Search Results (6,244)

The Johnson–Mehl–Avrami–Kolmogorov (JMAK) formalism provides a classical framework for describing polymer crystallization kinetics; its applicability under finite-domain confinement requires quantitative assessment. In this work, the influence of one-dimensional geometric restriction on cylindrical growth in polymer thin films is investigated using a stochastic Monte Carlo approach. The model considers site-saturated nucleation on randomly distributed cylindrical nanofibers with constant radial growth velocity under hard-wall boundary conditions. Crystallization kinetics were evaluated through automated segmented regression of the double-logarithmic JMAK representation. Under confinement, the Avrami plot departs from single-slope linearity and exhibits two successive quasi-linear regimes characterized by effective parameter pairs $\left(n_1,\ln k_1\right)$ and $\left(n_2,\ln k_2\right)$. The primary exponent $n_1$ remains thickness-independent, consistent with early-stage radial expansion prior to boundary interaction. The secondary exponent $n_2$ displays a non-monotonic dependence on reduced film thickness, reflecting the competing influence of wall-induced truncation and inter-domain impingement on late-stage transformation. These results support a geometric interpretation in which finite-domain constraints modify the apparent Avrami response through the competing effects of wall-induced truncation and inter-domain impingement and provide a reproducible framework for analyzing dual-regime Avrami behavior in confined crystallization systems. Full article

Heavy metals in lake sediments represent typical persistent contaminants characterized by recalcitrance, bioaccumulation potential, and delayed toxic effects, thereby exerting sustained adverse impacts on lacustrine ecosystem stability and human health. Liuye Lake is a representative small-to-medium urban lake impacted by ambient domestic sewage discharge and agricultural non-point source pollution, with documented nitrogen and phosphorus enrichment. However, the contamination profile of heavy metals in its surface sediments has not been systematically investigated to date. In this work, surface sediment samples were collected from Liuye Lake, and nine heavy metal elements (As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Zn) were determined. An integrated approach incorporating Monte Carlo simulation, the geo-accumulation index (I_geo), and the enrichment factor (EF) method was employed to assess the ecological risk and human health risk imposed by these metals. The results revealed the following: (1) Average concentrations of eight heavy metals exceeded the background values of the Dongting Lake water system, with the exception of As, and Hg displayed potential localized anomalies. (2) Surface sediments were collectively categorized as slightly contaminated, with Hg identified as the primary pollutant, followed by minor contamination of Mn, Cr, and Ni; Monte Carlo simulation further suggested a probable risk that Mn contamination could progress to moderate levels. (3) All heavy metals posed low potential ecological risk, with an overall potential ecological risk index (RI) of 62.71, where Cd, Hg, and As were the dominant contributors. (4) Both non-carcinogenic and carcinogenic risks were generally within acceptable limits, whereas children exhibited higher non-carcinogenic susceptibility relative to adults; As and Mn were the leading contributors to non-carcinogenic risk, while Cr and As dominated carcinogenic risk. This study offers a scientific foundation for the prevention and control of heavy metal pollution and the ecological management of urban lakes. Full article

This work presents the design of an attitude control experiment for onboard OPS-SAT-1 satellite execution, conceived with inherent extensibility to future mission architectures. OPS-SATs are ESA nanosatellite mission series designed as an in-orbit testbed for validating novel software and control techniques under real space conditions, OPS-SAT-1 being the first mission. Equipped with an advanced payload computer, OPS-SAT-1 enabled experimentation with innovative mission operations, including real-time attitude control strategies. Two attitude control algorithms, a modified Proportional–Integral–Derivative (mPID) and a fuzzy logic controller, were designed and implemented for the OPS-SAT-1. The design methodology applied to these controllers consisted of (i) modelling the space environment and satellite characteristics, (ii) assessing actuator feasibility, (iii) determining the operational ranges for attitude error and angular velocity, (iv) parametrizing controllers within these ranges, (v) fine-tuning controllers using multi-objective genetic optimization, and (vi) robustness analysis using the Monte Carlo method. Despite the technical issues related to communication with the OPS-SAT-1 hardware, which prevented the execution of the experiment in orbit, this work presents the simulation results that were obtained. These results indicate that fuzzy logic controllers may outperform PID controllers in terms of the accumulated error, settling time and steady-state error, whereas power efficiency appears to be less robust than in the PID. This suggest that a large uncertainty in the model could lead the PID to become more efficient. Near the nominal scenario, the fuzzy controller achieves superior error–cost trade-offs, enabling precise attitude stabilization with lower energy consumption. These findings suggest the potential advantages of modern control approaches compared to classical methods, which will be further assessed through future in-orbit experiments. Full article

Mercury (Hg) bioaccumulation in freshwater fish represents a major pathway of human exposure, particularly in cascade reservoir systems where hydrological retention and legacy contamination can enhance methylmercury (MeHg) formation and trophic transfer. This study quantified total mercury (THg) concentrations in seven tissues of seven fish species from the Arda River cascade (Bulgaria). Multi-tissue measurements were integrated with morphometric predictors, multivariate statistical analyses, and combined deterministic and probabilistic human-health risk assessments. Muscle and liver contained the highest THg concentrations, whereas gills and gonads exhibited the lowest levels. Predatory species and larger individuals accumulated significantly more Hg, reflecting trophic magnification and size-dependent exposure. A longitudinal gradient across the cascade reservoirs suggests hydrological retention effects influencing mercury distribution. Species- and tissue-specific size–Hg relationships further indicate heterogeneous bioaccumulation dynamics among taxa. Risk assessment indicated acceptable exposure for adults and pregnant women at average consumption (140 g·week⁻¹), but elevated exposure for children consuming high-Hg predators. Monte Carlo simulations (N = 30,000) revealed upper-tail risks, while Safe Weekly Intake thresholds provided species-specific consumption limits. These findings highlight the value of integrating multi-tissue monitoring with probabilistic risk modelling to support evidence-based fish-consumption advisories in contaminated freshwater systems. Full article

Spatially fractionated radiotherapy with X-ray minibeams (x-MBRT) aims to increase normal-tissue tolerance by delivering alternating high- and low-dose regions. We provide a Monte Carlo-based framework to design and optimize multi-slit collimators, quantifying how geometry and material govern peak–valley modulation. A validated digital twin of the SmART X-RAD225Cx irradiator was implemented in TOPAS/Geant4. Various x-MBRT collimators were simulated with parallel or divergent slits. The parameter space covered a slit width w (0.1–0.9 mm), center-to-center spacing CTC (1–3 mm), thickness T (1–5 mm), and acceptance angle θ. Dose was scored in a 2 × 2 × 2 cm³ water phantom at a 1 cm depth. For fixed w/CTC, peak-valley dose ratio PVDR increases with larger CTC via an increase in peak dose, with the valley dose nearly constant. Peak transmission saturated at θ ≈ 3°, indicating minimal benefit from larger acceptance. Divergent slits yielded flatter lateral profiles but higher valley doses than parallel slits, reducing PVDR around the central axis. This Monte Carlo study provides insights for optimizing collimator geometries in x-MBRT using small-animal irradiators, informing the design of more effective collimation systems to enhance treatment precision and normal-tissue sparing. Full article

Polarized side-scattering techniques are widely used in aerosol detection, oceanographic optics, and biomedical sensing due to their high sensitivity to weak optical signals in low-scattering coefficient media. Conventional polarized Monte Carlo methods face significant challenges in such regimes due to geometric mismatch, where photon exit positions deviate substantially from the detector plane. This study addresses the geometric mismatch issue in polarized Monte Carlo simulations for side scattering in low-scattering media (scattering coefficient ${\mu }_s=$ 1 cm⁻¹), where photon exit positions often deviate from the detector plane. We propose a novel algorithm incorporating backward ray tracing with geometric projection correction to enhance simulation accuracy. Experimental validation was conducted using 532 nm laser illumination on both 500 nm polystyrene microspheres (${\mu }_s=$ 0.21 cm⁻¹) and 5 nm TiO₂ nanoparticles (${\mu }_s=$ 1.06 × 10⁻⁶–1.06 × 10⁻⁵ cm⁻¹). The results demonstrate excellent agreement between simulations and experiments, confirming the algorithm’s capability to accurately capture the polarization characteristics of side-scattered light. This work provides a high-fidelity simulation tool for designing optical sensors in low-scattering media and holds direct applicability in nanoparticle concentration sensing and aerosol monitoring. Full article

Shellfish are one of the important aquatic products in coastal areas. Due to their feeding mechanism, viruses can accumulate in their tissues during the feeding process. Most of the current research on HEV in shellfish is limited to the sampling of the surface layer to detect its prevalence, and traditional quantitative risk assessment methods face challenges in assessing the potential risks associated with consumption. Using the R language, we combined 2011–2024 literature detection data with experimental results to simulate infection risk for Chinese urban and rural residents under cooked and raw-consumption scenarios. Single-exposure infection probabilities were similar, but annual risks were comparable across groups. For urban residents, the 95% CrI of annual risk was 3.83 × 10⁻⁵ (2.5 × 10⁻⁶–3.56 × 10⁻⁴) (raw) and 1.2 × 10⁻⁸ (3.8 × 10⁻¹⁰–4.3 × 10⁻⁷) (cooked); for rural residents, the confidence interval was 2.69 × 10⁻⁵ (1.8 × 10⁻⁶–2.50 × 10⁻⁴) (raw) and 8.4 × 10⁻⁹ (2.5 × 10⁻¹⁰–3.0 × 10⁻⁷) (cooked). By assessing the prevalence of HEV in shellfish and the probability of infection after consumption, the safety awareness of the Chinese population regarding shellfish consumption can be strengthened. Also, suggestions can be derived from HEV prevalence data in various countries, to improve the breeding environment and reduce relevant prevalence and risks. Full article

As typical natural disasters in coastal areas, node failure and link interruption caused by typhoons directly threaten the operation stability of the freight multimodal transportation network (FMTN) in urban agglomerations. Such disruptions, in turn, restrict the sustainable development of the regional transportation and logistics system. In order to scientifically assess the FMTN resilience level in coastal area urban agglomerations under typhoon disturbances, this study constructs a resilience assessment method that integrates structural performance and functional performance. The Spatial Local Failure model and the Monte Carlo method, combined with fragility curves, are used to dynamically simulate the damage process of FMTN nodes and links by different typhoons intensities. By constructing FMTN resilience performance function, the resilience ratio is used to quantitatively assess the damage resistance and resilience maintenance level of FMTN under disturbances. This study also analyzes the resilience difference between FMTN and its sub-networks. The Typhoon Bebinca case is applied to validate the application of FMTN assessment method. The results show that FMTN exhibits stronger invulnerability and robustness under typhoon disturbances, and its resilience is significantly better than that of sub-networks. Specifically, when a strong typhoon hits, the FMTN resilience ratio only decreases by 0.13, while the resilience ratio of each sub-network decreases significantly by 0.21, 0.42, 0.46 and 0.57, respectively. FMTN resilience under typhoon disturbances is further assessed through an example analysis. And it verifies not only the comprehensive advantage of FMTN under typhoon disturbances but also the rationality and practicability of the assessment method. The findings can provide an important theoretical basis and technical support for resilience assessment, disaster prevention, mitigation planning, and the sustainable development of FMTN in coastal area urban agglomerations. It is of great practical significance to promote the efficient operation of China’s FMTN. Full article

Ensuring uninterrupted access to essential medicines in public healthcare systems is a persistent challenge with clinical, economic, and environmental implications. Oncology services are particularly vulnerable to stockouts, which compromise therapeutic continuity and increase reliance on urgent procurement with high carbon and waste footprints. This study proposes a risk-informed, data-driven framework for pharmaceutical inventory governance in a high-complexity public oncology hospital in Chile, aligning with sustainability goals and green supply chain principles. Using operational data from 2023–2024, we integrate descriptive analytics, ABC–XYZ segmentation, and a continuous-review (s, Q) policy extended through a Logistic Risk Index (LRI) that consolidates demand variability, supply performance, and clinical-economic criticality. Empirical analysis reveals strong expenditure concentration in AX/AY segments and significant misalignment between institutional and analytically derived parameters. A Monte Carlo simulation N = 1000 runs per scenario) compares baseline, adjusted, and fully risk-informed policies under stochastic demand and lead-time conditions. Results show that the risk-informed configuration reduces stockout exposure by up to 46%, improves fill rates (93.1% → 96.4%), and shortens replenishment delays, while maintaining total logistic cost stability. Critically, urgent orders decrease from 27.4 to 14.8 per year, avoiding an estimated 630 kg CO₂ emissions and 25 kg of packaging waste annually. These findings demonstrate that resilience, efficiency, and sustainability are not competing objectives but can be jointly achieved through integrated analytics and governance. The proposed approach offers a scalable blueprint for public health systems seeking to transition from reactive inventory management toward anticipatory, transparent, and sustainability-oriented decision-making, contributing to SDG 3 (health and well-being) and SDG 12 (responsible consumption and production). Full article

The time-optimal rendezvous problem is crucial for efficiently executing on-orbit servicing (OOS) missions in the future. To fulfill the detection requirement during rendezvous process, it is an essential issue that the maneuvering spacecraft flies over the designated waypoint. This paper presents an innovative methodology for planning the time-optimal spacecraft rendezvous trajectory, involving the constraints related to a flyover waypoint and being forced by a constant thrust. The method is specifically designed to handle the optimal problems with the shortest and unspecified flyover time and terminal rendezvous time. First, this article outlines the scenarios for a time-optimal rendezvous that incorporates the constraints of a flyover waypoint. Second, a time-normalized relative dynamic model for maneuvering spacecraft is derived using the Clohessy–Wiltshire (CW) equation. Third, the time-optimal control output under the constant thrust is provided leveraging Pontryagin’s minimum principle (PMP). Meanwhile, an indirect solution equation is established with the constraints of relative position and velocity for the flyover waypoint during the rendezvous process. Finally, a computational methodology for solving this time-optimal problem is proposed, integrating the initial guess for the unspecified time, multi-objective particle swarm optimization using multiple search strategies (MMOPSO) and Newton–Raphson method (NRM). Simulation results demonstrate that the method can effectively and practically solve the time-optimal rendezvous trajectory planning under a constant thrust, while satisfying the constraints of the flyover waypoint. Moreover, Monte Carlo simulations are performed, the results of which indicate that the proposed methodology exhibits strong robustness and fidelity. Full article

Cosmological filaments, galaxy clusters, and galaxies are magnetized reservoirs of cosmic rays (CRs). The exchange of CRs across these structures is usually modeled assuming that they remain charged and magnetically confined. At high energies, hadronic interactions can convert CR protons to neutrons. This physics is routinely included in air-shower and ultra-high-energy (UHE) CR propagation Monte Carlo simulations used for composition studies but is rarely treated explicitly in propagation models of CR transport and exchange between magnetized reservoirs. CR neutrons are not affected by magnetic fields and can propagate ballistically over kpc-Mpc distances before decaying back into protons, with relativistic time dilation extending their effective decay length. We show how such charged–neutral switching modifies CR confinement and escape in four representative environments: a Milky Way-like galaxy, a starburst galaxy, a galaxy cluster, and a cosmological filament. By solving the transport of a confined CR proton population in each structure using a diffusion/streaming propagation approach with hadronic pp and p$\gamma$ interactions, and treating neutron production and decay as a stochastic Poisson “jump” process, we find that neutron-mediated steps can allow additional CR escape from large-scale cosmological structures at energies where charged-particle transport alone would predict strong CR confinement and attenuation in ambient radiation fields. These effects imply a qualitative shift in how ultra-high-energy CRs are transferred from embedded sources into filaments and voids once intermediate neutron propagation is considered, with consequences for the partitioning of CRs across the large-scale structure of the Universe. Full article

The correct valuation of collateral supporting real estate loans has always been a key issue for the stability of the credit system. Substandard lending practices and the absence of uniform valuation approaches have historically contributed to the accumulation of non-performing loans. In recent years, several regulatory measures operating at both the European and national level have introduced principles, rules and procedures aimed at standardizing the valuation of properties pledged as collateral for credit exposures. These interventions seek to promote greater transparency, consistency, and prudence in property appraisals, thereby enhancing the soundness and resilience of the financial system. In January 2025, the updated Regulation (EU) 575/2013 came into force, incorporating the Basel III reform (also referred to as Basel 3+ or Basel IV). Among the innovations introduced, the concept of property value (PV) is particularly relevant, a prudential value that excludes expectations of price growth and considers the sustainability of the value over time in relation to the duration of the loan. PV is defined as a derived value with respect to market value (MV), determined by considering the main current and forward-looking risk factors that may arise during the life of the loan, including environmental, social and governance (ESG) risks, the intrinsic characteristics of the property and expectations regarding the economic cycle. This paper proposes a quantitative model for the determination of PV, applied to a practical case involving a residential property located in a medium-sized city in Italy’s Veneto region. The model adopts a deterministic and a probabilistic approach, the latter implemented through Monte Carlo simulation, which is indeed a generalization of the deterministic one. The model links the assessment of PV to the possible evolution of the property’s key parameters and the real estate cycle over the duration of the loan. It was tested under the assumption of a twenty-year mortgage originated in 2025 for the purchase of a residential property in Italy, considering two alternative locations: a suburban area and a city-centre area. The analysis conducted showed a substantially higher MV haircut for the suburban property compared with the central location. This difference reflects the fact that PV is less sensitive to real estate cycle fluctuations in more premium, central locations. Furthermore, the use of Monte Carlo simulation in the probabilistic approach enabled the calibration of the haircut according to a predefined confidence level, confirming the pattern observed in the deterministic framework. The combined evidence strengthens the empirical robustness of the model and highlights the importance of locational and cyclical dynamics in collateral valuation. Full article

Climate change and rapid urbanization are intensifying flood risks in China, particularly in regions with complex terrain and dense populations. Traditional risk assessment methods often lack the flexibility to handle uncertainties in multi-dimensional risk systems. This study proposes a probabilistic flood risk assessment framework integrating Monte Carlo simulation with a composite indicator system from the perspective of disaster system theory. Taking Hunan Province as a case study, we constructed a hierarchical indicator system encompassing environmental susceptibility, hazard intensity, exposure vulnerability, and mitigation capacity. The analytic hierarchy process (AHP) and coefficient of variation (CV) methods were combined for indicator weighting, and Monte Carlo simulation was employed to quantify uncertainties and classify risk levels. Results reveal significant spatial heterogeneity in flood risk across the province, with high-risk areas concentrated in regions exhibiting intense rainfall, dense river networks, and insufficient mitigation infrastructure. The study provides a transferable, data-driven approach for spatially explicit flood risk zoning, offering evidence-based insights for land-use planning, resilient infrastructure development, and sustainable flood governance. This research contributes to the integration of probabilistic modeling into land system science, supporting disaster risk reduction and climate adaptation strategies aligned with SDG 11. This study also provides policy-relevant insights for regional flood governance by supporting risk-informed land-use planning, targeted infrastructure investment, and adaptive flood management strategies, thereby contributing to more resilient and sustainable land system development under increasing climate uncertainty. Full article

Accurate identification of slope failure mechanisms under shallow foundations is essential for reliable risk assessment and reinforcement design. However, existing studies often neglect the spatial variability of soil properties and the influence of footing shape. This study develops a non-intrusive stochastic finite difference framework integrating random field theory, Monte Carlo simulation, and a Gaussian mixture model to automatically characterize three-dimensional slope failure domains under rectangular footing loads. Results show that slope failure mechanisms are primarily governed by the footing aspect ratio and the scale of fluctuation in soil strength. Square footings mainly induce shallow slope face failure, whereas rectangular footings significantly increase the probability of deep toe failure as the scale of fluctuation increases. Stochastic analyses generally yield larger mean failure volumes than deterministic analyses. Risk assessment further indicates that risk levels are primarily controlled by the absolute failure volume at low safety factors, whereas failure variability becomes increasingly influential at higher safety factors. Full article

This paper focuses on the critical issue of change point detection in panel linear regression models and proposes a novel jump information criterion (JIC) for efficient solution. The core innovation of this criterion lies in reconstructing the traditional change point hypothesis testing problem into a parameter estimation problem: under the null hypothesis ($H_0$, i.e., no change point exists in the model) and the alternative hypothesis ($H_1$, i.e., a change point exists in the model), the number of potential change points is set to 0 and 1 for modeling and solution, respectively. To verify the theoretical reliability of the proposed method, this paper systematically establishes the consistency of the change point count estimator through rigorous mathematical deductions and further derives its optimal convergence rate. In terms of numerical validation, extensive Monte Carlo simulation experiments and real data empirical analysis both demonstrate that the estimator constructed based on JIC exhibits excellent performance in change point identification accuracy, stability, and computational efficiency, providing a reliable new tool for structural break analysis in panel data models. Full article