Search Results (21)

Physics-informed neural networks (PINNs) offer a mesh-free approach to solving partial differential equations (PDEs) with embedded physical constraints. Although PINNs have gained traction in various engineering fields, their adoption for railway bridge analysis remains under-explored. To address this gap, a systematic review was conducted across Scopus and Web of Science (2020–2025), filtering records by relevance, journal impact, and language. From an initial pool, 120 articles were selected and categorised into nine thematic clusters that encompass computational frameworks, hybrid integration with conventional solvers, and domain decomposition strategies. Through natural language processing (NLP) and trend mapping, this review evidences a growing but fragmented research landscape. PINNs demonstrate promising capabilities in load distribution modelling, structural health monitoring, and failure prediction, particularly under dynamic train loads on multi-span bridges. However, methodological gaps persist in large-scale simulations, plasticity modelling, and experimental validation. Future work should focus on scalable PINN architectures, refined modelling of inelastic behaviours, and real-time data assimilation, ensuring robustness and generalisability through interdisciplinary collaboration. Full article

Predicting the evolution of financial data, if at all possible, would be very beneficial in revealing the ways in which different aspects of a global environment can impact local economies. We employ an iterative stochastic differential equation that accurately forecasts an economic time series’s next value by analysing its past. The input financial data are assumed to be consistent with an $\alpha$-stable Lévy motion. The computation of the scaling exponent and the value of $\alpha$, which characterises the type of the $\alpha$-stable Lévy motion, are crucial for the iterative scheme. These two indices can be determined at each iteration from the form of the structure function, for the computation of which we use the method of generalised moments. Their values are used for the creation of the corresponding $\alpha$-stable Lévy noise, which acts as a seed for the stochastic component. Furthermore, the drift and diffusion terms are calculated at each iteration. The proposed model is general, allowing the kind of stochastic process to vary from one iterative step to another, and its applicability is not restricted to financial data. As a case study, we consider Greece’s stock market general index over a period of five years, from September 2019 to September 2024, after the completion of bailout programmes. Greece’s economy changed from a restricted to a free market over the chosen era, and its stock market trading increments are likely to be describable by an $\alpha$-stable L’evy motion. We find that $\alpha =2$ and the scaling exponent H varies over time for every iterative step we perform. The forecasting points follow the same trend, are in good agreement with the actual data, and for most of the forecasts, the percentage error is less than 2%. Full article

In the present paper, an evaluation of the damage behaviour of quasi-brittle composites exposed to mechanical, thermal, and other loads is studied by means of viscoelastic and/or viscoplastic material models, applying some non-local regularisation techniques to the initiation and development of damages. The methods above are presented as a strong tool for a deeper understanding of material structures in miscellaneous engineering disciplines like civil, mechanical, and many others. Nevertheless, all of the software packages reflect certain compromises between the need for effective computational tools, with parameters obtained from inexpensive experiments, within the possibilities and the complexity of both physical and geometrical descriptions of structure deformation within processes. The article is devoted to the mathematical aspects regarding a considerably wide class of computational modelling problems, emphasising the following ones: (i) the existence and the uniqueness of solutions of engineering problems formulated in terms of the deterministic initial and boundary value problems of partial differential equations theory; (ii) the problems of convergence of computational algorithms applied to (i). Both aspects have numerous references to possible generalisations and investigations connected with open problems. Full article

Based on a systematic literature review, no design guidelines addressing practical issues related to steel circular hollow section (CHS) members under hydrostatic pressure have been documented thus far, except for the design recommendations proposed by the European standard EN 1993-1-6 concerning the strength and stability of shell structures. Considering that the existing codes are often outdated and subject to improvement, there is a growing demand for modern solutions that can accurately replicate the stability loss response of equipment subject to external pressure. The development of a more direct and simple method, augmented by reliable computational techniques, is advisable to avoid the numerous challenges associated with manual calculations. This approach will streamline the design process and mitigate the complexity of current practical or technical approaches. Thus, this research has formulated a method to predict design strength through the direct application of the critical elastic buckling stress, determined from Generalised Beam Theory (GBT) analyses, induced by hydrostatic pressure in custom-crafted equations, finely tuned for this specific objective. The authors present a formulation of GBT to analyze the elastic buckling behavior of CHS subject to both combined axial compression and external pressure. This work provides an extensive study of the behavior of circular cylindrical shells under external loading conditions. It first introduces the analyses of GBT and the theoretical and empirical formulas applicable to this objective. It then describes the steps involved in the development and validation of a numerical model that simulates the response of circular cylindrical shells under hydrostatic pressure, conducting an extensive parametric study using finite element analyses (FEAs). The results from available tests validate the finite element (FE) model. Upon achieving adequate agreement between the generated numerical and experimental results, new resistance reduction curves for cylindrical shell members are developed based on the results of the parametric study. Additionally, the study compares the existing provisions of EN 1993-1-6 for the design of cylindrical shells under hydrostatic pressure. Finally, a statistical approach is adopted to compare the responses of cylindrical shells calculated according to the EN 1993-1-6 code recommendations with those obtained through the newly proposed method. Full article

Train configurations give rise to a primary wagon pass forcing frequency and their multiples. When any one of these frequencies coincides with the natural frequency of vibration of the bridge, a resonant response can occur. This condition can amplify the dynamic response of the bridge, leading to increased levels of displacement, stresses and acceleration. Increased stress levels on critical bridge structural elements increases the rate at which fatigue damage accumulates. Increased bridge acceleration levels can affect passenger comfort, noise levels, and can also compromise train safety. For older bridges the effects of fatigue, and being able to predict the remaining life, has become a primary concern for bridge engineers. Better understanding of the sensitivity of fatigue damage to the characteristics of the passing train will lead to more accurate remaining life predictions and can also help to identify optimal train speeds for a given train–bridge configuration. In this paper, a mathematical model which enables the dynamic response of railway bridges to be assessed for different train configurations is presented. The model is based on the well established closed from solution of the Euler–Bernoulli Beam (EBB) model, for a series of moving loads, using the inverse Laplace–Carson transform. In this work the methodology is adapted to allow different train configurations to be easily implemented into the formulation in a generalised form. A generalised equation, which captures the primary wagon pass frequency for any train configuration, is developed and verified by presenting the results of the bridge response in the frequency domain. The model, and the accuracy of the equation for predicting the primary wagon pass frequency, is verified using independently obtained measured field train–bridge response data. The main emphasis of this work is to enable the practicing engineer, railway operators and bridge asset owners, to easily and efficiently make an initial assessment of dynamic amplification, and the optimal train speeds, for a given bridge and train configuration. This is visually presented in this work using a Campbell diagram, which shows dynamic amplification and compares this with those calculated based on the design code, across a range of train speeds. The diagram is able to identify train speeds at which a resonance response can occur, and the wagon pass frequency, or its multiples, which are causing the increased dynamic amplification. The model is implemented in Matlab and demonstrated by analysing a range of short- to medium-single span simply supported plate girder railway bridges, typically found on the UK railway network, using the standard BS-5400 train configurations. The model does not consider the effects of the train mass and suspension system as this would require a non-closed form numerical solution of the problem which is not practical for the purposes of an initial assessment of the train–bridge interaction problem. Full article

The purpose of this study was to establish whether digital literacy and insurtech adoption influence insurance inclusion in Uganda. Principally, we sought to determine whether insurtech adoption mediates the nexus between digital literacy and insurance inclusion. This study adopted a cross-sectional and quantitative correlational approach. The study’s sample was 391 individuals who had used digital platforms such as mobile phones and computers to access insurance products and services in Uganda. Data were collected using structured survey questionnaires. Partial Least Squares Structural Equation Modelling (PLSEM) was employed to test the hypothesised relationships. The results demonstrated that both digital literacy and insurtech adoption significantly and positively influence insurance inclusion. We also found digital literacy to be a significant and positive determinant of insurtech adoption. Markedly, it was found that insurtech adoption mediates the association between digital literacy and insurance inclusion in Uganda. However, this study was conducted in a developing country with an underdeveloped insurance market and with low technological advancement. This may affect the generalisation of the study’s findings. This study’s novelty lies in establishing how digital literacy and insurtech adoption interact to influence insurance inclusion in Uganda. This is the first study to examine the effect of digital literacy and insurtech adoption on insurance inclusion. Full article

Ambient vibration energy is widely being harnessed as a source of electrical energy to drive low-power devices. The vibration energy harvester (VEH) of interest employs an electromagnetic transduction mechanism, whereby ambient mechanical vibration is converted to electrical energy. The limitations affecting the performance of VEHs, with an electromagnetic transduction structure, include its operational bandwidth as well as the enclosure-size constraint. In this study, an analysis and design of a nonlinear VEH system is conducted using the Output Frequency Response Function (OFRF) representations of the actual system model. However, the OFRF representations are determined from the Generalised Associated Linear Equation (GALE) decompositions of the system of interest. The effect of both nonlinear damping and stiffness characteristics, to, respectively, extend the average power and operational bandwidth of the VEH device, is demonstrated. Full article

In this research work, we investigate the complex structure of soliton in the Fractional Kudryashov–Sinelshchikov Equation (FKSE) using conformable fractional derivatives. Our study involves the development of soliton solutions using the modified Extended Direct Algebraic Method (mEDAM). This approach involves a key variable transformation, which successfully transforms the model into a Nonlinear Ordinary Differential Equation (NODE). Following that, by using a series form solution, the NODE is turned into a system of algebraic equations, allowing us to construct soliton solutions methodically. The FKSE is the governing equation, allowing for heat transmission and viscosity effects while capturing the behaviour of pressure waves in liquid–gas bubble mixtures. The solutions we discover include generalised trigonometric, hyperbolic, and rational functions with kinks, singular kinks, multi-kinks, lumps, shocks, and periodic waves. We depict two-dimensional, three-dimensional, and contour graphs to aid comprehension. These newly created soliton solutions have far-reaching ramifications not just in mathematical physics, but also in a wide range of subjects such as optical fibre research, plasma physics, and a variety of applied sciences. Full article

The concept of the smart city is well-established, and governments across the world are either planning, or already implementing, strategies to transform existing cities to smart status. However, governments cannot act alone. If the implementation of these smart city strategies are to be successful, public engagement is a key factor. This raises the question of how best to ensure public engagement. Currently, the various external factors that influence willingness to support, and actively participate in, the development of smart cities are not well-understood, as there are few studies which examine the issue. This is of significance across the globe, but is of particular significance in Saudi Arabia, which has announced an ambitious smart city development plan. The aim of this research is to explore this issue—that is, it seeks to identify the key variables that influence the intention to participate in smart city development, and explores how they ultimately affect engagement behaviours. To achieve this, the study used a quantitative methodology, based on data from residents of 10 Saudi cities, each of which is part of the Kingdom’s 2030 smart city plan. The data were analysed, using structural equation modelling (SEM), in order to test the reliability and predictive value of a model which hypothesised a positive relationship between five external variables: information availability, perceived benefits, social norms, behaviour management, and social responsibility and engagement behaviour. The results showed that information availability has a direct and positive effect on an individual’s engagement behaviour, while perceived benefits, responsibility and social norms have an indirect effect on engagement, by positively impacting the attitude of residents. Practical implications, based on these findings, are discussed. The study contributes important insights to the literature, as it is one of the few studies to explore such a model in the context of smart cities. It therefore acts as a useful foundation for further research. However, the focus on Saudi cities may be considered a limitation in terms of generalisability, and other external variables could usefully be explored in future research. Full article

Purpose: To investigate the relationship between the apolipoprotein E (APOE) ε4 allele and retinal structural and vascular characteristics in older adult participants from several research studies. We also studied the relationship between these structural and vascular characteristics with multifocal visual evoked potential (mfVEP) indices, neuropsychological parameters and MRI brain volumes in these participants. Methods: In this study, 109 participants with a mean (SD) age of 67.1 (9.0) years were recruited. Participants were classified as APOE ε4 carriers or non-carriers based on the presence or absence of the ε4 allele. Baseline measurements included peripapillary retinal nerve fibre layer optical coherence tomography (RNFL OCT), and OCT–angiography (OCT-A) for evaluation of the retinal layer thickness and vessel density (VD) parameters. A multifocal visual evoked potential (mfVEP) test, including amplitude and latency, was used to assess the visual pathway function. Finally, cognitive function was evaluated using a battery of neuropsychological tests. OCT-A images were analysed in ImageJ to quantify VD in the superficial and deep vascular plexus and the size of the foveal avascular zone (FAZ). The relationship between carriers of APOE ε4 allele and these ocular parameters was analysed using generalised estimating equation (GEE) models and data adjusted for age, sex and inter-eye differences as within-subject variables (p < 0.05). Results: Twenty-four participants were APOE ε4 carriers. Temporal RNFL thickness was decreased in APOE ε4 carriers (p < 0.01). Vessel density between carriers and non-carriers was not significantly different at either the superficial or deep level. The FAZ area was significantly smaller in ε4 carriers in both superficial (p < 0.01) and deep layers (p < 0.003). Conclusions: Retinal abnormalities were present in participants with increased genetic risk of dementia due to presence of the ε4 allele. These findings provide preliminary evidence for their potential role in the diagnosis of dementia. Full article

The study aims to investigate how an individual’s technology awareness, subjective financial literacy and personal innovativeness characteristics impact the intention to use blockchain-based digital currencies such as cryptocurrency. The UTAUT 2 (Unified Theory of Acceptance and Use of Technology 2) model is extended with crucial constructs to develop the conceptual model. A total of 312 responses are analysed using Covariance-Based Structural Equation Modelling (CB-SEM). The moderation effects are assessed using multi-group analysis. The findings show a significant moderating effect of technology awareness and subjective financial literacy on the relationship between performance expectancy (PE) and behavioural intention to use cryptocurrency (BI). It further identified that performance expectancy (PE) mediates personal innovativeness (PI) and usage intentions (BI). The study adds to the growing literature of digital currency adoption by focusing on individual innovativeness, technology awareness and financial literacy. It also proposes a research model that can be generalised for new-age consumer-based financial technology adoption. Full article

Parental consent for adolescent human papillomavirus (HPV) vaccine uptake is important; however, refusal is prevalent. Therefore, this study aimed to understand factors associated with parental consent for their adolescent daughter’s HPV vaccination. A cross-sectional study was conducted in Lusaka, Zambia, between September and October 2021. We recruited parents from different social settings. The means and standard deviations or median and interquartile ranges were used as appropriate to summarise continuous variables. Simple and multiple logistic regression models were fitted with robust estimation of standard errors. The odds ratios are presented with 95% CI. Mediation analysis was conducted using a generalised structural equation model. The study enrolled 400 parents, mean age 45.7 years [95% CI, 44.3–47.1]. Two hundred and fifteen (53.8%) parents reported consenting to their daughters’ HPV vaccination, and their daughters received it. None of the health belief model (HBM) construct scores showed an independent association with parental consent. Higher, compared to lower wealth index (AOR; 2.32, 95% CI: 1.29–4.16), knowing someone with genital warts (AOR = 2.23, 95 CI: 1.04–4.76), cervical cancer screening uptake (AOR = 1.93, 95% CI: 1.03–3.62) were associated with increased odds of parental consent. This study highlights factors influencing parental consent for their daughters’ HPV vaccination. Ongoing sensitisation programs are important to improve their decision-making. Full article

A cross-sectional study of 3860 health-sector workers across two data collections was conducted to identify the predictive power of different job demands and job resources during the COVID-19 pandemic based on four indicators of distress (COVID-19 traumatic stress, burnout, generalised anxiety, and depression) among health-sector workers. Exploratory and confirmatory factor analyses, measurement invariance checks, and structural equation models were used to evaluate the dimensionality and the effect of the job demands and resources on distress indictors. The identified job demands were workload, confinement, loss, and virus exposure, while the identified job resources were self-efficacy, momentary recuperation, and meaning making. Loss and workload predicted the distress indicators best, while confinement and virus exposure mainly predicted COVID-19 traumatic stress and were less important for the other distress outcomes. Self-efficacy and meaning making negatively predicted distress, while momentary recuperation, controlled for the other demands and resources, was positively related to the distress indicators. Of the typical pandemic-related demands and resources, the experience of loss due to COVID-19 infection was the most important predictor of distress outcomes. Confinement, and especially the awareness of virus exposure, were far less important predictors. Full article

We show that the equations of motion governing the dynamics of strings in a compact internal space can be written as dispersion relations, with a local speed that depends on the velocity and curvature of the string in the large dimensions. From a (3+1)-dimensional perspective these can be viewed as dispersion relations for waves propagating in the string interior and are analogous to those for current-carrying topological defects. This allows us to construct a unified framework with which to study and interpret the internal structure of various field-theoretic and fundamental string species, in a simple physically intuitive coordinate system, without the need for dimensional reduction or approximate effective actions. This, in turn, allows us to identify the precise conditions under which higher-dimensional strings and current-carrying defects are observationally indistinguishable, for macroscopic observers. Our approach naturally incorporates the description of so-called ‘cosmic springs’, whose dynamics are expressed in terms of an effective Finsler geometry, for circular loops, or generalised Finsler geometry, for non-circular configurations. This demonstrates the importance of these novel geometric structures and their utility in modelling complex physical phenomena in cosmology and astrophysics. Full article

The formalism of a bone cell population model is generalised to be of the form of an S-System. This is a system of nonlinear coupled ordinary differential equations (ODEs), each with the same structure: the change in a variable is equal to a difference in the product of a power-law functions with a specific variable. The variables are the densities of a variety of biological populations involved in bone remodelling. They will be specified concretely in the cases of a specific periodically forced system to describe the osteocyte mechanotransduction activities. Previously, such models have only been deterministically simulated causing the populations to form a continuum. Thus, very little is known about how sensitive the model of mechanotransduction is to perturbations in parameters and noise. Here, we revisit this assumption using a Stochastic Simulation Algorithm (SSA), which allows us to directly simulate the discrete nature of the problem and encapsulate the noisy features of individual cell division and death. Critically, these stochastic features are able to cause unforeseen dynamics in the system, as well as completely change the viable parameter region, which produces biologically realistic results. Full article