Bidirectional dual-anchoring buried interface regulates crystallization kinetics of perovskite prepared using two-step method for stable and efficient photovoltaics.

Spectra-based predictive mapping of soil erodibility and analysis of its influence mechanism: A typical case study for Northeast China

Effect of oleogelators on rheological tunability and 3D printability of xanthan gum-κ-carrageenan based bigel inks.

Competitive adsorption performance of volatile organic compounds on ZSM-5: Key influence factors and mechanisms

Methodology to assess the influence of thermocouple measurement errors on unsteady heat transfer characteristics in aero-engine experiments

Study on collapse behavior of corroded subsea pipelines for integrity assessment: Cellular automaton-finite element method sequential coupling simulation and parametric influence mechanism

Control of aromatic halogenated disinfection byproducts in chlorinated and chloraminated drinking water through pre-oxidation: Effects and mechanisms.

While most subsidence research focuses on urban high-rise buildings, this study addresses the unique challenge of densely distributed substation structures with varying sizes and irregular layouts. Densely distributed structures refer to the spatial arrangement of multiple artificial constructions concentrated within a defined geographic area. Substations, which serve as hubs for power generation and distribution, encompass numerous such structures that are highly sensitive to surface subsidence. While previous research on subsidence has predominantly focused on urban high-rise buildings, limited attention has been given to the interdependencies and subsidence sensitivities within densely distributed substation structures. This gap poses challenges to the design, operation, and maintenance of these specialized facilities. To address this issue, this study proposes an intelligent analysis approach utilizing a backpropagation (BP) neural network to assess the correlation effects of subsidence among densely distributed structures. A deformation correlation model is developed, and its application is demonstrated through a case study of a specific substation project. The quantitative impacts of adjacent structures on the subsidence of the main control building are analyzed, while the underlying influence mechanisms are qualitatively examined via numerical simulations. The results indicate a strong agreement between measured and predicted subsidence values using the BP neural network. Among the adjacent structures, the subsidence contributions to the main control building are quantified as 42% from the main transformer protection and station power room, 31% from the integrated pump house, and 27% from the protection cubicle. Sensitivity analysis reveals that the main control room and protection cubicle are most affected by structural weight, whereas the integrated pump house, alarm transmission room, and main transformer protection and station power room are predominantly influenced by structural size.

Exploring the spatiotemporal patterns and non-linear influencing mechanisms of ecosystem service values: a comparison between urban and rural areas at the municipal scale

Revealing the influence mechanism of slot-die coater shim structure on the thickness uniformity and edge profile of wet composite electrodes

This study aims to elucidate the influence mechanisms of carbon nanotubes (CNTs) on asphalt binder and mixture performance through multiscale experimental characterization. Dynamic shear rheometry (DSR), multistress creep recovery (MSCR), single-edge notched beam (SENB) fracture testing, and atomic force microscopy (AFM) were employed to quantitatively correlate CNT concentrations with enhanced rheological properties and creep resistance. The recommended CNT dosage was determined based on homogeneous dispersion, performance improvement, and cost-effectiveness analysis. Subsequent evaluations focused on the high- and low-temperature stability, viscoelastic behavior, and fatigue resistance of CNT-modified asphalt mixtures at the identified recommended dosage. The results demonstrated the following: Microstructural analysis showed that CNT-induced wax crystallization and chemical interaction reorganized the colloidal structure of the asphalt. A 1.0% CNT dosage was identified as the recommended value to achieve uniform dispersion, performance gain, and cost-effectiveness. Validation tests on the mixture showed a 27% reduction in rutting depth, a 9.9% to 45.1% increase in dynamic modulus, and a 28% increase in flexural strength, confirming the cross-scale synergies from nanomodification to macroscopic performance. This research establishes a theoretical-experimental framework for designing nanoengineered asphalt materials, offering a viable solution for durable pavement infrastructure under extreme environmental and mechanical stress conditions.

Influence mechanism of cable force adjustment and boundary stiffness on the seismic response of submerged floating tunnel

Improving the crack resistance of high strength steel manufactured via wire + arc direct energy deposition by controlling the inter-pass temperature

Study on the influence mechanism of background physical fields on acoustic streaming outside an elliptical heat exchange tube

Towards to climate change spatial-temporal characteristics and influencing mechanisms of urban spatial safety resilience in China

Amidst a growing awareness of the need for liveable and sustainable cities, urban renewal strategies are increasingly concerned with community well-being. Place attachment is a key element in understanding the impact of neighbourhood regeneration, as the resulting economic and social changes may positively or negatively affect the emotional ties that bind people and places together. Though widely studied in psychology and human geography, place attachment's potential in urban planning remains underexplored, especially in urban redevelopment or preservation. To overcome this gap, this study critically reviewed 124 relevant studies using thematic analysis and bibliometric visualisations to construct a framework of influence mechanisms between urban regeneration and place attachment. The bibliometric and thematic analyses reveal five main clusters: (A) place attachment and community dynamics, (B) creative urban design and public space, (C) gentrification and social change, (D) place identity and sustainable development, and (E) community health and quality of life, each representing critical dimensions of place attachment's manifestation in urban renewal. These clusters reveal the social and physical factors shaping place attachment, showing how they reinforce or diminish it and influence the success of renewal projects. Based on this, we introduce a place attachment assessment framework to guide future urban regeneration projects and ensure that urban regeneration strategies are inclusive and socially sustainable. The study highlights the critical need to address place attachment among urban regeneration, providing theoretical and practical guidance for improved understanding and methodological support towards community-oriented urban planning. • Systematically assesses how urban renewal reshapes place attachment across multiple dimensions. • Introduces an integrated assessment framework linking urban renewal processes with place attachment dynamics. • Derives planning guidance to strengthen social structure and improve resident satisfaction in renewal areas.

Unveiling the influence mechanism of electric furnace ash on the catalytic oxidation of chlorobenzene over VW/Ti catalyst

Influence mechanisms of hard shell layer on horizontal displacement of deep soft soil under surcharge loading: experimental, theoretical and numerical studies

The article examines the transformation of the organizational and economic mechanism of state influence on the economy in conditions of war and post-war recovery. The relevance of the research is determined by the need to develop an effective system of public governance capable of ensuring the resilience of the economic system under large-scale external shocks and structural transformations. Theoretical approaches to the concept of economic resilience and adaptability of socio-economic systems are analyzed. Particular attention is paid to modern interpretations of resilience in economic science, which emphasize the ability of economic systems not only to recover from shocks but also to transform their structure and development trajectory. It is substantiated that the integration of adaptability and resilience principles provides a methodological basis for improving the mechanism of state influence in crisis conditions. The study proposes the concept of an adaptive-resilient mechanism of state influence, which is interpreted as a dynamic system of institutional, economic, social, and security instruments of public policy. The functioning of the mechanism is based on several key principles, including phase transformation, structural flexibility, resource mobility, institutional continuity, social justice, and digital governance. A structural-functional model of the adaptive-resilient mechanism of state influence is developed. The model includes four interacting functional blocks: security, economic, social, and institutional. Their interaction determines the level of economic resilience and effectiveness of public policy implementation. The study emphasizes that the dominance of particular blocks changes depending on the phase of economic development. To ensure methodological consistency, the study introduces a mathematical formalization of the integral efficiency of the mechanism of state influence. The proposed approach considers the variable weights of functional blocks depending on the phase of economic development. This allows the mechanism to adapt to changes in the external environment and ensures structural flexibility in public policy. In addition, a transformation matrix of the mechanism of state influence is developed. The matrix reflects the relationship between phases of economic development, dominant policy instruments, budget priorities, and expected outcomes of state management. The phases include mobilization, stabilization, reconstruction, and strategic development. The scientific novelty of the research lies in the conceptualization of the adaptive-resilient mechanism of state influence and the development of a dynamic structural-functional model that allows adjusting public policy priorities depending on the phase of economic development. The practical significance of the research results lies in the possibility of applying the proposed approach for improving the effectiveness of economic policy in wartime conditions and during post-war recovery.

Abstract To capture the interdependencies between logistics and supply chain networks in real-world systems, this paper develops a load redistribution-based Logistics-Supply Chain Binary-Coupled Network (LSBCN) model. Employing a dynamic load redistribution strategy, we systematically investigate the robustness of LSBCN under cascading failures. We evaluate network performance under both random failures and deliberate failures, thoroughly analyze the influence mechanisms of capacity factor ($\beta$) and capacity index ($\gamma$) on network robustness, and design three optimization strategies: parameter optimization, critical edge protection, and redundant edge addition. Furthermore, we quantitatively examine the synergistic effects and cost-effectiveness among these strategies. The results reveal that capacity factors exert significant regulatory effects on network robustness; however, the marginal improvement diminishes beyond a critical threshold. Distinct optimal capacity parameter configurations correspond to different failure proportions. Protecting critical edges of the logistics network demonstrates superior robustness enhancement under random failures, whereas adding redundant edges proves more effective under deliberate failures. The synergistic effects between strategies exhibit strong dependence on both failure modes and proportions. Under random failures, critical edge protection should be prioritized, while under deliberate failures, redundant edge addition is preferable. These findings provide theoretical foundations and decision-making references for vulnerability assessment, collaborative optimization, and risk management in logistics-supply chain systems.