Search Results (897)

The development of efficient and accurate numerical methods forms a crucial foundation for revealing complex dynamic evolution in nonlinear dynamical systems. Focusing on nonlinear inertia-coupled systems, this paper constructs a semi-analytical method that integrates the mathematical framework of real modal analysis with the piecewise constant arguments and Taylor series (P-T) method. This method first conducts symmetric preprocessing on the second-order term coefficient matrix of the system to construct the proportional damping decoupling form. Then, it realizes the linear term decoupling corresponding to this proportional damping form by using the mathematical framework of real modal analysis. Finally, the P-T method is applied to solve the dynamic response of the nonlinear system. Numerical validation using a two-dimensional aeroelastic system demonstrates that, under the premise of achieving the same computational accuracy as the time-domain minimum residual method (TMRM), the computational efficiency of the proposed method is significantly better than that of TMRM. Full article

Diamorphine (DIM, heroin) is a semi-synthetic opioid that undergoes rapid conversion to 6-monoacetylmorphine and morphine, producing short-lived biomarkers that are difficult to capture during the process. This review critically explores the evolution of analytical techniques for quantitative DIM analysis in biological matrices from 1980 to 2025. It synthesizes findings across blood, plasma, urine, hair, sweat, and postmortem samples, emphasizing matrix-specific challenges and forensic applicability. Unlike previous opioid reviews that primarily focused on metabolites, this work highlights analytical methods capable of successfully detecting diamorphine itself alongside its key metabolites. This review examines 32 studies spanning three decades and compares three core analytical methods: gas chromatography–mass spectrometry (GC–MS), high-performance liquid chromatography (HPLC) with optical detection and liquid chromatography–mass spectrometry (LC–MS). Key performance metrics include sensitivity, sample preparation workflow, hydrolysis control, metabolite coverage, matrix compatibility, automation potential and throughput. GC–MS remains the workhorse for hair and sweat ultra-trace screening after derivatization. HPLC with UV, fluorescence or diode-array detection enables robust quantification of morphine and its glucuronides in pharmacokinetic and clinical settings. LC–MS facilitates the multiplexed analysis of DIM, its ester metabolites and its conjugates in a single, rapid run under gentle conditions to prevent ex vivo degradation. Recent advances such as high-resolution mass spectrometry and microsampling techniques offer new opportunities for sensitive and matrix-adapted analysis. By integrating validation parameters, forensic applicability, and evolving instrumentation, this review provides a practical roadmap for toxicologists and analysts navigating complex biological evidence. Full article

This paper proposes a 2D semi-analytical model based on the subdomain method for the performance analysis of a brushless doubly fed reluctance machine (BDFRM) with a salient pole rotor. In particular, assuming an infinite magnetic permeability of the iron core and assuming a smooth stator, the field calculation region is divided into two solution subdomains, i.e., the rotor slot and air-gap. The magnetic vector potential in each subdomain is obtained by solving the governing PDE by the separation of variables method and employing the boundary conditions between adjacent interfaces. Moreover, based on the stored magnetic energy in the air-gap, the calculation of the three-phase windings’ self and mutual inductances is presented. Through a case study involving a 6/2 pole BDFRM, the accuracy of the developed subdomain model is confirmed by comparing its analytically predicted results with those obtained from two-dimensional finite element method (FEM) simulations. Full article

Mathematical optimization, in both continuous and discrete forms, is well established and widely applied. This work addresses a gap in the literature by focusing on large-number optimization, where integers or fractions with hundreds of digits occur in decision variables, objective functions, or constraints. Such problems challenge standard optimization tools, particularly when exact solutions are required. The suitability of computer algebra systems and high-precision arithmetic software for large-number optimization problems is discussed. Our first contribution is the development of Python implementations of an exact Simplex algorithm and a Branch-and-Bound algorithm for integer linear programming, capable of handling arbitrarily large integers. To test these implementations for correctness, analytic optimal solutions for nine specifically constructed linear, integer linear, and quadratic mixed-integer programming problems are derived. These examples are used to test and verify the developed software and can also serve as benchmarks for future research in large-number optimization. The second contribution concerns constructing partially increasing subsequences of the Collatz sequence. Motivated by this example, we quickly encountered the limits of commercial mixed-integer solvers and instead solved Diophantine equations or applied modular arithmetic techniques to obtain partial Collatz sequences. For any given number J, we obtain a sequence that begins at $2^J-1$ and repeats J times the pattern ud: multiply by $3x_j+1$ and then divide by 2. Further partially decreasing sequences are designed, which follow the pattern of multiplying by $3x_j+1$ and then dividing by $2^m$. The most general J-times increasing patterns (ududd, udududd, …, ududududddd) are constructed using analytic and semi-analytic methods that exploit modular arithmetic in combination with optimization techniques. Full article

Background: Chronic pain affects nearly one in five adults worldwide and is increasingly recognized not only as a disease but as a potential risk factor for neurocognitive decline and dementia. While some evidence supports this association, existing systematic reviews are static and rapidly outdated, and none have leveraged advanced methods for continuous updating and robust uncertainty modeling. Objective: This protocol describes a living systematic review with dose–response Bayesian meta-analysis, enhanced by artificial intelligence (AI) tools, to synthesize and maintain up-to-date evidence on the prospective association between any type of chronic pain and subsequent cognitive decline. Methods: We will systematically search PubMed, Embase, Web of Science, and preprint servers for prospective cohort studies evaluating chronic pain as an exposure and cognitive decline as an outcome. Screening will be semi-automated using natural language processing models (ASReview), with human oversight for quality control. Bayesian hierarchical meta-analysis will estimate pooled effect sizes and accommodate between-study heterogeneity. Meta-regression will explore study-level moderators such as pain type, severity, and cognitive domain assessed. If data permit, a dose–response meta-analysis will be conducted. Living updates will occur biannually using AI-enhanced workflows, with results transparently disseminated through preprints and peer-reviewed updates. Results: This is a protocol; results will be disseminated in future reports. Conclusions: This living Bayesian systematic review aims to provide continuously updated, methodologically rigorous evidence on the link between chronic pain and cognitive decline. The approach integrates innovative AI tools and advanced meta-analytic methods, offering a template for future living evidence syntheses in neurology and pain research. Full article

This article analyses journalistic decisions in the face of disinformation, focusing on the case of Vaza Jato in Brazil. Drawing on a mixed-methods approach—combining critical discourse analysis of online articles with semi-structured interviews with two editors—the study explores how two ideologically contrasting newspapers (Folha de S.Paulo and Gazeta do Povo) framed and justified their editorial positions regarding the publication of hacked content. The findings reveal distinct narrative strategies, degrees of epistemological openness, and levels of institutional trust in the judiciary and political actors. The results also show how editorial decisions are shaped by broader concerns about professional legitimacy, audience trust, and the ambiguous boundary between journalism and disinformation. This article contributes to research on disinformation, editorial ethics, and media trust, proposing an analytical framework applicable to other high-risk communication contexts. Full article

This study optimizes the ultrasound-assisted extraction (UAE) of bioactive compounds from Spirulina platensis and develops a rapid, non-destructive analytical method. A Box–Behnken design and desirability function were used to find the optimal extraction conditions to simultaneously maximize total polyphenols, proteins, C-phycocyanin, and antioxidant activity. The optimal conditions were a solid-to-liquid ratio of 35 g/L, a time of 20 min, a pH of 10, and a temperature of 45 °C. Independent validation confirmed the model’s reliability, with experimental results closely matching predicted values. Furthermore, Near-Infrared (NIR) spectroscopy, combined with Artificial Neural Networks (ANNs), was explored as a predictive tool. The models, particularly those based on a semi-process NIR spectrometer, showed excellent predictive capabilities for key physicochemical properties, with an RPD of 3.9064 for L* and 2.8351 for TDS. This research establishes a highly reproducible and scalable extraction protocol, complemented by a fast and accurate analytical method, providing a significant advancement for the industrial application and quality control of Spirulina platensis extracts. Full article

This article presents the results of a study on the possibility of using a single-speed multiphase model with free surface allowance for simulating boiling and condensation processes. The simulation is based on the VOF method, which allows the position of the interphase boundary to be tracked. To increase the stability of the iterative procedure for numerically solving volume fraction transfer equations using a finite volume discretization method on arbitrary unstructured grids, the basic VOF method is been modified by writing these equations in a semi-divergent form. The models of Tanasawa, Lee, and Rohsenow are considered models of interphase mass transfer, in which the evaporated or condensed mass linearly depends on the difference between the local temperature and the saturation temperature with accuracy in empirical parameters. This paper calibrates these empirical parameters for each mass transfer model. The results of our study of the influence of the values of the empirical parameters of models on the intensity of boiling and evaporation, as well as on the dynamics of the interphase boundary, are presented. This research is based on Stefan’s problem of the movement of the interphase boundary due to the evaporation of a liquid and the problem of condensation of vapor bubbles water columns. As a result of a series of numerical experiments, it is shown that the average error in the position of the interfacial boundary for the Tanasawa and Lee models does not exceed 3–6%. For the Rohsenow model, the result is somewhat worse, since the interfacial boundary moves faster than it should move according to calculations based on analytical formulas. To investigate the possibility of condensation modeling, the results of a numerical solution of the problem of an emerging condensing vapor bubble are considered. A numerical assessment of its position in space and the shape and dynamics of changes in its diameter over time is carried out using the VOF method, taking into account the free surface. It is shown herein that the Tanasawa model has the highest accuracy for modeling the condensation process using a VOF method taking into account the free surface, while the Rohsenow model is most unstable and prone to deformation of the bubble shape. At the same time, the dynamics of bubble ascent are modeled by all three models. The results obtained confirm the fundamental possibility of using a VOF method to simulate the processes of boiling and condensation and taking into account the dynamics of the free surface. At the same time, the problem of the studied models of phase transitions is revealed, which consists of the need for individual selection of optimal values of empirical parameters for each specific task. Full article

This paper provides an overview of various size-dependent theories based on modified/consistent couple stress and strain gradient theories (CSTs and SGTs), highlighting the development of two-dimensional (2D) refined and advanced shear deformation theories (SDTs) and three-dimensional (3D) pure analytical and semi-analytical numerical methods, including their applications, for analyzing the static and dynamic behaviors of microscale plates and shells made from advanced materials such as fiber-reinforced composites, functionally graded (FG) materials, and carbon nanotube/graphene platelet-reinforced composite materials. The strong and weak formulations of the 3D consistent CST, along with their corresponding boundary conditions for FG microplates, are derived and presented for illustration. A comparison study is provided to show the differences in the results of a simply supported FG microplate’s central deflection, stress, and lowest natural frequency obtained using various 2D size-dependent SDTs and 3D analytical and numerical methods based on the consistent CST. A parametric study is conducted to examine how primary factors, such as the effects of dilatational and deviatoric strain gradients and couple stress, impact the static bending and free vibration behaviors of a simply supported FG microplate using a size-dependent local Petrov–Galerkin meshless method based on the consistent SGT. Influences such as the inhomogeneity index and length-to-thickness ratio are considered. It is shown that the significance of the impact of various material length-scale parameters on the central deflection and its lowest natural frequency (in the flexural mode) of the FG microplate is ranked, from greatest to least, as follows: the couple stress effect, the deviatoric strain gradient effect, and finally the dilatational strain gradient effect. Additionally, when the microplate’s thickness is less than 10⁻⁷ m, the couple stress effect on its static and dynamic behaviors becomes saturated. Conversely, the impact of the dilatational and deviatoric strain gradients consistently influences the microplate’s static and dynamic behaviors. Full article

The presence of discontinuities in fractured reservoirs, their mechanical and physical characteristics, and fluid flow through them are important factors influencing their effective large-scale properties. In this paper, the variation of elastic moduli in a block measuring 100 × 100 × 100 m³ that hosts a discrete fracture network (DFN) is evaluated using the discrete element method (DEM). Fractures are characterised by (1) constant, (2) interlocked, and (3) mismatched stiffness properties. First, three uniaxial verification tests were performed on a block (1 × 1 × 2 m³) containing a circular finite fracture (diameter = 0.5 m) to validate the developed numerical algorithm that implements the three fracture stiffnesses mentioned above. The validated algorithms were generalised to fractures in a DFN embedded in a 100 × 100 × 100 m³ rock block that reproduces in situ conditions at various depths (4.7 km, 2.3 km, and 0.5 km) of the Soultz-sous-Forêts geothermal site. The effective elastic moduli of this large-scale rock mass were then numerically evaluated through a triaxial loading scenario by comparing to the numerically evaluated stress field using the DFN, with the stress field computed using an effective homogeneous elastic block. Based on the results obtained, we evaluate the influence of fracture interaction and stress perturbation around fractures on the effective elastic moduli and subsequently on the large-scale P-wave velocity. The numerical results differ from the elastic moduli of the rock matrix at higher fracture densities, unlike the other methods. Additionally, the effect of nonlinear fracture stiffness is reduced by increasing the depth or stress level in both the numerical and semi-analytical methods. Full article

The integration of traditional ecological knowledge (TEK) into contemporary landscape planning is hampered by a lack of methodological frameworks that can translate site-specific practices into generalizable design principles. This study addresses this gap by developing and applying an integrated analytical framework to decode the resilient Ruza farming system in Nagaland, India. Employing a mixed-methods approach that triangulates qualitative data (ethnographic observation, semi-structured interviews) with spatial analysis (drone-based orthomosaics), this research moves beyond mere description to extract a set of transferable socio-ecological design principles. The findings identify four core principles such as vertical integration, gravity-fed resource flow, closed-loop resource cycling, and participatory governance, that underpin the system’s functionality. By demonstrating a clear methodological pathway from fieldwork to framework, this research contributes a replicable “methodological bridge” for landscape architects and planners. While derived from a single case study, the framework offers a robust approach for applying the logic of TEK to create climate-resilient and culturally grounded designs in diverse contexts. Full article

Illegal waste dumping poses a severe challenge to sustainable urban and regional development, undermining environmental integrity, public health, and the efficient use of resources. This study contributes to sustainability science by proposing a circular data feedback loop that enables dynamic, scalable, and cost-efficient monitoring and prevention of illegal dumping, aligned with the goals of sustainable waste governance. Historical data from the Slovenian illegal dumping register, UAV-based surveys and a newly developed application were used to update, monitor, and validate waste site locations. A comprehensive risk model, developed using machine learning methods, was created for the Municipality of Maribor (Slovenia). The modelling approach combined unsupervised and semi-supervised learning techniques, suitable for a positive-unlabeled (PU) dataset structure, where only confirmed illegal waste dumping sites were labeled. The approach demonstrates the feasibility of a circular data feedback loop integrating updated field data and predictive analytics to support waste management authorities and illegal waste dumping prevention. The fundamental characteristic of the stated approach is that each iteration of the loop improves the prediction of risk areas, providing a high-quality database for conducting targeted UAV overflights and consequently detecting locations of illegally dumped waste (LNOP) risk areas. At the same time, information on risk areas serves as the primary basis for each field detection of new LNOPs. The proposed model outperforms earlier approaches by addressing smaller and less conspicuous dumping events and by enabling systematic, technology-supported detection and prevention planning. Full article

Functionally graded porous beam (FGPB) structures are widely used in engineering due to their light weight, high strength, and vibration-damping performance. However, their energy localization and vibration suppression characteristics remain largely unexplored. To address this gap, this study proposes an axially functionally graded porous beam (AFGPB) structure capable of achieving energy localization and suppressing vibration transmission. A semi-analytical model is first developed within the Rayleigh–Ritz framework, using Gaussian functions as basis functions to accurately represent the displacement field. The accuracy of the model is validated by comparing its vibration characteristics with those obtained using the finite element method (FEM). Subsequently, the vibration behavior of double-AFGPB with simply supported boundary constraints is investigated. A series of numerical results are presented in this study to analyze the influence of porosity parameters on the energy localization effect and vibration suppression performance. Results reveal that the porosity power-law index N and truncation coefficient δ play key roles in energy localization and vibration suppression performance. When N ≥ 4, the energy localization effect and the vibration attenuation of the double-AFGPB become more pronounced with increasing N and decreasing δ, particularly in the low-frequency range. Full article

The initial part of this study fills a notable research gap by investigating the substantial impact of numerical diffusion errors from different schemes on sloshing tank models. Multiple numerical models were developed: first- and higher-order upwind schemes equipped with precise wall treatment using ghost nodes, MacCormack and central methods that are explicit second-order finite difference methods, and Preissmann and staggered methods employed in full-implicit and semi-implicit modes. Furthermore, the separation of variables technique was proposed for simulating sloshing tanks and deriving an analytical equation for the tank’s natural period. An analytical solution to the perturbation was employed to examine the numerical diffusion of the schemes. Subsequently, two sloshing tests, resonant and near-resonant excitations, were employed to determine the numerical diffusion and calibrate the physical diffusion coefficients, respectively. Finally, an efficient and accurate numerical scheme was applied to a linear shallow water model including physical diffusion and coupled with a single degree of freedom (SDOF), to simulate tuned liquid dampers (TLDs). It shows that the efficiency of TLD is associated with a compact domain around resonance excitation. Contrary to SDOF alone, when SDOF interacts with TLD the impact of structural damping on reducing the response is minimal in resonance excitation. Full article

This study aims to evaluate the effectiveness of five analytical and semi-analytical methods for estimating Lamb wave dispersion in viscoelastic plates—the Rayleigh–Lamb solution, the Global Matrix Method (GMM), the Semi-Analytical Finite Element (SAFE) method, the Scaled Boundary Finite Element Method (SBFEM), and the Legendre Polynomial Method (LPM). The Rayleigh–Lamb equations are solved using an optimized Newton–Raphson algorithm, enhancing computational efficiency while maintaining comparable accuracy. The SAFE method exhibited a remarkable balance between computational efficiency and physical accuracy, outperforming SBFEM at high frequencies. For epoxy and high-performance polyethylene (HPPE) plates, the SAFE method and the LPM significantly outperform the GMM in relation to computational efficiency, with errors below $1\%$ for fundamental symmetric and antisymmetric modes across the tested frequency range of 0 to 100 kHz. In addition, the ability of the SAFE method to accurately predict both phase velocity and attenuation in viscous media supports their use in guided-wave-based structural health monitoring applications. Among the investigated approaches, the SAFE method emerges as the most robust and accurate for viscoelastic plates, while the SBFEM and LPM show limitations at higher frequencies. This study provides a quantitative and methodological foundation for selecting and implementing numerical methods for guided wave analysis, emphasizing the dual necessity of physical fidelity and numerical stability. Full article