Search Results (9,299)

Adolescence is a key period of significant physiological and social development, during which social anxiety symptoms often emerge and can impact academic and social functioning. Social anxiety disorder (SAD) involves heightened sensitivity to social cues and impaired social information processing, potentially contributing to persistent anxiety symptoms. However, research exploring the neural mechanisms of social information processing in adolescents with social anxiety remains limited. The investigation employed a facial dot-probe paradigm combined with EEG measurements to assess differences in attentional processing and neurophysiological activity between two adolescent groups: a high-social-anxiety (HSA) group (N = 27) and a low-social-anxiety (LSA) group (N = 18). Results showed (1) there was a significant reduction in P2 amplitudes in the HSA group compared to the LSA group. (2) A significant negative correlation between the disengagement index (DI) and P2 amplitude was found. (3) Weaker functional connectivity in the theta band was found in the HSA group. (4) In the graph theory analysis, the HSA group exhibited significantly higher node efficiency across various frequency bands compared to the LSA group. The findings suggest that socially anxious adolescents have impaired attentional control toward social cues. This difficulty may reinforce their anxiety symptoms over time. Full article

In this work, an adaptive event-triggered-based consensus control strategy is proposed for the quadrotor unmanned aerial vehicle (QUAV) formation system in the presence of external disturbances and state constraints. Firstly, the disturbed QUAV formation system dynamic model is established. Then, to address the initial peaking explosion problem in the traditional active disturbance rejection control method, a time-varying gain extended state observer (TGESO) is designed to suppress external disturbances. Meanwhile, a novel barrier Lyapunov function (BLF) is constructed to cope with the adverse effects caused by state constraints. Furthermore, aiming to alleviate network congestion and reduce communication burden, the adaptive event-triggered mechanism (AETM) is adopted to design the formation flight controller. Finally, the stability of the developed consensus controller and the boundedness of all error signals are proved via Lyapunov theory. Comparative simulation results demonstrate the practicality of the presented control algorithm. Full article

Five-axis Computerized Numerical Control (CNC) machine tools play a pivotal role in the precision manufacturing of aeroengine turbine blades, where ultra-high reliability and accuracy are essential. Failure Mode, Effects and Criticality Analysis (FMECA) has been widely applied in the reliability assessment of such advanced machining systems due to its systematic evaluation of potential failure modes. However, traditional FMECA approaches often overlook the ambiguity of human cognition and the interdependence among expert evaluations, limiting their effectiveness in complex aerospace manufacturing environments. To address these issues, this paper proposes a novel FMECA framework based on generalized intuitionistic linguistic theory. A new Generalized Intuitionistic Linguistic Weighted Geometric Average (GILWGA) operator is introduced to couple multi-source expert information and quantify the fuzziness inherent in subjective assessments. Additionally, an intuitionistic linguistic entropy-based weighting scheme is developed to dynamically evaluate key risk factors, including severity, occurrence, detectability, and controllability. The proposed framework is applied to a case study involving the spindle system of a five-axis CNC machine tool used in aeroengine blade production. The results demonstrate that the proposed method offers more robust and consistent failure mode prioritization, providing effective decision support for reliability-centered maintenance in aerospace equipment manufacturing. Full article

In this work, iron–phosphorus-based composite biochar (FPBC) was prepared by modification with the leachate of spent LiFePO₄ batteries. The effects of solution pH, dosage, adsorption time, initial concentration, and temperature on the adsorption performance of FPBC were investigated by batch adsorption experiments with Pb(II) and Sb(III) as the target pollutants, and the adsorption mechanism was explored using SEM, BET, XPS, FTIR and XRD characterization. The results indicated that as the initial pH of the solution increased, the removal efficiency of FPBC for Pb(II) gradually increased, while the removal efficiency for Sb(III) remained largely unchanged. The removal of Pb(II) and Sb(III) by FPBC fitted the pseudo-second-order kinetic model and the three-step intraparticle diffusion model, indicating that their removal was primarily controlled by chemical adsorption. Isothermal adsorption studies revealed that FPBC adsorption of Pb(II) better fitted the Langmuir and D-R models, suggesting a monolayer-dominated adsorption process. In contrast, adsorption of Sb(III) fitted the Langmuir, Freundlich, and Temkin models, suggesting a combination of monolayer and multilayer adsorption characteristics. The maximum adsorption capacities of FPBC for Pb(II) and Sb(III) were 312.54 mg·g⁻¹ and 219.20 mg·g⁻¹ at 30 °C, which were approximately 12.85 and 3.37 times those of commercial corn stalk biochar (BC). Thermodynamic analysis confirmed that the removal of Pb(II) and Sb(III) by FPBC was a spontaneous and endothermic process. In addition, FPBC demonstrated strong selective adsorption of Pb(II) in the binary co-adsorption system of Pb(II) and Sb(III). Mechanism studies indicated that Pb(II) removal primarily occurred through co-precipitation, complexation, ion exchange, and electrostatic adsorption, while Sb(III) was mainly adsorbed by FPBC via redox reactions and complexation. Therefore, this work not only provides a low-cost, high-performance adsorbent for the remediation of water contaminated with Pb(II) and Sb(III), but also opens up new avenues for the resource recovery of the leachate of spent LiFePO₄ batteries. Full article

The complex architecture and stacking patterns of deepwater turbidite channel sandbodies introduce significant uncertainty in injector–producer connectivity. This uncertainty affects both the mechanisms and the quantitative evaluation of the waterflood sweep. In this study, a representative reservoir in the Niger Delta Basin is selected as a case study. Injector–producer well groups are first classified into three connectivity patterns—coeval, cross-stage, and hybrid based on geological and seismic constraints. Time-lapse seismic data are then interpreted to delineate sweep morphology and to infer the controlling mechanisms associated with each pattern. Coeval connectivity exhibits a relatively uniform and continuous front advance with minimal barriers. Cross-stage connectivity shows fragmented swept regions with pronounced bypassing, and localized preferential breakthrough caused by discontinuous sandbodies and pervasive barriers. Hybrid connectivity is characterized by intermediate behavior, combining features of both patterns. To translate these mechanistic differences into quantitative metrics for development evaluation, an oil–water relative permeability ratio correlation for low viscosity oil is established that remains valid across the full water cut range, thereby overcoming the limitations of conventional semi-log linear correlations at both low and ultra-high water cut stages. Based on this framework, a production data-driven predictive model for waterflood sweep efficiency is derived using production data and steady state flow theory. The model is validated across well groups representing different connectivity patterns. Field application yields a consistent ranking of sweep efficiency: coeval > hybrid > cross-stage, with group average values of 0.86, 0.80, and 0.70, respectively. These results agree with the mechanistic interpretation derived from time-lapse seismic analysis. The proposed methodology provides a practical quantitative framework for evaluating injector–producer connectivity and comparing development strategies in deepwater turbidite channel reservoirs. Full article

A piezoelectric actuator (PEA) is a fundamental part of a high-precision motion system, yet its performance is critically constrained by inherent nonlinearities such as the velocity dead zone and hysteresis. To overcome these limitations and the associated time-varying dynamics, this study introduces a novel control framework for a dual-mode standing wave PEA. The framework integrates a Global Linearized Sparse Prediction (GLSP) model with an Adaptive Kalman Observer-based Model Predictive Control (AKOBMPC) strategy, specifically designed for velocity dead-zone compensation. The GLSP model employs Koopman operator theory to lift the complex, nonlinear electromechanical and contact dynamics into a linear invariant subspace. Incorporated with a deep learning-based structured pruning mechanism, the model achieves an effective balance between prediction accuracy and computational efficiency, facilitating real-time implementation. Leveraging this high-fidelity model, the AKOBMPC algorithm is developed to estimate unmeasurable disturbances and optimize the control sequence for precise velocity tracking. Experimental results demonstrate the GLSP model’s accurate prediction of system behavior under varying loads and excitation frequencies. The proposed controller effectively suppresses the velocity dead zone, achieving tracking errors within ±0.35 mm/s for a 40.00 mm/s trapezoidal reference and within ±0.50 mm/s for sinusoidal tracking. These results confirm the superior performance of the AKOBMPC scheme over conventional methods, offering a robust solution for high-precision velocity regulation in PEA system and contributing to the advancement of next-generation precision actuator. Full article

This paper presents an integrated mathematical model to improve the safety and operational efficiency of train traffic in centralised railway dispatching systems. The proposed approach combines the alternative graph model with a Mealy automaton to synchronously address route planning, delay minimisation, and strict compliance with safety requirements. Formal control theory based on finite-state automata is employed to describe routing logic and signal control through state transitions, while the alternative graph model represents scheduling constraints and resource conflicts. To enhance real-time adaptability, a tabu search algorithm is implemented for train schedule optimisation, enabling dynamic rescheduling under changing operational conditions. The mathematical formulation incorporates blocking time parameters, a system of discrete constraints, and automaton-based safety conditions governing train movements and route authorisation. The integrated model explicitly formalises the processes of block section occupation and release, ensuring consistency between control logic and scheduling decisions. Practical testing and computational experiments demonstrate that the proposed approach effectively reduces train delays, improves the reliability of dispatch control, and increases system resilience to dynamic disturbances. The results confirm that the developed model can be implemented within existing centralised dispatching infrastructures without requiring a complete system overhaul. Overall, the proposed framework expands the functional capabilities of centralised dispatch systems by enabling efficient schedule generation, minimising the propagation of delays, and ensuring reliable command exchange between central control posts and field-level railway infrastructure. Full article

This study addresses a critical gap in the operationalization of sustainability frameworks at the project level by developing and validating an empirically grounded measurement instrument for assessing Environmental, Social, and Governance (ESG) compliance in manufacturing industry projects. While the United Nations Sustainable Development Goals (SDGs) articulate sustainability aspirations at the national and global level, and ESG frameworks capture organizational-level sustainability performance, no validated instrument exists for measuring ESG integration at the project level where sustainability commitments are ultimately operationalized. Drawing on the theoretical foundations of sustainable project management, stakeholder theory, and the ESG governance literature, the authors developed a 30-item survey instrument capturing six conceptual dimensions of ESG-aligned project performance. Data were collected from 2231 project sponsors and decision-makers in North American goods manufacturing firms classified under NAICS codes 31–33, which collectively encompass the entire manufacturing sector in North America. Through a sequential analytical approach employing principal component analysis (PCA) for initial item reduction, exploratory factor analysis (EFA) for dimensionality assessment, and structural equation modelling (SEM) for confirmatory validation, a parsimonious two-factor model emerged with excellent fit indices (CFI = 0.99, TLI = 0.98, RMSEA = 0.052, SRMR < 0.035). The first factor captures ESG planning activities undertaken during project initiation and planning phases, while the second factor represents ESG monitoring and controlling functions during project execution. The reduction from six theoretical dimensions to two empirical factors reflects lifecycle governance theory, where planning-phase governance and execution-phase control emerge as functionally distinct but correlated constructs. The validated instrument offers practical utility for project managers, organizational sustainability officers, and policy-makers seeking standardized benchmarks for ESG compliance at the operational project level. The validated instrument and complete survey are shared for replication and testing across different industries and countries. Full article

Objectives: This study investigated whether vegetarian and non-vegetarian university students exhibit distinct responses to questionnaires assessing symptoms of eating disorders and inflexibility to change. Methods: Participants completed a demographic questionnaire, the Disordered Eating Attitudes Scale, and the Behavioral Inflexibility Scale. Data were analyzed using descriptive and inferential statistics, including relative risk (RR), 95% confidence intervals (95% CI), and p-values. Results: Results indicated that vegetarian students presented a higher risk of disturbed eating attitudes compared to omnivores (RR = 1.17; 95% CI = 0.53–2.54; p = 0.69), though this difference was not statistically significant. In contrast, female students presented a significantly higher risk of disturbed eating attitudes than male students (RR = 2.72; 95% CI = 1.07–6.8; p = 0.02). No statistically significant differences were observed for race/ethnicity, or field of study in relation to disturbed eating attitudes. Regarding behavioral inflexibility, no significant differences were found between vegetarians and omnivores (RR = 1.74; 95% CI = 0.60–4.98; p = 0.29) or between female and male students (RR = 1.16; 95% CI = 0.42–3.33; p = 0.78). Conclusions: Additionally, participants characterized by higher behavioral inflexibility tended to exhibit more disturbed eating attitudes, highlighting the association between behavioral rigidity and eating-related patterns. The results are analyzed according to the TJC. Full article

Microcline is an important rock-forming mineral in the Earth’s crust, and characterizing its structural behavior under compression is essential for understanding the high-pressure response of feldspar minerals under geological conditions. In this study, the crystal structural evolution of microcline up to 12 GPa was investigated using first-principles calculations based on density functional theory. The results reveal an isosymmetric phase transition at approximately 6–7 GPa, accompanied by a ~7% volume collapse. Across this transition, the b-axis and unit-cell angles (α, β, γ) change abruptly, and the aluminum coordination transforms from fourfold to a distorted fivefold geometry intermediate between a trigonal bipyramid and a square pyramid. Analysis of bond lengths and angles indicates that compression in the low-pressure phase is primarily driven by shear deformation of tetrahedral Ring 1. Near the transition pressure, however, marked shear deformations of Ring 2 and Ring 3 induce a strong contraction of the b-axis and abrupt changes in the unit-cell angles. Comparison with the compression behavior of low albite reveals both similarities and distinct structural responses, highlighting the role of framework topology and extra-framework cations in controlling pressure-induced structural evolution in feldspar minerals. These results provide new insights into the high-pressure behavior of microcline and contribute to a better understanding of the structural stability of feldspar minerals in the Earth’s interior. Full article

In this study, we examine the effectiveness of combining interleukin-2 (IL-2) with highly active antiretroviral therapy (HAART) in controlling HIV replication. A mathematical model of the immune system is developed to analyze immune recovery when IL-2 is administered alongside HAART. We investigate the stability of the endemic equilibrium and Hopf bifurcation and determine the direction and stability of periodic solutions using center manifold theory. Numerical simulations are conducted to support the theoretical findings. The results show that the disease-free equilibrium is stable when the basic reproduction number $R_0<1$, while the endemic equilibrium exists when $R_0>1$. Our results also reveal the presence of a subcritical Hopf bifurcation in the system. An optimal control problem is also studied, showing that the combined therapy of IL-2 and HAART improves treatment outcomes, reduces side effects, and has a unique optimal control pair. Sensitivity analysis further highlights the importance of system parameters in influencing treatment effectiveness. Full article

Rapid housing expansion exacerbates the urban heat island (UHI) effect, yet the influence of household-level awareness on sustainable housing decisions remains underexplored, particularly in tropical contexts. This study integrates the Theory of Planned Behavior (TPB) into a moderated-mediation model to examine how UHI awareness shapes the relationships among attitude, subjective norms, perceived behavioral control, socioeconomic factors, purchase intention, and willingness to pay (WTP) for heat-mitigating housing. Survey data from 441 homebuyers in Bandung City, Indonesia, were analyzed using partial least squares structural equation modeling (SEM). Results reveal that awareness fundamentally alters decision pathways: without awareness, subjective norms (β = 0.066, p-value = 0.007) and perceived behavioral control (β = 0.050, p-value = 0.005) significantly influence WTP via purchase intention; with high awareness, attitude becomes the sole significant predictor (β = 0.109, p-value = 0.035), while the effects of social pressure (β = −0.015, p-value = 0.130) and perceived control (β = −0.005, p-value = 0.376) diminish. The model explains 50.1% of the variance in purchase intention (R² = 0.501) but only 14.7% of the variance in WTP (R² = 0.147), reflecting the low-price premiums respondents are willing to pay (0–5%). These findings highlight that climate-specific awareness acts as a cognitive filter, guiding pro-environmental housing choices, and underscore the importance of awareness-driven interventions for promoting sustainable urban development in tropical cities. Full article

This paper presents a comprehensive framework for the identification, state estimation, and robust control of a bistable Duffing–Holmes oscillator, validated through an experimental setup. First, to address parametric uncertainty, a Recursive Least Squares Method (RLSM) with a forgetting factor is applied to a filtered model representation, enabling accurate parameter convergence from noisy measurements. Subsequently, a Nonlinear Integral Extended State Observer (NIESO) is designed to reconstruct unmeasured states and estimate total disturbances. A key theoretical contribution is the derivation of explicit gain conditions that guarantee the observer’s stability, overcoming limitations of previous designs. For trajectory tracking, an observer-based backstepping controller is synthesized. Crucially, to bridge the gap between theory and practice, a drift-free integration scheme is implemented to generate feasible position commands for the shake table, preventing actuator saturation. Experimental results confirm the framework’s effectiveness, achieving a 3.7-fold reduction in RMS tracking error compared to open-loop operation, with the tracking error rapidly converging to a small neighborhood within approximately $0.2$ $\mathrm{s}$. Furthermore, the closed-loop system demonstrates superior energy efficiency, requiring significantly lower actuator voltage to sustain stable interwell oscillations. Full article

Background: Understanding the drivers of sustained volunteering among university students is crucial, as their continued participation yields significant individual and societal benefits. However, a notable decline in participation underscores the need to investigate the factors that underpin and sustain volunteering motivation. Methods: Using snowball sampling, 15 university students with volunteer experience were recruited for semi-structured interviews. A thematic analysis, guided by the Ecological Systems Theory (EST), was performed, with the mesosystem excluded from the analytical framework due to its indirect and less observable nature in participants’ self-reports. Results: Based on the interview responses, we identified 15 themes across the four systems (microsystem, exosystem, macrosystem, and chronosystem) influencing university students’ participation in volunteering. We further explored the restrictive factors that hinder their participation. To advance the analysis, we introduced a controllability framework (“controllable, partially controllable, minimally controllable”) as an analytical lens. This framework emphasizes that while behaviors are shaped by various factors, behavior change can be most effectively promoted by focusing intervention efforts on those within the immediate control of the individual or relevant actors. Implications: This study demonstrates the EST’s applicability to university students’ volunteering research and provides practical insights for the design of volunteer programs. Full article

Background: Theoretical frameworks are essential for understanding and predicting medication adherence behaviours. The Theory of Planned Behaviour (TPB) posits that behavioural intentions, shaped by attitudes, subjective norms, and perceived behavioural control, are the proximal determinants of behaviour. This cross-sectional study examined associations between TPB constructs and antiplatelet medication adherence among Saudi patients following percutaneous coronary intervention (PCI). Methods: A cross-sectional survey was conducted among 236 Saudi adults post-PCI at two tertiary cardiac centres in Riyadh. TPB constructs (attitude, subjective norms, perceived behavioural control, intention) were assessed using a validated questionnaire. Adherence was measured via the Morisky Medication Adherence Scale-8 (MMAS-8). Hierarchical multiple regression examined associations between TPB constructs and adherence, controlling for demographic and clinical variables. Results: The results demonstrated significant associations with adherence. In the final regression model, intention (β = 0.273, p < 0.001), perceived behavioural control (β = 0.189, p = 0.007), and subjective norms (β = 0.142, p = 0.038) were significantly associated with adherence. Attitude was not significantly associated (β = 0.087, p = 0.194). The TPB constructs explained an additional 18.7% of variance in adherence beyond demographic and clinical factors. Conclusions: The TPB provides a useful framework for understanding antiplatelet adherence patterns in Saudi post-PCI patients. These findings suggest that interventions addressing behavioural intentions, perceived control over medication-taking, and normative influences from significant others may potentially enhance adherence outcomes. Theory-informed nurse-led interventions incorporating strategies such as implementation intentions and family involvement are recommended. Full article