Search Results (11,381)

Humidity sensing is essential in medical fields such as respiratory support, neonatal care, sterilization, and pharmaceutical storage. However, current sensors face limitations, including slow response/recovery, low sensitivity, and poor long-term stability. To address these challenges, we developed borophene-multiwalled carbon nanotube (MWCNT) heterostructures using a stepwise in situ thermal decomposition method. The resulting humidity sensor exhibits an ultrabroad detection range (11–97% RH), ultra-high sensitivity (55,000% at 97% RH), and fast response/recovery times (10.04 s/4.8 s). Through interfacial charge-transfer engineering, the system facilitates rapid electron migration, enhances Schottky barrier modulation, and provides abundant active adsorption sites for water molecules, thereby achieving comprehensive improvement in sensing performance. It also demonstrates excellent selectivity, mechanical flexibility, and operational stability. Notably, the sensor’s sensitivity at 97% RH surpasses that of sensors based on pure borophene or MWCNT by 37–462 times, highlighting the advantages of heterostructure engineering. The multifunctionality of the device suggests its potential in areas beyond conventional sensing, including non-contact voice recognition, skin humidity mapping, and real-time breath monitoring. These results lay a solid foundation for developing borophene-MWCNT heterostructures into a high-performance platform for next-generation medical diagnostics and intelligent health monitoring. Full article

To address complex connections in prefabricated concrete structures, a novel joint connecting a prefabricated concrete-filled steel tubular column and a composite beam is proposed. Pseudo-static tests on six scaled specimens and ABAQUS finite element analyses were conducted to investigate seismic mechanisms, focusing on slab effects and beam-bottom configurations. Experimental results show the joints exhibit plump hysteretic curves. The composite beams displayed distinct shear-dominated failure, while the stiffened column remained intact. With an average ductility coefficient of 2.84 and an ultimate equivalent viscous damping coefficient of 0.207, the specimens demonstrated excellent deformation and energy dissipation capabilities. The slab’s flange effect significantly enhanced negative bearing capacity, causing mechanical asymmetry. Comparatively, the steel plate beam bottom configuration offered superior stiffness and stability over the reinforcement beam bottom configuration. Sensitivity analysis revealed that bearing capacity is highly sensitive to beam parameters (e.g., longitudinal rebar strength, connector length) but less sensitive to column parameters. Notably, the bearing capacity of the beam bottom configuration using reinforcement increases significantly with concrete strength and reinforcement ratio, whereas the beam bottom configuration using a steel plate shows marked insensitivity to these factors. These findings clarify the load transfer mechanism and support the seismic design of prefabricated structures. Full article

This study investigates the critical role of resonance capture dynamics in determining the energy dissipation performance of nonlinear energy sinks (NES). A fluid inerter combining mass amplification and damping characteristics is proposed as a core component, based on which two configurations of fractional-order NES (configured in series and parallel) are systematically constructed. The applicability of the complex averaging method in fractional-order systems has been addressed through fractional calculus (such as Leibniz properties), enabling it to be analyzed like integer-order systems. Employing the multi-scale perturbation method, the energy transfer mechanism between the primary oscillator and the NES is derived, leading to the analytical determination of optimal cubic stiffness and maximum energy transfer efficiency. Comparative simulation shows that the parameters of the inerter directly affect the magnitude of critical damping. The optimal cubic stiffness design method is more reliable than traditional methods and can ensure effective target energy transfer triggering. Further analysis of dissipation time shows that the performance of fractional-order NES is superior to integer-order NES; notably, the dissipation time of series fractional-order NES is significantly shorter than that of parallel and traditional NES. In summary, this study provides theoretical guidance for the design of lightweight and high-performance NES and will also promote the application of fractional calculus theory in the field of engineering vibration reduction. Full article

Agricultural industrial parks have been promoted as a key instrument for agricultural modernization, yet causal evidence of their impact on raising rural residents’ income remains limited. This study evaluates the income effects of National Modern Agricultural Industrial Parks (NMAIPs) in China, clarifying the transmission mechanisms and distributional consequences for rural households and the urban–rural income gap. Using county- and household-level panel data (2014–2022), we exploit the staggered rollout of NMAIPs as a quasi-natural experiment and employ a staggered Difference-in-Differences (DID) design with two-way fixed effects, complemented by event-study analysis. Results show that NMAIP establishment raises rural residents’ income by approximately 1.83% on average. Mechanism analysis indicates that this gain operates primarily through employment expansion, technological upgrading, and capital agglomeration. At the household level, NMAIPs significantly increase wage and operating income but have limited effects on property and transfer income, reflecting constraints in rural asset markets. Furthermore, NMAIPs reduce intra-rural inequality and moderate the urban–rural income gap following an inverted U-shaped path (initial widening followed by narrowing), as benefits diffuse through value chains. We conclude that NMAIPs are an effective policy lever for inclusive rural growth, yet their distributive outcomes could be enhanced by supporting reforms in rural factor markets and public service delivery. Full article

As 3D printing emerges as a transformative technology in construction, the structural performance of 3D-printed mortar (3DPM) has become a key research focus. This study conducted shear tests on reinforced specimens combining 3D-printed mortar (3DPM) and normal mortar (NM). Four different shapes of interfacial locking design (I-shaped, K-shaped, C-shaped, S-shaped) were examined, comparing reinforced (CR) and non-reinforced (NR) specimens. The investigation analyzed failure modes, crack propagation patterns, and shear transfer mechanisms at CR series specimens under direct shear loading. CR-S specimens exhibited a shear peak load value 14.0% higher than CR-K specimens, 33.2% higher than CR-C specimens, and 42.9% higher than CR-I specimens. CR-I specimens exhibited pure adhesive failure. CR-K, CR-C, and CR-S specimens showed composite failure patterns combining adhesive and shear failure mechanisms. Strain analysis revealed the maximum horizontal strain ε_xx across all specimen shapes. CR-C and CR-S specimens recorded strain values exceeding CR-I and CR-K specimens by over 50%. Reinforcement produced pronounced increases in ultimate bearing capacity for I-shaped and C-shaped specimens, achieving gains of 51.9% and 60.4%, respectively. Reinforcement substantially enhanced energy dissipation capacity. Compared with NR series specimens, the performance improvements ranked as follows: CR-C (+164.67%) > CR-S (+70.70%) > CR-I (+52.05%) > CR-K (+9.42%). Full article

Based on a previously developed empirical model of global solar irradiance (EMGSI) at the Dome C station under all-sky conditions, and on good simulations of global solar radiation and its losses in the atmosphere caused by absorption and scattering components, as well as albedos at the top of the atmosphere (TOA) and the surface (TOAsur) during 2006–2016, similar estimations for the above parameters during 2018–2021 and 2006–2021 were computed by further application of this empirical model, and reliable calculations were also obtained, as in 2006–2016. The long-term variations in the above variables were thoroughly investigated during 2006–2021. For annual averages over 2006–2021, the calculated and observed global solar radiation decreased, and the absorption and scattering losses increased, well associated with increases in absorption and scattering atmospheric substances. Air temperature increased by 0.99 °C, showing regional climate warming. The mechanisms of air temperature increase were fully studied, and the basic mechanism reported previously was further confirmed. Additionally, the mechanisms of air temperature change vary with gases, liquids, and particles (GLPs) and with sites. Therefore, a proposal is recommended that, to reduce climate warming, all forms of direct emissions of GLPs and the secondary formation of new GLPs in the atmosphere produced by these directly emitted GLPs via chemical and photochemical reactions (CPRs) should be controlled. The estimated and satellite-derived albedos during 2006–2021 decreased at the TOAsur. An integrated understanding of solar radiation transfer in the atmosphere and of energy balance at the TOAsur is necessary. Full article

Gas sensors are essential in areas such as environmental monitoring, industrial safety, and healthcare, where the accurate detection of hazardous and volatile gases is crucial for ensuring safety and well-being. Metal–organic frameworks (MOFs), which are crystalline porous materials composed of metal nodes and organic linkers, have recently emerged as a versatile platform for gas sensing due to their adjustable porosity, high surface area, and diverse chemical functionality. This review provides a detailed overview of MOF-based gas sensors, beginning with the fundamental sensing mechanisms of physisorption, chemisorption, and charge transfer interactions with gas molecules. We explore design strategies, including functionalization and the use of composites, which improve sensitivity, selectivity, response speed, and durability. Particular attention is given to the influence of MOF morphology, pore size engineering, and framework flexibility on adsorption behavior. Recent developments are showcased across various applications, including the detection of volatile organic compounds (VOCs), greenhouse gases, toxic industrial chemicals, and biomedical markers. Finally, we address practical challenges such as humidity interference, scalability, and integration into portable platforms, while outlining future opportunities for real-world deployment of MOF-based sensors in environmental, industrial, and medical fields. This review highlights the potential of MOFs to transform next-generation gas sensing technology by integrating foundational material design with real-world applications. Full article

Micro- and nanoplastics (MNPs) are a new type of pollutant that are widely present in terrestrial ecosystems due to agricultural plastics, sludge use, deposition, and litter degradation. Plants can absorb them through the soil and atmosphere, with adverse effects on plant growth and development. Several studies have reported the effects of MNPs on plant physiology, biochemistry, and toxicity. However, the food chain risk of plant uptake of MNPs has not been systematically studied. This review synthesizes current research on plant MNP pollution, focusing on the uptake and transport mechanisms of MNPs by plants, influencing factors, and health hazards. The size, type, and surface charge characteristics of MNPs, as well as environmental conditions, are key factors affecting MNP absorption and accumulation in plants. Furthermore, when MNP-enriched plants are consumed by humans and animals, the accumulated MNPs can diffuse through the bloodstream to various organs, impairing physiological functions and causing a range of health problems. While a comprehensive, traceable investigation of the transmission of MNPs through the terrestrial food chain remains unconfirmed, health risk signals are unequivocal—dietary intake is the primary route of human exposure to MNPs, with direct evidence of their bioaccumulation in human tissues. Addressing this critical research gap, i.e., systematically verifying the full terrestrial food chain translocation of MNPs, is therefore pivotal for conducting robust and comprehensive assessments of the food safety and health risks posed by MNPs. This study analyzed a total of 154 literature sources, providing important theoretical insights into the absorption, transport, and accumulation of MNPs in plants, as well as the health risks associated with their transfer to humans through the food chain. It is expected to provide valuable reference for the research on the transfer of MNPs in the “soil-plant-human” chain. Full article

Ship-to-ship (STS) transfer has become a major concern for maritime security and regulatory authorities, as it is frequently exploited for smuggling and other illicit activities. Accurate and timely identification of STS events is therefore essential for effective maritime supervision. Existing monitoring approaches, however, suffer from two inherent limitations: AIS-based surveillance is vulnerable to intentional signal shutdown or manipulation, and remote-sensing-based ship detection alone lacks digital identity information and cannot assess the legitimacy of transfer activities. To address these challenges, we propose a Multi-source Observation framework with SAR and AIS (MOSA), which integrates SAR imagery with AIS data. The framework consists of two key components: STS-YOLO, a high-precision fine-grained ship detection model, in which a dynamic adaptive feature extraction (DAFE) module and a multi-attention mechanism (MAM) are introduced to enhance feature representation and robustness in complex maritime SAR scenes, and the SAR-AIS Consistency Analysis Workflow (SACA-Workflow), designed to identify suspected abnormal STS behaviors by analyzing inconsistencies between physical and digital ship identities. Experimental results on the SDFSD-v1.5 dataset demonstrate the quantitative performance gains and improved fine-grained detection performance of STS-YOLO in terms of standard detection metrics. In addition, generalization experiments conducted on large-scene SAR imagery from the waters near Panama and Singapore, in addition to multi-satellite SAR data (Capella Space and Umbra) from the Gibraltar region, validate the cross-regional and cross-sensor robustness of the proposed framework. The effectiveness of the SACA-Workflow is evaluated qualitatively through representative case studies. In all evaluated scenarios, the SACA-Workflow effectively assists in identifying suspected abnormal STS events and revealing potential AIS inconsistency indicators. Overall, MOSA provides a robust and practical solution for multi-scenario maritime monitoring and supports reliable detection of suspected abnormal STS activities. Full article

In emergency rescue operations, coordinating ground users (GUs) efficiently to handle dispersed tasks is crucial for saving lives and property. However, challenges such as task assignment and channel access hinder effective performance. The heterogeneity of GU abilities and the multiple ability requirements of tasks often lead to mismatched assignments, reducing rescue efficiency. Furthermore, channel access is complicated by the lack of channel state information (CSI) in disaster environments, which increases resource consumption if all channels are explored exhaustively. To address these challenges, this paper proposes a two-stage optimization framework that combines task assignment and channel access under unknown environments. First, a clustering-based method groups GUs according to multiple ability requirements. The task assignment problem is formulated as a transferable utility coalition formation game (CFG) with defined utility and preference relations. Second, a channel access mechanism is designed and modeled as an optimal stopping problem to optimize exploration time and select the optimal channel from the explored set. A task assignment and channel access optimization algorithm for cooperative rescue is proposed, where a multi-round matching preprocessing step supports coalition formation, and a one-stage look-ahead (1-SLA) rule balances exploration and data reception. Simulation results show that the proposed algorithm effectively satisfies task ability requirements, accelerates channel access, and improves the actual total utility. Full article

With the continuous improvement of power system intelligence, multimodal data generated during distribution network maintenance have grown exponentially. However, existing power multimodal datasets commonly suffer from issues such as low sample quality, frequent factual errors, and inconsistent instruction expressions caused by regional differences.Traditional sample correction methods mainly rely on manual screening or single-feature matching, which suffer from low efficiency and limited adaptability. This paper proposes a multimodal sample correction framework based on large-model instruction enhancement and knowledge guidance, focusing on two critical modalities: temporal data and text documentation. Multimodal sample correction refers to the task of identifying and rectifying errors, inconsistencies, or quality issues in datasets containing multiple data types (temporal sequences and text), with the objective of producing corrected samples that maintain factual accuracy, temporal consistency, and domain-specific compliance. Our proposed framework employs a three-stage processing approach: first, temporal Bidirectional Encoder Representations from Transformers (BERT) models and text BERT models are used to extract and fuse device temporal features and text features, respectively; second, a knowledge-injected assessment mechanism integrated with power knowledge graphs and DeepSeek’s long-chain-of-thought (CoT) capabilities is designed to achieve precise assessment of sample credibility; third, beam search algorithms are employed to generate high-quality corrected text, significantly improving the quality and reliability of multimodal samples in power professional scenarios. Experimental results demonstrate that our method significantly outperforms baseline models across all evaluation metrics (BLEU: 0.361, ROUGE: 0.521, METEOR: 0.443, F1-Score: 0.796), achieving improvements ranging from 21.1% to 73.0% over state-of-the-art methods: specifically, a 21.1% improvement over GECToR in BLEU, 26.5% over GECToR in ROUGE, 30.3% over Deep Edit in METEOR, and 11.8% over Deep Edit in F1-Score, with a reduction of approximately 35% in hallucination rates compared to existing approaches. These improvements provide important technical support for intelligent operation and maintenance of power systems, with implications for improving data quality management, enhancing model reliability in safety-critical applications, and enabling scalable knowledge-guided correction frameworks transferable to other industrial domains requiring high data integrity. Full article

In this study, a targeted SSR (Simple Sequence Repeat) marker resource was developed based on genes and protein families associated with pathogen- and pest-related defense–resistance mechanisms in Camellia sinensis. Forty-one genes and protein families reported to show upregulation, increased expression, or functional validation under disease and pest stress were selected, and the corresponding 195 loci were mapped onto the Camellia sinensis cv. Shuchazao genome. SSR screening within gene bodies and gene-flanking regions (±5 kb) identified 5197 SSR loci. Putative QTL hotspot regions were defined using locus-based sliding-window analysis, Z-score calculations, and permutation tests, yielding 633 SSRs filtered at the 99% and 95% significance thresholds. Proteome-wide scans based on conserved amino acid motifs identified multiple loci within the WRKY, NAC, LRR, PRX, and CHI families, and Random Forest analysis was used to prioritize SSRs within these families. Finally, 386 SSR primer sets were designed and evaluated by in silico PCR across six tea genomes. Of these, 245 primers produced amplicons in more than one genome, and 124 exhibited polymorphic information content values greater than 0.500. Overall, the developed SSR panels represent a biologically contextualized and experimentally transferable marker resource targeting defense–resistance-associated genic and gene-proximal regions. Full article

Biochar supplementation has gained a lot of interest in recent years as a strategy to improve anaerobic digestion. As a result, research on the field has expanded in diverse directions, yet a clear pathway is not being followed, which can lead to unexpected or contradictory results. This review analyzed the most recent literature (2020–2024) on this topic and identified three major research trends: (i) investigating the mechanisms behind biochar enhancement of anaerobic digestion (analysis of microbial communities, interspecies electron transfer, metabolic pathways, enzymatic activity, gene expression, extracellular polymeric substances, quorum sensing, and antibiotic resistance genes); (ii) maximizing biochar applications in anaerobic digestion through the use of novel tools (biochar engineering, modeling and optimization, and integration of anaerobic digestion and other technologies); (iii) advancing towards the large-scale implementation of biochar addition to anaerobic digestion (continuous operation, biochar effects on digestate, techno-economic analysis, and life cycle assessment). By investigating these topics, key knowledge gaps and challenges to be addressed in future research were defined and discussed. This review aims to provide a clear and insightful picture of the current state and future prospects of scientific research in this field, which may be of great relevance given the current rise in this technology. Full article

The stability of perovskite materials in humid conditions significantly hinders their practical deployment. This study employed ab initio molecular dynamics (AIMD) simulations based on the Car–Parrinello approach to elucidate the adsorption mechanisms within two systems: CH₃NH₃PbI₃-15O₂-2H₂O and CH₃NH₃PbI₃-15O₂-5H₂O. The findings indicate that in the system with a higher water content (5H₂O), the degradation of the perovskite skeleton is more severe. Additionally, the adsorption energy of oxygen molecules significantly increases, along with more pronounced charge transfer between the oxygen and the perovskite material. The study also reveals that although water molecules contribute to the damage of the perovskite skeleton, oxygen molecules are the primary culprits. These insights not only clarify the specific impacts of various components in a mixed-gas environment on perovskite stability but also provide an essential theoretical basis for future modifications and optimizations of perovskite materials. Full article

A targeted modification approach involving the synthesis of Ce/C co-doped TiO₂ aerogels (CeCTi) via a sol–gel method combined with supercritical CO₂ drying and subsequent heat treatment is employed to enhance the photocatalytic CO₂ reduction performance of cost-effective and stable TiO₂ aerogels. The results demonstrate that the CeCTi exhibits a pearl-like porous network structure, an optical band gap of 2.90 eV, and a maximum specific surface area of 188.81 m²/g. The black aerogel sample shows an enhanced light absorption capability resulting from the Ce/C co-doping, which is attributed to the formation of oxygen vacancies. Under simulated sunlight irradiation, the production rates of CH₄ and CO reach 27.06 and 97.11 μmol g⁻¹ h⁻¹ without any co-catalysts or sacrificial agents, respectively, which are 82.0 and 5.7 times higher than those of the pristine TiO₂ aerogel. DFT reveals that C-doping facilitates the formation of oxygen vacancies, which introduces defect states within the calculational band gap of TiO₂. The proposed photocatalytic mechanism involves the light-induced excitation of electrons from the valence band to the conduction band, their trapping by oxygen vacancies to prolong the charge carrier lifetime, and their subsequent transfer to adsorbed CO₂ molecules, thereby enabling efficient CO₂ reduction, which is experimentally supported by photoluminescence measurements. Full article