Protection of sensitive information has been always the major security concern since decades to withstand against illegitimate access and usage. Substitution-boxes (S-boxes) are vital components of any modern day cryptographic system that allows us to ensure its resistance to attacks. The prime problem with creating S-box is that we are generally unable to discover a consistent distribution among its numerous features to withstand diverse cryptanalysis attacks. The majority of S-boxes investigated in the literature has good cryptographic defenses against some attacks but are susceptible to others. Keeping these considerations in mind, this paper proposes a novel approach for S-box design based on a pair of coset graphs and a newly defined operation of row and column vectors on a square matrix. Several standard performance assessment criteria are used to evaluate the reliability of proposed approach, and the results demonstrate that the developed S-box satisfies all criterions for being robust for secure communication and encryption.

The success of any endeavor or process is heavily contingent on the ability to reconcile and satisfy balance requirements, which are often characterized by symmetry considerations. In practical applications, the primary goal of decision-making processes is to efficiently manage the symmetry or asymmetry that exists within different sources of information. In order to address this challenge, the primary aim of this study is to introduce novel Dombi operation concepts that are formulated within the framework of interval-valued Pythagorean fuzzy aggregation operators. In this study, an updated score function is presented to resolve the deficiency of the current score function in an interval-valued Pythagorean fuzzy environment. The concept of Dombi operations is used to introduce some interval-valued Pythagorean fuzzy aggregation operators, including the interval-valued Pythagorean fuzzy Dombi weighted arithmetic (IVPFDWA) operator, the interval-valued Pythagorean fuzzy Dombi ordered weighted arithmetic (IVPFDOWA) operator, the interval-valued Pythagorean fuzzy Dombi weighted geometric (IVPFDWG) operator, and the interval-valued Pythagorean fuzzy Dombi ordered weighted geometric (IVPFDOWG) operator. Moreover, the study investigates many important properties of these operators that provide new semantic meaning to the evaluation. In addition, the suggested score function and newly derived interval-valued Pythagorean fuzzy Dombi aggregation (IVPFDA) operators are successfully employed to select a subject expert in a certain institution. The proposed approach is demonstrated to be successful through empirical validation. Lastly, a comparative study is conducted to demonstrate the validity and applicability of the suggested approaches in comparison with current techniques. This research contributes to the ongoing efforts to advance the field of evaluation and decision-making by providing novel and effective tools and techniques.

The formulation of models and solutions for various physical problems are the primary goals of scientific achievements in engineering and physics. Our paper focuses on using the Caputo fractional derivative operator to solve nonlinear fractional logistic differential equations. In order to solve general nonlinear fractional differential equations, we first introduce a novel numerical methodology termed the Homotopy perturbation transform method. The perturbation approach and the Yang transform method are combined to create the suggested strategy. Second, we introduce a new hybrid method that uses the time-fractional Caputo derivative to approximate and analytically solve nonlinear fractional logistic differential equations. This method combines the Yang transform with the decomposition method. To validate the analysis, we offer three numerical cases of nonlinear fractional logistic differential equations employing the Caputo fractional derivative operator. The resulting solutions exhibit rapid convergence and are presented in series form. In order to verify the efficacy and relevance of the suggested methodologies, the investigated issues were assessed through the implementation of different fractional orders. We examine and show that, under the specified initial conditions, the solution approaches under evaluation are accurate and effective. Graphs in two and three dimensions show the results that were obtained. Numerical simulations are presented to confirm the efficacy of the strategies. The numerical results show that an accurate, reliable, and efficient approximation can be obtained with a minimal number of terms. The results obtained demonstrate that the new analytical solution method is easy to apply and very successful in solving difficult fractional problems that occur in relevant engineering and scientific domains.

Symmetrical and asymmetrical information plays a critical role in resolving many issues. The implications of symmetry and asymmetry in interval-valued picture fuzzy decision-making, lie in their ability to represent and manage complex data. Decision makers approach the problem of information asymmetry through various methods. Integrating symmetric and asymmetric data in the context of a specific physical phenomenon poses significant challenges. To address these challenges, interval-valued picture fuzzy (IVPF) sets have emerged as an effective tool for managing complex data. In decision-making processes, it is essential to consider the complementary and conflicting nature of the analyzed data. This article aims to refine the shortcomings of the existing score function for Multiple Criteria Decision-Making (MCDM) problems in an IVPF environment, and present an improved score function. The IVPF sets are leveraged to propose IVPF weighted arithmetic operators, IVPF ordered weighted arithmetic operators, IVPF weighted geometric operators, and IVPF ordered weighted geometric operators, which are analyzed in terms of their key features. To demonstrate the effectiveness of the proposed score function and newly defined operators, a case study involving the selection of the best food item for manufacturing, is conducted. Additionally, a comparative analysis is established to investigate the significance of the newly defined techniques in solving decision-making problems under IVPF knowledge.

The exploration of peristaltic pumping and heat transfer in magnetohydrodynamic biofluids holds considerable significance with diverse physiological applications, including their use in surgical equipment for the heart, drug injection, cancer therapies, and dialysis. These studies find relevance in various industrial processes, such as the production of pharmaceutical fluids, liquid filtration, and the contamination-free dispensing of cosmetic/glue emulsions. Consequently, the current analysis delves into the intricacies of thermal emission and viscous dissolution in the peristaltic movement of a six-constant Jeffreys magneto-nanofluid within an asymmetric channel. This investigation considers double diffusion convection and incorporates slip conditions. The energy equation is formulated, incorporating features of thermal dispersion and viscous dissolution. The initial model includes a collection of non-linear partial differential equations (PDEs). To simplify the problems, the analysis is made simpler under the supposition of a small Reynolds number and large wavelength, leading to the governing system of PDEs that is further computed using the numerical technique NDSolve. A detailed analysis is conducted for various parameters, including nanoparticle fraction, pressure increase, velocity, temperature, pressure gradient, concentration, and stream functions. Graphical presentations of the obtained results showcase the influence of different flow quantities, noting that the temperature profile boosts due to the growing impact of the increasing concentration of thermal slip, while concentration decreases owing to the increasing concentration of the slip parameter. Moreover, it is also noted that as the thermophoresis parameter, thermal slip parameter, and Brinkman number increase, the temperature profile increases; conversely, it decreases with the thermal radiation parameter.

The development on entropy generation in fluid flows has applications in many medical equipment such as cryogenic devices and therapeutic heat apparatus. This study looks at how porous medium, multi-slips, and entropy formation affect the pumping of Jeffrey nanofluid flow through an asymmetric channel containing motile microorganims. A lubrication theory is used to neglect the fluctuation effects in the flow. Numerical simulations are utilized to generate data for specific physical features of the problem utilizing the Shooting approach on Mathematica. Following a thorough research, it is appropriate to conclude that the porous medium's permeability reduces flow speed along the walls while increases at the center of the flow region. Graphical representation of the results further reveals that entropy production can be decreased by including high thermal slip and low viscous slip elements. It is also worth noting that the Brinkman number reduces the thermal distribution in the flow while it helps in increasing the flow speed.