Search Results (1,297)

The growing popularity of biophilic design in architecture is often linked to the physical and mental well-being of building occupants. At the same time, increasing climate change requires greater emphasis on passive material strategies that support environmental regulation in buildings. In the literature, biophilic elements encompass a wide range of components, from natural materials, through plant systems, to environmental factors such as light and water. However, their classification often relies on perceptual criteria. The aim of this article was to critically analyse and evaluate the issues of materials and biophilic systems in the context of architectural adaptation to climate change. A classification based on impact mechanisms, rather than on the origin of materials or their aesthetic character, was proposed, which allows for associating material properties with measurable indoor environmental quality parameters such as temperature and humidity. The proposed framework suggests that the impact of biophilic materials and systems on users may be indirect, linked in part to the shaping of the interior microclimate and indoor environmental quality (IEQ) parameters. This perspective highlights the potential importance of environmental mechanisms as a complementary dimension of interpreting biophilia, an aspect that, in the authors’ view, has not yet been sufficiently explored in the literature. A mechanism-based approach could serve as a foundation for further assessment of the potential of biophilic materials and systems in the context of architectural adaptation to climate change. Full article

Engine noise is a predominant source of noise in the cabin of internal combustion engine vehicles and new energy hybrid vehicles. The conventional multi-channel active noise control (ANC) system, based on the adaptive notch filtered-X least mean square algorithm, is commonly employed to mitigate such multi-tonal noise. However, the computational efficiency and convergence performance of this system may be significantly hindered by the large estimated secondary path length and the frequency-dependent convergence behavior. To overcome these limitations, this paper proposes a computationally efficient and fast-converging multi-channel ANC system by incorporating a local secondary path (LSP) equalization method. The proposed method enhances the convergence speed by equalizing the magnitude responses of estimated secondary paths and reduces the computational complexity through an improved LSP modeling approach. Accordingly, a set of low-order equalized LSP models with normalized amplitude-frequency responses is generated and employed for reference filtering. A computational complexity analysis comparing the conventional system, a recent cost-effective system, and the proposed system is presented. Numerical simulations are conducted to evaluate the convergence speed and noise attenuation performance of these three systems. Additionally, real vehicle experiments are performed using a digital signal processing controller. The results demonstrate that the proposed multi-channel ANC system achieves a superior noise reduction effect. Under accelerated conditions, the average attenuation of the second-order noise component at the four error microphones is measured at 4.4 dB(A), 6.2 dB(A), 13.4 dB(A), and 10.0 dB(A). These findings confirm the practical effectiveness of the proposed multi-channel ANC system. Full article

Electric aviation and unmanned aerial vehicles (UAVs) depend on lightweight composites to preserve payload and range, yet mass reduction, recycled content, or bio-based content alone does not establish component suitability. Candidate systems must also satisfy coupled structural, thermal, fire, electrical, manufacturing, durability, repair, and circularity requirements. This structured critical narrative review evaluates thermoplastic carbon-fibre-reinforced polymer (CFRP) systems, recycled-carbon-fibre composites, natural-fibre systems, bio-based and recyclable matrices, hybrid architectures, and multifunctional composites using a component-specific framework based on source role, evidence maturity, test comparability, and failure consequence. The framework links processing and chemistry to defects, retained performance, repair and recovery, and the evidence required for defined aircraft and UAV components. Thermoplastic CFRP provides the strongest near-term pathway for secondary and semi-structural components, although weld durability, impact tolerance, fire response, and process conformity remain system specific. Recycled-carbon-fibre and natural-fibre systems are most defensible for lower-consequence covers, fairings, housings, interiors, and UAV parts when feedstock variability, moisture, porosity, and fire performance are controlled. Battery enclosures, primary structures, rotor-support members, and structural-battery systems require representative coupled-hazard and component-scale evidence. The resulting adoption pathways are bounded by component and operating conditions, with manufacturing, durability, repair, recovery, and qualification evidence specified for each application. Full article

As data centers become major and schedulable loads of the new power system, connecting them to multiple microgrids offers a promising route to absorb local renewable energy through cross-domain coordination. However, when the microgrids belong to competing operators, coordinated scheduling forces each party to disclose its data-center load curve, storage state, and pricing strategy, which constitutes a core operational secret that no microgrid is willing to reveal. This paper develops a secure and privacy-preserving distributed scheduling scheme for data-center-integrated microgrids built on blockchain. A “data-stays-local, energy-crosses-centers” model is established that elevates privacy from an add-on feature to a first-order architectural constraint, defining a “three-no” principle and a two-layer architecture in which each microgrid optimizes its interior in plaintext and exposes only encrypted matchable factors. On this basis, a decentralized ciphertext scheduling-negotiation algorithm is designed on blockchain smart contracts, performing cross-microgrid matching under secure multi-party computation entirely in the encrypted domain, committing auditable encrypted digests on-chain, and dynamically allocating scheduling priority through an on-chain reputation mechanism. Case studies on a cluster of interconnected microgrids show that the proposed scheme attains cost and renewable accommodation within about three-tenths of a percent of the centralized optimum while reducing operational data-leakage risk from 96.7 percent to 3.8 percent, at the manageable expense of a few seconds of negotiation latency. Benchmarking against an exact mixed-integer solver on small-scale systems bounds the mean optimality gap of the decomposed scheme at 0.74 percent, with a worst case of 2.54 percent over sixty instances. Full article

This paper presents a numerical method for solving transient one-dimensional heat conduction problems in multilayer slabs with temperature-dependent thermal conductivities. The governing nonlinear partial differential equations are formulated separately in each layer, allowing for distinct material properties. Perfect thermal contact at internal interfaces is enforced through continuity of temperature and heat flux, while general boundary conditions are imposed at the external boundaries, including prescribed temperature, specified heat flux, and convective exchange. A key feature of the proposed approach is to discretize the partial differential equations first in time using the implicit Euler method, thereby reducing the original problem to a sequence of nonlinear two-point boundary value problems with interface (transmission) conditions. A second-order finite difference scheme is employed for spatial discretization, and the resulting system is expressed in global form using a unified indexing strategy. The system is solved at each time step by Newton linearization, yielding a sparse Jacobian matrix that is tridiagonal in the interior and locally extended at the interfaces. Efficient banded solvers lead to O(N) cost per time step, where N is the number of spatial nodes. Numerical experiments confirm the expected accuracy, unconditional stability, and computational complexity of the method. Full article

The heterogeneous occurrence of coal-seam thickness represents a common geological characteristic in underground mining. Variations in coal thickness can directly alter the instability-failure behavior of coal–rock systems, thereby triggering various dynamic disasters. Therefore, revealing failure and disaster-inducing mechanisms of coal–rock systems dominated by coal-thickness effects is critical for deep mining engineering design as well as dynamic disaster prevention and control. To this end, uniaxial compression tests combined with acoustic emission (AE) monitoring were performed on coal–rock combinations with different coal thicknesses. The evolution laws of characteristic strengths (uniaxial compressive strength, initiation strength, and damage strength) versus coal thickness were systematically analyzed. Using full-process spatial localization of internal damage derived from absolute AE energy, an instability evolution model for coal–rock combinations was established. Furthermore, intrinsic disaster-inducing mechanisms governing coal–rock system instability under coal-thickness regulation were summarized, with corresponding engineering prevention-control suggestions put forward. The results show that: (1) UCS, initiation strength, and damage strength of specimens exhibit a nonlinear negative correlation with coal thickness. Initiation strength and damage strength account for approximately 50% and 75% of UCS, respectively; (2) Increasing coal thickness weakens the confinement effect of upper- and lower-sandstone, which shifts the dominant failure zone gradually from coal–rock interfaces to coal interiors. Meanwhile, internal energy accumulation-release processes of combinations present staged evolution characteristics; (3) Different coal thicknesses produce distinct disaster-evolution paths for coal–rock systems. Larger coal thickness corresponds to higher risks of high-energy dynamic disasters. Accordingly, a differentiated hierarchical prevention strategy of “thin protection, medium pressure relief, and thick control” was proposed. These findings provide a theoretical basis for mine engineering design and dynamic disaster prevention-control under dominant coal-thickness effects. Full article

Land use reconfiguration can substantially alter regional carbon source–sink patterns, yet integrated evidence remains limited for spatially constrained island systems where development and ecological land are closely juxtaposed. Using Hainan Island (HI) as a case, this study applied an integrated analytical framework linking land use mix, coefficient-based land use carbon emission (LUCE) accounting, spatial redistribution, spatially varying associations, interaction detection, and decoupling analysis across 18 administrative units from 2000 to 2023. Estimated LUCEs increased more than sevenfold during the study period, with emission growth concentrated mainly in coastal development areas, while the interior remained comparatively low in emissions. The spatial distribution of LUCEs gradually expanded inland, and socioeconomic development, built-up land, terrain, and their interactions exhibited heterogeneous associations with LUCEs across the island. The decoupling relationship between land mixed use and LUCEs generally improved after 2005 but remained unstable in several coastal cities. These results indicate that island-wide LUCE evolution is characterized by spatially differentiated relationships between land development and ecological land configuration rather than by a uniform regional process. By integrating land use structure, coefficient-based carbon accounting, spatial redistribution, heterogeneity in factor associations, and decoupling within a common coast–interior framework, this study provides an analytical perspective that can support comparable land use carbon assessments in islands and coastal regions experiencing concentrated development and strong ecological constraints. Full article

The growing demand for sustainable materials has renewed interest in replacing conventional petroleum-based wood adhesives with natural, environmentally friendly alternatives. This study evaluated the bonding performance of a conventional polyvinyl acetate (PVAc) adhesive and three natural adhesives—bone glue, fish glue and casein—for bonding European beech (Fagus sylvatica L.) wood of Greek origin. Bond quality was assessed according to ISO 6238:2018 by measuring shear strength and wood failure under ambient laboratory conditions (23 ± 2 °C) and after exposure to 50 °C for 15 days, simulating elevated temperatures that may occur in indoor environments. PVAc exhibited the most consistent bonding performance, whereas casein achieved shear strength comparable to that of PVAc, demonstrating its potential as a sustainable alternative for interior wood bonding. In contrast, bone glue and fish glue exhibited lower shear strength, greater variability in bond performance, and practical limitations associated with their shorter working and setting times. The percentage of wood failure generally followed the same trend as shear strength, confirming the relationship between bond quality and adhesive performance. Moderate thermal exposure did not significantly affect shear strength but resulted in lower wood failure percentages for the natural adhesives, whereas PVAc maintained, and slightly improved, its bond strength after thermal exposure. These findings demonstrate the promising performance of casein as a natural wood adhesive while highlighting the influence of moderate thermal exposure on the durability of natural adhesive systems intended for indoor applications. Full article

With the accelerated progress of computational aesthetics and digital interior design, the demand for real-time and precise detection of aesthetic objects on edge devices has become increasingly pressing in applications such as intelligent design assistance, domestic aesthetic assessment, and augmented reality-based interior staging. As a core task in digital home aesthetics governance, virtual interior furnishing, household cultural archive development, and automated aesthetic evaluation, multi-view aesthetic object detection plays an essential role. However, this task still faces substantial difficulties arising from pronounced viewpoint variation, scale inconsistency, reflective materials, intricate decorative patterns, and cluttered indoor scenes. To address these issues, this study presents GhostNetV2-YOLO, a lightweight yet robust detection framework designed for accurate localization of aesthetic objects under unconstrained multi-view acquisition settings. The task is formally defined as closed-set detection of 10 pre-selected home aesthetic decorative items, including both planar decorative pieces and three-dimensional ornamental objects, and all performance claims are bounded within the horizontal bounding box detection paradigm. The framework incorporates three complementary components tailored to the target task. First, a task-adapted GhostNetV2 backbone is employed to enable efficient multi-scale feature extraction and long-range dependency modeling, with optimization specifically oriented toward structured aesthetic objects with stable global contours under viewpoint variation. Second, an improved Attention-based Intra-scale Feature Interaction (AIFI) module is introduced, integrating compressed QKV projection, linear attention, depthwise spatial refinement, and channel gating so that reflection-induced noise and background disturbance can be effectively reduced. Third, an enhanced Distance-IoU regression loss is adopted, in which explicit edge alignment and dynamic sample weighting are incorporated to improve boundary regression accuracy for rectangular and regularly contoured aesthetic objects. These designs jointly enhance contextual representation, boundary localization, and computational efficiency. Extensive experiments on two newly constructed multi-view aesthetic object datasets (AestheticHome-12K and AestheticHome-2K) demonstrate that the proposed detector achieves 94.80 ± 0.32%/94.20 ± 0.37% mAP@0.5, 96.30 ± 0.28%/95.60 ± 0.31% precision, and 94.70 ± 0.35%/93.80 ± 0.39% recall across two datasets (reported as mean ± standard deviation of 5 independent training runs with distinct random seeds), with only 2.89 M parameters and 6.0 GFLOPs. Statistical significance is verified via paired two-tailed t-tests with Bonferroni correction (adjusted p < 0.05) for all performance comparisons against baseline models. Compared with the YOLOv11n baseline, the method improves mAP@0.5 by 1.87–2.09 percentage points and recall by 3.27–3.48 percentage points while reducing computational cost. Notably, it also achieves 79.2–80.5% mAP@0.5:0.95, outperforming the baseline by 4.7–4.9 percentage points, indicating significantly superior localization accuracy under stricter criteria. The proposed model achieves a remarkable balance between accuracy and efficiency, making it highly suitable for deployment on resource-constrained edge devices commonly used in digital design and home aesthetic monitoring systems. The results indicate that combining lightweight long-range feature extraction optimized for rigid aesthetic objects, compact attention-based feature interaction for interference suppression, and geometry-aware regression tailored for aesthetic targets provides an effective and efficient solution for robust aesthetic object detection in real-world computational aesthetics and digital interior design applications. Full article

Achieving uniform agrochemical deposition in coffee is challenging because canopy structure, terrain, and wind conditions influence spray movement and retention. This study compared an unmanned aerial spray system (UASS), backpack sprayer, and tractor-mounted sprayers across three commercial coffee farms on Hawai‘i Island. Spray coverage, droplet density, droplet size metrics, and operational efficiency were evaluated using water-sensitive cards positioned throughout the canopy and analyzed using mixed-effects models. UASS produced significantly lower spray coverage and droplet density than the ground-based application systems, whereas backpack and tractor sprayers did not differ. Deposition patterns varied with canopy position, with application method effects depending on canopy height, depth, and aspect. Volume median diameter decreased in the upper canopy and with increasing wind speed, while relative span varied modestly among methods and was greater within the canopy interior. Canopy position and wind strongly shaped agrochemical deposition across spray platforms. Although UASS required less field labor and improved accessibility in terrain-limited systems, these operational advantages were accompanied by reduced deposition relative to ground-based sprayers. These findings demonstrate that canopy position and environmental conditions strongly influence agrochemical deposition and support UASS as a complementary application platform rather than a direct replacement for conventional sprayers under the conditions evaluated. Full article

Sandwich composite floor panels are widely used in aircraft interior structures because of their lightweight and high stiffness-to-weight characteristics. However, the guided-wave response of such panels is strongly influenced by their multilayer configuration, honeycomb core, attenuation behavior, sensor-path geometry, and excitation frequency. In this study, an active guided-wave-based Structural Health Monitoring (SHM) configuration was experimentally evaluated on an aerospace-type sandwich composite floor panel using a piezoelectric (PZT) sensor network. The specimen consisted of glass fiber reinforced polyetherimide (GFR-PEI) face sheets and a phenolic-coated aramid honeycomb core. Controlled bonded patch-induced surface perturbations were sequentially applied over 25 predefined panel regions to introduce repeatable local mass-loading and damping changes. Guided-wave measurements were performed using an Acellent ScanGenie system over a frequency range of 75–600 kHz with 25 kHz increments and twelve directed actuator–receiver paths. The results showed that the measured Damage Index (DI) response depends strongly on excitation frequency, sensing path, and perturbation location. The 400–450 kHz range produced relatively higher DI values under the tested configuration, and 425 kHz yielded the highest mean DI among valid measurements. However, the valid sensing coverage at 425 kHz was only 50%; therefore, this frequency was not interpreted as the most robust overall monitoring frequency. Lower frequencies around 100–150 kHz provided full sensing coverage while maintaining relatively high DI values. Frequencies above 550 kHz showed reduced measurement reliability due to increased attenuation and poor usable signal response. Overall, the study provides a comparative sensitivity assessment of a guided-wave-based PZT network on a sandwich composite floor panel under controlled bonded patch-induced perturbations, rather than a direct validation of realistic internal sandwich-panel damage mechanisms. Full article

Fast Reroute (FRR) after link failures is essential for carrier-grade Software-Defined Networking (SDN), yet hybrid deployments remain dominated by slow legacy routing convergence. This paper presents two port-state-driven FRR mechanisms for homogeneous and hybrid SDN networks. First, Port-State-Aware Fast Reroute (PSA-FRR) uses OpenFlow port-status events to trigger proactive, rule-based protection in the data plane. Second, Port-State-Aware Neural Fast Reroute (PSAR-FRR) formulates hybrid FRR as a controller-local multi-class classification problem and predicts the backup egress port from a port-centric state representation, enabling microsecond-scale decision latency. We evaluate the methods on the Abilene wide-area network (WAN) topology using Mininet with Open vSwitch (OVS) and a Ryu controller (homogeneous case) and Graphical Network Simulator-3 (GNS3) with Cisco IOS routers (hybrid baseline). In homogeneous SDN emulation, PSA-FRR restores connectivity within 30–100 ms under the evaluated configurations. In the hybrid baseline, conventional routing protocols converge in 13.8–256.1 s (Enhanced Interior Gateway Routing Protocol (EIGRP), Intermediate System to Intermediate System (IS-IS), Open Shortest Path First (OSPF), Border Gateway Protocol (BGP), and Routing Information Protocol (RIP)), confirming that control-plane recovery cannot meet a 50 ms target. Using the collected dataset, PSAR-FRR reduces controller decision time from 6.753 $\mathsf{\mu }$s (PSA-FRR rule evaluation) to 0.214 $\mathsf{\mu }$s (deep neural network (DNN) inference), a 31.5× speedup. These results show that port-state awareness combined with learned, controller-local policies can substantially reduce the decision-to-action latency of FRR, providing a practical path toward low-latency failure recovery in SDN migration scenarios. Full article

This paper studies the interaction between status incentives and organizational design in a two-agent moral hazard framework with limited liability. A risk-neutral principal chooses between two regimes: favouritism, under which one agent receives exclusive decision rights and status recognition for successful project implementation, and fairness, under which both agents share equal decision rights and status is distributed across agents. We show that status incentives can make ex-post favouritism optimal even when the principal does not exhibit any ex-ante preferential bias toward any particular agent. Introduction of status incentives shrink the parameter region supporting interior inefficient favouritism, and eliminate it entirely whenever project returns are large enough to sustain interior contracts for both agents. We also show that, for a non-empty set of primitive parameter values, the principal’s optimal regime can be non-monotonic in status: favouritism is optimal when status valuation is sufficiently low or sufficiently high, while fairness may dominate for intermediate values. The results shed light on why selective, hierarchical recognition systems coexist with flat team-credit structures across organizations. Full article

To reduce the number of sensors in interior permanent magnet synchronous motor (IPMSM) drive systems, position-sensorless vector control can be combined with single-shunt current reconstruction using a single DC-link shunt resistor. However, applying high-frequency (HF) voltage injection to a single-shunt drive system (SDS) at zero and low speeds causes current reconstruction errors and voltage distortion, thereby degrading the rotor position estimation performance. This paper analyzes these errors and proposes carrier-based voltage vector modification methods for both pulsating voltage injection (PVI) and rotating voltage injection (RVI). Unlike conventional methods requiring multiple pulse-width modulation (PWM) periods and analog-to-digital converter samplings within one control period, the proposed methods retain a conventional carrier-based PWM structure with one control period per PWM period. The voltage vectors in the measurement and compensation intervals are separated and positioned to reflect the current variation induced by the injected HF voltage while satisfying the current reconstruction conditions. Consequently, current reconstruction errors and voltage distortion are reduced without motor parameter-based prediction. The proposed methods are validated through simulations and experiments. Full article

This research examines the behavioral shifts within a discrete-time predator–prey framework, constructed by applying the forward Euler discretization to a continuous model. The system incorporates Smith’s growth dynamics for the prey population alongside a Holling type III functional response to characterize predator behavior. Through bifurcation analysis, it is demonstrated that the interior fixed point undergoes stability loss via Neimark–Sacker and period-doubling transitions, leading to the emergence of quasiperiodic oscillations and chaos. Furthermore, the application of normal-form theory verifies the nondegeneracy of these bifurcations and establishes the direction of the resulting orbits. We use phase portraits, Lyapunov exponents, and bifurcation diagrams to confirm the model’s rich dynamics. These numerical tools demonstrate how the system moves from stable equilibria to more intricate behaviors. The application of partial rank correlation coefficients reveals the most influential parameters governing the system’s asymptotic population levels, providing a global perspective on parameter sensitivity. The Ott–Grebogi–Yorke (OGY) chaos control strategy is employed to suppress unwanted bifurcations and stabilize chaotic oscillations within the system. These results underscore the role of nonlinear interactions and discrete-time frameworks in precipitating unpredictable population fluctuations while simultaneously offering a suite of mechanisms for enhancing the stability of ecological networks. Full article