performance measures. Finally, we provide a numerical illustration of the optimal value for diverse parameters of the system, which highlights the results and implications of the article.

This paper deals with an integrated and interconnected stochastic queuing-inventory system with a fresh item, a returned item, and a refurbished item. This system provides a multi-type service facility to an arriving multi-class customer through a dedicated channel. It sells fresh and refurbished items, buys used items from customers, refurbishes the used items for resale, and provides a repair service for defective items. The assumption of purchasing a used item from the customer and allowing them to buy a fresh item is a new idea in stochastic queuing-inventory modeling. To do so, this system has four parallel queues to receive four classes of customers and five dedicated servers to provide a multi-type service facility. Customers are classified according to the type of service they require. Each class of arrival follows an independent Poisson process. The service time of each dedicated server is assumed to be exponentially distributed and independent. This system assumes an instantaneous ordering policy for the replenishment of a fresh item. In the long run of this considered system, the joint probability distribution of the seven-dimensional stochastic process, significant system performance measures, and the optimum total cost are to be derived using the Neuts matrix geometric technique. The main objective of the system was to increase the occurrence of all kinds of customers by providing a multi-type service facility in one place. Buying a used item is unavoidable in an emerging society because it helps form a green society. Furthermore, the numerical result shows that the assumption of a system that allows a customer to sell their used item and purchase a new item will increase the number of customers approaching the system.

Consider the Diophantine equation yn=x+x(x+1)+⋯+x(x+1)⋯(x+k), where x, y, n, and k are integers. In 2016, a research article, entitled – ’power values of sums of products of consecutive integers’, primarily proved the inequality n= 19,736 to obtain all solutions (x,y,n) of the equation for the fixed positive integers k≤10. In this paper, we improve the bound as n≤ 10,000 for the same case k≤10, and for any fixed general positive integer k, we give an upper bound depending only on k for n.

In this study, we consider a perishable inventory system that has an (s, Q) ordering policy, along with a finite waiting hall. The single server, which provides an item to the customer after completing the required service performance for that item, only begins serving after N customers have arrived. Impatient demand is assumed in that the customers waiting to be served lose patience and leave the system if the server’s idle time overextends or if the arriving customers find the system to be full and will not enter the system. This article analyzes the impatient demands caused by the N-policy server to an inventory system. In the steadystate, we obtain the joint probability distribution of the level of inventory and the number of customers in the system. We analyze some measures of system performance and get the total expected cost rate in the steadystate. We present a beneficial cost function and confer the numerical illustration that describes the impact of impatient customers caused by N-policy on the inventory system’s total expected cost rate.