ABSTRACT This paper introduces the concept of fundamental phase shift to provide a unified phase-shift control strategy description for power converters. It aims to simplify system control, reduce backflow power and improve operational efficiency. A Fourier-based Optimal Modulation Strategy (FOMS) is developed by decomposing transmitted active and reactive power for Dual-Active Bridge (DAB) converters. The unified mathematical model is applicable to Single Phase Shift (SPS), Extended Phase Shift (EPS), Dual Phase Shift (DPS) and Triple Phase Shift (TPS) modulation schemes. Theoretical analysis and simulation results indicate that under FOMS control, circulating harmonic components during constant active-power transmission are eliminated, significantly reducing the RMS value of inductor current. This RMS reduction diminishes backflow, thereby increasing overall converter efficiency. In all four modulation schemes and operating modes, backflow power is markedly reduced, and the system efficiency under the proposed FOMS can reach up to 95%. The proposed method simplifies implementation across different modulation strategies, offering a practical and efficient solution for power-electronics engineering. This study delivers valuable insights for optimising DAB converters and contributes to the progress of electric energy conversion technologies.

In this work, the time fractional mixed diffusion-wave equation on an unbounded domain with initial weak singularity is solved numerically. The equation is first transformed into equivalent integral-differential equation. Then we propose a fully discrete scheme based upon Laguerre Galerkin-spectral method in spatial direction and finite difference method on graded meshes in temporal direction. The unconditional stability of the proposed scheme is given. Moreover, the convergence under the regularity of the solution is proved. Numerical results are given to support the theoretical analysis.

Development of efficient and durable oxygen reduction reaction (ORR) electrocatalysts is of great interest yet remains challenging. Herein, we predicted and screened a bilayer graphite carbon-supported Ir-N4/Fe-N4 catalyst with high ORR activity using density functional theory calculations. Subsequently, various bimetallic single atom supported on 3D ordered macroporous carbon were rationally designed and experimentally synthesized via a colloidal microsphere template-confined reaction method. As anticipated, the resulting Ir-N4/Fe-N4 bimetallic single-atom catalysts (IrFe-SACs) exhibit superior ORR activity and durability, reaching a half-wave potential of 0.928V. The IrFe-SACs also demonstrate outstanding performance in Zn-air batteries, including a high discharge power density (314mW cm⁻2) and excellent cycling stability (~ 1650 cycles over 550h). Further experimental characterizations and theoretical analysis reveal that introducing interlayer-adjacent Ir-N4 sites facilitates the transition of Fe-N4 from a low-spin state to a medium-spin state, which optimizes the spin polarization of Fe 3d orbitals and enhances the non-localization of the Fe-O/OH molecular orbital, thereby significantly improving the ORR intrinsic activity and durability of atomic Fe-N4 sites.

The article addresses the issue of emotional burnout in sports activity as a systemic psychophysiological state, determined by the interaction between external demands of the sports environment and stable individual psychological characteristics of the athlete. A theoretical analysis of contemporary research demonstrates a high prevalence of the syndrome (45-65% among professionals), highlighting the importance of identifying predisposing factors for vulnerability. The aim of the study is to systematize the individual psychological features that determine the development and manifestation specifics of emotional burnout in athletes. Based on an analysis of key theoretical models (K. Maslach, K. Cherniss, A. Pines) and the identified main personal predispositions to burnout—dysfunctional perfectionism, high neuroticism, external locus of control, and dominance of external motivation—the study emphasizes the particularities of burnout manifestations across different sports (individual, team, combat sports). This underscores the need for a differentiated approach to diagnosis. The results of the analysis confirm that individual psychological characteristics are significant prerequisites for burnout.

To address performance degradation and control instability in electro-hydraulic servo active suspension systems due to internal leakage faults arising from wear and aging of hydraulic components, this paper proposes an innovative fuzzy PID fault-tolerant controller based on the Improved Giant Armadillo Optimization (IGAO) algorithm. Specifically, to overcome the limitations of the standard Giant Armadillo Optimization (GAO), which is prone to local optima and exhibits poor convergence performance when handling multi-constraint parameter optimization problems, this study introduces a nonlinear dynamic inertia weight mechanism and a random reflection strategy for out-of-bounds particles to improve the original algorithm’s performance. These enhancements significantly enhance its ability to balance global exploration and local exploitation. Furthermore, this research develops a comprehensive performance evaluation fitness function by quantifying key performance indicators such as body acceleration, suspension dynamic deflection, and tire dynamic load. A quarter-car model incorporating an internal leakage fault was established as a simulation validation platform to demonstrate the reliability of the proposed method. Simulation results indicate that under various road excitation conditions, the proposed IGAO algorithm can rapidly and stably converge to superior parameters for the fuzzy PID controller. Compared to the Particle Swarm Optimization (PSO) and standard GAO algorithm, the control system optimized by IGAO not only significantly more effectively suppresses body vibration and reduces shock amplitude but also exhibits stronger dynamic recovery performance and control robustness under varying degrees of internal leakage faults. This research provides a robust control approach for addressing internal parameter uncertainties in hydraulic systems and offers a new approach to theoretical modeling for enhancing the reliability of design and fault-tolerant control capabilities of active suspension systems.

Against the strategic backdrop of comprehensively advancing rural revitalization, the revitalization of rural culture is in urgent need of a paradigm shift from external "blood transfusion-style" supply to internal "hematopoiesis-style" development. The current practical model dominated by one-way "cultural delivery" often leads to the disconnection between the inheritance of red culture and the fabric of rural life, making it difficult to effectively stimulate endogenous motivation. This study aims to propose and demonstrate "red aesthetic education" as a key enabling path to achieve this transformation. It is argued that red aesthetic education is not a simple artistic education activity, but a comprehensive social practice integrating value guidance, emotional activation and subject creation. Through theoretical deduction, this paper constructs a trinity theoretical analysis framework of "Value Identity-Subject Empowerment-Space Production", and systematically explains how red aesthetic education drives the endogenous development of rural culture through three practical mechanisms: emotional activation and memory reconstruction, knowledge production and skill inheritance, and social connection and capital appreciation. The results show that red aesthetic education can effectively promote the in-depth integration of red genes and local values, reshape the subjectivity of rural culture, and activate rural public cultural spaces. Thus, it provides a solution with both theoretical depth and practical operability for breaking the predicament of "cultural alienation" and cultivating sustainable endogenous development capacity. This study offers a new theoretical perspective and practical path for the creative transformation of red cultural resources and the revitalization of rural culture in the new era.

Curriculum evaluation is a systematic process used to assess the effectiveness, relevance, and achievement of educational objectives through analysis of all components of the curriculum, from planning and implementation to learning outcomes. This article comprehensively discusses various curriculum evaluation models used in modern education systems, including research models, goal-oriented models, goal-free models, multivariate mixed models, EPIC models, and CIPP models. Each model is analyzed based on its characteristics, approach, and contribution in providing a comprehensive overview of curriculum quality. Evaluation not only serves as a tool to determine the success rate of a program, but also as a basis for accountability, continuous improvement, and strategic decision-making in curriculum development. In addition to describing various evaluation models, this article also highlights the importance of the competence of evaluators, both internal and external, who have theoretical understanding, accuracy, objectivity, and professional skills in conducting evaluations. The results of the study show that the use of an appropriate evaluation model greatly influences the accuracy of the findings and recommendations produced, thereby improving the quality of learning and ensuring that the curriculum remains adaptive to developments in science and the needs of students. Thus, curriculum evaluation is an important instrument in maintaining the quality of education and supporting the effective and sustainable achievement of national education goals.

A recently proposed scheme utilizing local noise addition and matrix masking enables data collection while protecting individual privacy from all parties, including the central data manager. Statistical analysis of such privacy-preserved data is particularly challenging for nonlinear models like logistic regression. By leveraging a relationship between logistic regression and linear regression estimators, we propose the first valid statistical analysis method for logistic regression under this setting. Theoretical analysis of the proposed estimator confirmed its validity under an asymptotic framework with large noise variances to account for strict privacy requirements. Simulations and real data analyses demonstrate the superiority of the proposed estimators over naive logistic regression methods on privacy-preserved datasets.

Shear-driven drop motion is a common phenomenon with critical implications for applications such as aircraft anti-icing, where efficient drop detachment is essential to reduce water retention, limit freezing, and suppress subsequent ice accumulation. While tangential air shear is typically associated with in-plane drop motion, it has not been considered effective for inducing detachment. Here, combining experiments, simulations, and theoretical analysis, we demonstrate that off-plane drop detachment can occur under specific conditions determined by surface wettability, drop radius, and wind speed. Notably, we identify a distinct scaling regime for the critical wind speed required for detachment as a function of drop radius, determined by the balance between lift and restoring force. Our findings advance the fundamental understanding of drop–airflow interactions and offer inspiring design strategies for efficient drop removal.

This article investigates the educational conditions under which unconscious psychological determinants contribute to the creative development of personality. The study is grounded in an integrative methodological framework combining cultural-historical, subject-oriented, contextual, and non-classical psychological approaches. Through theoretical analysis, it develops a structural-conceptual model that links educational environments with the dynamics between consciousness and the unconscious, focusing on how these interactions influence the learner’s personal and creative growth. The research identifies the psychological mechanism of self-awareness as central to the learner’s transition from an object of instruction to a subject of educational activity. The internalization of educational experiences activates unconscious predictors—such as archetypes, fixed attitudes, and emotional-cognitive functions—which shape the "I"-image and determine creative initiative. The educational process, viewed as a culturally mediated system, serves as a developmental space where learners gradually integrate unconscious content into conscious self-construction. Education, when oriented toward the development of the whole personality, must address not only rational-cognitive skills but also the symbolic, emotional, and unconscious layers of the learner’s psyche. Pedagogical strategies that promote self-reflection, symbolic engagement, and archetypal awareness can significantly enhance students’ creative potential. The study proposes a shift in educational practice—from content transmission to facilitating inner psychological development—as a foundation for fostering creative, self-determined individuals.

The spin Hall effect in a heavy metal intercorrelates an AC electric current to the magnetization dynamics in an adjacent ferromagnet, which manifests as an electric reactance in the system's current–voltage response. We present a comprehensive theoretical analysis for this emergent reactance contribution in the frequency regime relevant to transport measurements up to a few GHz. Our analysis reveals that the reactance becomes inductor-like at low frequency below the ferromagnetic resonance. Crucially, we find that the sign of the reactance is directly governed by the spin transfer mechanism at the interface, which depends on the competition between its damping-like and field-like components parametrized by the spin mixing conductance. This characteristic behavior in the reactance offers a powerful transport observable in distinguishing the interfacial spin transfer processes in spintronic materials.

ABSTRACT This study systematically investigates the effects of fluorinated graphite (FG) on 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (HMX) through an integrated approach combining theoretical calculations and experimental validation. Static theoretical analyses, encompassing frontier orbital theory, electrostatic potential mapping, interaction region analysis, and bond order calculations, were conducted. These analyses collectively revealed that fluorinated graphite enhances the reactivity of HMX while concurrently preserving its intrinsic safety profile. This theoretical finding was further substantiated by vacuum gas evolution tests, which confirmed the absence of any detrimental impact on HMX’s safety characteristics. Furthermore, thermal molecular dynamics simulations provided insights into the modulation of HMX thermal decomposition by FG with varying fluorination degrees. The simulations indicated a distinct mechanistic difference: low-fluorination-degree FG primarily promotes decomposition through the dissociation of its participating fluorine atoms, while high-fluorination-degree FG acts as a direct catalyst for the decomposition process. In parallel, experimental techniques including Differential Scanning Calorimetry (DSC), combustion pressure tests, and combustion residue characterization were employed. The results from these experiments consistently and conclusively verified the combustion-promoting effects of fluorinated graphite on HMX. Therefore, this comprehensive work lays a solid theoretical and experimental foundation for the potential application of fluorinated graphite in solid propellant formulations.

Transformation behaviors of polybrominated diphenyl ethers (PBDEs) in electronic waste during thermal dismantling processes: Effect mechanisms of coexisting metals.

The concept of mental disorder remains one of the most philosophically complex and clinically significant constructs in psychiatry. Although international classification systems such as ICD-11 and DSM-5-TR provide operational definitions, fundamental conceptual ambiguities persist regarding the distinction between pathology, cultural variation, and socially deviant behavior. In Japan, where psychiatric practice primarily follows the ICD system and cultural context plays a central role in shaping normative expectations, definitional clarity is particularly important. This article develops a strengthened conceptual framework grounded in three interdependent criteria: culturally contextualized deviation, harmfulness, and epistemic incomprehensibility requiring professional explanatory systems. Through theoretical analysis and integration of philosophy of psychiatry, cultural psychology, and Japanese sociocultural considerations, the study proposes a refined descriptive definition of mental disorder. The model clarifies the boundary between pathology and rationally intelligible misconduct while maintaining compatibility with contemporary psychiatric practice.

Cracking behavior and flexural performance of fiber-reinforced RC beams subjected to cryogenic freeze-thaw cycles under static and repeated loading: Experimental and theoretical analysis

Stress-controlled magnetoacoustic conversion efficiency of SH waves: Theoretical analysis and experimental validation

Abstract Molybdenum disulfide (MoS 2 ) and tantalum (Ta)-doped MoS 2 have been synthesized using a novel Azadirachta indica -mediated green method. Tantalum, having well-matched ionic radius with molybdenum, well suited as a dopant for MoS 2 . The structural, morphological, absorption and optical properties of synthesized materials were investigated by various characterization methods. Tantalum (7% by wt.)-enriched MoS 2 showed enhanced properties such as reduced particle size (~ 47 nm to ~ 42 nm) and bandgap (2.05 eV to 1.87 eV) and decreased charge recombination rate which is well depicted by PL analysis. Furthermore, BET analysis reveals the enhanced specific surface area (13.05 m 2 /g to 31.37 m 2 /g), which an essential aspect for any degradation process. The Ta 7% -MoS 2 showed 91.41% and 82.82% degradation of MB dye and metformin with cyclic stability. COMSOL Multiphysics analysis has been performed using experimental parameters, and quite interesting experimental results are well consistent with the theoretical analysis. The COMSOL simulations provided us an opportunity to understand the underlying science associated with the present study. Graphical abstract

Biventricular assist for failing Fontan circulation remains challenging. Because fenestration effectively reduces stressed blood volume and central venous pressure in Fontan patients with increased pulmonary vascular resistance (PVR), systemic ventricular assist device (VAD) combined with fenestration may improve hemodynamics in failing Fontan patients with increased PVR who would require biventricular assist. To validate this hypothesis, we performed a computational hemodynamic simulation of the failing Fontan circulation using a lumped parameter model. We compared hemodynamic variables between the models with and without fenestration while the PVR index was increased sequentially from 3.01 to 6.81 Wood Units m2. Following VAD initiation and stressed blood volume reduction, central venous pressure was maintained at a lower level in the fenestration models. This positive effect was greater in the model with larger fenestration diameter. However, excessive fenestration caused significant desaturation. In failing Fontan circulation with elevated PVR, systemic VAD combined with fenestration significantly improved hemodynamics.

Polyp image segmentation based on parallel dilated convolution and dual attention mechanisms.

Shapley value is a widely used tool in explainable artificial intelligence (XAI), as it provides a principled way to attribute contributions of input features to model outputs. However, estimation of Shapley value requires capturing conditional dependencies among all feature combinations, which poses significant challenges in complex data environments. In this article, EmSHAP (Energy-based model for Shapley value estimation), an accurate Shapley value estimation method, is proposed to estimate the expectation of Shapley contribution function under the arbitrary subset of features given the rest. By utilizing the ability of energy-based model (EBM) to model complex distributions, EmSHAP provides an effective solution for estimating the required conditional probabilities. To further improve estimation accuracy, a GRU (Gated Recurrent Unit)-coupled partition function estimation method is introduced. The GRU network captures long-term dependencies with a lightweight parameterization and maps input features into a latent space to mitigate the influence of feature ordering. Additionally, a dynamic masking mechanism is incorporated to further enhance the robustness and accuracy by progressively increasing the masking rate. Theoretical analysis on the error bound as well as application to four case studies verified the higher accuracy and better scalability of EmSHAP in contrast to competitive methods.