Search Results (24,648)

Rigid polyurethane foams (RPUFs) are essential polymeric materials, prized for their low density, high mechanical strength, and superior thermal insulation, making them indispensable in construction, refrigeration, and transportation. Despite these advantages, their highly porous, carbon-rich structure renders them intrinsically flammable, promoting rapid flame spread, intense heat release, and the generation of toxic smoke. Traditional strategies to reduce flammability have primarily focused on incorporating additive or reactive flame retardants into the foam matrix, which can effectively suppress combustion but often compromise mechanical integrity, suffer from migration or compatibility issues, and involve complex synthesis routes. Despite recent progress, the long-term stability, scalability, and durability of surface flame-retardant coatings for RPUFs remain underexplored, limiting their practical application in industrial environments. Recent advances have emphasized the development of surface-engineered flame-retardant coatings, including intumescent systems, inorganic–organic hybrids, bio-inspired materials, and nanostructured composites. These coatings form protective interfaces that inhibit ignition, restrict heat and mass transfer, promote char formation, and suppress smoke without altering the intrinsic properties of RPUFs. Emerging deposition methods, such as layer-by-layer assembly, spray coating, ultraviolet (UV) curing, and brush application, enable precise control over thickness, uniformity, and adhesion, enhancing durability and multifunctionality. Integrating bio-based and hybrid approaches further offers environmentally friendly and sustainable solutions. Collectively, these developments demonstrate the potential of surface-engineered coatings to achieve high-efficiency flame retardancy while preserving thermal and mechanical performance, providing a pathway for safe, multifunctional, and industrially viable RPUFs. Full article

This paper investigates the cooperative path-following control problem for multiple unmanned aerial vehicles (UAVs) under Global Navigation Satellite System (GNSS) denial conditions. To achieve equidistant distribution and uniform velocity motion within the swarm, a distributed control strategy based on Linear Matrix Inequalities (LMI) is proposed. Additionally, a novel virtual arc-length cooperation strategy is introduced, decomposing the formation maintenance problem into two subtasks: path following and velocity synchronization. This approach reduces control complexity and significantly minimizes frequent velocity cooperation issues caused by angular separation errors. To enable online estimation and compensation for model uncertainties and external disturbances, a USDE is incorporated, offering enhanced adaptability to time-varying disturbances. Simultaneously, a dynamic event-triggered mechanism (ETM) is designed to exchange neighbor information only when necessary, substantially reducing communication load. Global consistent ultimately bounded stability of the closed-loop system is rigorously proven using Lyapunov theory. Finally, validation results from the simulation platform demonstrate the proposed method’s certain feasibility and effectiveness in practical applications. Full article

Arid inland basins represent critical hotspots of intensified conflict among water resources, ecological integrity, and economic development on a global scale. The coevolution of groundwater systems and land use patterns plays a pivotal role in shaping regional sustainability trajectories. This study synthesizes multi-source data spanning 2000 to 2020 from the Wuwei Basin, located within the Shiyang River watershed in China, to elucidate the synergistic dynamics between hydrological and land use transformations. Key findings reveal: (1) Around 2010, a significant structural shift in land use occurred, transitioning from production-oriented expansion to ecologically driven priorities. This shift was characterized by a reduction in cultivated land, increased utilization of artificial surfaces, and accelerated ecological restoration efforts. These changes were jointly influenced by enhanced water governance frameworks and spatial planning policies. (2) Groundwater levels exhibit marked spatial variability. While stability is maintained in piedmont and discharge zones, persistent overdraft has led to pronounced declines in transitional and distal recharge areas. This heterogeneity is primarily governed by the interplay of hydrogeological factors—such as recharge capacity and aquifer permeability—and anthropogenic pressures, including the extent of cultivated land and intensity of groundwater extraction. Notably, these patterns cannot be explained solely by the proportion of cultivated land or total extraction volumes. (3) A positive feedback mechanism—termed the “gain-loss regime shift”—has been identified in the discharge zone, where simultaneous increases in groundwater extraction and water-level recovery are observed. However, human activities have disrupted the natural coupling between precipitation and groundwater recharge, resulting in a significant attenuation of recharge rates (exceeding 80%). These findings offer a robust scientific basis for implementing spatially differentiated water resource management strategies and optimizing land use in arid basin environments. The implications extend beyond regional contexts, contributing to broader efforts in harmonizing human–environment interactions globally. Full article

The widespread but often poorly regulated use of pesticides has triggered urgent debates on their hidden effects beyond resistance in target pests. This study investigates the morphological effects of pesticide exposure, specifically the organophosphate chlorpyrifos, using geometric morphometrics to assess fluctuating asymmetry (FA) in wing shapes of houseflies. Developmental stability (DS), the capacity of an organism to maintain an optimal phenotype under stress, serves as a key indicator of environmental and genetic stress. Flies collected from pesticide-exposed areas in rural areas in Chile (Arbolillo) exhibited significantly higher wing asymmetry than those from less exposed zones, reflecting developmental disturbances caused by chlorpyrifos. These findings emphasize the potential of FA as a biomarker for pesticide-related environmental stress. By linking pesticide exposure to measurable phenotypic disruption, this study calls for urgent integration of morphometric and genomic tools to better understand resistance mechanisms, while also promoting sustainable pest management practices. Our findings demonstrate that even a common insect like the housefly can serve as a biological sentinel, warning of broader ecological and public health risks in pesticide-dominated landscapes. Full article

Earth-rock dams are critical components of hydraulic engineering, undertaking core functions such as flood control and disaster mitigation. However, the potential occurrence of dam breach poses a severe threat to regional socioeconomic stability and ecological security. To address the limitations of traditional Bayesian network (BN) in capturing the complex nonlinear coupling and dynamic mutual interactions among risk factors, they are integrated with machine learning techniques, based on a collected dataset of earth-rock dam breach case samples, the PC structure learning algorithm was employed to preliminarily uncover risk associations. The dataset was compiled from public databases, including the U.S. Army Corps of Engineers (USACE) and Dam Safety Management Center of the Ministry of Water Resources of China, as well as engineering reports from provincial water conservancy departments in China and Europe. Expert knowledge was integrated to optimize the network topology, thereby correcting causal relationships inconsistent with engineering mechanisms. The results indicate that the established hybrid model achieved AUC, accuracy, and F1-Score values of 0.887, 0.895, and 0.899, respectively, significantly outperforming the data-driven model G1. Forward inference identified the key drivers elevating breach risk. Conversely, backward inference revealed that overtopping was the direct failure mode with the highest probability of occurrence and the greatest contribution. The integration of data-driven approaches and domain knowledge provides theoretical and technical support for the probabilistic quantification of earth-rock dam breach and risk prevention and control decision-making. Full article

To meet the requirements of integrated accelerometers for a high-precision reference voltage under wide supply voltage range, high current drive capability, and low power consumption, this paper presents a bandgap reference operational amplifier (op-amp) circuit implemented in CMOS/BiCMOS technology. The proposed design employs a folded-cascode input stage, a push–pull Class-AB output stage, an adaptive output switching mechanism, and a composite frequency compensation scheme. In addition, overcurrent protection and low-frequency noise suppression techniques are incorporated to balance low static power consumption with high load-driving capability. Simulation results show that, under the typical process corner (TT), with VDD = 3 V and T = 25 °C, the op-amp achieves an output swing of 0.2 V~2.8 V, a low-frequency gain of 102~118 dB, a PSRR of 90 dB at 60 Hz, overcurrent protection of ±25 mA, and a phase margin exceeding 48.8° with a 10 μF capacitive load. Across the entire supply voltage range, the static current remains below 150 μA, while maintaining a line regulation better than 150 μV/V and a load regulation better than 150 μV/mA. These results verify the feasibility of achieving both high drive capability and high stability under stringent power constraints, making the proposed design well-suited as a bandgap reference buffer stage for integrated accelerometers, with strong engineering practicality and potential for broad application. Full article

Glioblastoma (GB) is one of the most aggressive and treatment-resistant cancers affecting the central nervous system (CNS), predominantly in adults. Despite significant advancements in this field, GB treatment still relies primarily on conventional approaches, including surgical resection, radiotherapy, and chemotherapy, which, due to its complex pathological characteristics, resistance mechanisms, and restrictive nature of the blood–brain barrier (BBB) and blood–brain tumor barrier (BBTB), remain of limited efficacy. In this context, the development of innovative therapeutic strategies able to overcome these barriers, induce cancer cell death, and improve patient prognosis is crucial. Recently, nanoparticle platforms and focused ultrasounds seem to be promising approaches for cancer treatment. Nanoparticles enable targeting and controlled release, whilst focused ultrasounds enhance tissue permeation, increasing drug accumulation in a specific organ. However, nanoparticles can suffer from synthesis complexity, long-term biocompatibility and accumulation in the body with consequent toxicity, whereas focused ultrasounds require specialized equipment and can potentially cause thermal damage, hemorrhage, or cavitation injury. Cyclodextrins (CYDs) possess good properties and represent a versatile and safer alternative able to improve drug stability, solubility, and bioavailability, and depending on the type, dose, and administration route, can reduce local and systemic toxicity. Thus, CYDs emerge as promising novel excipients in GB treatment. Despite these advantages, CYD complexes suffer from receptor specificity, reducing their potential in precision medicine. By combining CYD complexes with polymeric or lipidic platforms, the advantages of CYD safety and drug solubilization together with their specific targeting can be obtained, thus enhancing selectivity and maximizing efficacy while minimizing recurrence and systemic toxicity. This review provides a comprehensive overview of GB pathology, conventional treatments, and emerging CYD-based strategies aimed at enhancing drug delivery and therapeutic efficacy. Full article

To address the complexity of tensile mechanical behavior in fissured rock masses, this study conducted Brazilian splitting tests and numerical simulations on yellow sandstone containing randomly distributed fissures. Based on secondary development of the ABAQUS platform, a numerical model considering the spatial distribution of mineral components was established. A random fissure network was generated using the Weibull distribution, and crack propagation was characterized by employing cohesive elements. The influence mechanisms of the fissure inclination angle (θ = 0°~90°) and fissure ratio (R = 3~15%) on Brazilian tensile strength, failure mode, and crack propagation were systematically analyzed. The research demonstrates the following: (1) Brazilian tensile strength exhibits an overall decreasing trend with an increasing fissure ratio, while the effect of the fissure inclination angle is non-monotonic: at a low fissure ratio (R = 3%), Brazilian tensile strength shows a “decrease–increase–decrease” characteristic; at a medium to high fissure ratio (R ≥ 9%), Brazilian tensile strength continuously increases with an increasing fissure inclination angle. (2) The fissure ratio dominates the deviation of the failure path (deviation intensifies when θ ≤ 67.5° and is minimal at θ = 90°). At the mesoscale, the proportion of tensile cracks increases with an increasing R, while the contribution of shear cracks significantly enhances with an increasing θ (sharply increasing after θ > 45°). (3) Crack propagation is controlled by the spatial interaction of initial cracks. Under the combined action of a high inclination angle (θ = 90°) and high fissure ratio (R = 15%), a tensile–shear composite failure pattern forms, characterized by dual-source crack initiation and central coalescence. This study provides a mesoscale mechanical basis for the stability assessment of engineering structures in fissured rock masses. Full article

Quantum-dot light-emitting diodes (QLEDs) have emerged as promising candidates for next-generation display technologies owing to their high color purity and external quantum efficiency. Despite rapid advancements in device performance, operational stability and long-term reliability remain critical challenges, particularly for cadmium-free and blue-emitting QLEDs. This review provides a comprehensive overview of the degradation mechanisms of QLEDs, emphasizing the relationship between environmental factors, such as moisture, oxygen, and thermal stress, and excitonic factors, including charge-injection imbalance, Auger recombination, and interface deterioration. We further highlight the role of nondestructive characterization techniques, including impedance spectroscopy, Fourier transform infrared spectroscopy, transient photoluminescence, transient electroluminescence, transient absorption, and electroabsorption spectroscopy, in probing real-time charge dynamics and material degradation. By integrating the insights from these operando analyses, this review offers a detailed perspective on the origins of device degradation and provides guidance for rational design strategies aimed at enhancing the operational stability and commercialization potential of QLEDs. Full article

Graphene, owing to its exceptional mechanical properties and interfacial modulation capability, is considered an ideal material for enhancing the interfacial strength and damage resistance during the fabrication of ultra-thin lithium foils. Although previous studies have demonstrated the reinforcing effects of graphene on lithium metal interfaces, most analyses have been restricted to single-temperature or idealized substrate conditions, lacking systematic investigations under practical, multi-temperature environments. Consequently, the influence of graphene coatings on lithium-ion conductivity and mechanical stability under real thermal conditions remains unclear. To address this gap, we employ LAMMPS-based molecular dynamics simulations to construct atomic-scale models of pristine lithium and graphene-coated lithium (C/Li) interfaces at three representative temperatures. Through comprehensive analyses of dislocation evolution, root-mean-square displacement, frictional response, and lithium-ion diffusion, we find that graphene coatings synergistically alleviate interfacial stress, suppress crack initiation, reduce friction, and enhance ionic conductivity, with these effects being particularly pronounced at elevated temperatures. These findings reveal the coupled mechanical and electrochemical regulation imparted by graphene, providing a theoretical basis for optimizing the structure of next-generation high-performance lithium metal anodes and laying the foundation for advanced interfacial engineering in battery technologies. Full article

This paper proposes a deep reinforcement learning-based predictive control scheme to address cushion pressure prediction and stabilization in hovercraft systems subject to modeling complexity, dynamic instability, and system delay. Notably, this work introduces a long short-term memory (LSTM) network with a temporal sliding window specifically designed for hovercraft cushion pressure forecasting. The model accurately captures the dynamic coupling between fan speed and chamber pressure while explicitly incorporating inherent control lag during airflow transmission. Furthermore, a novel adaptive behavior cloning mechanism is embedded into the twin delayed deep deterministic policy gradient with behavior cloning (TD3-BC) framework, which dynamically balances reinforcement learning (RL) objectives and historical policy constraints through an auto-adjusted weighting coefficient. This design effectively mitigates distribution shift and policy degradation in offline reinforcement learning, ensuring both training stability and performance beyond the behavior policy. By integrating the LSTM prediction model with the adaptive TD3-BC algorithm, a fully data-driven control architecture is established. Finally, simulation results demonstrate that the proposed method achieves high accuracy in cushion pressure tracking, significantly improves motion stability, and extends the operational lifespan of lift fans by reducing rotational speed fluctuations. Full article

In the realm of sustainable public transportation, the integration of intelligent electric bus propulsion systems represents a novel and promising approach to reducing environmental impact—particularly through the mitigation of NOx emissions and overall exhaust pollutants. This emerging technology underscores the growing need for advanced drive control architectures that ensure not only operational safety and reliability but also compliance with increasingly stringent emissions standards. The present article introduces an innovative analysis of energy-optimized dual-drive electric propulsion systems, with a specific focus on their potential for real-world application in emission-conscious urban mobility. A detailed dynamic model of a dual-drive electric bus was developed in MATLAB Simulink, incorporating a Fuzzy Logic-based decision-making algorithm embedded within the Transmission Control Unit (TCU). The proposed control architecture includes a torque-limiting safety strategy designed to prevent motor overspeed conditions, thereby enhancing both efficiency and mechanical integrity. Furthermore, the system architecture enables supervisory override of the Fuzzy Inference System (FIS) during critical scenarios, such as gear-shifting transitions, allowing adaptive control refinement. The study addresses the unique control and coordination challenges inherent in dual-drive systems, particularly in relation to optimizing gear selection for reduced energy consumption and emissions. Key areas of investigation include maximizing efficiency along the motor torque–speed characteristic, maintaining vehicular dynamic stability, and minimizing thermally induced performance degradation. The thermal modeling approach is grounded in integral formulations capturing major loss contributors including copper, iron, and mechanical losses while also evaluating convective heat transfer mechanisms to improve cooling effectiveness. These insights confirm that advanced thermal management is not only vital for performance optimization but also plays a central role in supporting long-term strategies for emission reduction and clean, efficient public transportation. Full article

This study explores chitosan (CS)-based materials for water purification, assessing their disinfection and contaminant degradation capabilities. A reproducible protocol was developed to fabricate homogeneous, stable CS films, validated through permeability testing and characterized using thermal (TGA), mechanical (tensile strength, elongation), and physico-chemical (FTIR-ATR, water contact angle, SEM-EDX) analyses. A catalyst was employed to complex iron ions and crosslink CS chains via acrylamide functions, stabilizing the CS structure and reducing washout in water. Disinfection tests showed that pure CS exhibited strong antimicrobial activity under varying contamination levels, attributed to direct contact and slight dissolution. Functionalized CS materials acted as catalytic surfaces, requiring hydrogen peroxide (H₂O₂) to generate reactive oxygen species (ROS). This ROS-mediated process effectively disinfected high bacteria loads and degraded phenol. Electron paramagnetic resonance (EPR) confirmed hydroxyl radicals as the primary active species when H₂O₂ was present. Under lower contamination levels, residual CS within the functionalized material contributed to direct antimicrobial effects, demonstrating a synergistic action between CS and ROS. These findings highlight CS as a reliable disinfectant and functionalized CS as a versatile material for ROS-driven antimicrobial action and contaminant degradation. The results suggest potential for scalable, sustainable water treatment applications. Future work will focus on optimizing the catalyst structure to enhance ROS production and improve contaminant removal efficiency. Full article

Distinct paradigms, such as the “enzymic latch” and “iron gate” theories, have been proposed to elucidate SOC loss or accumulation, but their relative significance and whether they are mutually exclusive in permafrost peatlands remain unclear. To address this, we evaluated their relative importance and identified the dominant factors controlling SOC stability. Therefore, we employed a space-for-time substitution approach across a permafrost gradient (continuous, discontinuous, and isolated) by systematically quantifying extracellular enzyme activities, iron (Fe) phases, and iron-bound soil organic carbon (Fe-SOC) at various depths (0–10, 10–30, and 30–50 cm) in peatlands. Our results did not support the “enzymic latch” theory, with hydrolytic enzyme activities (β-glucosidase (BG), cellobiohydrolase (CBH), and β-N-acetylglucosaminidase (NAG)) showing positive correlations with phenolics but negative correlations with phenol oxidase (PHO) activity. However, ferrous iron (Fe(II)) was significantly positively correlated with PHO activity, and ferric iron (Fe(III)) stabilized SOC through co-precipitation with it to form Fe-SOC, supporting the “iron gate” theory. Moreover, Fe-SOC decreased from the continuous to the isolated permafrost zone, and with soil depth from 0–10 cm to 30–50 cm. Partial least squares path modeling (PLS-PM) analysis indicated that Fe(III) directly and indirectly (via Fe-SOC and phenolics) affected SOC. Our study demonstrated the primacy of the “iron gate” mechanism in controlling carbon stability in the Great Hing’an Mountains permafrost peatlands, providing new insights for projecting carbon-climate feedback. Full article

Against the background of the rapid transformation of traditional economies and societies and continuous global climate change, how to ensure the long-term stability of the coastal ecological environment has become a key issue to be studied. In this paper, we take the 20 km buffer zone extending inland from the South African coastal zone as the study area. By constructing a vegetation vulnerability evaluation system, the current and future scenarios are compared in depth based on the base period (2010–2020), the near term (2030–2059), and the long term (2070–2099) with the help of GIS spatial analysis, the Moran index, and other methods. The results show that there are obvious spatial differences in vegetation vulnerability in the South African coastal zone. The extremely vulnerable areas of vegetation are mostly distributed on the west coast of South Africa, and some areas have obvious high–high aggregation patterns. The transfer of SSP1-2.6 scenarios in the near term is relatively stable, and the vegetation vulnerability level rebounds significantly in the long term; the vulnerability level of SSP2-4.5 scenarios has increased in both the near term and the long term, indicating that the risk of vegetation vulnerability has increased; while the SSP5-8.5 scenario has a significant deterioration trend in the long term, and the risk of vegetation vulnerability shifting to a high vulnerability level has increased significantly. Land use type has a significant impact on the response of vegetation vulnerability to SSP prediction. In the process of transformation from the base period to the long term, the proportion of vegetation vulnerability shifting to extremely vulnerable and severely vulnerable levels is notably high for both cultivated land and forest land—particularly under high-emission scenarios, driven by agricultural intensification for cultivated land and climate stress for forest land. This paper deeply explores the spatiotemporal evolution law and driving mechanism of vegetation vulnerability in the South African coastal zone under different shared socioeconomic pathway (SSP) scenarios, providing decision support for better development and protection of the South African coastal zone in the future. Full article