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This study presents a novel approach focused on extensively addressing the dynamics of Rabineurodeficiency Syndrome by developing a mathematical compartmental model without recuperation. The equilibria of the rabies-free and present states are analyzed locally and globally. Real-world data on annual rabies cases are integrated to confirm and enhance the model’s accuracy. Likewise, a parameter estimation technique is employed to optimize the model, aiding in calculating the basic reproduction number. Sensitivity analysis examines the impact of critical parameters on transmission dynamics, providing a deeper understanding of the determining factors influencing disease spread. Visual representations of the relationship between essential parameters and the reproduction number offer valuable insights into factors influencing disease control. Advancing the understanding of Rabineurodeficiency Syndrome dynamics, the inclusive control actions to mitigate infectious diseases are evaluated, emphasizing the importance of accounting for individuals with disabilities.

In real-life production, the cutting stock problem is often associated with additional constraints and objectives. Among the auxiliary objectives, two of the most relevant are the minimization of the number of different cutting patterns used and the minimization of the maximum number of simultaneously open stacks. The first auxiliary objective arises in manufacturing environments where the adjustment of the cutting tools when changing the cutting patterns incurs increased costs and time spent in production. The second is crucial to face scenarios where the space near the cutting machine or the number of automatic unloading stations is limited. In this paper, we address the one-dimensional cutting stock problem, considering the additional goals of minimizing the number of different cutting patterns used and the maximum number of simultaneously open stacks. We propose two Integer Linear Programming (ILP) formulations and a Constraint Programming (CP) model for the problem. Moreover, we develop new upper bounds on the frequency of the cutting patterns in a solution and address some special cases in which the problem may be simplified. All three approaches are embedded into an iterative exact framework to find efficient solutions. We perform computational experiments using two sets of instances from the literature. The proposed approaches proved effective in determining the entire Pareto front for small problem instances, and several solutions for medium-sized instances with minimum trim loss, a reduced maximum number of simultaneously open stacks, and a small number of different used cutting patterns.

This article utilizes balanced score card (BSC) and resilience engineering factors for organizational performance. The methodology involves two stages: in the first stage, we tried to find the efficiency of organization based on previous projects of the organization applying data envelopment analysis (DEA). In order to apply DEA model for organizational assessment, some questionnaires have been spread among managers of the organization. Principal component analysis (PCA) is introduced in the second stage to highlight the shaping factors that influence overall efficiency. Furthermore, a comparison will be made with sensitivity analysis of DEA and PCA results. The results of the comparison highlight the importance of the three categories (BSC, RE, and sustainability) on organizational performance. After identifying the shaping factors and assessing the organization’s situation, artificial neural network (ANN) is applied to help us find the success factor (utility) of future projects and a mathematical formulation is presented which helps the decision makers select the best projects considering organizational situation and values. According to results, resilience engineering factors, including flexibility, management commitment, reporting culture, learning, awareness, preparedness, teamwork, redundancy, self-organization, and fault tolerance, are the most shaping and decisive factors in organization efficiency. The importance of RE over environmental factors and the coverage of data made by RE factors indicate that this construction environment devoted a great deal of attention to RE factors.

The present paper proposes a mathematical development of the plasticity and damage approaches to simulate sheet metal forming processes. It focuses on the numerical prediction of the deformation of the sheet metal during the deep drawing process when a crack appears. Anisotropic plasticity constitutive equations are proposed. A fully implicit integration of the coupling constitutive equations is used and leads to two nonlinear local scalar equations that are solved by Newton’s method. The developed model allows predicting the onset of cracks in sheet metals during cold forming operations. The numerical model is implemented in ABAQUS software using user-defined subroutines, which are VUMAT and UMAT. The accuracy of the anisotropic elastoplastic model fully coupled with ductile damage is evaluated using numerical examples.

Cancer remains a formidable global health challenge, claiming millions of lives annually. Timely and accurate cancer diagnosis is imperative. While numerous reviews have explored cancer classification using machine learning and deep learning techniques, scant literature focuses on traditional ML methods. In this manuscript, we undertake a comprehensive review of colorectal and gastric cancer detection specifically employing traditional ML classifiers. This review emphasizes the mathematical underpinnings of cancer detection, encompassing preprocessing techniques, feature extraction, machine learning classifiers, and performance assessment metrics. We provide mathematical formulations for these key components. Our analysis is limited to peer-reviewed articles published between 2017 and 2023, exclusively considering medical imaging datasets. Benchmark and publicly available imaging datasets for colorectal and gastric cancers are presented. This review synthesizes findings from 20 articles on colorectal cancer and 16 on gastric cancer, culminating in a total of 36 research articles. A significant focus is placed on mathematical formulations for commonly used preprocessing techniques, features, ML classifiers, and assessment metrics. Crucially, we introduce our optimized methodology for the detection of both colorectal and gastric cancers. Our performance metrics analysis reveals remarkable results: 100% accuracy in both cancer types, but with the lowest sensitivity recorded at 43.1% for gastric cancer.

We provide a new theoretical contribution to the geophysical signal processing on how the ghost operator can be approximately analytically modeled. We derive a time-space-domain receiver ghost modeling operator for a wavefront traveling under a flat sea surface. The operator can be used to model the ghost wavefront on the native acquisition geometry without going into the temporal or spatial Fourier domain. We demonstrate the ghost operator with a multivariate generalization of the Gaussian function in conjunction with a hyperbolic traveltime function and compared it with modeled Green’s functions. This multivariate special function was specifically conceived for seismic data decomposition and promotes the signal cone of the data. Its composition with the hyperbolic traveltime function also ensures signal cone preservation and stable ghost operator computation. The ghost model derived is valid independent of streamer depth, i.e., for shallow as well as deep towed-streamer geometry, and it can also be extended to the source ghost. The proposed method, when combined with an appropriate data decomposition approach, provides a step toward developing deghosting algorithms in the native acquisition geometry with minimal user-defined parameters.

To date, the mechanical models of magnetoelectric couplings at finite strains have mainly been limited to time-independent constitutive equations. This paper enhances the literature by developing a time-dependent electromagnetic constitutive equation to characterise the mechanical behaviour of soft solids at finite strains and take into account the full form of the Maxwell equations. Our formulation introduces a symmetrical total stress and uses recently developed spectral invariants in the amended energy function; as a result, the proposed constitutive equation is relatively simple and is amenable to a finite-element formulation.

Atomization is an intricate operation involving unstable and complex networks with rupture and fusion of liquid molecules. There are diverse details that typify the spray formation, which are the technique and configuration of the atomization process, dimension and structure of the nozzle, experimental parameters, etc. Ultimately, the process generates fine sprays from the bulk of a liquid. Some examples of atomization that we come across in our day-to-day life are antiperspirant or hair spray, shower head, garden sprinkler, or cologne mist. In this review paper we are briefly discussing the theoretical steps taking place in an atomization technique. The instabilities of the jet and sheet are explained to understand the underlying theory that breaks the jet or sheet into droplets. Different types of atomization processes based on the energy sources are also summarized to give an idea about the advantages and disadvantages of these techniques. We are also discussing the various biomedical applications of the electrohydrodynamic atomization and its potential to use as a drug delivery system. In short, this paper is trying to demonstrate the diverse applications of atomization to show its potency as a user friendly and cost-effective technique for various purposes.

Recent large-scale operations, including frequent maritime transportation and unauthorised as well as unlawful collisions of drainage wastes, have polluted the ocean’s ecology. Due to the ocean’s unsuitable ecology, the entire globe may experience drastic aberrant conditions, which will force illness onto all living things. Therefore, an advanced system is very necessary to remove the undesired waste from the ocean’s surface and interior. Through the use of progressive unmanned amphibious vehicles (UAV), this study provides a dynamic operational mode-based solution to damage removal. In order to successfully handle the heavy payloads of ravage collections when the UAV reveals centre of gravity concerns, a highly manoeuvrable-based design inspired by nature has been imposed. The ideal creatures to serve as the inspiration for this piece are tropical birds, which have a long tail for navigating tricky situations. The design initialization was carried out by focusing on the outer body of tropical birds. Following this, special calculations were conducted and the full design parameters of the UAV were established. This study proposes a unique mathematical formulation for the development of primary and secondary design parameters of an UAV. The proposed mission profile of this application is computationally tested with the aid of sophisticated computational methodologies after the modelling of this UAV. The computational methods that are required are one-way coupling-based hydro-structural interaction assessments and computational hydrodynamic analyses. Computing is used to determine the aerodynamic and hydrodynamic forces over the UAV, the lightweight materials to withstand high fluid dynamic loads, and the buoyancy forces to complete the UAV components. These computational methods have been used to produce a flexible and fine-tuned UAV design for targeted real-time applications.

The conjugate problem of aerodynamics and heat and mass transfer in heat-shielding structures made of ablating polymer composite materials is considered. To determine the heat fluxes in the shock layer, the chemical composition of the atmosphere is taken into account. A mathematical formulation of the joint problem is formulated and an algorithm for numerical solution is proposed. An example of a numerical solution of the problem for the reentry spacecraft Stardust is presented. It is shown that due to the high temperatures of aerodynamic heating of a structure made of a polymer composite material, an intense internal generation of gas appears in the structure of the material, which can lead to the destruction of the material.