Search Results (2,252)

The stability of a circular vortex is studied in the thermal quasi-geostrophic (TQG) model. Several radial distributions of vorticity and buoyancy (temperature) are considered for the mean flow. First, the linear stability of these vortices is addressed. The linear problem is solved exactly for a simple flow, and two stability criteria are then derived for general mean flows. Then, the growth rate and most unstable wavenumbers of normal-mode perturbations are computed numerically for Gaussian and cubic exponential vortices, both for elliptical and higher mode perturbations. In TQG, contrary to usual QG, short waves can be linearly unstable on shallow vorticity profiles. Linearly, both stratification and bottom topography (under specific conditions) have a stabilizing role. In a second step, we use a numerical model of the nonlinear TQG equations. With a Gaussian vortex, we show the growth of small-scale perturbations during the vortex instability, as predicted by the linear analysis. In particular, for an unstable vortex with an elliptical perturbation, the final tripolar vortices can have a turbulent peripheral structure, when the ratio of mean buoyancy to mean velocity is large enough. The frontogenetic tendency indicates how small-scale features detach from the vortex core towards its periphery, and thus feed the turbulent peripheral vorticity. We confirm that stratification and topography have a stabilizing influence as shown by the linear theory. Then, by varying the vortex and perturbation characteristics, we classify the various possible nonlinear regimes. The numerical simulations show that the influence of the growing small-scale perturbations is to weaken the peripheral vortices formed by the instability, and by this, to stabilize the whole vortex. A finite radius of deformation and/or bottom topography also stabilize the vortex as predicted by linear theory. An extension of this work to stratified flows is finally recommended. Full article

Background/Objectives: The dual burden of cancer and pain during chemotherapy can negatively impact individuals’ personal integrity, or the “self”. Yet, coping strategies addressing these dual challenges are rarely employed in cancer-related pain management. Recent findings from evidence-based behavioral models, such as psychological flexibility in pain, highlight the potential role of self-as-context (SAC) as a central coping strategy for adjustment. The aim of this study was to examine the network structure of “conventional” coping strategies, such as active coping, behavioral disengagement, substance use, seeking support, religion, humor, and avoidance (Brief-COPE-8 coping strategies), in relation to “self-based” coping strategies. Methods: Individuals diagnosed with cancer, mostly in advanced stages (i.e., II and III), experiencing cancer-related pain (n = 135), completed a cross-sectional online study. Participants filled out self-reported questionnaires, including the Brief-COPE, the Psychological Inflexibility in Pain Scale—Greek Version (G-PIPS-II), and the Self-as-Context Scale (SACS) scale, which included two subfactors: centering and transcending. The study employed a stepwise analysis plan. We first conducted a series of traditional correlations, analysis of variance (ANOVA), and hierarchical multiple linear regressions, to examine the predictive role of demographics/clinical characteristics, psychological inflexibility, and SAC (independent variables) on the eight coping strategies (dependent variables). We then selected the highest predictors of coping in cancer-related pain and included them in a network analysis model. In the network analysis, we estimated the LASSO network regularization and examined network stability. We also assessed the centrality and stability of the network model, focusing on the associations between SAC items, the most predictive coping strategies (Brief-COPE), and psychological inflexibility (G-PIPS-II). Results: SAC correlated positively with effective coping (active coping and humor) and negatively with substance use. There were no correlations between demographics, type, stage of cancer, and coping strategies for pain. Multiple linear regressions identified psychological inflexibility and SAC as the main contributors to pain adjustment, with SAC explaining substantially more variance in active coping. The partial correlation network included 12 nodes. Active coping, centering, and three of the six transcending items were the most influential in the network. Active coping demonstrated the highest centrality, exerting positive links with SAC items that reflected calm reactions and invariant perspective-taking in response to the pain experience. Conclusions: SAC might be considered as a tailored, self-based coping strategy for managing cancer-related pain. Future analog studies should explore the role of integrating self-based perspective-taking strategies to momentarily address cancer-related pain. Full article

Microseismic monitoring technology serves as a vital tool for assessing the stability of coal and rock masses. The precision of energy calculations and the ability to integrate data across different systems have a direct impact on the effectiveness of early warning systems for hazards such as rockburst. This study utilized the 6306 working face of Shandong Energy Group’s Dongtan Coal Mine as its experimental site to address data inconsistencies caused by variations in sensor responses, localization algorithms, and energy calculation methods among microseismic monitoring systems. Two microseismic monitoring platforms, designated as System A and System B, were deployed to conduct a comparative and integrative study of cross-system energy calculations. The optimization of sensor layout facilitated a comprehensive analysis of the differences between the two systems in terms of P-wave arrival times, amplitude–frequency characteristics, and localization accuracy. Results indicated that System A achieved significantly lower localization errors, with an average of 49 m, compared to System B’s average of 70 m. Substantial differences were also found in waveform amplitude and dominant frequency, with a correlation coefficient of only 0.59 between the two systems. To bridge these disparities, an energy calculation method based on the displacement gauge function was developed. By fitting a localized gauge function R(Δ) and incorporating empirical coefficients, the energy calculation outputs of both systems were harmonized. Validation experiments demonstrated that the linear correlation coefficient of energy calculations between Systems A and B increased to 0.977 under the new method, confirming its effectiveness for data unification. This research provides critical theoretical and technical guidance for integrating microseismic data across systems and establishing unified early warning standards, thus advancing the monitoring and prediction of dynamic hazards in mining environments. Full article

The reliability of ocean-going ship engine fuel systems is crucial for the safety and continuous operation of vessels. Failure of this system can lead to serious operational and economic consequences; therefore, effective diagnostics and failure prediction are essential elements of modern fleet management. This paper presents an analysis of the reliability of fuel systems based on operational data from ten bulk carriers operated by Polska Żegluga Morska in Szczecin. The analysis combined classical statistical methods with artificial intelligence algorithms to develop a hybrid diagnostic and forecasting framework. The Weibull lifetime distribution was applied to estimate time-to-failure parameters, revealing mixed failure mechanisms—random failures (k < 1) and aging-related processes (k > 1). Using the k-means algorithm, ships were automatically classified into two reliability groups: high-failure-rate units and stable operational vessels. Individual linear regression models were then developed for each ship to forecast the time to the next failure, achieving satisfactory predictive performance (R² > 0.75 for most vessels). Sensitivity analysis quantified model robustness under different disturbance scenarios, yielding mean Relative Prediction Deviation (RPD) values of approximately 65% for Missing Data, 60% for False Failure, and 26% for Data Noise. These results confirm that the proposed hybrid reliability–AI framework is resistant to random noise but sensitive to incomplete or erroneous historical data. The developed approach provides an interpretable and effective tool for predictive maintenance, supporting reliability management and operational decision-making in marine engine systems. The article presents a hybrid model that has been developed to enable the detailed characterization of emergency processes and the identification of the most important factors that influence damage forecasting. For systems with variable failure risk, it was found that both classical probabilistic models and machine learning methods must be considered to interpret damage patterns correctly. Implementing data filtration and validation procedures before using data in artificial intelligence models has been shown to improve forecast stability and increase the usefulness of forecasts for planning repairs. Full article

Reclaimed coastal areas are highly susceptible to uneven subsidence caused by the consolidation of soft marine deposits, which can induce differential settlement, structural deterioration, and systemic risks to urban infrastructure. Further, engineering activities, such as construction and loadings, exacerbate subsidence, impacting infrastructure stability. Therefore, monitoring the integrity and vulnerability of linear urban infrastructure after construction on reclaimed land is critical for understanding settlement dynamics, ensuring safe and reliable operation and minimizing cascading hazards. Subsequently, in the present study, to monitor deformation of the linear infrastructure constructed over decades-old reclaimed land in Mokpo city, South Korea (where 70% of urban and port infrastructure is built on reclaimed land), we analyzed 79 Sentinel-1A SLC ascending-orbit datasets (2017–2023) using the Persistent Scatterer Interferometry (PSInSAR) technique to quantify vertical land motion (VLM). Results reveal settlement rates ranging from −12.36 to 4.44 mm/year, with an average of −1.50 mm/year across 1869 persistent scatterers located along major roads and railways. To interpret the underlying causes of this deformation, Casagrande plasticity analysis of subsurface materials revealed that deep marine clays beneath the reclaimed zones have low permeability and high compressibility, leading to slow pore-pressure dissipation and prolonged consolidation under sustained loading. This geotechnical behavior accounts for the persistent and spatially variable subsidence observed through PSInSAR. Spatial pattern analysis using Anselin Local Moran’s I further identified statistically significant clusters and outliers of VLM, delineating critical infrastructure segments where concentrated settlement poses heightened risks to transportation stability. A hyperbolic settlement model was also applied to anticipate nonlinear consolidation trends at vulnerable sites, predicting persistent subsidence through 2030. Proxy-based validation, integrating long-term groundwater variations, lithostratigraphy, effective shear-wave velocity (V_s³⁰), and geomorphological conditions, exhibited the reliability of the InSAR-derived deformation fields. The findings highlight that Mokpo’s decades-old reclamation fills remain geotechnically unstable, highlighting the urgent need for proactive monitoring, targeted soil improvement, structural reinforcement, and integrated InSAR-GNSS monitoring frameworks to ensure the structural integrity of road and railway infrastructure and to support sustainable urban development in reclaimed coastal cities worldwide. Full article

This paper presents a systematic approach for rapid assessment of the performance and robustness of linear control systems through geometric analysis in the complex plane. By combining indirect performance indices within a defined zone of desired performance in the complex s-plane, a connection is established with direct performance indices, forming a foundation for the synthesis of control algorithms that ensure root placement within this zone. Analytical relationships between the complex variables s and z are derived, thereby defining an equivalent zone of desired performance for discrete-time systems in the complex z-plane. Methods for verifying digital algorithms with respect to the desired performance zone in the z-plane are presented, along with a visual assessment of robustness through radii describing robust stability and robust performance, representing performance margins under parameter variations. Through parametric modeling of controlled processes and their projections in the complex s- and z-domains, the influence of the discretization method and sampling period, as forms of a priori uncertainty, is analyzed. This paper offers original derivations for MISO systems, facilitating the analysis, explanation, and understanding of the dynamic behavior of real-world controlled processes in both the continuous and discrete-time domains, and is aimed at integration into expert systems supporting control strategy selection. The practical applicability of the proposed methodology is related to discrete control systems in energy, electric drives, and industrial automation, where parametric uncertainty and choice of method and period of discretization significantly affect both robustness and control performance. Full article

The emergence of multidrug-resistant (MDR) Proteus mirabilis poses a significant threat in porcine farming and public health, highlighting the need for alternative biocontrol agents. This study aimed to isolate and characterize a lytic bacteriophage with therapeutic potential against MDR P. mirabilis. Using the clinical MDR P. mirabilis strain Pm 07 as host, a bacteriophage, vB_Pmc_P-07 (P-07), was successfully isolated from fecal and sewage samples via an enrichment protocol. Phage P-07 forms plaques surrounded by a distinct translucent “halo,” suggesting the production of depolymerase. It achieved high titers of up to 1.40 × 10⁸ PFU/mL and exhibited a narrow host range, high stability across a broad range of temperatures (40–60 °C) and pH (4–12), as well as considerable anti-biofilm activity. An optimal multiplicity of infection (MOI) of 0.001 was determined. Whole-genome sequencing revealed a linear double-stranded DNA genome of 58,582 bp with a GC content of 46.91%, encoding 63 open reading frames. Crucially, no virulence or antibiotic resistance genes were detected, supporting its safety profile. Phylogenetic analysis classified P-07 within the Casjensviridae family, closely related to phages PM87 and pPM01. These findings indicate that phage P-07 is a novel, safe, and effective lytic phage with strong potential as a biocontrol agent against biofilm-forming MDR P. mirabilis in swine. Full article

This study evaluated the integration of non-invasive remote sensing and colorimetry to classify the maturity stages of Coffea arabica fruits across four varieties: Caturra Amarillo, Excelencia, Milenio, and Típica. Multispectral signatures were captured using a Parrot Sequoia camera at wavelengths of 550 nm, 660 nm, 735 nm, and 790 nm, while colorimetric parameters L*, a*, and b* were measured with a high-precision colorimeter. We conducted multivariate analyses, including Principal Component Analysis (PCA) and multiple linear regression (MLR), to identify color patterns and develop predictors for fruit maturity. Spectral curve analysis revealed consistent changes related to ripening: a decrease in reflectance in the green band (550 nm), a progressive increase in the red band (660 nm), and relative stability in the RedEdge and near-infrared regions (735–790 nm). Colorimetric analysis confirmed systematic trends, indicating that the a* component (green to red) was the most reliable indicator of ripeness. Additionally, L* (lightness) decreased with maturity, and the b* component (yellowness to blue) showed varying importance depending on the variety. PCA accounted for over 98% of the variability across all varieties, demonstrating that these three parameters effectively characterize maturity. MLR models exhibited strong predictive performance, with adjusted R² values ranging between 0.789 and 0.877. Excelencia achieved the highest predictive accuracy, while Milenio demonstrated the lowest, highlighting varietal differences in pigmentation dynamics. These findings show that combining multispectral imaging, colorimetry, and statistical modeling offers a non-destructive, accessible, and cost-effective method for objectively classifying coffee maturity. Integrating this approach into computer vision or remote sensing systems could enhance harvest planning, reduce variability in specialty coffee lots, and improve competitiveness by ensuring greater consistency in cup quality. Full article

The high-speed maglev train employs linear induction motors for propulsion and incorporates electromagnetic suspension for levitation. Ensuring the stability of the suspension control is imperative for the effective operation of the maglev train at high speeds, necessitating precise calculation of the suspension force. The commonly employed models, while simple in structure, lack the accuracy needed for high-precision suspension control. This paper conducts finite element analysis to simulate the static suspension conditions of high-speed maglev trains and refines the magnetic force calculation model using the obtained data to minimize computational inaccuracies arising from factors like magnetoresistance effects. The revised model is particularly well-suited for scenarios with significant air gaps and elevated currents, showcasing practical value for engineering applications. Full article

Tensegrity structures, by definition composed of compressed members suspended in a network of tensile cables, are characterised by a high strength-to-weight ratio and the ability to undergo reversible deformations. Their application as cores of sandwich panels represents an innovative approach to lightweight design, enabling the regulation of mechanical properties while reducing material consumption. This study presents a finite element modelling procedure that combines analytical determination of prestress using singular value decomposition with implementation in the ABAQUS™ 2019 software. Geometry generation and prestress definitions were automated with Python 3 scripts, while algebraic analysis of individual modules was performed in Wolfram Mathematica. Two models were investigated: M1, composed of four identical modules, and M2, composed of four modules arranged in two mirrored pairs. Model M1 exhibited a linear elastic response with a constant global stiffness of 13.9 kN/mm, stable regardless of the prestress level. Model M2 showed nonlinear hardening behaviour with variable stiffness ranging from 0.135 to 1.1 kN/mm and required prestress to ensure static stability. Eigenvalue analysis confirmed the full stability of M1 and the increase in stability of M2 upon the introduction of prestress. The proposed method enables precise control of prestress distribution, which is crucial for the stability and stiffness of tensegrity structures. The M2 configuration, due to its sensitivity to prestress and variable stiffness, is particularly promising as an adaptive sandwich panel core in morphing structures, adaptive building systems, and deployable constructions. Full article

To address the global plastic crisis, recycled plastics from food packaging were used as road materials by the dry method for practical application research. First, the main components of the recycled plastics were identified based on FTIR, and their thermal stability was evaluated through DSC, TG, and microscopic analysis. Then, the workability of the plastic–asphalt mixture was evaluated using the gyratory compaction indicator, void content, and compaction energy index (CEI). Finally, the effect of reused plastics on the cracking resistance of bituminous mixtures was examined with the Superpave IDT test. The results indicate that recycled plastics from food packaging are polyolefin composite materials, primarily consisting of Low-Density Polyethylene (LDPE), Linear Low-Density Polyethylene (LLDPE), High-Density Polyethylene (HDPE), and Polypropylene (PP), and that their thermal stability meets production requirements. Good compaction performance was observed with plastic content below 2% of the aggregate weight, while higher contents reduced void content due to the space occupied by plastics. When the plastic content increased from 0.5% to 2.0%, creep compliance decreased from 68.4% to 77.87%, while the m-value, tensile strength, and elastic energy maximum decreased by 30.77%, 5.6%, and 7%, respectively. In contrast, the failure strain, fracture energy, and maximum DSCE increased by 25.86%, 87.43%, and 133.05%, respectively. The recycled plastic enhanced the toughness of the asphalt mixture, increasing the dissipated energy during crack propagation and improving its resistance to permanent deformation. Moreover, the plastics hindered crack propagation through a bridging effect, leading to fewer cracks within plastic zones compared with surrounding areas. This study provides actionable guidance for the application of composite plastics in asphalt pavements and supports their sustainable development. Full article

Background: Conflicts are an inevitable part of interpersonal relationships, and personality traits influence how they are resolved. In the nursing work environment, conflicts often arise from poor communication and stress, negatively impacting nurses’ well-being and quality of care. The “Big Five” personality model highlights how traits such as extraversion, agreeableness, and emotional stability shape conflict approaches. Understanding these traits aids in developing effective conflict management strategies. This study investigates intragroup conflicts among nurses by identifying their types and examining how sociodemographic factors and personality traits predict their occurrence. The aim is to provide insights that support targeted interventions and improve team dynamics in nursing practice. Methods: The study was conducted as a cross-sectional analysis within the University Hospital Centre Osijek from March to August 2024, involving nurses and technicians. Data was collected using structured questionnaires with clearly defined inclusion and exclusion criteria. The questionnaire included the Process Conflict Scale, the Big Five Inventory, and a Demographic questionnaire. Appropriate statistical analyses were conducted, including descriptive statistics, normality testing with the Kolmogorov–Smirnov test, non-parametric Spearman and Point-Biserial correlations, and linear regression to examine predictors of intragroup conflicts. All assumptions for regression were met, with significance set at p < 0.05, and analyses were performed using JASP software version 0.17.2.1. Results: The research reveals significant differences among various types of team conflicts, where personality traits such as neuroticism increase, while conscientiousness decreases conflicts. The professional competence of respondents also positively correlates with logistical conflicts, and personality explains the variance in conflicts among nurses. Conclusions: Intragroup conflicts among nurses, particularly task-related, stem from communication issues and high care standards. Neuroticism negatively affects team dynamics, while conscientiousness can reduce conflicts but may also lead to disagreements if expectations are unmet. Education on conflict management and clearly defined roles can improve teamwork and quality of care. Full article

A decentralized control problem for vehicular platoon systems with heterogeneous dynamic behaviors is investigated in this paper. To simplify the controller design, a longitudinal model is established as an interconnected form. On this basis, a series of decentralized state feedback controllers are designed to ensure the individual stability, string stability and connective stability of the vehicular platoon system. Then, a new scenario in which additional vehicles are added to the platoon is also considered by developing an expanding construction system (ECS) based on the proposed longitudinal model. As a result, a corresponding controller can be designed as a new one of the decentralized controllers without changing the original control laws of the interconnected system. The stability conditions are presented with rigorous analysis by virtue of linear matrix inequality (LMI) for the interconnected system and the ECS. Simulation results are carried out to demonstrate the effectiveness of the proposed decentralized tracking controllers. Full article

Given the environmental hazards of 2,4,6-trinitrophenol (TNP) and the limitations of existing detection methods, sodium-doped fluorescent carbon dots (Na-CDs) were successfully synthesized via a one-step hydrothermal method using citric acid and ascorbic acid as carbon sources. Compared with undoped carbon quantum dots, Na-CDs exhibited nearly identical surface functional groups but significantly enhanced fluorescence stability and markedly improved selective responsiveness toward TNP. Accordingly, a Na-CD-based fluorescent probe was developed for the highly selective detection of TNP. Results demonstrated a good linear relationship between the relative fluorescence intensity change (F₀ − F)/F₀ and TNP concentration ranging from 7 × 10⁻⁷ to 2 × 10⁻⁵ mol/L, with a detection limit of 3.5 × 10⁻⁸ mol/L. When applied to detect TNP in local river water samples, the method achieved recoveries of 95.40–104.0%, confirming its reliability for real-world environmental sample analysis. This study develops a novel, sensitive, and highly selective approach for monitoring TNP in environmental systems. Full article

The vertical tail plays a crucial role in aircraft directional stability and lateral control, especially during low-speed operations such as takeoff and landing. This study examines the effect of aircraft mass on vertical tail geometry through a statistical analysis of 65 design parameters from civil jet aircraft. Aerodynamic performance of a sub-scale Boeing 777-200 vertical tail model was further investigated in a low-speed wind tunnel under rudder deflections and sideslip angles. Experiments were conducted at freestream speeds of 20 and 30 m/s, corresponding to Reynolds numbers of 5 × 10⁵ and 7.5 × 10⁵, with model blockage ratios below 2% in all configurations. Side force and drag coefficients were measured for rudder deflections from −30° to +30° and sideslip angles from −7.5° to +7.5°. Results show a nearly linear variation of side force with rudder deflection, while drag exhibits noticeable nonlinearity at higher deflections. At zero sideslip, increasing rudder deflection from 0° to 30° raised the side force coefficient from 0 to 0.65, with a maximum uncertainty of ±0.011, while drag coefficient uncertainty remained below ±0.0055. Furthermore, the application of positive or negative sideslip resulted in substantial variations in the side force coefficient, reaching values of up to ±1.1 depending on the direction. By integrating experimental data with statistical analysis of real aircraft geometries, this study provides reliable quantitative benchmarks and highlights the vertical tail’s aerodynamic importance. Full article