Search Results (7,914)

Leukocyte recruitment from blood into tissues involves sequential adhesive steps, including rolling and integrin-dependent arrest. VLA-4 can support firm adhesion and, in some settings, rolling interactions, whereas CD44–hyaluronan interactions have also been implicated in leukocyte rolling. Here, we used adhesion assays and parallel-plate flow chamber experiments to analyze CD44–hyaluronan-dependent monocyte interactions on ECV304 monolayers and to compare them with α4-integrin-sensitive adhesion on endothelial monolayers. WEHI 78/24 monocytoid cells interacted with ECV304 monolayers in a CD44- and hyaluronan-dependent manner, whereas adhesion to HMEC-1 and bEnd.3 monolayers was sensitive to α4-integrin blockade. Blocking CD44, adding soluble hyaluronan, or treating ECV304 monolayers with hyaluronidase reduced adhesion and rolling. Mixed primary human monocyte preparations also showed CD44-dependent adhesion and rolling on ECV304 monolayers. ECV304 cells are interpreted here not as endothelial cells, but as T24-derived, hyaluronidase-sensitive cellular monolayers useful for functional analysis of CD44–hyaluronan-dependent interactions. These findings support a substrate-dependent functional hierarchy in which CD44–hyaluronan-dependent monocyte rolling becomes detectable when α4-integrin-dependent adhesion is not dominant, while emphasizing the cell-model-based nature of the assay. Full article

Hydraulic fracturing is the core technology for stimulation and reform of low-permeability and unconventional oil and gas reservoirs. Reservoir fracability directly determines fracture morphology, complexity, and stimulated reservoir volume. To address the shortcomings of existing fracability evaluation models, such as poor applicability, subjective weighting and insufficient accuracy, five key indicators are selected, including brittleness index, brittle mineral index, stress difference coefficient, minimum horizontal principal stress and porosity. First, the three-dimensional discrete lattice method is used to clarify the influence of each parameter on fracture complexity. Then, the Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM) are combined to determine the indicator weights, a continuous fracability evaluation model is constructed, and a classification standard for fracturing applicability is established. The results show that the brittleness index has the greatest influence on fracture complexity with a weight of 0.3559, followed by brittle mineral index (0.2986), minimum principal stress (0.1994), stress difference coefficient (0.0993) and porosity (0.0467). The reservoir fracability indices of 0.37 and 0.59 are the mutation points of fracture complexity. Based on microseismic evaluation of stimulated reservoir volume (SRV) using an envelope surface method, it is found that reservoirs with low fracability are more suitable for fracturing designs characterized by large cluster spacing, fewer clusters, and smaller stage spacing. In contrast, reservoirs with medium and high fracability can develop more complex fracture networks by reducing cluster spacing, increasing the number of clusters, and adopting higher pumping rates. The research results can provide theoretical basis and technical support for hydraulic fracturing operation design. Full article

Due to climate change and rapid urbanization, cities worldwide face the dual challenge of improving flood resilience and providing accessible green space within limited land resources. Sponge City parks offer a landscape-based approach for integrating stormwater management with park services. However, how park morphology structures this combined performance remains insufficiently understood. This study examines 26 Sponge City parks in Shanghai and evaluates how node-, line-, and patch-type morphologies are linked to stormwater storage and service provision. Using geospatial analysis, DEM-derived catchment delineation, land-cover interpretation, and statistical analysis, this study compares estimated stormwater storage, storage efficiency, local park availability, and land-cover composition across different park morphologies. The results show that estimated performance of stormwater management and park service provision vary across morphological types, but these differences do not follow a simple node–line–patch hierarchy. Rather, the observed patterns are jointly shaped by park morphology, catchment setting, land-cover allocation, and surrounding urban context. These findings suggest that Sponge City parks should not only be evaluated by total stormwater storage. Their contribution depends on morphology, scale, catchment setting, land-cover allocation, and urban context. The study provides a morphology–performance perspective to support more differentiated planning of multifunctional green infrastructure. Full article

Accurate identification of visually similar targets in Unmanned Aerial Vehicle (UAV) imagery is hindered by significant inter-class ambiguity and viewpoint variability. While hierarchical deep learning mitigates these challenges, existing architectures relieve manual design, introducing subjectivity and limiting cross-domain scalability. In this work, we propose an objective, data-driven method for the automated synthesis of hierarchical classification structures. Our approach uses a hybrid inter-class proximity metric that integrates geometric distances between latent-feature-space centroids with empirical misclassification probabilities. Using a hierarchical agglomerative clustering algorithm optimized via an inconsistency coefficient, we synthesize a coarse-to-fine cascade that deploys YOLOv11 for feature extraction and FT-Transformers for specialized identification. Experimental validation on the VisDrone2019 and UAV123 datasets demonstrates that the automatically generated hierarchy achieves a peak F1-score of 94.9%, outperforming the monolithic YOLOv11 model by 0.8% and matching human-designed cascades. Sensitivity analysis indicates an optimal hybrid weight range of 0.4–0.6. The findings confirm that our automated synthesis provides high adaptability and reliability for real-time edge AI deployments, ensuring robust performance in dynamic monitoring environments without requiring manual redesign. Full article

This work presents a case study of sensitivity analysis applied to the modeling of ethanol steam reforming (SRE) in a catalytic porous medium, with a focus on hydrogen production. Considering the high variability of parameters reported in the literature, the objective is not to propose a universal model, but rather to assess the impact of uncertainties associated with input parameters on the model outcomes. The model was developed under steady-state conditions, coupling flow in porous media, species transport, and heat transfer, with kinetics described as a function of partial pressures. The sensitivity analysis was conducted through the systematic variation of kinetic and physicochemical parameters within ranges associated with their uncertainties. The results indicate that activation energy is the parameter most sensitive to uncertainty variation, exhibiting the greatest impact on hydrogen production. The thermal properties of the medium, particularly thermal conductivity and solid density, also stand out, highlighting the role of thermo-kinetic coupling. In contrast, parameters such as porosity, water reaction order, and particle diameter exhibited low sensitivity under the analyzed conditions. As a main contribution, this work establishes a sensitivity hierarchy associated with parameter uncertainties and provides guidance for other researchers regarding the prioritization of their determination and calibration in hydrogen production models. Full article

Soil vulnerability is commonly assessed using environmental indicators; however, the lack of systematic and continuous monitoring often leads to incomplete and fragmented data, particularly in surface coal mining areas affected by potentially toxic element (PTE) contamination. Existing studies mainly focus on impact assessment, with limited emphasis on structured decision-support frameworks for selecting optimal soil protection strategies. This study addresses this gap by proposing an integrated hybrid decision-making framework that combines the Analytic Hierarchy Process (AHP), Sustainability Balanced Scorecard (SBSC), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The main contribution lies in integrating strategic sustainability perspectives (SBSC) with quantitative multi-criteria methods (AHP and TOPSIS), enabling a transparent and consistent evaluation of soil protection strategies across environmental, economic, technical, and social dimensions. The framework was applied to the Kostolac mining and energy complex in Serbia as a representative case study, using data from the State of the Environment Report as the basis for expert evaluation. The results identify risk reduction and environmental effectiveness as the dominant criteria, while the Progressive Strategy (SBSC) achieved the highest ranking. Sensitivity analysis confirmed the robustness of the model. From a policy perspective, the findings support prioritizing sustainability-oriented and risk-reduction strategies in mining regulations and investment planning. Full article

Increasing attention has been directed toward walkability evaluation because pedestrian environments are closely associated with mobility patterns, environmental quality, and everyday spatial experience. However, most existing walkability studies either emphasize objective spatial indicators or rely on subjective satisfaction surveys, while the relationship between expert evaluation and user satisfaction has received relatively limited attention, particularly regarding its nonlinear characteristics. In addition, walkability frameworks developed for urban public environments are often directly applied to university campuses without adequately considering the distinctive behavioral characteristics of campus pedestrian activities. To address these limitations, this study proposes an integrated AHP–Kano walkability evaluation framework for campus pedestrian systems. The framework combines the Analytic Hierarchy Process (AHP) with the Kano model to establish a perception-sensitive and behavior-oriented evaluation structure. AHP is employed to determine the relative importance of environmental indicators through expert judgment, while the Kano model is introduced to capture the asymmetric effects of different environmental attributes on user satisfaction. GIS analysis and field investigation were employed as supplementary spatial diagnostic tools to support the interpretation of pedestrian–environment characteristics. Using the Xiamen campus of Huaqiao University as a case study, this research constructs a multidimensional evaluation system covering accessibility, safety, comfort, landscape quality, and service functionality. Questionnaire surveys and expert evaluations were conducted to analyze the relationship between objective environmental importance and subjective perceptual response. The results indicate that safety- and accessibility-related attributes primarily function as must-be requirements that prevent dissatisfaction, whereas environmental cleanliness and selected experiential elements exhibit stronger satisfaction-enhancing effects. Several landscape-related indicators, commonly emphasized in urban walkability studies, demonstrate relatively weak perceptual sensitivity in campus contexts, reflecting the task-oriented and time-constrained nature of campus pedestrian behavior. The present study extends existing walkability research in several important respects. Rather than relying on conventional linear assumptions, the proposed framework incorporates nonlinear perceptual responses into walkability evaluation. The findings further demonstrate that pedestrian perception is highly context-dependent in campus environments, while the integrated framework further provides a behavior-sensitive basis for prioritizing spatial interventions. Full article

Food loss and waste are a major global problem as reflected in the United Nations Sustainable Development Goal 12. Households constitute the primary source of food waste worldwide. The development of effective solutions depends on a comprehensive understanding of consumer attitudes and behaviors. This cross-sectional study used the Value–Attitude–Behavior (VAB) hierarchy to examine consumers’ food waste reduction intentions. It was conducted on individuals in Turkiye via an online survey. The results showed that consumers’ hedonic value and attitudes were positively associated with food waste reduction intentions. The strongest associations with intentions were observed for anticipated guilt, attitude toward reducing food waste, and hedonic value. Furthermore, education level and household size showed significant effects on food waste reduction intentions. In conclusion, these findings based on the VAB model showed the central role of anticipated guilt in shaping food waste reduction intentions, suggesting that emotionally driven intervention strategies may be more effective than approaches focusing solely on attitudes. Full article

This paper investigates the viability of utilizing Fused Deposition Modeling (FDM) for the fabrication and follow-up testing of a hemispherical resonator (HR). This form of resonator has several significant applications, including the design of vibratory gyroscopes. While traditional high-precision resonators for this application rely on expensive fused-silica fabrication, this study proposes a macro-scale approach using Polylactic Acid (PLA) to enable accessible lab-scale experimentation. The specimens, featuring a unique central-hole mounting configuration, were designed in SolidWorks and analyzed via finite element methods to establish the modal hierarchy. Experimental Modal Analysis (EMA) was conducted using a Laser Doppler Vibrometer (LDV) to acquire vibration signals, which were then analyzed in NVGate, MATLAB, and MEscope to extract natural frequencies and quality factor. Results for a lab-scale HR specimen identified the n = 2 wine-glass mode with a deviation from theoretical natural frequency predictions largely attributed to inherent defects in the fabrication process. Furthermore, a frequency split of 2.15 Hz was observed due to the inherent asymmetries and mass imbalances of the fabrication method. The quality factor was evaluated via the ring-down method and validated using the half-power bandwidth (HPBW) technique. This work demonstrates that 3D-printed resonators serve as an effective, low-cost platform for isolating modal behaviors and optimizing geometric parameters before advancing to micro-scale fabrication. Full article

Temporomandibular disorder (TMD) and bruxism affect a significant portion of the adult population, yet why patients with comparable occlusal findings respond so differently to identical interventions remains unexplained by both structural and biopsychosocial frameworks. Traditional occlusal paradigms identified the importance of structural relationships but could not account for clinical variability. Biopsychosocial models advanced understanding of central regulation but lack the physiological specificity needed to connect regulatory state to functional jaw behavior. This paper proposes the Functional Occlusion Regulated Model (FORM), a hierarchical framework integrating central regulatory state, masticatory performance, and structure into a coherent model of jaw function, and identifies its clinical and research implications. Narrative synthesis of the peer-reviewed literature across masticatory physiology, autonomic neuroscience, pain neuroscience, and clinical dentistry was conducted; seventy-two references are cited. Converging evidence supports a three-tier hierarchy in which autonomic and neuromuscular regulatory state is proposed to shape masticatory performance, which influences how structural occlusal conditions are expressed and clinically experienced. FORM generates four testable predictions distinguishing it from existing models, and a preliminary clinical observation documents symptom resolution through regulatory intervention alone without occlusal modification, representing an early published dental observation of this connection. FORM provides a physiologically grounded framework for understanding treatment response variability and proposes central regulatory state as a potentially important upstream influence on functional jaw outcomes. Full article

Smart museums increasingly rely on digital media, interactive installations, artificial intelligence, augmented reality, and virtual reality to support cultural communication and visitor engagement. However, existing studies have mainly examined specific technologies, usability, or visitor satisfaction, while a systematic and quantitative framework for comparing interactive experience across different smart museums remains limited. To address this gap, this study proposes a hybrid multi-criteria decision-making framework for evaluating smart museum interactive experience. Based on the Strategic Experiential Modules, an evaluation system consisting of five dimensions—Sense, Feel, Think, Act, and Relate—and sixteen indicators was constructed. The Analytic Hierarchy Process was used to determine subjective weights from expert judgments, the entropy method was applied to capture the data-driven dispersion characteristics of expert evaluation data, and a game-theoretic combination weighting strategy was used to integrate the two weighting results. Subsequently, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was employed to compare five representative smart museum cases. The results show that Zhejiang Provincial Museum achieved the highest relative closeness value (C_i = 0.9891), followed by Shanghai Museum (C_i = 0.8457) and Hunan Museum (C_i = 0.5326). Robustness analysis further showed that the ranking order remained consistent under entropy weights, AHP weights, average weights, and game-theoretic combined weights. The Friedman test indicated no significant difference in the relative closeness coefficients across weighting schemes (χ² = 1.200, p = 0.753). These findings indicate that the proposed framework can effectively identify relative strengths and weaknesses in smart museum interactive experience and provide a replicable decision-support tool for experience-oriented museum design and optimization. Full article

Background: Circular supply chains (CSC) have emerged as a strategic response to sustainability challenges, while adoption remains uneven. Supplier selection is a key driver of effectiveness, shaped by organizational capabilities, institutional support, and leadership. This study develops a structured framework for circular supplier selection (CSS) using a hybrid multi-criteria decision-making approach, addressing fragmented research and strengthening the link between methodological innovation and practice. Methods: The proposed framework integrates fuzzy DEMATEL, the Best-Worst Method (BWM), and the Analytic Hierarchy Process (AHP) within MCDM. Fuzzy DEMATEL identifies cause-and-effect relationships among criteria, distinguishing net causes from net effects. The most influential and dependent criteria serve as anchors for the BWM weighting, followed by AHP to evaluate sub-criteria and alternatives. Results: Environmental governance emerged as the most influential driver in the causal analysis, while circular performance received the highest weight in BWM. The final AHP evaluation ranked Alternative 5 as the most suitable, followed by A9 and A3, confirming the framework’s ability to deliver consistent, actionable insights for circular supplier selection. Conclusions: This integration enables a more granular and robust evaluation of supplier strategies within CSC, reinforcing their role in accelerating sustainability transitions. It establishes a structured framework for CSS, highlighting CSS performance and upstream supply chain decision-making. Full article

Natural and human-caused disasters have operated as selection mechanisms in the evolution of within-polity and interpolity sociocultural systems by destroying lives and the human-built environment, and they have provoked challenge-and-response dynamics that caused human polities to innovate and to implement innovations that resulted in increases in complexity and hierarchy. Individuals, households, communities, settlements, and polities and interpolity systems that were most prepared and resilient to these selection mechanisms survived and prevailed. This article reviews the theoretical literature in geography, historiography, sociology, anthropology, political science and economics on hypotheses regarding the effects of disasters on human social change, including both increases and decreases in sociocultural complexity and hierarchy. Full article

Water resources safety is a crucial prerequisite for nuclear power development and a key component of the safety system for inland nuclear power. Based on an analysis of the influencing factors of water resources safety during the site selection stage of inland nuclear power, this paper constructs an evaluation index system for water resources safety in this stage using the Pressure–State–Response (PSR) model. Combining current technical standards related to nuclear power site selection with Strictest Water Resources Management System formulated by the Chinese government, the evaluation standards for water resources safety during the site selection stage of inland nuclear power are established. Two water resources safety evaluation models for inland nuclear power plant site selection are presented, employing the Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation Method (FCEM) respectively. Finally, the water resources safety evaluation system established in this paper is applied to the water resources safety evaluation during the site selection stage of Xiaomoshan Nuclear Power Station. The evaluation results of the two models are basically consistent, and both conclude that the water resources safety during the site selection stage of Xiaomoshan Nuclear Power Station could be basically guaranteed. This provides an effective means for the water resources safety evaluation during the site selection stage of inland nuclear power plants. Full article

Arnold tongues are wedge-shaped regions in parameter space associated with mode locking and synchronization phenomena in nonlinear dynamical systems. The Caputo fractional standard map extends the classical standard map by incorporating long-memory effects through fractional derivatives and is known to generate Arnold tongue structures as the fractionality parameter approaches unity. In this paper, we investigate the fractional standard map applied to matrix-valued state variables, with particular emphasis on systems governed by high-dimensional nilpotent matrices. We show that the interplay between fractional memory and nilpotent algebra produces hierarchical families of Arnold tongues associated with divergent dynamics. This phenomenon is not observed in either the classical standard map or the non-fractional standard map of nilpotent matrices alone. For idempotent matrices, the fractional standard map retains the same level of dynamical complexity as its scalar counterpart. For nilpotent matrices, higher-order terms induce coupling between the map coefficients, giving rise to substantially richer dynamical behavior. This combination of fractional memory and nilpotent algebra provides a systematic framework for studying higher-dimensional nonlinear dynamics beyond the scalar setting. To support numerical investigations, an efficient computational scheme for the auxiliary parameters is derived and calibrated using the H-rank algorithm, which provides a concise measure of algebraic complexity in sequences generated by dynamical systems. Numerical simulations reveal hierarchical structures of Arnold tongues of divergence together with characteristic divergence rates of the auxiliary parameters. The hierarchical level of a given auxiliary parameter is identified as a key quantity determining the algebraic complexity of the transient dynamics, with potential implications for information encoding in applications exploiting transient dynamical processes. Full article