Search Results (3,246)

The accurate and timely identification of urban building footprints is critical for sustainable urban planning and disaster management. Traditional remote sensing methods for this task often face limitations in scalability, accuracy, and adaptability to complex urban morphologies. This paper addresses these challenges by developing and evaluating a novel data-centric framework that synergistically integrates Graph Neural Networks (GNNs) with zero-shot superpixel segmentation derived from the Segment Anything Model (SAM) applied to Sentinel-2 imagery. A cornerstone of our methodology is a rigorous assessment of OpenStreetMap (OSM) data, refined through temporal NDVI stability analysis to generate high-quality ground truth. We propose an optimized UrbanGraphSAGE model, enhanced with spectral data augmentation and trained using a robust loss function with label smoothing to mitigate label noise. In the complex urban landscape of Algiers, Algeria, our approach achieves a Test F1-Score of 0.7131, demonstrating highly competitive performance with standard pixel-based baselines like U-Net while offering significant topological and computational advantages. Specifically, our model operates with merely 19,585 parameters—orders of magnitude fewer than pixel-based CNNs. A rigorous Gold Standard evaluation against manually labeled imagery confirms the model’s high recall (0.8484) and reliability for automated urban monitoring. Full article

This study presents the results of research on the modification of gypsum with bio-waste to improve its thermal insulation properties and to evaluate the influence of the type and amount of the additive on the physical, mechanical, and microstructural properties of the composite. Various fractions of plant-based bio-waste were used in amounts ranging from 0.75 to 10% by weight. The thermal conductivity coefficient and thermal diffusivity were determined. Additionally, analyses of dimensional stability over time, visual appearance, and phase distribution uniformity were conducted. Mechanical tests included surface hardness measurements. In order to determine the material’s durability, water absorption and frost resistance tests were performed, and structural changes and properties after these cycles were analyzed. It was found that selecting the appropriate type and proportion of additive makes it possible to obtain composites with a favorable balance between thermal insulation, dimensional stability, and mechanical performance. The conducted research confirms the potential for effective use of bio-waste as a gypsum-modifying raw material, contributing to the development of sustainable building materials with a reduced environmental footprint and improved functional parameters. Full article

This paper formulates the “Minimum Vertex Cut with Reachable Set” (MVCRS) problem as an optimization framework to suppress botnet propagation in networked systems, and clarifies its computational complexity and algorithmic solutions. Building a firewall to minimize damage is essential for addressing botnet propagation in Internet of Things (IoT) networks. We define the basic MVCRS problem as minimizing the sum of the weight of the deployed resources and the resulting propagation scope. While we demonstrate that the constrained version of the problem is NP-complete, we show that the fundamental trade-off optimization model can be solved in polynomial time by reducing it to the maximum flow–minimum cut problem. This provides a theoretical baseline for optimal resource allocation in cybersecurity. Experimental evaluations reveal the limitations of conventional heuristics. In community-structured networks, the degree-based greedy algorithm overlooks critical bridge nodes, yielding an optimality gap of up to 72.6% above the theoretical minimum cost. Conversely, our exact algorithm consistently guarantees the optimal minimum cost (a 0% gap) with high statistical stability across diverse topologies. Furthermore, it scales efficiently to solve 100,000-node IoT networks within practical time limits, proving to be a reliable and efficient foundation for botnet suppression in complex real-world systems. Full article

This paper proposes an integrated robust–learning control framework for uncertain systems with external disturbances. An $H_{\infty }$ state-feedback controller is first synthesized to ensure closed-loop stability and a prescribed disturbance attenuation level under norm-bounded uncertainties. Building on this robust baseline, the Deep Deterministic Policy Gradient (DDPG) is used to refine the $H_{\infty }$ feedback gains online to improve tracking and transient performance while reducing the conservatism of fixed robust gains. To improve the exploration process in reinforcement learning, a tracking-error-guided mechanism is developed. It adaptively adjusts the exploration intensity by means of tracking error energy, promoting reasonable exploration under steady-state conditions while suppressing excessive exploration during large transients, thereby improving both learning efficiency and system transient performance. The simulation results verify the effectiveness of the proposed method. Full article

During coal mining, parallel voids ahead of an advancing working face often trigger intense dynamic loading and structural instability, posing significant risks to operational safety. Using the 43,201 working face of the Shiyangou Coal Mine as a case study, this research investigates the mechanisms of surrounding rock instability and proposes an integrated synergistic control strategy. Based on voussoir beam theory, a mechanical model of the roof structure—incorporating the nonlinear coupling between the gangue and immediate roof—was developed to establish the critical thresholds for the rotational instability of key blocks. Analytical results indicate that the limit breaking distance for “Key Block B” in the main roof is 24.49 m, which defines the primary zone for advanced reinforcement and hazard prevention. Furthermore, applying short-arm beam theory, this study clarifies how pre-split roof cutting disrupts the transmission of advance abutment pressure, identifying 8° as the optimal cutting angle. Building on these insights, a multi-faceted control system was implemented, combining hydraulic fracturing for pressure relief, pumpable backfill pillars, and an artificial false roof (utilizing a suspended I-beam structure 1.2 m above the floor). Field monitoring confirms that this collaborative approach effectively stabilizes the surrounding rock, ensuring the safe and continuous passage of the working face through parallel void areas. Full article

Historic buildings often exhibit high energy use intensity (EUI), while conservation constraints limit envelope retrofits, making it difficult to identify robust and actionable operational predictors. Using four in-use historic buildings in Shenyang, China, this study presents a pilot methodological demonstration with a controlled-comparability workflow consisting of two linked layers: (i) a Driver layer of intervenable operational variables and (ii) a Pathway layer of calibrated EnergyPlus heat-balance terms for physics-informed interpretation. Three importance approaches (Spearman, wrapper RFE with XGBoost, and Random Forest) are compared; rankings are fused via reciprocal rank fusion, and stability is tested using cross-period rolling validation across Top-K feature sets. After similarity screening, EUI variation is better explained by operational predictors and the corresponding simulated loss channels than by macro-scale structural heterogeneity. Infiltration-related indicators and envelope/infiltration loss components remain consistently prominent, while Spearman importance is less stable in the Pathway layer under seasonal switching and nonlinear coupling. A Top-10 subset provides a favorable accuracy–stability trade-off. The proposed Driver–Pathway mapping supports conservation-compatible prioritization hypotheses within a simulation-consistent interpretive framework; findings are associational and context dependent and should be validated through field measurements and experimental or quasi-experimental studies before prescriptive claims are made. Full article

This study presents a comprehensive life cycle assessment (LCA) of 30 variants of pitched roofs compositions, focusing on global, regional, and local environmental indicators. The aim of this study was to quantify the environmental footprint of roof structures, comparing traditional technical solutions with modern systems using bio-based materials. The results show that the integration of solid wood elements and bio-based insulations significantly increases carbon sequestration potential, with the best identified composition showing a significantly negative GWP-total. A dynamic analysis of the optimal variant over time horizons of 50, 100 and 150 years, confirming the stability of environmental benefits in the long term, is presented. In order to achieve a global character, the best composition is modified and optimized for mild, cold and warm climate zones. The work provides important background for decarbonization of the construction sector and the design of adaptive, low-emission building envelope structures. Full article

Micro air vehicles (MAVs) operating at low Reynolds numbers face aerodynamic and structural challenges that differ significantly from those encountered by conventional aircrafts. Nature provides effective solutions to these constraints, as insects, birds, and bats demonstrate highly efficient flight through integrated interactions between morphology, kinematics, and unsteady aerodynamic mechanisms. This review examines how biological flight principles can inform the design of next-generation MAVs. The study first analyzes biological flight strategies across insects, birds, and bats, with emphasis on scaling laws and physiological adaptations relevant to small-scale flight. It then reviews key unsteady aerodynamic phenomena governing low-Reynolds-number flight, including leading-edge vortex stability, wing–wake interactions, tandem-wing effects, and ground influence, as well as current modeling approaches ranging from quasi-steady methods to high-fidelity Navier–Stokes simulations. Building on these principles, the paper discusses biomimetic design strategies for MAV wings, structural–aerodynamic coupling, and actuation technologies used to replicate flapping flight. Existing MAV demonstrators inspired by biological flyers are analyzed, including concepts relevant to planetary exploration environments. Finally, the review identifies current technological limitations and research gaps in materials, actuation, aerodynamic modeling, and system integration. By synthesizing insights from biology and engineering, this work highlights key directions for the development of efficient, adaptable biomimetic MAV platforms capable of operating in complex environments. Full article

The stability of underground building foundations in fractured rock masses is a critical concern in geotechnical engineering, particularly for urban projects situated in complex geological settings. In such environments, the interaction between weak planes, groundwater seepage, and in situ stress plays a decisive role in controlling deformation and failure mechanisms. This study presents a novel weak plane–seepage–stress coupling model specifically developed to evaluate the stability of underground excavations and foundation walls under these challenging conditions. Unlike conventional approaches that often assume isotropy or consider isolated factors, the proposed model integrates multiple interacting variables—including weak plane orientation, seepage coefficient, and excavation direction—to systematically assess their combined influence on stress redistribution and failure pressure. A key innovation lies in the quantitative evaluation of the permeability-sealing coefficient, which reflects the effectiveness of waterproofing measures, and its coupling with weak plane characteristics. The results demonstrate that weak planes significantly alter the surrounding stress field, inducing directional instability. The optimal excavation orientation for minimizing instability is identified within the range of 200° to 280°. Moreover, increasing δ from 0 to 1 leads to a substantial reduction in the required supporting pressure, underscoring the critical role of effective sealing and waterproofing in enhancing foundation stability. While the current model is based on a single weak plane assumption and focuses on short-term mechanical responses, it provides a foundational framework for understanding coupled instability mechanisms. Future work will extend the model to incorporate multi-set weak planes, time-dependent degradation, and dynamic excavation processes. This research offers both theoretical insights and practical guidance for optimizing geotechnical design in fractured rock environments, contributing to more resilient and sustainable underground construction. Full article

The traditional Yikeyin dwellings in central Yunnan exhibit a distinctive spatial layout and skywell design that passively adapt to the mild plateau monsoon climate through natural ventilation. Although their courtyard-based configuration and skylight design are widely recognized for climatic adaptability, the quantitative relationship between courtyard orientation and ventilation performance remains insufficiently explored. This study integrates on-site environmental monitoring with validated Computational Fluid Dynamics (CFD) simulations to investigate how different courtyard orientations influence airflow organization and the indoor thermal environment. Based on detailed field surveys and measured data, three representative orientation schemes were established. The RNG k-ε turbulence model was adopted, and one-way coupled simulations using OpenFOAM and EnergyPlus were conducted to evaluate seasonal ventilation behavior and indoor thermal comfort. The findings reveal synergistic design principles between building orientation and courtyard spatial configuration, as well as spatial differentiation patterns contributing to thermal environment stability. Three orientation types—leeward, windward, and transitional—were identified, each demonstrating distinct advantages and limitations. The study quantitatively confirms the effectiveness of Yikeyin dwellings in utilizing natural ventilation for environmental regulation during both summer and winter seasons. These results provide scientific evidence and design support for modern buildings seeking to achieve enhanced ventilation performance and climatic adaptability. Full article

Takayasu arteritis (TAK) is a refractory chronic vasculitis of the aorta and its major branches, characterized by unsatisfactory treatment responses and high relapse rates. This review synthesizes current evidence to propose and elaborate a novel pathogenic paradigm: a self-reinforcing “metabolism–epigenetics–inflammation” feedback loop that sustains chronic vascular inflammation in TAK. We detail how immunometabolic reprogramming in immune and vascular wall cells not only meets bioenergetic demands but also generates metabolites (e.g., acetyl-CoA, lactate) that serve as substrates or cofactors for epigenetic modifications. These modifications, in turn, lock in a persistent pro-inflammatory gene expression profile. A central focus is the dissection of the ANK2–MAVS–IL-8 axis, a critical link connecting genetic susceptibility (via ANK2 variants) through mitochondrial dysfunction to sustained, IL-8-driven vascular injury. Building on this mechanistic framework, the review explores the translational potential of emerging biomarker candidates (e.g., IL-8, specific methylation marks) and proposes stratified therapeutic strategies that target distinct nodes within this interactive network, including metabolic drivers, epigenetic stabilizers, and inflammatory effectors. Ultimately, this work provides an integrated conceptual and translational roadmap for advancing precision medicine in TAK. Full article

Wind design aims to ensure the stability, safety, and durability of a structure exposed to wind forces. This comparative study using Computational Fluid Dynamics (CFD) was conducted to evaluate the effects of surrounding structures in wind building design. Two scenarios were analyzed: the first, in which the building was exposed to an open field, and the second, in which the building was surrounded by other buildings of equal or lower height. A CFD model, previously calibrated with experimental data, was used to simulate wind behavior. The results obtained showed significant differences between the two scenarios, confirming that nearby structures have a considerable impact on the distribution of wind pressures on the building. Therefore, the importance of considering surrounding buildings is highlighted. CFD could be a useful complementary tool for obtaining pressure coefficients and for detailed analyses of wind behavior, which could improve the design and safety of buildings under wind loads. Full article

To address the limited simultaneous optimization of mechanical performance and heavy-metal stabilization in waste-based alkali-activated systems, this study investigates the development and characterization of a novel composite cementitious material for potential construction applications, utilizing lead and zinc smelting slag (LZSS) and electroplating sludge (ES) as precursors. The novelty of this study lies in the co-modification of an LZSS-based alkali-activated matrix with PVA and KH792 to improve both compressive behavior and heavy-metal stabilization in ES-containing specimens. Based on single-factor optimization, the optimal matrix was obtained at 3.5% alkali content, a water-glass modulus of 1.4, and a liquid-to-solid ratio of 0.22, followed by 28 days of curing before testing. On this basis, ES and PVA-KH792 were introduced to investigate their effects on mechanical behavior, heavy-metal leaching, and immobilization mechanisms. The results showed that adding ES reduced the compressive strength of the alkali-activated matrix, whereas PVA-KH792 modification partially restored matrix integrity and improved performance. At 5% ES content, the compressive strength of the modified specimen increased by 7.66% compared with that of the unmodified ES-containing sample. More importantly, under the sulfuric acid–nitric acid leaching method, the Cr leaching concentration decreased from 20.1 mg/L to 13.7 mg/L, meeting the relevant regulatory limit (GB5085.3-2007 and EPA limit). Microstructural and spectroscopic analyses indicated that the beneficial effect of PVA-KH792 was associated with matrix densification and enhanced heavy-metal immobilization. The immobilization mechanisms were mainly attributed to Cr(VI) reduction by Fe(II), complexation/coordination with functional groups introduced by PVA-KH792, and physical encapsulation within the alkali-activated matrix. The findings provide a promising approach to waste valorization and the development of sustainable building materials, contributing to resource efficiency and reducing the environmental impact of the construction sector. Full article

This paper presents a finite-time uniformly ultimately bounded (FTUUB) cooperative control strategy based on a nonlinear disturbance observer (NDOB) for high-precision collaborative control of multi-hydraulic robotic arm systems operating under unknown disturbances and model uncertainties in confined scenarios such as coal silo cleaning. The proposed approach simplifies control design by lumping various uncertainties into a total disturbance, which is estimated and compensated in real time by the NDOB. Building upon this, a finite-time convergent sliding mode controller is developed, wherein the disturbance compensation is inherently embedded, ensuring that both position and velocity tracking errors converge to a small neighborhood of zero within a finite time. A master–slave distributed control architecture is adopted, with the agent communication topology characterized by graph theory. To mitigate the chattering inherent in traditional sliding mode control, a smooth hyperbolic tangent function is employed to construct the sliding surface. Rigorous Lyapunov stability analysis demonstrates that the closed-loop system achieves uniform ultimate boundedness within a finite time. Comprehensive simulation experiments, including a digital twin-based visualization in a virtual coal silo environment, validate the superior performance of the proposed method in terms of tracking accuracy, convergence speed, disturbance rejection, and control smoothness. Full article

Multi-agent swarm collaboration, inspired by the collective behaviors of biological swarms in nature, has wide applications in dynamic open environments. However, hybrid action spaces in multi-agent reinforcement learning (MARL) present a critical challenge: the inherent coupling between discrete and continuous actions severely undermines policy stability and convergence, especially under dynamic topologies. Existing methods fail to decouple this coupling, leading to suboptimal policies and unstable training. This paper addresses the core problem of action coupling under dynamic topologies, proposing a Parametrized Graph Convolution Reinforcement Learning (P-DGN) method. Operating within the actor–critic framework, P-DGN decouples the optimization pathways for hybrid actions, with a biomimetic observation design inspired by starling flock behaviors: each agent only observes the states of its seven nearest neighbors to achieve efficient local interaction and global collaboration. Its actor network uses multi-head attention to build dynamic relation kernels, develops temporal relation regularization (TRR) to improve policy consistency across time steps, and generates continuous actions with a Gaussian policy. Meanwhile, P-DGN’s critic network, based on deep Q-network (DQN), evaluates Q-values for discrete actions to guide optimal choices. We evaluate P-DGN in two different multi-agent cooperative environments. Experimental results show that compared with parametrized deep Q-network (P-DQN) and DQN baseline, the proposed method has faster convergence speed and stronger training stability. Moreover, with dense rewards, P-DGN agents learn emergent tactics like encirclement. Overall, P-DGN offers a new approach for optimizing hybrid action spaces in multi-agent systems within open, dynamic environments, balancing theoretical generality with practical utility, and its biomimetic design provides a biologically plausible framework for multi-agent swarm collaboration. Full article