Search Results (342)

Accurately simulating the asymmetric spectral profiles of blue LEDs is crucial for photobiological research, yet it remains a challenge for traditional symmetric models. This study proposes a novel spectral simulation model that effectively captures these asymmetries. The proposed model structure is partly motivated by known broadening and dispersion mechanisms observed in real LED spectra; it employs a ‘base model + correction’ framework, where an Exponentially Modified Gaussian (EMG) function captures the primary spectral shape and falling edge and an Asymmetric Pseudo-Voigt (APV) function corrects the deviations on the rising edge. Requiring only the central wavelength and bandwidth as user inputs, the simulation results exhibit a high degree of agreement with the experimental data spectra. The model provides a rapid and robust tool for pre-evaluating light sources against regulatory criteria (e.g., >99% of the spectral intensity is in the 400–500 nm band), thereby enhancing the efficiency of experimental design in blue light protection studies. Full article

The model explicitly incorporates boundary conditions that account for the complex interplay between sections experiencing varying degrees of reduction. This interaction significantly influences the overall deformation behavior and force loading. The control effect is associated with boundary conditions determined by the unevenness of the compression, which have certain quantitative and qualitative characteristics. These include additional loading, which is less than the main load, which implements the process of plastic deformation, and the ratio of control loads from the entrance and exit of the deformation site. According to this criterion, it follows from experimental data that the controlling effect on the plastic deformation site occurs with a ratio of additional and main loading in the range of 0.2–0.8. The next criterion is the coefficient of support, which determines the area of asymmetry of the force load and is in the range of 2.00–4.155. Furthermore, the criterion of the regulating force ratio at the boundaries of the deformation center forming a longitudinal plastic shear is within the limits of 2.2–2.5 forces and 1.3–1.4 moments of these forces. In this state, stresses and deformations of the plastic medium are able to realize the effects of plastic shaping. The force effect reduces with an increase in the unevenness of the deformation. This is due to a change in height of the longitudinal interaction of the disparate sections of the strip. There is an appearance of a new quality of loading—longitudinal plastic shear along the deformation site. The unbalanced additional force action at the entrance of the deformation source is balanced by the force source of deformation, determined by the appearance of a functional shift in the model of the stress state of the metal. The developed theory, using the generalized method of an argument of functions of a complex variable, allows us to characterize the functional shift in the deformation site using invariant Cauchy–Riemann relations and Laplace differential equations. Furthermore, the model allows for the investigation of material properties such as the yield strength and strain hardening, influencing the size and characteristics of the identified limit state zone. Future research will focus on extending the model to incorporate more complex material behaviors, including viscoelastic effects, and to account for dynamic loading conditions, more accurately reflecting real-world milling processes. The detailed understanding gained from this model offers significant potential for optimizing mill roll designs and processes for enhanced efficiency and reduced energy consumption. Full article

The interconnections among water, energy, and food (WEF) systems are growing increasingly complex, making it essential to understand their evolutionary mechanisms and coordination barriers to enhance regional resilience and sustainability. In this study, we investigated the WEF system in Northeast China by constructing a comprehensive indicator system encompassing resource endowment and utilization efficiency. The coupling coordination degree (CCD) of the WEF system was quantitatively assessed from 2001 to 2022. An obstacle degree model was employed to identify key constraints, while grey relational analysis was used to evaluate the driving influence of individual indicators. Furthermore, a co-evolution model based on logistic growth and competition–cooperation dynamics was developed to simulate system interactions. The results reveal the following: (1) the regional WEF-CCD increased from 0.627 in 2001 to 0.769 in 2022, reaching the intermediate coordination level, with the CCDs of the food, water, and energy subsystems rising from 0.39 to 0.62, 0.38 to 0.60, and 0.40 to 0.55, respectively, highlighting that the food subsystem had the most stable and significant improvement; (2) Jilin Province attained the highest WEF-CCD, 0.850, in 2022, while that for Heilongjiang remained the lowest, at 0.715, indicating substantial interprovincial disparities; (3) key indicators, such as food self-sufficiency rate, electricity generation, and ecological water use, functioned as both core constraints and major drivers of system performance; (4) co-evolution modeling revealed that the food subsystem exhibited the fastest growth, followed by water and energy (${\alpha }_3$ >${ \alpha }_1$ > ${ \alpha }_2$ > 0), with mutual promotion between water and energy subsystems and inhibitory effects from the food subsystem, ultimately converging toward a stable equilibrium state; and (5) interprovincial co-evolution modeling indicated that Jilin leads in WEF system development, followed by Liaoning and Heilongjiang, with predominantly cooperative interactions among provinces driving convergence toward a stable and coordinated equilibrium despite structural asymmetries. This study proposes a transferable, multi-method analytical framework for evaluating WEF coordination, offering practical insights into bottlenecks, key drivers, and co-evolutionary dynamics for sustainable resource governance. Full article

The concept of “material effort” appears in continuum mechanics wherever the response of a material to the currently existing state of loads and boundary conditions loses its previous, predictable character. However, within the material, which still descriptively remains a continuous medium, new physical structures appear and new previously unused physical features of the continuum are activated. The literature is dominated by a simplified way of thinking, which assumes that all these states can be characterized and described by one and the same measure of effort—for metals it is the Huber–Mises–Hencky equivalent stress. Quantitatively, perhaps 90% of the literature is dedicated to this equivalent stress. The remaining authors, as well as the author of this paper, assume that there is no single universal measure of effort that would “fit” all operating conditions of materials. Each state of the structure’s operation may have its own autonomous measure of effort, which expresses the degree of threat from a specific destruction mechanism. In the current energy sector, we are increasingly dealing with “low-cycle thermal fatigue states”. This is related to the fact that large, difficult-to-predict renewable energy sources have been added. Professional energy based on coal and gas units must perform many (even about 100 per year) starts and stops, and this applies not only to the hot state, but often also to the cold state. The question arises as to the allowable shortening of start and stop times that would not to lead to dangerous material effort, and whether there are necessary data and strength characteristics for heat-resistant steels that allow their effort to be determined not only in simple states, but also in complex stress states. Do these data allow for the description of the material’s yield surface? In a previous publication, the author presented the results of tension and compression tests at elevated temperatures for two heat-resistant steels: St12T and 26H2MF. The aim of the current work is to determine the properties and strength characteristics of these steels in a pure torsion test at elevated temperatures. This allows for the analysis of the strength of power turbine components operating primarily on torsion and for determining which of the two tested steels is more resistant to high temperatures. In addition, the properties determined in all three tests (tension, compression, torsion) will allow the determination of the yield surface of these steels at elevated temperatures. They are necessary for the strength analysis of turbine elements in start-up and shutdown cycles, in states changing from cold to hot and vice versa. A modified testing machine was used for pure torsion tests. It allowed for the determination of the sample’s torsion moment as a function of its torsion angle. The experiments were carried out at temperatures of 20 °C, 200 °C, 400 °C, 600 °C, and 800 °C for St12T steel and at temperatures of 20 °C, 200 °C, 400 °C, 550 °C, and 800 °C for 26H2MF steel. Characteristics were drawn up for each sample and compared on a common graph corresponding to the given steel. Based on the methods and relationships from the theory of strength, the yield stress and torsional strength were determined. The yield stress of St12T steel at 600 °C was 319.3 MPa and the torsional strength was 394.4 MPa. For 26H2MH steel at 550 °C, the yield stress was 311.4 and the torsional strength was 382.8 MPa. St12T steel was therefore more resistant to high temperatures than 26H2MF. The combined data from the tension, compression, and torsion tests allowed us to determine the asymmetry and plasticity coefficients, which allowed us to model the yield surface according to the Burzyński criterion as a function of temperature. The obtained results also allowed us to determine the parameters of the Drucker-Prager model and two of the three parameters of the Willam-Warnke and Menetrey-Willam models. The research results are a valuable contribution to the design and diagnostics of power turbine components. Full article

This study aimed to analyze whether formal managers’ qualifications explain the Brazilian pension funds’ disclosure level. It started from the assumption of information asymmetry between stakeholders. We also recognize that the problems related to asymmetry in companies participating in the capital market, commonly pointed out in the literature, would not behave in the same way in pension funds. Other factors explain the disclosure in these organizations, like the qualification of managers. We calculated the disclosure level for each of the 209 Brazilian pension funds that made up the sample. We analyzed the dates using multiple linear and logistic regression as a robustness test. The results indicated that the formal qualification of managers, characterized by master’s and or doctoral degrees, has a positive relationship with the level of disclosure of pension funds, indicating that the greater the formal qualification of the manager, the greater the level of disclosure. Thus, this study shows insights that the explanations about company disclosure given in the literature, especially its effect on market value, are not necessarily the same in pension funds, which are explained by other factors, such as the qualification of managers. The results can contribute to regulatory bodies to formulate new rules that favor the capability of managers, in addition to identifying the information demanded by stakeholders, allowing for an increase in the level of disclosure and a reduction in information asymmetry, as well as the improvement of governance practices. Full article

Background/Objectives: Quantitative assessments of facial muscle function and cognitive responses can enhance the clinic evaluations in neuromuscular disorders such as Bell’s palsy and psychiatric conditions including anxiety and depression. This study explored the application of Digital Image Speckle Correlation (DISC) in detecting enervation of facial musculature and assessing reaction times in response to visual stimuli. Methods: A consistent video recording setup was used to capture facial movements of human subjects in response to visual stimuli from a calibrated database. The DISC method utilizes the displacement of naturally occurring skin pores to map the specific locus of underlying muscular movement. The technique was applied to two distinct case studies: Patient 1 had unilateral Bell’s palsy and was monitored for 1 month of recovery. Patient 2 had a comorbidity of refractory depression and anxiety disorders with ketamine treatment and was assessed over 3 consecutive weekly visits. For patient 1, facial asymmetry was calculated by comparing left-to-right displacement signals. For patient 2, visual reaction time was measured, and facial motion intensity and response rate were compared with self-reported depression and anxiety scales. Results: DISC effectively mapped biomechanical properties of facial motions, providing detailed spatial and temporal resolution of muscle activity. In a control cohort of 10 subjects, when executing a facial expression, the degree of left/right facial asymmetry was determined to be 13.2 (8)%. And showed a robust response in an average of 275 (81) milliseconds to five out of the five images shown. For patient 1, obtained an initial asymmetry of nearly 100%, which decreased steadily to 20% in one month, demonstrating a progressive recovery. Patient 2 exhibited a prolonged reaction time of 518 (93) milliseconds and reduced response rates compared with controls of 275 (81) milliseconds and a decrease in the overall rate of response relative to the control group. The data obtained before treatment in three visits correlated strongly with selected depression and anxiety scores. Conclusions: These findings highlight the utility of DISC in enhancing clinical monitoring, complementing traditional examinations and self-reported measures. Full article

Under the background of intensified global economic fluctuations, to prevent the systemic risk of real estate (e.g., the U.S. subprime crisis), this study constructs a linkage network of the real estate industry in the U.S. based on the complex network method, reveals the fluctuation diffusion mechanism, identifies the key pivotal industries through the network characteristic indicators, and analyses the characteristics of the fluctuation conduction paths by applying the industrial fundamental association trees. The study found that (1) the U.S. real estate industry is a ‘supply hub’ industry, with first-order and second-order weighted degrees of mean 6.78, 3.98, and significant asymmetry in the supply structure of the industrial network; (2) industries like architectural, engineering, and related services (541300), nonresidential maintenance and repair (230301), and electric power generation, transmission, and distribution (221100) show high degree centrality and betweenness centrality. Their strong propagation and control capabilities form real estate fluctuations’ core transmission mechanisms; (3) foundational association trees reveal long, broad propagation paths where financial investment and energy-supply sectors act as “traffic hubs,” decisively influencing risk diffusion depth and breadth. Targeted policy recommendations address four dimensions: optimizing industrial chain structures, strengthening financial risk isolation, improving housing supply systems, and enhancing policy coordination. This aims to help China avoid U.S.-style real-estate-bubble risks and achieve coordinated real estate macroeconomy development. Full article

The Asymmetric Double Cantilever Beam (ADCB) is a common test configuration used to produce mixed mode I/II in composite materials. It consists of two sublaminates with different thicknesses or elastic properties, a situation that usually occurs in bimaterial adhesive joints. During this test, the sample undergoes rotation. In this work, the influence of this rotation on the calculation of the energy release rate (ERR) in modes I and II was studied using the Finite Element Method (FEM). Several models with different degrees of asymmetry (different thickness ratio and/or elastic modulus ratio) and different applied displacements were prepared to obtain different levels of rotation during the test. As is known, the concept of modes I and II refers to the components of the energy release rate calculated in the direction perpendicular and tangential to the delamination plane, respectively. If the model experiences significant rotation during the application of the load, this non-linearity must be considered in the calculation of the mode partition I/II. In this work, appreciable differences were observed in the values of modes I and II, depending on their calculation in a global system or a local system that rotates with the sample. When performing crack growth calculations, the difference between critical loads can be in the order of 4%, while the difference between mode I and mode II results can reach 4% and 14%, respectively, for an applied displacement of only 5 mm. Currently, this correction is not usually implemented in Finite Element calculation codes or in analytical developments. The purpose of this article is to draw attention to this aspect when the rotation of the specimen is not negligible. Full article

In this paper we investigate the non-Markovian dynamics of a giant atom coupled to a one-dimensional photonic lattice with synthetic gauge fields. By engineering a complex-valued hopping amplitude, we break reciprocity and explore how chiral propagation and phase-induced interference affect spontaneous emission, bound-state formation, and atom–field entanglement. The giant atom interacts with the lattice at multiple, spatially separated sites, leading to rich interference effects and decoherence-free subspaces. We derive an exact expression for the self-energy and perform real-time Schrödinger simulations in the single-excitation subspace, for the atomic population, von Neumann entropy, field localization, and asymmetry in emission. Our results show that the hopping phase $\varphi$ governs not only the directionality of emitted photons but also the degree of atom–bath entanglement and photon localization. Remarkably, we observe robust bound states inside the photonic band and directional asymmetry, due to interference from spatially separated coupling points. These findings provide a basis for engineering non-reciprocal, robust, and entangled light–matter interactions in structured photonic systems. Full article

This study investigates whether government subsidies promote R&D cost stickiness in the new energy vehicle (NEV) industry in China—that is, whether public funding encourages firms to retain R&D resources even during periods of declining sales. While prior literature primarily explores the relationship between subsidies and R&D investment levels, it often overlooks firms’ financial position and dynamic cost behaviors. Given that R&D investment has high adjustment costs and is sensitive to cash flows, reductions in R&D spending during downturns may reflect managerial cost asymmetry rather than a crowding-out effect of subsidies. Moreover, government subsidies may serve as a signal of long-term market optimism, motivating managers to retain R&D resources during economic downturns. Using a panel dataset of 573 listed new energy vehicle (NEV) firms in China’s A-share market from 2007 to 2021, we construct a model based on the asymmetric cost behavior framework to empirically assess the impact of government subsidies on R&D cost stickiness. The results show that government subsidies significantly increase the degree of R&D cost stickiness. Serving as a signal of future market optimism, subsidies raise managerial expectations and incentivize decisions to retain R&D-related costs during economic downturns. This positive relationship is more pronounced in firms with high levels of green innovation, large-scale enterprises, and non-state-owned firms. These findings suggest that public funding alleviates managerial pressure to cut R&D expenses amid revenue declines, thereby supporting firms’ long-term innovation strategies. Our study contributes to the cost management literature by highlighting a novel channel through which subsidies influence managerial discretion under uncertainty. It also provides policy implications for the future phase-out of subsidies, emphasizing the need for complementary market mechanisms to sustain innovation investment, particularly for small, young, and financially constrained firms. Full article

Facial palsy (FP) significantly impacts patients’ quality of life. The accurate classification of FP severity is crucial for personalized treatment planning. Additionally, electromyographic (EMG)-based biofeedback shows promising results in improving recovery outcomes. This prospective study aims to identify EMG time series features that can both classify FP and facilitate biofeedback. Therefore, it investigated surface EMG in FP patients and healthy controls during three different facial movements. Repeated-measures ANOVAs (rmANOVA) were conducted to examine the effects of MOTION (move/rest), SIDE (healthy/lesioned) and the House–Brackmann score (HB), across 20 distinct EMG parameters. Correlation analysis was performed between HB and the asymmetry index of EMG parameters, complemented by Fisher score calculations to assess feature relevance in distinguishing between HB levels. Overall, 55 subjects (51.2 ± 14.73 years, 35 female) were included in the study. RmANOVAs revealed a highly significant effect of MOTION across almost all movement types (p < 0.001). Integrating the findings from rmANOVA, the correlation analysis and Fisher score analysis, at least 5/20 EMG parameters were determined to be robust indicators for assessing the degree of paresis and guiding biofeedback. This study demonstrates that EMG can reliably determine severity and guide effective biofeedback in FP, and in severe cases. Our findings support the integration of EMG into personalized rehabilitation strategies. However, further studies are mandatory to improve recovery outcomes. Full article

In the contemporary global educational environment, the automatic assessment of students’ online engagement has garnered widespread attention. A substantial number of studies have demonstrated that facial expressions are a crucial indicator for measuring engagement. However, due to the asymmetry inherent in facial expressions and the varying degrees of deviation of students’ faces from a camera, significant challenges have been posed to accurate emotion recognition in the online learning environment. To address these challenges, this work proposes a novel VGG-SwishNet model, which is based on the VGG-16 model and aims to enhance the recognition ability of asymmetric facial expressions, thereby improving the reliability of student engagement assessment in online education. The Swish activation function is introduced into the model due to its smoothness and self-gating mechanism. Its smoothness aids in stabilizing gradient updates during backpropagation and facilitates better handling of minor variations in input data. This enables the model to more effectively capture subtle differences and asymmetric variations in facial expressions. Additionally, the self-gating mechanism allows the function to automatically adjust its degree of nonlinearity. This helps the model to learn more effective asymmetric feature representations and mitigates the vanishing gradient problem to some extent. Subsequently, this model was applied to the assessment of engagement and provided a visualization of the results. In terms of performance, the proposed method achieved high recognition accuracy on the JAFFE, KDEF, and CK+ datasets. Specifically, under 80–20% and 10-fold cross-validation (CV) scenarios, the recognition accuracy exceeded 95%. According to the obtained results, the proposed approach demonstrates higher accuracy and robust stability. Full article

The intervention of distributed loads, propelled by the swift advancement of distributed energy sources and the escalating demand for diverse load types encompassing electricity and cooling within virtual power plants (VPPs), has exerted an influence on the symmetry of the grid. Consequently, a quantitative assessment of the annual peak-shaving capability of a VPP is instrumental in mitigating the peak-to-valley difference in the grid, enhancing the operational safety of the grid, and reducing grid asymmetry. This paper presents a peak-shaving optimization method for VPPs, which takes into account renewable energy uncertainty and flexible load demand response. Firstly, wind power (WP), photovoltaic (PV) generation, and demand-side response (DR) are integrated into the VPP framework. Uncertainties related to WP and PV generation are incorporated through the scenario method within deterministic constraints. Secondly, a stochastic programming (SP) model is established for the VPP, with the objective of maximizing the peak-regulation effect and minimizing electricity loss for demand-side users. The case study results indicate that the proposed model effectively tackles peak-regulation optimization across diverse new energy output scenarios and accurately assesses the peak-regulation potential of the power system. Specifically, the proportion of load decrease during peak hours is 18.61%, while the proportion of load increase during off-peak hours is 17.92%. The electricity loss degrees for users are merely 0.209 in summer and 0.167 in winter, respectively. Full article

In the research and practice of integrated scheduling problems, the tree structure of complex products usually presents an asymmetric and complex form. This asymmetry is mainly reflected in the hierarchical relationship between the various components of the product, the degree of dependence, and the sequence of production processes. Existing studies often neglect that leaf nodes with the lowest layer priority can be scheduled at any moment, leading to underutilization of parallelism potential under symmetric structures and exacerbation of critical path delays under asymmetric structures. Aiming at solving this kind of problem, an integrated scheduling algorithm based on the improved Floyd algorithm (ISA-IFA) is proposed. According to the improved Floyd algorithm, the algorithm proposed a path-weighted strategy, which constructs the vertical path value according to the processing time of the process itself. Combined with the proposed process scheduling advantage strategy, the leaf node process is especially emphasized as the priority scheduling object, which makes the connection between the processes more closely, and then significantly reduces the idle time of the equipment. The empirical results show that the ISA-IFA algorithm shortens the completion time of complex products and simultaneously improves the equipment utilization rate to 55.9%, verifying its effectiveness in dynamic scheduling and resource co-optimization. Full article

In deeply buried, small-clearance tunnels, the failure of the surrounding rock is profoundly influenced by the superposition of stresses and the cumulative disturbance effects from multiple blasting events. Consequently, the failure characteristics and mechanisms of the surrounding rock are highly complex. Through a comprehensive analysis encompassing failure investigations, geological assessments, and surrounding rock pressure monitoring, this study systematically examines the spatio-temporal failure characteristics and geological discrepancies across 3 parallel tunnels (namely, a pilot tunnel, a left tunnel, and a right tunnel). The analysis reveals the asymmetric failure behavior of the surrounding rock and offers a detailed discussion of the underlying mechanisms. The temporal and spatial evolution of the surrounding rock pressure in these tunnels is carefully analyzed, with an emphasis on uncovering the asymmetric failure mechanisms during the excavation of deep, small-clearance tunnels. The results demonstrate that the failure of the surrounding rock exhibits significant asymmetry during excavation, with the damage being more pronounced on the valley side compared to the mountain side. Furthermore, the degree of damage in the advance tunnel is substantially greater than that in the backward tunnel, particularly in sections following the excavation of the backward tunnel. Additionally, the distribution of the surrounding rock pressure in the advance tunnel also exhibits pronounced asymmetry. The asymmetric failure of the surrounding rock is primarily attributed to the stress concentration in the deep valley and the disturbances introduced by the excavation process, which induces tangential stress concentrations in the surrounding rock mass. The findings of this study hold considerable significance for the design and optimization of tunnel support systems, as well as for disaster prevention strategies in deeply buried, small-clearance tunnels. Full article