Search Results (3,982)

Background: This study deploys the Lean Six Sigma DMAIC framework to achieve systemic optimization of the school subscription process in Tunisia’s public transport service, a critical administrative operation affecting efficiency and customer satisfaction across the urban mobility network. Methods: Beyond conventional applications, the research integrates advanced analytical and process engineering tools, including capability indices, measurement system analysis (MSA), variance decomposition, and root-cause prioritization through Pareto–ANOVA integration, supported by a structured control plan aligned with ISO 9001:2015 and ISO 31000:2018 risk-management standards. Results: Quantitative diagnosis revealed severe process instability and nonconformities in information flow, workload balancing, and suboptimal resource allocation that constrained effective capacity utilization. Corrective interventions were modeled and validated through statistical control and real-time performance dashboards to institutionalize improvements and sustain process stability. The implemented actions led to a 37.5% reduction in cycle time, an 80% decrease in process errors, a 38.5% increase in customer satisfaction, and a 38.9% improvement in throughput. Conclusions: This study contributes theoretically by positioning Lean Six Sigma as a data-centric governance framework for stochastic capacity optimization and process redesign in public service systems, and practically by providing a replicable, evidence-based roadmap for operational excellence in governmental organizations within developing economies. Full article

Robotic mobile fulfillment systems have become an integral part of e-commerce warehouses. The pod repositioning problem, due to its interdependence with robot task allocation strategies, poses a significant challenge that constrains system performance. In this paper, we aim to jointly optimize the two interrelated problems of pod repositioning and task allocation. A multi-objective mixed-integer planning model is developed to minimize the maximum completion time of robots and the deviation between the pod position and the expected position. To tackle the challenges of decision coupling and a vast solution space, an adaptive genetic-neighborhood search algorithm guided by pod heat maps is designed. Additionally, to promptly correct expected layout deviations and avoid layout instability, a progressive storage mechanism is designed to update the expected layout. The numerical experiments show that compared to the staged optimization strategy, the joint optimization strategy proposed in this paper can reduce the maximum completion time by approximately 48%, and that the strategy reduces the maximum completion time by 9% to 16% compared to the nearest allocation strategy, which is commonly used and performs best in practice. Full article

Water inrush disasters pose a serious threat during tunnel construction. Accurately evaluating their evolution process is essential for timely prevention and risk mitigation. Given the staged nature of seepage-instability-induced inrushes and the sensitivity of borehole resistivity imaging to water-bearing anomalies, this study explores the use of borehole resistivity methods to monitor the evolution of such events. A four-stage geoelectrical evolution model is developed based on the characteristics of inclined fault-related water inrushes. A time-lapse evaluation method combining least squares inversion and resistivity ratio analysis is proposed to assess the inrush process. Numerical simulations show that this method achieves a localization error below 2 m for inclined water-conducting channels. Across the four stages, the resistivity ratio of the channel ranges from 0.65 to 1.40, capturing the three-dimensional expansion of the inrush pathway. These findings confirm that borehole resistivity imaging effectively characterizes the evolution of water inrush disasters and supports early warning and mitigation strategies. Full article

Background: BRAF mutations are found in 10% of colon cancers (CCs) and are associated with poor prognosis in metastatic disease. BRAF V600E predicts sensitivity to cetuximab + encorafenib in the metastatic setting. With new trials testing encorafenib-containing regimens for early-stage CC, we sought to characterize the clinical outcomes of early-stage BRAF V600E CC. Methods: We performed a systematic review and meta-analysis. Key inclusion criteria were a diagnosis of stage 2/3 BRAF V600E CC. Co-primary endpoints were overall survival (OS) and recurrence/disease-free survival (DFS). Meta-analysis was performed with a random-effects model incorporating sample size, hazard ratio (HR), and 95% confidence intervals (CIs). Results: A total of 206 studies underwent full-text review. Of these, six randomized controlled trials were included, comprising 6836 and 843 patients with wild-type (WT) and BRAF V600E, respectively. BRAF V600E was associated with inferior OS (HR 1.49, CI 1.21–1.75) and DFS (HR 1.17, CI 1.03–1.33). This finding remains in patients with microsatellite instability—low/stable or proficient mismatch repair (OS: HR 1.66, CI 1.36–2.02, DFS: HR 1.45, CI 1.22–1.72). Conclusions: BRAF V600E is associated with inferior prognoses compared to BRAF WT in early-stage CC. This finding will help optimize trial design for this population. Full article

The creation of simulation-ready digital twins for real-world simulations is hindered by two key challenges: the lack of widely consistent, application-ready open access terrain data and the inadequacy of conventional evaluation metrics to predict practical, in-engine performance. This paper addresses these challenges by presenting an end-to-end, open-data pipeline that generates simulation-ready terrain and procedural 3D objects for the Unity engine. A central finding of this work is that the architecturally advanced Swin2SR transformer exhibits severe statistical instability when applied to Digital Elevation Model (DEM) data. We analyze this instability and introduce a lightweight, computationally efficient stabilization technique adapted from climate science—quantile mapping (qmap)—as a diagnostic remedy which restores the model’s physical plausibility without retraining. To overcome the limitations of pixel-based metrics, we validate our pipeline using a three-axis evaluation framework that integrates data-level self-consistency with application-centric usability metrics measured directly within Unity. Experimental results demonstrate that qmap stabilization dramatically reduces Swin2SR’s large error (a 45% reduction in macro RMSE from 47.4 m to 26.1 m). The complete pipeline, using a robust SwinIR model, delivers excellent in-engine performance, achieving a median object grounding error of 0.30 m and real-time frame rates (≈100 FPS). This study provides a reproducible workflow and underscores a crucial insight for applying AI in scientific domains: domain-specific stabilization and application-centric evaluation are indispensable for the reliable deployment of large-scale vision models. Full article

Background: Glenohumeral instability is one of the most frequent and clinically impactful complications following proximal humerus resection and reconstruction with a megaprosthesis, especially in patients treated for bone tumors or complex fractures. Its incidence, risk factors, and influence on functional recovery remain variably reported in the literature. Methods: A systematic review was conducted according to PRISMA guidelines, searching PubMed, Scopus, and Google Scholar up to April 2025. Studies reporting on postoperative instability, dislocation, functional outcomes (MSTS, DASH), and related complications were included. Two independent reviewers performed data extraction and quality assessment. A pooled analysis was performed using random-effects models. Results: A total of 17 studies including 387 patients were analyzed. The pooled incidence of glenohumeral instability was 32%, with a revision surgery rate of 10% due to instability. The most common reconstruction technique was modular megaprosthesis (47%), followed by allograft–prosthesis composites (APCs) and reverse total shoulder arthroplasty (RSA). Functional outcomes were reported in 12 studies using the Musculoskeletal Tumor Society (MSTS) score, with a weighted mean of 22.3 ± 3.8 (74.3% ± 12.7%). Disabilities of the Arm, Shoulder, and Hand (DASH) scores, reported in 3 studies, showed worse outcomes in unstable shoulders (mean 61.4 ± 5.2 vs. 26.6 ± 4.1). Soft tissue reconstruction, particularly involving the rotator cuff and deltoid, significantly influenced postoperative stability and function. Conclusions: Glenohumeral instability after proximal humerus megaprosthesis is a common and disabling complication that adversely affects functional outcomes and revision rates. Optimizing soft tissue management and prosthetic design is essential to improve joint stability and long-term results. Full article

Extensive high and steep open-pit slopes in gneiss are distributed in cold regions at high altitudes or high latitudes of China, such as Qinghai, Tibet, and Xinjiang, posing significant hazards to mine safety. Several recent slope failure incidents highlight the urgent need to study the failure modes and mechanisms of gneiss open-pit slopes in these cold regions. This study focuses on the 14 September 2023 landslide at the Jinbao Mine in Xinjiang. Initially, field investigation and displacement monitoring were employed to analyze its failure characteristics and mode. Subsequently, utilizing mechanical parameters of the gneissic foliation and the rock mass obtained under various conditions, discrete element numerical modeling was conducted to study the failure mechanisms. The results indicate that the landslide was a typical bedding failure characterized by an upper bedding-controlled sliding zone, combined with buckling and crushing of the slope toe. Under the long-term combined effects of rainfall, freeze–thaw cycles and blasting, the shear strength of the gneissic foliation decreased. This reduction led to a decrease in the anti-sliding force and an increase in the sliding force within the upper bedding-controlled sliding zone. Consequently, the load transferred to the rock mass at the slope toe progressively increased. Under prolonged compression, the toe rock mass experienced bending, which intensified over time. Coupled with the strength reduction caused by the repeated action of rainfall, freeze–thaw cycles and blasting, the toe rock mass gradually fractured and ultimately failed in a buckling mode. This led to the loss of support for the upper mass, which then subsided along the foliation, precipitating the landslide’s overall instability. Full article

To mitigate vibration in thin-walled composite combustion liners of aero-engines, this study proposes an optimization strategy for stiffener design to maximize natural frequencies and suppress resonance. The approach enhances structural dynamics by installing transverse and longitudinal stiffeners along the tubular wall, with their dimensions and orientations systematically optimized. Design variables were chosen: combustion liner wall thickness, stiffener thickness, transverse stiffener width/angle, longitudinal stiffener width, and composite lamination layup scheme. The orthogonal experiments were completed and followed by range analysis and variance analysis. The results demonstrated that wall thickness had the most significant impact on the natural frequency, and the 45° lamination scheme showed a superior performance compared to other configurations. Finally, a predictive equation was developed using a multiple linear regression model. The optimized stiffener configuration markedly enhances natural frequencies, mitigating vibration-induced instability. This methodological framework provides a systematic basis for designing optimized stiffener layouts in composite combustion liners for aero-engines. Full article

When a helicopter is ground taxiing, the dynamic characteristics of the landing gear wheels change with the taxiing speed, and the rotor generates significant aerodynamic forces. Therefore, the dynamic stability of the rotor/fuselage coupling system when a helicopter is ground taxiing is an aeromechanical stability issue that requires consideration of rotor aerodynamics. In this paper, the aeromechanical dynamic model and analytical method of the rotor/fuselage coupling system in helicopter ground taxiing are presented, including the aerodynamic forces of the rotor blades, the flapping and lagging motions of the blades, as well as the pitching, rolling, and lateral motions of the fuselage. The aeromechanical stabilities of the rotor/fuselage coupling system under different taxiing speeds are calculated. The calculation results show that with the increase in taxiing speed, the frequencies of the lateral and rolling motions of the fuselage decrease and coincide with the frequency of the regressing lag motion of the rotor, causing a decrease in the damping of the rolling motion of the fuselage and a reduction in the aeromechanical stability. When considering the aerodynamic forces, the critical instability taxiing speed increases and the range of instability taxiing speeds decreases compared to when not considering the aerodynamic forces. Full article

The urgent need to mitigate climate change has elevated green hydrogen as a sustainable alternative to fossil fuels, while green cryptocurrencies have emerged to address the environmental concerns of traditional cryptocurrency mining. This study investigates the dynamic correlation between the green hydrogen market and selected green cryptocurrencies (Cardano, Stellar, Hedera, Algorand, and Chia) from July 2021 to April 2024, utilizing the Dynamic Conditional Correlation GARCH (DCC-GARCH) model with robustness checks using EGARCH and GJR-GARCH specifications. Our findings reveal significant correlations, with peaks reaching up to 50% in 2022, a period likely influenced by the Russia-Ukraine conflict. Subsequently, a decline in these correlations was observed in 2023. These results underscore the interconnectedness of sustainability-driven markets, suggesting potential contagion effects during periods of global instability. The high persistence of correlation shocks (α + β values approaching unity) indicates that correlation regimes tend to be long- lasting, with important implications for portfolio diversification and risk management strategies. Robustness checks using EGARCH and GJR-GARCH specifications confirmed qualitatively similar patterns, reinforcing the validity of our findings into the evolving landscape of green finance and energy. Full article

Local thunderstorms are among the major meteorological hazards in the Australian region. These storms inherently have compound impacts, including hail, flash floods, and wind gusts, and consistently cause some of the highest insured losses. Studies on the climate change impact on local storms face the challenges of unreliable storm climatology and uncertainties in the numerical modeling of physical processes. In this study we have adopted an approach to examining the ingredients of severe storm development based on regional climate simulations. We examined two generations of NARCliM datasets (NSW and Australian Regional Climate Modeling). Projected changes in convective indices for the latter half of the twenty-first century indicate an environment more conducive to thunderstorm development, primarily due to enhanced atmospheric instability, despite a concurrent increase in convective inhibition. A measure that combines the dynamic factor of vertical wind shear further shows that the potential storm days will increase substantially, such as a doubling of days with storms during summer, under the influence of climate change over tropical, eastern, and southeastern Australia. The storm season in a year is also expected to elongate. These projections imply increasing thunderstorm-related hazards in the future, including hail, flood, and high winds. Full article

This paper proposes an integrated trajectory tracking strategy for unmanned delivery vehicles operating under complex road geometries and varying adhesion conditions. The method combines adaptive speed regulation informed by road curvature and adhesion with lateral predictive control. A Proportional-Integral-Derivative (PID) controller is utilized for speed regulation to suppress tire force saturation. while the lateral controller adopts model predictive control (MPC) and generates steering commands by solving a quadratic programming (QP) problem with explicit constraints that cover bounds on input magnitude and input rate. Extensive co-simulations using MATLAB/Simulink and Carsim demonstrate that the proposed method outperforms traditional fixed-speed control strategies in both single- and double-lane change scenarios. It achieves superior tracking accuracy and vehicle stability and effectively suppresses sideslip and instability under low adhesion conditions. The results validate the effectiveness of the control strategy, providing key theoretical and practical insights for the safe and reliable operation of unmanned delivery vehicles in complex urban environments. Full article

To address the issue of wellbore instability during drilling in fractured formations, this study systematically investigates the influence mechanisms of fracture geometry and strength parameters on wellbore stability by constructing a multi-weak plane strength criterion and a thermo-hydro-chemical coupling model. Based on Jæger’s single weak plane criterion, a multi-weak plane strength criterion considering the synergistic effects of multiple fracture groups is established. By integrating Boit’s effective stress theory, an analytical solution for the stress field around a wellbore in fractured formations has been derived. A method for calculating collapse pressure and predicting instability zones is also proposed, utilizing the Newton–Raphson iterative algorithm. The results demonstrate that fracture systems markedly alter the anisotropic characteristics of wellbore stress. While the collapse pressure contour in intact formations exhibits bilateral symmetry (25.5–30 MPa), in formations with four fractures, the pressure increases to 29–37 MPa and the symmetry is lost. Furthermore, the instability zone in vertical wells evolves from a “crescent-shaped” pattern in homogeneous formations to a “quadrilateral-shaped” expansion. Notably, the instability area in horizontal wells is significantly smaller than in vertical wells. These outcomes offer theoretical guidance for optimizing the drilling fluid density window and well trajectory design in fractured formations. Full article

Modern power distribution systems are increasingly stressed as they operate closer to their voltage stability limits, driven by growing electricity demand, complex load behaviors, and the evolving structure of power networks. Radial distribution systems, in particular, are highly susceptible to voltage instability under critical loading conditions, where even minor load increases can trigger voltage collapse. Such events threaten the continuity and quality of power supply and can cause damage to infrastructure and sensitive equipment. While large-scale cascading failures are typically associated with transmission systems, localized cascading effects such as sequential voltage drops, feeder outages, and protective device operations can still occur in distribution networks, especially under high loading. Therefore, reliable and timely voltage stability assessment is essential to maintain system reliability and prevent disruptions. This study presents a comprehensive comparative analysis of four voltage stability indices designed for radial distribution networks. The performance of these indices is evaluated on the IEEE 33-bus and 69-bus test systems under various critical loading conditions and multiple static load models, including Constant Power Load (CPL), Constant Current Load (CIL), Constant Impedance Load (CZL), Composite Load (COML), and Exponential Load (EXL). The analysis investigates each index’s effectiveness in identifying voltage collapse points, estimating critical load levels, and calculating load margins, while also evaluating their robustness across diverse operating scenarios. The findings offer practical insights and serve as a valuable benchmark for selecting suitable voltage stability indicators to support monitoring and planning in modern distribution networks. Full article

Federated learning (FL) is a foundational technology for enabling collaborative intelligence in vehicular edge computing (VEC). However, the volatile network topology caused by high vehicle mobility and the profound security risks of model poisoning attacks severely undermine its practical deployment. This paper introduces DTB-FL, a novel framework that synergistically integrates digital twin (DT) and blockchain technologies to establish a secure and efficient learning paradigm. DTB-FL leverages a digital twin to create a real-time virtual replica of the network, enabling a predictive, mobility-aware participant selection strategy that preemptively mitigates network instability. Concurrently, a private blockchain underpins a decentralized trust infrastructure, employing a dynamic reputation system to secure model aggregation and smart contracts to automate fair incentives. Crucially, these components are synergistic: The DT provides a stable cohort of participants, enhancing the accuracy of the blockchain’s reputation assessment, while the blockchain feeds reputation scores back to the DT to refine future selections. Extensive simulations demonstrate that DTB-FL accelerates model convergence by 43% compared to FedAvg and maintains 75% accuracy under poisoning attacks even when 40% of participants are malicious—a scenario where baseline FL methods degrade to below 40% accuracy. The framework also exhibits high resilience to network dynamics, sustaining performance at vehicle speeds up to 120 km/h. DTB-FL provides a comprehensive, cross-layer solution that transforms vehicular FL from a vulnerable theoretical model into a practical, robust, and scalable platform for next-generation intelligent transportation systems. Full article