Solution Of Problem Research Articles

SLIDING FRICTION IN CONTACTS WITH ONE- AND TWO-DIMENSIONAL VISCOELASTIC FOUNDATIONS AND VISCOELASTIC HALF-SPACE

Solid viscoelasticity is one of the essential origins of sliding friction, as every solid exhibits energy dissipation due to it during deformation processes. In this paper, we first show theoretical solutions for one-dimensional (1D) problems of viscoelastic friction with a 1D viscoelastic foundation. Then, we extend the 1D model to a two-dimensional (2D) model to find theoretical solutions for 2D problems of viscoelastic friction. Finally, we apply the Method of Dimensionality Reduction (MDR) to the theoretical solutions for the 1D problems to discuss three-dimensional (3D) problems of viscoelastic friction.

A Lean Six Sigma approach aided improvement for simultaneous electrochemical determination of antiviral drug favipiravir and levodropropizine as an option in the treatment of COVID-19 using glassy carbon electrode modified NiFe2O4 nanocomposite in different matrices

Favipiravir (FPV) is a widely used drug that works well against a variety of infectious RNA viruses. It is commonly used as an anti-influenza medication. To treat patients infected with RNA viruses, combination therapy consisting of FPV and levodropropizine (LDP) is required. As a result, an effective electrochemical sensor for identifying FPV in human plasma samples has been developed. The hydrothermal method is used to synthesize NiFe2O4NPs, a binary transition metal oxide comprising iron and nickel. The effective synthesis of these materials is verified by energy-dispersive X-ray analysis (EDX) and X-ray diffraction (XRD). The developed nanocomposite underwent physicochemical and electrochemical characterization, and the experimental setup was refined. Two broad linear dynamic ranges were obtained for both medications using Differential Pulse Voltammetry (DPV): 0.5 µM–200 µM for FPV and 1.0 µM–110 µM for LDP. For FPV, the computed detection and quantitation limits were 0.148 µM and 0.45 µM, while for LDP, they were 0.297 µM and 0.9 µM. The recommended technique was successfully used to analyze both medications at the same time in human plasma samples, and acceptable percentage recoveries were attained. In terms of greenness, EcoScale and GAPI greenness tools were used to evaluate the analytical methodology. Additional studies on repeatability, stability testing, interference analysis, and greenness evaluation supported the validity of the recommended method for the simultaneous measurement of FPV and LDP in laboratories for quality assurance. Additionally, Lean Six Sigma (LSS) quality technique is regarded as a collection of management disciplines for continuous improvement and method control. It is thought to offer the most practical way to address the negative effects of variation by taking steps toward analytical process improvement. As a result, LSS can be considered an invaluable tool in any laboratory, serving as a standard method for process optimization and problem solutions as well as a managerial discipline. Furthermore, it guarantees a strong method specification at a high degree of statistical confidence and targeted performance.

Modal Analysis and Optimization of Fluid-Structure Coupling for Rotor and Inner Cylinder of Vertical Condensate Pump

Background: Low-frequency resonance is one of the common issues encountered during the variable-frequency operation of condensate water pumps. There have been numerous patents and papers proposing solutions to address the low-frequency resonance problem in condensate water pumps. However, the solutions for resonance problems often need to be tailored to specific circumstances. Methods: Based on the acoustic method, the dynamic model of the rotor and inner cylinder of Jiangsu Guohua Chenjiagang Power Plant 2B condensate pump is established to compare the difference between dry modal and fluid-structure coupling modal, the influence of perpendicularity, concentricity and bearing wear on the natural frequency of rotor is studied. Results: The rotor is rigid under normal conditions. When the bearing is worn, the frequency of the rotor will be greatly reduced and may fall into the frequency conversion operation range to excite resonance. The deviation of perpendicularity and concentricity will not directly lead to the decrease of rotor modal but will lead to the increase of bearing stress, aggravate bearing wear, and then affect the rotor modal. As the inner cylinder only relies on the fixed support at the top, the structure stiffness is low, which may lead to low-frequency resonance. By adding two support structures at the guide vane, the first-order modal frequency of the inner cylinder can be increased from 3.29 Hz to 28.88 Hz, effectively avoiding the operating frequency range of the system. Conclusion: This study can guide the optimization of similar pump structures.

A computation analysis with heat and mass transfer for micropolar nanofluid in ciliated microchannel: With application in the ductus efferentes

Inherited heat enhancement capabilities and their significance in the field of medical sciences and industry make nanofluids the focus of research nowadays. Furthermore, due to the remarkable advancements in bionanotechnology and its significance in biomedical fields such as drug delivery systems, cancer tumor therapy, bioimaging, and many others, it has emerged as a key research area. Contribution of cilia for the flow in ductus efferentes of human male reproductive tract is elaborated. A novel mathematical scheme is presented for the heat and mass transfer of MHD micropolar nanofluid transport in an asymmetric channel lined with cilia. The pertinent equations of nanofluid transport are exposed to lubrication approximation theory and solution for the physical problem is examined with efficient bvp4c technique in MATLAB. Fluid rheology is explored with the variations of different transport parameters like Hartmann number, Grashof number, Brownian motion, buoyancy, thermophoresis and Darcy number. It is reported that nanofluid transport is affected with rise in the Lorentz force and show reverse behavior with rising permeability. The temperature of the nanofluid in ciliated microchannel is raised with enhanced value of Hartmann number, Grashof number, Prandtl number, and Darcy number while diffusion phenomenon of nanofluid is slowed down with these parameters. Spinning motion of the nanofluid is enhanced with Grashof number and slow down with nanoparticle Grashof number and different behavior is recorded for Darcy and viscosity parameters in different flow regime. Reported investigation presents crucial findings for ciliary transport of micropolar nanofluid and tackled with appropriate selection of micropolar parameter, Brownian motion parameter, thermophoresis and Grashof number. Moreover, this investigation will be handful for cilia-based actuators which work as micro-mixers in controlling the flow in minute bio-sensors and may prove their worth in micro-pumps employed in various drug-delivery systems.

Existence and uniqueness of periodic pseudospherical surfaces emanating from Cauchy problems

We study implications and consequences of well-posed solutions of Cauchy problems of a Novikov equation describing pseudospherical surfaces. We show that if the co-frame of dual one-forms satisfies certain conditions for a given periodic initial datum, then there exist exactly two families of periodic one-forms satisfying the structural equations for a surface. Each pair then defines a metric of constant Gaussian curvature and a corresponding Levi-Civita connection form. We prove the existence of universal connection forms giving rise to second fundamental forms compatible with the metric. The main tool to prove our geometrical results is the Kato’s semi-group approach, which is used to establish well-posedness of solutions of the Cauchy problem involved and ensure C 1 regularity for the first fundamental form and the Levi-Civita connection form.

Work Perceptions by Italian Nurses: Implications for Managers at the Point of Care.

The aim of this article is to report on Italian nurses' perceptions of their performance and work-related behaviors. The data for the study were derived from a questionnaire that included the items from the Individual Workplace Performance Scale, which was distributed via the internet during March 2021. The analysis of the responses found that women complained more about their work than men. Older nurses reported concerns about keeping up-to-date; they also thought that they carried out their work more efficiently than younger nurses and that they were better able to come up with creative solutions for new problems. The nurses who had been working for 6 to 10 years reported feeling more vulnerable in their positions. Further research is needed to help nurse managers manage their staff and reach their organizational goals.

Existence Results for Differential Equations with Tempered Ψ–Caputo Fractional Derivatives

The method of the equivalent system of fractional integral equations is used to prove the existence results of a unique solution for initial value problems corresponding to various classes of nonlinear fractional differential equations involving the tempered Ψ–Caputo fractional derivative. These include equations with their right side depending on ordinary as well as fractional-order derivatives, or fractional integrals of the solution.

Reduced-dimensional modelling for nonlinear convection-dominated flow in cylindric domains

The aim of the paper is to construct and justify asymptotic approximations for solutions to quasilinear convection–diffusion problems with a predominance of nonlinear convective flow in a thin cylinder, where an inhomogeneous nonlinear Robin-type boundary condition involving convective and diffusive fluxes is imposed on the lateral surface. The limit problem for vanishing diffusion and the cylinder shrinking to an interval is a nonlinear first-order conservation law. For a time span that allows for a classical solution of this limit problem corresponding uniform pointwise and energy estimates are proven. They provide precise model error estimates with respect to the small parameter that controls the double viscosity-geometric limit. In addition, other problems with more higher Péclet numbers are also considered.

Level-set based shape optimization for plane elastic structures using radial basis functions and Hilbertian descent direction

Structural optimization problems are often associated with the so-called shape functionals depending on a shape through its geometry and the state being a solution of given partial differential equation. In such a framework it is convenient to work with the gradient-like method based on a concept of a shape derivative and level set method. The key idea of level set method is to represent the structural boundary with zero level set of given function (level set function—LSF). Now, changing the shape of a structure under optimization is equivalent to transport the LSF in such a direction that ensures decreasing the value of the objective functional. To this end, we make use of coercive bilinear form taken from the weak formulation of elasticity problem to obtain descent direction at each iteration. This descent direction is a solution of an additional variational problem, involving the bilinear form mentioned above and the volumetric expression of the shape derivative plays the role of a linear form. In this paper, we combine level set method with radial basis functions (RBFs) used to approximate LSF. We focus on the so-called multiquadric RBFs, but other classes of RBFs are also briefly considered. This eventually leads to transformation of partial differential equation (linear transport equation governing the evolution of shapes) to a system of linear ordinary differential equations which admits analytical formula for the solution. We apply our method to compliance minimization of a cantilever problem as well as to total potential energy minimization of a structure with kinematic loading. To run all the numerical experiments, we wrote our own code in Wolfram Mathematica environment.

Character-Level Embedding using FastText and LSTM for Biomedical Named Entity Recognition

Extracting biomedical entities has caught many researchers’ attention in which the recent technique of word embedding is employed for such a task. Yet, the traditional word embedding architectures of Word2vec or Glove are still suffering from the ‘out-of-vocabulary’ (OOV) problem. This problem occurs when an unseen term might be encountered during the testing which leads to absence of embedding vector. Hence, this study aims to propose a character-level embedding through FastText architecture. In fact, handling the character-level seems a promising solution for the OOV problem. To this end, the proposed FastText architecture has been used to generate embedding vectors for the possible N-gram combinations of each word. Consequentially, these vectors have been fed to a Long Short Term Memory (LSTM) architecture for classifying the words into its biomedical classes. Using two benchmark datasets of BioCreative-II and NCBI, the proposed method was able to produce an f-measure of 0.912 and 0.918 respectively. Comparing these results with the baseline studies demonstrates the superiority of the proposed character-level embedding of FastText in terms of Biomedical Named Entity Recognition (BNER) task.

Population-based algorithm for discrete facility location with ranking of candidate locations

Facility location problems are mathematical optimization problems that involve finding the best locations for facilities (e.g., factories, warehouses, stores) to serve customers within a given geographic area. The goal is typically to minimize costs, maximize efficiency, or optimize other objectives. Facility location problems can vary in several ways, including customer behavior rules, the type of search space, and constraints on locations for new facilities being located. These variations directly impact the complexity of the problem and the appropriate solution methods that can be used to tackle the problem. This research is focused on the discrete competitive facility location problem for an entering firm, which is a crucial scenario for new firms entering the existing market. The goal is to strategically locate new facilities to maximize their profit, while considering existing competitors. A new random search heuristic algorithm to approximate the optimal solution for discrete competitive facility location problems for firm expansion has been developed. The algorithm extends its precursor that ranks potential locations for the new facilities depending on their usefulness and uselessness in creating new solutions in the past. The new algorithm uses a population to handle and reuse the best solutions found so far and new strategies for ranking potential locations, considering features of the solutions in the population. The designed algorithm has been investigated by solving competitive facility location problems actual for an entering firms using real geographical data.

Ensemble Graph Neural Networks for Fake News Detection Using User Engagement and Text Features

In this digital world with massive information sharing, spreading misinformation is relatively easy, but its consequences are really enormous. Detecting fake news is a critical challenge in today's digital age, where misinformation can spread rapidly and influence public opinion. This paper proposes an ensemble model (EGNN) that leverages Graph Neural Networks (GNNs) and text features to enhance the accuracy of fake news detection. The model is designed to operate effectively even when labeled data is scarce by utilizing a substantial amount of unlabeled data. We employ multiple GNNs, including a standard GNN, a Graph Attention Network (GAT), and a Bidirectional GCN (BiGCN), to capture user engagement patterns and social context. Additionally, text embeddings are extracted using spaCy, BERT, and a combination of spaCy with user profile information. These embeddings are then classified using a neural network, and the final detection is performed using ensemble techniques such as Majority Voting, Weighted Average, and Stacking. To address class imbalance, we incorporate focal loss alongside the traditional binary cross-entropy loss. Experimental results demonstrate that our proposed EGNN model significantly improves the detection of fake news, providing a robust solution for this pervasive problem.

Effect of step bottom and waterway on flexural gravity wave scattering

Flexural gravity wave scattering by two semi-infinite non-identical ice sheets, which are separated by a clean water surface, is investigated in the presence of a step bottom topography. The problem is investigated in the cases of (i) intermediate water depth and (ii) shallow water. The effect of two edge conditions, (i) simply supported edge and (ii) free edge, on wave scattering is also analyzed. Employing linear velocity potential theory, the problem is studied in the frequency domain. The physical phenomenon is modeled as a boundary value problem having the Laplace equation as the governing equation, and it is solved using the eigenfunction expansion method. Considering the bottom topography and upper boundary, the fluid domain is divided into three regions, and in each region, velocity potential is expressed in terms of infinite Fourier series. Velocity and pressure are matched at the intermediate surface of two regions, and a system of algebraic equations with unknown coefficients is obtained. The complete solution of the present problem is recognized by solving the system of equations numerically. The energy relation is derived using Green's theorem. The reflection and transmission coefficients are computed and compared with the energy relation to check the accuracy of the present method. For different parameters (depth ratio, clean waterway, and different ice properties), reflection coefficient and transmission coefficient are computed and presented as a function of angular frequency. The value of the reflection coefficient ranges from zero to unity, whereas at certain frequencies, the transmission coefficient attends value more than unity.

Empirical risk minimization for big data driven prescriptive analytics: An exploration of two-stage stochastic programs with recourse

In the operations research literature, data driven analyses using big data are receiving more and more interest and attention. However, big data driven operational analyses are still limited in scope, with only unconstrained big data driven problems, e.g. the newsvendor problem, being comprehensively explored. If big data driven analyses are to become a core part of operations research and practice, one must be able to formulate and solve constrained big data driven models. We therefore propose a direct empirical risk minimization (DERM) method for formulating and solving a class of constrained big data driven operation research problems. In big data driven problems, relevant operational prescriptions are dependent on a set of observed features. In this paper, we assume linear feature relationships, which enable us to fundamentally base the DERM method on linear stochastic programming. The assumption of linear feature relationships is also seen in the literature on big data driven newsvendor models. We prove that if a big data driven solution exists, the DERM method will always, for the class of constrained problems we study, arrive at a feasible solution of the initial operational problem. Moreover, we exemplify the DERM method by formulating and solving two specific big data driven operational problems. In the numerical study of the two operational problems, we show, that under linear demand, the DERM method outperforms, with regard to cost, two benchmark methods and a big data driven method from literature.

A novel dimensionality reduction iterative method for the unknown coefficient vectors in TGFECN solutions of unsaturated soil water flow problem

The main purpose of this paper is to reduce the dimensionality of unknown coefficient vectors in finite element (FE) solutions of two-grid FE Crank-Nicolson (CN) (TGFECN) format for the unsaturated soil water flow (USWF) problem with two strong nonlinear terms by using proper orthogonal decomposition (POD). For this purpose, our first step involves designing a time semi-discrete CN (TSDCN) scheme for the USWF problem and demonstrate the existence, boundedness, and error estimations of TSDCN solutions. Thereafter, we discretize the TSDCN scheme using the two-grid FE method to create a new TGFECN format and prove the existence, boundedness, and error estimations of TGFECN solutions. The primary focus should be on reducing the dimension of unknown coefficient vectors of TGFECN solutions through the utilization of the POD technique in creating a novel format, referred to as dimension reduction iterative TGFECN (DRITGFECN) format, while establishing the existence, boundedness, and error estimations for DRITGFECN solutions. Lastly, we use two sets of numerical tests to exhibit the advantage of the DRITGFECN format. Due to the presence of two highly nonlinear terms in the unsaturated soil flow problem, the development and analysis of DRITGFECN format pose greater challenges and necessitates more advanced technical skills compared to previous studies. However, the significance and broad applications of this research make it a valuable subject for investigation.

Damage Prediction Effect of Reinforced Concrete Column and Beam Structure Improved by Multimedia Technology

In order to improve the damage prediction effect of concrete structural column and beam structure, this paper uses multimedia technology to improve the damage prediction effect of reinforced concrete structural column and beam structure. Moreover, this paper presents the intelligent transformation model and the corresponding solution of the general damage problem, and deduces the error relationship between the result estimator and the importance function according to the error of the importance function. In addition, by analyzing the relationship between the importance function and the dual transport calculation, this paper proposes a complementary dual calculation process that can provide the importance function to each other, and builds an intelligent prediction model. Through the experimental research, it can be seen that the multimedia technology algorithm proposed in this paper can play an important role in the damage prediction of concrete structural columns and beams.

A Second-Order Numerical Method for a Class of Optimal Control Problems

The numerical solution of optimal control problems through second-order methods is examined in this paper. Controlled processes are described by a system of nonlinear ordinary differential equations. There are two specific characteristics of the class of control actions used. The first one is that controls are searched for in a given class of functions, which depend on unknown parameters to be found by minimizing an objective functional. The parameter values, in general, may be different at different time intervals. The second feature of the considered problem is that the boundaries of time intervals are also optimized with fixed values of the parameters of the control actions in each of the intervals. The special cases of the problem under study are relay control problems with optimized switching moments. In this work, formulas for the gradient and the Hessian matrix of the objective functional with respect to the optimized parameters are obtained. For this, the technique of fast differentiation is used. A comparison of numerical experiment results obtained with the use of first- and second-order optimization methods is presented.

Large deformation problem of hyperbolic shallow shells with bimodular effect: A perturbation‐variation method

AbstractAs an important analytical method, the perturbation‐variation method combines the advantages of perturbation method and variational method, and is widely used for the solution of nonlinear plate and shell problems. In this study, the perturbation‐variation method is used to solve the large deformation problem of a flexible hyperbolic thin shallow shells with different moduli in tension and compression (bimodular effect). First, we establish the governing equations expressed in terms of three displacement components, in which the bimodular effect of materials is considered in physical equations and the large deformation of shell is considered in geometrical equations. Next, we use the perturbation‐variation method to solve the governing equations established, obtaining the perturbation‐variation solution up to third‐order. During the application of the method, the displacements are expressed into perturbation formulas of all levels first, and the unknown constants and functions in the perturbation formulas are determined by the extreme value conditions of the functional established (variational principle), hence the perturbation‐variation method gets its name from this practice. The numerical results from FEM basically agree with the perturbation‐variation solution obtained. The method proposed may be extended into the solution of similar partial differential equations established in applied fields.

Advanced CFD simulation of two-phase anion exchange membrane water electrolysis

Anion exchange membrane (AEM) water electrolysis is a promising and inexpensive solution for hydrogen production and environmental problems. Owing to its low technical proficiency, AEM electrolysis necessitates high fidelity to improve its durability, reliability, and efficiency. Therefore, a CFD-based model for AEM electrolysis was developed to analyze the three-dimensional and two-phase phenomena inside the cell. The temperature, pressure, and gas generation profiles inside the cell were studied by combining electrochemical models with mass, momentum, and heat transfer models. Parameters were estimated using the experimental data from a high-accuracy model. The results showed that the applied voltage, which determined the exothermic/endothermic mode, significantly influenced the water electrolysis performance. Specifically, in the exothermic mode, with voltages exceeding the thermo-neutral voltage (1.48 V), the amount of hydrogen generated (15.53, 25.05, and 28.82 mol/m3 at 1.6, 1.8, and 2.0 V, respectively) was higher than that in the endothermic mode (4.78 mol/m3 at 1.45 V). However, the increased gas generation caused a rapid increase in the temperature and pressure drop inside the cell, which adversely affected durability. The model developed in this study can be used in experiments of various scales to optimize serpentine designs and commercial AEM electrolysis stack developments.

A project and lift approach for a 2-commodity flow relocation model in a time expanded network

We deal here with a general 2-commodity flow model over a time expanded network designed for the management of a shared mobility systems. The model involves an integral flow vector that represents carriers together with an integral flow vector that represents the items transported by those carriers. It simultaneously copes with temporal and resource issues, and is difficult to handle in the practice. So we propose here a Project and Lift approach to handle it. We start by projecting the time expanded network model on the original transit network to obtain a simpler two-commodity flow projected model. In order to make this projected model consistent with the original problem, we introduce some complex constraints, prove that these constraints can be separated in polynomial time and discuss the experimental behavior of the related Branch-and-Cut algorithm. Next, we introduce the Lift issue about the way one may turn an optimal solution of our projected model into a solution of the original problem. Finally, we thoroughly study a somewhat restrictive Strong Lift setting of this Lift issue, design and test an exact mixed integer programming Strong Lift model, and discuss some flexible alternative approaches.